Development of a Yield Projection
Technique for Arizona Cotton
E.R. Norton, Plant Sciences Department
J.C. Silvertooth, Plant Sciences Department
A series of boll measurements were taken at numerous locations across the state in 1997 in an
attempt to continue to develop a yield prediction model that began in 1993.
Results from 1995 showed the strongest relationship between final open boll counts and yield.
Based on these results, data was collected in 1997 from several locations around the state.
Boll counts were made just prior to harvest and then correlated to yield. Results showed that a
good estimate for lint yield could be obtained using the factor of approximately 13 bolls/row-ft./bale
of lint for Upland cotton on 38 to 40 inch row spacings.
Cotton grown in the desert southwest has the advantage of a longer growing season allowing
producers at lower elevations the option of carrying the crop through a second fruiting cycle, and
attempting to produce a "top-crop" to increase yield. Additional inputs are required to support a
second fruiting cycle. If a producer were able to obtain a reasonable estimate of crop yield potential
at the time when the decision for crop termination is to be made, it would help in deciding whether to
terminate the crop or carry it through a second fruiting cycle. A reliable yield estimation technique
could serve a number of useful purposes in managing cotton fields for optimum yields, efficiencies, and
profits. The objective of this study was to develop a model for predicting yield as a function of
easily measured plant parameters.
Materials and Methods
In an effort to continue to build upon previous boll sampling work, boll counts were taken from
several experiments conducted around the state of Arizona in 1997. Data was collected either on the
date of harvest or as close to that date as was reasonably possible (all within 4-5 days). Data
collected included; number of open bolls per meter and number of green bolls per meter.
Yield estimates were made by mechanically picking the plots from which the boll counts were taken.
Percent turnout for each plot was obtained from small sub-samples that were individually ginned.
Data from 1996 was combined with the data from 1997. Linear regression analysis was performed
according to procedures outlined by the SAS institute (1994), on the data to determine if a linear
relationship existed in the data set between open bolls per meter and final lint yield. A mean and
standard deviation was calculated for the number of open bolls per meter needed to produce one bale of
Results and Discussion
The original idea of developing a model that would assist in predicting final lint yield was based
upon easily obtained boll measurements such as boll weight, boll diameter, and bolls/meter
(Norton et al., 1995 and 1996). These results revealed a high degree of variability among these
parameters that reduced the predictive capability of the model to a point where the model was not useful.
However, data collected in 1995 showed promising results with respect to a correlation between final
open boll counts (within one week of harvest) and final lint yield (Norton et al., 1996 and Norton et
al., 1997). Data collected in 1996 resulted in estimates of number of bolls needed to produce a bale of
lint yield of 13 per foot and 43 per meter. Associated with these means were large standard deviations.
Data collected in 1997 went to further improve that estimate by lowering the coefficient of variation of
the model from 29% to 19% which is due to a much lower standard deviation associated with the mean.
Results of the data analyses in Table 1 show that a count
of approximately 11 harvestable (open) bolls/foot or 36 harvestable (open) bolls/meter will result in
approximately one bale of lint yield. A high degree of variability exists among varieties, plants,
and within individual plants with respect to parameters such as boll size, number of locks/boll,
and percent turnout. For this reason, the mean has a relatively large standard deviation associated
with it. The estimate of bolls needed to produce one bale of lint may need to be adjusted,
particularly in the case of varieties that tend to have small bolls (i.e. DPL 5415 and DPL 5409).
Regression analysis performed on the data revealed a linear relationship between lint yield and
open boll count on a meter basis (Figure 1). It is important to note
that the regression equation obtained from this analysis should not be used to estimate yield. As an
example; if you estimate the number of bolls per meter needed to produce one bale (480 lbs.) of lint
with this equation you will obtain 14.1 bolls per meter. This underestimates the actual mean
obtained (Table 1) by approximately 40%. It is suggested that
yield approximations be made using the mean obtained in Table 1.
Data collection will continue for the 1998 growing season to expand that database and to
improve accuracy and precision of lint yield estimations.
This project was funded in part by the Arizona Cotton Growers Association and Cotton Inc..
- SAS Institute. 1994. The SAS system for Windows. Release 6.10. SAS Inst., Cary, NC.
- Norton, E.R.. and J.C. Silvertooth. 1995. Development of a yield projection technique for Upland and Pima cotton. Cotton. A College of Agriculture Report. Series P-99 p.29-33.
- Norton, E.R.. and J.C. Silvertooth. 1996. Development of a yield projection technique for Upland and Pima cotton. Cotton. A College of Agriculture Report. Series P-103 p.69-71.
- Norton, E.R.. and J.C. Silvertooth. 1997. Development of a yield projection technique for Upland and Pima cotton. Cotton. A College of Agriculture Report. Series P-108 p.105-106.
This is a part of publication AZ1006:
"Cotton: A College of Agriculture Report," 1998, College of Agriculture,
The University of Arizona, Tucson, Arizona,
85721. Any products, services, or organizations that are mentioned, shown, or indirectly
implied in this publication do not imply endorsement by The University of Arizona.
The University is an Equal Opportunity/Affirmative Action Employer.
This document located at http://ag.arizona.edu/pubs/crops/az1006/az10062c.html
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