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Prelimi nary
A SUGGESTED METHOD FOR IMPROVING THE INFORMATION BASE
FOP ESTABLISHING PRIORITIES IN CASSAVA RESEARCH
Per Pinstrup-Andersen
Rafael 0. DTaz
Paper prepared for the cassava review meeting, CIAT,
Cali, Colombia, January 30-February 6, 1975.
1
In order to establish sound research priorities, information is needed
on expected benefits, costs and time requirements for each of the lines of
I/
research considered. Ideally, the research manager- would have complete know-
ledge of research outcomes and their expected contribution to the achievement
of established goals as well as costs and time requirement for each line of
research. If this were the case, and assuming a well defined goal, single or
aggregate, available research resources could always be allocated in such a
way as to maximize the contribution to the achievement of this goal and no
subjective judgement would be needed in the decision-making process.
However, because of the very nature of research, decisions on research
priorities will always be subject to uncertainty. This inherent uncertainty
of research outcomes is frequently accompained by lack of information on issues
relevant to the decisions that can in fact be estimated with some certainty.
These issues include potential production and productivity gains from alterna-
tive research outcomes, and their impact on employment, nutrition, and farm
-,------------------I----------
Portions of this paper are taken from: Per Pinstrup-Andersen, et. al. A Pro -
posed Model for Improving the Information Base for Research Resource Allocation.
Paper presented at Workshop on Methods Used to Allocate Resources in Applied
Agricultural Research in Latin America, Cali, Colombia, November 26-29, 1974.
1/ The term "research manager" is used to indicate the person or group of
persons making the decision on research priorities. Depending on the research
organization and the level in the research process at which priorities need
to be established, the "research manager" may be the individual scientist, a
team of scientists, a research director or any other person or group of persons
in the research system.
2
revenues. It is argued here that additional information on these and related
issues is likely to be highly useful to the research manager in establishing
research priorities.
2/
An overall model for providing such information is suggested elsewhere-
This paper is limited to a presentation of a methodology for 1) describing
the production process, 2) identifying factors limiting production and pro -
ductivity, 3) estimating the relative importance of each of these factors, and
4) obtaining indications of the technology characteristics preferred by the
farmer.
In addition to the information requirements discussed in this paper, other
information relevant to decision-making on research resource allocation include
expected future product demand, resource supply and consumer acceptance.
This paper is divided in two parts. First, a simple methodology for ob-
taining the above mentioned information from the farm sector is suggested and
second, the experience gained from the empirical testing of the methodology for
cassava in Colombia is discussed with illustrations of the kind of information
obtained. The paper is focused on the practical aspects of the data collection
and analysis.
2/ Pinstrup-Andersen, Per. Allocation of Resources in Applied Agricultural
Research in Latin America Preliminary Approach. Paper prepared for the
Regional Seminar on Socioeconomic Aspects of Agricultural Research, IICA,
Maracay, Venezuela, April 10-13, 1973.
Pinstrup-Andersen, Per. Toward a Workable Management Tool for Resource
Allocation in Applied Aricultural Research in Developing Countries. Re-
vised version of paper presented at the Ford Foundation Meeting for Pro-
gram Advisors in Agriculture, Ibadan, Nigeria, April 29-May 4, 1974.
Pinstrup-Andersen, Per and David Franklin. A Systems Approach to Agricul-
tural Research Resource Allocation in Developing Countries. Paper presen-
ted for Conference on Resource Allocation and Productivity in International
Agricultural Research, Airlie House, Virginia, January 26-29, 1975.
A SUGGESTED METHODOLOGY.
Priorities in applied agricultural research are frequently established
on the basis of very limited information about existing problems and their
relative economic importance in the production process. The communication
between the farm sector and the research institute is often deficient and
the demands at the farm level for problem solving research frequently are
not well known by the research manager. Farmers in most developing countries,
maybe with the exception of large commercial ones and members of efficient
producer associations, tend to have severe difficulties in communicating their
research needs to the research institutes because of institutional and social
barriers. Because of that situation, some research may be irrelevant to the
actual farm problems and research results may not be adopted.
