• TABLE OF CONTENTS
HIDE
 Front Cover
 Title Page
 Copyright
 Introduction
 Acknowledgement
 Table of Contents
 Agronomy
 Breeding
 Protection
 Economics






Group Title: Proceedings of the ... Regional Wheat Workshop for Eastern, Central, and Southern Africa
Title: Proceedings of the 12th Regional Wheat Workshop for Eastern, Central, and Southern Africa
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 Material Information
Title: Proceedings of the 12th Regional Wheat Workshop for Eastern, Central, and Southern Africa
Series Title: Proceedings of the ... Regional Wheat Workshop for Eastern, Central, and Southern Africa
Physical Description: Serial
Language: English
Creator: International Maize and Wheat Improvement Center (CIMMYT)
Publisher: International Maize and Wheat Improvement Center (CIMMYT) ; Kenya Agricultural Research Institute (KARI)
Publication Date: 2004
 Subjects
Subject: Africa   ( lcsh )
Farming   ( lcsh )
Agriculture   ( lcsh )
Farm life   ( lcsh )
Spatial Coverage: Africa
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Funding: Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
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Bibliographic ID: UF00077529
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
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Table of Contents
    Front Cover
        Front cover
    Title Page
        Page i
    Copyright
        Page ii
    Introduction
        Page iii
    Acknowledgement
        Page iv
    Table of Contents
        Page v
        Page vi
    Agronomy
        Page 1
        Effects of nitrogen fertilizer levels and varieties on gluten content and some rheological characteristics od durum wheat flour
            Page 2
            Page 3
            Page 4
            Page 5
            Page 6
            Page 7
            Page 8
        Impact of irrigation frequency and farmyard manure on wheat productivity on a saline-sodic soil on Dongoia, Sudan
            Page 9
            Page 10
            Page 11
            Page 12
            Page 13
            Page 14
            Page 15
            Page 16
            Page 17
            Page 18
            Page 19
            Page 20
            Page 21
            Page 22
            Page 23
            Page 24
            Page 25
            Page 26
            Page 27
            Page 28
            Page 29
            Page 30
            Page 31
            Page 32
            Page 33
            Page 34
        Agronomic and economic evaluation of break crops and management practices on grain yield of wheat at Shambo, Western Oromiya, Ethiopia
            Page 35
            Page 36
            Page 37
            Page 38
            Page 39
            Page 40
        Response of bread wheat to nitrogen and phosphorus fertilizers at different agroecologies of Northwestern Ethiopia
            Page 41
            Page 42
            Page 43
            Page 44
            Page 45
        Grain yield, water use and water use efficiency as affected by moisture level under rain-out shelter
            Page 46
            Page 47
            Page 48
            Page 49
            Page 50
            Page 51
            Page 52
            Page 53
    Breeding
        Page 54
        Current status of stem rust in wheat production in Kenya
            Page 55
            Page 56
            Page 57
            Page 58
            Page 59
            Page 60
            Page 61
            Page 62
        Genotype-by-nutrient interaction in wheat grown in marginal environment in Kenya
            Page 63
            Page 64
            Page 65
            Page 66
        Improving wheat productivity for the drought prone areas of Kenya using the doubled haploid technique
            Page 67
            Page 68
            Page 69
            Page 70
            Page 71
            Page 72
            Page 73
            Page 74
            Page 75
        Grain yield stability of bread wheat genotypes in favorable and stressed environments
            Page 76
            Page 77
            Page 78
            Page 79
            Page 80
            Page 81
            Page 82
            Page 83
            Page 84
            Page 85
        Seedling and adult plant resistance in Ethiopian wheat varieties to local Puccinia graminis isolates
            Page 86
            Page 87
            Page 88
            Page 89
        Evaluation of Kenyan wheat (Triticum aestivum L.) lines for bread making quality
            Page 90
            Page 91
            Page 92
            Page 93
            Page 94
            Page 95
            Page 96
            Page 97
            Page 98
            Page 99
            Page 100
            Page 101
            Page 102
            Page 103
            Page 104
            Page 105
            Page 106
            Page 107
            Page 108
        Allelism of resistance genes to Phaeosphaeria nodorum in wheat
            Page 109
            Page 110
            Page 111
            Page 112
            Page 113
            Page 114
            Page 115
            Page 116
        Evaluation of Kenyan breadwheat (Triticum aetivum L.) varieties for resistance to Russian wheat aphid in multi-location trials
            Page 117
            Page 118
            Page 119
            Page 120
            Page 121
            Page 122
            Page 123
            Page 124
        On-farm evaluation and comparison of new and old wheat varieties
            Page 125
            Page 126
            Page 127
            Page 128
            Page 129
            Page 130
            Page 131
            Page 132
            Page 133
        Evaluation of improved wheat varieties under different management practices in Eastern Wallagga Highlands
            Page 134
            Page 135
            Page 136
            Page 137
            Page 138
            Page 139
        Cell membrane stability (CMS) as screening technique for drought tolerance in bread and durum wheat genotypes
            Page 140
            Page 141
            Page 142
            Page 143
            Page 144
        Physiological races and virulence diversity of Puccina graminis f. sp. tritici on wheat in Ethiopia
            Page 145
            Page 146
            Page 147
            Page 148
            Page 149
            Page 150
        Participatory evaluation of bread wheat varieties in the Central Highlands of Ethiopia
            Page 151
            Page 152
            Page 153
            Page 154
            Page 155
            Page 156
            Page 157
            Page 158
            Page 159
    Protection
        Page 160
        Survey of natural enemies of the Russian wheat aphis, Diuraphis noxia (Kurdijimov) in Kenya
            Page 161
            Page 162
            Page 163
            Page 164
            Page 165
        Evaluatuion of the herbicide monitor, alone and in tank mixes for weed control on wheat (Triticum aestivum L.)
            Page 166
            Page 167
            Page 168
            Page 169
            Page 170
            Page 171
            Page 172
            Page 173
            Page 174
        Control of the Russian wheat aphid, Diuraphis Noxia (Kurdijumov) in wheat using systemic insecticides in Kenya
            Page 175
            Page 176
            Page 177
            Page 178
            Page 179
    Economics
        Page 180
        Page 181
        Analysis of marketing and pricing policies on technology, input use and production of wheat in the Sudan
            Page 182
            Page 183
            Page 184
            Page 185
            Page 186
            Page 187
            Page 188
            Page 189
            Page 190
            Page 191
            Page 192
            Page 193
            Page 194
        Opening speech
            Page 195
            Page 196
        Closing speech
            Page 197
            Page 198
        Question and answer sessions
            Page 199
            Page 200
            Page 201
            Page 202
            Page 203
            Page 204
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Full Text





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.. ... .... .................... ...











Proceedings
of the
12th Regional Wheat Workshop for
Eastern, Central and Southern Africa

Nakuru, Kenya, 22-26 November 2004


BE ER 1 Bav-er 0-oplcience


MONSANTO
im ine,


CIMMYT


1











CIMMYT (http://www.cimmyt.org/) is an internationally funded, not-for-profit organization that conducts
research and training related to maize and wheat throughout the developing world. Drawing on strong science and
effective partnerships, CIMMYT works to create, share, and use knowledge and technology to increase food
security, improve the productivity and profitability of farming systems, and sustain natural resources. Financial
support for CIMMYT's work comes from many sources, including the members of the Consultative Group
on International Agricultural Research (CGIAR) (http://www.cgiar.org/), national governments, foundations,
development banks, and other public and private agencies.

The Kenya Agricultural Research Institute (KARI) i,111i' ..!iii .]/) was established in 1979 with the
express mission of increasing sustainable agricultural production by generating appropriate technologies through
research, and disseminating these to the farming community. Inherent to this mission is the protection,
conservation, and improvement of the basic resources, both natural and human. Such resources are critical for
Kenya's agricultural development and expansion of the nation's scientific and technological capacity. KARI has
an extensive history of productive collaborators with national and international institutes and universities, as well
as with the private sector.


KARI/CIMMYT 2006. All rights reserved. The designations employed in the presentation of materials in this
publication do not imply the expression of any opinion whatsoever on the part of KARI, CIMMYT or their
contributory organizations concerning the legal status of any country, territory, city, or area, or of its authorities, or
concerning the delimitation of its frontiers or boundaries. KARI and CIMMYT encourage fair use of this material.
Proper citation is requested.

Correct citation: M.G. Kinyua, J. Kamwaga, J.O. Owuoche, A. C.Ndiema, P.N. Njau, D. K. Friesen, D. Ouya
(Editors) 2006. Proceedings of the 12th Regional Wheat Workshop for Eastern, Central, and Southern Africa.
Nakuru, Kenya, 22-26 November 2004. Mexico, D.F.; CIMMYT and KARI


ISBN: 970-648-135-4

AGROVOC Descriptors Triticum durum; Triticum aestivum; Varieties; Plant breeding; Breeding methods;
Plant production; Production increase; Plant diseases; Food production; Food security;
Production factors; Economic policies; Pests of plants; Pest resistance; Yield increases;
Kenya; Ethiopia; Tanzania; Sudan; Africa

Additional Keywords CIMMYT; KARI

AGRIS Category Codes F30 Plant Genetics and Breeding

E14 Development Economics and Policies

H20 Plant Diseases


Dewey Decimal Classification


633.116









Introduction


Like its predecessors, the 12th Regional Wheat Workshop for Eastern, Central and
Southern Africa, held at Merica Hotel in Nakuru, Kenya, 22-26 November 2004
provided a forum where wheat scientists from the region could come together to
exchange their results, views, and ideas on the way forward in securing this important
food crop.

Ethiopia has an annual production of 1,600,000 metric tons, of both bread and durum
wheats, produced mainly on small scale farms. A large gap exists between wheat
production and demand in Ethiopia, and the country relies heavily on imports of
nearly 800,000 metric tons each year. Kenya's domestic bread wheat requirement,
which currently stands at 720,000 tons p.a., is projected to reach 1 million tons by
2010. Like Ethiopia, Kenya produces less wheat than she needs, importing some
400,000 tons each year. Clearly therefore, increased wheat production in the region-
through approaches such as breeding, agronomy, crop protection and improved
economic policies, is not just desirable, but essential for the food security of millions
of people.

This proceedings presents valuable new information from research conducted in
Kenya (11 articles), Ethiopia (9), The Sudan (2), and Tanzania (1), and is organized
into four sections, namely Agronomy, Breeding, Protection, And Economics.

The Agronomy section contains 6 papers, ranging in subject mater from water and
fertilizer use efficiency in wheat varieties, to a comparison of field pea and barley as
break crops in wheat farming. Breeding is the largest section, with 14 articles,
including results from a three-year survey of the wheat stem rust situation in Kenya.
The Protection section, with 3 articles, reports on the chemical management of weeds,
and the Russian wheat aphid Diuraphis noxia-a new and damaging pest in the
region. Results from a survey of the natural enemies ofD. noxia are also presented, as
the starting point for designing a biological control strategy for the aphid. In his
economics article, Professor Abbas Elsir M. Elamin deals with the financial and
economic profitability of wheat production in The Sudan, and its international
competitiveness. The comprehensive analysis discusses government reform policies
in the 1990s, and their role in wheat production, consumption and input use from that
time to the present.

We believe that this volume represents an important contribution to the regional and
global knowledge bases on wheat production and economics, and that a better
understanding of the subject matter will contribute to the ultimate goal of improved
livelihoods for the people of Africa.


Romano Kiome, PhD
Permanent Secretary, Ministry ofAgriculture









Acknowledgments


The Workshop organizers would like to acknowledge the contributions of several
institutions and individuals towards the success of the workshop, and the publication
of this proceedings.

We thank Monsanto, Bayer Crop science, and Osho chemicals, for funding the
workshop; KARI and CIMMYT for technical and administrative support; and all the
workshop participants, for their cooperation during all stages, starting with the
preparation and presentation of the papers, to their review/revision for publication.

CIMMYT reviewers Karim Ammar, Hans-Joachim Braun, Jose Crossa, Hugo De
Groote, Etienne Duveiller, Augustine Langyintuo, Ivan Monasterio, Wilfred Mwangi,
Tom Payne, Javier Pena, Matthew Reynolds, Ken Sayre, Ravi Singh, Richard
Trethowan, and Pat Wall, provided thorough and constructive comments on the
manuscripts, including suggestions for improvement. This was a valuable contribution
towards seeing the proceedings to completion, for which we are very grateful.


Dr. Miriam Kinyua
Chair, Organizing Committee










Contents


Part 1. AGRONOMY

Effect of Nitrogen Fertilizer Levels and Varieties on Gluten Content and Some Rheological
Characteristics of Durum Wheat Flour
Bemnet Gashawbeza, Solomon Assefa, Ameha Yaekob, Alemayehu Zemede, Jemanesh
Kifetew and Bekele M ekuria ......................................................................................... 2

Impact of Irrigation Frequency and Farmyard Manure on Wheat Productivity on a Saline-
Sodic Soil in Dongola, Sudan
Elmoiez M. Fadul and Mukhtar A. Mustafa .............................................. ............... 9

Consumptive Use of Water and Water Use Efficiency by Wheat (Triticum aestivum) in
Relation to Irrigation and Nitrogen
Antony M. Kibe, Subedar Singh, and Naveen Kalra ............................................... 21

Agronomic and Economic Evaluation of Break Crops and Management Practices on Grain
Yield of Wheat at Shambo, Western Oromiya, Ethiopia
Tolera Abera and Mathewos Belissa......................................... ............................ 35

Response of Bread Wheat to Nitrogen and Phosphorous Fertilizers at Different Agro-
ecologies of Northwestern Ethiopia
Minale Liben, Alemayehu Assefa, Tilahun Tadesse and Abreham Mariye................ 41

Grain Yield, Water Use and Water Use Efficiency as Affected by Moisture Level Under
Rain-Out Shelter
P. A. Ooro M.G.Kinyua, and J.B.O. Ogola.............................................................. 46

Part 2. BREEDING

Current Status of Stem Rust in Wheat Production in Kenya
R. Wanyera, M.G Kinyua, P. Njau, J. W. Kamundia and S.Kilonzo........................... 55

Genotype-by-Nutrient Interaction in Wheat Grown in a Marginal Environment in Kenya
J. Kamwaga, H. Okwaro, P. Njau, P. Kimurto, P. Ndungu. andE. Kimani................... 63

Improving Wheat Productivity for the Drought Prone Areas of Kenya Using the Doubled
Haploid Technique
Njau P. N, Kimurto, P.K, Kinyua M. G, Okwaro H. K and Ogolla J.B.0 ................... 67

Grain Yield Stability of Bread Wheat Genotypes in Favorable and Stressed Environments
Desalegn Debelo, Solomon Gelalcha, Balcha Yaie, Bedada Girma, Berhanu Mamo, and
D ebebe M asresha......................................................................................................... 76

Seedling and Adult Plant Resistance in Ethiopian Wheat Varieties to Local Puccinia graminis
Isolates
Emebet Fekadu, Belayneh Admassu and Zerihun Kassaye...................................... 86

Evaluation of Kenyan Wheat (Triticum aestivum L.) Lines for Bread Making Quality
Kimani E.N., J. Ndung'u, M.G. Kinyua and J. Owuoche................................................ 90










Physiological Traits Associated with Drought Tolerance in Bread Wheat (Triticum Aestivum
L.) under Tropical Conditions
Kimurto, P.K., M.G. Kinyua, J.B.O. Ogola, J.M. Macharia, andP.N. Njau ............... 96

Allelism of Resistance Genes to Phaeosphaeria nodorum in Wheat
C. A. Kuwite and G. R. H ughes...................................................................................... 109

Evaluation of Kenyan Breadwheat (Triticum aetivum L.) Varieties for Resistance to Russian
Wheat Aphid in Multi-location Trials
J. Maling'a, M. G. Kinyua, A. Kamau, J. K. Wanjama ,P. Njau, and
J. K am undia .................................................................................................................... 117

On-Farm Evaluation and Comparison of New and Old Wheat Varieties
R. V Ndondi, C.A. Kuwite andR.Shekibula .............................................................. 125

Evaluation of Improved Wheat Varieties Under Different Management Practices in Eastern
Wallagga Highlands
Tolera Abera, Daba Feyisa, Girma W. Tsadik, Hasan Yusuf and Gemechu Keneni 134

Cell Membrane Stability (CMS) as Screening Technique for Drought Tolerance in Bread and
Durum Wheat Genotypes
Alemayehu Zemede, H. Martens, and M.T. Labuschagne ......................................... 140

Physiological Races and Virulence Diversity ofPuccinia graminis f sp. tritici on Wheat in
Ethiopia
Belayneh Admassu, Emebet Fekadu and Zerihun Kassaye........................................ 145

Participatory Evaluation of Bread Wheat Varieties in the Central Highlands of Ethiopia
Kassa Getu, Kassahun Zewdie, Yeshimebet Gebrehiwot andAddisu Alemayehu......... 151

Part 3. PROTECTION

Survey of Natural Enemies of the Russian Wheat Aphid, Diuraphis Noxia (Kurdijimov) in
Kenya
M.Macharia, M. Njuguna, and L Koros ....................................................................... 161

Evaluation of the Herbicide Monitor, Alone and in Tank-Mixes for Weed Control in Wheat
(Triticum aestivum L.)
D.O.K. Amadi, J.N. Kamwaga and G.O. Mbanda........................................................ 166

Control of the Russian Wheat Aphid, Diuraphis Noxia (Kurdijumov) in Wheat Using
Systemic Insecticides in Kenya
M. Macharia, M. Njuguna and I. Koros ....................................................................... 175

Part 4. ECONOMICS

Analysis of Marketing and Pricing Policies on Technology, Input Use and Production of
Wheat in the Sudan
A bbas Elsir M Elam in..................................................................................................... 181

Appendixes
Op ening Sp eech.................... ............................................................. .................. ....... 195
C losing Sp eech ........................................................................ .... .... .............. ........197
Question and Answer Sessions........................ ........................................................ .... 199
P participants E -m ail A ddresses.............................................................................................. 231









Part 1. AGRONOMY


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Effect of Nitrogen Fertilizer Levels and
Varieties on Gluten Content and Some
Rheological Characteristics of Durum Wheat
Flour

Bemnet Gashawbeza', Solomon Assefa', Ameha Yaekob', Alemayehu Zemedel,
Jemanesh Kifetewland Bekele Mekuria2

Ethiopian Agricultural Research Organization, Debre ZeitAgricultural Research Center, P.O.Box
32, Debre Zeit, Ethiopia;
2Kality Food Share Company, P.O.Box 1819, AddisAbaba, Ethiopia


Abstract-Improved gluten and theological characteristics of durum wheat
(Triticum durum Desf) have recently received increased attention due to their positive
effect on the quality of pasta products. An experiment was conducted at Debre Zeit
and Akaki in the Central Highlands of Ethiopia, during the 2000/01 cropping season,
to study the influence of nitrogen fertilization levels (0, 30, 60, 90 and 120 KgNha-1)
on gluten content and some theological characteristics (dough resistance, expansion
and extensibility) of five durum wheat varieties at Akaki and Debre Zeit. At Debre
Zeit, gluten content significantly varied (P<0.05) depending on wheat genotype
(variety) and nitrogen fertilizer levels, but at Akaki only varietal differences were
significant. Nitrogen level increment consistently increased wet gluten content of
varieties at Debre Ziet and; the highest nitrogen level, 120 Kgha-', gave significantly
higher wet gluten percent 29.5 % than all other treatment levels, except 90 Kgha-'
(27.3%). Tob 66 (30.8%) had the highest wet gluten content followed by Foka
(27.5%). At Akaki, Tob 66 was the highest (24.9%), followed by Boohai (22.4%).
The studied theological characteristics at Debre Zeit showed that nitrogen fertilizer
application had no effect on either of the traits (dough resistance and extensibility),
but varietal differences were observed in dough resistance. Therefore, durum wheat
quality improvement should concentrate both on selection of appropriate varieties
and management practices such as nitrogen fertilizer application. Further study on
input-responsive semi dwarf varieties is recommended.

Introduction
Durum wheat is used for pasta production because of its hard grain texture, amber color, and
other grain quality traits related to endosperm protein. Increasing grain protein concentration
and improving other grain quality traits have been the major objectives in most varietal
development processes (Metho, Hammes and Beer, 1997). This is because the processing
quality of wheat is largely dependent on the amount and quality of endosperm protein. Grain
protein content affects milling and other industrial qualities of wheat. As a result, premiums
are commonly paid for protein levels above base line (Woolfolk et al., 2002).
Gluten is an important endosperm protein that affects pasta quality. It is a visco-elastic
component of wheat dough responsible for physical dough properties (C'uric et al., 2001).
Due to its strong relation with greater cooked firmness and increased tolerance to
overcooking, strong gluten varieties are preferred (Josephides et al., 1987). Besides gluten
content, theological characteristics that measure gluten quality are also important criteria of


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










selection for quality durum wheat. D'Egidio et al. (1990) have shown that Alveogrphic
parameters are excellent indicator of durum wheat gluten properties.
Quality durum wheat grain used for production of pasta is achieved by selection of
appropriate variety, environment and management practices (Rharrabti et al., 2001). Under
high rainfall and low soil fertility conditions grain protein production is limited (Simmonds,
1989). The effect of environment and management methods, especially availability of
nitrogen in the soil during ripening, on vitreousness of durum wheat has been reported
(Mosconi and Bozzini, 1973; Ottman et al., 2000). Numerous authors have obtained
improved grain protein upon intensive nitrogen fertilization (Geleto et al., 1996;
Gashawbebeza et al., 2002; Virga et al., 2003). The work of Hadjichristodoulou (1979)
showed significant effects of nitrogen fertilization, genotype and location on vitreousness, a
physical grain quality correlated with protein content, of durum wheat. Dexter et al. (1982)
also found significant difference between varieties for several quality traits at different
nitrogen fertilizer levels.
Durum wheat is a traditional crop for the Ethiopian farmers. Its production however has
been limited to locally made foods. The current increasing of food processing industries and
importance of pasta products by the urban people of the country has increased the importance
of quality durum wheat production.
The objective of this experiment was, therefore, to evaluate the effect of nitrogen
fertilizer and varieties on gluten content and some theological properties of durum wheat
flour.

Materials and Methods
A field experiment was conducted during the 2000/01 cropping season under rain-fed
conditions at two locations in the Central Highlands of Ethiopia (Debre Zeit and Akaki).
Debre Zeit (8 44 N, 39 o 02'E) is mid-highland (1900 m.a.s.l.) characterized by moderate
rainfall (85 1mm average annual rainfall); 17.9C average mean temperature and Pellic
Vertisol soil; and Akaki (8 052'N, 38 047'E) mid altitude area (2100masl) characterized by
average annual rainfall of 1086mm and 15.6C average mean temperature. Five medium tall
to tall durum wheat varieties viz (Kilinto, Tob66, Foka, Assasa and Boohai) that were
selected for their industrial quality by the local pasta industries were planted at five different
nitrogen levels (0, 30, 60, 90 and 120 kgha' N) with uniform basal application of 10kgha1
phosphorus in the form of Triple Super Phosphate (TSP). The experiment was laid out in
Randomized Complete Block (RCB) in factorial arrangement with three replications. The plot
size was 3m x 4m (12m2) and data was recorded from 10.4m2. Seeding rate was 150 kgha1.
Nitrogen was split applied half at planting and the remaining half at full tillering. Wet gluten
content was determined from flour and was determined by gluten wash method (ICC standard
No. 106/2) while theological characteristics viz. extensibility (L in mm) and dough resistance
(P=height X 1.1 in mm) were measured using Chopin Alveograph (ICC No.121) (ICC, 2000).
Rheological data was taken for Debre Zeit only. Data was analyzed by ANOVA using
MSTATC.

Results
Wet gluten. ANOVA showed that wet gluen content significantly varied depending on
varieties, locations and; location X nitrogen level interaction was significant (P<0.05) but no
marked difference between the nitrogen levels in the combined analysis. However, the
difference between varieties and fertilizer levels were significant (P<0.05) at Debre Zeit. At
Debre Zeit, the highest nitrogen level (120 Kgha1) had significantly higher wet gluten percent


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










than all other treatment levels except 90 Kgha'. At Akaki, on the other hand, only varietal
differences were significant (Table 1).
Varietal differences were evident at both locations. In the combined analysis Tob 66
gave the highest wet gluten content (27.9%) while the lowest was Kilinto (21.18%). The
response to applied nitrogen was higher at Debre Zeit and Tob 66 also gave the highest wet
gluten percent (30.8) while the least was Kilinto (22.55%). But no significant difference was
observed between Boohai, Foka and Assassa.
Dough resistance. Varietal difference was significant for Dough resistance. But no
marked difference between nitrogen levels was observed. Boohai (113.9) gave the highest
dough resistance followed by Foka (101.5) while the least was Assassa.
Dough extensibility. This trait was not affected by the applied nitrogen fertilizer levels
(Table 2). Besides, there was no statistically significant difference between varieties.

Table 1. Nitrogen fertilizer level effects on wet gluten (%) of durum wheat varieties at two
locations (2000/01)
Wet gluten

Treatment
Debre Akaki Mean
Zeit
Nitrogen (Kg ha1) 0 24.4c 22.2 23.3
30 26.5bc 21.8 24.2
60 26.5bc 22.8 24.6
90 27.3ab 21.29 24.3
120 29.5a 20.95 25.2
LSD (0.05) 2.543 NS NS
CV (%) 12.91 15.57 14.1
Variety Boohai 27.02b 22.4ab 24.73b
Foka 27.5b 20.65b 24.1 lb
Kilinto 22.5c 19.8b 21.18c
Tob 66 30.8a 24.93a 27.9a
Assassa 26.2b 21.29b 21.29b
Means within a column with similar letters are not significantly different at P<0.05 by DMRT. NS =
no statistically significant difference

Table 2. Effect of nitrogen levels on theological characteristics of durum wheat flour at Debre
Zeit (2000/01)
Treatment Dough resistance Expansion Extensibility P/L
(P) (G) (L)
Nitrogen 0 95.6 19.35 78.8 1.1
30 97.8 18.09 68.6 1.4
60 93.7 19.1 76.9 1.2
90 88.8 18.5 73.4 1.2
120 101.7 19.27 70.1 1.4

Variety Boohai 113.9a 20.3 78.8 1.4
Foka 101.5ab 18.7 73.3 1.4
Kilinto 92.5bc 18.8 74.6 1.2
Tob66 91.8bc 18.0 68.7 1.3
Assassa 78.1c 18.6 72.1 1.1
LSD(0.05) 15.8 NS NS
CV(%) 22.59 11.6 18.64
Means within a column with similar letters are not significantly different at P<0.05
by DMRT. NS = no statistically significant difference


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Generally, nitrogen level increment increased wet gluten contents of durum wheat varieties at
Debre Zeit but not on theological characteristics (dough resistance and extensibility). The
response of gluten contents was linear with the respective applications of 0, 30, 60, 90, and
120 kgha-1. In similar studies, the positive effect of nitrogen increment on grain protein
(Prima et al., 1982 and Geleto et al., 1996) and also on gluten content of wheat (Prima et al.,
1982 and Varga et al., 2003) was reported.
At Akaki, on the other hand, the response to the applied nitrogen was not consistent. The
work of Campbell et al. (1993) also showed significant contribution of environmental factors
on grain nitrogen content of wheat in addition to nitrogen application. As in most grain
quality traits in wheat, protein content is known to be affected by genetic and environment
mainly location, fertilizer application and other management practices. The effect of nitrogen
fertilizer on whole meal protein content of durum wheat was reported (Gashawbeza et al.,
2002). Thus this difference could be ascribed to the difference between the two locations in
air temperature and degree of water-logging. Akaki is more waterlogged than Debre Zeit and
could have inhibited efficient utilization of the applied nitrogen (Gashawbeza et al., 2002).
According to Spiertz and Devos (1983), under high temperature especially during grain filling
period protein synthesis is favored. Therefore, the environment at Debre Zeit could favor
protein synthesis due to its relatively higher mean temperature and less water-logging stress.
Besides, no correlation between gluten content and grain yield at Debre Zeit (r=0.15)
suggesting improving gluten content couldn't risk grain yield. From the result of the study, for
high rainfall and waterlogged environments like Akaki, it appears that other crop management
practices such as drainage of excess water and adjustment of planting dates should be studied,
in addition to nitrogen application, to increase gluten content of durum wheat.
Gluten content of varieties was significant at both locations and Tob 66 had the highest
while kilinto had the lowest (Table 1). As shown in Fig. 1, at Debre Zeit, there is a general
linear increasing trend of gluten content of varieties with increasing nitrogen level. However,
the increase was sharp beyond 90 N kg/ha for Tob 66, which gave 37 % gluten content at the
highest nitrogen fertilizer level. Besides, Tob 66 had consistently high wet gluten starting
from the nil nitrogen treatment to the highest level and, this could suggest the efficiency of
the variety in converting assimilates to protein. At Akaki on the other hand, there is no
definite trend for the applied nitrogen levels and gluten content (Fig.2).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004

















































0 30 60 90 120
Nitrogen Level(kglha)


Fig. 1. Gluten Content of durum wheat varieties at different nitrogen levels at Debre Zeit


60
Nitrogen level (kglha)


Fig. 2. Gluten Content of durum wheat varieties at different nitrogen levels at Akaki




According to ICC (2001), the theological characteristics of a dough are expressed as the

resistance of the dough to stretching and its extensibility until it begins to rupture. (Curic et

al., 2001) measured the physical properties of the dough of wheat flour, which primarily





12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


Assassa
-- Boohal
-9 Foka
*OKilinto
(-Tob 66


30



25



20



8 15



10
10 -



5



0


I--4P 1










depend on the gluten quality. In this study, the observed non-significant difference in
theological properties due to increasing application of nitrogen fertilizer could suggest that
the traits are affected more by genotype rather than by environment in which varieties are
grown. Unlike this, however, Virga et al. (2003) reported the use of the intensive production
system in bread wheat resulted in a significant improvement in dough resistance. Curic et al.
(2001) reported gluten quality of wheat to be dependent on location and region of cultivation.
In this study, varietal differences were observed in dough resistance. Assassa showed the least
performance in dough resistance but it was within the acceptable range for pasta industry use.
From the alveograph curve, the resistance to stretching is taken from the maximum height
reached by the curve (P) while extensibility is taken from the total length (L) in the horizontal
direction of the curve. Alveograph strength is taken from the area under the alveogram (W) X
10-3 ergs and the greater the reference area shows the higher the value ofW. Alveograph
strength (W X 10-3 ergs) and the ratio of dough resistance to extensibility (P/L) are the two
commonly used indicators of quality of durum wheat theological characteristics. When W is
greater or equal to 250 and P/L ratio is greater than 0.8, the flour is considered to be obtained
from strong grains (Professional pasta website, 1999). Considering P/L ratio, all varieties fall
under strong gluten category.

