Raju Thonta, M. Pandey, Rajneesh Kumar, Santhoshini
{"title":"绿克(Vigna radiata L. Wilczek)生长与产量性状的相关及通径系数研究","authors":"Raju Thonta, M. Pandey, Rajneesh Kumar, Santhoshini","doi":"10.22271/tpi.2023.v12.i6v.20691","DOIUrl":null,"url":null,"abstract":"The current study was conducted at the agriculture research farm of the Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab during the kharif season 2022. A Randomized Block Design (RBD) with three replications were used to study variability, correlation and path including 20 Green gram germplasm for the 13 traits studied viz. days to 50% flowering, days to maturity, plant height, number of primary branches, number of clusters per plant, number of pods per plant, number of pods per cluster, number of seeds per pod, pod length (cm), seed index (g), biological yield per plant (g), seed yield per plant (g) and harvest index. Finding revealed that Seed yield showed significant and positively correlated with Biological yield (0.9406 and 0.9318) followed by harvest index (0.7592 and 0.7573) and number of clusters per plant (0.5264 and 0.4585) at both genotypic and phenotypic level respectively. Highest positive direct effect was noted for Biological yield per plant (0.7526) and lowest for number of clusters per plant (0.0039). Hence, selection for these characters could bring improvement in yield and yield components. Correlation was likewise noteworthy and favourable between these features. Therefore, identifying high-yielding genotypes from a population with substantial segregation would be aided by direct selection for these traits.","PeriodicalId":22936,"journal":{"name":"The Pharma Innovation","volume":"28 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Studies on correlation and path coefficient for growth and yield attributes in green gram (Vigna radiata L. Wilczek)\",\"authors\":\"Raju Thonta, M. Pandey, Rajneesh Kumar, Santhoshini\",\"doi\":\"10.22271/tpi.2023.v12.i6v.20691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current study was conducted at the agriculture research farm of the Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab during the kharif season 2022. A Randomized Block Design (RBD) with three replications were used to study variability, correlation and path including 20 Green gram germplasm for the 13 traits studied viz. days to 50% flowering, days to maturity, plant height, number of primary branches, number of clusters per plant, number of pods per plant, number of pods per cluster, number of seeds per pod, pod length (cm), seed index (g), biological yield per plant (g), seed yield per plant (g) and harvest index. Finding revealed that Seed yield showed significant and positively correlated with Biological yield (0.9406 and 0.9318) followed by harvest index (0.7592 and 0.7573) and number of clusters per plant (0.5264 and 0.4585) at both genotypic and phenotypic level respectively. Highest positive direct effect was noted for Biological yield per plant (0.7526) and lowest for number of clusters per plant (0.0039). Hence, selection for these characters could bring improvement in yield and yield components. Correlation was likewise noteworthy and favourable between these features. Therefore, identifying high-yielding genotypes from a population with substantial segregation would be aided by direct selection for these traits.\",\"PeriodicalId\":22936,\"journal\":{\"name\":\"The Pharma Innovation\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Pharma Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22271/tpi.2023.v12.i6v.20691\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Pharma Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22271/tpi.2023.v12.i6v.20691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Studies on correlation and path coefficient for growth and yield attributes in green gram (Vigna radiata L. Wilczek)
The current study was conducted at the agriculture research farm of the Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Punjab during the kharif season 2022. A Randomized Block Design (RBD) with three replications were used to study variability, correlation and path including 20 Green gram germplasm for the 13 traits studied viz. days to 50% flowering, days to maturity, plant height, number of primary branches, number of clusters per plant, number of pods per plant, number of pods per cluster, number of seeds per pod, pod length (cm), seed index (g), biological yield per plant (g), seed yield per plant (g) and harvest index. Finding revealed that Seed yield showed significant and positively correlated with Biological yield (0.9406 and 0.9318) followed by harvest index (0.7592 and 0.7573) and number of clusters per plant (0.5264 and 0.4585) at both genotypic and phenotypic level respectively. Highest positive direct effect was noted for Biological yield per plant (0.7526) and lowest for number of clusters per plant (0.0039). Hence, selection for these characters could bring improvement in yield and yield components. Correlation was likewise noteworthy and favourable between these features. Therefore, identifying high-yielding genotypes from a population with substantial segregation would be aided by direct selection for these traits.