Low rates of adoption of new technology are frequently explained as a
result of an ineffective extension service. Whereas the-ability of the exten-
sion service to assure adoption of new technology may indeed be deficient ,
one of the primary reasons for low adoption rates may well be that available
new technology does not meet the most urgent on-farm needs and farmer prefer-
ences. A continuous flow of information to the research manager on the poten-
tial gains in production, productivity and risk obtainable from such research
activities as 1) developing resistance to existing diseases and insects, 2)
changing cultural practices, 3) changing plant types, 4) chaDging plant res-
ponse to nutrients, etc., as well as information on the farmers' preferences
with respect to new technology, is likely to be useful to assure that new tech-
nology corresponds with the farmers' needs and preferences, hence accelerate
adoption and increase research pay-off.
Such an information flow may consist of a continuous feed back of in -
formation from the farmer through the extension service to the research ins-
titutions. Direct contact between researchers and farmers through meetings,
farm visits, etc., would be another effective vehicle for such information. To
complement these we are suggesting a third method. This method consists of a
combination of agro-economic surveys and agro-biological experiments. Each of
these will be discussed in the following.
Agro-economic surveys
The agro-economic survey attempts to transmit to the research manager
the farm level demand for applied agricultural research through he establish-
ment of a direct link between the farm and the research institute. In addi -
tion to serving the needs of research managers, the information generated by
the agro-economic surveys is expected to be useful for establishing or review-
ing public policy on such issues as agricultural extension, credit and prices.
Finally, the information may be useful to producer associations and individual
farmers (Fig. 1). However, the primary purpose of the surveys is to supply in-
formation for establishing research priorities.
The basic framework underlying the choice of data to be collected is
shown in Figure 2. Attempts are made to describe certain key aspects of the
structure, conduct and performance of the production process, the farmer objec-
tives, and the interaction among these factors. Emphasis is placed on iden -
tifying the principal factors limiting production and productivity and estimat-
ing the implications of removing these factors.
Process structure. The structure of the production process refers to the pro-
cess characteristics determined by factors external to the process itself.
5
The structure represents the constraints within which the process operates.
Some of the constraints may be modified or removed by the farmer while o -
thers are beyond his control. Figure 3 illustrates the structural factors
described by the agro-economic surveys. Given the purpose of the survey,
major emphasis is placed on agro-biological and ecological factors.
Most of the data related to the agro-biological factors are obtained
from direct observation in the farmers' fields. The occurrence and severity
of disease and insect damage, mineral deficiencies and weed occurrence are
noted. Furthermore, altitude, soil quality 'by means of soil tests), avail-
ability of water, plant type and general plant development are described. The
farmer's perception of the agro-blological problems are compared to the field
observations. In addition, data are obtained from the farmers on product and
input prices and their fluctuations; availability of commercial inputs, credit
and technical assistance; land tenure, farm size, capital and certain charac-
teristics of the farmer and his family.
Process conduct. The conduct describes the action resulting from the farmers
decisions with respect to the production process. The survey obtains data on
1) use of the land controlled by the farmers; 2) crops founds in the production
process studied; 3) planting, cultural and harvesting practices; 4) use of
inputs such as fertilizers and insecticides as well as credit and technical
assistance and 5) the utilization of the products produced by the process stu-
died (Fig.4). Emphasis is placed on analyzing the relationship between struc-
ture and objectives on the one hand and conduct on the other, to determine
the major production limiting factors.
6
Process performance. The performance measures the outcomes or results of the
production process in terms of established goals. The survey obtains data on
yields, production, costs, labor absorption, home consumption, yield varia -
tion (risk) and gross and net revenues (Fig.5).
Farmers' objectives. Attempts are made to describe the farmer's goals and the
relative importance of incomes, risk and availability of products for home con-
sumption in his objective function to help identify technology with high expec-
ted rate of adoption. This work includes the collection of data on reasons why
various types of new technology was or was not adopted and factors underlying
the choice of cropping systems.
Data gaatherin-mechanism. Primary data are obtained by a small specialized team
of agronomists and economists, from a panel of farms expected to be representa-
tive of the farms for which agro-biological research is intended. The field
team makes periodic visits (normally 3 4 visits) to each farm throughout a
complete crop cycle. About half of the time on the farm is spent in the field
collecting data on agro-biological issues (by direct observation), while the
other half is used to interview the farmer.
Before the farm visits are initiated the field team receives extensive
training in diagnosing farm level production problems. Training of the field
team is one of the most critical issues in assuring high quality data from the
agro-economic survey. Making a correct diagnosis in the field, e. g. distin -
guishing among the symptoms of certain diseases, insect damage, mineral defi -
ciencies, etc., in most cases requires considerable expertise. Hence, direct
participation of a highly qualified multidisciplinary research team in the
training and field execution phases is essential to the success of the survey.
