Abstract
The purpose of this paper is to demonstrate the advantage of using weather elements as covariates in studying yield differentials between varieties of wheat over different climatological regions. Using regression methods, the dependence of varietal yield differences on weather elements was demonstrated with a relatively small sample consisting of yield and weather data over a 3-year period from nine locations in Kansas. For each location, the sample-derived regression equation was used to calculate predicted yield differentials and 95% confidence intervals for the mean (CLM) for each year from 1950 through 1989. The proportion of CLMs that covered positive (or negative) values only was considered an important statistic. For each location, it estimated the proportion of years when the average yield of one variety was quite certain to exceed that of another .
The procedure was applied to the problem of choosing new varieties for release to wheat growers. Results showed that a new variety, Karl, could be expected to outyield a popular variety, Newton, in more than 50% of the years in climates with mean annual precipitation exceeding 28 inches. Further, the mean yield of Karl could be expected to exceed that of another popular variety, Arkan, in over 50% of the years at almost all locations across the state .
Keywords
wheat varieties, weather, interactions
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Feyerherm, Arlin M.; Sears, Rollin G.; and Paulsen, Gary M.
(1990).
"GENOTYPE X WEATHER INTERACTIONS IN GRAIN YIELDS OF WHEAT,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1433
GENOTYPE X WEATHER INTERACTIONS IN GRAIN YIELDS OF WHEAT
The purpose of this paper is to demonstrate the advantage of using weather elements as covariates in studying yield differentials between varieties of wheat over different climatological regions. Using regression methods, the dependence of varietal yield differences on weather elements was demonstrated with a relatively small sample consisting of yield and weather data over a 3-year period from nine locations in Kansas. For each location, the sample-derived regression equation was used to calculate predicted yield differentials and 95% confidence intervals for the mean (CLM) for each year from 1950 through 1989. The proportion of CLMs that covered positive (or negative) values only was considered an important statistic. For each location, it estimated the proportion of years when the average yield of one variety was quite certain to exceed that of another .
The procedure was applied to the problem of choosing new varieties for release to wheat growers. Results showed that a new variety, Karl, could be expected to outyield a popular variety, Newton, in more than 50% of the years in climates with mean annual precipitation exceeding 28 inches. Further, the mean yield of Karl could be expected to exceed that of another popular variety, Arkan, in over 50% of the years at almost all locations across the state .
