Experimental design and data collection procedures for IBSNAT collaborators

MISSING IMAGE

Material Information

Title:
Experimental design and data collection procedures for IBSNAT collaborators
Alternate title:
Experimental design and data collection procedures for International Benchmark Sites Network for Agrotechnology Transfer collaborators
Physical Description:
94 p. : ; 28 cm.
Language:
English
Creator:
Jones, C. A
International Benchmark Sites Network for Agrotechnology Transfer
Publisher:
IBSNAT
Place of Publication:
Hawaii
Publication Date:

Subjects

Subjects / Keywords:
Agriculture -- Technology transfer -- Data processing -- Design   ( lcsh )
Crops -- Data processing -- Simulation methods   ( lcsh )
Genre:
bibliography   ( marcgt )
non-fiction   ( marcgt )

Notes

Bibliography:
Includes bibliographical references (p. 93-94).
Statement of Responsibility:
prepared by IBSNAT collaborators ; edited by C.A. Jones.
General Note:
"Prepared under a project funded by the Agency for International Development (DAN-4054-C-00-2071-00)."

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
oclc - 630174209
ocn630174209
Classification:
lcc - S565.7 .E97 1980z
System ID:
AA00007155:00001

Full Text










EXPERIMENTAL DESIGN AND DATA COLLECTION PROCEDURES

FOR IBSNAT COLLABORATORS


1/
Prepared by IBSNAT collaborators-




















Prepared under a project funded by the Agency

for International Development (DAN-4054-C-00-2071-00).






1/ Edited by C. A. Jones, Plant Physiologist, USDA, Agricultural

Research Service, P. 0. Box 748, Temple, TX 76503, USA. Special

thanks to F. B. Cady, J. A. Comerma, P. T. Dyke, and 3. A. Silva for

help in preparing the first draft.








2


Experimental Design and Data Collection Procedures

for IBSNAT Collaborators

Page
I DESIGN OF IBSNAT EXPERIMENTS ---------------------------- 5

A. Site Selection and Characterization ------- ------- 5

B. Treatment Alternatives --------------------- 7

C. Number of Treatment Factors ------ -------------- 9

D. Experimental Design ---------------------------- 11

E. Plot Size ------------------------------- ------12

F. Examples of Possible Experiments ---------- 14

II THE MINIMUM IBSNAT DATA SET ------------------------------ 18

A. FORM A Institutional Information ------------- 22

B. FORM B Nearby Long-Term Climatic Stations ----------- 24

C. FORM C Daily Weather ------------------------------- 26

D. FORM 0 Field -------------------------------- 28

E. FORM E Experiment ---------------------------- 30

F. FORM F Experimental Factors and Levels -------- 32

G. FORM 6 Experimental Layout ---- -------------- 36

H. FORM H Plot -- --------------------- ---- 38

I. FORM I Soil Fertility ---- ----------------- 40

3. FORM J Soil Water ---------------------- 45

K. FORM K Tillage ------------------------------------- 48

L. FORM L Cultivar ----------------------------------- 50

M. FORM M Planting ------------------------------------- 52

N. FORM N Fertilizers, Inoculants, and Amendments -------- 54

0. FORM 0 Biocides and Hormones ----------------------- 56

P. FORM P Irrigation ----------------------------------- 58













Q. FORM Q -

R. FORM R -

S. FORM S -

III CHRONOGRAM OF

IV APPENDIXES

A. Appendix

B. Appendix

C. Appendix



0. Appendix

E. Appendix

F. Appendix

G. Appendix



H. Appendix

I. Appendix

J. Appendix

K. Appendix

L. Appendix

M. Appendix

N. Appendix

0. Appendix

P. Appendix

Q. Appendix

R. Appendix


Crop

Growt

Plant

ACTIVE


Damage ----------------------------------

:h Stage and Yield Components -------------

SNutrient Concentrations ---------------

ITIES FOR A TYPICAL EXPERIMENT ---------


1 Institute Codes for IBSNAT Experiments -

2 Fertilizer and Amendment Material Codes -

3 -- Fertilizer, Inoculants and Amendment

Placement and Method Codes ----

4 Biocide Product Codes ---- ------

5 Maize Growth Stage Codes ---------

6 Maize Harvest Codes ---- -------

7 Grain Sorghum, Wheat, Rice Growth Stage

Codes ----------------- -------------

8 Grain Sorghum, Wheat, Rice Harvest Codes -

9 -- Soybean and Field Bean Growth Stage Codes-

10 Soybean and Field Bean Harvest Codes ---

11 Peanut Growth Stage Codes ---------------

12 Peanut Harvest Codes ---- --- -- --

13 Aroid Growth Stage Codes -- ------

14 Aroid Harvest Codes -----------

15 Cassava Growth Stage Codes ----------

16 Cassava Harvest Codes ------ -------

17 -- Potato Growth Stage and Maturity Rating -

18 -- Potato Harvest Codes -------------------


V LITERATURE CITED


-----------------------------------------









Experimental Design and Data Collection Procedures

for IBSNAT Collaborators

IBSNAT has two objectives: (a) to accelerate the flow of

agro-technology from Its site of origin to new locations, and (b) to

increase the success of this transfer. IBSNAT will use soil-crop

weather simulation models to accomplish these objectives. However,

simulation modeling approaches used by IBSNAT collaborators must be

adequately tested and validated in a representative network of

experimental sites. Such model testing requires that numerous

experiments be conducted and that in each experiment a minimum set of

soil, crop, and weather data be recorded. These data sets must then

be assembled and used to test and calibrate appropriate simulation

models.

The purpose of this manual is to (a) describe some experimental

designs which are appropriate for testing and validating simulation

models, (b) describe the minimum set of soil, crop, and weather data

to be recorded in each experiment, and (c) provide forms to record the

minimum data set. It is important to note that experiments described

here can also be analyzed by site-specific procedures. IBSNAT

collaborators are encouraged to do normal statistical analyses and to

publish the results of their experiments in the traditional manner.

Data from experiments with complete site characterization will be

available to IBSNAT collaborators to compare their experimental

results with those from other countries.











DESIGN OF IBSNAT EXPERIMENTS

Cooperation with IBSNAT does not require that researchers conduct

specific experiments. IBSNAT recognizes that research objectives and

experimental approaches are determined by the agronomic problems of

individual collaborators. Cooperation requires only that the minimum

data set be collected and shared within IBSNAT for experiments of

general interest to other IBSNAT collaborators.

The major differences in experiments described here and those

normally conducted for site-specific analyses are: completeness of

site characterization, size of experimental plots, and number of plant

growth observations. However, the quality and quantity of results

obtained from these experiments as well as additional information on

other experiments obtainable through IBSNAT should more than offset

the additional labor involved.



SITE SELECTION AND CHARACTERIZATION

IBSNAT-related experiments may be conducted on experiment

stations or in farmers' fields. As in any agronomic experiment, the

site should be selected to (a) be representative of an important or

otherwise interesting agroenvironment, (b) be easily accessible for

routine observation and sampling, (c) be conducted near permanent or

portable weather stations to permit collection of accurate weather

data on a daily basis. In addition, the experimental area should

consist of a single soil series, and sites should be selected to

minimize or eliminate soil variability that may affect crop

performance. During site selection the collaborator should identify

the taxon at the site, conduct (if possible) a detailed soil survey of










the site, and take preliminary auger samples throughout the site to

assure that the soil is uniform.

It is very important that all IBSNAT sites be characterized as

fully as possible to (a) permit valid extrapolation of results to

similar locations and (b) to provide as much information as possible

about the conditions under which experiments are conducted. Thus, the

IBSNAT minimum data set includes a complete soil characterization at

each experimental site. After site selection, the cooperator should

request this characterization by contacting the AID country mission or

writing to: Dr. T. S. Gill, S&T/AGR/RNR, USAID/Washington, D.C. 20523

USA

IBSNAT will arrange for full characterization of at least one

pedon near the experimental plots. If necessary, IBSNAT will assist

the collaborator, to:

(a) fully describe and partially characterize a second pedon near

the experiment,

(b) conduct satellite sampling by auger within the experimental

location to determine variation in selected properties, e.g., residual

effects of previous management and subsurface morphological variation,

(c) produce an oriented plot sketch with a map of surface

features such as slope, microrelief, and aspect,

(d) provide full documentation of pertinent site information,

e.g., previous management history and special mention of site and soil

conditions which are likely to affect crop growth and development.

IBSNAT will provide special forms for recording such site

characterization data. They will be used to create a computerized

Pedon Data File (PDF) and an information booklet describing each

experimental site.









It would be very desirable for individual countries or regions to

set up their own networks of sites representing a range of conditions

(weather, soil, and/or management) of particular interest in that

region. These'sites could be used for coordinated regional trials of

local interest as well as of interest to IBSNAT.



TREATMENT ALTERNATIVES

Selection of treatment factors is the responsibility of the

IBSNAT collaborator. Foremost, the selection should be based on the

needs of the collaborator's local, national, or international programs

or problems. However, the following factors are of general interest

to IBSNAT because simulation models which consider these factors are

available.

Planting Dates

Planting dates should be manipulated to take advantage of local

weather conditions. Experiments with a range of planting dates (15 to

30 days between planting dates in many crops) can be used to test the

sensitivity of models to different weather conditions.

Variety Trials

Cereals and legumes normally have a wide range of maturity

genotypes, plant types, and disease and insect resistance. Several

crop models simulate the growth of a range of maturity genotypes and

plant types and it is often possible to adjust both maturity genotype

and planting date to obtain the optimum fit of cultivar and

environment.












Plant Density

Plant density is used in several crop growth models, and these

models can be used to predict the optimum density for a particular

location. Experiments are needed to test these models.

Irrigation

Irrigation experiments can be used to determine the optimum

timing and amount of irrigation. When simulation models have been

adequately tested, they can provide the same information much more

rapidly and inexpensively at any site desired

Fertilizer Amounts and Sources

IBSNAT currently has access to models which predict the amount of

N, P, and lime needed by crops as well as the effects of nutrient

deficiency and aluminum toxicity. Experiments with a wide range of

fertilizer and lime rates, sources, and methods of application can be

used to test and improve these models.

Drainage

Surface and/or subsurface drains are needed for crop production

in many areas. Several models predict the behavior of drainage

systems and their effects on crop growth. Experiments are needed to

test and improve these models.

Residue Management

Management of crop residues through incorporation, removal,

addition of green manures, etc. can affect infiltration, runoff, soil

erosion, soil tempearture, and nutrient cycling. Models predict these

effects, but they need to be tested and may need modification for use

in the tropics.











Pest Control

Few simulation models now consider the full range of effects of

insects, diseases, and weeds on crop growth. However, data sets with

pest variables would be useful for future model development.

