Analysis of multi-environment trials （METs） of crops for the evaluation and recommendation of varieties is an important issue in plant breeding research. Evaluating on the both stability of performance and high yiel...Analysis of multi-environment trials （METs） of crops for the evaluation and recommendation of varieties is an important issue in plant breeding research. Evaluating on the both stability of performance and high yield is essential in MET analyses. The objective of the present investigation was to compare 11 nonparametric stability statistics and apply nonparametric tests for genotype-by-environment interaction （GEI） to 14 maize （Zea mays L.） genotypes grown at 25 locations in southwestern China during 2005. Results of nonparametric tests of GEl and a combined ANOVA across locations showed that both crossover and noncrossover GEI, and genotypes varied highly significantly for yield. The results of principal component analysis, correlation analysis of nonparametric statistics, and yield indicated the nonparametric statistics grouped as four distinct classes that corresponded to different agronomic and biological concepts of stability. Furthermore, high values of TOP and low values of rank-sum were associated with high mean yield, but the other nonparametric statistics were not positively correlated with mean yield. Therefore, only rank-sum and TOP methods would be useful for simultaneously selection for high yield and stability. These two statistics recommended JY686 and HX168 as desirable and ND108, CM12, CN36, and NK6661 as undesirable genotypes.展开更多
Assessment of yield stability is an important issue for maize （Zea mays L.） cultivar evaluation and recommendation. Many parametric procedures are available for stability analysis, each of them allowing for differen...Assessment of yield stability is an important issue for maize （Zea mays L.） cultivar evaluation and recommendation. Many parametric procedures are available for stability analysis, each of them allowing for different interpretations. The objective of the present study was to assess yield stability of maize hybrids evaluated in the National Maize Cultivar Regional Trials in southwestern China using 20 parametric stability statistics proposed by various authors at different times, and to investigate their interrelationships. Two yield datasets were obtained from the 2003 and 2004 national maize cultivar regional trials in southwestern China. A combined analysis of variance, stability statistics, and rank correlations among these stability statistics were determined. Effects of location, cultivar, and cultivar by location interaction were highly significant （P〈0.01）. Different stability statistics were used to determine the stability of the studied cultivars. Cultivar mean yield （Y） was significantly correlated to the Lin and Binns stability statistic （LP, r=0.98^＊＊ and 0.97^＊＊ for 2003 and 2004 trials, respectively） and desirability index （HD, r=0.38 and 0.84^＊＊ for the 2003 and 2004 trials, respectively）. The statistics LP and HD would be useful for simultaneously selecting for high yield and stability. Based on a principal component analysis, the parametric stability statistics grouped as four distinct classes that corresponded to different agronomic and biological concepts of stability.展开更多
Identification of high-yielding stable promising rice lines and determination of suitable areas for rice lines would be done by additive main effects and multiplicative interaction(AMMI) model. Seven promising rice ge...Identification of high-yielding stable promising rice lines and determination of suitable areas for rice lines would be done by additive main effects and multiplicative interaction(AMMI) model. Seven promising rice genotypes plus two check varieties Shiroudi and 843 were analyzed using a randomized complete block design with three replications in three consecutive years(2012, 2013 and 2014). Homogenous error variance was indicated in the nine environments for grain yield. The combined analysis of variance indicated significant effects of environment, genotype and genotype × environment(GE) interactions on grain yield. The significant effect of GE interaction reflected on the differential response of genotypes in various environments and demonstrated that GE interaction had remarkable effect on genotypic performance in different environments. The application of AMMI model for partitioning the GE interaction effects showed that only the first two terms of AMMI were significant based on Gollob's Ftest. The lowest AMMI-1 was observed for G7, G2 and G6. G7 and G6 had higher grain yield. According to the first eigenvalue, which benefits only the first interaction principal component scores, G1, G6, G2 and G9 were the most stable genotypes. The values of the sum of first two interaction principal component scores could be useful in identifying genotype stability, and G6, G5 and G2 were the most dynamic stable genotypes. AMMI stability value introduced G6 as the most stable one. According to AMMI biplot view, G6 was high yielding and highly stable genotype. In conclusion, this study revealed that GE interactions were an important source of rice yield variation, and its AMMI biplots were forceful for visualizing the response of genotypes to environments.展开更多