Discussion
Increasing grain protein, especially that of gluten content of durum wheat and its strength has
recently received higher attention due to the premium product produced out of it. In Ethiopia,
growing selected varieties like Boohai, Foka and Tob 66 with high gluten content and
acceptable dough characteristics under appropriate growing environment and; could be a good
option for durum wheat growers to produce high quality durum wheat. Considering the varied
agro-climatic conditions of the country, which varies within a short distance, the durum wheat
growing environments should be characterized for suitability to produce industrial quality
durum wheat. Regarding the studied theological properties, the observed non-significant
difference between nitrogen fertilizer levels could show selection of appropriate varieties
could be more important factor than the growing environment. Although early to conclude,
the observed significant differences in gluten content between 60kgha1, recommended for
grain yield at Debre Zeit, and 120Kg ha' N levels in this study could suggest the need to
consider economically important quality traits besides grain yield in fertilizer rate
recommendations. The durum wheat breeding program should also concentrate on
development of varieties with desirable chemical grain quality as well as physical dough
properties required by Pasta industries. Such type of study on input responsive semi dwarf
durum wheat varieties is recommended.


Acknowledgments-The authors are thankful to the technical staff of Durum Wheat Research
Project of the Debre Zeit Agricultural Research Center. The authors would like to
acknowledge Kality Food Share Company for quality analysis.



References
Campbell, C.A., Selles. F., Zentner, R.P. and MacConkey B.G. 1993. Nitrogen management for zero
till spring wheat: disposition in plant and utilization efficiency. Commun. Soil Sci. Plant Anal
24:2223-2239
Curic, D., Karlovic, D., Tusak, D., Petrovic,B.and Dugum, J.2001. Gluten as a standard of wheat flour
quality. Biotechnol.39: 353-361


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










D'Egidio,M.G., Mariani, B.M., Nardi,S., Novaro,P. and Cubadda,R.(1990). Chemical and technological
variables and their relationships: A predictive equation for pasta cooking quality. Cereal
Chem., 67,275-281
Dexter, J.E., Crowle, W.C. Matsuo, R.R. and Kosmulax, F.G. 1982. Effect of N fertilization on quality
characteristics of five North American amber durum wheat variety. 1. Can.J. Plant Sci.
(Canada), 62: 90-902
Gashawbeza, B., Mekuria, B., Yaekob, A., Mitiku, D., Tadesse, T., and Kifetew, J. 2002. Effect of
nitrogen fertilization on grain protein content of durum wheat variety. Proceedings of 6th
Annual Conference of Ethiopian Soil Science Society. (in press)
Geleto, T.,Tanner, D.G., Mamo, T. and Gebeyehu, G.,. 1996. Response of rainfed bread and durum
wheat to source, level and timing of nitrogen fertilizer on two Ethiopian Vertisols: II. N
uptake, recovery and efficiency.
Hadjichristodoulou, A. 1979. Genetic and environmental effects on vitreousness of durum wheat.
Euphytica 28:711-716
International Association for Cereal Science and Technology. 2000. ICC Standards 106/2,Viena,
Austria
Josephides, C.M.; Joppa, L.R. and Youngs, V.L. 1987. Effect of chromosome 1 B on gluten strength
and other characteristics of durum wheat. Crop Sci. 27:212-216
Metho, A.L, Hammes, P.S. and De Beer,J.M. 1997. Effect of cultivar and soil fertility on grain yield,
yield components and grain nitrogen content of wheat. African Crop Science Proceedings,
Vol. 3: 695-709
Mosconi, G and Bozzini, A. 1973. Effects of application of late nitrogen fertilizer to durum wheat.
Revista di Agronomia:75 (Cited in Field Crop Abstr. (1975) 4226)
Ottman, M.J., Doerge, T.A. and Edward, E.M. 2000. Durum grain quality as affected by nitrogen
fertilization near anthesis and irrigation during grain fill. Agron. J. 92:1035-1041.
Prima, G.Di., Sarrino, R. and Stringi, L. 1982. Nitrogen, its role in controlling yield and quality of
durum wheat in the warm arid zone of Sicily. Inst. Agron. Gen. Erbace, Italy (Cited in An
Annoted Bibliography in Durum Wheat 1972-1984, ICARDA)
Rharrabti,Y., Villegas,D., Moral,L.F.G., Aparicio, N., Elhani, S. and Royo, C. 2001. Environmental
and genetic determination of protein content and grain yield in durum wheat under
Mediterranean conditions. Plant Breeding 120,381-388
Simmonds, D.H. 1989. Inherent quality factors in wheat. Wheat and wheat quality in Australia.
CSIRO, Australia, P31-61
Spiertz, J.H.J. and Devos, N.M. 1983. Agronomical and physiological aspects of the role of nitrogen
in yield formation of cereals. Plant and soil 75:379-391
Woolfolk, C.W., Raun, W.R. Johnson. G.V. Thomason, W.E., Mullen, R. W., Wynn, K. J. and
K.W.freeman.2002. Influence of late-season foliar nitrogen application on yield and grain
nitrogen in winter wheat. Agron.J. Agron.J. 94:429-434


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Impact of Irrigation Frequency and Farmyard
Manure on Wheat Productivity on a Saline-
Sodic Soil in Dongola, Sudan

Elmoiez M. Fadul' and Mukhtar A. Mustafa2
1Dongola Agric. Research Station (ARC), Sudan.
2Faculty ofAgriculture, University of Khartoum, Sudan

Abstract-A field experiment was conducted in January 2001 and December 2002,
at Dongola University Farm to investigate the effects of irrigation frequency and
farmyard manure application on salt leaching and on wheat (Triticum aestivum L.)
growth on a saline-sodic sandy loam soil classified as fine loam, mixed,
hyperthermic, sodic haplocalcids. Each experiment consisted of three irrigation
frequencies: 7, 14, and 21 days, and three levels of farm yard manure (F.Y.M): 0, 4.8
and 9.7 ton/fed. The quantity of water applied was proportional to the irrigation
frequency and estimated from knowledge of reference evapotranspiration as
predicted by Jensen and Haise equation, a crop factor and an irrigation efficiency
value. Each treatment was replicated thrice in a split-plot design. Irrigation
treatments accommodated main plots (7 x 18m) and manure application sub-plots (7
x 6m). Data, collected at harvest, showed that all irrigation treatments caused salt
leaching, which decreased with increase of soil depth. The data did not reflect the salt
distribution between irrigation intervals. The 'irrigated weekly' (Fl) was the superior
treatment; all forage and grain yields and their components increased with irrigation
frequency.

INTRODUCTION
Northern Sudan is dominated by hyper-arid, arid and semiarid ecological zones that favor the
formation of salt-affected soils (Nachtergaele, 1976; Mustafa, 1986). Dongola, in the
Northern State, has two main soil orders: Entisols in the first terrace and Aridisols in the
upper second and third terraces. Entisols, at the close proximity of the Nile, are fertile, non-
saline, non-sodic and highly productive soils. However, they are endangered by gully erosion
at the riverside and sand encroachment from the adjacent desert. Furthermore, the land is
intensively cultivated and fractionated due to land tenure laws. The accessibility of good
quality Nile water (Mustafa, 1973) and Nubian aquifer water prompted horizontal expansion
of agriculture in salt-affected soils of the upper terraces (Aridisols). The productivity of these
soils is constrained by osmotic and specific ion effects and nutritional imbalance.
Wheat (Triticum aestivum) is a strategic field crop in Sudan, since it constitutes the main
staple food for most of the urban population. It is grown in Northern and Central Sudan.
However, the new trend is to restrict its production to the northern State because of its
favorable climatic environment and consequent higher yield as compared to Central Sudan.
The national need for more wheat production necessitated the expansion of wheat production
to salt-affected areas. The proper use of these soils requires appropriate soil and water
management.
The share of the Nile water of Sudan is limited because of the large expansion of
irrigated agriculture in the arid and semi-arid regions. Thus, there is need to economize on
water use by increasing its efficiency.
The present research was undertaken to investigate the effect of irrigation frequency and
farm yard manure on salt leaching and wheat growth on a saline-sodic Aridisol in Dongola.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Materials and Methods
A field experiment was conducted in two successive seasons (Jan. 2001 April 2001 and Dec.
2001- April 2002) on an old alluvium saline-sodic sandy loam soil classified as fine loam,
mixed, hyperthermic, sodic Haplocalcids (Soil Survey Staff 1996) at Dongola (19 N' 290 30'
E), 228 above sea level. The characteristics of this soil are presented in Table 1.
The treatments consisted of three irrigation frequencies:7 (Fl), 14 (F2) and 21 (F3) days,
and three levels of farm yard manure: 0 (MO), 4.8 (Ml) and 9.7 (M3) ton/feddan (1 feddan =
0.42 ha).Each treatment was replicated three times in a split-plot design. Irrigation
frequencies were designated to main plots and farmyard manure levels were accommodated in
subplots. The main plots were arranged in completely randomized block design. The land was
disc ploughed to 20-cm depth, and leveled using a long-span blade leveler. Nine main plots (7
x 18 m), each subdivided into three sub-plots (7 x 6 m) were constructed using earth
embankments. The main plots were 1-meter apart to check lateral water movement. In the
second season, the experiment was repeated in the same plots, which were harrowed before
seeding.
Wheat (Wadi El Niel variety ) was sown on 1st January 2001 in the first season and on
27th December 2001 in the second season. Seeds were hand dibbled in rows 20 cm apart in
each subplot with a seed rate of 60-kg/ feddan. The quantity of water applied per irrigation
(Q, mm) was estimated by the following relationship:

Q =kc x ETp x F x Ei

Where: kc = a crop coefficient, ETp = potential evapotranspiration (mm/day), F = irrigation
frequency (days) and Ei = efficiency of irrigation water application (0.7). kc was estimated
using the FAO (1984) procedure, ETp was estimated using the following Jensen and Haise
(1963) equations:

ETp = CT (T Tx) Rs

CT = 1/(Ci+7.6 CH)

C1 = 38 2E/305

CH= 50 mb/ (e2-el)

Tx= 2.5 0.14(e2-ei) E/550

Where: T= mean air temperature (C), E = the site elevation (m), el and e2 = the saturation
vapor pressure of water (mb) at the mean monthly minimum and maximum air temperature of
the warmest month in the year, respectively, Rs = short wave incoming solar radiation. Thus,
the water applied at each irrigation event was proportional to the irrigation frequency and
varied with the month. However all treatments received the same total amount (seasonal) of
water by the time of harvest. These amounts were 856.6 and 774.7 mm in the two successive
seasons. The estimated irrigation water requirement (IWR) in each month expressed in
mm/day is presented in Table 2. The quantity of water applied per irrigation, Q is the product
of IWR and F. Thus using Table 2, a predetermined quantity of water was applied to each
subplot using Parshall flume. Three irrigations at 7-day frequency were applied to all subplots
for establishing the crop before subjecting it to different irrigation regimes. The FYM was


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










heaped, mixed with water, and composted for one month before application. The average EC
of the composted FYM was 20.7 dS/m. It was applied at a predetermined rate at the third
irrigation. In all treatments, P fertilizer (Triple super phosphate) was applied before sowing in
the order of 80 kg/feddan. Twenty-one and 63 days after sowing, urea at the rate of 20 kg N/
feddan was applied to all treatments. Fertilizers were applied at the same rate and stage in
both seasons. Manual weeding was done whenever needed.
Soil samples were collected, before sowing and at harvest, by an auger from each subplot
at an increment of 0.2 m from the surface to a depth of one meter. Gravimetric moisture
content, electrical conductivity (ECe) and sodium adsorption ratio (SAR) of the saturation
extract were determined using standard procedures (Richards, 1954, Black, 1962).
At harvest, ten plants were selected at random from each subplot and their height, head
length and leaf area index were determined. One-meter square was taken at random and the
number of heads was counted. Ten heads were selected at random and threshed collectively
and the number of seeds per head was counted. Thousand grains were taken randomly from
each treatment and weighed. The total biomass enclosed in an area of 5 x 6 m2 in each subplot
was cut at ground level and the weight was measured and expressed in ton/feddan. The
harvested crop was left to dry for a week threshed and the total gain yield was determined in
ton/feddan. The crop water use (CWU) was determined by the following water balance
equation:

CWU = I+ P + AM

where: I = Amount of irrigation water (mm), P = Amount of rainfall (mm) and AM = The
difference between cumulative water content before sowing minus that at harvest in one meter
depth (mm). The crop water use efficiency (CWUE) was calculated by dividing grain yield by
crop water use (kg/m3)


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Table 1. Seedling and adult plant reactions (0-4 scale) of wheat varieties when tested with to P.
raminis isolates from Ambo
Isolate 1 Isolate 2
No. Variety Seedling reaction Adult plant reaction Seedling Adult plant
reaction reaction
Durum wheat
1 Assassa 2 3 2 2
2 Tob-66 1 1 1 1
3 Kilinto 1 3 2 2
4 Foka 3 2 1 1
5 Gerardo 1 1 2 2
6 DZ1640 2 1 2 2
7 DY1050 2 2 2 2
8 Cocorit-71 1 3 1 3
9 Yielma 2 1 1 1
10 DZ1928-2 1 1 1 2
11 DZ 1691 2 2 2 2
12 DZ 1695-5 2 2 3 2
13 DZ1543 1 2 1 3
14 Boohai 2 2 2 2
15 Bichena 3 2 1 3
Susceptible 4 4 4 4
check
Bread wheat
1 Kubsa 2 4 2 3
2 Wabe 3 3 0 1
3 Galama 2 2 2 2
4 Tuse 3 3 0 1
5 Katar 3 2 2
6 Shina 3 3 0 2
7 Hawi 0 0 0
8 Simba 0 0 0
9 Wetera 0 0 0
10 HAR 2192 1 2 0 2
11 HAR 2508 3 1 1
12 F-H-6-1-7 1 3 1
13 Abola 2 0 0
14 Tura 2 1 0
Susceptible 4 4 4 4
check


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Table 2. Estimated irrigation water requirements (IWR) of wheat for the two seasons in
Dongola.*


* ETp=
ETcrop


I


Results and Discussion

The results of the two seasons showed that irrigation per se caused significant salt leaching.
Furthermore, salt leaching was not significantly affected by irrigation frequency (IF),
farmyard manure (FYM) or by their interaction. Thus, the ECe data of each season were
averaged over the three levels of FYM and plotted to reflect the main effects of irrigation
frequency (Fig. la and Fig.lc), and averaged over the three levels of irrigation frequency and
plotted to reflect the main effects of FYM (Fig. lb and Fig. Id). In general, the effectiveness of
salt leaching decreased with increase in the depth of the soil layer. It may be cautioned that
this data was collected at harvest. It indicates the overall effect of treatments at harvest, but it
does not reflect the salt distribution between irrigation intervals.
For the first season, the ECe redistribution profiles depicted a top desalinized zone (0 -
60 cm) and a salt accumulation zone (60-100 cm). The main effect data of IF showed that F1,
F2 and F3 reduced the initial ECe of the 0 20 cm by 89, 90 and 79 %, respectively (Fig. la).
The reductions of the initial ECe (20-40 cm) by the same treatments in sequence were 56, 50
and 59 %, respectively. The reductions of the initial ECe (40-60 cm) by the same treatments
in sequence were 22, 36 and 19 %, respectively. Irrigation with good quality Nile water
(Mustafa, 1973) caused desalinization of these layers. It is evident that the efficiency of salt
leaching decreased with increasing soil depth. This may be attributed partly to the gradual
decrease of water available for salt leaching and consequent decrease in downward water
movement with increase in soil depth, and partly due to the rise of salt by capillarity during
the drying cycle.
The initial ECe (0-20 cm) was reduced by 85, 84 and 88% due to the application of Mo,
M1 and M3, respectively (Fig. b). The same treatments in sequence reduced the initial ECe
(20-40 cm) by 53, 58 and 54 %, respectively. At the 40 -60 cm depth, the initial ECe was
reduced by 28, 26 and 23, respectively. The reductions of the initial ECe in the successive
depths due to FYM were of nearly similar order of magnitude as that due to IF. The effect is
conceivably an indirect effect of irrigation. FYM is expected to promote water movement,
enhance root development and ramification, and thereby enhance salt leaching. However, its
effect was not significant. Although, the FYM was washed before its application, its residual
salinity limited its effectiveness in salt leaching. Furthermore, vaporization during
composting reduced its potential as a nitrogen source.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


Month ETp kc ETcrop IWR
(mm/day) (mm/day) (mm/day)

First season
(2001)
January 3.50 0.70 2.45 3.50
February 4.48 1.2 5.38 7.70
March 6.70 1.2 8.04 11.4
April 8.69 0.70 6.08 8.70

Second season
(2001-2002)
December 3.64 0.60 2.18 3.10
January 3.50 0.70 2.45 3.50
February 4.48 1.10 4.93 7.00
March 6.70 1.10 7.37 10.5
Potential evapotranspiration estimated by Jensen and Haise equation, kc = crop factor,
= Crop (actual) evapotranspiration










For the second season, irrigation reduced the salinity throughout the profile (0 100 cm)
(Fig.lc and Fig. Id). Treatments F1, F2 and F3 reduced the initial ECe (0-20 cm) by 59, 80 or
84 %, respectively. Mo, M1 and M3 reduced the initial ECe (0-20 cm) by59, 81 and 84 %,
respectively. It seems that the reduction of salinity was due mainly to irrigation and not to the
application of farmyard manure. This is because the top layer is permeable and did not need
FYM to promote water movement. It is evident that salt leaching was greater in the first
season because of the initial higher salt level in the virgin uncultivated soil. However, trends
of salt leaching were similar.
Fig. la indicates that F2 was relatively more efficient in salt leaching than Fi or F3, since
it desalinized the top 70 cm whereas Fi and F3 desalinized the top 60 cm. However, the effect
was not significant.
The second season data showed that irrigation reduced the initial ECe throughout the soil
profile (0-100 cm). This was a cumulative effect, since the experimental plots of the first
season were irrigated in the second season. Treatments Fi, F2 and F3 reduced the initial ECe
(0-20 cm) by 59, 80 and 84 %, respectively. Mo, M1 and M3 reduced the initial ECe at the
same depth by 59, 81 and 84%, respectively. The results indicate that the effect of FYM was
an indirect effect of IF. FYM did not enhance salt leaching by water because the inherent salt
content of the manure was not reduced greatly and it was not incorporated in the soil.
Furthermore, salt leaching indicated, as percentage decrease of the initial ECe, was greater in
the first season. This is because the initial ECe in the first season was greater than in the
second season.

SAR redistribution
The main effects of treatments on SAR are presented on Figs. 2a, b, c, d. Irrigation per se
significantly reduced the initial SAR in the top 50 cm in the first season and through out the
whole profile in the second season. In the first season, Fi and F2 reduced the initial SAR
throughout the profile; however, the percentage decrease in SAR was minimal below 50 cm
depth. F3 increased the initial SAR in the third layer. In general, the effectiveness of
dealkalization decreased with increase in soil depth. This trend was similar to desalinization
and could be explained on the same manner. Dealkalization was due to dissolution of ca-
bearing compounds, replacement of Na by Ca ions on the exchange complex and leaching
of the more mobile Na ions (Mustafa and Abdelmagid, 1981). It is evident that the initial
SAR of the top layer was rapidly and markedly reduced merely by leaching with water, this
may attributed to the low SAR of the irrigation water and decrease in soil solution SAR
values during leaching because of dilution and faster leaching of sodium compared with
calcium and magnesium. Similar results were obtained in India (Leffellar and Sharma, 1977;
Dahiya etal., 1981,1982).
For the first season, the initial SAR of the 0-20 cm was reduced by 72, 80 and 64 % by
F1, F2 and F3, respectively The reductions in the second layer caused by the same frequencies
in sequence were 35, 27 and 39 %, respectively. The initial SAR values of the third layer were
reduced by 6 and 7 and increased by 12 % by the same frequencies in sequence. The
differences between treatments were not significant. The effect of FYM on SAR
redistribution profile was qualitatively similar to that of irrigation frequency. The trend of
FYM effect on SAR profile was similar to that of salt leaching and it may be explained in the
same manner.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004














ECe, dS/m
0 5 10 15 20 25 30 35 40 45 50
i I I I I I I I I I


20





40

Soil
depth, cm

60





80




20
100
0


40




60




soil80
depth,
cm



100


Initial


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


Fig. (la) Mean electrical conductivity
(dS/m) profile as affected by irrigation
frequency (days) at the end of the first
season (Dec. 2000- April 2001)




























Fig. (lb) Mean electrical conductivity
(dS/m) profile as affected by farm yard
manure (ton) at the end of the first season
(Dec. 2000- April 2001)


ECe, dS/m


10 15 20 25 30 35 40
1 1 1 1 1 1


5
1






ECe, dS/m
10 15 20 25
1 1 1 1


ECe, dS/m
10 15 20 25
1 1 1 1


30 35
1 1


20



40



60
Soil
depth,
cm
80



100


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


0 5
1


Mo Initial


Fig. (Ic) Mean electrical conductivity (dS/m)
profile as affected by irrigation frequency (days) at
the end of the second season (Dec. 2001- April
2002)






























40


Fig. (Id) Mean electrical conductivity (dS/m)
profile as affected by farm yard manure (ton)
at the end of the second season (Dec. 2001-
April 2002)


0 5
1


60



80






100
Soil
depth,
cm










SAR
10 20 30 40


20


40



60


80

Soil
depth,
cr100










20



40



60



80




100


Soil
depth,
cm


50 60 70


50 60 70


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


Fig. (2a) Mean sodium adsorption ratio (SAR)
profile as affected by irrigation frequency (days)
at the end of the first season (Dec. 2000- April
2001)


7 Initial


Initial


SAR
0 10 20 30 40


Ivii


Fig. (2b) Mean sodium adsorption ratio (SAR)
profile as affected by farm yard manure (ton) at
the end of the first season (Dec. 2000- April 2001)









SAR
20 30 40 50
1 1 1 1


Fig. (2c) Mean sodium adsorption ratio
(SAR) profile as affected by irrigation
frequency (days) at the end of the second
season (Dec. 2001- April 2002)


M1 SAR
40 0 10 20 30




60





80



Soil
depi l0
cm


40 50 60
1 1I


Fig. (2d) Mean sodium adsorption ratio (SAR)
profile as affected by farm yard manure (ton) at
the end of the second season (Dec. 2001- April
2002)


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


0 10
I I


20



40



60


80
Soil
depth,
cm
100


Initial


Initial










Yield components and total grain yield
Since irrigation had the predominant impact on growth and yield of wheat, only the main
effects of irrigation frequency are reported in Table 3. In general, all variables increased with
increase in FYM, but the effect in many cases was not significant. In the first seasons, LAI,
head length, number of grains per head, and total biomass increased with increase of irrigation
frequency; but the difference was only significant between F1 and F3;. Plant height, 1000
grains weight total grain yield and water use efficiency increased significantly with increase
of irrigation frequency. The number of heads/m2 increased with increase of irrigation
frequency but the effect was not significant. In all cases, F1 was the superior treatment. In the
second season, all forage and grain yields and their components increased with increase in
irrigation frequency but the effects were only significant in the case of LAI and number of
grains per head.
For the first season, the impact of irrigation frequency and FYM on grain yield, and
consumptive water use efficiency, which were significant, is presented in Table 4. It is
evident that treatment F1M2 was the superior treatment and treatment F3M0 was the inferior
treatment. In comparison to the inferior treatment, the total grain yield was significantly
increased by 170 % and the CWUE was increased by 100 %. Increasing the irrigation interval
would prolong both osmotic and water stress, reduce cell elongation and decrease plant
growth and grain yield (Heyn, 1940; Mustafa and Abdelmagid, 1981). Irrigating weekly will
increase the water potential between irrigation and alleviate both stresses. Treatment F1M2
was also superior in the second season, but the effect was not significant. In comparison to the
inferior treatment, the total grain yield was significantly increased by 46 % and the CWUE
was increased by 31 %. The beneficial impact of the superior treatment was reduced in the
second season because was relatively ameliorated in the first season.
It is recommended that in these higher terrace saline-sodic sandy loam Aridisols, wheat
should irrigated weekly at a rate equivalent to the potential evapotranspiration. Farm Yard
manure may be washed first properly composted and incorporated into the plough layer after
the first month.

Table 3. Main irrigation effect (means at harvest for the three levels of F.Y.M) on the growth and
yield of wheat in two successive season (2000/01- 2001/02)
Type of data Irrigation frequency /day LSD
F1 F2 F3
First season (April 2001)
LAI 1.6 1.2 1.0 LSD 0108 = 0.30
Plant height (cm) 65.7 56.1 49.5 LSD 00022= 5.06
Head length (cm) 6.8 6.2 6.0 LSD 0 0042= 0.41
No. of heads /m2 378.6 339.7 307.1 NS
No. of grains / head 30.6 25.6 20.3 LSD 00185= 5.63
1000 grains weight (gm) 33.3 30.7 29.7 LSDo0002= 0.64
Total biomass ton/fed 2.9392 2.2050 1.5563 LSD o 0225 = 0.8073
Total grain yield ton/fed 1.0834 0.8220 0.5220 LSD 00045 0.20963
Water use efficiency kg/m3 0.301 0.228 0.145 LSD o0046= 0.06
Second season (April 2002)
LAI 1.5 1.4 1.1 LSD o0 041 =0.29
Plant height (cm) 61.7 58.8 56.4 NS
Head length (cm) 6.30 6.00 5.70 NS
No. of heads /m2 422.9 398.1 391.6 NS
No. of grains / head 31.3 26.0 24.1 LSD 0076 = 3.2
1000 grains weight (gm) 34.0 33.1 31.9 NS
Total biomass ton/fed 2.3092 2.0549 1.9795 NS
Total grain yield ton/fed 0.9303 0.7966 0.7060 NS
Water use efficiency Kg/m3 0.285 0.244 0.217 NS
F1, F2 and F3 mean 7, 14 and 21 days respectively.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Table 4.Mean grain yield (ton/feddan) and consumptive water use efficiency of wheat (kg/m3) as
affected by irrigation frequency and farm yard manure.*
Frequency (day) MO M1 M2 Mean

Grain yield

7 0.828 1.121 1.302 1.083 a
14 0.622 0.929 0.915 0.822 b
21 0.482 0.511 0.573 0.522 c
Mean 0.644 a 0.854 b 0.930 b
Water use efficiency
7 0.230 0.311 0.361 0.301 a
14 0.172 0.258 0.254 0.228 b
21 0.134 0.141 0.159 0.145 c
Mean 0.179 a 0.237 b 0.258 b
* Mo = Zero farm yard manure, M1= 4.8 ton / feddan farmyard manure, M2 = 9.7 ton/feddan.
Main frequency effect (F) LSD 00045 = 0.20963
Main farmyard manure effect (M) LSD o 0003 = 0.11100
Main frequency effect (F) LSD o 0046 = 0.06
Main farmyard manure (M) LSD o 0003 = 0.03


References
Black, C. A. (1962). Methods of Soil Analysis. Part I. Agronomy Monograph No. 9. American Society
of Agronomy, Inc., Publisher, Madison, Wisconsin, USA.
Dahiya, I.S., Malik, R.S. and Singh, M. (1981). Field studies on leaching behaviour of a highly saline
sodic soil under two methods of water application in the presence of crops. J. of Agric. Sci.
Cambridge. 97: 383-389.
Dahiya, I.S., Malik, R.S. and Singh, M. (1982). Reclaiming a saline -sodic, sandy loam soil under rice
production. Agricultural water management. 5: 61-72.
FAO (1984). Irrigation and drainage in crop water requirements. Paper No. 24. Rome, P. 35-44.
Heyn, A.N.F. (1940). The physiology of cell elongation. Bot. Rev. 6: 515.
Jensen, M. E. and Haise, H. R. (1963). Estimating Evapotranspiration from Solar Radiation. Proc. Am.
Soc. CN. Engr., J. 89:5-41.
Leffellaar, P.A. and Sharma, R.P. (1977). Leaching of a highly saline sodic soil J. of hydrology. 32:
203-219.
Mustafa, M. A. (1973). Appraisal of the water quality of the Blue and the White Niles for irrigation
use. African Soils. 18: 113-124.
Mustafa, M.A. (1986). Salt affected soils in the Sudan their distribution, properties and management.
Reclamation and revegetation research. 5 : 115 124.
Mustafa, M.A. and Abdelmagid, E.A. (1981). The effect of irrigation interval, urea -N, and gypsum on
salt redistribution on a highly saline-sodic montmorillonitic clay soil under forage sorghum.
Soil Sci. 132 4t: 308-315.
Nachtergaele, F.O.F. (1976). Studies on saline and sodic soils in Sudan. FAO/ UNDP project for
strengthening the soil survey administration: SUD/71/553. Technical Bulletin N. 24. May
1976. Wad Medani, Sudan.
Richards, L. A. (1954). Diagnosis and improvement of saline and alkali soils. Hand book 60., USDA.
Soil Survey Staff (1996). Soil Taxonomy (key). Seventh Edition.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Consumptive Use of Water and Water Use
Efficiency by Wheat (Triticum aestivum) in
Relation to Irrigation and Nitrogen

Antony M. Kibel, Subedar Singh2, and Naveen Kalra3
'Egerton University, Agronomy Department, P.O. Box 536 Njoro, Kenya (akmwangi(iivahoo.comn)
2Indian Agricultural Research Institute, Water Technology Center, 110012 N. Delhi, India; 3Indian
Agricultural Research Institute, Center for Agriculture Systems Simulation, 110012 N. Delhi, India

Abstract-A field experiment was carried out on a sandy loam soil to study the use
relationships to yields of a late sown wheat cultivar, HD-2285 under limited and
adequate water and nitrogen regimes. The experiment was laid out in a split-plot
design with four irrigation levels (Io, no post-sowing irrigation; Ii, one irrigation at
CRI; 12, two irrigations, each at CRI and flowering; 13, four irrigations each given at
CRI, jointing, flowering and dough stages) in main plots and a combination of three
N levels, viz. No, N50 and N100 and two zinc levels, Zo and Z5 in sub-plots, subscriptt
numbers signifying N and Zn quantities in kg/ha), in three replicates. The
consumptive use of water (CU) by wheat increased with every additional irrigation
level to a maximum of 328.4 mm and 301.7mm. Water use efficiency (WUE) was
maximum (1.38 kg grain/m3 water use) with two irrigation treatments given at the
crown root initiation (CRI) and flowering stages. This did not correspond with the
above ground biomass and grain yield production, which were highest under four
irrigation treatments (13). The moisture use rate increased with increase in irrigation
water to a maximum of 2.74 and 2.51 mm/day in the first and second seasons,
respectively. Moisture extraction was maximum (59.4% 65.8%) from the 0-30 cm
soil layer. Water use efficiency increased markedly with increase in nitrogen
application attaining a maximum (1.42 and 1.52 kg grain/m3 water use) under 100 kg
N/ha application. Maximum WUE did not correspond to the highest grain yield. The
rate of increase in both grain yield and WUE started to decline as ET further
increased beyond 270 mm.