Erosion Control

Erosion control is.a key to long-term agricultural productivity.

Models can predict the long-term consequences of different types of

erosion control practices, but they need testing under tropical

conditions.

Soil and/or Climatic Variability

The same experiment or treatment can be installed on several

sites varying in soil and/or weather conditions. This type of

experiment replicated over space and/or time is very valuable in

determining the sensitivity of models to a wide range of experimental

conditions.



NUMBER OF TREATMENT FACTORS

Four types of experiments are anticipated: zero-factor,

single-factor, two-factor, and multifactor experiments.

Zero-factor experiments consist of a single plot or several plots

with no imposed treatment variable. The objective of this type of

experiment is to monitor closely the growth of the crop and/or changes

in the soil and use the data for model testing or model development.

Zero factor experiments are often replicated over time and space to

produce several data sets with considerable climatic (and/or soil)

variation. These experiments, when repeated over a wide range of

environmental conditions and years, are very useful for model












evaluation and extrapolation. They have the added advantage of

resembling farmers' fields and can be conducted using normal

agricultural equipment. Border effects are small, and multiple

samples can easily be taken.

Single-factor experiments are those in which a single treatment

variable (e.g., several fertilizer rates, or several cultivars, or

several planting dates) is imposed. The treatment factor will

normally have two or more categorical states (e.g., tillage

implements, planting dates, or times of irrigation) or three to five

quantitative levels (e.g., rates of fertilizer or lime application,

irrigation amounts, planting densities). The number of treatments in

a single-factor experiment is the number of categorical states or the

number of quantitative levels. These experiments can be analyzed by

standard analysis of variance or regression procedures for evaluation

of planned comparisons among the treatment means. The data can also

be used to test the sensitivity of crop simulation and extrapolation

models to a single treatment factor. For these reasons, single-factor

experiments are often preferred by both experimentalists and modelers.

Two-factor experiments are factorial experiments utilizing two

treatment factors. The number of treatments is the product of the

number of levels or states for each of the two factors. These

experiments permit analysis of both simple effects and interactions of

the two treatment factors, and response surfaces can be produced if

both factors have several quantitative levels. Despite these

advantages, the number of plots in two-factor experiments is often

larger than in single-factor experiments. If collection of the











complete minimum data set from all plots is prohibitive, collaborators

may wish to collect complete minimum data sets on selected treatments.

Multifactor experiments consisting of combinations of several

management practices (management packages) such as varieties,

fertilizers, pest control, etc. are often used to compare farmers'

practices with several alternative management packages. For example,

farmers' practices may be compared with one treatment which includes

all recommended practices (improved variety, fertilization, pest

control, etc.). Another treatment might include recommended practices

with another variety or fertilizer rate. The advantage of this type

of experiment is that, like zero-factor experiments, it closely

mirrors the actual situation occurring in farmers' fields.


EXPERIMENTAL DESIGN

In single-factor and two-factor experiments, treatments are

assigned to the experimental plots by rules restricting the

randomization of treatments to plots. In the IBSNAT network, most

collaborators will use completely randomized designs (no restriction

on randomization) or randomized complete block designs. Small

experiments with a limited number of treatments and replication, and

with relatively homogeneous field plots, would best utilize completely

randomized designs. In general, however, the additional effort needed

for blocking is minimal while reduction of experimental variability

can be considerable.

The basic design principle of a randomized complete block design

is to maximize variability among the blocks and to minimize

variability among the plots within a block. Two guidelines are












helpful. Blocks should be oriented along a major gradient such as

slope or fertility. The long axis of rectangular pilots should be

parallel to the major gradient. Contiguous and compact blocks, and

contiguous plots within a block, are usually, but not always,

consistent with the basic blocking principle. Three of four

replications are usually sufficient, especially in a series of field

experiments with the same treatments. More replication may be needed

for site-specific experimentation, depending on site variability.

Many other experimental designs such as fractional factorial

designs including more than two factors at two levels can be used.

These are especially useful for determining the limiting factor at a

specific site. These may or may not be replicated.


PLOT SIZE

It is impossible to specify plot sizes and dimensions adequate

for IBSHAT experiments. These decisions will be made by collaborators

after considering the specific type of experiment, the need for border

area, the available area, and many other factors.

For collection of the minimum data set, the basic experimental

plot must often be larger than usual to accommodate harvests of both

biomass and final economic yield. Examples of possible plot

dimensions for the IBSNAT crops are given in Table 1. Researchers may

modify these dimensions, plant populations, etc. as needed. For

example four-row plots may be sufficient for experiments with minimal

border effects. The two outside rows would then be used for both

phenological observations and for border rows.















Table 1. Examples of acceptable plot dimensions. Researchers are free to modify these dimensions and numbers as needed.


Rows in
Biomass Length Length
Number of and of of Number of Plants
Number Plants/ Row Plants/ Biomass Harvest Biomass Harvest
Crop of Rows m2 Spacing row Harvests Plots Plots Plots Biomass Harvest

(m) m m

Maize 4 6 0.67 4 3 2 1.0 9.0 8 72
Sorghum 4 15 0.67 10 3 2 0.5 3.6 10 72
Wheat and rice 15 250 0.20 50 3 5 0.25 1.0 63 250
Soybean, peanuts,
and field beans 4 30 0.67 20 4 2 1.0 3.6 40 144
Cassava 8 1 1.0 1 3 6 1.0 1.0 6 6
Aroids 6 4.63 0.6 1.67 4 4 0.6 3.0 4 20
Potato 6 4.5 0.9 4 3 4 0.5 2.5 8 40











If the treatments are allocated to the experimental plots

according to a randomized complete block design, then the end of the

plot used for biomass harvests would be selected at random and would

be the same for all plots within a block.

General experimental plot technique should be followed. For

example, soil and surface water movement between plots should be

controlled.

With phenological observations and biomass harvests, plot

activity is increased. Walking and general experimental traffic

between rows in the final economic yield harvest area should be

minimized. Biomass harvest rows should be entered from the biomass

end of the plots to avoid unnecessary disturbance of the final yield

plots.



EXAMPLES OF POSSIBLE EXPERIMENTS

Examples of zero factor, single factor, and two factor

experiments are included. These examples simply illustrate

applications of the principles described above.

Effects of Altitude on Soybean Growth

This is a hypothetical experiment using a series of five sites to

determine the adaptability of an improved soybean cultivar to

variation in soil and climate along the altitudinal transect on an

island with no previous history of soybean production.

Five sites are selected. These range from a site with a Typic

Chromustert, fine kaolinitic, isohyperthermic at 10 m elevation to a

site with a Typic Hydrandept, thixotropic, isothermic at 700 m. A

single experimental area is selected at each site. Four plots are









located in each area. An automatic recording weather station is

installed at each site. Nonlimiting amounts of fertilizer and

amendments are applied according to soil test and experience of the

agronomists and soil scientists involved. Irrigation systems are

installed at two of the sites with unreliable rainfall. Two crops are

planted each year at each site for two years to obtrain a range of

climatic variation. The minimum data set is taken at each location

using the four replicates in each experimental area to obtain a

measure of variability in the various measurements. Stepwise multiple

regression is used to relate yields and physiological maturity dates

to such factors as ambient temperature, solar radiation, and rainfall

(or irrigation amounts) during critical periods. The minimum data

sets are used to test and calibrate a soybean growth model provided by

IBSNAT. This model is then used with existing weather data from other

sites on the island to make predictions concerning the best locations

and planting dates for soybean production on the island.

Effects of Soil Acidity on Crop Growth

The government of a tropical country is encouraging subsistence

farmers to migrate to sparsely populated areas with acid, infertile

Ultisols. Lime is expensive because of transportation costs, and the

objective of this experiment is to determine the optimum lime rates

and levels of aluminum saturation for the two most important crops,

maize and peanuts.











Four rates of lime are used to establish five levels of soil pH

and aluminum at each of two sites with slightly different soils. Four

replicates are used in a randomized complete block design. Plot sizes

are those needed to obtain the minimum data set for maize (Table 1).

A one-year maize-peanut rotation is used for two years at each site.

The minimum data set is taken at each site. Results are analyzed with

standard statistical procedures. The experimental results are also

used to validate a general agricultural management model provided by

IBSNAT. This model considers the effects of lime, fertilizer N source

and rate, and N fixation on soil pH and aluminum saturation. It also

simulates the effects of aluminum saturation on maize and peanut

growth. Model coefficients are adjusted for local crop cultivars, and

the model is then used in conjunction with routine soil analyses to

recommend the economic optimum combination of lime rates, fertilizer

sources and rates, and crop species for several sites with different

soil and climatic conditions.

Effects of Irrigation and Fertilizer Nitrogen on Maize Yields

Irrigation and fertilizer nitrogen are the two most important

factors limiting maize yield in this region. A government development

agency needs to determine the response surface to these two factors

for planning a new irrigation project. A large factorial experiment

is undertaken to provide this information.

According to Hanks et al. (1980) the line-source sprinkler system

has the advantage of minimizing the amount of land needed for the

experimental area as well as providing continuous variation from

excess to no irrigation. The disadvantage of the line-source

sprinkler system is that no valid experimental error exists for











evaluating the main effects of irrigation levels (Cochran and Cox,

1957). In most experiments, differences among irrigation levels,

averaged over the fertilizer rate treatments, are well known and a

statistical evaluation between the two treatment factors. The

interaction, as well as the main effect of nitrogen rate, can be

evaluated with a valid measure of experimental error. Johnson et al.

(1983) give an alternative analysis if the main effect of irrigation

is of primary importance.

Four irrigation rates, four N rates, and three replications are

used in a design like that described by Hanks et al. (1980). Because

of manpower limitations, the minimum set of soil and plant data are

collected for only two irrigation rates and two N rates. Only yield

data are collected in the other treatments.

Effects of Improved Management Packages on Crop Yields

This experiment was conducted for two years at CATIE (Centro

Agronomico Tropical de Investigacion y Ensenanza). It compares three

technological packages with the farmers' current technology.

Recommended technology (varieties, fertilizers, pest control) for

(a) a modified (low fertilization) maize-sorghum intercrop, were

compared with the farmer's practice. The treatments were imposed

without replication at 60 sites in Central America. The data were

analyzed statistically using multivariate linear models and by using

agroclimatic models. Weather data were collected at each site and at

nearby weather stations. Initial soil fertility, soil water content,

biomass production, and crop yields were measured at all sites. Soils

ranged from Typic Haplustalfs to Mollic Ustifluvents. This project

required a network of 4 researchers in 4 countries.











THE MINIMUM IBSNAT DATA SET

The minimum IBSNAT data set is a relatively balanced set of

weather, soil, crop management, and crop response data. It will be

used by many researchers to validate a variety of crop models.

Therefore, it is important that the data sets be as complete and as

accurate as possible.

