Rapeseed variety needs to be tested by regional trial in multiple sites for many years before being applied in market in China.Performants of rapeseed were affected by the interaction of sites and varieties.Evaluation...Rapeseed variety needs to be tested by regional trial in multiple sites for many years before being applied in market in China.Performants of rapeseed were affected by the interaction of sites and varieties.Evaluation of regional trials is very important for guiding rapeseed breeding.GGE(genotype main effects and genotypeenvironment interaction)biplot was used to evaluate yield,stability,adaptability,representativeness and discrimination of national winter rapeseed trials in the upper reaches of Yangtze River in 2017-2018.Results showed that the main effects of genotype(G),environment(E)and genotypeenvironment interaction(GE)were significant(P<0.01)for yield.Among them,E accounted for 46.95%total variation on average,G and GE accounted for 19.34%and 33.71%respectively.Eight varieties were found with high-yield,excellent stability and adaptability,including‘Yiyou 29’,‘Xiwang 920’,‘Liyouza 108’,‘Nanyou 546’,‘Dadi 195’,‘Jiayou 1’,‘Huayouza 28’and‘Yuhua 2’.Test sites included Nanchong,Mianyang,Wanzhou,Shuangliu and Chengdu in Sichuan Province and Zunyi together with Guiyang in Guizhou Province were selected for their excellent representativeness and discrimination.These results would provide theoretical basis for rapeseed breeding.展开更多
Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predi...Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.展开更多
According to the basic concepts of precision and the principles of analysis of variance (ANOVA), precision types for experiments and variety comparison in regional crop trials (RCT) were studied and developed; expecte...According to the basic concepts of precision and the principles of analysis of variance (ANOVA), precision types for experiments and variety comparison in regional crop trials (RCT) were studied and developed; expected variety comparison precision (EVCP) and realized variety comparison precision (RVCP) and the corresponding statistical indexes of them were proposed. It was explained that experimental precision (EP) and variety comparison precision (VCP) are two kinds of precision of RCT; EP includes error precision and variety mean precision, which can be measured respectively by the coefficient of variation of single observation's error (CVe) and the coefficient of variation of variety mean's error (CVy); VCP includes EVCP and RVCP, which can be measured respectively by the detectable least relative difference (DLRD) and the relative least significant distance (RLSD); EP is an important factor of VCP but not identical to it; RVCP is the realization of EVCP. Besides error, experimental design and GE interaction and ANOVA model affect VCP. Several application examples for these precision indexes were presented, and the precision of regional cotton trials in the Yellow River Valley and the Changjiang Valley were investigated through the historical data of RCTs from 1980 to 1999.展开更多
基金supported by the National Regional Trial of Crop Varieties,Scientific and Technical Innovation Project of Chinese Academy of Agricultural Sciences.
文摘Rapeseed variety needs to be tested by regional trial in multiple sites for many years before being applied in market in China.Performants of rapeseed were affected by the interaction of sites and varieties.Evaluation of regional trials is very important for guiding rapeseed breeding.GGE(genotype main effects and genotypeenvironment interaction)biplot was used to evaluate yield,stability,adaptability,representativeness and discrimination of national winter rapeseed trials in the upper reaches of Yangtze River in 2017-2018.Results showed that the main effects of genotype(G),environment(E)and genotypeenvironment interaction(GE)were significant(P<0.01)for yield.Among them,E accounted for 46.95%total variation on average,G and GE accounted for 19.34%and 33.71%respectively.Eight varieties were found with high-yield,excellent stability and adaptability,including‘Yiyou 29’,‘Xiwang 920’,‘Liyouza 108’,‘Nanyou 546’,‘Dadi 195’,‘Jiayou 1’,‘Huayouza 28’and‘Yuhua 2’.Test sites included Nanchong,Mianyang,Wanzhou,Shuangliu and Chengdu in Sichuan Province and Zunyi together with Guiyang in Guizhou Province were selected for their excellent representativeness and discrimination.These results would provide theoretical basis for rapeseed breeding.
文摘Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.
文摘According to the basic concepts of precision and the principles of analysis of variance (ANOVA), precision types for experiments and variety comparison in regional crop trials (RCT) were studied and developed; expected variety comparison precision (EVCP) and realized variety comparison precision (RVCP) and the corresponding statistical indexes of them were proposed. It was explained that experimental precision (EP) and variety comparison precision (VCP) are two kinds of precision of RCT; EP includes error precision and variety mean precision, which can be measured respectively by the coefficient of variation of single observation's error (CVe) and the coefficient of variation of variety mean's error (CVy); VCP includes EVCP and RVCP, which can be measured respectively by the detectable least relative difference (DLRD) and the relative least significant distance (RLSD); EP is an important factor of VCP but not identical to it; RVCP is the realization of EVCP. Besides error, experimental design and GE interaction and ANOVA model affect VCP. Several application examples for these precision indexes were presented, and the precision of regional cotton trials in the Yellow River Valley and the Changjiang Valley were investigated through the historical data of RCTs from 1980 to 1999.