The field teams working on the on-going CIAT agro-economic surveys have re -
ceived 3 4 months of such pre-survey training in direct contact with the
scientists from the relevant disciplines.
Agro-biological experiments
The agro-economic survey provides an estimate of the area affected by
each of the problems identified. Furthermore, it gives an indication of the
yield depressing effect. However, it is frequently difficult to estimate the
yield impact from survey data with a great deal of accuracy. Hence, contro-
lled experiments are carried out to help quantify the yield impact of the
problems.
Data analysis
The data obtained from the agro-economic survey and the related experi -
ments are analyzed for the general purpose of 1) describing the structure, con-
duct and performance of-the production process under study and 2) estimating
the impact of changing process structure and conduct on performance. In addi-
tion to aggregating the data for the purpose of presenting a description of
the process, attempts are made to estimate the economic loss caused by each
of the agro-biological and ecological factors such as diseases, insects, weeds,
soil deficiencies and adverse rain fall conditions and the implications of
changing these factors. Furthermore, estimation is made of 1) production costs
and labor absorption by production activity, 2) net returns to the process for
each of the principal cropping systems, 3) the contribution of each of the
principal resources to net returns and 4) the factors influencing the farmer
decision-making on adoption of new technology and choice of cropping system.
ILLUSTRATION OF EMPIRICAL RESULTS
Projects are currently under way in Colombia to field test the above
methodology for maize, cassava and beans. While the information obtained from
these empirical studies is expected to be useful to Colombian national insti-
tutions and CIT, the primary purpose of the work is to develop and test a
simple methodology for use by national research agencies in Latin America and
elsewhere. The purpose of this section is to present a few preliminary re -
suits from the agro-economic analysis of cassava production in Colombia to
illustrate the kind of information obtained. Since the data collection is not
yet completed, little data analysis has been done.
The agro-economic analysis of the cassava production process in Colombia
is based on the collection of primary data from personal visits to approxima-
tely 300 cassava producers located in five regions of Colombia. Each farm is
visited three times during the growing season by a team-of two agronomists and
an agricultural economist previously trained in identifying agro-biological
problems in cassava and carrying out farm interviews. The growing season for
cassava in Colombia is around 12 months except in one zone (North Coast Region)
where it is 8 10 months. The three visits are distributed throughout the
growing season with the fist occurring less than four months after planting
and the last right after harvest.
As of October 1, 1974, all the sample farms have been visited once, and
80 and 53 per cent have been visited twice and three times, respectively. Hence,
except for those obtained during the first visit, the data reported below are
preliminary and serve primarily as illustration of the kind of information that
the agro-economic analysis can make available.
9
The location of the five zones included in the survey are shown in Fi-
gure 6. The selection of zones was based on their importance within total
national cassava production and their ability to represent the characteris-
tics of the various cassava producing regions of the country.
Table 1 shows the altitude, farm size and land use characteristics of
the sample farms. The altitude of the farms varies from over 1.000 meters
in zones I and II to almost sea level in zone V. The farms are relatively
large when measured in terms of total area. However, a large portion of the
land is idle or in-pasture, hence the cultivated area per farm is small. Al-
though a few of the farms had large cassava plantations, the average cassava
area per farm was estimated at about 5 ha. Meta (zone IV) shows the largest
cassava area per farm. The farms visited had, on the average, two lots with
cassava. The importance of other crops on the sample farms varied with lo -
cation. Coffee and plantain, in most cases intercropped, were the most impor-
tant crops in zones I, II and III. Furthermore, sugar cane, maize and banana
showed some importance in certain zones.
Table 2 shows the cropping systems most predominant among the sample
farms, and lot size and plant population for each of these systems. A total
of 14 different crop combinations were identified at the first visit. More
than half of the farmers grew cassava alone while about one-fourth grew cas-
sava intercropped with maize. About 60 per cent of the area was planted with
cassava alone. Although lot size varied greatly with cropping system, addi -
tional data analysis is needed to determine the possible relationship between
these two variabjls.
10
The plant population of cassava was found to be similar whether grown
alone or intercropped with one other crop. However, when grown with two or
more crops, the cassava plant population tends to diminish. A comparative
economic analysis of various cropping systems for cassava has been initiated
to provide more information on this issue including the factors determining
the farmer's choice of system.