Cooperators should attempt to measure all data requested;

however, if human error or instrument failure preclude obtaining the

entire minimum data set, the cooperator should send the partial set to

IBSNAT. In most cases, the partial data set can also be used.

The minimum data set will be stored in a number of computer files

which are cross-referenced with identification codes. These codes are

all limited to a maximum of six characters and many are defined in the

tables and appendices of this manual. In the case that the

appropriate code is not defined in the manual, the cooperator should

enter 999999 in the blank and clearly describe what the code

represents. It is very important that these codes be recorded

accurately.

Simulation models developed by IBSNAT collaborators must be

adequately tested before they can be used with confidence. This

requires that soils, weather, and crop response data from a number of

experiments be collected, computerized, and used for comparison of

actual and simulated crop growth. These comparisons can then be used

to improve IBSNAT simulation models.

To facilitate the process of data collection and computerization,

experimental scientists, modelers, and statisticians have designed the

"Minimum IBSNAT Data Set". This data set is designed to capture the













minimum amount of soil, weather, and crop response data needed to test

simulation models available to IBSNAT. The data set is designed to be

collected on forms provided by IBSNAT and to be stored in the IBSNAT

data management system.

Dual-purpose forms are provided to collaborators by IBSNAT.

These forms have two purposes. First, they provide a convenient log

of initial conditions, management activities, weather data, and crop

and soil responses for the collaborator's personal use. Second, they

provide a means to transfer experimental data to the centralized

IBSNAT data base for testing simulation models. The data will be

entered into a centralized data management system. Routine

statistical analyses will be conducted, and the collaborator will be

sent summaries of his experimental data in convenient tabular form.

The Minimum IBSNAT Data Set is divided into 19 types of data to

be recorded on 19 forms (A-S). The types of data to be recorded on

each of the forms are summarized in Table 2. Note that three types of

experiments are defined: (a) those in which fertility is a variable

or is expected to be suboptimal, (b) those in which water is a

variable or is expected to be suboptimal, and (c) other experiments.

The minimum data set varies among the three types of experiments. The

detailed requirements are explained in the following sections, which

describe the 19 forms used to record data. These forms have been

designed to minimize the time required to record the necessary

information. For example, the same forms can often be used for

several experiments, and repetitive entry of information is minimized.










20


Table 2. Summary of the data requirements of the IBSNAT Minimum Data Set.
The minimum requirements for three types of experiments are indi-
cated with X. Optional data are indicated with 0.


Type of Experiment
Type of Data Form
Fertility Water All other
suboptimal suboptimal experiments
or variable or variable


Institutional information A X X X
Long-term weather data from B 0 0 0
nearby weather stations
Daily weather data during the C X X X
experiment
General information about the D X X X
experimental area (field)
General information about the E X X X
experiment
Codes and cross-references F X X X
of experimental factors,
levels, and plots
Experimental layout G X X X
General plot information H X X X
Soil fertility I
Preplant surface samples X X X
Postharvest surface samples X 0 0
Preplant and postharvest X 0 0
subsurface samples
Preplant and postharvest 3 0 X 0
volumetric soil water in
profile
General tillage information K X X X
Crop cultivar information L X X X
General planting information M X X X
General information on N X X X
fertilizer, inoculant, and
amendment application
General information on biocide 0 X X X
and hormone application
Irrigation information P X X X
General information on damage Q X X X
to the crop
Data on growth stage and yield R X X X
components several times
during the season
Plant nutrient concentrations S X 0 0









Also note that the minimum IBSNAT data set need not be collected

for each plot or each treatment of an experiment. For example, a

two-factor fertilizer rate experiment could easily have 15

treatments. The cooperator may not have resources to collect the

minimum data set on all treatments. He may choose to report the

minimum data set on only a few treatments but to report final economic

yields for all 15 treatments. All cooperators must recognize that our

interests and resources vary. IBSNAT asks only that cooperators

collect the minimum data set on a few carefully chosen treatments of

large experiments. The following sections describe the Minimum IBSNAT

Data Set for each of the 19 types of data to be recorded.






22


FORM A INSTITUTIONAL INFORMATION

FORM A gives Institutional information including the INSTITUTION

IO (from Appendix 1), INSTITUTE NAME, MAILING ADDRESS, COUNTRY, TELEX,

and TELEPHONE numbers.









FORM

INSTITUTIONAL


A

INFORMATION


INSTITUTE ID:

INSTITUTE NAME:

MAILING ADDRESS:







COUNTRY:

TELEX:

TELEPHONE:









FORM B NEARBY LONG-TERM CLIMATIC STATIONS

It is usually not necessary to have long-term mean weather data

to test simulation models. However, it is often important to obtain

long term weather data from weather stations at or near the site of a

experiment station to develop weather simulation models for the region.

FORM B is used to alert IBSNAT to the existence of long-term

weather data for the region. The information is not part of the

minimum IBSNAT data set, but collaborators should obtain the

Information if possible. Up to three nearby weather stations with

long-term data can be reported. The information requested include the

INSTITUTE ID, the WEATHER STATION NAME, the ORGANIZATION RESPONSIBLE

for the weather station, the ADDRESS of the organization, the

LATITUDE, LONGITUDE, and ELEVATION of the station, and the DISTANCE

from that weather station to the experimental site.

For each weather station, the approximate number of years of

record for each of the following weather variables should be

reported: MINIMUM and MAXIMUM TEMPERATURES, PRECIPITATION, SOLAR

RADIATION, HOURS OF SUNSHINE, PERCENT CLOUD COVER, HUMIDITY, SOIL

TEMPERATURE, WIND, RAINFALL INTENSITY, AND OTHER VARIABLES. If any

variable is not measured at the station, N/A should be recorded.








25


FORM B

NEARBY LONG-TERM CLIMATIC STATIONS


INSTITUTE ID:

WEATHER STATION NAME:

ADDRESS OF

RESPONSIBLE

ORGANIZATION

LONGITUDE (deg.min.):

LATITUDE (deg.min.):

ELEVATION (m):

DISTANCE FROM SITE (km):


YEARS OF RECORD


TMIN

TMAX

PRECIPITATION

SOLAR RADIATION

HOURS'OF SUNSHINE

PERCENT CLOUD COVER

HUMIDITY

SOIL TEMPERATURE

WIND

RAINFALL INTENSITY

OTHER (SPECIFY)











FORM C DAILY WEATHER

FORM C is used to record daily weather data during the course of

the experiment. If possible, the data should begin at or before the

date of the initial soil sample and continue until the date of the

final soil sample. The minimum data set requires the DATE, THIN,

TMAX, PRECIPITATION, and SOLAR RADIATION. If gaps in the record occur

due to equipment failure or human error, 999 should be entered in the

space to indicate missing data.

In addition, space is provided to record the following optional

weather data: DRY BULB TEMPERATURE, WET BULB TEMPERATURE, WIND RUN,

and COMMENTS concerning special events which may have some effect on

the crop. These events (e.g., hail, wind storms, sand blasting by

blowing soil, frost damage to the crop, etc.) should be noted in the

space set aside for comments. A qualitative estimate of damage to the

crop would also be helpful.

The data required for the minimum data set permits calculation of

reference evapotranspiration by the Radiatio, Priestley-Taylor,

Hargreaves, Blaney-Criddle, Jensen-Haise, and Thornthwaite methods.

By including wet-bulb and dry-bulb temperatures and wind run (2m),

somewhat more accurate estimates may be obtained by the Radiation and

Blaney-Criddle methods. In addition, the Penman method may be used.

Discussions of the various methods can be found in Doorenbos and

Kassam (1979), Doorenbos and Pruitt (1977), Hargreaves (1975, 1977)

and 3ensen (1973).

A detailed discussion of weather station design and maintenance

and the use of weather data in agriculture is found in World

Meteorological Organization (1981).












FORM C

Daily Weather


INSTITUTE ID:


DO/MM/YY THIN

(C)


REQUIRED

THAX

(C)


TIME OF NORMAL WEATHER OBSERVATIONS:

RECOMMENDED

PRECIP. SOL. RAD. WET BULB DRY BULB WINDRUN COMMENTS


(mm)


(M1/m2)


(km)


---------









FORM 0 FIELD

FORM 0 is used to record general information about the field on

which a particular experiment is conducted. These data are stored

separately from the actual plot data and allow retrieval of all data

collected over a period of years on a particular field. The data

requested include the INSTITUTE 10, FIELD ID, REFERENCE PEDON NUMBER,

NATURAL VEGETATION in the field (e.g., savanna, deciduous forest),

approximate YEARS IN CULTIVATION (to 1985), LATITUDE, LONGITUDE,

ELEVATION, WEATHER STATION ID (up to 6 character assigned by

collaborator), and DISTANCE FROM WEATHER STATION TO FIELD. In most

cases the weather station will be located in the field. In that case,

the distance is 0.















INSTITUTE ID:

FIELD ID:

PEDON NO.:

NATURAL VEGETATION:

YEARS IN CULTIVATION (to 1985):

LATITUDE:

LONGITUDE:

ELEVATION (m):

WEATHER STATION ID:

DISTANCE FROM WEATHER STATION (kn


I) :















FORM E EXPERIMENT

The collaborator should invent a EXPERIMENT CODE (up to 6

characters) to distinguish this experiment from others conducted by

the same institute. This code will be recorded on this and subsequent

forms to identify the experiment to which the data refer.

The first page of FORM E is used to record the EXPERIMENT CODE,

EXPERIMENT NAME, a short narrative EXPERIMENT DESCRIPTION (in which

the researcher may give the reason for conducting the experiment and

other information), the name of the PRINCIPAL INVESTIGATOR(S), the

BEGINNING DATE (usually the first date of weather data) and the ENDING

DATE (the last date of weather data). The EXPERIMENTAL DESIGN with

the number of treatments and replications can be given in narrative

form. the SOIL SERIES NAME, SOIL CLASSIFICATION by Soil Taxonomy and

any other classification system, and REFERENCE PEDON NUMBER are given

in order to locate soil characterization data in IBSNAT's soil pedon

data base. The NATURAL VEGETATION and YEARS IN CULTIVATION are. given

because there are sometimes used to condition the rates of soil

processes. LATITUDE, LONGITUDE, and ELEVATION of the experiment and

DISTANCE FROM WEATHER STATION are also given.

Some experiments are conducted in valleys or near forests where

the sun's direct rays are obstructed in the morning or evening. The

VERTICAL ANGLE from horizontal to the top of hills or other

obstructions to the sun's rays should also be estimated.











