{"title":"面包小麦籽粒产量的加性主效应与乘性互作分析","authors":"M. A. Khan, F. Mohammad, F. Khan, S. Ahmad","doi":"10.36899/japs.2020.3.0080","DOIUrl":null,"url":null,"abstract":"Testing breeding material in diverse environments is required for cultivar development to curtail cross over interaction. Seventy-nine bread wheat Recombinant Inbred Lines (RIL’s) along with two check cultivars were field-tested across nine environments (sites × year network) in Khyber Pakhtunkhwa, Pakistan using alpha lattice design with two replicates during 2013/16. Combined analysis of variance revealed significant differences among genotypes, environments and genotype by interactions (GEI) for grain yield. The AMMI analysis revealed a major role of GEI (72.4%) in total phenotypic expression of grain yield. Larger variation due to GEI indicated that both performance and ranking of genotypes were fluctuated mainly due to the interaction of genotypes with environments. Environment and genotypes had almost equal contributions to the total sum of squares. Sum of squares due to GEI was 5 times larger than that for genotypes, suggesting the existence of mega environments. Similarly, smaller sum of squares due to environments and genotypes indicated minor contribution towards total variation. Conversely, larger GEI sum of squares implies unstable performance and the existence of cross over interactions between genotypes and environments for all studied traits. AMMI analysis partitioned GEI sum of squares into eight principal components for the studied traits. The first two principal components (PC1 and PC2) explained half of the total GEI sum of squares, thus sufficient to explain the complex patterns of GE interaction for studied traits. The AMMI1 model identified G-79 as the most stable and high yielding genotype for grain yield. Similarly, AMMI2 biplot revealed G-58 as widely adaptable genotype for grain yield Among environments, E-02 and E-07 were the highest and lowest productive environments for grain yield. AMMI analysis identified G-79 as the most stable and high yielding RILs and thus, recommended for extensive testing.","PeriodicalId":14924,"journal":{"name":"Journal of Animal and Plant Sciences","volume":"30 1","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"ADDITIVE MAIN EFFECT AND MULTIPLICATIVE INTERACTION ANALYSIS FOR GRAIN YIELD IN BREAD WHEAT\",\"authors\":\"M. A. Khan, F. Mohammad, F. Khan, S. Ahmad\",\"doi\":\"10.36899/japs.2020.3.0080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Testing breeding material in diverse environments is required for cultivar development to curtail cross over interaction. Seventy-nine bread wheat Recombinant Inbred Lines (RIL’s) along with two check cultivars were field-tested across nine environments (sites × year network) in Khyber Pakhtunkhwa, Pakistan using alpha lattice design with two replicates during 2013/16. Combined analysis of variance revealed significant differences among genotypes, environments and genotype by interactions (GEI) for grain yield. The AMMI analysis revealed a major role of GEI (72.4%) in total phenotypic expression of grain yield. Larger variation due to GEI indicated that both performance and ranking of genotypes were fluctuated mainly due to the interaction of genotypes with environments. Environment and genotypes had almost equal contributions to the total sum of squares. Sum of squares due to GEI was 5 times larger than that for genotypes, suggesting the existence of mega environments. Similarly, smaller sum of squares due to environments and genotypes indicated minor contribution towards total variation. Conversely, larger GEI sum of squares implies unstable performance and the existence of cross over interactions between genotypes and environments for all studied traits. AMMI analysis partitioned GEI sum of squares into eight principal components for the studied traits. The first two principal components (PC1 and PC2) explained half of the total GEI sum of squares, thus sufficient to explain the complex patterns of GE interaction for studied traits. The AMMI1 model identified G-79 as the most stable and high yielding genotype for grain yield. Similarly, AMMI2 biplot revealed G-58 as widely adaptable genotype for grain yield Among environments, E-02 and E-07 were the highest and lowest productive environments for grain yield. AMMI analysis identified G-79 as the most stable and high yielding RILs and thus, recommended for extensive testing.\",\"PeriodicalId\":14924,\"journal\":{\"name\":\"Journal of Animal and Plant Sciences\",\"volume\":\"30 1\",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2020-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Animal and Plant Sciences\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.36899/japs.2020.3.0080\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Animal and Plant Sciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.36899/japs.2020.3.0080","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
ADDITIVE MAIN EFFECT AND MULTIPLICATIVE INTERACTION ANALYSIS FOR GRAIN YIELD IN BREAD WHEAT
Testing breeding material in diverse environments is required for cultivar development to curtail cross over interaction. Seventy-nine bread wheat Recombinant Inbred Lines (RIL’s) along with two check cultivars were field-tested across nine environments (sites × year network) in Khyber Pakhtunkhwa, Pakistan using alpha lattice design with two replicates during 2013/16. Combined analysis of variance revealed significant differences among genotypes, environments and genotype by interactions (GEI) for grain yield. The AMMI analysis revealed a major role of GEI (72.4%) in total phenotypic expression of grain yield. Larger variation due to GEI indicated that both performance and ranking of genotypes were fluctuated mainly due to the interaction of genotypes with environments. Environment and genotypes had almost equal contributions to the total sum of squares. Sum of squares due to GEI was 5 times larger than that for genotypes, suggesting the existence of mega environments. Similarly, smaller sum of squares due to environments and genotypes indicated minor contribution towards total variation. Conversely, larger GEI sum of squares implies unstable performance and the existence of cross over interactions between genotypes and environments for all studied traits. AMMI analysis partitioned GEI sum of squares into eight principal components for the studied traits. The first two principal components (PC1 and PC2) explained half of the total GEI sum of squares, thus sufficient to explain the complex patterns of GE interaction for studied traits. The AMMI1 model identified G-79 as the most stable and high yielding genotype for grain yield. Similarly, AMMI2 biplot revealed G-58 as widely adaptable genotype for grain yield Among environments, E-02 and E-07 were the highest and lowest productive environments for grain yield. AMMI analysis identified G-79 as the most stable and high yielding RILs and thus, recommended for extensive testing.
期刊介绍:
The Journal of Animal and Plant Sciences (JAPS) is a bi-monthly publication and is being published regularly since 1991 by the Pakistan Agricultural Scientists Forum (PAS FORUM). It publishes original research papers, review, extension/clinical articles on all aspects of animal (including fisheries/wildlife) and plant sciences, agricultural economics, rural sociology and other related subjects. The journal is read, abstracted and indexed by the abstracting/indexing agencies of international repute.