Introduction
The importance of irrigation water to wheat is to provide the water for enhanced transpiration.
This permits higher leaf area indices and stomatal apertures and therefore, a greater rate of
biomass production which often lead to higher yields (Davis, 1994). Improving water use
efficiency (WUE) in crop production and sustainable use of water resources are the need of
the day. Fully satisfying crop water requirements may be prohibitive in terms of sustainable
utilization of limited water. The solution therefore, is to limit water application to specific
stages thereby minimizing loss of yield from water stress. Thus, it is imperative to study and
know which critical growth stages of wheat; a small amount of water application would
results in optimal WUE and minimum loss of yield.
Apart from water, other factors such as essential nutrients play important roles in
optimizing growth and yield of wheat. Major wheat growing regions of the world are poor in
available nitrogen. Nitrogen fertilization is essential for obtaining reasonable yields.
Improvement of plant nutrition often leads to increased leaf area index (LAI). As the LAI
increases, transpiration increases and evaporation from the soil surface declines because of
shading and canopy closure. Nitrogen fertilization can enhance new leaf growth (increased
LAI and CGR) and delay plant senescence (increased leaf area duration), resulting in


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










increased transpiration demand. Nutrient deficiencies however often lead to more rapid
senescence (Davis, 1994). Thus, a better understanding of the response and relationship of
wheat growth (i.e., dry mater accumulation and LAI) to nutrient and water inputs is necessary
in our assessment of a cultivar. This will also enable us make appropriate decisions for
purposes of optimizing the productivity of wheat under various environments.
Seasonal consumptive use of water by wheat is universally acknowledged to increase
with increasing available soil moisture. This is commensurate with the increase in growth
and yield of wheat. Water use efficiency is however, known to decrease with increase in
irrigation water applied beyond an optimum (Zhang, et al. 1999). The quantities of moisture
used and the efficiency of it's utilization differs however, as influenced by factors such as the
environment, cultivars, duration of the cultivars on the land and the rooting pattern of the
crop.
The effects of irrigation on crop production are usually quantified using crop production
functions that relate crop yield to the amount of water applied (English and Raja, 1996).
These functions are used to optimize on-farm irrigation and economic evaluation of irrigation
water application. Water production functions are mathematical equations relating crop
response in terms of biomass or grain yield with water availability or its uptake by the crop.
These functions can be used in managing water resource for achieving maximum returns with
minimum amount of water application as irrigation. The use of water-yield relationships has
been employed in the development of models that are used for prediction purposes. This type
of work has mostly been done successfully in the developed countries. There is a need for
more work in the developing countries, where water is limited, for purposes of determining
the optimum amounts of water required in producing appreciable and sustainable crop yields.
In light of the considerations mentioned above, the present investigation was undertaken
at the Water Technology Center, Indian Agricultural Research Institute, New Delhi during the
winter seasons of 1999-2000 and 2000-2001 with the following objectives:
1. To determine the influence of irrigation, nitrogen and zinc on the growth of wheat
2. To determine the seasonal consumptive water use, water use efficiency and moisture
use rate of wheat under varying irrigation and nutrient levels
3. To compute production functions for wheat under varying water supply conditions.

Materials and Methods
Four irrigation levels (Io, no post-sowing irrigation; Ii, one irrigation at CRI; 12, two
irrigations, each at CRI and flowering; 13, four irrigations each given at CRI, jointing,
flowering and dough stages) were allotted to main plots and six fertilizer levels (NoZo, no
nitrogen and zinc; NoZ5, no nitrogen and 5 kg Zn/ha; N5oZo, 50 kg N/ha and no Zinc; N50Z5,
50 kg N/ha and 5 kg Zn/ha; N1ooZo, 100 kg N/ha and no zinc; Ni00Z5, 100 kg N/ha and 5 kg
Zn/ha) were allotted to the sub-plots of a split plot design replicated thrice.
Dry matter production (DMP), Leaf Area Index (LAI), grain and straw yield data was
recorded. Periodic soil samples from 0-120 cm soil depth were collected layer-wise to
compute water use by crop as described by Dastane (1972). Crop evapo-transpiration to yield
relationships was determined through regression analysis.
Soil samples were taken from plots at depth intervals of 0-15, 15-30, 30-60, 60-90,and
90-120 cm soil profiles and dried to, respectively, to determine the soil moisture. Samples
were taken at sowing time; 48 hours before; and after irrigating; and at harvest, with the help
of a tube auger. Samples were dried in the oven at 1050 C for over 24hr till constant dry
weight. The moisture content was measured thermo-gravimetrically. Seasonal consumptive
water use (CU) and the water use efficiency (WUE) of the crop, daily moisture use rate


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










(MUR) and soil moisture extraction pattern of the crop were computed from the periodic soil
moisture content data.
The seasonal consumptive water use by the crop under different treatments was worked
out using the formula described by Dastane (1972):

N n
CU= Z (Epx0.6)+Z (M M2x Asi x Di + ER + GWC
1 i=1 100

where
CU= Consumptive use of water (mm)
Ep= Pan evaporation value from the USWB class A open pan evaporimeter for the period
from the date of irrigation to the date of soil sampling after each irrigation (mm)
A constant used for obtaining ET value from Ep value for the given period of time
M, = Per cent soil moisture (w/w) of the ith layer of the soil at the time of sampling after
each irrigation
M2 = Per cent soil moisture (w/w) of the ith layer of the soil at the time of sampling before
each irrigation
Asi = Apparent specific gravity of the ith layer of the soil
Di = Depth of ith layer of soil (mm)
ER = Effective rainfall, if any during the period under consideration, mm
GWC =Ground water contribution to the root zone moisture during the given period of time
(mm)
n = Number of soil layers
N = Number of days between pre-irrigation and post-irrigation soil moisture samplings

The ground water contribution (GWC) was considered negligible as the ground water table
during crop growth periods remained below 4.0 from soil surface during in both the seasons.
Crop water use efficiency was computed using the following formula and was expressed as kg
grain /m3 water used.


Grain yield (Economic yield)
WUE =
Consumptive Water Use (Seasonal)

Leaf area index was measured using the leaf area to dry leaf weight relationship. At each dry
mater sampling date, a sub sample of fresh leaves from the main sample (Im row length) was
taken from one replication and leaf area was recorded with the help of LI-3100 Area Meter,
LI-COR, Inc. The leaves were then dried at 60 OC for about 24 hr until a constant weight was
obtained. Specific leaf area (SLA) was calculated as the ratio of leaf area (cm2) to leaf weight
(g). This SLA value for each treatment at each sampling time was multiplied by the
corresponding dry leaf weight values, to get leaf area index. Leaf area index is expressed as
total leaf area of the crop (one side only) per unit ground area occupied by the crop. The area
occupied by the plants under consideration in the field was taken as 0.25 m x 1.00 m.
The experimental data pertaining to each character was analyzed statistically by using
Analyses of Variance technique (ANOVA) for split plot. Standard error of mean difference
and significant difference (LSD) at 5% level of significance were worked out for each
character. Pooled analysis of the two years data was done only for grain and straw yield. The


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










computed parameters such as data on soil moisture studies were explained on the basis of
comparative performance.


Results and Discussion

Growth of Wheat (Dry matter and Leaf area index)
The four irrigation treatment applied at CRI, jointing, flowering and dough stages along with
one pre-sowing irrigation increased the dry matter production of wheat at harvest significantly
over other irrigation treatments in both the 1999-00 and 2000-01 seasons.
Total above ground dry matter (yields) production (TDMP) at 30, 60 and 90 days after
sowing was significantly more with added irrigation, compared to the no post-sowing
irrigated TDMP production in second season (Table 1). In the first season however, only the
90 days after sowing (DAS) above ground DM showed significant differences due to
irrigation treatments. This was attributed to the 68.2mm rainfall (Fig. 1) during the initial part
of the first season that mitigated irrigation effects on DMP up to the 60 DAS. Similarly,
application of irrigation increased the leaf area index (LAI) of wheat significantly over the
non-irrigated control treatment at 60 and 90 DAS, in the second year (Table 2).


Table 1: Influence of I, N and Z on total dry matter production (g/m2), at different growth stages
Treatment 30 DAS 60 DAS 90 DAS Harvest
1999-00 2000-01 1999-00 2000-01 1999-00 2000-01 1999-00 2000-01
IO 304.9 222.5 1299.2 999.4 5711.8 5192.3 7061.0 6852.5
I1 316.5 218.9 1306.5 1082.9 6966.1 6181.1 8739.2 8354.4
12 316.6 224.4 1309.6 1139.9 7518.3 6695.2 9876.2 9553.1
13 317.8 236.0 1308.0 1238.7 7915.8 7300.5 10454.2 10524.1
SEm+ 4.34 1.77 10.37 7.57 54.56 42.77 89.60 75.26
CD(p=0.05) NS 5.3 NS 22.8 164.3 128.9 269.9 226.8
NO 292.2 202.9 1086.3 929.5 5423.3 5174.9 7998.4 7744.8
N50 306.6 224.2 1295.2 1085.9 7098.1 6228.7 9029.8 8889.2
N100 343.1 246.4 1536.0 1330.3 8562.6 7623.2 10069.7 9829.6
SEm+ 2.11 2.2 12.34 8.64 65.24 52.89 97.7 87.2
CD(p=0.05) 15.4 6.6 37.2 26.1 196.6 159.4 300.5 262.2
ZO 313.5 225.2 1303.9 1114.6 7018.6 6331.7 8982.2 8800.3
Z5 314.5 225.7 1307.9 1115.9 7037.4 6352.8 9083.1 8842.0
SEm+ 4.17 1.79 10.05 53.26 43.18 85.4 81.4 71.2
CD(p=0.05) NS NS NS NS NS NS NS NS


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004














90

80
C)
o
70-a

60 = -

50 0 ,2

40 Ec --

30 co

20 C,

10

0


Standard meteorological weeks

Rainfall = Evaporation -a-Average temperature ---Average humidity.


90

80

70 ig

60 .'2
wE
50 2

40 "
E-
30 ,

20 o

10

0


= Rainfall
-a- Average temperature


I Evaporation
-u-Average humidity.


Fig l:Pattern of rainfall, evaporation, average temperature and average relative humidity during
Late sown wheat growth periods of 1999-00 and 2000-01


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


60


50


"aE 40

"~ 30
-cc





10


0


0
.m

o 40
t-
a

E 30
SE
- 20
C
20

C
A~nn










Table 2 :Influence of irrigation, Nitrogen and Zinc on the LAI of late sown wheat at 30, 60 and 90
DAS
Treatment 30 DAS 60 DAS 90 DAS
1999-00 2000-01 1999-00 2000-01 1999-00 2000-01
10 0.164 0.291 0.595 0.561 2.349 2.007
11 0.163 0.289 0.614 0.564 3.178 2.697
12 0.163 0.293 0.607 0.566 3.467 2.922
13 0.162 0.292 0.613 0.576 3.603 3.11
SEm+ 0.01 0.05 0.007 0.008 0.036 0.028
CD(p0.05) NS NS NS NS 0.01 0.09
No 0.14 0.226 0.519 0.493 2.696 2.314
N50 0.159 0.278 0.616 0.525 3.272 2.77
N100 0.19 0.368 0.687 0.682 3.48 2.963
SEm+ 0.001 0.005 0.008 0.008 0.047 0.034
CD(p 0.05) 0.003 0.014 0.024 0.025 0.141 0.103
Zo 0.163 0.291 0.606 0.566 3.142 2.676
Z5 0.163 0.291 0.608 0.568 3.157 2.693
SEm+ 0.001 0.004 0.006 0.007 0.038 0.028
CD(p 0.05) NS NS NS NS NS NS

Grain and Straw yield of Wheat
The maximum average grain yield of 4.0 tons in first season and 3.9 tons per hectare (t/ha) in
the second season was obtained with the four irrigation treatment (13) given at CRI, jointing,
flowering and dough stages of the crop (Fig. 2). Minimum yields of 2.3 t/ha in both the
seasons were obtained with no post sowing irrigation (Io). The per cent increase in grain yield
due to one (Ii), two (I2) and four irrigation levels over the no irrigation treatment was 36.2,
58.0 and 71.5 in 1999-2000, and the corresponding per cent increase in 2000-2001 was 32.0,
57.8 and 73.9, respectively. Each and every addition of either irrigation or nitrogen resulted
in a progressive and significant increase in grain yield up to I3No00 level in first and second
year of experimentation, respectively (Table 3). The minimum grain yield of 2.00 t/ha and
1.96 t/ha were obtained with IoNo in the respective seasons.
Straw yield increased significantly with addition of irrigation attaining a maximum of 6.4
t/ha with four irrigations in 1999-2000 and 6.6 t/ha in 2000-2001 (Fig. 2). Application of one
and two irrigations, resulted in a percentage increase of the straw yield by, 17.6 and 30.9 in
the first season and 17.0 and 30.4 increase in the second season, over the control (Io),
respectively.

Table 3:Interactive effects of I and N on the grain yield (kg/ha) of late sown wheat at harvest
IxN effects on grain yield
Io II I2 13 10 I1 12 13
No 2038.8 2649.9 3013.0 3301.2 1959.8 2407.8 288505 3271.7
Nso 2337.1 3199.9 3713.1 4108.7 2259.8 3011.0 3587.9 4042.1
Nloo 2637.1 3699.9 4359.7 4615.4 2535.1 3499.9 4186.9 4436.1

N within I I within N N within I I within N
SEm+ 144.3 149.52 130.49 136.2
CD(p=0.05) 298.1 302.2 268.9 275.2


Fig. 2. Straw yield increase with additional irrigation


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004













12000.0


10000.0


8000.0


6000.0


4000.0


2000.0


0.0


10
Year 1999-200(


10454.2
9876.2 -
8739.2




6180.9 6445.8
56.0


3695.3 4008.4
83.2




11 12 13


0


Irrigation


10524.


9553.1


6852.5



4601.1



2251



10
n levels


11 12
Year 2000-2001


Consumptive Use of Water (CU) by Wheat
Increasing frequency of irrigation increased the CU progressively and markedly in both the
seasons (Fig 3 and Table 4). The maximum consumptive use of 328.6 mm in 1999 2000
and 302.0 mm in 2000-2001 was attained with the four irrigation treatments, given at CRI,
jointing, flowering and dough stages of the crop growth. The minimum CU was obtained
with no post sowing irrigation, i.e., control (191.5 mm and 178.2 mm) in corresponding
seasons, respectively. The percent increase in CU values due to Ii, 12 and 13 over 10 treatment
was 21.5, 44.5, and 71.5, in 1999 2000 and 25.5, 39.8, and 69.3 in 2000 2001 seasons,
respectively. Moisture use rate of wheat increased with the increase in the number of
irrigation levels given. The increase in moisture use rate of wheat due to Ii, 12 and 13 levels
over the no irrigation treatment (lo), was in the order of 21.3%, 39.6%, and 68.5% in 2000-
2001 season, respectively.


Water Use Efficiency by Wheat
The pooled average water use efficiency (kg grain/m3 water use) of Ii (1.35) and 12 (1.38)
were higher than those of 0o (1.24) and 13 (1.27) treatments in both the seasons (Table 4).
Highest WUE for the first season crop was recorded with 11 (1.37), while it was with 12 (1.42)
in the second season (Fig 3 and Table 4). Minimum water use efficiency was recorded with lo
(1.22 and 1.26 kg grain/m3 water use) in both the respective seasons.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










0)





0
Mi
G I"
o: a,
u !
a ^
g g


I0 I 1 13 No N, Nim Zo Z5


Irrigation level


Nitrogen level


0 1999-2000
M 2000-2001
S 2
S I .E I


4 *


ligation level
Irrigation level


No N5 N10
Nitrogen level


Zinc level


Figure 3. Influence of irrigation, nitrogen and zinc on the consumptive use of water, moisture use
rate and water use efficiency by late sown wheat


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


Zinc level










Table 4:Influence of I, N and z on seasonal consumptive water use, moisture use rate and WUE
of late sown wheat

CU (mm) WUE(kg grain/m3 water) Moisture use rate (mm/day)
1999-00 2000-01 1999-2000 2000-2001 1999-2000 2000-2001
0o 191.52 178.20 1.22 1.26 1.60 1.49
11 232.67 223.66 1.37 1.33 1.94 1.86
12 276.10 249.10 1.34 1.42 2.30 2.08
13 328.39 301.66 1.22 1.31 2.74 2.51


No 253.14 234.36 1.09 1.12 2.11 1.95
N50 257.08 237.95 1.30 1.35 2.14 1.98
N100 261.28 242.16 1.46 1.52 2.18 2.02


Zo 257.11 238.15 1.27 1.32 2.14 1.98
Z5 257.23 238.16 1.30 1.34 2.14 1.98



Nutrient Nitrogen and Zinc Effects on Water Use
Application of nitrogen did not enhance the CU appreciably as in case of irrigation
application. With application of nitrogen fertilizer at the rate of 50 and 100 kg /ha, the
percent increase in CU of wheat over no nitrogen (No) application was marginal i.e. 1.56 and
3.22 in the first season and 1.53 and 3.32 in the second season respectively (Table 4).
Similarly Zinc application did not have much influence on the consumptive use of wheat.
Application of nitrogen had very little effect on the daily moisture use rate of wheat, while
zinc application had practically no effect at all, in both the cropping seasons (Table 4).
Nitrogen application increased water use efficiency of the crop progressively up to 100
kg / ha (1.46 and 1.52 kg grain/m3 water use) during both the years of experimentation. Zinc
application however, induced negligible influence in WUE of wheat in both the seasons (Fig.
3 and Table).
Nitrogen application up to 100 kg/ha did not bring any noticeable change in seasonal
consumptive use and daily moisture use rate of the crop (Table 4). Water use efficiency
increased progressively with N application and the mean maximum WUE recorded with 100
kg N/ha was 1.46 and 1.52 kg grain/m3 water use, in first and second seasons, respectively.

Moisture Extraction
The influence of irrigation and fertility (N and Z) interactive effects on the soil moisture
extraction patterns is depicted in Table 5. Maximum (58.6 % to 66.8 %) soil moisture was
extracted from within the 0- 30cm soil profile layer with the highest being under the four
irrigation regime (64.7 to 66.8 %) and lowest under the no post-sowing irrigation treatment
(58.2 to 60.1 %). This trend of declining soil moisture extraction percentages with increasing
irrigation frequency was evident at the 60-90 cm and 90-120 cm depth soil layer profiles also.
The ranges were 9.6 11.7 % and 6.4 8.0 % in the 60-90 cm and 90-120 cm soil profiles,
respectively.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004














Application of nitrogen induced the plants to extract proportionately greater amount of
soil moisture from 60-120 cm layers as compared to the non- fertilized ones. Zinc application
on the other hand, caused negligible increase in moisture extraction pattern at different soil
profiles that followed the similar effect as in the case of irrigation effects.
Table 5: Influence of irrigation, nitrogen and zinc on soil moisture
extraction pattern (o%)
1999-2000 2000-2001
Seasonal moisture extracton patern Seasonal moisture extracton patem
90-120
Treatment 0-30 cm 30-60 cm 60-90 cm 90-120 cm 0-30 cm 30-60 cm 60-90 cm cm
Irrigation
lo 59.35 21.90 11.65 7.10 58.10 21.62 12.53 7.75
I1 61.50 20.98 11.12 6.40 60.15 21.00 12.05 6.80
12 64.32 20.05 10.00 5.63 61.62 20.25 11.65 6.48
13 65.80 19.30 9.58 5.32 64.68 19.72 10.13 5.47
Nitrogen
No 63.56 20.70 10.58 5.16 61.43 20.54 11.78 6.26
Ns5 62.94 20.53 10.60 5.94 61.13 20.63 11.60 6.65
NIoo 61.73 20.45 10.59 7.24 60.86 20.78 11.40 6.96
Zinc
Zo 62.69 20.54 10.56 6.21 61.10 20.62 11.56 6.73
Z5 62.79 20.58 10.62 6.02 61.18 20.68 11.63 6.53

Production Function for Wheat
Water yield relationships depicted as production functions are considered as useful tools in
the management of water and nitrogen application for the purposes of optimizing crop
productivity. Crop production functions that relate water-yield relationships, are
mathematical equations relating crop response in terms ofbiomass or grain yield with water
availability and it's uptake by the crop.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












1.5

E
c.0
2 1.0


0.5 +
10


Evapo-transpiration (cm)


4.0


3.0


2.0


60 70 80 90


100 110


Total water use up to anthesis (mm)


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


y = -0.0025x2 + 0.1288x 0.288. R2=0.108
*



**
$

2" '+


120
















8000







Ia
y=53;.1*x+726
,










00020.8
*. .*





Seasonal water uptake (mm)




Water use efficiency is generally considered as a conservative term and is expressed as
the ratio of DMP or Y to water supply or water use, expressed in terms of evapotranspiration
Seasonal water uptake (mm)




(ET) or transpiration (Tr) on daily or seasonal basis (Sinclair et al, 1984). Water use
efficiency generally ranged from 1.22 to 1.42 kg/m3 (Table 4), with the highest WUE
observed at one and two irrigation levels of the first and second season crop, respectively.
The values of WUE were higher than those reported from the Mediterranean region by Zhang
and Oweis (1999) that ranged from 1.08 to 1.19 kg/m3 and close to those (1.23-1.46 kg/m3) of
the Loess plateau in China (Kang et al., 2002).
Regression analysis indicated a quadratic relationship between WUE and seasonal evapo-
transpiration (Fig. 5), which was reflected in a poor correlation of 11%. WUE reached its
maximum value at an evapo-transpiration of approximately 260-270 mm then started a
decrease with evapo-transpiration. Maximum WUE did not correspond to the highest grain
yield (Fig 2 and 3). When ET is relatively low, water availability is the limiting factor for
grain yield and an increase in ET results in significant increase in both grain yield and WUE.
However, the rate of increase in both grain yield and WUE starts to decrease as ET further
increases. Once WUE reaches its maximum value, an increase in total crop water use could
still lead to a marginal increase in grain yield. Thus, WUE would decrease (Figure 5). This
was in agreement with the findings of Singh (1977) and Kang et al. (2002). This means that
relatively high crop yield and WUE can be maintained while substantially reducing irrigation
volume under limited-irrigation management (Singh et al. 1991; Zhang and Oweis, 1999;
Kang et al.2002).
When evaluating dry matter production, expansive growth deserves special attention, since it
is the means for developing leaf area for intercepting light and carrying out photosynthesis.
The sensitivity of expansive growth to small water deficits is marked by reduction in leaf area
(Hsiao et al., 1976b; Vaux and Pruitt, 1983). Maximum LAI for wheat is generally noticed at
anthesis. LAI at flowering is mainly used for forecasting wheat yields, with the prime


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










assumption that there is no stress in the subsequent stages of crop growth. The LAI estimates
based on water use (Fig 8) accounted for 75% of the variations only.
It can be concluded that wheat grown under lower levels of irrigation water results in
lower consumptive use of water (Fig 3 and Table 4). This further influences the production of
less leaf area indices (Table 3 and Fig 6), that ultimately causes the decline in the total above
ground biomass and grain yield production (Fig 2).
Final biomass and grain yield of wheat depends upon the sensitivity of various stages
towards moisture availability that scheduling of irrigation is carried out. Dated production
functions take care of the crop stage sensitivity and thus gives better predictability for
biomass and yield estimates (Kalra, 1986; Singh et al., 1987). The highest rate of biomass
gains of 53.1 kg/ha-mm was obtained over the 60-90 day period, a period that falls within the
maximum growth phase of wheat, followed by 28.3 and 6.7 kg/ha-mm during the 90-120 and
0-60 DAS periods (Fig 7). This is in agreement with the findings for semi arid regions of
Hisar in India (Singh et al., 1987) and China (Zhang et al., 1999). Therefore, scheduling of
water application ought to consider providing less quantities of water during the 0-60 DAS
period as compared to the 90-120 and 60-90 DAS periods, respectively. This should be
aimed at providing just sufficient amounts of water and nitrogen for the necessary
developmental processes to take place. Further research aimed at optimizing growth and
production of wheat through the application of minimum quantities of water and nitrogen, at
various stages of wheat growth, is therefore recommended.


References
Dastane, N.G., Singh, M. Hukkeri, S.B. and Vasudevan, V.k. 1970. Review of work done on water
requirement of crops in India. New Bharat Prakashan, Poona, India.
Davis, G.J. 1994. Managing plant nutrients for optimum water use efficiency. Advances in Agronomy
53 : 85-110.
English, M., Raja, S.N. (1997). Perspectives on deficit irrigation Agricultural Water Management, 32
(1): 1-14.
Hsiao, T.C., Feres, E., Acevedo, E. and Henderson, D.W. 1976b. Water stress and dynamics of growth
and yield of crop plants. Ecological Studies, 19: 281-305.
Jackson, M. L. 1958. Soil Chemical analysis. Prentice Hall of India. (Pvt.) Ltd. New Delhi 1973, India.
Kalra, N. 1986. Evakuation of soil water status, plant growth and canopy environment in relation to
variable water supply to wheat. P.hD. Theses. P.G. School, I.A.R.I., New Delhi: 103pp.
Kang, S.Z. and Dang, Y.H. 1987. Research on crop water production functions and optimal irrigation
scheduling. Water Resource Hydraulic Eng. 1: 1-12.
Khang, S., Zhang, L., Liang, Y., Hu, X., Cai, H. and Gu, B. 2002. Effects of limited irrigation on yield
and water use efficiency of winter wheat in the Loess plateau of C liiu Ilric. Water Manage.
55 : 203-216.
Novoa, R and Loomis, S.S. 1981. Nitrogen in plant production. Plant and Soil. 58 (1) : 177-204.
Sinclair, T. R., Tanner, C. B. and Bennet, J. M. 1984. Water use efficiency in crop production.
Bioscience 34 : 46- 40.
Singh N.T., Vig A.C., Rachhpal Singh, Chaudhary M. R., Singh R., (1977). Influence of different
levels of irrigation and nitrogen on yield and nutrient uptake by wheat, Agronomy Journal, 71
(3) : 401-404.
Singh, A.K. 1991. Response of irrigated wheat (Triticum aestivum) to nitrogen and phosphorus in
farmers' fields in Ganga diara of Bihar, Indian J Agron., 41 (1) 157-159.
Singh, P., Wolkewitz, H. and Kumar, R. 1987. Comparative performance of different crop production
functions for wheat (Triticum aestivum). I,, ,,r,. ', Sci. 8 (4) : 273-290.
Stewart, J. I., Cuerca, R. H., Prutt, W.O., Hagon, R.M. and Tosso, J. 1977a. Determination and
utilizationof water production functions for principal California crops, W-67 Calif Contri.
Proj. Rep. University of California, Davis.
Tandon H.L.S. (Ed.) 1998. Methods of analysis of soils, plants, waters and fertilizers. Fertilizer
Development and Consultations Organization, New Delhi, India. Pp. 144+vi.
Vaux, H.J. and Pruitt, W.O. 1983. Crop water production functions. In: D. Hillel (Editor), Adv. in
I, ,;,'a,. 2. Academic Press, New York, pp 257-272.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Watson, D.J. 1952. Adv. Agron. 4: 101-145.
Zhang H., Wang X., You M. and Liu C., (1999). Water-yield relations and water-use efficiency of
winter wheat in the North China Plain, I, '..,, Science, 19 (1) : 37-45.
Zhang H.P, and Oweis T., (1999). Water-yield relations and water-use efficiency of winter wheat in the
North China Plain, Agricultural Water Management, 38 (3) : 195-211.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Agronomic and Economic Evaluation of Break
Crops and Management Practices on Grain
Yield of Wheat at Shambo, Western Oromiya,
Ethiopia

Tolera Abera and Mathewos Belissa
Oromiya Agricultural Research Institute, Bako Agricultural Research Center
P.O. Box 03, Email: akthirpha@yahoo.com Bako, Western Oromiya,Ethiopia

Abstract-Sustainable production of wheat (Triticum aestivum) may be limited by a
number of crop management practices, including crop rotation and cultural practices.
A field experiment was conducted for three years at Shambo, Ethiopia, to evaluate
the agronomic and economic effects of break crops and management practices on the
grain yield of wheat. After a field pea break crop wheat grain yield was 32% higher
than after a barley crop. Management practices gave significant effects on the mean
grain yield of wheat. Wheat performed better after the field pea break crop with both
farmer's management practices and the recommended practices. Both local and
improved varieties gave greater yield with intensive management and fertilizer
application. The highest economic benefits came from the use of field pea break crop
with improved management practices and fertilizer application and the extension
program under way in the area should consider this recommendation for sustainable
production of wheat.

Introduction
Wheat is one of the major cereal crops produced in the Ethiopian highlands (1,500 to 3,000
m.a.s.l) (Hailu et al., 1991), and in the highlands of Shambo, wheat ranks fourth among the
cultivated crops in terms of production (Asfaw et al., 1997). Both biotic and abiotic factors
limit agricultural productivity in the country. Human degradation on the natural resource base
is generally very swift, but interventions to amend the decline are very slow. Lal (1989)
indicated that conservation tillage and crop rotation are considered the major means of
sustaining agricultural productivity at the global scale. Soil fertility can, in many cases, be
maintained through the combined use of suitable legumes in a suitable crop rotation and
modem artificial fertilizers capable of correcting nutrient deficiencies (Whyte et al., 1969).
Practical cropping systems options with appropriate management practices for wheat in
western parts of Ethiopia have not been clearly identified. However, making use of their
indigenous knowledge, most farmers practice crop rotation based on short-term agronomic
benefits break crops, and most studies in the past focused on the short-term agronomic
benefits of break crops for wheat production (Hailu et al., 1989).
The application of chemical fertilizer has been recommended for wheat production in
eastern and southern Africa (ESA) without considering the sustainability of continuous
application (Tanner, 1997). Demonstration and extension of fertilizer and improved seeds
along with all the recommended practices were started in Ethiopia with the introduction of the
Minimum Package Program (MPP) (1967 78). In this Program, based on multi-locational
trials and demonstration results, "blanket fertilizer recommendations" were made for major
cereal crops in the country. The "blanket" fertilizer rate recommendations of EPID during the
1970s are still used for wheat production (Asnakew et al., 1991), and there are no reports
available on the long-term effects of these recommended fertilizer rates on wheat production
in the Shambo highlands. However, increasing productivity and system sustainability through


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










crop rotation has been suggested to be a sound management options for small-scale farmers in
the Ethiopian highlands. Hailu et al. (1989) reported that faba bean as a break crop increased
wheat grain yield by 1,100 kg ha' or 69 % cf. the yield of second-year continuously cropped
wheat, while the study of Asefa et al. (1992) indicated that a faba bean crop increased the
yield of the following wheat crop by 982 kg ha', or 44 %, compared to that of continuously
cropped wheat. However, studies have not been conducted in the highlands of Shambo in
relation to these agronomic interventions. Furthermore, the agronomic results of "multi-
optional and local input inclusive trials" are important to obtain useful information on break
crops for wheat production in the area. Therefore, the objective of this study was to evaluate
the effects of pulse and cereal break crops along with management practices on wheat
productivity in the Shambo highlands.