The occurrence of insects, insect damage and diseases in cassava was
estimated on the basis of direct field observations. The final results from
the first visit and preliminary results from the second and third visits are
shown in Tables 3, 4, 5 and 6.
Thrips was the insect most frequently found, followed by gall midge and
white fly (Bemisia s.). (Table 3). It appears that the occurrence of these
insects and the visible damage they cause is less frequent in crops more than
eight months old. One explanation of this situation is that the crop in many
cases outgrows the visual damage caused by the initial attacks. However, data
are not yet available to determine whether in fact the attacks had any sign -
ficant impact on yields.
While the occurrence of most insects and their visible damage seems to
diminish as the plant grows older, the opposite seems to occur for some insects
including white fly and mites.
The occurrence of each of the major insects varies considerably among
zones (Table 4). For example, Fruit fly (in stems), was found on 76 per cent
of the farms in Zone II while it was of little importance od the other zones.
Leaf hopper was important only in Zone V. and White fly (Bemisia s_.) was found
on 70 per cent of the farms in Cauca, Magdalena and Atlantico (Zones I and V)
while it was much less important in the other three zones.
11
The visible damage caused by diseases in cassava was mos pronounced in
crops between 4 and 8 months of age. The diseases most frequently found were
White Leaf Spot, Phoma Leaf Spot, Brown Leaf Spot, Powder Mildew and Cercospora
Leaf Blight (Table 5). As in the case of insects, it appears that the cassava
plant in some cases is capable of outgrowing the disease symptoms. However, it
is interesting to note that the proportion of the lot affected.increases with
the age of the crop for most diseases. One possible conclusion might be that
while lighter attacks tend to be overcome by plant growth, the somewhat more
serious attacks continue to spread in the field. The relationship between
rainfall conditions and disease spread will be analyzed as more data are co-
llected.
As in the case of insects, the occurrence of cassava disease varies
greatly among zones. Phoma Leaf Spot, the disease most frequently found dur-
ing the second visit (in plantations 4 8 months old), was found on about 70
per cent of the farms in Cauca, Valle and Quindio (zones I and II) and only
30-40 per cent of the farms in the other three zones (Table 6). Superelongation,
while of little or no importance in four zones, was found on two-thirds of the
farms in Tolima (Zone III). Likewise, the occurrence of Cassava Bacterial Blight
and White Leaf Spot differed greatly among zones.
It should be noted that the data from second and third visits are not
complete, hence are subject to change as more data are collected. Therefore,
the above findings and conclusions are tentative and subject to revision when
the analysis is completed.
During the first visits, 92 weeds were identified. Table 7 shows the
ten weeds most important in terms of percentage of farms where they occurred.
12
Pteridium candatum was found on one-forth of the sample farms but the plant
density was relatively low. It was most frequently found in Zone III (79%
of all farms) while it was not found in Zone V.
Other agro-biological problems in cassava production assessed by the
-field team include scarcity or excess of water. It appears that excess of
water was a severe problem particularly in Valle and Quindio (zone II) while
water scarcity appeared to reduce yields in Magdalena and Atlantico (Zone V).
Once the data collection is completed, attempts will be made to estimate
the relative economic loss caused by each of the major insects, diseases,
weed and other agro-biological problems, in collaboration with the respective
biological scientist within the Cassava program. / Such estimates are ex-
pected to be useful to the cassava program in establishing and reviewing
priorities among and within disciplines.
The distribution of production costs and labor requirements among pro-
duction activities is another factor likely to provide guidelines for research
resource allocation. Table 8 shows the estimated labor requirements by pro-
duction~ activity and the percentage distribution of labor requirements and
4/
available costs. Weeding was the most labor-consuming activity (and accoun-
ted for the highest percentage of variable costs), followed by harvesting/
3/ The data collection extends over a two-year period to cover two complete
growing seasons and most of the data analysis cannot be performed until
a complete data set is obtained. The data collection will be completed -
around June 1, 1975.
4/ Since the data collection within the agro-economic survey is not stffi-
ciently advanced to provide estimates of labor and cost distribution, the
data presented in Table 8 are taken from prior work (Rafael O.Diaz, Per
Pintrup-Andersen and Rub6n Dario Estrada. Costs and Use of Inputs in
Cassava Production in Colombia: A Brief Description. CIAT,EE-Noz.5,Sep-
tember, 1974).
packing, land preparation and planting.
