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Prediction of Cultivar Performance Based on Single‐ versus Multiple‐Year Tests in Soybean
Author(s) -
Yan Weikai,
Rajcan Istvan
Publication year - 2003
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2003.5490
Subject(s) - cultivar , best linear unbiased prediction , biology , selection (genetic algorithm) , statistic , crop , predictive power , statistics , generalized linear mixed model , genotype , microbiology and biotechnology , agronomy , mathematics , computer science , machine learning , philosophy , biochemistry , epistemology , gene
Because of the omnipresent genotype × year or genotype × location × year interactions in crop performance trials, it is commonly believed that multiple‐year data should be used in selecting cultivars for the next year. An implicated but rarely tested hypothesis is that multiple‐year data are more predictive than single‐year data of cultivar performance in the next year. Yield data of the 1991 to 2000 Ontario Soybean Variety Trials in the 2800 Crop Heat Unit (CHU) area were used to study the power of single‐year, multiple‐location trials in predicting cultivar performances in the following year, and to see if data from multiple‐year trials are more predictive. Mixed models were used to estimate best linear unbiased predictions (BLUP) of tested genotypes on the basis of single‐ or multiple‐year trials, and the t ‐statistic of BLUP (tBLUP) was used as a measure of cultivar performance. Results indicated that a single‐year, multiple‐location trial had sufficient power for identifying genotypes that would perform well or poorly in the next year. Two to four years' data gave only slightly better predictions of next‐year performances than single‐year data but allowed more genotypes to be evaluated conclusively. The tBLUP of genotype effects based on 2 yr of multiple‐location trials should be used as a basis for soybean cultivar selection and recommendation in the 2800 CHU area of Ontario.