FORM E

EXPERIMENT



INSTITUTE ID: EXPERIMENT 10:

EXPERIMENT NAME:

EXPERIMENT DESCRIPTION:





PRINCIPAL INVESTIGATORSS:



BEGINNING DATE (dd/mm/yy):

ENDING DATE (dd/mm/yy):

EXPERIMENTAL DESIGN:





SOIL SERIES NAME:

SOIL CLASSIFICATION:



REFERENCE PEDON NUMBER:

NATURAL VEGETATION:

YEARS IN CULTIVATION:

LATITUDE (deg. min.):

LONGITUDE (deg. min.):

ELEVATION (m):

DISTANCE FROM WEATHER STATION (m):

VERTICAL ANGLE FROM HORIZONTAL TO THE TOP OF HILLS OR OTHER

OBSTRUCTIONS TO SUN'S RAYS (deg):












FORM F EXPERIMENTAL FACTORS AND LEVELS

FORM F is used to list the locally assigned TREATMENT

IDENTIFICATION code (which should not exceed 4 numbers and/or

letters), the TREATMENT NAME, and the PLOT NUMBERS belonging to the

treatment.

Below, space is provided for the REPLICATE IDENTIFICATION CODE,

REPLICATE NAME, and PLOT NUMBERS. This page provides the necessary

information to cross reference plots, treatments, and reps. The

TREATMENT NAME and REPLICATE NAME are provided for convenience and can

be left blank.

FORM F is used to assign experimental factor and level codes,

describe those, and assign plots to the various combinations of

factors and levels.

The cooperator first enters the INSTITUTE 1D and EXPERIMENT ID

from FORM E. This provides positive identification for the data.

Some IBSNAT experiments will have only one variable factor

(planting date, fertilizer rate, etc.); others will be two-farctor or

three-factor experiments. In the next section of FORM F, treatment

factors are described and are given identification codes. For

example, in an experiment with several rates of N both with and

without irrigation, the following factor codes and descriptions might

be assigned:



FACTOR CODE DESCRIPTION

NITRO Nitrogen fertilizer rate

IRRIG Irrigated or not irrigated










The factor codes are limited to 6 or fewer letters and numbers.

Since they will be used as headings on printed output, they should be

combinations of letters or numbers which help identify the factor.

In many experiments one or more factors will occur at several

levels or times. For example, three N fertilizer rates, six

cultivars, or five planting dates may be used. These levels are

described and given codes (up to 6 letters and numbers) in the next

section. For example:


LEVEL CODE

60

120

ADEO

NONE


DESCRIPTION

60 kg N/ha

120 kq N/ha

Adequate irrigation

No irrigation


The final portion of FROM F is used to record the plots in which

various levels of the treatment factors occur. The example is for an

experiment with three levels of fertilizer N, two levels of

irrigation, and four replicates.


PLOTS


1. 7. 16. 24

3,12, 14, 19

5. 11, 17, 23

2. 9. 13. 20

4. 8. 15, 22

6. 10, 18, 21


F

NITRO 6

NITRO 12

NITRO 24

NITRO 6

NITRO 12

NITRO 24


FACTOR (F) AND LEVEL (L) CODES

L F L F L F L

0 IRRIG ADEQ

!0 IRRIS ADEQ

10 IRRIG ADEQ

,0 IRRI6 NONE

0 IRRIG NONE

0 IRRIG NONE


F L












FORM F

EXPERIMENTAL FACTORS AND LEVELS


INSTITUTE ID:

FACTOR CODES


EXPERIMENT 10:

DESCRIPTION


LEVEL COOES


DESCRIPTION


FACTOR (F) AND LEVEL (L) CODES

L F L F L


PLOTS


L F


F L












FORM F

EXPERIMENTAL FACTORS AND LEVELS


TREATMENT ID


TREATMENT NAME


PLOT NUMBERS


PLOT NUMBERS


REP ID


REP NAME






36


FORM 6 EXPERIMENTAL LAYOUT

FORM G is used to draw and label (with plot numbers, treatment

codes, and replicate codes) the layout of the experiment. This may

provide important information for subsequent statistical analysis.

Please indicate north direction and row direction.






37


FORM 6

EXPERIMENTAL LAYOUT



Draw and Label Experiment Layout


INSTITUTE ID:


PERIMENT ID:


.










FORM H PLOT

This form provides information about the individual plots in the

experiment. If all plots are very similar, only one copy of FORM H

will be needed. However, if plots differ in area, slope, aspect,

etc., several forms may be required. The information requested

include the PLOT NUMBERS of all similar plots, as well as the PLOT

AREA, SLOPE, SLOPE LENGTH, ASPECT (direction down slope), DEPTH OF

SOIL DRAIN, DISTANCE BETWEEN DRAINS, amount of INITIAL SOIL RESIDUE

(dry weight on the soil surface), TYPE OF RESIDUE (maize stover,

grassy weeds, etc.), and any OTHER INFORMATION concerning the

condition of the plots judged to be similar. This information may be

quite important in interpreting experimental results. Finally, any

other factors which may be expected to limit crop performance in the

plots should be noted. These might include the presence of plow pans,

gravel layers, poor drainage, crusting problems, or any number of

other problems which modelers should be aware of. Models cannot

explicitly simulate all factors which can affect yields, and this

section allows the collaborator to alert the modeler to problems which

might otherwise be overlooked.

Slope length is generally used only in models concerned with soil

erosion. If no erosion is expected because the borders of the

experiment or plot are protected, the value entered should be the

width of the plot or experiment. However, if large unprotected blocks

or plots are used, the slope length is the distance from the nearest

break in slope above the experiment to the nearest break in slope or

concentration of runoff into an outlet or channel below the

experiment. Slope lengths normally vary from a few meters to about

100 meters.









FORM H

PLOT


INSTITUTE ID:

PLOT NUMBERSS:

PLOT AREA (m2):

SLOPE (%):

SLOPE LENGTH (m):

ASPECT (deg. from north):

DEPTH OF SOIL DRAIN (mm):

DISTANCE BETWEEN DRAINS (m):

INITIAL CROP RESIDUE (kg/ha):

TYPE OF RESIDUE:

OTHER INFORMATION:


PERIMENT ID:


POSSIBLE CONSTRAINTS

OR LIMITATIONS

ON CROP

PERFORMANCE














FORM 1 SOIL FERTILITY

The minimum IBSNAT data set for soil fertility measurements

differs for different types of experiments. It is much simpler when

soil fertility is not a treatment factor and the collaborator feels

that soil fertility and plant nutrition will not limit crop

performance. More measurements are required when fertility is a

treatment factor or when it is judged to be suboptimal.

Nonlimiting Fertility

When soil fertility is non-limiting the IBSNAT minimum data set

requires only preplant surface soil sampling. In these experiments,

16 to 20 surface (0-150 mm) samples should be taken from throughout

the experiment no more than two weeks before planting. If, however,

previous site characterization has revealed significant spatial

variability in soil characteristics within the experiment, 16 to 20

samples should be taken from each homogeneous area. Each group of 16

to 20 samples should be composite, mixed thoroughly and subsampled

(200 g) for chemical extraction and analysis. For most soils,

mineralization and degradation of soil proteins can be avoided by

immediately drying the subsamples at 50 to 60 C. However, drying will

irreversibly change some amorphous soils. For those, samples should

be stored in a refrigerator and analyzed as soon as possible.

The preplant surface soil samples should be analyzed for the

following according to procedures described in detail in Page et al.

(1982) and the IBSNAT manual on soil sampling and analysis:












(a) soil pH in a 1:1 soil:H20 slurry,

(b) soil pH in a 1:1 soil:N KC1 slurry,

(c) KCL-extractable NO3,

(d) KCl-extractable NH4,

(e) NH4OAc-extractable K,

(f) P extractable by one of the following:

(1) sodium bicarbonate

(2) dilute HCl + H 2SO

(3) dilute acid-flouride

(4) anion exchange resin

(g) for soils with pH < 5.5, aluminum saturation computed as a

percentage of effective cation exchange capacity.

Fertility Experiments

When soil fertility or fertilizer amounts or sources are

treatment variable, more extensive measurements of soil fertility are

required. In these experiments, preplant surface soil samples should

be taken as described above. In addition, postharvest surface soil

samples should be taken within two weeks after harvest and analyzed as

above. In most experiments of this type several fertilizer treatments

will be used. This will create differences among treatments in

postharvest (and in residual fertilizer treatments, preplant)

fertility. In order to minimize the amount of sampling and the cost

of analysis, two (or more) treatments differing widely in expected

crop response or residual fertility can be selected. These can be

sampled intensively, for both soil fertility and plant growth and can

be used to test models which simulate the effects of soil fertility.














In most cases, one treatment with nonlimiting fertility and another

with severe nutrient deficiency should be chosen for detailed sampling.

In addition to preplant and postharvest surface soil samples,

experiments with a fertility treatment variable should be sampled to

determine subsoil fertility. Preplant and postharvest subsoil samples

should be taken from each soil horizon described in soil

characterization. At least three auger samples (or one sample per

plot) should be taken from each treatment to be sampled intensively.

The samples can be composite by horizon or they can be analyzed

separately. Of course, separate analysis is preferable since it gives

an indication of spacial variability. The same chemical extractions

and analyses should be used for both surface and subsoil analyses.

FORM I is provided to record the following:

(a) method of P extraction,

(b) date of sampling,

(c) plots represented by the sample,

(d) upper and lower depths of the horizon sampled,

(e) soil Ph in H20

(f) soil pH in KCI,

(g) elemental N in extractable NO3

(h) elemental N in extractable NH4,

(i) elemental extractable P,

(j) elemental extractable K,

(k) percent Al saturation.






43


In the simplest case, only one line of data would be required.

This would be the case for experiments with uniform soil

characteristics throughout and in which soil fertility was judged to

be nonlimiting. Other experiments could require much more data,

especially those in which soil fertility is a treatment variable.










FORM I
SOIL FERTILITY


INSTITUTE IO: EXPERIMENT ID:
METHOD OF P EXTRACTION:


DO/MM/YY PLOT(S) UPPER LOWER
( .1 )


pH NO3 NH4 P K
H20 KC1 (------g/Mg-----)


~












FORM 3 SOIL WATER

As in the case of soil fertility, the minimum IBSNAT data set for

soil water measurements varies with the type of experiment. When

adequate irrigation is applied or in areas where rainfall is expected

to prevent drought stress, soil water need not be measured. In this

case, modelers will assume that the initial water content of the soil

profile is near field capacity.

If drought stress is expected to limit crop growth, preplant and

postharvest volumetric water content should be determined for the soil

horizons described in the pedon characterization data. If a layer

described in the characterization exceeds 30 cm, it should be split

for soil moisture determination. A minimum of 3 cores should be taken

from each experiment. Each depth increment of each core should be

subsampled, and gravimetric water content should be determined.