The data reported in Table 8 suggest that high priority might be plh-
ced on research aimed at exploring whether and how the economic efficiency
in weeding, harvesting/planting and land preparation might be improved. Such
work might include the estimation of the impact of alternative degrees of
land preparation and weeding on yields and economic net return as well as
the impact of alternative methods applied in these activities and harvest-
ing/packing.
The potential impact of the development and adoption of mechanical,
chemical and biological technology on labor use in cassava production was
estimated for various adoption rates. Extensive mechanization and/or her-
bicide use was estimated to have a significant negative impact on labor de-
mand while biological technology is expected to increase labor demand slight-
ly.- The impact of the various types of technology on costs would depend on
existing relative prices, hence may differ among localities.
Before data such as the above, are used to help establish research prio-
rities, the objectives of the society for which the research is intended must
be clearly specified. Social and private objectives may conflict, e.g. the
social objective of creating productive employment may conflict with private
objectives of maximizing profits. Chemical weed control, for example, may
increase net returns to the producer but reduce employment. The impact of
5/ The quantitative results of the analysis are reported in: Per Pinstrup-
Andersen and Rafael 0. Diaz. Present and Potential Labor Use in Cassava
Production in Colohbia. Paper presented at the third International Sym-.
posium on Tropical Root Crops, Ibadan, Nigeria, December 2-9, 1973.
14
new technology on-net returns depends, at least in part, on relative factor
prices, which in turn may be influenced by public policy. It is important
that possible conflicts between social and private objectives as well as
government's ability and desire to introduce corrective and facilitating
policy measures be fully understood before research priorities are establi-
shed in order to assure a large contribution of the research to the achieve-
ment of social and economic development goals.
In addition to the above, the agro-economic survey seeks information
on a number of other issues expected to be useful for the cassava program
in allocating its' research resources as discussed earlier in this paper.
This information will be reported.when the data collection an, analysis are
completed.
Training benefits
In addition to the expected utility of the information made available
by the agro-economic analyses, the work provides a valuable training oppor-
tunity for young agronomists and economists interested in production. The
extensive initial training along with the experience gained while carrying
out the surveys produce professionals extremely knowledgeable of farm level
production limitations and possible ways to remove these limitations in the
crop or crops for which the survey was .carried out. It is expected that
these professionals in their future activities will complement the empirical
survey results by providing a close linkage between research and farm level
problems.
Concluding remarks
No claims are made here that the agro-economic survey is a new inven-
tion. A very large number of farm surveys have been carried out in the past.
15
However, certain aspects of the work discussed above tend to distinguish it
from traditional farm surveys and hopefully make it more useful for establish-
ing priorities in applied agricultural research. These aspects are:
1. A considerable proportion of the data are obtained from direct
field observations made by agronomists previously trained for
this job;
2. Each farm is visited periodically during a complete growing
season;
3. The work is multidisciplinary in nature and involves direct
participation by professionals from all the relevant disciplines.
4. The work is specifically focused on providing information nee-
ded to establish research priorities. Although the information
may be useful for other purposes, such utility is considered
secondary.
The work described above is in its preliminary stages and no signifi-
cant contribution to research resource allocation can yet be identified. It
may be expected, however, that the direct participation of the CIAT agricul-
tural production scientists in project planning and training of field agrono-
mists as well as communication with these agronomists when they are back
at the research station and the distribution of preliminary project findings
may have been of some value to the scientists in planning their future re -
search. However, more time is needed to terminate the first round of data
collection and analysis before the real value of these efforts for research
resource allocation can be established.
The methodology and experience gained from the work will be made
available to interested national research agencies upon request. Further-
more, CIAT will consider requests for technical assistance for project of
this type. Currently, a collaborative project with INIAP, Ecuador for cas-
sava is being planned. The possibility of carrying out projects for cassava
in Brazil and Thailand are being discussed, and funds have been assured to
provide technical assistance for two similar projects for beans in Latin A -
merica.
Figure 1.
Figure 2. Basic model underlying choice of data to be
collected.
Figure 3. Factors determining the structure of the production
process.
Figure 4. Factors expressing the conduct of the
production process.
Figure 5. Factors expressing the-performance of the
production process.
* Figure 6. Location of the five zones included in the agro-cconomic analysis
of cassava production in Colombia.