Materials and Methods
The experiment was conducted during the 1997, 1998 and 1999 cropping seasons at Shambo:
934'N latitude and 37006'E longitude at an altitude of 2400 meters above sea level. Mean
annual rainfall is 1,695 mm (NMSA, 2003). It has a cool humid climate with the mean
minimum, mean maximum, and average air temperatures of 8.15C, 15.720C, and 11.940C,
respectively. The soils are nitisols.
The experiment was laid out as split plot in a randomized complete block design with
precursor crops as main plots and management practices as sub-plots. The precursor crops
were field pea (Pisum sativum) variety (G-22763-2c) and barley (Hordeum vulgar) variety
(Shege) and were sown in the 1997 cropping season. Wheat was sown on these plots in six
management sub-treatments in the 1998 and 1999 seasons The wheat management practices
included wheat variety, cultural practices and fertilizer level, arranged as follows:
- Farmer's variety and farmer's traditional practices without fertilizer (FVFP-FE)
- Improved variety and farmer's traditional practices without fertilizer (IVFP-FE)
- Farmer's variety with improved practices without chemical fertilizer (FVIP-FE)
- Improved variety with improved agronomic practices without chemical fertilizer (IVIP-FE)
- Farmer's variety with all improved agronomic practices with chemical fertilizer (FVIP + FE)
- Improved variety with all improved agronomic practices with chemical fertilize (IVIP + FE).
The wheat varieties used were the local variety "Molgo" awnlesss wheat) and HAR-604
(Galama), an improved variety. The improved cultural practices were the recommendation
practices as for wheat. For the improved cultural practices, the herbicide 2,4-D was applied 30
to 45 days after planting to control weeds while in plots with the farmer's cultural practices,
hand weeding was done once at 25 days after sowing. The recommended fertilizer rates of
100 kg ha' each for DAP and Urea were applied at planting n the plots receiving fertilizers.
The plot size was 10 m x 10 m. The seed rates were 150 kg ha' for field pea, barley and
the improved wheat variety, whereas the normal farmer practice of 160 kg ha' was used for
the local variety. Sowing dates were between mid June and early July.
The data were analyzed using MSTAT-C Computer Software Program. Selected
orthogonal contrasts were used to separate the effects of the two levels of the three factors:
management practices, fertilizer effects, and variety.

Economic evaluation was conducted using the partial budget, values to cost ratio (VCR)
and marginal analyses methods. Wheat grain yield was valued at the average open market
price over the last five years of Ethiopian Bihr (EB) 143.00/100 kg. Plot grain yields were
reduced by 10 % to reflect actual production environments (CIMMYT, 1988). The wheat seed
cost used was EB 2.40/kg for the improved variety and EB 1.43/kg for the local variety. Urea
and DAP were valued at the official prices ofEB 192.00 and 256/100 kg respectively. The


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










cost utilized for labour for weeding was EB 3.50/day. The average rental price of a sprayer
was EB 10.00 ha', and the cost of 2,4-D herbicide was EB 0.42/liter.


Results and Discussion

The yields of the precursor crops sown in the 1997 cropping season are shown in Table 1.


Table 1. Mean grain yield of break crops, field pea and barley in 1997.
Crop Grain yield (kg ha-')*
Field pea 556
Barley 1549
* Statistically significant t-value at P=0.01


With all management practices, the grain yield of wheat was significantly greater (P<0.05)
following field peas than following barely in both cropping seasons (Tables 2 and 3). The
mean grain yield of wheat was increased by 39% and 25% following field pea compared to
barley in the 1998 and 1999 cropping seasons respectively, and on average by 32%. This
benefit of the field pea break crop has also been shown by Tanner et al. (1991), who reported
that wheat after barley break crop was not significantly different from continuous wheat
production, and Tilahun et al. (2000). Tanner et al. (1999) showed that wheat grain yield was
consistently higher in rotation with dicotyledonous crops than with cereal crops, exhibiting
grain yield increments ranging from 22 to 54 %. In addition, in their studies, wheat grain yield
was higher in rotation with faba bean than with rapeseed, with grain yield increases ranging
from 8 to 31 %. This is likely due to the fixing of free atmospheric nitrogen by Rhizobium
bacteria in association with

Table 2. Effects of break crops and management practices on grain yield of wheat (kg
ha-1) at Shambo in 1998.
Treatment Management practices Mean
Break crop FVFP IVFP FVIP IVIP FVFP IVIP
-FE -FE -FE -FE +FE +FE
Barley 1093 1563 1300 1400 1590 1763 1451
Field pea 1510 2250 1650 2390 1970 2373 2024
Mean 1302 1906 1475 1895 1780 2068 1718
Yield change (%) 38 44 27 71 24 35 39
(Pea/barley)
Break crop Mgmt practices Break crop x Mgmt practices
LSD (5%) 206 480 NS
CV % 8.25 22.94

Table 3. Effects of break crops and management practices on grain yield of wheat (kg ha-1) at
Shambo in 1999.
Treatment Management practices Mean
Break crop FVFP IVFP FVIP IVIP FVFP IVIP
-FE -FE -FE -FE +FE +FE
Barley 1087 1800 1400 1210 1767 1947 1535
Field pea 1567 2033 1633 2133 1933 2200 1917
Mean 1327 1917 1517 1672 1850 2073 1726
Yield change (%) 44 13 17 76 9 13 25
(Pea/barley) _


LSD (5%)
CV %


Break crop
155
6.26


Mgmt practices
NS
25.40


Break crop x Mgmt practices
NS


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Table 4. Effects of break crops and management practices on mean grain yield of wheat (kg ha-1)
at Shambo (combined over two years), 1998-1999.
Treatment Management practices Mean
Break crops FVFP IVFP FVIP IVIP FVFP IVIP
-FE -FE -FE -FE +FE +FE
Barley 1090 1681 1350 1305 1678 1855 1493
Field pea 1538 2142 1642 2262 1952 2287 1970
Mean 1314 1911 1496 1783 1815 2071
Yield change (%) 41 27 22 73 16 24 32


Break crop Mgmt practices Break crop x Mgmt practices
LSD (5%) 83.02 345.7 NS
CV % 7.33 24.19

the legume break crops, as the amount of nitrogen left in the soil by a crop may influence the
yield of the crop that follows it (Martin et al., 1976).
The yield increment of local variety was lesser in field pea break as compared to barley
in two consecutive years as the management practices increased. This might be due to the
more nitrogen left in the soil from legume break crop. Tanner et al. (1991) reported that for
most of the characteristics, the effect of faba bean break crop was similar to that of N-
fertilizer. The mean grain yield increment ranged from 24 of 71 % was observed from the
FVFP+FE and IVIP-FE following field pea as compared to barely in 1998 (Table 2). Mean
grain yield advantage of 9 to 76 % was recorded from FVFP+FE and IVIP-FE following field
pea as compared to barely in 1998 (Table 3). The result argues that with improved agronomic
managements both fields gave similar yields.
Management practices had significant (P<0.05) effects for grain yield in 1998 and when
combined over the two years, but differences were not significant in 1999 (Tables 2, 3 and 4).
There was no significant interaction bewteen previous crop and management practices on
grain yield of wheat in either year, nor in the combined data (Tables 2, 3 and 4).
Orthogonal contrasts of all three factors (variety, cultural practices and fertilizer use)
showed highly significant mean grain yield difference (P< 0.01) (Table 5). The improved
variety gave a mean grain yield increases of 191 kg ha', the improved management practices
a yield advantage of 78 kg ha', fertilizer application a mean wheat grain yield increase of 115
kg ha'. Thus improved agronomic practices are very advantageous for wheat production in
the Shambo highlands.

Table 5. Statistical significance of orthogonal comparisons in the wheat management trial at
Shambo, 1998-1999.


Contrasts Mean grain yield
Farmers vs. improved management practices **
Local vs. improved variety **
With fertilizer vs. without fertilizer application **
** Significant at 1% level of probability.
a See materials and methods for complete description of orthogonal contrasts used

Economic analysis of the management practices indicated that the highest net benefit of EB
1554.23 ha' and a cost:benefit ratio of EB 1.26 profit per unit of investment were obtained
from the treatment with the improved variety, improved management practices and fertilizer
application (IVIP+FE)(Table 6). The second highest net benefit ofEB 1537.83 ha and a
cost:benefit ratio of EB 3.03 profit per unit investment, was achieved with the farmers'
variety, improved agronomic management practices without fertilizer application (FVIP-FE).
However, the marginal rate of return of IVIP+FE over FVIP-FE was only 2.2%, far too low to
warrant the recommendation of this treatment. The cost:benefit ratios of the other


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










management practices were EB 1.29, 1.19, 1.30 and 1.08 profit per unit investment, from
IVFP-FE, IVIP-FE, FVIP+FE and FVFP-FE respectively.

Table 6. Partial budget and marginal rate of return (MRR) analyses for the effects of
management practices on the grain yield of wheat at Shambo, 1998-1999.
Item Management practices
FVIP FVFP FVIP IVIP IVFP IVIP
-FE -FE +FE -FE -FE +FE
Average yield (kg ha') of wheat 1496 1314 1815 1783 1911 2071
Adjusted yield (kg ha') Wheat 1346 1183 1634 1605 1720 1864
Gross field benefit of Wheat grain 1925 1691 2336 2294 2459 2665
Average straw yield (kg ha-') 2400 1947 2850 2003 1870 2457
Gross field benefit of wheat straw 120 97 143 100 94 123
Total field benefit (EB ha') 2045 1788 2478 2395 2553 2788
Costs that vary (EB ha 1)
Wheat seed cost (EB ha' 215 215 215 360 360 360
Urea 192 192
DAP 256 256
Rental price of sprayer (EB ha') 10 10 10 10
Herbicide cost (EB ha ') 42 42 42 42
Fertilizer application cost (EB ha ') 11 10.5
Total labour cost (EB ha') 241 645 350 683 756 364
Total costs that vary (EB ha-') 508 860 1075 1095 1117 1234
Net benefit 1538 929D 1403D 1300D 1436D 1554
Value to cost ratio 3.03 1.08 1.30 1.19 1.29 1.26
Marginal rate of return (MRR) ____2.20%
Note: D= dominated treatment, Urea= EB 1.92/kg, DAP= EB 2.56/kg, Labour cost =EB
3.5/day, 2,4-D= EB 0.42/litter, Grain price= EB 1.37/kg, Local seed = EB 1.43/kg, Improved
seed= EB 2.40/kg, Straw cost= EB 0.05/kg, Rental price of sprayer= EB 10.00 ha', Fertilizer
application cost= EB 10.50 ha', Yield was down adjusted with 10 % coefficient

It is noteworthy that the farmers' common practice (FVFP-FE) was dominated in the partial
budget analysis, because the best treatment (FVIP-FE) gave higher net benefits with lower
costs that vary. In the current study the low cost of seed of the farmers' variety resulted in this
variety dominating the treatments with the improved variety. However, it should be noted that
the full cost of buying new seed of the improved variety was used, whereas this can probably
be discounted as usually the farmer will use this seed for several years. The high cost of
commercial fertilizer and improved seed made the improved agronomic practices for wheat
production costly, and reduced prices of improved seed and commercial fertilizer will benefit
wheat producers of the area. However, with the average current prices of inputs, use of
farmers' variety with improved technology without fertilizer or the improved variety with
improved practices and fertilizer application were economically viable and profitable. Both
the local and improved varieties gave better grain yield under intensive management practices
with fertilizer application (Table 4). The least profitable management option of wheat is
farmer's variety with farmer's management practices and without fertilizer application.
However, the escalating price of chemical fertilizer and improved seed, together with the
reduced market price of grain drastically decrease the profitability of wheat production with
improved packages.

Conclusion

A previous field pea crop significantly increased the grain yield of wheat compared to a
previous barley crop. Both the local variety and the improved variety gave the greatest yields
under improved agronomic management with chemical fertilizer application when following


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










after a field pea break crop. The economic analysis indicates that optimum market prices
should be determined by the policy makers for producers of wheat in order to get the potential
benefit of the recommended package. Alternative technologies should be developed on the
integration of inorganic and organic fertilizer use for profitable wheat production. Long term
investigation on the economic benefit of rotation effects with intensive management practices
and the extension of the results to the farmers is essential for sustainable wheat production in
the Shambo highlands.

Acknowledgment-The authors thank Oromiya Agricultural Research Institute for funding
the project. We are most grateful to our senior researchers Mr. Abdissa Gemeda and Mr.
Abubeker Mussa for their priceless contributions to us in executing this experiment. We are
also grateful to Mr. Asefa Mijena, Tesema Tesso and Yosef kenea for their assistance in
carrying out the experiment and efficiently collecting the data. Bako Research Center
Management is also thanked for facilitating the execution of the field trial.


References
Asefa Taa, Tanner, D G. and Amanuel Gorfu. 1992. The effects of tillage practices on bread wheat in
three different cropping sequences in Ethiopia. pp. 376-386. In: Tanner, D. G. and Mwangi,
W. (eds.). Seventh Regional Wheat Workshop for Eastern, Central and Southern Africa.
CIMMYT, Nakuru, Kenya.
Asfaw Negassa, Abdissa Gemeda, Tesfaye Kumsa and Gemechu Gedeno. 1997. Agro ecological and
Socioeconomical Circumstances of farmers in East Wallagga Zone of Oromiya Region,
Ethiopia. Research Report No. 32. Institute of Agricultural Research, Addis Ababa, Ethiopia.
Asnakew Woldeab, Tekaligne Mamo, Mengesha Bekele and Tefera Ajema. 1991. Soil fertility
management studies on wheat in Ethiopia. pp.137-172. In: Hailu Gebre-Mariam, Tanner, D.G.
and Mengistu Hulluka (eds.). Wheat Research in Ethiopia: A Historical Perspective. Addis
Ababa, IAR/CIMMYT.
CIMMYT. 1998. From Agronomic Data to Farmer Recommendations. An Economics Training
Manual. Completely Revised Edition. CIMMYT, Mexico, D.F., Mexico. 79 pp
Hailu Gebre, Amsal Tarekegne and Endale Asmare. 1989. Beneficial break crops for wheat production.
Ethiopian Journal of Agricultural Sciences Vol. 11: 15-24.
Hailu Gebre-Mariam, Tanner, D.G. and Mengistu Hulluka. 1991 Wheat Research in Ethiopia: A
Historical Perspective. Addis Ababa, IAR/CIMMYT.
Martin, J. H., Leonard, W. H., and Stamp, D. L. 1976. Principles of Field Crop Production (3rd ed.).
Collier Macmillan Publishing. London, UK.
Lal, R. 1989. Conservation tillage for sustainable agriculture: Tropics versus temperate environment.
Advances in Agronomy 42:85-197.
NMSA (National Meteorological Service Agency). 2003. Meteorological data of Shambo area for
1969-2002. NMSA, Addis Ababa, Ethiopia.
Tanner, D. G., Amanuel Gorfu and Kassahun Zewdie. 1991. Wheat agronomy research in Ethiopia. pp.
95-135. In: Hailu Gebre-Mariam, Tanner, D.G. and Mengistu Hulluka (eds.). Wheat Research
in Ethiopia: A Historical Perspective. Addis Ababa: IAR/CIMMYT.
Tanner, D.G. 1997. Sustainable wheat production: global perspectives and local initiatives. pp. 10-41
In: Woldeyesus Sinebo (ed.). Crop Management Research for Sustainable Production: Status
and Potentials. Proceedings of the Second Annual Conference of the Agronomy and Crop
Physiology Society of Ethiopia. ACPSE, Addis Ababa, Ethiopia.
Tanner, D.G., Verkuij, H., Asefa Taa and Regassa Ensermu. 1999. An agronomic and economic
analysis of long-term wheat based crop rotation trial in Ethiopia. pp. 213-248. In: The Tenth
Regional Wheat Workshop for Eastern, Centeral and Southern Africa. Addis Ababa, Ethiopia:
CIMMYT.
Tilahun Geleto, Kedir Nefo and Feyissa Tadesse. 2000. Crop rotation effects on grain yield and yield
components of bread wheat in the Bale highlands of southeastern Ethiopia. pp. 316-324. In:
The Eleventh Regional Wheat Workshop for Eastern, Central and Southern Africa. Addis
Ababa, Ethiopia: CIMMYT.
Whyte, R.O., Neisser, G. N. and Trumble, H.C. 1969. Legumes in Agriculture. Food and Agricultural
Organization of the United Nations, Rome, Italy.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Response of Bread Wheat to Nitrogen and
Phosphorous Fertilizers at Different Agro-
ecologies of Northwestern Ethiopia


Minale Liben, Alemayehu Assefa, Tilahun Tadesse and Abreham Mariye
Adet Agricultural Research Center, P. O. Box 08, Bahir Dar, Ethiopia

Abstract-Wheat is one of the major cereal crops grown in northwestern Ethiopia,
though its productivity in farmers' fields is very low. In northwestern Ethiopia, N and
P deficiencies are among the major biophysical constraints. Wheat fertilizer response
trials were conducted at different agro-ecologies on farmers' field during 1999, 2000
and 2001. The objective of the trial was to determine economically optimum rates of
N and P fertilizer for the high-yielding semi-dwarf bread wheat cultivars HAR 1868
and HAR 604 at Farta and Laie-Gaient areas, respectively. Four rates of N (0, 46, 92
& 138 kg/ha for Farta where as 0, 41, 82 & 123 kg/ha for Laie-Gaient) and four rates
of P205 (0, 23, 46 & 69 kg/ha for both localities) were laid out in a factorial
arrangement in RCB design with three replications. The results indicated highly
significant differences on grain yield, plant height, tiller and spike density and
thousand-kernel weight amongst the fertilizer rates in the two locations. There was a
linear increase in grain yield of bread wheat as the rates of N and P increased. The
increase in grain yield is significant for nitrogen, P and N by P interaction. The
highest grain yield, 3025 kg/ha at Farta and 2610 kg/ha at Laie-Gaient were obtained
at the highest fertilizer rates of 138/69 kg N/ P205 ha-' and 123/69 kg N/ P205 ha-1,
respectively. Fertilizer rates of 138/46 kg N/P205 ha-1 at Farta and 123/46 kg N/ P205
ha-' at Laie-Gaient were found economically feasible with net benefit (NB) of
Ethiopian Birr 3538 and 3062, respectively.



Introduction
Wheat ranks fifth in production and area and fourth in mean-yield among the principal cereal
crops grown in the country. The national mean yield is low ranging from about 1.1 t/ha for
peasant farmers to about 2 t/ha for state farms (Hailu et al., 1991). Soil degradation is a
serious problem in many parts of the country, largely as a result of mismanagement of natural
resources. Erosion and farmers' practice of continuous cultivation without fallow aggravate
the soil fertility problem. Northwestern Ethiopia is accompanied with diversified agro
ecologies. Poor soil fertility particularly N and P deficiencies are among the major
biophysical constraints in those agro ecologies (Hailu et al. 1991, UNDP 1996, Aleligne et
al. 1992, ANRS BOPED 2000, Aleligne & Regassa 1992). Previous experiments conducted at
the different agro ecologies of the region indicated variations in yield responses of the wheat
crop to fertilizer application. Therefore, this wheat fertilizer response trial was conducted at
the two agro ecologically different localities on farmers' field during 1999, 2000 and 2001.
The objective was to determine economically optimum rates of N and P fertilizer for the high-
yielding semi-dwarf bread wheat cultivars HAR 1868 and HAR 604 at Farta and Laie-Gaient
areas, respectively.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












Materials and Methods
The experiment was carried out on luvisols at Farta and Laie-Gaient region on farmers' fields
for three consecutive years (1999-2001) on a total of five sites at Farta and seven sites at Laie-
Gaient. Laie-Gaient and Farta at an altitude of 2860 and 2630 m.a.s.l., respectively are
located on the same zone (south Gondar) of northwestern Ethiopia but represent different agro
ecologies. Laie-Gaient is characterized by erratic rainfall, short rainy season (late onset and
early cease) and low temperature compared to Farta area. The soil fertility status of Farta area
is total N 0.08%, available P 3.70%, OC 3.20, C/N 40 and pH of the soil 5.17.
The experiment consisted of 16 factorial combinations of four N rates 0,46,92 and 138
kg/ha for Farta, 0,41,82 and 123 kg/ha for Laie-Gaient and four P205 rates (0, 23, 46 & 69
kg/ha) at both sites. The design was a complete factorial arrangement within an RCB with
three replications. The improved varieties HAR-1868 (shina) at Farta and HAR-604 (Galema)
at Laie-Gaient were used. Seeds were broadcasted at the recommended seed rate of 175 kg/ha.
DAP, urea and TSP were the sources of N and P205. All P and half of the N were applied at
sowing, and the remaining N was top dressed at early to mid-tillering stage of the crop. The
gross and net plot sizes were 20m2 and 12m2, respectively. Data were collected on grain yield,
tiller and spike density at maturity, plant height and thousand-kernel weight. All data were
subjected to analysis of variance (ANOVA) using the MSTATC microcomputer software.
The mean grain yield data over sites for each location was adjusted down by 10% and
subjected to partial budget and sensitivity analysis (CIMMYT, 1988). Total costs that varied
(fertilizer cost) for each treatments was calculated and treatments were ranked in order of
ascending total variable cost (TVC) and dominance analysis was used to eliminate those
treatments costing more but producing a lower net benefit than the next lowest cost treatment.
The marginal rate of return (MRR) was calculated for each non-dominated treatment and a
minimum acceptable MRR of 100% was assumed. Sensitivity analysis was made through the
assumption that cost of fertilizer and price grain increased by 10%, respectively.

Results and Discussion
Analysis on mean grain yield of the individual sites indicated significant responses for N
application in all sites. At Farta, all sites except one showed significant response to P
application where as at Laie-Gaient only one site showed significant responses to P (Table 1).
Fertilizer application increased grain yield ranging from 1554 to 2602 kgha1 at Farta and
1208 to 2447 kgha-' at Laie-Gaient compared to the unfertilized control.
Results on combined analysis indicated significant response for N application in all traits
except thousand kernel weight at Laie-Gaient. The response for P application was significant
on grain yield, plant height and thousand kernel weight at Farta. At Laie-Gaient all traits
showed significant response except thousand kernel weight. Most of the traits showed a
significant responses to NxP interaction (Table 2). Generally there was linear increase in all
the parameters as the N and P rates increased. This is in line with previous findings that at
most sites of northwestern Ethiopia, wheat grain yield responds positively to increasing
fertilizer rates (Minale et al. 1999; Ammanuel et al. 1990). The responses were relatively
larger for N than P in all parameter considered. Biologically the highest grain yield 3052
kgha' at Farta and 2610 kgha' at Laie-Gaient were obtained at the highest fertilizer rates in
both of the locations (Table 3 & 4). An increase in grain yield, 175.70 and 106.50%, over the
control was recorded at Farta and Laie-Gaient areas, respectively.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004



















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Table 3: Effect of nitrogen (N) and phosphorus (P205) on the grain yield (kg/ha) of bread wheat (Shina variety)
at Farta area
N levels (kg/ha) P205 levels (kg/ha) Mean
0 23 46 69
0 1107 1429 1570 1802 1477
46 1535 1832 2115 1990 1868
92 2033 2359 2696 2426 2379

138 2116 2833 3025 3052 2757
Mean 1698 2113 2352 2318


C.V(%)


24.8


N P
LSD (5%) 190 190


NxP
380


lable 4: Efiect o1 N anda on the grain yield (Kg/na) o1 reaa wneat (ialema variety)
P205 rates kg/ha Mean
N rates (kg/ha) 0 23 46 69
0 1264 1103 1280 1355 1251
41 1630 1413 1754 1605 1601
82 1817 2206 2237 2297 2139
123 1890 2457 2599 2610 2389
Mean 1650 1795 1967 1967


31.2
N P
174.8 174.8


at Laie-Gaient area


NxP
349.6


The economic analysis indicated 138/46 kg N/P205 ha was more profitable with net benefit (NB) of birr
3538.4 and an acceptable marginal rate of return (MRR) of 171.9% at Farta area (Table 5). The NB
increased by birr 1958.6 over the unfertilized one through the application of 138/46 kg N/P205 ha'. The
sensitivity analysis revealed the same recommendation as to the current situations.

Table 5: Results of the economic analysis of N and P205 fertilizers rate on grain yield of bread wheat at Farta
area
At current cost and price Scenario (cost of fertilizer & price of grain
increased and decreased, respectively by
10%)
N/P205 TVC NB MRR TVC NB MRR
(kgha-1) (Eth. birr) (Eth. birr) (%o) (Eth. birr) (Eth. birr) (%)
0/0 0 1579.8 0 1421.8
0/23 138.8 1900.5 231.0 152.7 1682.7 170.8
46/0 192.7 1998.7 182.4 211.9 1760.3 131.1
46/23 293.8 2321.5 319.2 323.2 2030.6 243.0
92/0 385.3 2516.0 212.5 423.9 2187.4 155.7
46/46 395.0 2624.5 1128.4 434.4 2283.0 905.3
92/23 486.5 2881.6 280.9 535.1 2496.1 211.6
92/46 587.6 3261.2 375.3 646.4 2817.5 288.9
138/23 679.1 3364.5 112.9 747.1 2892.2 74.2
138/46 780.3 3538.4 172.0 858.3 3028.5 122.5


Note: Cost of DAP = Birr 2.77/kg
Cost of Urea = Birr 1.92/kg
Price of wheat grain = Birr 1.58/kg


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


C.V(%)

LSD (s%)


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The highest NB of birr 3213.2 with acceptable MRR (122.51%) was obtained at fertilizer rates of 138/46 kg
N/P205 ha-'. At Laie-Gaient, 123/46 kg N/P205 ha was more profitable with a NB of birr 3061.7 and MRR
117.5% (Table 6). The sensitivity analysis showed 123/46 kg N/P205 ha1 gave the highest NB, however, the
MRR is below the acceptable level. Therefore, with the assumption that price of grain and fertilizers
decreased and increased, respectively by 10%, fertilizer rate of 82/23 kg N/P205 ha1' will be the optimum
rate to be recommended.

Table 6 Results of the economic analysis of N and P205 fertilizers rate on grain yield of bread wheat at Laie-
Gaient area

At current cost and price Scenario (cost of fertilizer & price of grain
increased and decreased, respectively by
10%)
N/P205 TVC NB MRR TVC NB MRR
(kgha-1) (Eth. birr) (Eth. birr) (%0o) (Eth. birr) (Eth. birr) (%)
0/0 0 1846.7 0 1662
41/0 181.5 2200.5 194.9 199.7 1944.1 141.3
82/0 363.3 2290.7 49.6 399.6 1989.0 22.5
82/23 458.6 2764.0 496.5 504.4 2395.9 388.2
123/23 640.1 2949.4 102.2 704.1 2526.4 65.3
123/46 735.6 3061.7 117.5 809.2 2608.4 78.1

Note: Cost of DAP = Birr 2.70/kg
Cost of Urea = Birr 2.03/kg
Price of wheat grain = Birr 1.62/kg



References
Aleligne Kefyalew, and Regassa Ensermu. 1992. Bahir-Dar Mixed Farming Zone: Diagnostic Survey Report. Research
Report No 18. Institute of Agricultural Research, Addis Ababa, Ethiopia Amahara National Regional State
Bureau of Planning and Economic Development (ANRS BOPED). 2000. Annual Statistical Bulletin, Bahir
Dar Ethiopia.
CIMMYT. 1988. From agronomic data to farmer recommendations: An economics training manual. Completely
revised edition. Mexico, D.F.
Hailu Gebre-Mariam, Tanner, D.G., and Mengistu Hulluka, (eds.). 1991. Wheat Research in Ethiopia: A historical
perspective. Addis Ababa: IAR/CIMMYT.
UNDP. 1996. Sustainable Agricultural and Environmental Rehabilitation Program (SAERP). House Hold Level Socio-
Economic Survey of the Amhara Region. V.1 Produced by the Cooperative Endeavors of the Amhara
Regional Council. Bahir Dar, Ethiopia.
Ammanuel G, D.G. Tanner, Lemma Z, Tilahun G, Zewdu Y. and Eyasu E. 1990. Derivation of Economic fertilizer
recommendations for bread wheat in the Ethiopian highlands: On-Farm trial in the peasant sector. PP. 63-72.
In; Tanner, D.G., M. van Ginkel, and W. Mwangi, eds. Sixth Regional Wheat Workshop for Eastern, Central
and Southern Africa. Mexico, D.F; CIMMYT.
Minale Liben, Alemayehu Assefa, D.G. Tanner and Tilahun Tadesse. 1999. The response of bread wheat to N and P
application under improved drainage on Bichena Vertisols in northwestern Ethiopia. The Tenth Regional
Wheat Workshop for Eastern, Central and Southern Africa. Addis Ababa, Ethiopia: CIMMYT.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Grain Yield, Water Use and Water Use
Efficiency as Affected by Moisture Level
Under Rain-Out Shelter

P. A. Ooro 1, M.G.Kinyua and J.B.O. Ogola2

'KARI-NPBRC, P.O. Njoro, Tel. 254-051-61070, Kenya, paooro@yahoo.com
2Department ofplant production, University of Venda, Private BagX5050,
Thohoyandou, Republic of South Africa, *Corresponding author

Abstract-About one-third of the developing world's wheat area is located in
environments that are regarded as marginal for wheat production, because of drought,
heat, and soil problems. Nearly one-third of the area planted to bread wheat and
about three-quarters of the area planted to durum wheat suffer from drought stress
during the growing seasons. Despite these limitations, the world's dry and difficult
cropping environments are increasingly crucial to food security in the developing
world. Gains in wheat productivity in marginal environments are important because it
is unlikely that increased productivity in the favourable environments will be
sufficient to meet the projected growth in demand for wheat from the present to
2020. This study was aimed at evaluating wheat genotypes' water use efficiency
(WUE) as affected by moisture regime. An experiment was conducted under rain
shelter for two seasons (2001-2002) with six cultivars (Duma, Ngamia, Chozi,
Kwale, Mbuni and Pasa) tested under two moisture regimes (High and low moisture
regimes). The experiment was a randomized complete block design (RCBD) with
split arrangement of the treatments. Moisture regime was assigned as the main plot
and cultivars as the sub-plot. An analysis of variance was carried out on combined
season using SAS computer package. The genotypes tested were significantly
different in their water use efficiency (WUE) under both low and high moisture
conditions. The drought-tolerant cultivars (DTC)-Duma, Ngamia and Chozi-had
significantly higher WUE under moisture stress than the drought-susceptible
cultivars (DSC)-Kwale, Mbuni and Pasa. Under high moisture the WUE of the
DTC was decreased by 10-19% and in the DSC, it increased by 26-29.