Volumetric water content is then calculated using bulk density

measurements from the soil characterization data (or other

measurements). The data should then be averaged to obtain mean soil

water by horizon at the beginning of the experiment. Care must be

taken that soil samples do not dry before wet soil weights are

obtained. This requires use of tight soil moisture cans or plastic

bags.

Preplant, postharvest, and other measurements of volumetric soil

water are recorded on FORM 3. The data required include the DATE of

sampling and the PLOT or PLOTS represented by the sample. The upper

and lower boundaries of each soil layer sampled should be recorded in

the parentheses at the head of each column. The units should be






46


centimeters. For example, (0-150) indicates that the numbers in the

column below represent the volumetric water content of the 0 to 150 mm

layer.







FORM 3

SOIL WATER

INSTITUTE 10: EXPERIMENT 10:



DO/MM/YY PLOTS ( ) ( ) ( ) ( ) ( ) ( ) ( )














FORM K TILLAGE

Tillage information is needed to estimate the effects of

incorporation and mixing of residues, fertilizers, and amendments.

The information required include the DATE of each tillage operation,

the PLOTS tilled, and IMPLEMENT CODE (Table 3), the DEPTH of tillage,

and any OTHER INFORMATION the user cares to provide concerning the

reason for or effectiveness of the operation.



Table 3. Implement Codes



Implement Implement Code Implement Implement Code



Combine 1 Harrow-springtooth 12

Tandem disk 2 Harrow-spike 13

Offset disk 3 Rotary hoe 14

Oneway disk 4 Roto-tiller 15

Moldboard plow 5 Row crop planter 16

Chisel plow 6 Drill 17

Disk plow 7 Shredder 18

Subsoiler 8 Hoe 19

Bedder/Lister 9 Planting Stick 20

Field cultivator 10 Animal-drawn implement 21

Row crop cultivator 11 Other 22












49


FORM K

TILLAGE



INSTITUTE ID: EXPERIMENT ID:



IMP

DD/MM/YY PLOT(S) CODE DEPTH OTHER INFORMATION

(mn)



















FORM L CULTIVARS

FORM L is used to provide Information concerning crop cultivar(s)

used in the experiment. This will help in assigning cultivar-specific

coefficients used in most crop growth models and will help in

interpreting cultivar response to various stresses which may occur.

The crop code (Table 4) cultivar's common and alternative NAMES, its

TYPE (e.g., open-pollinated, hybrid, inbred, short-season,

long-season, spring wheat, winter wheat, dwarf, semidwarf, tall,

etc.), its BACKGROUND (e.g., its pedigree, whether it is a land race,

selection from a specific open-pollinated composite, etc.), and

COMMENTS (e.g., disease or insect resistance, drought tolerance, names

of similar cultivars, etc.) should be provided.




Table 4. Crop codes..


Crop Code


Maize MAI

Grain sorghum SOR

Wheat WHE

Rice RIC

Soybean SOY

Field beans FIE

Peanuts PEA

Aroids ARO

Cassava CAS

Potato POT







FORM L

CULTIVARS


INSTITUTE 10:



CROP CULTIVAR ALTERNATIVE

CODE NAME NAMES


EXPERIMENT 1D:





TYPE BACKGROUND


COMMENTS









FORM M PLANTING

The minimum data set can be used with experiments with single

crops, crop rotations, or associated crops. The data required include

DATES of planting, and, in rice, transplanting, PLOTS planted with the

crop, the name of the CROP CODE (Table 4), the CULTIVAR, ROW SPACING,

SEED RATE, SEED DEPTH, and an IMPLEMENT CODE (Table 3).

If some type of paired-row planting configuration is used,

specify by entering both row widths separated by a comma in the column

titles "row spacing*. For example, a paired-row configuration for

maize with 25 cm between rows within a pair and 75 cm between pairs

would be entered as ".25, .75".









FORM M

PLANTING


INSTITUTE ID:


EXPERIMENT ID:


ROW SEED SEED IMPLEMENT


PLANTING

TRANSPLANTING

(--00/MM/YY.---)


PLOT(S) CROP CULTIVAR SPACIHG RATE DEPTH CODE

CODE (-(m)-) (seed/m) (mm)












FORM N FERTILIZERS, INOCULANTS, AND AMENDMENTS

Information concerning fertilizer, inoculant, and amendment

application is recorded on FORM N. The codes needed for this form

include a MATERIAL CODE (Appendix 2), a PLACEMENT CODE (Appendix 3),

and a METHOD CODE (Appendix 3). Appendix 2 includes codes for most

common fertilizer, organic and inorganic amendments, and rhizobial

inoculants. Appendix 3 includes codes for the placement and method of

application of the fertilizer, amendment, or inoculant.

Information to be recorded on FORM N include the INSTITUTE and

EXPERIMENT CODES, the INOCULANT SOURCE (name of the firm), DATE and

PLOTS on which the material is applied, the MATERIAL CODE, the

PLACEMENT CODE, the METHOD CODE; the DEPTH of placement or

incorporation, and the elemental amount of N, P, K and CaCO3

equivalent of lime or basic amendments applied. The CaCO3

equivalent of N-P-K fertilizers need not be recorded since it can be

estimated for the material used.

The following example if for a broadcast, incorporated

application of 100 kg single superphosphate (44%P)/ha, a banded

application of 100 kg ammonium nitrate (35%N)/ha, and application of

rhizobium as seed treatment. All applications were made to plots 6,

12, and 15 by machine.

FORM N
FERTILIZERS, INOCULANTS, AMENDMENTS

Mat. PL. METHOD ELEMENTAL AMOUNT
DD/MM/YY PLOT(S) CODE CODE CODE DEPTH H P K CaCO3
(mm) (------kg/ha-------)
15/03/84 6. 12, 15 13 02 02 15 0 44 0 0
1/04/84 6. 12, 15 01 04 02 15 35 0 0 0
1/04/84 6. 12. 15 24 08 02 10 0 0 0 0








55


FORM N

FERTILIZERS, INOCULANTS, AND AMENDMENTS



Mat. PL. METHOD ELEMENTAL AMOUNT

DD/MM/YY PLOT(S) CODE CODE CODE DEPTH N P K CaCO3


(ma)









FORM 0 BIOCIOES AND HORMONES

Information concerning insecticides, herbicides, fungicides, and

plant growth regulators is recorded on FORM 0. It includes the DATE

of application, the PLOTS to which the product was applied, a PRODUCT

CODE (Appendix 4), the AMOUNT OF ACTIVE INGREDIENT, the TARGET insect,

weed, or disease, and OTHER INFORMATION concerning the estimated

degree of damage or crop loss due to target, the effectiveness of the

control, and any other relevant information. These data may or may

not be used as model inputs, but they aid in the interpretation of

experimental results.

Every effort should be made to eliminate pest damage from

experiments.










INSTITUTE 1D:


D/MM/YY


PLOT(S)


FORM 0

BIOCIDES AND HORMONES

EXPERIMENT 10:

PROD. AMOUNT

CODE ACT. INGRED. TARGET

(kg Al/ha)


OTHER INFORMATION


~









FORM P IRRIGATION

Information concerning irrigation is recorded on FORM P. It

includes the DATE, PLOTS receiving irrigation, the AMOUNT, the

IRRIGATION METHOD CODE (Table 5), and OTHER INFORMATION concerning

unusual methods, uniformity, runoff, or other problems encountered.

Some experiments are irrigated to prevent water stress, but the

amount of irrigation water is not measured. In such cases, 999 should

be recorded as the amount. If an irrigation method other than those

in Table 5 is used, assign a code of 99 and describe the method in

detail.




Table 5. Irrigation method codes.


Method Code


Furrow 01

Alternating furrows 02

Flood 03

Sprinkler 04

Drip or trickle 05

Other 99









59


FORM P

IRRIGATION


INSTITUTE ID:


EXPERIMENT ID:


AMOUNT METHOD OTHER INFORMATION

(mm) CODE


DD/MM/YY


PLOT(S)






60


FORM Q CROP DAMAGE

FORM Q is provided to describe any event or circumstance which

resulted in crop damage (e.g., wind, pest, disease, drought, rats,

cattle, theft, etc.). We recommend that these observations be made

weekly and any crop damage or unusual circumstances be recorded.









61


FORM Q

CROP DAMAGE



OD/MM/YY OBSERVATIONS
/














FORM R GROWTH STAGE AND YIELD COMPONENTS

FORM R is provided to record the phenological growth stage of the

crop and its yield components throughout its development. It can be

used to report the growth stage of the crop at any time. It can also

be used to report the growth stage and yield components when biomass

harvests are taken prior to physiological maturity. Finally it can be

used to report final harvest data at or after physiological maturity.

The data which must be reported on FORM R are the DATE, the PLOT

(or plots) sampled, the CROP CODE (Table 4), and the GROWTH STAGE of

the crop. In addition, yield components can be reported for both

biomass and final harvests. If many yield components are measured,

more than one line of FORM R can be used for each harvest.


Maize

Maize growth stages and their codes are given in Appendix 5.

Yield components and their codes are given in Appendix 6. The minimum

data set requires that the dates of stages VE, V6, R1, and R6 be

reported (FORM R). Biomass harvests should occur at approximately

stages V6, R1, and R4; and an accurate estimate of growth stage should

be given at the time of harvest. Final harvest should occur as soon

after stage R6 as possible. The minimum data set to be collected for

biomass and final harvests and reported on FORM R is given in

Appendix 6. Of course, additional harvests and yield components can

be reported if the cooperator desires.











Grain Sorghum. Wheat, and Rice

Growth stages and their codes for grain sorghum, wheat, and rice

are given in Appendix 7. Yield components and their codes are given

in Appendix 8. The minimum data set requires that the dates of 50%

emergence 50% of main tillers with 3 collared leaves, 50% anthesis,

and physiological maturity be reported (FORM R). Since Zadock's

system does not specify these events, we recommend that emergence be

defined as stage 10, that 50% of the main tillers with three fully

expanded leaves be defined as stage 13, that 50% of the main tillers

at some stage of anthesis be defined as stage 65, and that

physiological maturity (end of grain dry matter accumulation) be

defined as stage 94. Biomass harvests should occur at approximately

stages 13, 65, and 85; and an accurate estimate of growth stage at the

time of these harvests should be given. Final harvest should occur as

soon after physiological maturity as possible. The minimum data set

to be collected for biomass and final harvests is given in

Appendix 8. Of course, additional harvests and yield components can

be reported if the cooperator desires.



Soybeans and Field Beans

Soybean and field bean growth stages and their codes are given in

Appendix 9. Yield components and their codes are given in

Appendix 10. The minimum data set requires that the dates of stages

VO, V4, R4, R6, RT, and R8 be reported (FORM R). Biomass harvests

should occur at approximately stages V4, R4, halfway between R5 and

R6, and R7; and an accurate estimate of growth stage sold be given at

the time of harvest. Final harvest should occur at stage R8. The










minimum data set to be collected for biomass and final harvests is

given in Appendix 10. Of course, additional harvests and yield

components can be reported if the cooperator desires.