I---
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__ ,' -r ,--..*'_ =,
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Table 1. Altitude, farm size and land use on sample farms. Agro-economic analysis of cassava production in
Colombia (preliminary data)
Simple
Z 0 N E Averagne
I II III IV V
Altitude of farm (meters) 1.254 1.187 886 396 33 761
Total farm size (ha) 7.2 37.5 16.5 61.3 18.0 25.9
Area in crops (ha) 3.5 18.3 4.7 10.9 8.4 9.9
Area in cassava (ha) 2.9 6.4 2.0 9.4 5.3 5.2
Area in pasture and unused land (ha) 3.7 19.2 11.8 50.1 9.6 16.0
Number of cassava lots/farm 2.16 1.91 2.16 1.98 1.59 1.96
Size of cassava lot observed (ha) 1.30 3.35 0.90 3.37 2.16 2.22
Crops other than cassava on farms:
Coffee (% of farms) 32.4 61.4 31.6 10.0 0.0 28.7
Plantain (% of farms) 18.9 54.5 5.3 10.0 4.5 22.0
Maize (% of farms) .2.7 11.4 15.8 15.0 4.5 8.5
Sugar cane (% of farms) 5.4 0.0 26.3 0.0 0.0 4.3
Banana (% of farms) 2.7 0.0 0.0 0.0 6.8 2.4
Other crops (% of farms) 0.0 9.1 5.3 10.0 18.2 9.1
Table 2. Cropping systems, lot sizes and plant population. Agro-economic analysis of cassava
production in Colombia ( preliminary data).
Cropping system
Cassava alone
Cassava Maize
Cassava Plantain
Cassava Beans
Cassava Maize Beans
Cassava Maize Plantain
Cassava Maize Sesame
Cassava with other crops
Percent of
farms
60.0
24.5
4.1
3.4
2.2
1.3
1.0
2.3
Lot size
(ha)
2.5
1.'4
3.6
2.7
0.6
2.0
0.6
1.7
Percent of
area
69.3
15.8
6.8
4.2
0.6
1.2
0.3
1.8
Plant population (No. of Plants/ha)
Cassava 2nd.crop 3rd.crop
9811
S9421 5578
12172 574
9455 2127
8988 5113 7813
7617 3583 833
7333 4133 4283
S7386
Table 3. Preliminary data on insect occurrence in cassava. Aro-economic analysis of cassava production in Colombia.
1/ 2/ 3/
First visit Second visit Third visit -
% of % of Inten- % of % of Inten-. % of % of Inten/
Insect farms lot sity f4/ farms lot sity_ farms lot sity -
Thrips 80.0 80.9 2 84.0 41.6 2 46.0 41.6 2
Gall midge 51.0 22.1 2 54.0 15.6 1 21.0 17.9 1
White fly (Bemisia sp.) 44.2 26.6 2 41.0 37.1 2 21.0 15.3 2
Shoot fly 16.7 25.0 3 16.0 15.9 2 1.0 10.0 1
Leaf cutter ants 14.4 35.2 4 12.0 14.2 2 10.0 25.3 1
Leaf hoppers 12.8 15.9 2 4.0 15.6 2 0.0 -
Fruit fly (in stems) 12.0 26.4 2 24.0 37.3 2 9.0 36.6 1
Horn worm 7.2 18.4 2 2.4 20.8 2 2.0 11.7 1
White fly 5.6 12.1 2 16.0 22.7 1 19.0 44.6 2
Chrysome lids 4.2 11.9 1 4.0 14.6 2 0.0 -
Tingids 3.6 22.7 2 8.0 18.8 2 4.0 15.7 1
Mites 2.0 3.5 2 25.0 41.0 2 27.0 60.0 3
Termites 1.0 36.7 2 0.0 2.0 27.5 1
Ants 0.6 10.0 2 2.0 14.0 1 0.0 -
Cutworms 0.6 45.0 1 0.0 0.0 -
Stemborers (hepidopterous) 0.3 15.0 1 0.4 30.0 2 0.0 -
Scale insects 0.0 0.0 1.0 35.0 2
Stemborers (colepterous) 0.0 -0.0 1.0 5.0 1
I/ 305 farms included
2/ 248 farms included
3/ 162 farms included
4/ Intensity of attack using scale of 1-4 with 1 being low and 4 high intensity
1/
Table 4. Distribution of major insect occurrence among zones, second visit (% of farms).