Introduction
Cereals contribute significantly to food security in Kenya (Wanjama et al, 1993). Among
cereals, wheat has been ranked second to maize (KARI, 1991) and is grown on an estimated
area of 105,000 ha (representing about 6% of the total area under cereal production in Kenya)
giving an annual production of about 350,000 metric tones (Ekboir, 2002). The crop is mainly
grown in the Rift Valley province with Nakuru, Uasin Gishu and Narok districts contributing
about 85% of the total national production (Wanjama et al, 1993). The national wheat
production has varied over time. For example, in the period 1988 2000, wheat production
declined annually by about 1.5% (Aquino et al., 2002).
Due to the reduction in wheat area, Kenya produces only 40% of the national demand of
approximately 720,000 tonnes, and importing about 60% of its wheat requirement (Aquino et
al., 2002). For example, between 1997-1999, wheat imports stood at 484,900 tonnes (5.4
million 90-kg bags), costing about 5.85 billion Kenya shillings (US$ 84 million). Kenya is
bound to remain a net importer of wheat and wheat products unless domestic wheat
production is significantly stepped up. Thus for wheat production to be increased to meet the
increasing demand in Kenya, among other technologies, wheat growing has to be expanded to


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










the marginal rainfall areas which consist of 83% of the total land area with unused arable
potential of approximately 200,000 hectares (World Bank, 1989).
Furthermore, it has been reported that 32% of the 99 million hectares of wheat grown in
developing countries experiences varying levels of drought stress (Rajaram et al., 1996). In
Kenya, for example, marginal rainfall areas have been able to achieve wheat yields of
between one third and one half of those from high rainfall areas (Kinyua et al., 1989).
Promotion of wheat farming in the dry lands of Kenya can be done through several ways.
These include use of irrigation and/or drought resistant wheat varieties. Irrigation would
require steady supply of water and due to scarcity of water in the marginal areas and large
capital required, irrigation is not easily achievable. Thus development of appropriate varieties
for marginal areas may be the most effective alternative for utilizing these areas for crop
production. Therefore, the main objective of this study was to evaluate WUE as an indirect
method for selecting drought tolerant wheat cultivars.

Materials and Methods
An experiment was conducted in the rain shelter for two seasons between August, 2001 and
May, 2002 at the National Plant Breeding Research Centre (NPBRC), Kenya (0 20' S and
35056'E and altitude 2185 metres) [NPBRC Meteorological Station No. 9035021, 1999].
The site lies within the Agro-ecological zone LH3 (AEZ LH3) with a bi-modal rainfall pattern
(Jaetzold and Schmidt, 1983). The site receives an annual rainfall of about 960 mm with an
average maximum and minimum temperatures of 24 o C and 8 o C, respectively (NPBRC,
Njoro Meteorological station No.9035021, 1999).
The soil at the is site well drained, deep to very deep, dark reddish brown, friable and
smeary, silt clay, with humic topsoil classified as mollic Andosols (Jaetzold and Schmidt,
1983). The site was under fallow for two seasons before this study was carried out.
The experiment was carried out under a mobile rain-out shelter (which is an open ended
structure measuring 30 m long and 7 m wide constructed at NPBRC) to exclude rain and
consequently induce drought stress. The shelter consists of a roof mounted on wheels that
allows it to roll on two parallel-elevated concrete tracks. Translucent sheets (which allow up
to 90% photosynthetic photon flux density) covered the roof. The sides had metal frame,
which was covered by foldable polythene sheets, with open-end 0.5 m above the ground. A
concrete barrier had also been constructed to a depth of 0.6 m below the ground level and
0.15 m above the ground level along the two longer sides of the shade from a rail. The length
of the rail was 30 m but the shelter rested on half the length. The barrier also helped to
prevent the rainwater from flooding the shade. The mobile rainout shelter used is similar to
that described by Legg et al. (1978) and Upchurch et al. (1983).
Six bread wheat genotypes Duma, Chozi, Ngamia, Kwale, Mbuni and Pasa were grown
under two watering regimes (High and low watering regimes) for two seasons. The
experiment was laid out in a randomized complete block design (RCBD) with split plot
arrangement with the watering regime being the main plot and cultivar as sub-plot.
Thirty-six (36) access tubes (PVC in nature) with 39.4 mm and 41.4 mm as internal and
outside diameters, respectively, were installed in the field before planting. In each sub-plot, an
access tube was installed in holes drilled by hand using a soil auger. The tubes were cut to a
depth of 1.7 m out of which 1.1 m was driven into the holes and 0.6 m was left above the soil
surface. Moisture readings were taken by use a Troxler moisture meter (Neutron probe). In
the process of moisture reading a standard count was at the beginning of each moisture
regime.
Hydrogen ions, standard counts and moisture percentage by volume readings were taken
through the access tubes at an interval of 7 days at an interval of 10 cm in the upper 40 cm


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










and 20 cm below 40 cm. The hydrogen counts were divided by the standard counts to derive
the count ratio that was later fitted in the calibration equations, for different soil levels within
the profile, to calculate the actual soil water content.
The seeds of the wheat varieties used in the trial were tested for germination before
planting and the seed-rate was adjusted according to the germination percentage. The
recommended seed-rate of 125 kg ha' was used.
The six cultivars were planted in plots of 0.8 metres length and 2 metres wide with ten
rows. The rows were 20 cm a part and planting was done by hand. The seeds were drilled
continuously on the furrows (5 cm deep) made by hand. Triple super-phosphate (0-46-0) was
applied in the furrows at 60 kg P205 ha' planting and calcium ammonium nitrate (CAN) at 40
kg N ha' (recommended rate) was top-dressed at early tillering stage to supply Water was
supplied through a drip irrigation at a constant pressure as per the treatments. One drip lateral
was laid between two wheat rows.
Watering was done once weekly and a day before watering was done moisture reading
were taken by use of neutron probe. Watering was done when the moisture level had come to
50% field capacity and watering done according to treatments. The high moisture treatment
received 14.5 mm and the low moisture regime received 7.5 mm once weekly. The total
amount of water applied during each season was 217 mm and 113 mm for the high and low
moisture regimes, respectively.
Weed control was done by the use ofBuctril Mc at the rate of 1.4 L ha' at the 3-4-leaf
stage of crop. The chemical was used to take care of broad-leaved weeds but for the grasses,
hand weeding was done. Six innermost rows were hand harvested for biomass and grain yield
determination.
Evapo-transpiration (ET) included both transpiration and direct evaporation of water
from the soil surface (Esc). Evapo-transpiration (ET) was determined by using the soil water
balance equation given below:

ET= -AS +I -D R (3.1)

where -AS is the change in storage (obtained by the difference in volumetric moisture content
of the entire profile at the beginning and end of the season), I is irrigation water applied, D is
the drainage and R is the run-off Drainage and run-off were assumed to be negligible hence
total crop water use for the whole season obtained by summing total irrigation where
applicable) and changes in storage for the entire profile (Ogola, 1999). Pilbeam et al., (1995)
suggested that significant drainage is considered to have occurred where the soil water at the
base of the profile was increased above its initial value. Drip irrigation was used hence
drainage was assumed to be zero and thus not included in the water balance equation.
For the purposes of this study, water use efficiency (WUE) was defined as a ratio of grain
yield (GY) to evapo-transpiration (ET). Thus WUE was determined as follows:

WUE = GY/ET. (3.2)

where GY is the grain yield.
Grain yield (GY) was determined by harvesting one metre length of the two inner-most
rows. Harvesting was done by hand and threshed by the use of laboratory single head thresher
and grain yield was standardized at 12.5% moisture content.
Thousand-kernel weight (TKW) was determined after grain weight had been recorded from
both experiments. A thousand seeds were picked randomly and weighed to determine TKW.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Neutron probe calibration procedure
The soil profile of the site (NPBRC field 1) was described and the soil depth of the site
determined and the pumice was realized to start immediately after 60-cm depth. For
calibration, two access tubes were installed each at a depth of 110 cm. One of the tubes was
used to get wettest point of the calibration curve whereas the other one was for the drier
points of the curve (Ooro et al., 2001).
The place surrounding the tube for the wettest point was flooded with water and left to
settle for 24 hours and then soil samples for gravimetric moisture determination were taken at
10, 20, 30, 40, 60, 80 and 100 cm depths. At the corresponding depths, neutron probe
readings were taken for the hydrogen ion counts and hence volumetric water content. The
same approach was used around the access tube for the lower points of the calibration curve
(Manual of operation and Instruction, 1996).
The data generated from the neutron probe readings (from the wet and dry calibration
spots) were used to calculate count ratios (F/Standard count) plotted on the x-axis of the
calibration curves and two equations were then developed for the top soil (upper 20 cm) and
below 20 cm depths. The two calibrations were developed due to the variations between the
readings of depths up to 20 cm and those below 20 cm. Hydrogen ions readings up to 20 cm
depth were relatively lower due to scatter effect while this effect did affect readings below 20
cm. Plotting gravimetric moisture readings on the y-axis and the count ratios on the x-axis
developed the equations. The equations were as follows:

0 20 cm depth: Y = 0.0661n + 0.001615 (3.3)

30 100 cm depth: Y = 0.20960n + 0.001132 (3.4)

where Y is the actual moisture volumetricc moisture), n = count ratios (W/standard counts)
[H+ was read from the neutron probe].

The data read by neutron probe in the rain-shade experiment was fitted on the calibration
curve to give the actual moisture content.
Data from all the parameters, combined over two seasons (2001 and 2002), were
subjected to an analysis of variance (ANOVA) using SAS (SAS User's guide, 1985). Least
significant difference procedure (Lsd) was used to carry out mean separations. The data was
also subjected to correlation and path coefficient analysis was done to separate the direct and
indirect between the agronomic traits and water use efficiency.


Results
The interaction between genotype and moisture regime affected final grain yield. High
watering regime increased grain yield of both the drought tolerant and drought susceptible
varieties but the increase in yield due to high watering regime was greater in susceptible
(110%-134%) than in tolerant (55-64%) varieties. The drought tolerant varieties produced
greater yield than the drought susceptible ones under low watering regime. Under high
moisture regime, in contrast, the drought sensitive varieties produced greater yields than the
tolerant ones. Significant genotypic differences in grain yield were detected. Averaged over
the low watering regimes, the drought tolerant cultivars had higher yield (1274 kg ha') while
the drought susceptible ones had relatively lower yield (972 kg ha '). Moreover, drought
tolerant varieties produced greater (by 39%) yield than the drought susceptible varieties under
low watering regime. Averaged over all the genotypes, high watering regime increased grain
yield by 89% (from 1123.2 kg ha' to 2119.0 kg ha').


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










There was significant effect of the interaction between moisture regime and cultivar on
crop water use, such that the increase in water use due to high watering regime was greater for
drought sensitive (96%) than for drought tolerant (93%) varieties. Also, under low moisture
conditions Kwale used more water (by 10%) than all the other cultivars tested while under
high moisture, Chozi had significantly lower (by 3%) water use value than the rest of the
cultivars. Significant genotypic differences on water use were detected. Averaged over the
watering regimes, Kwale had the highest water use (139 mm) while Pasa had the lowest water
use (132 mm) as compared to the other varieties tested. High watering regime increased
water use (averaged over all varieties) by 95% (from 91 to 177 mm).
The interaction between variety and moisture regime affected water use efficiency
(WUE) significantly (Table 1). High moisture regime decreased (by 10%-19%) WUE of
drought tolerant varieties (Duma, Ngamia and Chozi) but increased (by 26%-29%) WUE of
drought sensitive varieties (Kwale, Mbuni and Pasa). Under low moisture regime, drought
tolerant varieties had higher WUE values than the drought sensitive varieties while the
converse was true under high moisture level (Table 1). No significant effects of cultivar on
WUE were detected. However, high watering regime increased WUE (averaged over all
wheat varieties) by 4% (from 9.6 to 9.9 kg ha' mm-') (Table 1).

Table la. Grain yield, water use and water use efficiency of six wheat genotypes under two
watering regimes
Treatment Grain Yield Water Use Water Use
Moisture regime Cultivar (kg ha- ) (mm) Efficiency (kg ha mmn )

Low
Duma 1213.ab 90.b 10.7ab
Ngamia 1286.a 91.b 10.9a
Chozi 1324.a 91.b 11.la
Kwale 1152.abc98.a 9.0b
Mbuni 902.bc 88.b 7.9c
Pasa 862.c 87.0b 7.7c

High
Duma 1886.b 177.a 8.7b
Ngamia 2097.b 177. a 9.8ab
Chozi 2173.ab 171.b 9.6b
Kwale 2424.a 179. a 11.3a
Mbuni 2114.ab 177.a 10.lab
Pasa 2020. b 177.a 9.9ab

SE 11 3 0.58

F-test probabilities

Irrigation (I) P<0.001 P<0.001 P<0.05
Cultivar (C) P<0.05 P<0.05 ns
Interaction (CXI) P<0.05 P<0.001 P<0.001
Figures followed by the same letter within the same moisture regime in the same column are
not significantly different at Lsd 5%.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Table lb. Varietal differences in yield components of wheat at two moisture levels
Treatment No. of Plant TKW No. of
Moisture regime Cultivar tillers/plant height (cm) (g/l000seeds) seeds/spike

Low
Duma 4.5ab 53.b 43.b 26.c
Ngamia 2.7c 52. b 39.c 40.a
Chozi 3.7bc 58.a 46.a 27.bc
Kwale 3.5bc 55.ab 45.ab 25.c
Mbuni 4.0b 55.ab 46.a 35.abc
Pasa 5.7a 58.a 43. b 36.ab

High
Duma 3.8bc 69.bcd 44.bc 33.b
Ngamia 3.7bc 66.cd 41.d 36.ab
Chozi 5.7a 81.a 49.a 28.b
Kwale 4.7ab 70. bc 46.b 34.ab
Mbuni 3.3c 73.bc 42.cd 35.ab
Pasa 4.5abc 65.d 40.d 43.a

SE 0.63 2. 1 9

F-test probabilities

Irrigation (I) P<0.001 P<0.05 ns P<0.001
Cultivar (C) P<0.001 ns P<0.05 P<0.05
Interaction (CXI) P<0.05 P<0.001 P<0.001 P<0.001
Figures followed by the same letter within the same moisture regime in the same column are
not significantly different at Lsd 5%.

Discussion
Improving drought tolerant of wheat has long been a major objective of most breeding
program because water deficits during some parts of growing period are common in most
regions of the world where wheat is produced under rain-fed conditions. Therefore in this
study the cultivars tested were evaluated with an aim of understanding their reactions under
low and high moisture regimes. Significant interactions were observed between moisture level
and water use efficiency (WUE) of wheat cultivars. The WUE of drought tolerant wheat
cultivars (Duma, Ngamia and Chozi) was decreased (by 14%) under high moisture but
increased (by 30%) WUE of drought sensitive varieties (Kwale, Mbuni and Pasa). This
behaviour of drought tolerant cultivars under low moisture was probably due to the fact they
had less tiller number per plant compared to the susceptible varieties. Fewer tillers of drought
tolerant wheat have been reported from studies by Ehlig and Lemert (1976) and Singh et
al., (1979). Low tiller number per plant under low moisture could be a mechanism that
drought tolerant used reducing the demand for water. In a study involving the evaluation of
the effects of moisture stress, reduced maximum tiller number of Triticum tauschii (wild
relative of wheat) were reported to be strongly reduced by low moisture. Those findings were
similar to those reported for cultivated wheat (Cone et al., 1995).
The significantly high WUE of a cultivar such as Chozi might have been due to
therelatively taller plants under low moisture which probably converted into higher biomass
and relatively higher grain yield. Drought tolerant cultivars (Duma and Ngamia) maintained
shorter plant stature under low moisture, which is another mechanism of economizing on
moisture hence, increased WUE. The findings of this study are in disagreement with those
reported by Rezgui et al., (1999) from their study involving evaluation of 61 durum wheat


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










genotypes in a moisture stressed environment at Mograne in Tunisia. From their study it came
out that taller plants were associated with increased WUE.
The thousand-kernel weight (TKW) for the drought tolerant cultivars (Chozi, Duma and
Ngamia) was higher under both low and high moisture. Less tillers per plant under low
moisture observed on the drought tolerant cultivars was boosted by the higher TKW value.
The high TKW value resulted in heavy individual seeds which in turn culminated in higher
grain yield which appeared to increase WUE mainly due to higher harvest index (HI). The fact
that the drought tolerant cultivars (Chozi, Duma and Ngamia) were shorter in stature HI was
inversely related to plant height resulting into higher WUE under both low and high moisture
conditions. Ehdaie (1995) reported higher WUE of shorter wheat cultivars under both low
and high moisture regimes in a study conducted on bread wheat to evaluate seasonal WUE
and its components in Spring wheat.
Lower seed number per spike was observed on drought tolerant cultivars (Duma and
Chozi) a part from Ngamia under low moisture. The low seed number per spike translated
into increased seed size and therefore increased TKW. Rebetzke et al., (2001) reported
increased kernel size due to die back of wasteful tillers in wheat under drought in Australia. A
study carried out to evaluate the stability of grain yield and its components under moisture
stress also revealed that the overall moisture deficit induced reduction in yield of specific
wheat cultivars were largely due to similar effects on kernels per spike (Guttieri et al., 2001).
Drought tolerant cultivars (Chozi, Duma and Ngamia) maintained high TKW even under
low moisture. Despite the fact that these cultivars had fewer tillers per plant under low
moisture, they had relatively higher WUE value. The high WUE value may be attributed to
high TKW, which helped to maintain higher grain yield resulting into increased WUE. The
drought tolerant cultivars (Duma and Chozi) a part from Ngamia had relatively lower seed
number per spike under low moisture. The high seed number per spike translated into
increased TKW which may be because the low seed number per spike resulted into less
competition giving rise to increased kernel size. Rebetzke et al., (2001) reported that wheat
cultivars that had tiller inhibition genes had increased kernel size. Correlation study
confirmed that tiller number per plant had a high negative (P<0.05) correlation with WUE of
Duma under low moisture. However, under the same moisture regime, Ngamia and Chozi
were not significantly correlated to tiller number per plant. This showed that tiller number
controlled WUE positively on Duma but not Ngamia and Chozi under low moisture regime.

Conclusion and Recommendation
Moisture affected the grain yield and water use efficiency (WUE) of the genotypes tested
significantly. Drought tolerant wheat cultivars (Duma, Ngamia and Chozi) under moisture
stress used moisture more efficiently than the drought susceptible cultivars (Kwale, Mbuni
and Pasa). The increased WUE of drought tolerant wheat cultivars (Duma, Ngamia and
Chozi) was the basis of their drought tolerance. This has an implication on the drought
tolerance selection in wheat research.
In view of the aforementioned results, the understanding of the traits that contributed to
the increased WUE of the drought tolerant wheat genotypes under moisture stressed
environment was addressed in the second part of this study. However, the results of that
section of the study have not been included in this paper.

References
Aquino, P., Carrion, F., and Calvo, R. 2002. Selected Wheat Statistics. In Ekboir J.(ed.) 2002.
CIMMYT 2000 2001 World Wheat over-view and outlook: Developing no till packages for
small-scale farmers. Mexico, D.F.: CIMMYT.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Cone, A. E., Stafer, G.A., and Halloran, G.M. 1995. Effects of moisture stress on leaf appearance,
tillering and other aspects of development in Triticum tauschii.Euphytica. 86 (1): 56-64.
Ehdaie,B. 1995. Variation in water-use efficiency and its components in wheat: II. Well-watered pot
experiment. Crop Science. 1995. 35 (6). 1617-1626.
Ehlig, C.F., and LeMert, R.D. 1976. Water use and productivity of wheat under five irrigation
treatments. Soil Sci. Soc. Am. J 40:750-755.
Ekboir, J. (ed.) .2002. CIMMYT 2000-2001World Wheat Overview and Outlook: Developing No-Till
Packages for Small-Scale Farmers. Mexico, DF:CIMMYT.
Guttieri, M.J., Stark, J.C., O'Brien, K., and Souza, E. 2001. Relative sensitivity of Spring wheat grain
and quality parameters to moisture deficit. Crop Science. 41 (2): 327- 335.
Jaetzold, R., and Schmidt, H. 1983. Farm Management Handbook of Kenya, Vol IIB, Central Kenya
(Rift Valley and Central Provinces). Ministry ofAgriculture in Cooperation with the German
Agric. Team (GAT) of the German Agencyfor Technical Cooperation (GTZ). Printed by
Typo-druck, Rossdorf, W. Germany. 381-416pp.
KARI. 1991. KARI agricultural research priorities to the year 2000. KARI, Nairobi, Kenya.
Kinyua, M.G., Wanjama, J.K., Kamwaga, J., and Migwi, S. 1989. The situation in wheat production in
Kenya. Kenya Agricultural Research Institute (KARI) Report.
Legg, B.J., Day, W., Brown, N.J., and Smith, G.J. 1978. Small plots and automatic rain shelter. A field
appraisal. Journal ofAgricultural Science 91: 321 326.
Manual of Operation and Instruction, 1996. Calibration of Depth moisture gauge (Model 4300), pp.C-
24. Troxler Electronic Laboratories, Inc. and subsidiary Troxler International, Ltd, North
Carolina, USA.
National Plant Breeding Research Centre (NPBRC). 1999. Weather Data. Meteorological Station No.
9035021.
Ooro, P.A., Kinyua, M.G., Ogola, B.O., Owido, S.O., Kimurto, P.K., and Mwangi, S.K. 2001. Soil
Profile characterization and Moisture meter (Neutron Probe) calibration. Report, National
Plant Breeding Research Centre (NPBRC), Njoro.
Rajaram, S., Braun, H.J., and Ginkel, M. van. 1996. CIMMYT's approach to breed for drought
tolerance. Eupytica. 92, (1/2), 147-153.
Rebetzke, G.J., Bonnett, D.G., Richards, R.A., Condon, A.G., and Herwaarden van, A. 2001. Breeding
for high water use efficiency increases grain yield. CSIRO, Plant Industry.
Rezgui, S., Yahyaoui, A., Amara, H., and Daaloul, A. 1999. Relationships between water
use efficiency and agronomic traits of selected durum wheat cultivars. Revue de 1'INAT. 14
(1): 143-153.
SAS Institute Inc. 1985. SAS user's guide: Statistics, Version 5 Edition. SASInst. Inc. Carry, NC.
Singh, N.T., Singh, R., Mahajan, P.S. and Vig, A.C. 1979. Influence of supplemenatary irrigation and
pre-sowing soil water storage on wheat. Agron.J 71:483-486.
Upchurch, D.R., Ritchie, J.T., and Foale, M.A. 1983. Design of a large dual-structure rainout
shelter. Agronomy Journal 75: 845 -848.
Wanjama, J.K., Macharia, M., Karanja, D.D., Pinto, J.M., Maina, M.P.D., Kinyua, M.G., Wanyera, R.,
Faraj, A., and Gitari, J.N. 1993. Strategic Planning For Wheat Research To The Year 2013.
National Plant Breeding Research Centre, Njoro, pp.2-28.
World Bank. 1989. Kenya Agricultural growth and strategy options. Unpublished Sector Report.
Nairobi, Kenya.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004









Part 2. BREEDING


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Current Status of Stem Rust in Wheat
Production in Kenya

R. Wanyera, M.G Kinyua, P. Njau, J.W. Kamundia and S.Kilonzo

Kenya Agricultural Research Institute- National Plant Breeding Research Centre
P.O. Private Bag, Njoro- 20107, Kenya. Email: cepnjr@wananchi.com, or rvkepawae@wananchi.com

Abstract-Stem rust Puccinia graminis f. sp tritici is among the three rusts currently
threatening wheat (Triticum aestivum L) production in Kenya. A three-year survey
(2002-2004) was carried out to determine the distribution of stem rust on the wheat
varieties in the country, and to study the reaction of wheat varieties/lines to stem rust
inocula from different sources. Fifty-three (53) Stem Rust Parental Collections
(SRPC) were also screened in the experimental cage at Njoro whereas 16 commercial
wheat varieties were screened in the field in Njoro, Mau-Narok and Eldoret arranged
in a RCBD with 3 and 2 replications respectively. Fourteen (14), 9 and 11 sets of
breeders F3, stem rust differentials from Mexico and Australia were also screened in
the greenhouse. The survey results indicated that stem rust has reached the high
altitude areas where maximum and minimum temperatures range from 22 to 260 C
and 6 tol40C respectively. Out of 53 SRPC screened, 79.3% were susceptible, while
20.7% showed resistance. The 16 commercial varieties were susceptible. Varieties
Ngamia, Duma, Yombi, Heroe were most susceptible with a mean score of 63%,
48%, 46%, and 43% respectively. Kenya Fahari, K. Paka and Njrbwl were least
susceptible (5%, 4%, and 14%). The infection types of stem rust spores from
different sources were different on the stem differentials from Australia. These
preliminary data indicate the possibility of more than one stem rust race attacking the
wheat crop. Joint effort is required to utilize the current biotechnology tools to
identify and breed for resistance to the new race(s).


Introduction
Stem rust (Puccinia graminisfp. tritici) is among the cereal rusts that cause severe losses
throughout the world. The rust range can cause losses ranging from slight to complete
destruction of a wheat crop. Losses of 50-70-% have been reported in the field. Infected grain
is shriveled, light in weight and of low quality (Stubbs et all, 1986; Agrios, 1988; Wiese,
1991; Minzenmayer, 2000; Cereal Disease Laboratory, 2004). In addition to reducing grain
yield, rusts lower the crop's forage value and predispose plants to other diseases. Rusted
wheat plants are less palatable and are toxic to livestock (Wiese, 1991). Puccinia graminis
commonly attacks wheat; other hosts include barley, rye, oats, wild barley and goat grass.
Wheat production in Kenya is highly affected by stem rust and other rusts like yellow
and leaf rusts. Under favorable environmental conditions, infection of the wheat crop with
stem rust disease reduces both the quantity and quality of the grain (KARI annual reports
2000, 2001, 2002, and 2003). At the beginning of the wheat breeding efforts in Kenya in 1927
up to the early 1980s, stem rust was the most serious of the three rusts. This was given a high
priority by the breeding team and due to wide resistance breeding, this problem disappeared
for some time and subsequently many resistant commercial wheat varieties were developed
and released to farmers. Since 1992, severe epidemics have continued to occur on commercial
bread wheat and introductions (Danial et al, 1994; KARI annual reports 1999, 2002, and
2003). In 1996 the disease was recorded on some commercial wheat varieties in Mau-Narok
and Molo. By 2000, all the varieties had succumbed to the disease, and at present, they are


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










susceptible. Stem rust outbreak is now widespread in all the wheat growing areas in the
country in low, medium and high altitude areas (KARI annual reports 2000-2003). The
resurgence of this disease even in the high altitude areas (2700-2900 masl) has necessitated
the need to revive work on this pathogen to incorporate genetic resistance to the prevalent
race(s) within the commercial varieties to work on this pathogen. Therefore, the objective of
this study was to determine the distribution of stem rust on wheat varieties around the
country and also to study the reaction of wheat varieties/ lines to rust inocula collected from
different sources.

Materials and Methods
1. Survey and collection of stem rust spore from the fields
The survey was carried out on farmers' commercial fields and also experimental plots in some
parts of Uasin-Gishu, Nakuru, Meru, Nyeri, Nyandarua and Narok districts between years
2002-2004. Farms were picked along routes at random, stopping at every 3- 5 kilometers or
whenever the nearest farm was, especially in areas with sparsely distributed farms. In every
farm, plants were examined randomly by walking across the field. When sampling, a two
meter distance from the edge was left to avoid border effect. Disease severities were taken
using modified Cobb's scale (Peterson, et al.,1948) and coefficient of infection calculated by
multiplying the disease severity and host response. Growth stage was entered in the field data
form. The stem rust (sr) spores (uredospores) were then collected using a suction pump and
some were scrapped from the leaves and stems using sterile scalpel blades. In the laboratory
the spores were dried using Silica gel in the dessicator, vacuumed sealed in vials and stored
for further work.

2. Screening of Stem Rust Parental Collection (SRPC)
Fifty-three SRPC were planted by hand in the cage at Kari-Njoro and evaluated for stem rust
infection. Variety Morocco, the universal suscept was used as the check. Each collection was
planted in a hill at 2-3 seeds/hill. Diammonium phosphate (DAP) fertilizer was applied at the
recommended rate of 130kg/ha.The plants were sprayed with Metasystox insecticide at the
rate of 0.5L/ha to control the Russian wheat aphid (RWA) and other aphid vectors for the
barley yellow dwarf disease. No fungicide was applied and the plants were monitored for the
appearance of stem rust. Disease severity scores were taken twice at the heading stage using
Cobb's modified scale (Peterson et al., 1948). The scores were then transformed using square
root (x+1) and the means transformed back to original scores. These were statistically
analysed using analysis of variance and least significance difference used to separate the
means.

3 .Screening of wheat commercial varieties against stem rust in the field
Sixteen wheat commercial varieties were planted in Njoro (2185 m asl) and Eldoret -
Chepkoilel campus (2150 m asl) while 14 varieties were planted in Mau-Narok-Purko ranch
( 2900 m asl) and evaluated for resistance against stem rust. In Njoro and Mau-Narok the
varieties were planted in a randomized complete block design with three replications. Plots
were 8 rows by 2 meters per variety. In Eldoret, two replicates of the same were planted.
Furrows were made using the seed drill and both seed and fertilizer placed by hand.
Immediately, after planting the experiment was sprayed with Stomp 500E a pre-emergent
herbicide at the rate of 3.0L/ha to control grass weeds. At the tillering stage the experiment
was sprayed with Buctril MC at the rate of 1.25L/ha to control broad leaved weeds. The
Russian wheat aphid and other insect pests were controlled as above. Disease severity
readings were taken at the heading stage and data were analysed as above.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











4. Screening of breeders F3 lines and stem rust differential lines for resistance against
stem rust
Seventy-eight F3 lines and 50 and 40 stem rust differential lines from Cimmyt-Mexico and
Australia respectively were planted in 14,8 and 11 sets respectively. Each set was planted in
4 inch plastic pots filled with soil and placed in the green-house. The pots were placed on
trays with gravel filled with water. In every pot there were four lines/varieties. The
uredospores collected from : Njbw2, ISR5RA(SR5), ISR9DRA, F1 material, Chozi, Ngamia
Duma, Heroe/Rwa8, Heroe/Rwa9, K7892/Rwa9, differentials Yalta, Anautka, Timboroa
(Matharu), Eldoret and National Dryland Wheat Preliminary Trial (NDWPT) The rust spores
were tested for viability and suspended in distilled water. A drop of Tween 20 was added to
each collection and sprayed on 7 day old seedlings. The seedlings had been treated at
emergence with Maleic hydrazide 0.01 g in 30 mls of water to enhance spore production. The
plants were incubated for 24 hrs in a polythene chamber kept moist by frequent spraying with
water under high relative humidity of 80-100%, and temperature of 18-220C. They were
removed and placed on the benches in the green house for 14 days and infection types
recorded using 0-4 scale proposed by Stakman et al. ( McIntosh et al, 1995) for stem rust: 0-
Immune, ;(fleck)-Very resistant,l-Resistant, 2-Resistant to moderately resistant,3-Moderately
resistant/moderately susceptible,4- Susceptible. Data on infection types was compiled and
analyzed using SAS system and means separated using least significance difference.