Peanuts

Peanut growth stages and their codes are given in Appendix 11.

Yield components and their codes are given in Appendix 12. The

minimum data set requires that the dates of stages VE, V4, R4, R6, R7,

and R8 be reported (FORM R). Biomass harvests should occur at

approximately stages V4, R4, halfway between R5 and R6, and R7; and an

accurate estimate of growth stage should be given at the time of

harvest. Fihal harvest should occur at stage R8. The minimum data

set to be collected for biomass and final harvests is given in

Appendix 12. Of course, additional harvests and yield components can

be reported if the cooperator desires.



Aroids (Colocasia esculenta and Xanthosoma)

Unlike cereals and grain legumes, aroids do not have well-defined

growth stages which correlate with changes in partitioning of dry

matter. Therefore, plant development is expressed in terms of the

number of fully-opened leaves which the main stem has produced since

emergence (Appendix 13). The minimum data set requires that growth

stage be determined at the time of each biomass harvest and the final

harvest. Since leaves continually die, it is recommended that the

leaves of five plants per treatment be tagged to keep track of the

total number of leaves produced. In addition, the date when suckers

appear above ground should also be recorded (FORM R).














Biomass harvests should be conducted at approximately 1/4, 1/2,

and 3/4 crop development. Yield components and their codes for both

biomass and final harvests are given in Appendix 14. At final harvest

above-ground biomass can be determined on a subsample of four plants.

For all harvests the total above-ground biomass undriedd) should

include leaf blades and petioles. Dry weights of above-ground biomass

can be determined by subsampling two average-size plants from each

plot, separating them into their components, and slicing into 5 mm

segments before drying.


Cassava

Like aroids, cassava lacks well-defined growth stages which

correlate with changes in dry matter partitioning. However, cassava

branches in response to flowering, and the number of apical meristems

affects both leaf area index and partitioning of dry matter.

Therefore, growth stage will be defined in terms of the number of

apical meristems present on the plant (Appendix 15).

The minimum data set requires only that growth stage (number of

apical meristems) be reported at each harvest (FORM R). Biomass

harvests should occur at approximately 1/3 and 2/3 of the expected

crop cycle. Yield components and their codes for both biomass and

final harvests are given in Appendix 16 and should be reported on

FORM R. Of course, additional harvests and yield components can be

reported.















Potato

The IBSNAT minimum data set for potato is somewhat more complex

than that of other crops. Potato growth stages and their identifying

characteristics as well as codes for describing canopy maturity at the

end of the crop are given in Appendix 17. The minimum data set

requires that the dates of growth stages VE, T1, and T4 be recorded

(FORM R). In addition, a weekly estimate of ground cover should be

reported throughout the crop. For this measurement, quadrats the

width of the row and approximately 0.5 m to 1.0 m long should be held

over the canopy at several points and the percentage of green ground

cover should be estimated visually. Alternatively, line-intercept or

point-intercept methods can be used to estimate the percent land area

covered by green leaves. In addition to weekly estimates of ground

cover, beginning at growth stage T1 + 3 weeks, weekly estimates of

crop maturity should be made (Appendix 17).

Biomass harvests should be made at approximately growth stage T1,

T1 + 3 weeks, and T1 + 6 weeks. For these harvests, at least 8 plants

should be harvested in each plot. The measurements to be made on

these 8 plants and a subsample of two typical plants are summarized in

Appendix 18.

Final harvest consists of at least 40 plants per plot. A

representative tuber sample (4 kg) is used to determine dry matter

percentage of the tubers.









FORM R

GROWTH STAGE AND YIELD COMPONENTS


INSTITUTE 10:


EXPERIMENT 10:


CROP GROWTH


YIELD COMPONENTS


CODE STAGE CODE AMT. CODE AHT. CODE AHT. CODE AMT. CODE AMT.


DD/MM/YY


PLOT(S)


--




~---"c


--~-









FORM S PLANT NUTRIENT CONCENTRATIONS

FORM S is provided to record nutrient concentrations of plant

components. These data are not part of the minimum IBSNAT data set

unless plant nutrition is expected to limit crop growth and yield.

However, in experiments in which soil fertility is a variable or is

expected to be suboptimal, the minimum data set should include at

least the nutrient concentration (N, P, or K depending on the

experiment) of the total above-ground biomass at final harvest. Of

course, nutrient concentrations of other yield components and at

different times can also be reported on FORM S.

The data to be recorded on FORM S include the DATE of harvest,

the PLOT or plots sampled, the CROP CODE (Table 4), the COMPONENT CODE

(from the Appendixes), and the concentration of N, P, K, or other

elements in the sample.

For example, the following represents the N and P concentration

of the total above-ground maize biomass and grain in plot 6.


CROP COMPONENT NUTRIENT CONCENTRATION

OD/MM/YY PLOT(S) CODE CODE N P K Other (specify)



20/07/83 6 MAI 3 1.21 0.14






69


FORM S

PLANT NUTRIENT CONCENTRATIONS


INSTITUTE ID:


EXPERIMENT 10:


CROP COMPONENT

DD/MM/YY PLOT(S) CODE CODE


NUTRIENT CONCENTRATION

N P K Other (specify)

() (%) (M)









CHRONO6RAM OF ACTIVITIES FOR A TYPICAL EXPERIMENT

Collecting the minimum data set in an experiment requires

planning. Several activities, including land preparation, initial

soil sampling, planting, several biomass measurements, phenological

observations, and final soil sampling must be coordinated. Table 6 is

a hypothetical chronogram of activities for a single-factor nitrogen

rate experiment with a 120-day maize cultivar grown under dryland

conditions.

All dates are expressed relative to planting on day 0.









Table 6. Chronogram of activities for a typical experiment. All days are
relative to planting on day 0.


Day


Activity


-180 to -90






-90 to -14


Decide on experimental site, experimental factors, and
experimental design. Calculate size of area needed. Assure
that land, machinery, laboratory, and human resources are
adequate. Assure that the soil characteristics of the plot
are similar to those of available soil pedon
characterization data. If they are not, arrange for IBSNAT
to characterize the soil at the site.

Obtain all necessary inputs and equipment for experiment.
Assure that weather instruments are calibrated.


-14 to 0 Since both N and drought stress are possible limiting
factors in the experiment, take preplant soil samples for
initial soil water, pH, N03, NH4, P, and K. Conduct
final land preparation, preplant fertilizer application,
herbicide application, etc.

0 Plant and apply any other fertilizer, herbicide, and
pesticide treatments.

0 to 120 Apply and record dates and amounts of products used for
weed, insect and disease control (as necessary).

3 to 10 Record date of VE stage (emergence) by plot.

12 to 20 Record date of V6 stage (6 leaves collared) and take first
biomass harvest.


20 to 30

50 to 70

110 to 130


110 to 144


Apply supplemental N fertilizer (if necessary).

Record date of R1 stage and take second biomass harvest.

Record date of R6 stage and take final harvest yield
components.

Take postharvest soil water, pH, NO NH 4 P, and K
samples.









APPENDIX 1

Institute Codes for IBSNAT Experiments1


Code Name

AARD Agency for Research and Development, Jakarta, Indonesia

ACSAD Arab Center for Studies of Arid Zones and Dry Lands, Syria

AVRDC Asian Vegetable Research and Development Center, Taiwan

CATIE Centro Agronomico Tropical de Investigacion y Ensenanza,
Turrialba, Costa Rica

CENIAP Centro Nacional de Investigaciones Agropecuarias, Maracay,
Venezuela

CIAT Centro Internacional de Agricultura Tropical, Call, Columbia

CIP Centro Internacional de la Papa (International Potato Center),
Lima, Peru

CORNEL Cornell Univ., Ithaca, New York, U.S.A.

CSIRO Commonwealth Scientific and Industrial Research Organization,
Brisbane, Australia

CSR Center for Soil Research, Bogor, Indonesia

DSIR Department of Scientific and Industrial Research, Lower Hutt,
New Zealand

EMBRA Empresa Brasileira de Pesquisas Agropecuaria, Brasilia, Brazil

ERS Economic Research Service, Temple, Texas, U.S.A.

FAO Food and Agriculture Organization, United Nations, Rome, Italy

FFTC Food & Fertilizer Technology Center for the Asian & Pacific
Region, Taipei, Taiwan, ROC

FONAIA Fondo Nacional de Investigaciones Agropecuarias, Caracas,
Venezuela

GSWRL Grassland, Soil and Water Research Laboratory, Temple, Texas,
U.S.A.

IBSNAT International Benchmark Sites Network for Agrotechnology
Transfer, Honolulu, Hawaii, U.S.A.

ICAR Indian Council for Agricultural Research, New Delhi, India









APPENDIX 1. Continued.


ICRISA International Crops Research Institute for the Semi-Arid
Tropics, Hyderabad, India

IDIAP Instituto de Investigacion Agropecuaria de Panama, Panama

IFCD International Fertilizer Development Center, Muscle Shoals,
Alabama, U.S.A.

INRA Institut National de la Recherche Agronomique, Paris, France

INTSOY International Soybean Program, Taiwan, ROC

IRA Institut de la Recherche Agronomique, Yaounde, Cameroon

IRRI International Rice Research Institute, Manila, Philippines

LINCOL Lincoln College, Canterbury, New Zealand

LSU Louisiana State University, Baton Rouge, Louisiana, U.S.A.

HARDI Malaysian Agricultural Research & Development Institute, Kuala
Lumpur, Malaysia

MPI Ministry of Primary Industries, Suva, Fiji

HSU Michigan State University, East Lansing, Michigan, U.S.A.

NBSS National Bureau of Soil Survey and Land Use Planning,
Bangalore, India

NifTAL Nitrogen Fixation by Tropical Agricultural Legumes, Honolulu,
Hawaii, U.S.A.

NOAA National Oceanographic and Atmospheric Administration,
Columbia, Missouri, U.S.A.

ORSTOM Office de la Recherche Scientifique et Technique d'Outre-Mer,
Paris, France

PARC Pakistan Agricultural Research Council, Islamabad, Pakistan

PCARRD Philippine Council for Agriculture and Resources Research and
Development, Manila, Philippines

SCEP Soil and Crop Evaluation Project, Suva, Fiji

TAMU Texas A&H University, College Station, Texas, U.S.A.

THALDD Thailand Land Development Department









APPENDIX 1. Continued.


University

University

University

University

University

University

University

Utah State

University


Burundi, Bujumbura, Burundi

Florida, Gainesville, Florida, U.S.A.

Guam, Hangilao, Guam

Guelph, Guelph, Ontario, Canada

Hawaii, Honolulu, Hawaii, U.S.A.

