GGE biplot for studying paste property of chinese spring wheat
Yong Zhang
GGE biplot for studying paste property of chinese spring wheat - Beijing (China) : Science Press, 2003. - Printed
Abstract in Chinese and Enlgish. Peer-review: No - Open Access: Yes|http://211.155.251.148:8080/zwxb/EN/column/column81.shtml Peer review Open Access
This paper introduced a GGE biplot as a graphic method for analyzing wheat peak viscosity based on data from regional trials. The average performance at each environment was subtracted from the original pasting properties data first so that the derived data contains only genotype main effect G and genotype by environment interaction GE, which were collectively named GGE. The GGE data was then subjected to singular value decomposition and was approximated by the first two principal components. Plotting the first principal component against the second for all genotypes and environments resulted in a GGE bip lot. In light of the biplot, peak viscosity of starch pasting characteristics for twenty cultivars from ten locations in Chinese spring sown spring wheat regions was analyzed. The results indicated that Tiechunl performed both high and stable for peak viscosity, followed by Jinchun9, while N ingzuo17 performed the poorest. Harbin was the best environment facilitating identification of peak viscosity.
Text in Chinese
0496-3490
Triticum aestivum
Genotypes
Genotype environment interaction
Statistical methods
GGE biplot for studying paste property of chinese spring wheat - Beijing (China) : Science Press, 2003. - Printed
Abstract in Chinese and Enlgish. Peer-review: No - Open Access: Yes|http://211.155.251.148:8080/zwxb/EN/column/column81.shtml Peer review Open Access
This paper introduced a GGE biplot as a graphic method for analyzing wheat peak viscosity based on data from regional trials. The average performance at each environment was subtracted from the original pasting properties data first so that the derived data contains only genotype main effect G and genotype by environment interaction GE, which were collectively named GGE. The GGE data was then subjected to singular value decomposition and was approximated by the first two principal components. Plotting the first principal component against the second for all genotypes and environments resulted in a GGE bip lot. In light of the biplot, peak viscosity of starch pasting characteristics for twenty cultivars from ten locations in Chinese spring sown spring wheat regions was analyzed. The results indicated that Tiechunl performed both high and stable for peak viscosity, followed by Jinchun9, while N ingzuo17 performed the poorest. Harbin was the best environment facilitating identification of peak viscosity.
Text in Chinese
0496-3490
Triticum aestivum
Genotypes
Genotype environment interaction
Statistical methods