Agro-economic analysis of cassava production in Colombia.
ZONE
Insect I II III IV V
Thrips 61 89 100 100 83
Gall midge 25 46 68 68 85
White fly (Bemisia sp.) 70 10 .24 26 71
Shoot fly 8 32 5 38. 0
Leaf cutter ants 20 6 32 21 2
Leaf hoppers 2 2 0 0 15
Fruit fly (in stems) 7 76 3 6 8
Horn worm 0 2 0 0 10
White fly 46 5 16 0 4
Chrysome lids 5 6 0 0 6
Tingids 15 3 13 12 0
Mites 7 8 38 15 44
1/ Preliminary data from 248 farms
Table 5. Preliminary
Disease
Brown leaf spot
White leaf spot
Cassava ash disease
Cercospora leaf blight
Phoma leaf spot
Superelongation
Cassava bacterial'blight
Root rotting
Leaf sooty mold
Frog skin root disease
data on disease occurrence in cassava. Agro-economic analysis of cassava
production in
I/
First visit -
% of % of
farms lot
34.4 22.3
28.2 33.1
19.0 39.7
15.1 16.8
15.0 19.9
5.9 22.5
4.6 26.7
1.3 42.5
0.3 10.0
0.0
Inten4
sity -
2
2
2
2
2
3
2
3
1
production in
1/ 305 farms included
2/ 248 farms included
3/ 162 farms included
4/ Intensity of attack using a scale-of 1-4 with 1 being low and 4 high intensity.
Co0 ombia.
Second
% of
farms
53.6
58.5
43.1
23.0
54.4
11.7
12.9
1.2
2.4
0.0
2/
visit
% of
lot
32.9
40.8
42.3
25.6
32.7
44.5
38.3
15.0
42.3
Intenr 7
sity
2
2
2
1
2
4
3
3
3
Third
% of
farms
34.6
35.8
20.4
6.8
43.2
1.2
9.3
0.0
1.9
3.7
visit
% of
lot
36.0
53.7
56.8
39.5
35.8
47.5
44.7
26.7
-- --
Inten-,
sity
2
2
2
2
J
1
2
Table 6. Distribution of major disease occurrence among Zones, second visit (% of farms).
A_~ro-economic analysis of cassava production in Colombia.
Z 0 N E
Disease I II III IV V
Brown leaf spot 28 32 79 68 83
White leaf spot 71' 95 28 9 54
Cassava ash disease 43 57 84 15 10
Cercospora leaf blight 39, 8 40 18 14
Phoma leaf spot 72 71 34 32 42
Superelongation 2 0 66 9 0
Cassava bacterial blight 2 0 11 24 37
Root rotting 2 3 0 0 0
_- Preliminary data from- 248 farms.
1/ Preliminary data from 248 farms.
Table 7. The ten most important weeds in cassava in terms of
proportion of sample farms where they occurred,(first visit).
Agro-economic analysis of cassava production in Colcnbia.
1Weed
% of farms
Pteridium caudatum
Sida acuta
Commelina difusa
Bidenes pilosa
Melinis minutiflora
Portulaca oleracea
Cyperus ferax
Rychardia scabra
Cyperus rotundus
Drymaria cordata
24
18
17
16
14
12
10
10
10
9
Weed density
(Plants/ha).
78.000
90.000
136.000
102.000
134.000
168.000
148.000
84.000
188.000
234.000
Table 8. D stribution of labor requirements and variable costs among
cassava production activities in Colombia.
Labor requirements
Land preparation
Planting
Re-planting
Weeding
Fertilizers and apl.
Insecticides and apl.
Harvesting and packing
Seed
Total
Mech. land
pnerrat ion
Man-days %
per ha.
118
9.1 10.4
0.3 0.3
46.8 53.4
0.5 0.6
0.3 0.3
30.7 35.0
87.7
87.7
100
Manual land
norenar t. on
Man-days %
per ha.
25.0 23.6
10.8 10.2
0.6 0.6
43.7 41.2
0.3 0.3
0.6 0.6
24.9 23.5
105.9
100
Variable
costs (?)
23
8
1
36
1
1
24
6
100
Source: Rafael O. Diaz, Per Pinstrup-Andersen y Rub6n Dario Estrada. Costs
and Use of Inputs in Cassava Production in Colombia: A Brief Des-
crijtion. CIAT, Series EE',No.5, September, 1974
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