Jordan, Amman, Jordan

Puerto Rico, Mayaguez, Puerto Rico

University, Logan, Utah, U.S.A.

Zambia, Lusaka, Zambia


SIf institute is not specified here, enter 999999 and specify the
institute. IBSHAT personnel will assign an appropriate code.


UBURUN

UFLOR

UGUAM

UGUELP

UHAW

U30R

UPP

UTAHST

UZAM









APPENDIX 2

Fertilizer and Amendment Material Codes


Material name Chemical formula Material
Code


Ammonium nitrate
Ammonium sulfate
Ammonium nitrate-sulfate
Anhydrous ammonia
Urea
Oiammonium phosphate
Monoammonium phosphate
Calcium nitrate
Aqua ammonia
Urea ammonium nitrate solution
Calcium ammonium nitrate solution
Ammonium polyphosphate
Single superphosphate
Triple superphosphate-
Liquid phosphoric acid
Potassium chloride
Potassium nitrate
Potassium sulfate
Calcitic limestone
Dolomitic limestone
Rock phosphate
Green manure
Barnyard manure
Rhizobium
Other


NH4NO3
(NH4)2SO4
NH4NO3 (NH4)2SO4
NH3
CO(NH2)2
(NH4)2HPO4
NH4H2PO4
Ca(N03)2
NH40H
CO(NH2)2+NH4N03
Ca(NO3)2+NH4NO3


CaH4(PO4)2+CaSO4
CaH4(P04)2

H3PO4
KC1
KNO3
K 2SO4
2 K4
*ft**









APPENDIX 3

Fertilizer, Inoculant, and Amendment
Placement and Method Codes



Code


Placement

Broadcast, not incorporated 01

Broadcast, incorporated 02

Banded on surface 03

Banded beneath surface 04

Applied in irrigation water 05

Follar spray 06

Bottom of hole 07

On the seed 08

Other (specify) 99



Method

Hand 01

Machine 02









APPENDIX 4

Biocide Product Codes


Common name Product Code


Herbicides

Alachlor, Methachlor 1001
Propanil 1002
Trifluralin 1003
Dalapon 1004
MCPA 1005
2,4-0 1006
2,4,5-T 1007
Other (specify) 1999

Insecticides

Carbaryl 2001
Malathion, Mercaptothion 2002
Haled 2003
Dimethoate 2004
Fenthion 2005
Diazinon 2006
Ethion, diethion 2007
Oxydemeton-methyl 2008
Azinphos-methyl 2009
Phosphamidon 2010
Mevinphosl 2011
Methyl paranthion, Parathion-methyl 2012
Parathion 2013
DOT 2014
BHC, HCH 2015
Chlordane 2016
Heptachlor 2017
Toxaphene 2018
Aldrin 2019
Oieldrin 2020
Endrin, Mendrin 2021
Other (specify) 2999

Fungicides

Captan 3001
Benomyl 3002
Zineb 3003
Maneb 3004
Mancozeb 3005
Other (specify) 3999









APPENDIX 5

Maize Growth Stage Codes

We suggest that the following codes be used in describing growth
stages (Ritchie and Hanway, 1982).


Growth stage


plants

plants

plants

plants

plants

plants

plants


with

with

with

with

with

with

with


VE

V1

V2

V3

V4

V5

V6

V(N)

VT


some part

collar of

collar of

collar of

collar of

collar of

collar of


visible at soil surface

first leaf visible

second leaf visible

third leaf visible

fourth leaf visible

fifth leaf visible

sixth leaf visible


last branch of tassel visible but silks


R1 50% plants with some silks visible outside husks

R2 50% plants in "blister" stage endosperm is abundant
clear fluid often 10-14 days after R1

R3 50% plants in "milk" stage kernels yellow on outside
and inner fluid milky often 18-22 days after R1

R4 50% plants in "dough" stage endosperm with pasty
consistency often 24-28 days after-silking

RS 50% plants in "dent" stage shelled cob dark red in
color dent beginning to form in top of kernel

R4 50% plants at physiological maturity brown or black
abscission layer visible at base of embryo when kernel
sectional longitudinally husks no longer green often
55-65 days after R1


Code


50%

50%

50%

50%

50%

50%

50%

etc.

50%
not


plants with
yet visible









APPENDIX 6

Haize Harvest Codes


Minimum Data Set

Code Component Units Biomass Final
Harvests Harvests


Plant population of harvest area

Area harvested

Above-ground biomass (dry)

Seed weight undriedd)

Seed weight (dry)

Seed number

Ear number

Leaf blade weight (dry)

Leaf sheath weight (dry)

Stem + tassel weight (dry)

Cob + shuck weight (dry)

Root weight (dry)

Leaf area index

Other (specify)


plants/m2
2
m

g/m2

g/m2
g/M 2

seed/in

ears/m2

g/m2



g/m2


g/m2
g/m2








80



APPENDIX 7


Grain Sorghum, Wheat, and Rice Growth Stage Codes


We suggest that the following codes be used in describing phenological
events (Zadoks et al., 1974).


COOt GROWTH STAGE CO

0 Germination 4
00 Dry seed 40
01 Start of Imbibition 41
02 42
03 mlbibition complete 43
04 44
05 Radicle emerged from seed coat 4S
06 46
07 Coleoptile emerged from seed coat 47
08 48
09 Leaf just at coleoptlle tip 49

1 Seedling growth 5
10 First leaf through coleoptile 50
11 First leaf unfolded 51
12 2 leaves unfolded 52
13 3 leaves unfolded 53
14 4 leaves unfolded 54
15 S leaves unfolded 55
16 6 leaves unfolded 5S
17 7 leaves unfolded 57
18 8 leaves unfolded e5
19 9 or more leaves unfolded 59

2 Tillrina 6
20 Main shoot only 60
21 Main shoot and 1 tiller 61
22 Main shoot and 2 tillers 62
23 Main shoot and 3 tillers 6
24 Main shoot and 4 tillers 64
25 Main shoot and S tillers 65
26 Main shoot and 6 tillers 66
27 Main snoot and 7 tillers 61
28 Main snoot and 8 tillers 68
29 Main shoot and 9 or more tillers 69

3 Stem elongation
30 Pseudo-stem erection (winter cereals
31 1st node detectable only)
32 2nd node detectable
33 3rd node detectable
34 4th node detectable
35 5th node detectable
36 6th node detectable
37 Flag leaf just visible
38 -
39 Flag leaf llgule Just visible


Dl


E GROWTH STAGE


Booting

Flag leaf sheath extending

8oots just visibly swollen

Soots swollen

Flag leaf sheath opening

First awns visible


First spikelet of ear Just visible

1/4 of ear emerged

1/2 of ear emerged

3/4 of oar emerged

Emergence of ear completed

Flowering

Beginning of flowering (not easily
-detectable in barley)

Flowering half-way


Flowering complete


COOt goVTen STAGE

7 Milk dovelooment
10 --
71 Sed coat water ripe
72 -
73 Early milk
74 -
5 Mediam milk ) Increase in solids of
76 ) liquid endosperm
77 Late milk ) notable when crushing
78 ) the seed between
79 ) fingers

8 Dous devlooment
80 -
81 --
82
83 Early dough
84 -
85 Soft dough (Finger-nail impression
86 not held)
87 Hard dough (Finger-nail impression
88 held. head losing
89 chlorophyll)

9 lieninmr
90
91 Seed coat hard (difficult to divide
by thumb-nail)
92 Seed coat hard (can no longer be
dented by thumb-aail)
93 Seed coat loosening In daytime
94 Over-ripe, straw dead and collapsing
95 Seed dorment
96 Viable seed giving 50% germination
97 Seed not dormant
98 Secondary dormancy induced
99 Secondary dormancy lost








APPENDIX 8

Grain Sorghum, Wheat, and Rice Harvest Codes

Minimum Data Set

Code Component Units Biomass Final
Harvests Harvests


Plant population of harvest area

Area harvested

Above-ground biomass (dry)

Seed weight undriedd)

Seed weight (dry)

Seed number

Panicle number

Leaf blade weight (dry)

Leaf sheath weight (dry)

Stem weight (dry)

Panicle rachis weight (dry)

Root weight (dry)

Leaf area index

Other (specify)


plants/m2

m2

g/m2

g/m2
9/M 2

g/m2
2
seed/m2

panicles/m2
2
g/r2

g/m2
2
g/m

g/m2
g/m2









APPENDIX 9

Soybean and Field Bean Growth Stage Codes

We suggest that the following codes be used in describing growth stages (Fehr
et al., 1971).


Code!/ Growth stage


VO 50% plants with some part visible at soil surface

V1 50% plants with completely unrolled leaf at unifoliate node

V2 50% plants with completely unrolled leaf at first node above the
unifoliate node

V3 50% plants with 3 nodes on main stem beginning with the unifoliate
node

V4 50% plants with 4 nodes on main stem beginning with unifoliate node

V(N) etc.

R1 50% plants with one flower at any node

R2 50% plants with flower at node immediately below the uppermost node
with a completely unrolled leaf

R3 50% plants with a pod 0.5 cm long at one of the four uppermost
nodes with a completely unrolled leaf

R4 50% plants with a pod 2.0 cm long at one of the four uppermost
nodes with a completely unrolled leaf

R5 50% plants with beans beginning to develop (can be felt when pod is
squeezed) at one of the four uppermost nodes with a completely
unrolled leaf

R61/ 50% plants with a pod containing full size green beans at one of
the four uppermost nodes with a completely unrolled leaf

R7 50% plants with pods yellowing; 50% of leaves
yellow...Physiological maturity

R8 50% plants with 95% of pods brown...Harvest maturity

/The stage descriptions apply to populations. By eliminating "50% plants"
they apply to individual plants. Only development of the main stem is consi-
dered by this system; branches are ignored. A leaf is considered completely
unrolled when the leaf at the node immediately above it has unrolled suffi-
ciently so the two edges of each leaflet are no longer touching. At the
terminal node on the main stem, the leaf is considered completely unrolled
when the leaflets are flat and similar in appearance to older leaves on the
plant.









APPENDIX 10

Soybean and Field Harvest Codes


Minimum Data Set

Code Component Units Biomass Final
Harvests Harvests


Plant population of harvest area

Area harvested

Above-ground biomass (dry)

Seed weight undriedd)

Seed weight (dry)

Seed number

Pod number

Leaf blade weight (dry)

Petiole weight (dry)

Stem weight (dry)

Empty hull weight (dry)

Root weight (dry)

Leaf area index

Nodule weight (dry)

Other (specify)


plants/m2
2

g/m2
g/m2


g/m2

seed/m2

pods/m2

g/m2

g/m2

g/m2

g/m2

g/m2


g/m2









APPENDIX 11

Peanut Growth Stage Codes

We suggest that the following codes be used in describing growth stage
(Boote, 1982).

