Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be c...Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be constructed by the mixed linear model approaches for experimental data with sampling errors within populations or with some missing values.Unweighted pair-group method ( UPGM ) is suggested as fusion method. Sampling variances of estimated dissimilarity coefficient can be obtained by the jackknife procedure.A one-tail t-test is applicable for detecting significance of dissimilarity of populaions within specific group.Unbiasedness and efficiency for estimation of dissimilarity coefficients are proved by Monte Carolo simulations.Worked example from cotton yield data is given for demonstration of the use of these cluster methods.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
文摘Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be constructed by the mixed linear model approaches for experimental data with sampling errors within populations or with some missing values.Unweighted pair-group method ( UPGM ) is suggested as fusion method. Sampling variances of estimated dissimilarity coefficient can be obtained by the jackknife procedure.A one-tail t-test is applicable for detecting significance of dissimilarity of populaions within specific group.Unbiasedness and efficiency for estimation of dissimilarity coefficients are proved by Monte Carolo simulations.Worked example from cotton yield data is given for demonstration of the use of these cluster methods.
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.