Results
1. Survey and collection of stem rust spore from the fields
The total number of commercial farms sampled between 2002 and 2004 were 61, from which
46 (75.4% ) of the farms had stem rust infection( Table 1). In some farms the wheat crop had
dried but the stem rust infection spores basidiosporess) were obvious. The farmers were in
most cases not able to identify the varieties because they bought planting seed from fellow
farmers. Those who kept their own seed were growing old varieties.

2. Screening of Stem Rust Parental Collection (SRPC)
Disease evaluation was based on 29 lines out of the 53 SRPC and Morocco the susceptible
check. Twenty-three of these (79.3%) and Morocco were susceptible while six ( 20.7%) were
resistant. There were significance (P< 0.05) differences among the line in disease infection.
Table 2 shows that SRPC1(b), SRPC4(b), SRPC 25, SRPC 38(b) and SRPC 204 were highly
susceptible while SRPC10, SRPC 27(a), SRPC (b), SRPC 29, SRPC 166 and 245 were
resistant.

3. Screening of wheat commercial varieties in the field
There were significance (P< 0.05) differences among the varieties in stem rust infection
(Table3). Thel6 commercial wheat varieties were all infected with stem rust and the level of
infection varied from variety to variety in all the three sites. In Njoro ( 2185 m asl), the most
infected varieties were: Duma and Ngamia (56.7%, K.Tembo (46.7%) Yombi and Chozi
(43.3%) Heroe and K. Kongoni (40%), Kwale (30%) and Chiriku, Mbega, Mbuni. K. Fahari,
K.Paka. and Njrbwl were least infected. In Eldoret( 2150 m asl ), the most affected varieties
were: Ngamia and Duma (70%), Chozi, Kwale, Heroe and K. Kongoni(50%), Yombi (45%),
while Chiriku, K.Nyangumi, K. Fahari, K.Paka K. Tembo and Njrbwl were less infected. In
Mau-Narok (2900 m asl), the most infected were: Yombi (50%), K. Nyangumi (30%) and
Heroe (40%) wheras, Chiriku, Kwale, K. Nyangumi, Mbuni, K. Fahari and K. Kongoni were
less infected. Varieties Ngamia, Duma, Yombi, Heroe and Chozi were most susceptible


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










across the three sites with a mean disease score of 63.4%, 48.3%,46.1%, 43.3% and 40.0%
respectively.
Table 1: Stem rust scores and coefficient of infection on commercial wheat varieties year 2002-
2004
District Place/Area Sr score/ Coefficient District Place/Area Sr score/ Coefficient
Year reactions of reactions of
infection infection
2002 UasinGishu Ainabkoi 20 MR 8 Nyeri Bagati 40S 40
Ainabkoi 40S 24 Bagati 60MS 36
Plateau 30MS 18 Naromoru 50MR 20
Plateau 60MS 36 Mweiga 5MS 3
Plateau 5MR 2 Mweiga 30MS 18
Plateau 70S 70 Kieni 40MS 24
Lembus 10S 10 Nairutia 20S 20
Lembus 5MR 2 Narok Olokurto 70S 70
Timboroa 5MR 2 Olokurto 20S 20
Timboroa 10S 10 Olokurto 50S 50
Timboroa 40S 24 Olokurto 30MS 30
Timboroa 20MR 8 Lopito 80S 80
Timboroa 5S 5 Elmasharani 80MS 32
2002 Nyeri Mbogo 5MR 2 Elmasharani 20S 20
Mbogo 20S 20 Ilipson 90S 90
Mbogo 10MR 4 Ntulele 60S 60
2003 Nakuru Lare 20S 20 Ntulele 5MR 1
2004 Nakuru M/Narok 80S 80 Navasha 40S 40
M/Narok 70S 70 Navasha 30MS 18
M/Narok 40S 40 Navasha 20S 20
M/Narok 15S 15
2004 Meru W/Embori 20S 20
Magara 30S 30
Kararu 10S 10
Mwireri 30S 30
M/Narok=Mau-Narok, W/Embori=Wangu Embori


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Table : Mean Stem Rust Disease Infection score and relative ranking (Lsd) on the Stem Rust
Parental Collection (SRPC) in the Cage Kari-Njoro, 2002
SRPC Pedigree Mean SRPC NO. Pedigree Mean
disease Disease
score score
SRPC 1(b) Africaxmayo 3529-1y-4m-3c-lt 45ab SRPC 36 E.N.4X" i, PlloL\iid CII2316)xGza 0.5 hij
1392 ,1289-2196
SRPC1( c) Africa/mayo 15 def SRPC 38(a) 17.5
cde
SRPC 2 Africa/mayo 3529-ly-4m-3y-lm 0.5 ij SRPC 38(b) 45 ab
SRPC 2(a) 30 bcd SRPC 41 (FederationxHope) xBolim, PI124830 5 fghij
SRPC 4(b) Bza sibx(CI 12633,WIS245) 35 bc SRPC 71 Gbx(fn-K58/N,II-50-17), II-53-649 5 ghij
SRPC 8(b) Chinca-A-ElongatumxRd,K.Sel.A 10 efgh SRPC 140 MbxSR, LM-72-14-57 10 efghi
SRPC 10 Chinca-A-ElongatumxRd)x(cl 0 j SRPC 148 My54XL1266-61,1448-4603 10 efgh
12633xldaed
SRPC 12 CI 8154xfr2 III-1009-2t-3b-lt-2b- 10 efgh SRPC 153 Mt-KxN-M,(fr-fn/y2),15224-5b-lt- 10efgh
It lb-4t
SRPC 15 C1.12632xCeres R6421198.A.2.1 3 hij SRPC 166 ND 463 Oj
SRPC 25 30 bcd SRPC 204 Sandos No63x CI12633-Idaed2) 40 ab
Gb 56xVeranopolis, 5134.B.3.B2.A
SRPC 27(a) (CI 12633,Wis245)2 Oj SRPC 238( 57.5a
-s5lx(fr-fn /y)III-l 13-6-6b-3t- a)
2b.K.sel .1
SRPC 27(b) (CII2633, WIS245)/(for-fn/y)2 Oj SRPC 245 0j
SRPC 28(b) 3 hij SRPC 250 5 ghij
SRPC 29 Oj SRPC 263 2.5 hij
SRPC 32 Desc-CI7800 /Bza3,14951-9b-lt 5 ghij Morocco 12.5 efg
Lsd P<0.05 1.7 Lsd P<0.05 1.7
Cv 26.4 Cv 26.4
Means in the same column followed by the same letter do not differ significantly using Lsd
P<0.05
-Pedigree to be traced


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Table 3: Mean % stem rust disease infection and relative ranking (Lsd) on commercial wheat
varieties in Njoro, Eldoret and Mau-Narok 2003
Variety Site/ Mean disease score % mean score
Njoro Reaction Mau-Narok Reaction Eldoret Reaction across the sites
type type type
Yombi 43.3 b S 50.0 a S 45.0 b MR 46.1
Duma 56.7 a S 18.3 abcd S 70.0a S 48.3
Chiriku 5.0 g MR 6.6 cd MR 5.0 f MR 5.5
Chozi 43.3 b S 26.6 bcd S 50.0b S 40.0
Ngamia 56.7 a S -70.0a MS 63.4
Njrbw2 20.0 def MR 11.6 bcd MR 25.0cd MS 18.9
Mbega 13.3 efg MS 23.2 abcd S 30.0c MS 22.2
Kwale 30.0 cd S 1.6 d MS 50.0b S 27.2
K.Nyangumi 21.7 de MS 30.3 abc MS 5.0 f MS 19.0
Mbuni 5.0 g MR 10.0 cd MS 20.0de S 11.7
K.Fahari 10.0 efg MR 5.0 cd MR 0.Of R 7.5
K.Paka 8.3 fg MR 5.0f MR 4.4
Heroe 40.0 be S 40.0 ab S 50.0b S 43.3
K.Kongoni 40.0 be MR 5.3 cd MR 50.0b MS 31.8
K.Tembo 46.7 ab S 17.0 bcd MR 5.0f MS 22.9
Njrbwl 11.7 efg MR 16.6 abcd MR 15.0f MR 14.4
P<0.05 12.3 3.092 9.482
Cv 26.16% 48.3% 14.38%


Means in the same column followed
P<0.05


by he same letter do not differ significantly using Lsd


4. Screening of breeders F3 lines and stem rust differential lines for resistance against
stem rust
Significant differences were observed in sources of stem rust inocula on sr differential lines
acquired from Australia (table 4a). Stem rust spores collected from sr differential Anautika,
ISR5RA(SR) and K 7892/Rwa9 had the highest mean infection (reaction) type while
Heroe/Rwa9, Timboroa (Matharu), Eldoret, and NDLWPT had the lowest mean infection
(reaction) type. This was not significant on breeders F3 material and also on sr differential
lines acquired from Mexico. Test lines, the lines x source of inocula did not differ
significantly for all the breeders F3 and sr differential lines. The analysis of variance (Table
4b) showed significant differences among the sources of sr inocula for the differentials
acquired from Australia (F=0.001**) were significant.


Table 4a :Mean disease score of
lines from Australia 2003


stem rust inocula from different sources on sr differential


Source of inocula Mean disease score
Variety Chozi 0.82 def
ISR5RA(SR) 2.14 ab
Timboroa( Matharu) 0.31 f
ISRDRA 1.27 cde
Heroe/Rwa8 1.42 bcd
Heroe/Rwa9 0.30 f
K7892/Rwa9 2.01 abc
Yalta 0.52 ef
Anautika 2.69 a
Eldoret 0.36 f
NDLWPT 0.36 f
Lsd (P<0.05) 0.825
Means in the same column followed by the same letter do not differ significantly


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










using Lsd P<0.05

Table 4b: Analysis of variance for sources of stem rust inocula
Source DF SS F
Set 10 359.514 0.001**
Variety 39 183.086 0.4709
Set x Variety 288 1475.120 0.1133
Error 219 960.833


Discussion
Levels of stem rust infection varied with environment as well as varieties/lines. This could
have been due to the temperature and rain distribution which varies from place to place with
some areas experiencing drought while others were wet. In Kenya, wheat is grown in many
agro- ecological zones that have different planting dates ( Ralph and Schmit,1983). This
staggered planting provides a green crop most part of the year allowing stem rust spores to
move by wind from one area to another and that way spreads to different areas. It is therefore,
a problem to reduce the disease infection in susceptible varieties. Almost all the wheat fields
had stem rust infection and the problem is advancing and becoming more serious in high
altitude areas where maximum and minimum temperatures range from 22C- 26 C and 6C-
14C respectively. The varied infection ( reaction) types of stem rust inocula from different
sources on differential lines from Australia probably showed that there could be more new
races attacking the wheat varieties. Although, Ngamia was not among the varieties screened
in Mau-Narok (2900m ASL), the records from a different study ( data not shown) showed
that the infection of stem rust was very high (Kari annual report, 2003).

Conclusion
The survey of stem rust revealed that the disease is on the increase in Kenya. Apparently all
the wheat growing areas are prone to this disease. There is therefore, an urgent need to have
more work done to determine the isolates so that the breeding programme can be effectively
sustained. Commercial varieties like K. Fahari, K.Paka, Chiriku and some of the old varieties
which have remained resistant/ moderately resistant to stem rust can be utilized in the
breeding programme. It is evident that stem rust is widely distributed in the wheat growing
areas and joint effort is required to utilize the current biotechnology tools to identify and
breed for resistance to the apparently new race(s).

Acknowledgement-The authors wish to acknowledge funds from CIMMYT for the
implementation of this study; Dr. Ravi Singh (CIMMYT, Mexico) for technical discussions
and germplasm; Drs.C.R. Wellings and Robert Park (Australia) for the differentials; Mr. D.
Onyango for maintaining the stem rust spores; and colleagues in pathology section for
cooperation and technical support.

References
Agrios, G.N. 1988. Plant Pathology.3 rd edition. Academic Press. ISBN 0-12-044563-8
Cereal Disease Laboratory '4). Wheat Stem Rust (Puccinia graminis f.sp. tritici ) at
hllup n \\\ .cdl.umn.edu
Danial, D.L., 1994. Aspects of Durable Resistance in Wheat to yellow rust. PhD Thesis. Wagenigen
Agricultural University, The Nertherlands, 144pp.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Kenya Agricultural Research Institute. 1999-2003.Annual reports. Kenya Agricultural Research
Institute.2002-2003.Annual reports.
McIntosh,R. A.,C.R. Wellings and R.F.Park. 1995. Wheat Rusts: An Atlas of resistance Genes.
CSIRO, Australia.
Minzenmayer Richard (2000). Pest Management News at http:// www.tpma.org
Peterson,R.F., A.B. Campell and A.E. Hannah. 1948. A diagrammatic Scale for estimating Rust
Severity on leaves and stems of cereals. Can.J. Res; 26:496-500.
Ralph Jaetzold and Helmut Schmidt. 1993. Farm Management Handbook Agriculture Vol.1, Part B.
Ministry of of Kenya in cooperation with German Agricultural Team (GAT) of Germany
Agency for Technical for Technical Cooperation ( GTZ).
Stubbs, R.W., J.M. Prescott, E.E. Saari and H.J.Dubin. Cereal Disease Methodology Manual. Centro
International de Mejoramiento de Maiz y Trigo (CIMMYT), Mexico. 1986.
Wiese, M.V.1991. Compedium of Wheat Diseases 2nd Edition. APS Press.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Genotype-by-Nutrient Interaction in Wheat
Grown in a Marginal Environment in Kenya


J. Kamwaga, H. Okwaro, P. Njau, P. Kimurto, P. Ndungu. and E. Kimani

Abstract-Six wheat (Triticum aestivum L.) cultivars (Chozi, Ngamia, Duma, Njoro
BW1, K.Heroe, and Chiriku) were grown in a marginal environment at two levels of
fertilizer; 0:0:0, 30:60:0 kg ha (N:P205:K).and at a seed rate of 125 kg. ha' to assess
their response to fertilizer application and nutrient use efficiencies. Grain yield, spike
numbers, harvest index (HI), nitrogen (N) uptake, N concentration and nitrogen use
efficiency (NUE) were recorded. There were no significant differences in grain yield
or spikes m2 among varieties when averaged across fertilizer levels. Differences in
HI between varieties were significant, with cv. Duma, a variety recommended for
marginal environments, having a higher HI than cv. K.Heroe. Fertilizer did not affect
the HI. There were no significant differences among varieties in N acquisition,
indicating similar nutrient uptake abilities, or in NUE, although this was reduced by
fertilizer application, probably because the increased N uptake did not translate into a
corresponding grain yield increase due to the poor growing conditions. Grain N
content ranged between 2.2% in the fertilized plots and 1.8% in the unfertilized plots
(meaned across cultivars) and 2.2% in Njoro BW1 and 1.9% in Ngamia.

Introduction
Genotypic differences in nutrient utilization have been documented in wheat. These
differences have been attributed to both differences in the acquisition and the efficiency of use
of nutrients between cultivars (Inthapanya et al., 2000). One reason for differences in
efficiency has been attributed to the development of different root systems between wheat
cultivars. Nitrogen (N) and phosphorous (P) deficiencies limit the yield of wheat in most
wheat growing areas of Kenya. A number of approaches have been used to enhance
productivity of wheat in such environments: principally the development of site-specific
fertilizer recommendations for various areas. Inorganic fertilizers are expensive and not
affordable to most wheat growers, while. Organic sources of nutrients are not easily available
in the quantities and qualities that would give adequate yields in farmers' fields. The use of
nitrogen fixing crops also has its limitations. Another approach would be to identify cultivars
that do well in low soil fertility conditions but that also respond well to applied fertilizer.
These would be the preferred cultivars because they would be useful to both farmers with
fertilizer inputs and resource-poor farmers. This type of cultivar usually has a high harvest
index (El Bassam 1998)
The efficiency of utilization of both N and P determines grain and dry matter yields.
Variety by fertilizer level interactions will be very important: researchers need to find
varieties that have low yield interactions with fertilizer level, and that, therefore, respond in in
a similar manner in low and high fertility environments. This is especially important as
varieties widely adapted to diverse soil fertility status will be preferable.
Cultivars grown in the marginal environments of Kenya have not been evaluated for their
nutrient use efficiency, yet this is an important factor determining yield of wheat in such
areas. Identification of cultivars that do well under low nutrient and moisture conditions will
improve wheat production in such areas and the the breeding program will be enhanced by
incorporation of characters associated with nutrient use efficiency. Improved cultivar


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










response to nutrients will help reduce inputs and hence protect the environment (El Bassam
1998).

The objectives of this project were to:
I. Determine genotypic variation in nitrogen uptake between cultivars recommended for the
arid and semi arid areas (ASALs) of Kenya.
ii. Determine the efficiency of utilization of N in recommended cultivars.
Materials and Methods
The trial was established in Kajiado, Kenya, on a moderately fertile vertisol with P ststus
above the critical levels (Table 1). The treatments were arranged in a split plot design with
three replications, with fertilizer levels as the main treatments and varieties as sub-treatments.
The two fertilizer levels used were 0:0:0, and 30:60:0 kg ha1 (N:P205:K), and the cultivars
assessed for nutrient use efficiency were: Ngamia, Chozi, Duma, Njoro BW1, Chiriku and K.
Heroe. Sub-plot size was 6m x 3m.
Seed was dribbled by hand into furrows spaced at 20 cm apart at a rate of 125 kg. ha1,
and fertilizer dribbled into the same furrows. At four weeks after seeding, Buctril MC. (a.i.
Bromoxynil +MCPA) was applied at 1.2 1 ha' to control weeds. At harvest, a 1 m2 quadrat
was harvested by cutting the plants at ground level. Parameters evaluated were total biomass
(Total Dry Matter), grain yield and nitrogen (N) concentration in grain and straw, determined
using the kjeldahl method. N uptake, nitrogen use efficiency (NUE) and harvest index (HI)
were calculated from the evaluated parameters.

Table 1 Soil chemical and physical characteristics of the trial site
Depth (cm) pH % N P (ppm) % O.M.
0-15 5.8 0.15 33 2.4
15-30 6.5 0.09 30 2.0
30-60 6.9 0.07 31 1.7
60-90 6.9 0.08 31 0.8

Results and Discussion
There were no significant effects of genotype on grain yield, harvest index, nitrogen uptake,
use efficiency or grain N concentration, nor were there fertizer by genotype interactions with
respect to these variables (Table 2), indicating that the varieties responded similarly to
fertilizer application. However there were differences between varieties with respect to
thousand kernel weight (TKW): Chozi had significantly higher TKW than all the other
varieties (Table 3). Fertilizer application significantly increased grain yield, total N uptake
and grain N concentration, but reduced nitrogen use efficiency, and had no significant effect
on HI nor TKW. (Table 2 and Table 4).

Table 2. Degrees of freedom F ratio and level of significance for grain yield, Harvest Index (HI),
Total N uptake, Grain N concentration and Nitrogen Use Efficiency.
Source of variation DF Grain HI Total N Grain N NUE TKW
yield Uptake (%)
Genotype 5 0.94 1.46 0.69 1.49 0.95 6.49**
Fertilizer 1 12.75** 0.68 65.6** 19.65** 18.51** 2.94
Genotype*Fertilizer 5 0.85 0.51 0.97 0.42 0.46 1.12
** Significant at (p<0.01)


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Table 3. Variety yield parameters measured across fertilizer levels at Kajiado
Variety Spikes/m2 Grain yield kg Harvest TKW
ha 1 index (HI)
Duma 182 1853 0.40 A 38.9 B
Ngamia 179 1751 0.38 AB 35.6 BC
Njoro bwl 173 1491 0.37 AB 37.9 BC
Chiriku 170 1642 0.37 AB 34.6 C
Heroe 163 1417 0.31 B 39.0 B
Chozi 150 1522 0.37 AB 44.0 A
LSD 5% NS NS 0.06 3.8
C.V % 24 26.2 15.7 8.3

Table 4. Fertilizer effects on yield parameters measured across varieties at Kajiado
Fertilizer level Grain yield Harvest TKW NUE Total N Uptake Grain N
kg ha-1 index g grain g'- g m-2 Concentration
N (%)

O 1361 B 0.37 A 39.2 41.8 a 330 a 0.38 a
NXP 1864 A 0.36 A 37.4 31.9b 600 b 0.36 b
LSD 5% 29.4 NS NS 0.05 69.6 0.04


There were no significant differences between genotypes in either nitrogen uptake
(acquisition) or utilization of the absorbed N: there were no significant differences in NUE
(grain production per unit of the total N ) (Table 5) However, cv. Njoro BW1 had a
significantly higher N concentration than c.v Ngamia. It has been shown that grain yield is a
function of NUE, total N uptake and HI as in the equation of Inthapanya et al. (2000).

Y=NUE X Total N uptake x HI

Where NUE= Nitrogen Use Efficiency
Hi=Harvest Index.

The results from this study show that of the three variables, the tested cultivars only
differed in HI, suggesting that the only potential for increasing yields in the wheat cultivars
would be in improving the HI of the cultivars.

Table 5. Total N uptake, grain nitrogen concentration and nitrogen use efficiency (NUE) meaned
over two fertilizer levels in wheat at Kajiado
Variety Total Nitrogen Uptake g m-2 Grain N Concentration (%) Nitrogen Use
Efficiency (NUE) g
grain g-1 N
Duma 5.22 2.08 Ab 38
Njoro BW1 4.72 2.17 A 33
Chiriku 4.67 1.96 Ab 37

Ngamia 4.60 1.87 B 40
K. Heroe 4.50 1.93 Ab 34

Chozi 4.18 2.00 Ab 39
LSD NS 0.26 NS
C.V 2.15 10.8 18.8
Means followed by the same letter are not significantly different at p>0.05


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










References

Inthapanya P., Sipaseuth, Sihavong P., Sihathep V., Chanphengsay M., Fukai S., Basnayake J. 2000.
Genotype differences in nutrient uptake and utilization for grain yield production of rainfed
lowland rice under fertilized and non-fertilized conditions. Field Crops Research 65 (2000)
57-68.
El Bassam N. 1998. A concept of selection of low input wheat varieties. Euphytica 100 (1/3) 95-
100.Improvement of Wheat


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Improving Wheat Productivity for the
Drought Prone Areas of Kenya Using the
Doubled Haploid Technique

Njau P. N1, Kimurto, P.K2, Kinyua M. G1, Okwaro H. K1 and Ogolla J.B.02
1. National Plant Breeding Research Center, Njoro, P.O. Njoro, Kenya'1
2. Dept. ofAgronomy, Egerton University, P.O. Box 536, Njoro, Kenya

Abstract- Various breeding methods have been applied in an effort to develop
superior wheat varieties for the marginal areas of Kenya. These include germplasm
introductions, mutation breeding and doubled haploid (DH) production. .The
application of DH in breeding for drought tolerance has proved to be very effective
and efficient. This study was aimed at evaluating and validating DH lines that were
developed in 2000 using the chromosome elimination technique. The resulting lines
were compared with other lines introduced from CIMMYT and two mutants
developed in Njoro. The lines were tested in multi-locational trials in 2002 and
2003. The sites included were Lanet, Mogotio, Naivasha, Mweiga, Kajiado and
Katumani. The results show that the DHs were as good as the conventionally
developed lines and yielded more than the check varieties Chozi and Duma. One of
the DHs had average yielded 1.7tonsHa1, which was not significantly different from
Chozi. The DH technique has proved to be applicable in saving time of breeding
without compromising the output.

Introduction
Wheat is the second most important cereal crop in Kenya (FAO, 2002) but Kenya's current
national wheat production (approximately 300,000 tons per annum) meets only about 50% of
the national demand. Moreover, increasing population and changing eating habits is
expected to have a bigger impact on wheat demand; estimated to reach 850,000 tons p.a. in
the year 2020 (FAO 2003). Land area currently suitable for wheat production in the high
potential areas is less than 2% and hence expansion of wheat production in these regions is
limited. In recent years wheat production has expanded in the marginal rainfall areas (such
as lower Narok, Naivasha, Laikipia and Machakos) which were hitherto considered unsuitable
for wheat growing. Introduction of wheat in the non-traditional areas began in 1992. Over this
period 4 varieties (Duma, Ngamia, Chozi and Njoro BW1) have been released (Kinyua et al,
2002). However, varieties with greater yields are still needed to meet the farmers' needs.
Future production increases must come largely from vertical expansion (i.e., greater
production per unit area), which will require more intensive research to further improve yield
potential and cultural technology. Wheat improvement in Kenya has been directed into
developing broadly adapted, high yielding germplasm with high yield stability, durable
disease resistance and acceptable end use quality (CIMMYT 2002). Resistance to biotic stress
and tolerance to abiotic stress can be critically important in maintaining high yield and
adaptation over time and locations. Over the last decade wheat breeding has been enhanced
by the application of various biotechnological approaches; these have been used to accelerate
the breeding process and also complemented the conventional breeding methods. The DH
technique and mutation breeding have been used to improve stress tolerance in wheat. These
include breeding for drought tolerance, tolerance to soil acidity, lodging tolerance and
resistance to Russian wheat aphid.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Drought is a multidimensional stress affecting plants at various levels of their organisation
(Blum, 1996). Improvement of yield under stress must combine a reasonably high yield
potential with specific plant factors which would buffer yield against severe reduction due to
drought (Blum, 1983). Measurement of plant response to drought at the whole-plant level is
complex because it reflects the integration of stress effects and responses at all underlying
levels of organisation, over space and time (Blum, 1996). Conventional breeding (which
involves multi-location testing and hence gauges spatial adaptation of genotypes) is used
extensively by the Kenya bread wheat program to identify temporally stable, drought tolerant
germplasm (Maarten, 1994 this does not appear in the reference list). However, practical
breeding programs for self-pollinated crops (such as wheat) must include a process of genetic
fixation (for uniformity of agronomic traits) after genetic recombination to increase variability
(Inagaki, 1996). Repeated selection ofheterozygous material can increase uniformity but
many generation cycles are required to reach homozygosity in loci associated with agronomic
traits. Haploid production followed by chromosome doubling offers a quick method for
developing homozygous breeding lines (Bentolila et al, 1992, Murignaux et al. 1993,
Beanziger et al., 1989a, Baenziger, 1996). The DH lines derived from hybrid progenies can
be used as recombinant inbred lines with favourable gene combinations (Inagaki, 1996). This
technique could thus complement the conventional breeding programs to accelerate the
release of new varieties.
Since the double haploids are completely homozygous, all stocks are identical and no
purification process is required. In contrast, in the conventional system stocks are usually
derived from a single plant of an advanced generation (Baenziger, 1996) hence several
generations are required to build up sufficient quantities of seeds for release. Compared to
selection during the early generations a DH system increases the efficiency of selection for
both qualitative and quantitative characters. This study aimed to evaluate and validate DH
lines and compare them with conventionally bred materials. It was hypothesised that the
DH technique is superior to conventional breeding when dealing with complex factors like
drought.

Materials and Methods
Introduction
Two experiments were carried out. Experiment I involved development of the double
haploids (including embryo rescue, regeneration of haploid plantlets and chromosome
doubling of haploids) and preliminary evaluation of the DHs. Experiment II was a field
evaluation of the performance of the DHs as compared with the conventionally developed
lines

Development of doubled haploids
Six F1 hybrids were produced by crossing three drought tolerant lines (Duma, K. Mbweha and
Ngamia) as females with two high yielding commercial varieties (Kwale and Kenya Chiriku)
as males. The F1 plants were emasculated at anthesis. The glumes and awns were not clipped,
as is the case with normal-crossing emasculation. The emasculated spikes were then covered
with polyethylene bags to maintain high humidity. One day before (predicted) anthesis,
emasculated spikes were pollinated with freshly collected maize pollen. The pollen was
collected by picking mature anthers and placing them on petri-dishes. Once the anthers burst
to release the pollen, a soft brush was used to brush the emasculated spikelets with the pollen.
Extreme care was taken not to damage the stigma. After pollination, the uppermost intemodes
of wheat culms (with pollinated spikes) were injected with a 100mg 1-1 2, 4-D solution daily
(for two consecutive days) to increase the rate of fertilisation and embryo formation.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










After about 14 days of spike growth, wheat caryopses were removed from spikes and
sterilized (in 2% sodium hypochlorite) for 15 minutes. After rinsing with sterilized water
(under laminar flow bench), embryos were aseptically excised and transferred onto half
strength Murashige and Skoog medium supplemented with 20g L-' sucrose and 8g L-' agarose
in petri dishes (Inagaki 1996). These were then placed in the fridge (at 4 oC) for three days
after which they were incubated (at 25 oC) in the dark until embryos germinated (5-7 days).
The germinated embryos were transferred to a lighted growth room with controlled
temperature of 24 oC and 16 hours day length. The light intensity was Ca 5000 Lax. Cultured
plants with fully developed roots and leaves were transplanted to potted soil for further
growth. The temperature was maintained at 21 C -25 oC using 24 hours day length. The size
of the stomata was used to determine the ploidy level of the plants. This is because haploid
plants have stomata half the size of diploid plants. At the third tillering stage, a leaf from each
plant was cut and coated with clear nail varnish. The varnish was pealed off (upon drying)
and mounted on high power objective of light microscope; the size of the stomata was then
compared with that of known diploid plants.
In addition, at the third tillering stage the plants were watered and then removed from the
pots. The roots were trimmed to about 2 cm below the crown (to increase solution
absorption). The plants were then immersed in colchicine solution (0.2% colchicine, 2%
dimethyl sulfoxide and 15 drops oftween-20) for 3 hours at room temperature. The plants
were then washed thoroughly with running tap water for 3 hours after which they were
planted in pots (using forest soil enriched with copper dust) at a temperature of 200 C-25 o C
under high humidity (90-100%).

Preliminary evaluation of the doubled haploids
Twenty DH lines were selected (based on the amount of seed available). These selections and
their five parents were initially screened in the rain-shelter at the National Plant Breeding
Research Centre (NPBRC) Njoro in 2000 and later evaluated in the field (in Njoro and
Katumani) through observation trials in 2001. They were planted in a randomized complete
block design (RCBD) with three replications. Each plot was 1 metre long with two rows 20
cm apart. Five seeds were planted per row. DAP (18-46-0) fertilizer was applied at planting at
the rate of 150 kg ha'. Drip irrigation was used to water the plots (Chapin Watermatics,
1999). Water was applied at the rate of 20 mm every fortnight (up to grain filling stage),
giving a total of 200 mm water during the crop season. The amount and frequency of water
application simulates the amount and nature of rainfall pattern usually received in most
marginal areas during the cropping season (Mugo et al., 1998; Jaetzold and Smith, 1983).
The following parameters were measured (both in the rain shelter and in the field): Ear length
(measured from the base of the spike to the tip of the apical spikelet, excluding the awns);
number of spikes per plant, sterile spikelets per head; number of grains per head counted on
10 spikes selected randomly in each experimental at maturity; and weight of 10-kemels (g).
All the data was subjected to analysis of variance using the general linear model (SAS, 1996).