Code Growth stage


VE 50% plants with some part visible at soil surface

V1 50% plants with 1 developed node on the main axis (its
tetrafoliate unfolded and its leaflets flat)

V2 50% plants with 2 developed nodes on the main axis

V3 50% plants with 3 developed nodes on the main axis

V4 50% plants with 4 developed nodes on the main axis

V(N) etc.

R1 50% beginning bloom. 50% plants with one open flower at any
node

R2 50% beginning peg. 50% plants with one elongated peg
(gynophore)

R3 50% beginning pod. 50% plants with one peg in soil with
turned swollen ovary at least twice the width of the peg

R4 Full pod. 50% plants with one fully expanded pod, to
dimensions characteristic of the cultivar

R5 Beginning seed. 50% plants with one fully-expanded pod with
cotyledon growth visible when pod cut in cross section with
razor blade (past liquid endosperm phase)

R6 Full seed. 50% plants with one pod with seeds filling cavity
of pod when fresh

R7 Beginning maturity. 50% plants with one pod showing visible
natural coloration or blotching of inner pericarp or testa

R8 Harvest maturity. 50% plants with 2/3 to 3/4 of all
developed pods have test or pericarp coloration

R9 Over-mature pod. 50% plants with one undamaged pod showing
orange-tan coloration of the testa and/or natural peg
deterioration









APPENDIX 12

Peanut Harvest Codes


Minimum Data Set
Code Component Units Biomass Final
Harvests Harvests


Plant population of harvest area

Area harvested

Above-ground biomass (dry)

Seed weight undriedd)

Seed weight (dry)

Seed number

Pod number

Leaf blade weight (dry)

Petiole weight (dry)

Stem weight (dry)

Hull weight (dry)

Root weight (dry)

Leaf area index

Nodule weight (dry)

Other (specify)


plants/m2

2
m

g/m2
g/m2
g/rn2

seed/m2

pods/m2

g/m2

g/m2

g/m2

g/m2
g/m2


g/m






86


APPENDIX 13

Aroid (Colocasia esculenta and Xanthosoma) Growth Stage Codes



Code Growth stage


V1 50% of plants having produced 1 fully opened leaf

V2 50% of plants having produced 2 fully opened leaves
since emergence

V3 50% of plants having produced 3 fully opened leaves
since emergence

V(N) etc.

S 50% of plants having suckers above ground









APPENDIX 14

Aroid Harvest Codes


Minimum Data Set

Code Component Units Biomass Final
Harvests Harvests

2
1 Plant population of harvest area plants/m X X
2 Area harvested m X X
3 Above-ground biomass (dry) g/m2 X X
4 Corm weight undriedd) g/2
5 Corm weight (dry) g/m2 X X
6 Corm number corms/m2 X X
7 Cormel weight undriedd) g/m2
8 Cormel weight (dry) g/m2 X X
9 Cormel number cormels/m X X
10 Leaf blade weight (dry) g/m2
11 Petiole weight (dry) g/m2
12 Root weight (dry) g/m2
13 Leaf area index
99 Other (specify)









APPENDIX 15

Cassava Phenology Codes

We'suggest that the following growth stages be used in describing
phenological events. Biomass harvests should be conducted at
approximately 1/3 and 2/3 of the normal period of development as well as
at harvest maturity. Phenological stages should be noted at that time.


Code Growth stage


E 50% of plants with at least 1 shoot on the planting
stick more than 1 cm in length or when some part visible
at the soil surface

M1 50% of plants with at least 1 apical meristem

M2 50% of plants with at least 2 apical meristems

M3 50% of plants with at least 3 apical meristems

M(N) etc.








APPENDIX 16

Cassava Harvest Codes


Minimum Data Set
Code Component Units Biomass Final
Harvests Harvests


Plant population of harvest area

Area harvested

Above-ground biomass (dry)

Total tuber weight (undried)1/

Total tuber weight (dry)

Total tuber number

Useable tuber weight undriedd)/

Useable tuber weight (dried)

Useable tuber number

Leaf blade weight (dry)

Petiole weight (dry)

Stem weight (dry)

Feeder root weight (dry)

Leaf area index

Other (specify)


plants/m2

m2

g/rm2

g/m2

g/m2

tubers/m2

g/m2

g/m2

tubers/m2

g/m2

g/m2

g/m2

g/m2


- Useable tubers are defined as tubers over 200 g undriedd).









APPENDIX 17

Potato Growth Stage and Maturity Rating Codes

We suggest that the following codes be used in describing growth stages.


Code Growth stage


VE 50% plants with some past visible at soil surface

VI 50% plants with 1 developed node on the main axis

V2 50% plants with 2 developed nodes on the main axis

V(N) etc.

T1 Tuber Initiation. 50% plants have at least one tuber
> 1 cm in diameter

T4 Date when green canopy cover reaches 20% of the maximum
achieved (harvest maturity)









We suggest that the following codes be used in describing crop maturity
(Regel and Sands, 1983).


Maturity Name and Code Leaf and stalk condition
rating


0 Tops dead, TD Plant tops are dead, stalks are dry
1 Stalks are slightly sappy
2 Sappy stalks, with a few yellow leaves

3 Golden leaf, GL Leaves are golden yellow
4 Plants are yellow with tinge of green
5 Plants are yellow with obvious green visible
6 Plants are 50% green and yellow

7 Yellow-green, YG Plants are green with obvious yellow visible
8 Plants are green with tinge of yellow

9 Dark green leaf, 06 Plants are green with first evidence of
yellow appearing
10 Absolutely no evidence of yellowing, leaves
are green, growth is lush










APPENDIX 18

Potato Harvest Codesl/


Minimum Data Set

Code Component Units Biomass Final
Harvests Harvests

Large Biomass Sample (8 plants) or Final Harvest (40 plants)


1 Plant population of harvest area
2 Area harvested
3 Number of main stems
4 Above-ground biomass + tubers
5 Tuber number (5-30 mm, undried)
6 Tuber weight (5-30 mm, undried)
7 Tuber number (>30 mm, undried)
8 Tuber weight (>30 mn, undried)

Small Biomass Sample (2 plants)

9 Node number
10 Main stem length
11 Number of axillary branches (20 cm
12 Leaf weight undriedd)
13 Leaf weight (dry
14 Stem weight undriedd)
15 Stem weight (dry)
16 Tuber weight (5-30 mm, undried)
17 Tuber weight (5-30 mm, dry)
18 Tuber number (5-30 mm)
19 Tuber weight (>30 mm, undried)
20 Tuber weight (>30 mm, dried)
21 Tuber number (>30 mm)

Representative Tuber Sample (4 kg)

22 Tuber dry matter percentage

Canopy Measurements (weekly)


plants/m2
m2
stems/m2
g/m2
g/m2
g/m2
g/m2
g/m2


nodes
cm
branches/m2
g/m2
g/m2
g/m2
g/m2
g/m2
g/m2
tubers/m2
g/m2
g/m2
tubers/m2


23 Leaf area index
24 Ground cover % X
25 Plant maturity rating X
99 Other (specify)

/A leaf refers to the entire compound leaf, including petiole, rachis,
and leaflets. To be included, at least half the leaf should be green.
The stem includes the main stems plus auxiliary branches, down to but
not including the mother tuber, stolons, or roots. Main stems originate
at the mother tuber. Auxiliary branches, whether arising above or below
the soil surface, are not counted as main stems.











LITERATURE CITED

Boote, K. 3. 1982. Growth stages of peanut (Arachis hypoqaea L.).
Peanut Sci. 9:35-40.

Cochran, W. 6. and G. M. Cox. 1957. Experimental Designs, 2nd ed.
John Wiley & Sons, Inc., New York, London, Sidney.

Doorenbos, 3. and W. D. Pruitt. 1977. Crop Water Requirements. FAO
Irrigation and Drainage Paper 24. FAO, Rome.

Doorenbos, 3. and A. H. Kassam. 1979. Yield Response to Water. FAO
Irrigation and Drainage Paper 33. FAO, Rome.

Fehr, W. R. and C. E. Caviness. 1980. Stages of soybean develop-
ment. Special Report 80. Coop. Ext. Serv., Iowa State Univ.,
Logan, Utah, U.S.A.

Fehr, W. R., C. E. Caviness, D. T. Burmood, and 3. S. Pennington.
1971. Stage of development descriptions for soybeans, Glycine
max (L.) Merrill. Crop Sci. 11:929-931.

Hanks, R. 3., D. V. Sisson, R. L. Hurst, and K. 6. Hubbard. 1980.
Statistical analysis of results from irrigation experiments using
the line-source sprinkler system. Soil Sci. Soc. Am. 3.
44:886-888.

Hargreaves, G. H. 1975. Water Requirements Manual for Irrigated
Crops and Rainfed Agriculture. Utah State Univ., Logan, Utah,
U.S.A.

Hargreaves, 6. H. 1977. World Water for Agriculture. Utah State
Univ., Logan, Utah, U.S.A.

3ansen, M. E. (ed.). 1973. Comsumptive Use of Water and Irrigation
Water Requirements. Am. Soc. Civil Eng., New York.

Johnson, D. E., U. N. Chandhuri, and E. T. Kanemasu. 1983.
Statistical analysis of line-source sprinkler experiments and
other nonrandomized experiments using multivariate methods. Soil
Sci. Soc. Am. 3. 47:309-312.

Page, A. L., R. H. Miller, and D. R. Keeney (eds.). 1982. Methods of
Soil Analysis. Part 2 Chemical and Microbial Properties. 2nd
Ed. Soil Sci. Soc. Am., Madison, Wisconsin, U.S.A.

Regel, P. A. and P. 3. Sands. 1983. A model of the development and
bulking of potatoes (Solanum tuberosum L.). IV. Daylength,
plant density and cultivar effects. Field Crops Res. 6:1-23.

Ritchie, S. W. and 3. 3. Hanway. 1982. How a corn plant develops.
Special Report No. 48, Revised February 1982. Iowa State Univ.
of Science and Technology, Coop. Ext. Serv., Ames, Iowa, U.S.A.






94


Vanderlip, R. L. 1972. How a sorghum plant develops. C-447. Coop.
Ext. Serv., Kansas State Univ. May 1972. 19 pp.

Vanderlip, R. L. and H. E. Reeves. 1972. Growth stages of sorghum
(Sorghum bicolor (L.) Moench). Agron. 3. 64:13-16.

World Meteorological Organization. 1981. Guide to Agricultural
Meteorological Practices. 2nd Ed., W.M.O., Geneva.

Zadoks, J. C., T. T. Chang, and C. F. Konzak. 1974. A decimal code
for the growth stages of cereals. Eucarpia Bull. 7.