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Optimal numbers of environments to assess slopes of joint regression for grain yield,grain protein yield and grain protein concentration under nitrogen constraint in winter wheat |
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| Authors: | Bing Song Zheng Jacques Le Gouis Dorvillez Daniel Maryse Brancourt-Hulmel |
| Affiliation: | 1. INRA/USTL UMR SADV 1281, Estrées-Mons BP 50136, 80203 Péronne cedex, France;2. School of Forestry & Biotechnology, Zhejiang Forestry University, 311300, Lin An, China;3. INRA/UBP UMR 1095 GDEC 1095, Site de Crouël, 234 avenue du Brézet, 63100 Clermont-Ferrand, France |
| Abstract: | Plant breeders are interested in rationally reducing the number of testing environments for breeding new genotypes adapted to diverse conditions. One way to characterize the adaptation of a genotype is to use the joint regression model. Our objectives were to estimate the stability for grain yield (GY), grain protein yield (GPY) and grain protein content (GPC) of a set of wheat genotypes grown under varying nitrogen conditions and then to determine optimal numbers of environments for assessing the slopes of joint regression. |
| Keywords: | Bootstrap method Genotype × environment interaction Joint regression Stability statistics Winter wheat |
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