{"title":"利用gge双图方法对白山药基因型进行多位点评价。","authors":"Emmanuel C Nwachukwu","doi":"10.4314/gjass.v12i2.14","DOIUrl":null,"url":null,"abstract":"Yams are Cultivated in diverse agroecologies and there is evidence of strong genotype and environment interaction. This has necessitated the evaluation of new yam genotypes in multi-locational trials. Five new white yam genotypes were evaluated in different locations of major yam producing areas; Umudike, Nsukka, Ubiaja, Abuja and Katsina-Ala, to test the performance and stability of these genotypes across the environments using GGE bi-plot software. The GGE bi-plot generated several graphic bi-plots which showed Umudike, Nsukka, Ubiaja and Katsina-Ala belonging to one mega- environment while Abuja and Ubiaja belong to another. The GGE bi-plot also showed the discriminating and non-discriminating environments. Katsina-Ala was the most discriminating environment while Nsukka was the least. A test environment that lacks discriminating ability lacks the capacity to provide information about the genotype being used. Such environment lacks usefulness and should be discarded as a test environment Katsina-Ala, with the longest vector is the most discriminating. This is followed by Ubiaja, Umudike and Abuja in that order. Nsukka is the least discriminating.","PeriodicalId":250072,"journal":{"name":"Global Journal of Agricultural Sciences","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multilocational evaluation of white yam genotypes using gge bi-plot methodology.\",\"authors\":\"Emmanuel C Nwachukwu\",\"doi\":\"10.4314/gjass.v12i2.14\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Yams are Cultivated in diverse agroecologies and there is evidence of strong genotype and environment interaction. This has necessitated the evaluation of new yam genotypes in multi-locational trials. Five new white yam genotypes were evaluated in different locations of major yam producing areas; Umudike, Nsukka, Ubiaja, Abuja and Katsina-Ala, to test the performance and stability of these genotypes across the environments using GGE bi-plot software. The GGE bi-plot generated several graphic bi-plots which showed Umudike, Nsukka, Ubiaja and Katsina-Ala belonging to one mega- environment while Abuja and Ubiaja belong to another. The GGE bi-plot also showed the discriminating and non-discriminating environments. Katsina-Ala was the most discriminating environment while Nsukka was the least. A test environment that lacks discriminating ability lacks the capacity to provide information about the genotype being used. Such environment lacks usefulness and should be discarded as a test environment Katsina-Ala, with the longest vector is the most discriminating. This is followed by Ubiaja, Umudike and Abuja in that order. Nsukka is the least discriminating.\",\"PeriodicalId\":250072,\"journal\":{\"name\":\"Global Journal of Agricultural Sciences\",\"volume\":\"183 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Journal of Agricultural Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/gjass.v12i2.14\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Journal of Agricultural Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/gjass.v12i2.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multilocational evaluation of white yam genotypes using gge bi-plot methodology.
Yams are Cultivated in diverse agroecologies and there is evidence of strong genotype and environment interaction. This has necessitated the evaluation of new yam genotypes in multi-locational trials. Five new white yam genotypes were evaluated in different locations of major yam producing areas; Umudike, Nsukka, Ubiaja, Abuja and Katsina-Ala, to test the performance and stability of these genotypes across the environments using GGE bi-plot software. The GGE bi-plot generated several graphic bi-plots which showed Umudike, Nsukka, Ubiaja and Katsina-Ala belonging to one mega- environment while Abuja and Ubiaja belong to another. The GGE bi-plot also showed the discriminating and non-discriminating environments. Katsina-Ala was the most discriminating environment while Nsukka was the least. A test environment that lacks discriminating ability lacks the capacity to provide information about the genotype being used. Such environment lacks usefulness and should be discarded as a test environment Katsina-Ala, with the longest vector is the most discriminating. This is followed by Ubiaja, Umudike and Abuja in that order. Nsukka is the least discriminating.