Field performance of the double haploids
Eight DH lines (DH4, DH5, DH6, DH7, DH9, DH12, DH15, DH16) and 2 mutants (BM1 and
BM3) were selected in a preliminary yield trial in 2001. The selection was on the basis of
drought tolerance. These lines, together with Chozi and Njoro BW1 (checks), were entered in
the National Performance Trial (NPT) in 2002 and consequently planted at three sites (i.e.,
Naivasha, Katumani, and Lanet). The design was a RCBD replicated 3 times. The seeds were
drilled in plots of four rows that were 6 metres long and 20 cm apart.
Seven DHs (DH4, DH5, DH6, DH7, DH9, DH12 and DH16) were selected form the first year
of NPT and entered into the second year of National Performance Trial (in 2003) alongside 7


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










conventionally developed lines (R840, R960, R962, R963, R965, R966 and K7872) and the
check varieties (Njoro BW1 and Chozi). These were evaluated at Katumani, Naivasha,
Mweiga, Lanet and Ravine. The Design was a RCBD replicated three times. The plots were 4
rows, 20 cm apart and 6 m long.
The following parameters were measured in both the first and second year NPT: grain yield,
Kernel weight, plant height and reaction to rust diseases.
ANOVA was used for data analysis and means were separated using LSD

Results and Discussion
Development of Doubled Haploids
A total of 1800 florets were cross pollinated out of which 890 Fl seeds were harvested and
the embryos excised and planted in-vitro. This shortened the Fi seed production by over four
months compared to the in-vivo method where the seed is left to dry in the field. The in-vitro
F1 plants grew faster due to the conducive environment and reached heading stage one month
earlier than in the conventional method.
Over 2,880 florets of F plants were cross pollinated with maize. 413 of these developed
seeds from which 57 embryos were rescued (Table 2). Out of the 57 embryos rescued 46
were haploid. When treated with colchicine 24 of the 40 survived. The time taken for
pollination to colchicine treatment was 8 weeks and the DHs were ready for harvesting in 20
weeks.

Performance of doubled haploids
There was high variability among the DHs in the rainout shelter for the yield components
measured (Table 1). These results are comparable to those reported by Baenziger (1996);
whilst there was variation among doubled haploid lines, there was little variation within
individual haploid lines. This increased the efficiency of selecting lines with superior
characteristics (Njau et al, 2000) because the response to selection is indicated by the
variability between the treatments. Such variation can be used to select lines with the required
characteristics (Njau 2001).
There were significant differences in yield and other growth parameters between the
DHs and their respective parents (Table 1) and some DHs showed heterosis for drought
tolerance over their better parent or the mean of the two parents (Table 4). For example, one
of the DHs (DH17) developed from the cross between Kenya Mbweha and Kenya Chiriku had
greater number of spikes (6.1) than the parents (2.0 and 5.0, respectively for Kenya Chiriku
and Kenya Mbweha). DH17 also had more grains per head (43) than the mean of the parents
(27.5). DH 12 (developed from Duma/Kenya Chiriku cross) had more grains (%) than either
of the parents. The expression of heterosis in DH lines (Njau 2002) makes the DH technique
superior to that of conventional breeding. This is because heterosis is lost in conventional
breeding due to repeated selfing of the hybrids. Similar results have been reported elsewhere
(Ba-Bong and Swaminathan, 1995).
Over 26% of the cost of developing a fixed line using conventional selection was saved
in the production of the DHs (data not provided). This saving was attributed to the fewer
number of generations required to produce homozygous lines when using haploids. Similar
findings have been reported in rice (Sunint, 1993).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












Table 1. Mean performance for various parameters of 20 DHs as compared to their parents
tested for drought tolerance under the rainshelter at Njoro. Kenya.
Parents DH lines No. of tillers Effective Spikelets/He Sterile Grains/ weight of
at booting Heads ad Spikelets head 10 grains


K. Mbweha 5.00 5.0 15.333 2.000 24.333 0.367
Kwale 4.21 2.16 14.533 3.994 27.936 0.306
(K.mbweha x DHl1 5.33 4.00* 16.000** 2.00* 34.00 0.301
Kwale) DH18 5.71 3.67* 17.533** 2.494* 35.936 0.317**
DHl19 3.71" 3.66 15.533 1.494* 32.936 0.27*
K. Chiriku 4.33 2.00 15.333 3.000 30.667 0.312
(K. Chiriku x DH17 7.39** 6.11** 19.301 2.009 43.489*** 0.282
KMbeha) DHl14 2.67* 2.33 17.333 1.333* 36.667** 0.343

Ngamia 3.67 3.00 10.00 1.667* 41.667 0.349
(Ngamia x DH12 4.39 4.11 19.301** 1.009* 41.489** 0.336
Kwale) DH13 5.21 3.66 16.033** 1.995* 24.94' 0.21*
DH11 4.33 2.00* 13.333 1.006* 27.67* 0.346
DHil3 4.30 3.95 15.349** 1.996* 41.755** 0.304
DHil5 3.33* 3.33 15.333** 0.67*** 30.00* 0.367
DHil6 8.39** 6.1*** 19.301** 0.09*** 28.489 0.304


(Ngamia DHil7 0.803* 0.45** 13.765 4.980** 4.33** 0.12**
xK.Chiriku) DH120 5.00 4.33 14.000** 1.667** 28.67* 0.19**
Duma 6.33 3.00 15.000 2.000 28.333 0.467
DH14 2.80** 2.45 13.349 2.996 19.255 0.305*
(Duma x DH15 3.39 3.11 19.301 2.009** 35.489 0.310*
Kwale) DH16 7.39 2.89 14.617 1.510** 33.308 0.367*
DH19 7.00 4.00 11.333 2.333** 29.333 0.266*
DHl18 4.30 2.45 12.349 1.996** 32.255 0.326*


(Duma x DH1ll 3.71* 2.16 14.533 0.995 40.936* 0.307*
K.Chiriku) DHil2 5.67 3.67 17.333 2.000 44.00** 0.421**
Significantly better at 5% level than the poorer parent.
** Significantly better than the mean of the parent at P<0.5
*** Significantly better than the better parent at 5 % level
SSignificantly poorer than the better parent at 5 % level.
Significantly poorer than the poor parents at 5 % level.

Preliminary performance of the double haploids
Significant differences in yield Among genotypes were noted in Katumani and Naivasha
while no differences were noted in Lanet. Two lines DH6 and DH4 performed quite well at
all the sites. DH6 was better than all the other entries in Naivasha and it was better than the
checks at all the sites. DH7 and DH9 also performed well at all the sites


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Table 2. Grain yield of the test lines (DHs, mutants and check varieties) at 3 different sites (t ha-1)
LINE YIELD (t ha ')
KATUMANI NAIVASHA LANET
DH4 .9AB 1.OBC 1.4AB
DH5 .3E .3D 1.1B
DH6 .9AB 1.5A 1.5AB
DH7 1.OA 1.3AB 1.1B
DH9 .7BCD 1.4AB 1.6A
DH12 .7ABCD .9C 1.2AB
DH15 .7CD .7C 1.3AB
DH16 .8ABC .8C 1.2AB
BM1 .6CD .8C 1.OB

BM3 .7BCD .7C 1.3AB
NJORO BW1 .8ABC .9C 1.3AB
CHOZI .5DE. .9C 1.1B
LSD .27 .37 0.56
SE 0.22 0.11
P(F-ratio) <0.05 <0.05 <0.05
Values followed by the same letter are not significantly different at p = 0.05

Genotype did not affect 1000-kernel weight in Katumani and Naivasha but did affect 1000-
kernel weight in Lanet (Table 3). The double haploids had greater 1000-kernel weight (16%
on average) than the check varieties and the mutant BM3 in Lanet (Table 3). Also, the mutant
BM1 had 9% 13% greater 1000-kernel weight than the double haploids in Lanet (Table 3).

Table 3. 1000 kernel weight of the entries in the three sites during the year 2002
Line 1000-Kerel weight (g)
Katumani Naivasha Lanet
DH4 76.6 73.4 83.1A
DH5 72.0 78.8 81.0AB
DH6 72.4 76.7 78.7AB
DH7 72.4 72.4 78.4AB
DH9 70.7 71.2 78.0AB
DH12 77.4 78.3 78.0AB
DH15 75.9 75.8 77.9AB
DH16 76.6 76.4 77.4AB
BM1 73.9 72.7 75.6AB
BM3 72.9 68.2 69.7CD
NJORO BW1 74.2 76.1 69.4CD
CHOZI 75.3 78.6 66.9D

Lsd -- 10.85
P (F-ratio) ns ns <0.05
SED 4.1 3.2 4.04
Values followed by the same letter are not significantly different at p = 0.05

Genotype affected the average coefficient of infection (ACI) by stem rust in 2002 (Fig 1).
Chozi (check variety) was more susceptible to stem rust than the double haploids (except
DH15 and DH16) and the mutants (Figure 1). NjoroBWl (check variety) had lower stem rust
infection than the mutants and most double haploids (DH5, DH9, DH12, DH15, DH16)
(Figure 1).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004








Fig 1. Stem rust average coefficiet of infection


80

60







o*
40

20

0

-2 i

Lines O



Performance of the DHs as compared to the conventionally developed lines
There was a significant effect of site on variety in terms of grain yield and hectolitre weight
in 2003 (Table 4). Katumani had lower yields than Lanet (by 80%), Mogotio (by 70%),
Naivasha (by 70%), Mweiga (by 30%) and Kajiado (by 30%). Kajiado and Mweiga also had
lower yields compared with Lanet (38%), Mogotio (31%) and Naivasha (31%) (Table 4). The
lower yield in Katumani (compared with other sites) could be due to the low rainfall (100
mm) recorded in Katumani during the growing period of the crop.

Lanet had lower hectolitre weight (by 20%, 19%, 10%, 13% and 7% for Mogotio, Naivasha,
Mweiga, Kajiado and Katumani, respectively) compared with the other sites (Table 4).
Katumani had 12%, 11% and 5% lower hectolitre weight than Mogotio, Naivasha and
Kajiado, respectively. Also, Mweiga had lower hectolitre weight compared with Mogotio
(9%), Naivasha (8%) and Kajiado (2%). Moreover, Kajiado had 6% lower hectolitre weight
compared with Lanet and Mogotio (Table 4).

Table 4. Average yield in tons per hectare and hectolitre weight in the six sites
Site Yield (t ha-') Hectolitre weight (g)
Lanet 1.8a 67.3d
Mogotio 1.7a 80.9a
Naivasha 1.7a 80.2a
Mweiga 1.3b 74.3c
Kajiado 1.3b 76.0b
Katumani 1.0c 72. c

Mean 1.5 75.1
LSD 0.18 1.70
SED 0.21 4.21
P (F-ratio) <0.01 <0.01
CV (0%) 29.7 5.6

The yields and hectolitre weight for the lines averaged across the sites are shown in Table 5.
Genotype affected grain yield and hectolitre weight (Table 5). Chozi (check variety) had 55%
greater yield than DH6 and DH16 and 113% greater yield compared with DH12.
NJOROBW1 (check variety) also had greater yield (by 88%) than DH12 (Table 5).
Chozi had greater hectolitre weight compared with R960, R962 and R966 (9%), K7872
(12%), R965 (10%), which are lines developed through conventional breeding (Table 5).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Chozi also had greater hectolitre weight (by 8% 13%; average 11%) compared with a
number of double haploid lines (DH4, DH9, DH5, DH7, DH16, DH12) (Table 5). The check
variety NJOROBW1 had 7% greater hectolitre weight than DH12 (Table 5). These results
show that in addition to being reducing the breeding time, lines developed using the DH
technique, compete well with conventionally developed lines which have taken over 13 years
to develop.

Table 5. Yield and hectolitre weight of the sixteen lines averaged over the sites
Line Yield (t ha-1) Hectolitre weight (g)
R960 1.9a 74.5bcd
DH4 1.7a 73.0cd
R840 1.7a 78.lab
Chozi 1.7a 81.3a
R966 1.6ab 74.3bcd
R963 1.6ab 76.6abcd
K7872 1.5abc 72.3cd
DH9 1.5abc 75.0bcd
NJBW1 1.5abc 77.0abc
DH5 1.5abc 73.5bcd
R965 1.5abc 73.9bcd
DH7 1.4abc 74.7bcd
R962 1.4abc 74.6bcd
DH16 1. bcd 72.9cd
DH6 1.lcd 78.0ab
DH12 0.8d 72.0d

Mean 1.5 75.1
LSD .29 2.77
SED 0.09 17.7
P (F-ratio) <0.01 0.01


Conclusion

The DH technique proved to be quite useful in breeding for complex characters such as
drought and compares well with the conventional methods. The time saved in DH
development makes the methodsuperior to the other methods. It is important to note that the
multiloctional testing increases the efficiency of measuring yield stability. The two lines
(DH4 and R960) are recommended for release as they both out yielded the check varieties at
almost all sites.


References
Ba Bong B. and M.S. Swaminathan 1995. Magnitude of hybrid vigour retained in double haploid lines
of some heterotic rice hybrids. Theo. Appl. Genet. 90:253-257.
Baenziger P.S. C.J Peterson, M.R Morris and P.J Mattern 1989a. Quantifying gametoclonal variation in
wheat doubled haploids. M. Muluszynski (Ed). Current Options for cereal improvement pp.
1-9. Kluwer Academic Publishers. Boston.
Baenziger S.P. 1996. Reflections on doubled haploids in plant breeding. S.M. Jains, S.K Sopory and
R.E Veilleus (Ed). In vitro Haploid production in Higher plants 1: 35-48. Klumer Academic
Publishers. Netherlands.
Bentolila S, T. Hardy, C. Guitton and G. Freyssient 1992. Comparative genetic analysis of F2 plants
and anther culture derived plants of maize. Genome 35: 575-582.
Bitch C., G. Sabine and J. Lelley 1998. Effect of parental genotypes on haploid
embryo and plantlet formation in wheat x maize crosses. Euphytica 103: 319-
323.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Blum A. 1996. Crop responses to drought and the interpretation of adaptation. Plant Growth
Regulation 20:135-148.
FAO, 1986. Production yearbook. Vol. 40. FAO ROME.
Inagaki M.N. (1990). Wheat Haploid through Bulbosum technique. Biotechnology in Agriculture and
Forestry 13:448-58.
Inagaki M.N. (1996). Technical advances in wheat haploid production using ultra-wide crosses.
IIRCAS Journal 4:51-62.
Jaetzold R. and H. Schmidt, 1983. Farm management Handbook of Kenya. MOA and GTZ.
Kinyua M.G. 1997. Transfer of genes of resistance to yellow rust (Puccinia stiifarmis L.) from wild
emmer Triticum dicoccoides into Kenyan wheat commercial varieties. PhD Thesis. Nairobi
University.
Kinyua, M.G,., Karanja, L., and Njau, P.N. 2002. Drought tolerant wheat varieties developed through
mutation breeding technique. Workshop on Dryland Farming January 2002. Paper submitted
and accepted.
Kinyua, M.G., J.K. Wanjama, J. Kamwaga, M. Migui 1989. The situation of wheat production in
Kenya KARI Report.
Lefebure D. and P. Devaux 1996. Doubled Haploid of wheat from wheat x maize crosses: genotypic
influence, fertility and inheritance of the IBL-IRS chromosomes. Theor. Appl. Genet. 93:
1267-1273.

Murignaux A., D. Barloy, P, Leray and M. Beckont 1993. Molecular and morphological evaluation of
doubled haploid lines in maize, Homogeneity within DH lines. Theor. Appl. Genet. 86:837-
842.
Njau P. N. 2001. Development of drought tolerant wheat lines through chromosome elimination
technique. Msc. Thesis. Egerton University.
Njau P.N., M.G. Kinyua and R.S. Pathak.2000. Drought Tolerant Doubled Haploid (DH) of Bread
Wheat for Kenya. Proceedings of the 7t Biennial KARI Scientific Conference Paper
No.40.KARI Headquarters. Nairobi.
Sunint L.R., C.P. Martinez, A. Ramirez and Z. Lentini, 1993. Rice anther culture versus conventional
breeding: A cost/benefit analysis. Trends in CIAT commodities working document NO.128.
Contro International De Agricultura Tropical, Call.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











Grain Yield Stability of Bread Wheat
Genotypes in Favorable and Stressed
Environments

Desalegn Debelo, Solomon Gelalcha, Balcha Yaie, Bedada Girma, Berhanu
Mamo, and Debebe Masresha

EARO, Kulumsa R. C., P. O. Box 489, Asella, Ethiopia
E-mail: (, k.. ,. I-,,:fi..i ioi,,;1 ,. t

Abstract-A multilocational trial consisting of 18 bread wheat genotypes including
standard and local checks was conducted in 39 locations between 1999 and 2001
across the diverse wheat agro-ecologies of Ethiopia. Yield stability of the genotypes
was assessed in high potential, moisture stress and waterlogged growing
environments using the AMMI (Additive Main Effects and Multiplicative
Interaction) model. The results showed highly significant genotypic and G x E
interaction affects in all three environmental categories. Genotypes FH 8-2, HAR
3354, ETBWC 037 showed low positive interaction while HAR 3116, and FH 6-1-7
showed low negative IPCA axis 1 scores indicating stable performance in the high
potential wheat growing areas. In the low moisture areas FH 8-1, ETBWC026, HAR
3224 and HAR 2870 showed low positive IPCA axis 1 scores. Among these
genotypes, HAR 2818 gave the highest mean grain yield and is better suited to
moisture stressed areas. The analysis of waterlogged areas showed that HAR 3354,
FH 4-2-11 and ETBWC037 had high mean grain yield performance and low G x E
interaction. From the results we concluded that FH 8-2, HAR 3354, ETBWC 037,
HAR 3116 and FH 6-1-7 are widely adaptable; FH 8-1, ETBWC026, HAR 3224 and
HAR 2870 perform better in the moisture stressed areas while FH 4-2-11 and
ETBWC037 are tolerant to waterlogged vertisols.

Introduction
In developing crop varieties with high and stable yields, data from multi-environments,
representing spatial and temporal target domains, play an important role in estimating and
predicting yield and yield stability. The pattern of response of genotypes to different
environments is used by the plant breeder to select the best varieties for any particular region.
Yield response of genotypes tested in different environments is almost always subject to
genotype x environment interaction (GxE). To estimate the level of interaction of genotypes
to environments and eliminate as much as possible the unexplainable and extraneous
variability contained in the data, several statistical techniques have been developed to
describe G x E and measure the stability of genotypes. These techniques include conventional
analysis of variance (Yates and Cochran, 1938; Cochran and Cox, 1957); the joint regression
method proposed by Yates and Cochran (1938),modified by Finlay and Wilkinson (1963) and
further improved by Eberhart and Russell (1966); combined analysis of variance for each pair
of genotypes (Plaised and Peterson, 1959); ecovalence (Wrickle, 1962;1964); stability
variance (Shuka, 1972); cluster analysis (Lin et al., 1986); and cultivar superiority measure
(Lin and Binns, 1988).
Furthermore, the additive main effect and multiplicative interaction method, widely
known as AMMI model, has recently been developed and used to analyze multi-


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










environmental trials (Gauch and Zobel, 1988; Zobel et al., 1988; Crossa et al., 1990). It is a
unified approach that fits the additive main effects of genotypes and environments by the
usual analysis of variance and then describes the non-additive part by principal components
analysis fitted to the AMMI model according to the following equation:

u
Yge = p + ag +pe + Z Agn n en + Oge,
n=l
where Yge is the yield of genotype g in environment e; PI is the grand mean;
ag are the genotype mean deviations (the genotype means minus the grand mean);
3e are the environment mean deviations; Xn is the eigenvalue of principal components
analysis (PCA) axis n; ygn and ygn are the genotype and environment PCA scores for PCA
axis n; u is the number of PCA axes retained in the model; Oge is the residual.

Wheat is a widely grown crop in the world, produced under a wide range of environments
(Hanson et al., 1982). In Ethiopia, wheat is grown between 6 and 140N latitudes; and between
35 and 420E longitude at altitudes from 1500 m to 3200 m. The current total area of
production of both durum (Triticum turgidum var. durum) and bread wheat (Triticum
aestivum) is estimated to be between 1.2 to 1.5 million hectares. The environmental variation
within the wheat growing range is noticeable over short distances. This type of environment
obviously affects the adaptation of a particular crop variety and complicates the process of
plant breeding.
To counterbalance this problem, categorizing environments and conducting multi-
environment variety evaluation and stability analysis are imperative. In the last two decades, a
considerable number of bread wheat varieties were released in Ethiopia; all were assessed for
adaptation and stability over different environmental categories before release (Desalegn et
al., 1996; Debebe et al., 2000; Bedada et al., 1999; Desalegn et al., 2001). The purpose of this
paper is to report on the stability of yield performance and yield potential of advanced bread
wheat genotypes in different environments in Ethiopia.

Materials and Methods
A national variety trial consisting of 18 bread wheat genotypes was conducted from 1999 to
2001 across the wheat growing agro-ecologies in Ethiopia. The genotypes included advanced
materials from a breeding program and selections from introductions. The entries were
established on six rows of 2.5m plots with a distance of 20cm between rows. The seeds were
drilled into the row at the rate of 150kg ha1. A randomized complete block design with four
replications was used at all locations. Site-specific agronomic practices were applied. The
central 4 rows were harvested to determine the yield potential of each genotype.
The testing sites included nine high potential locations, two waterlogged sites (Ginchi
and Arsi-Robe) and three moisture stress sites (Alemaya, Asasa and Dhera) as described in
Table 1.
For the three environmental categories, analysis of variance was performed on yield data
of individual trials and AMMI analysis was carried out separately on pooled data using
Agrobase 99 (Agronomix Software, Inc., 1999).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












Table 1. Environmental characteristics of national bread wheat testing sites in Ethiopia.
Location Altitude (masl) Long-term Major production constraints)
Annual
Rainfall (mm)
Kulumsa 2200 830 SR
Bekoji 2780 1098 YR, STB
Adet 2240 1250 SR
Holetta 2400 1078 STB
Arsi-Negele 1800 763 SR
Sinana 2400 1023 YR, SR, STB
Hossana 2450 YR, SR
Kokate 2150 SR, YR
Alemaya 1900 638 SR, drought
Ginchi 2100 1093 Waterlogging
Arsi-Robe 2400 873 Waterlogging
Asasa 2360 644 Terminal drought
Dhera 1680 617 Intermittent drought

SR= Stem rust; YR=yellow rust; STB=Septoria blotch

Results and Discussion
In high potential wheat growing areas, the AMMI analysis showed that environments,
genotypes and G x E interaction were highly significant. In this set of environment, IPCA 1
explained 33 per cent of the G x E interaction sum of squares and IPCA2 explained 23 per
cent of the interaction. The first principal component explained more of the interaction
variation and this could be interpreted in terms of morphological, phenological, agronomic or
disease factors that may affect the performance the genotypes (Table 2).
In the drought stressed sites, the environments, genotypes and G x E were highly
significantly different. About 41 per cent of the interaction sum of squares was explained by
IPCA1. IPCA2 and IPCA3 explained 17% and 14% of the interaction, respectively. The first
principal component factor has a high contribution to the interaction sum of squares while the
IPCA2 and IPCA3 are small. This indicates that one primary factor is influencing the G x E
interaction in this set of environment (Table 2).
Likewise, in the waterlogged areas the environments, genotypes and G x E interaction
were significantly different (Table 2). IPCA1 explained 42% of sum of squares of the
interaction, while IPCA2 and IPCA3 were responsible for 24% and 17 % of the interaction
sum of squares, respectively. This indicates that one fundamental factor affects G x E
interaction; this could be either genotypic or environmental in nature.
In AMMI analysis, IPCA scores of genotypes are stability indicators. IPCA scores closer
to zero (0), either from a positive or negative direction, indicate stable performance of
genotypes over sampled environments for the particular trait under consideration.
Accordingly, in high potential wheat growing environments, FH 8-2, which had IPCA
score nearest to zero (Table 3), was the most stable variety although it was low yielding. FH
8-2 was developed from a cross between Ethiopian and Germany materials for multiple
diseases resistance. Moreover, genotypes HAR 3316, HAR 3354, FH 6-1-7 and ETBWC 037
showed stable and predictable yield performance across the different environments (Figure 1).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004













TABLE 2. Analysis of variance for multi-environment bread wheat trial over the period of 1999
to 2001.
Source Favorable Environment Low moisture Water logged environment
environment
df MS Prob df MS Prob df MS Prob

Total 1799 57 43
5 1
Environments 24 43510329.0 ** 7 98028937.3 ** 5 160558072.6 **
Genotype 17 5002302.5 ** 17 2974331.8 ** 17 6143106.4 **
GxE. 408 1279672.6 ** 11 585980.1 ** 85 1158614.0 **
9
IPCA 1 40 4251121.2 ** 23 1234844.4 ** 21 1969767.6 **
IPCA 2 38 3222205.7 ** 21 565213.7 ** 19 1258203.6 **
IPCA 3 36 1396068.3 ** 19 499430.6 17 1023044.6 *
IPCA 4 34 1234018.4 **
IPCA 5 32 969418.0 **
IPCA 6 30 979453.2 **
IPCA 7 28 779923.7 **
Residual 1275 414285.4 40 284442.936 30 433747.8
8 6


*, ** =significant at 0.05 and 0.01 levels respectively


TABLE 3. Genotype IPCA Axis 1 Scores for High potential environment

No Genotype Score Mean No Genotype Score
1 a HAR 1522 20.5423 3688.481 11 11 HAR 2870 29.0941
2 b HAR 3224 16.4640 3908.44 1 10 10 HAR 2818 26.0322
3 c HAR 3116 -2.0432 4091.36 1 8 8 HAR 2812 20.8600
4 d HAR 3354 2.1311 4036.38 1 1 1 HAR 1522 20.5423
5 e ETBWC026 -10.4608 3621.87 1 2 2 HAR 3224 16.4640
6 f ETBWC028 -10.5972 3872.90 1 14 14 FH 9-3-4 10.7835
7 g ETBWC037 2.7556 3560.85 1 9 9 HAR 2814 7.7190
8 h HAR 2812 20.8600 3691.62 1 7 7 ETBWC037 2.7556
9 i HAR 2814 7.7190 3832.50 1 4 4 HAR 3354 2.1311
10 j HAR 2818 26.0322 3963.50 17 17 FH 8-2 1.1397
11 k HAR 2870 29.0941 3746.581 3 3 HAR 3116 -2.0432
12 1 FH 4-2-11 -17.3445 3787.62 16 16 FH 6-1-7 -2.5637
13 m FH 81 -27.9384 4039.08 1 5 5 ETBWC026 -10.4608
14 n FH 9-3-4 10.7835 4117.90 1 6 6 ETBWC028 -10.5972
15 o FH 7-1-5 -24.6687 4059.52 12 12 FH 4-2-11 -17.3445
16 p FH 6-1-7 -2.5637 3459.061 15 15 FH 7-1-5 -24.6687
17 q FH 8-2 1.1397 3372.47 13 13 FH 81 -27.9384
18 r L.CHECK -41.9050 3986.09 18 18 L.CHECK -41.9050


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












29.094

3
h
D b
G
II n
W R S XI
a P
N g d

V pA
wH s
e C




TI
= m I
-41.90 I
2535.8 3824.2 5109.3














BEKOJI 00, L=D-ZEIT 00, M= HOLETTA 00, N=HOSSAENA 00, O=KOKATE 00,
P=KULUMSA 00, Q=SINANA 00, R=A-NEGELLE 99, S=ADET 99, T=BEKOJI 99,
U=HOLETTA 99, V=HOSSAENA 99, W= KOKATE 99, X=KULUMSA 99, Y= SINANA
99; a=HAR 1522, b=HAR 3224, c=HAR 3116, d=HAR 3354,e=ETBWC026, f=ETBWC028,
g=ETBWC037, h=HAR 2812, I=HAR 2814,j =HAR 2818, k=HAR 2870, 1=FH 4-2-11,
m=FH 81, n=FH 9-3-4, o=FH 7-1-5, p=FH 6-1-7, q=FH 8-2, r=L.CHECK


Figure 1. AMMI biplot for bread wheat variety trial consisting 18 genotypes and 25
environments (high potential) over the period of 1999 to 2001. (Note: 1 genotype and 3
environments in place of others with similar means and not shown)



On the other hand, FH 8-1 and FH 7-1-5 showed high negative IPCA1 scores, which is
evidence of their specific adaptability to favorable environments. It was noted that the
genotypes have considerably high variation around the mean grain yield of 3824 kg ha'. The
test sites also showed year-to-year variation in mean grain yield and were evenly distributed
in all four quadrants indicating the importance of seasonal climatic variation. Clearly, two or
more seasons of testing are better than a single year.
High seasonal variation was observed among the drought stressed environments (Figure
2). This is probably attributable to seasonal rainfall variation both in amount and distribution.
The genotypes tended to vary widely in grain yield around the grand mean (3576.8 kg ha').
Among these genotypes, HAR 2818 gave the highest mean grain yield indicating that it could
be an ideal variety for low moisture stress areas; while ETBWC026 was the most stable
genotype in this environment (Table 4).


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












For water logged environment, genotypes like ETBWC037 and FH 4-2-11, which had IPCA
score close to zero, were found to perform stably and may be used in such areas as Arsi Robe
and Ginchi (Table 5)


39.3

















-29.4:
1998.


D q


........... ...C....
k m
.d
a.

