Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions
The genetic diversity of yield and yield attributing characteristics was explored in this research. In the topical study, fifty-two rice genotypes including four checks were used under three environmental conditions i.e. irrigated (IR), rainfed (RF) and terminal stage drought (TSD) conditions. The...
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| Format: | Article |
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Action for Sustainable Efficacious Development and Awareness
2022-05-01
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| Series: | Environment Conservation Journal |
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| Online Access: | https://journal.environcj.in/index.php/ecj/article/view/969 |
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| author | Hamsa Poorna Prakash Suman Rawte Ritu Ravi Saxena Satish Balakrishna Verulkar Ravi Ratna Saxena |
| author_facet | Hamsa Poorna Prakash Suman Rawte Ritu Ravi Saxena Satish Balakrishna Verulkar Ravi Ratna Saxena |
| author_sort | Hamsa Poorna Prakash |
| collection | DOAJ |
| description |
The genetic diversity of yield and yield attributing characteristics was explored in this research. In the topical study, fifty-two rice genotypes including four checks were used under three environmental conditions i.e. irrigated (IR), rainfed (RF) and terminal stage drought (TSD) conditions. The prevalence of genetic divergence was evaluated using clustering and Principal component analysis (PCA) was used to determine the relative contribution of various traits. To fulfill the aim of the study, fifty-two genotypes were grouped into three distinct and non-overlapping clusters among these 3 clusters, cluster-I was the largest with the highest number of genotypes i.e. 47, 49 and 49 under IR, RF and TSD conditions, respectively. The highest average intra-cluster distance was observed in cluster-I, also the genotypes showed high variability under all three conditions. The highest inter-cluster distance between the cluster-II and cluster-III (IR and TSD) and cluster-I and cluster-II (RF) was observed, indicated that genotypes from the group should be considered for direct use as parents in hybridization programme to produce high yield. Only five of the 13 principal components (PCs) have been considered in the study based on the Eigen values and variability criteria. From the complex matrix it was revealed that the first-PC accounted for the highest variability. Genotypes which fall under a common PC were observed to be the most important factor for grain yield.
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| first_indexed | 2024-04-13T21:24:10Z |
| format | Article |
| id | doaj.art-767e41d7a35d4eb08e7a4e0c38af006e |
| institution | Directory Open Access Journal |
| issn | 0972-3099 2278-5124 |
| language | English |
| last_indexed | 2024-04-13T21:24:10Z |
| publishDate | 2022-05-01 |
| publisher | Action for Sustainable Efficacious Development and Awareness |
| record_format | Article |
| series | Environment Conservation Journal |
| spelling | doaj.art-767e41d7a35d4eb08e7a4e0c38af006e2022-12-22T02:29:23ZengAction for Sustainable Efficacious Development and AwarenessEnvironment Conservation Journal0972-30992278-51242022-05-0123310.36953/ECJ.9692201Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditionsHamsa Poorna Prakash0Suman Rawte 1Ritu Ravi Saxena 2Satish Balakrishna Verulkar3Ravi Ratna Saxena4Department of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur, Chhattisgarh, India.Department of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur, Chhattisgarh, IndiaDepartment of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur, Chhattisgarh, IndiaDepartment of Plant Molecular Biology and Biotechnology, College of Agriculture, IGKV, Raipur, Chhattisgarh, India.Department of Agricultural Statistics, College of Agriculture, IGKV, Raipur, Chhattisgarh, India The genetic diversity of yield and yield attributing characteristics was explored in this research. In the topical study, fifty-two rice genotypes including four checks were used under three environmental conditions i.e. irrigated (IR), rainfed (RF) and terminal stage drought (TSD) conditions. The prevalence of genetic divergence was evaluated using clustering and Principal component analysis (PCA) was used to determine the relative contribution of various traits. To fulfill the aim of the study, fifty-two genotypes were grouped into three distinct and non-overlapping clusters among these 3 clusters, cluster-I was the largest with the highest number of genotypes i.e. 47, 49 and 49 under IR, RF and TSD conditions, respectively. The highest average intra-cluster distance was observed in cluster-I, also the genotypes showed high variability under all three conditions. The highest inter-cluster distance between the cluster-II and cluster-III (IR and TSD) and cluster-I and cluster-II (RF) was observed, indicated that genotypes from the group should be considered for direct use as parents in hybridization programme to produce high yield. Only five of the 13 principal components (PCs) have been considered in the study based on the Eigen values and variability criteria. From the complex matrix it was revealed that the first-PC accounted for the highest variability. Genotypes which fall under a common PC were observed to be the most important factor for grain yield. https://journal.environcj.in/index.php/ecj/article/view/969Cluster analysisPCAyield |
| spellingShingle | Hamsa Poorna Prakash Suman Rawte Ritu Ravi Saxena Satish Balakrishna Verulkar Ravi Ratna Saxena Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions Environment Conservation Journal Cluster analysis PCA yield |
| title | Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions |
| title_full | Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions |
| title_fullStr | Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions |
| title_full_unstemmed | Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions |
| title_short | Assessing the genetic diversity for yield traits in rice (Oryza sativa L.) genotypes using multivariate analysis under controlled and water stress conditions |
| title_sort | assessing the genetic diversity for yield traits in rice oryza sativa l genotypes using multivariate analysis under controlled and water stress conditions |
| topic | Cluster analysis PCA yield |
| url | https://journal.environcj.in/index.php/ecj/article/view/969 |
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