基金supported by the Program for Changjiang Scholars and Innovative Research Team in University(No.ITR0453)the Youth Foundation of Sichan Province Office of Education(No.2006B005)
基金the Program for Changjiang Scholars and Innovative Research Team in University,China(IRT0453)the Youth Foundation of Sichuan Province Office of Education(2006B005) of China,for supporting this research
文摘Analysis of multi-environment trials （METs） of crops for the evaluation and recommendation of varieties is an important issue in plant breeding research. Evaluating on the both stability of performance and high yield is essential in MET analyses. The objective of the present investigation was to compare 11 nonparametric stability statistics and apply nonparametric tests for genotype-by-environment interaction （GEI） to 14 maize （Zea mays L.） genotypes grown at 25 locations in southwestern China during 2005. Results of nonparametric tests of GEl and a combined ANOVA across locations showed that both crossover and noncrossover GEI, and genotypes varied highly significantly for yield. The results of principal component analysis, correlation analysis of nonparametric statistics, and yield indicated the nonparametric statistics grouped as four distinct classes that corresponded to different agronomic and biological concepts of stability. Furthermore, high values of TOP and low values of rank-sum were associated with high mean yield, but the other nonparametric statistics were not positively correlated with mean yield. Therefore, only rank-sum and TOP methods would be useful for simultaneously selection for high yield and stability. These two statistics recommended JY686 and HX168 as desirable and ND108, CM12, CN36, and NK6661 as undesirable genotypes.
基金the Program for the Changjiang Scholars and Innovative Research Team in University, China (IRT0453)the Youth Fund of Sichuan Provincial Department of Education (2006B005)
文摘Assessment of yield stability is an important issue for maize （Zea mays L.） cultivar evaluation and recommendation. Many parametric procedures are available for stability analysis, each of them allowing for different interpretations. The objective of the present study was to assess yield stability of maize hybrids evaluated in the National Maize Cultivar Regional Trials in southwestern China using 20 parametric stability statistics proposed by various authors at different times, and to investigate their interrelationships. Two yield datasets were obtained from the 2003 and 2004 national maize cultivar regional trials in southwestern China. A combined analysis of variance, stability statistics, and rank correlations among these stability statistics were determined. Effects of location, cultivar, and cultivar by location interaction were highly significant （P〈0.01）. Different stability statistics were used to determine the stability of the studied cultivars. Cultivar mean yield （Y） was significantly correlated to the Lin and Binns stability statistic （LP, r=0.98^＊＊ and 0.97^＊＊ for 2003 and 2004 trials, respectively） and desirability index （HD, r=0.38 and 0.84^＊＊ for the 2003 and 2004 trials, respectively）. The statistics LP and HD would be useful for simultaneously selecting for high yield and stability. Based on a principal component analysis, the parametric stability statistics grouped as four distinct classes that corresponded to different agronomic and biological concepts of stability.
文摘Identification of high-yielding stable promising rice lines and determination of suitable areas for rice lines would be done by additive main effects and multiplicative interaction(AMMI) model. Seven promising rice genotypes plus two check varieties Shiroudi and 843 were analyzed using a randomized complete block design with three replications in three consecutive years(2012, 2013 and 2014). Homogenous error variance was indicated in the nine environments for grain yield. The combined analysis of variance indicated significant effects of environment, genotype and genotype × environment(GE) interactions on grain yield. The significant effect of GE interaction reflected on the differential response of genotypes in various environments and demonstrated that GE interaction had remarkable effect on genotypic performance in different environments. The application of AMMI model for partitioning the GE interaction effects showed that only the first two terms of AMMI were significant based on Gollob's Ftest. The lowest AMMI-1 was observed for G7, G2 and G6. G7 and G6 had higher grain yield. According to the first eigenvalue, which benefits only the first interaction principal component scores, G1, G6, G2 and G9 were the most stable genotypes. The values of the sum of first two interaction principal component scores could be useful in identifying genotype stability, and G6, G5 and G2 were the most dynamic stable genotypes. AMMI stability value introduced G6 as the most stable one. According to AMMI biplot view, G6 was high yielding and highly stable genotype. In conclusion, this study revealed that GE interactions were an important source of rice yield variation, and its AMMI biplots were forceful for visualizing the response of genotypes to environments.