1 o

3576.8


key for the letters in the AMMI biplot
A=AS01, B=DH01, D=ASOO, E=DHOO, F=AS99, G=DH99, H=AL99, I=AL01; a=HAR
1522, b=HAR 3224, c=HAR 3116, d=HAR 3354,e=ETBWC026, f=ETBWC028,
g=ETBWC037, h=HAR 2812, I=HAR 2814, j=HAR 2818, k=HAR 2870, 1=FH 4-2-11,
m=FH 81, n=FH 9-3-4, o=FH 7-1-5, p=FH 6-1-7, q=FH 8-2, r=L.CHECK

Figure 2. AMMI biplot for bread wheat variety trial consisting 18 genotypes and 9 environments
(moisture stress areas) over the period of 1999 to 2001.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004


B


5219.U












TABLE 4. Genotype IPCA Axis 1 Scores for Moisture stress environment


No Genotype Score Mean No Genotype Score
1 a HAR 1522 -8.4258 3571.911 8 HAR 2812 30.0680
2 b HAR 3224 -0.9773 3829.22 16 FH 6-1-7 18.7863
3 c HAR 3116 -19.9266 4065.53 18 L.CHECK 14.0816
4 d HAR 3354 -4.8353 3701.38 9 HAR 2814 8.0520
5 e ETBWC026 0.2994 3561.94 17 FH 8-2 5.5885
6 f ETBWC028 4.4483 3638.341 6 ETBWC028 4.4483
7 g ETBWC037 3.9407 3348.19 7 ETBWC037 3.9407
8 h HAR 2812 30.0680 3445.28 5 ETBWC026 0.2994
9 i HAR 2814 8.0520 3545.06 2 HAR 3224 -0.9773
10 j HAR 2818 -5.8004 4134.16 13 FH 81 -2.1974
11 k HAR 2870 -2.9071 3390.59 11 HAR 2870 -2.9071
12 1 FH 4-2-11 -13.4219 3373.72 4 HAR 3354 -4.8353
13 m FH 81 -2.1974 3680.75 10 HAR 2818 -5.8004
14 n FH 9-3-4 -13.3237 3891.50 1 HAR 1522 -8.4258
15 o FH 7-1-5 -13.4493 3535.34 14 FH 9-3-4 -13.3237
16 p FH 6-1-7 18.7863 2938.75 12 FH 4-2-11 -13.4219
17 q FH 8-2 5.5885 3054.97 15 FH 7-1-5 -13.4493
18 r L.CHECK 14.0816 3676.22 3 HAR 3116 -19.9266

TABLE 5. Genotype IPCA Axis 1 Scores for water-logged environment

No Genotype Score Mean No Genotype Score
1 a HAR 1522 1.0963 4994.58 6 ETBWC028 21.1901
2 b HAR 3224 -3.0194 5094.63 17 FH 8-2 18.9806
3 c HAR 3116 -12.8362 5441.63 16 FH 6-1-7 12.4562
4 d HAR 3354 -1.9025 5489.25 15 FH 7-1-5 11.3533
5 e ETBWC026 -15.6519 4746.42 11 HAR 2870 9.9798
6 f ETBWC028 21.1901 4486.79 18 L.CHECK 9.9606
7 g ETBWC037 1.8652 4576.63 10 HAR 2818 6.9080
8 h HAR 2812 -9.4631 4733.50 7 ETBWC037 1.8652
9 i HAR 2814 -3.0989 4962.17 12 FH 4-2-11 1.6042
10 j HAR 2818 6.9080 5120.92 1 HAR 1522 1.0963
11 k HAR 2870 9.9798 4760.33 1 4 HAR 3354 -1.9025
12 1 FH 4-2-11 1.6042 4129.79 2 HAR 3224 -3.0194
13 m FH 81 -16.7825 4533.42 9 HAR 2814 -3.0989
14 n FH 9-3-4 -32.6399 5225.58 8 HAR 2812 -9.4631
15 o FH 7-1-5 11.3533 4313.711 3 HAR 3116 -12.8362
16 p FH 6-1-7 12.4562 4298.67 5 ETBWC026 -15.6519
17 q FH 8-2 18.9806 3399.08 13 FH 81 -16.7825
18 r L.CHECK 9.9606 4744.17 14 FH 9-3-4 -32.6399


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004













33.7








0





-32.6 h
rr







e
EDI







3272 4725 1 739O_4





Key for the letters in the AMMI biplot
A=Arsi-Robe 01, B Ginchi 01, C=Arsi-Robe 00, D Ginchi 00, E Arsi-Robe 99, F Ginchi 99; azHAR1522,b=HAR3224c-HAR3116,
d=HAR3354e=EIBWC026,f-EIBWCOI2g=EIBWC37,h=IAR2812ZI-IAR2814j-AR2818, k HAR2870,1=FH42-l11,n=FH81, n=FH9-3-40FH7-1-5,
p=FH6-1-7,q=FH8-ZriLCHECK

Figure 3. AMMI biplot for bread wheat variety trial consisting 18 genotypes and 6 environments
(water logging stress) over the period of 1999 to 2001. (Note: one environments in place of other
with similar means and not shown)


The genotypes were ranked for their yield stability in the favorable environments
according to each genotype by environment interaction statistical analysis procedure
used.(Table 6). Spearman's rank correlation coefficient was computed for each of the
possible pairs of the G x E statistics (Table 7). Student's t test for the Spearman's rank
correlation coefficients showed no significant correlation with AMMI, but was highly
significantly associated with the other procedures. A similar trend was noted for the two
extreme moisture stress environments (data not presented). Clearly, the stability analysis
procedures do not conform to AMMI analysis.
From the results, we can conclude that HAR 3116 and HAR 3354 are high yielding and
stable across high potential environments; HAR 3224 and HAR 2818 perform better in the
drought stress environment while FH 4-2-11 and ETBWC037 are tolerant to waterlogged
vertisols.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004











TABLE 6. Estimates of various G x E statistics and stability parameters for 18 bread wheat genotypes
grown at 25 environments during 1999 to 2001.
No Genotypes Cultivar Supernonty Ecovalence, Stability Vanance Beta Deviation
Measure, Lin and Wricke Shukla Finlay and from
Binns Wilkinson Linearity
1 HAR 1522 996717 5817426 1010788 1011008 0.7T 121138
2 HAR 3224 735159 4445462 753545 784681 1T.035 70T43
3 HAR 3116 525681 5887418 T1023911 97 553 1.180T 113926
4 HAR 3354 530726 5952597 1036132 993175 1.178 117176
5 ETBWCO26 973059 5052679 867398 835330 0.841 82099
6 ETBWCO28 716908 9040414 1615098 1681013 1.047 270028
7 ETBWC037 1024086 2243215 340623 300359 0.858 -36784
8 HAR 2812 1086634 7680015 1360023 1308673 0.801T 187286
9 HAR 2814 767383 6031427 1050913 1057356 1120I 131438
T--10 HAR2818 828490 7437071 1314471 1372687 0.983T 201512
11 HAR2870 1084103 9258608 1656010 1724961 0.958 279795
12 FH4-2-11--743175 7003698 1233214 1282976 0.955 181576
13 FH 81-- 463092 8720217 1555061 1593398 1.105 250558
14 FH 9-3-4 555071 7247264 1278882 1336333 0.995 193433
15 FH 7-1-5 422436 6374056 1115156 1140053 1.095 149815
16 FH6-1-7-- 1279747 10782393 1941719 2027627 0.988 347054
T7-- FH 8-2 1288069 2611873 -409747 429482 1.001T -8090
18 L.CHECK 708448 18940766 3471414 3623810 0.987 T0176


TABLE 7. Spearman's rank correlation for various stability parameters
Cultivar Ecovalence Stability Stability Deviation AMMI
Superiority (Wricke) Variance Variance from
Measure (Shukla) (Finlay & Linearity
Wikinson)
Cultivar U.--- U.88* .-ns U.66* TT.36
Superiority
Measure
Ecovalence 1.uu -- .9 U.9u- .1T3
(Wricke)

Stability 99* U. 99. 1.3
Variance
Shukla)
Stability U.9-0* -.T14
Variance Finlay
& Wikinson)
Deviation from U.4
Linearity
*Student's t test is significant at 0.01 level of signficance


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












References

Bedada Girma, Desalegn Debelo and Bekele Geleta. 1999. Evaluation and characterization of some
bread wheat genotypes for waterlogging tolerance in Ethiopia. African Crop Science
Proceedings, vol.4.pp.113-116, Uganda.
Crossa, J. 1990. Statistical analysis of multilocation trials. Advances in Agronomy 44: 55-86.
Cochran, W. G. and Cox, G. M. 1957. Experimental designs. John Wiley &Sons Inc., New york, 2nd
Ed.
Debebe Masresha, Desalegn Debelo, Bedada Girma, Solomon Gelalcha and Balcha Yaie.2000. Bread
wheat yield stability and environmental clustering of major wheat growing zones in Ethiopia.
pp. 78-86. In: CIMMYT. 2000. The Eleventh Regional Wheat Workshop for Eastern, Central
and Southern Africa. Addis Ababa, Ethiopia: CIMMYT.
Desalegn Debelo, Bekele Geleta, Balcha Yaie and Zewdie Alemayehu. Grain Yield Response of Some
Bread Wheat Cultivars in Diverse Environments of Ethiopia. pp.382-86. In: Tanner, D. G.,
Payne, T. S., and Abdalla, O. S. Eds. 1996. The Ninth Regional Wheat Workshop for Eastern,
Central and Southern Africa. Addis Ababa, Ethiopia: CIMMYT.
Desalegn Debelo, Bedada Girma, Zewdie Alemayehu and Solomon Gelalcha. 2001. Drought tolerance
of some bread wheat genotypes in Ethiopia. African Crop Sci. J. 9(2): 385-392.
Eberhart, S. A. and W. A. Russell. 1966. Stability parameters for comparing varieties. Crop sci.6: 36-
40.
Finlay, K. W. and G. N. Wilkinson. 1963. The analysis of adaptation in plant breeding programs.
Austral. J. Agri. Res. 14: 742-754.
Guach, H. G. 1988. Model selection and validation for yield trials with interaction. Biometrics 88: 705-
715.
Guach, H. G. and R. W. Zobel. 1988. Predictive and postdictive successes of statistical analysis of yield
trials. Theor. Appl. Genet.76: 1-10.
Hanson, H., Borlaug, N. E. and Anderson, R. G. 1982. Wheat in the third world. Boulder, CO, USA,
Westview Press.
Lin, C. S. and Binns, M. R. 1988. A superiority measure of cultivar performance for cultivar x location
data. Can. J. Plant Sci. 68: 193-198.
Plaised, R. L. and Peterson, L. C. 1959. Atechnique for evaluating the ability of selection to yield
consistently in different locations and seasons. Amer. Potato J. 36: 381-385.
Shukla, G. K. 1972. Some statistical aspects of partitioning genotype-environmental components of
variability. Heredity 28: 237-245.
Wright, A. J. 1971. The analysis and prediction of some two factors interactions in grass breeding. J.
Agric. Sci. 76: 301-306.
Yates, E. and Cochran. 1938. The analysis of grouped experiments. J. Agric. Sci. 28: 556-580.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Seedling and Adult Plant Resistance in
Ethiopian Wheat Varieties to Local Puccinia
graminis Isolates

Emebet Fekadul, Belayneh Admassu2 and Zerihun Kassaye

Ethiopian Agricultural Research Organization, Plant Protection Research Center,
P.O. Box 37, Ambo, Ethiopa: E-mail: 1' ,. i,. r i ,,....... .-.11 2 belayl20@yaho.com

Abstract-Wheat entries showing resistance to stem rust at the seedling stage do not
necessarily possess adult plant resistance, and vice-versa. This investigation was
therefore undertaken to evaluate some wheat varieties from Ethiopia for their
resistance to four virulent stem rust isolates collected from Ambo and Debre Zeit
(two isolates from each locality) at seedling as well as adult plant stages. Out of 15
durum (Triticum turgidum) and 14 bread wheat (T. aestivum) varieties tested, 10
durum and 7 bread wheat varieties were found to be resistant both at the seedling and
adult stages to the first Ambo isolate. Whereas 11 durum and 13 bread wheat
varieties were resistant to the second isolate at both growth stages. Eight durum and 8
bread wheat varieties exhibited a resistant infection type to the two Debre Zeit
isolates at both growth stages. Some materials, for instance durum wheat varieties
Kilinto and Gerardo were resistant at the seedling stage but were susceptible at the
adult stage, whereas variety DZ 169505 exhibited a susceptible and resistant reaction
at the seedling and adult stages respectively to the first Debre Zeit isolate. Our results
indicate that selection for resistance must involve rigorous field evaluation with a
range of isolates to achieve effective resistance.



Introduction
Stem rust, caused by Puccinia graminis f. sp. tritici, occurs every year in the wheat growing
regions of Ethiopia. For over 20 years, stem rust has been controlled through the use of
resistant cultivars. Appearance of new races and conditions favorable for diffusion of the
pathogen enhance the likelihood of epidemics that may significantly reduce wheat yield.
Although host resistance is the best method to avoid epidemics and minimize yield losses,
changes in pathogen virulence and the attendant loss of resistance complicates this control
strategy. Goludan et al. (1928) reported that adult plant resistance was inherited
independently of seedling resistance. Mutkekar et al. (1985) also reported similar results
stating that entries showing resistance at the seedling stage do not necessarily posses adult
plant resistance and vice-versa. The present investigation was undertaken to evaluate selected
wheat varieties for their resistance to stem rust at seedling as well as adult plant stages. The
resistant varieties are recommended as the best sources for breeding programs.

Materials and Methods
Stem rust field populations from Ambo and Debre Zeit were multiplied on the adult plants of
the susceptible variety Morocco in a greenhouse under conditions favourable for the
development of the pathogen. Two most virulent isolates from each location were selected for
the present study.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Four sets of the seedlings and adult plants of 29 bread and durum wheat cultivars were grown
in 4*4 cm size earthen pots in a glass house where they were maintained disease free. After
inoculating seedlings at 2-leaf stage and adult plants at 5-leaf stage with individual races, each
set were placed in a moist chamber for 24 hours for incubation and then transferred to glass
house benches for the development of uredinia (pustules). Rust reactions were recorded about
14 days after inoculation by following the 0-4 scale (Stakman and Levine, 1922) where 0 -;
= immune, 1-2 = resistant, and 3 and 4 = susceptible.


Results

Seedling and adult plant reactions of the cultivars are given in Tables 1 and 2 for isolates from
Ambo and Debre Zeit, respectively. Variety 2 exhibited highly resistant reactions to both
isolates at both growth stages with Ambo isolates whereas varieties 5, 6, 7, 9, 10, 11, and 14
exhibited moderately resistant reactions and hence are suggested to be used as alternatives
(Table 1).
Bread wheat varieties exhibited highly resistant reaction compared to durum wheats.
Some varieties were immune to the pathogen isolates at either of the two growth stages.
Varieties 8 and 9 were highly resistant with immune or resistant reactions to the Ambo
isolates at both growth stages. Varieties 3, 7, 10, 13, 14 had a reaction type ranging from
immune to moderately resistant (Table 1). Hence, these varieties could provide additional
resistance sources. With Debre Zeit isolates varieties 8, 9, 13 had immune to highly resistant
reaction type. As alternatives 2, 3, 10, 12 and 14 could be used as their reactions ranged from
immune to moderately resistant to the two pathogen isolates (Table 2).
Some materials, for instance durum wheat varieties Kilinto and Gerardo were resistant at
the seedling stage but were susceptible at the adult stage, whereas variety DZ 169505
exhibited a susceptible and resistant reaction at the seedling and adult stages, respectively to
the first Debre Zeit isolate (Table 2). Resistance that could be to all isolates can be generated
by carefully choosing the right parents based on the data we have presented here.



Table 1. Reaction of seedling and adult wheat plants to p.graminis isolate from Ambo

Isolate 1 Isolate 2
Plot no. Variety Seedling Adult infection Seedling infection Adult
infection type (0-4scale) type(0-4scale) infection
type(0- Type (0-
4scale) scale)
Durum
1 Assassa 2 3 2 2
2 Tob-66 1 1 1 1
3 Kilinto 1 3 2 2
4 Foka 3 2 1 1
5 Gerardo 1 1 2 2
6 DZ1640 2 1 2 2
7 DY1050 2 2 2 2
8 Cocorit-71 1 3 1 3
9 Yielma 2 1 1 1
10 DZ1928-2 1 1 1 2
11 DZ 1691 2 2 2 2
12 DZ 1695-5 2 2 3 2
13 DZ1543 1 2 1 3
14 Boohai 2 2 2 2
15 Bichena 3 2 1 3


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Local check 4 4 4 4
Bread Wheat
1 Kubsa 2 4 2 3
2 Wabe 3 3 0 1
3 Galama 2 2 2 2
4 Tuse 3 3 0 1
5 Katar 3 2 2
6 Shina 3 3 0 2
7 Hawi 0 0 0
8 Simba 0 0 0
9 Wetera 0 0 0
10 HAR 2192 1 2 0 2
11 HAR 2508 3 1 1
12 F-H-6-1-7 1 3 1
13 Abola 2 0 0
14 Tura 2 1 0
Local check 4 4 4 4


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004












Table 2. Seedling and adult plant reactions (0-4 scale) of wheat varieties when tested with to P.
graminis isolates from DebreZeit

Isolate 1 Isolate 2
No. Variety Seedling Adult plant Seedling reaction Adult plant
reaction reaction reaction
Durum wheat
1 Assassa 2 2 2 3
2 Tob-66 1 2 1
3 Kilinto 2 3 1
4 Foka 1 2 1 1
5 Gerardo 2 3 1 1
6 DZ1640 1 2 1 2
7 DY1050 2 2 2 2
8 Cocorit-71; 1 1 2
9 Yielma 3 4 1 2
10 DZ1928-2 2 2 1 2
11 DZ 1691 1 2 2 2
12 DZ 1695-5 3 2 1 2
13 DZ1543 2 2 1 2
14 Boohai 3 3 3 1
15 Bichena 3 4 2 2
Susceptible check 4 4 4 4
Bread Wheat
1 Kubsa 1 3 1 0
2 Wabe 2 2 1 0
3 Galama 2 2 2
4 Tuse 2 1 3
5 Katar 3 3 1 0
6 Shina 2 4 1 2
7 Hawi 3 0 0
8 Simba 0 0 0
9 Wetera 0 0
10 HAR 2192 1 2 1 0
11 HAR 2508 2 3 1 3
12 F-H-6-1-7 1 2 1
13 Abola 1 0
14 Tura 2 0
Susceptible check 3 4 3 4


REFERENCES

Goluden, C.H., Neatby, K.W. and Welsh, J.N. (1928). The inheritance of resistance of Puccinia
graminis tritici in a cross between two varieties of Triticum vulgare. Phytopathology 18:631-
658.
Mutkekar, M.L., Bhangale, G.T., Patil, J.V. and Kalekar, A.R. (1985). Source of resistance to stem rust
of wheat. Cereal Rust Bulletin 13:19-22.
Stakeman, E.C. and Levine, M.N. (1922). The determination of physiologic forms of Puccinia
graminis on Triticum spp. Tech. Bull. 10 Univ. Minn. Agric. Exp. Stn. 1-lOpp.


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










Evaluation of Kenyan Wheat (Triticum
aestivum L.) Lines for Bread Making Quality

Kimani E.N., J. Ndung'u, M.G. Kinyua and J. Owuoche

KARI- Njoro P.O. Private Bag- 20107 Njoro

Abstract-The grain composition and baking quality of wheat (Triticum aestivum
L.) are important in determining end-use product acceptability, although some of
these factors are influenced by environmental conditions. This study investigates the
bread making quality and protein content of Kenyan wheat advanced lines. Eleven
lines and one wheat variety (control) were planted in four locations in 2001 and
2002, and evaluated for flour extraction rate; protein content; farinographic dough
water absorption and dough development time (DDT); and bread loaf volume, using
official methods of the American Association of Cereal Chemists. There were
significant (p<0.01) effects associated with year of planting for protein, DDT; water
absorption and loaf volume. Effects due to genotype were significant (pO0.01) for
flour yield and DDT. No significant (P>0.05) genotype x year interaction was
observed. Genotype K7972-1 had 5.94% higher mean FY than the control K. Heroe.
Lines 92B20 and R932 showed 4.5 and 2.67mins, respectively, longer DDT than K.
Heroe. R899 had the highest mean flour Water Absorption (WA), 2.18% more than
the control. R946 had the highest Loaf Volume (LV) of 619.38cm3 (20.1% higher
than K. Heroe). K. Heroe recorded the lowest loaf volume of 515.63 cm3. 92B19,
92B24 and R946 had higher protein content, 19.2%, and 17.1% and 15.9%,
respectively, than K. Heroe. Protein content and loaf volume correlated significantly
(r = 0.657** and 0.707**, respectively) with DDT. Protein content and loaf volume
correlated significantly (r= 0.642**) while flour yield correlated negatively (r-
0.462**) with flour water absorption. From this study, we suggest that 92B9, 92B19
and R946 can be used in the breeding program to improve the quality of wheat.

Introduction
Grain and baking quality of wheat (Triticum aestivum L.) refers to its suitability for the type
of processing or utilization for which the raw material is destined (Morris and Rose, 1996).
Grain composition and baking quality are variable factors that depend on both genotype and
the growing conditions. Environmental conditions such as weather-related factors, soil
fertility, temperature, and soil moisture regimes have a major influence on grain and end use
quality of wheat (Peterson et al, 1998). Therefore, there is genetic variation in wheat baking
quality although some of the quality factors are influenced by the environment (Busch et al.,
1969; Baezinger et al., 1985; Bassett et al., 1989; Peterson et al., 1992). Wheat strength is
usually associated with flour protein. Both protein quantity and quality are considered to be
primary factors in measuring the quality of flour in relation to bread making. The quantitative
expression of crude protein is related to total organic nitrogen in the flour, whereas quality
evaluations relate specially to physicochemical characteristics of the gluten-forming
component. Protein quality criteria are related primarily to the gluten portion of the flour
protein. Glutenins and gliadins are the major components of the storage protein in wheat and
make a significant contribution to dough rheology and baking quality (Payne, 1987; Weegels
et al. 1996). Quality is appraised largely by subjecting the flour to several physical testing
devices, which measure various theological characteristics. The tests are performed usually
on flour-water dough. They characterize the dough as related to the properties of the gluten


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










portion of the protein. Resistance to extension of dough at rest, hydration time, maximum
development time and tolerance or resistance to breakdown at a predetermined consistency
during mechanical mixing, are some of the most common dough parameters evaluated.
Mixing characteristics are usually related to gluten quality, and can be reasonably well
defined by the use of recording dough mixers such as the farinograph. Mixing requirements of
bread dough correlate with some of the measurements obtained with recording dough mixers.
Performance of flour is evaluated experimentally under conditions that are similar to
those applied by the millers and bakers. The evaluation of flour is carried out by test baking
depending on intended use. Tests are performed under rigidly controlled and standardized
condition (AACC methods).
Flour water absorption is an important factor in production of all types of baked goods.
Usually high water absorption values are desirable, since they tend to increase unit yields of
baked products. It is measured as the amount of water required to yield dough of
predetermined consistency (Pratt, 1971).
In Kenya wheat is mainly used for chapatti and bread making but rarely used for pasta
production. The increased demand for these products has prompted the breeding of more new
varieties with good qualities. Although yield and resistance to diseases and pest have been the
main objective of breeding work, recently, there has been an increasing emphasis on
improvement of quality of the grain for milling and baking. The objective of this study was to
investigate the bread making quality of advanced wheat lines, evaluated at four locations in
Kenya.

Materials and Methods
Two wheat genotypes developed in Kenya (K7972-1 and K7872), five CIMMYT lines (R946,
R891, R892, R932, R899) and four from Kenya Seed Company (92B9, 92B19, 92B20 and
92B24) were used in this experiment. K. Heroe, a variety was used as a control. The
genotypes are described in Table 4.
The experiment was conducted at Lanet (004'S; 3603'E), Naivasha (006'S; 3605'E), Mau
Narok (006'S; 3508'E) in Rift Valley Province and at Katumani (16'S; 3704'E) in the Eastern
Province of Kenya. The cultural practices were followed according to the recommendations in
all sites in order to sustain plant growth and production of grain. The seeding rate was
maintained at 138 Kg ha1. Diammonium phosphate fertilizer was applied at the rate of 231
Kg ha' in order to supply 42 Kg N and 100g of DAP (18% N + 20% P) per plot during
planting time. Pre-emergence herbicide STOMPR (Pendimethalin 500g/litre) was applied at
sowing time to restrict early weed growth. The experiment was laid out in a partially balanced
lattice design, replicated three times and in each replicate, there were 4 blocks with 4 entries.
At physiological maturity, the crop was harvested by Hege combine Model 140, seed cleaned
and composite. Due to inadequate seed for entries, the sites were considered as replicates.
About 800-1000g of wheat samples were sieved and cleaned, tempered to 15% moisture
content (MC) and left overnight at room temperature about 20-210C. These samples were
then milled using a Buhler mill (Buhler Brothers Ltd., Switzerland) to determine flour
extraction. The milled products were withdrawn and weights of all six flour streams (blended)
and of shorts and bran were determined. Flour yield was calculated using equation:

Flour
FlourYield = Flour x 100
total recovered milleqbroducts

Chemical, theological, and baking tests were carried out to evaluate the baking quality of the
wheat. The flour water absorption (WA) and dough development time (DDT) were analysed


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










using a small bowl (50g) Brabender Farinograph (brabender OHG. Duisburg Germany) as
described in the AACC method 54-21 (AACC, 1983). The amount of flour used was 50g
(14% moisture basis). Flour water absorption is the amount of water required to centre the
farinograph curve on the 500 brabender unit line.
Dough development time (DDT) is the duration required to develop dough visco elastic
properties. It is the interval from first addition of water to that point of maximum consistency
range immediately before first indication of weakening. This value has also been referred to
as "peak" or "peak time".
Bread making was performed using a modified basic straight dough method. The baking
formula used included 100g flour at 14% moisture basis (mb), 1.2g yeast, 2.5g sugar, Ig salt,
3g dry milk powder, 3g fat and 1ml ofbromate phosphate solution. Dough ingredients were
mixed until optimum mixing time and then the dough was fermented (300C and 80% relative
humidity) for about four hours, with intervals of moulding the dough and finally proofing for
55minutes. This was then baked for 25 minutes in the oven at 2200C. Loaf volume (LV) was
measured using the Rapeseed displacement method 10 minutes after the loaf was removed
from the oven, using a Loaf Volumeter (National Mfg. Co., Lincohl, Nebraska.)
Crude flour protein (PC) analysis was done using the Kjeldahl method (N X 5.7) using a
Tecator Kjeltec system.
SAS system was used to do statistical analysis using the General Linear Model. Analysis
of variance for all the parameters, involving sites and years was done for each quality trait.
Pearson correlation was done between some of the baking quality parameters.

Results
The mean year effects were significantly different (p< 0.01) for all the traits (Table 1). The
effects due to genotype were also significant (p<0.05) for FY and DDT. No significant
(P>0.05) effects due to year x genotype interaction were observed.
A comparison of the genotypes for the two years showed much difference across the
traits (Table 2). The means of the second year were lower for flour yield and higher for DDT,
LV and PC than those of the first year.
Among the tested genotypes, K7972-1 produced 5.94% more FY than the control K.
Heroe (Table 4). 92B20 and R932 showed longer differences of DDT of 4.5 and 2.67min,
respectively, as compared to K. Heroe. R899, 92B19 and 92B24 showed higher water
absorption than the control (Table 4).
The loaf volumes were generally low for all the genotypes (lower than the desirable
700cm3 and above). The highest loaf volume was shown by R946 with 619.38 cm3. This was
higher than K. Heroe by 20.1%. Genotype 92B19, 92B24 and R946 exhibited protein ranging
from 118.30 -115.01 g/kg. This was 19.2%, 17.1% and 15.9% than K. Heroe (Table 4).

Table 1: Mean Squares for flour yield, Dough Development, Flour Water absorption, loaf volume
and protein content of the 12 wheat genotypes (Triticum aestivum L.)
Source DF FY DDT WA LV PC
(%O) (min) (cm3) g.Kg-'
Year 1 343.01** 0.90** 32.67** 112951.40** 1889.08**
Genotype 11 29.68* 0.37** 3.92 9422.79 237.93
Rep 3 107.78 7.22 12.23 314602.39 8021.20
Gen*Year 11 29.19 0.13 9.14 7482.89 138.81
Error 64k 12.86 0.10 4.14 5492.40 167.14
C.V 5.54 13.72 3.36 13.26 11.75
*, ** P<0.05, P<0.01


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004










portion of the protein. Resistance to extension of dough at rest, hydration time, maximum
development time and tolerance or resistance to breakdown at a predetermined consistency
during mechanical mixing, are some of the most common dough parameters evaluated.
Mixing characteristics are usually related to gluten quality, and can be reasonably well
defined by the use of recording dough mixers such as the farinograph. Mixing requirements of
bread dough correlate with some of the measurements obtained with recording dough mixers.
Performance of flour is evaluated experimentally under conditions that are similar to
those applied by the millers and bakers. The evaluation of flour is carried out by test baking
depending on intended use. Tests are performed under rigidly controlled and standardized
condition (AACC methods).
Flour water absorption is an important factor in production of all types of baked goods.
Usually high water absorption values are desirable, since they tend to increase unit yields of
baked products. It is measured as the amount of water required to yield dough of
predetermined consistency (Pratt, 1971).
In Kenya wheat is mainly used for chapatti and bread making but rarely used for pasta
production. The increased demand for these products has prompted the breeding of more new
varieties with good qualities. Although yield and resistance to diseases and pest have been the
main objective of breeding work, recently, there has been an increasing emphasis on
improvement of quality of the grain for milling and baking. The objective of this study was to
investigate the bread making quality of advanced wheat lines, evaluated at four locations in
Kenya.

Materials and Methods
Two wheat genotypes developed in Kenya (K7972-1 and K7872), five CIMMYT lines (R946,
R891, R892, R932, R899) and four from Kenya Seed Company (92B9, 92B19, 92B20 and
92B24) were used in this experiment. K. Heroe, a variety was used as a control. The
genotypes are described in Table 4.
The experiment was conducted at Lanet (004'S; 3603'E), Naivasha (006'S; 3605'E), Mau
Narok (006'S; 3508'E) in Rift Valley Province and at Katumani (16'S; 3704'E) in the Eastern
Province of Kenya. The cultural practices were followed according to the recommendations in
all sites in order to sustain plant growth and production of grain. The seeding rate was
maintained at 138 Kg ha1. Diammonium phosphate fertilizer was applied at the rate of 231
Kg ha' in order to supply 42 Kg N and 100g of DAP (18% N + 20% P) per plot during
planting time. Pre-emergence herbicide STOMPR (Pendimethalin 500g/litre) was applied at
sowing time to restrict early weed growth. The experiment was laid out in a partially balanced
lattice design, replicated three times and in each replicate, there were 4 blocks with 4 entries.
At physiological maturity, the crop was harvested by Hege combine Model 140, seed cleaned
and composite. Due to inadequate seed for entries, the sites were considered as replicates.
About 800-1000g of wheat samples were sieved and cleaned, tempered to 15% moisture
content (MC) and left overnight at room temperature about 20-210C. These samples were
then milled using a Buhler mill (Buhler Brothers Ltd., Switzerland) to determine flour
extraction. The milled products were withdrawn and weights of all six flour streams (blended)
and of shorts and bran were determined. Flour yield was calculated using equation:

Flour
FlourYield = Flour x 100
total recov eredmilledproducts

Chemical, theological, and baking tests were carried out to evaluate the baking quality of the
wheat. The flour water absorption (WA) and dough development time (DDT) were analysed


12th Regional Wheat Workshop for Eastern, Central, and Southern Africa Nakuru, Kenya, 22-26 November 2004




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