Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill)
In the present study, 33 soybean genotypes were selected to study the association between the fourteen quantitative characters under study and to assess the magnitude of divergence between 33 genotypes for 14 traits during Kharif, 2021. For all measured traits, the results revealed significant vari...
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| Format: | Article |
| Language: | English |
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Action for Sustainable Efficacious Development and Awareness
2023-04-01
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| Series: | Environment Conservation Journal |
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| Online Access: | https://journal.environcj.in/index.php/ecj/article/view/1453 |
| _version_ | 1797677596442361856 |
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| author | Devi Sri Dunna Nanita Devi Heisnam Renuka Devi Thokchom Bireswar Sinha Okendro Singh |
| author_facet | Devi Sri Dunna Nanita Devi Heisnam Renuka Devi Thokchom Bireswar Sinha Okendro Singh |
| author_sort | Devi Sri Dunna |
| collection | DOAJ |
| description |
In the present study, 33 soybean genotypes were selected to study the association between the fourteen quantitative characters under study and to assess the magnitude of divergence between 33 genotypes for 14 traits during Kharif, 2021. For all measured traits, the results revealed significant variation among tested entries. The principal component analysis (PCA) was conducted for the 1quantitative characters and only 7 showed > 1 Eigen value and showed about 81.748% of total variation and remaining 7 components having a eigen value less than 1.00 and contributed only 18.252% of total Variation. Among the traits studied PC1 showed 20.7235 while, PC2 to PC 14 exhibited 15.205%, 12.69%, 9.476%, 9.142%,7.271%, 7.241%, 6.171%, 4.089%, 2.865%, 2.185%, 1.506%, 0.897% and 0.536% variability, respectively. Scree plots explained the percentage of variance. A high PC score for a specific genotype shows high value for those variables like EC 915989, EC 915900, EC 915993, EC 915975, EC 915903, EC 915898 and EC 915959 in PC1 and this indicated that these genotypes have high values for traits such as 100 Fresh pod weight and 100 Fresh seed weight.
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| first_indexed | 2024-03-11T22:47:33Z |
| format | Article |
| id | doaj.art-20c1b739f093474f88c9b8bf66b9fb55 |
| institution | Directory Open Access Journal |
| issn | 0972-3099 2278-5124 |
| language | English |
| last_indexed | 2024-03-11T22:47:33Z |
| publishDate | 2023-04-01 |
| publisher | Action for Sustainable Efficacious Development and Awareness |
| record_format | Article |
| series | Environment Conservation Journal |
| spelling | doaj.art-20c1b739f093474f88c9b8bf66b9fb552023-09-22T05:09:46ZengAction for Sustainable Efficacious Development and AwarenessEnvironment Conservation Journal0972-30992278-51242023-04-0124310.36953/ECJ.14532442Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill)Devi Sri Dunna0Nanita Devi Heisnam1Renuka Devi Thokchom2Bireswar Sinha3Okendro Singh4Department of Genetics and Plant Breeding, College of Agriculture, Central Agricultural University, Imphal, Manipur, India, 795004Department of Genetics and Plant Breeding, College of Agriculture, Central Agricultural University, Imphal, Manipur, India, 795004Department of Genetics and Plant Breeding, College of Agriculture, Central Agricultural University, Imphal, Manipur, India, 795004Department of Plant Pathology, College of Agriculture, Central Agricultural University, Imphal, Manipur, India, 795004Department of Basic Sciences, College of Agriculture, Central Agricultural University, Imphal, Manipur, India, 795004 In the present study, 33 soybean genotypes were selected to study the association between the fourteen quantitative characters under study and to assess the magnitude of divergence between 33 genotypes for 14 traits during Kharif, 2021. For all measured traits, the results revealed significant variation among tested entries. The principal component analysis (PCA) was conducted for the 1quantitative characters and only 7 showed > 1 Eigen value and showed about 81.748% of total variation and remaining 7 components having a eigen value less than 1.00 and contributed only 18.252% of total Variation. Among the traits studied PC1 showed 20.7235 while, PC2 to PC 14 exhibited 15.205%, 12.69%, 9.476%, 9.142%,7.271%, 7.241%, 6.171%, 4.089%, 2.865%, 2.185%, 1.506%, 0.897% and 0.536% variability, respectively. Scree plots explained the percentage of variance. A high PC score for a specific genotype shows high value for those variables like EC 915989, EC 915900, EC 915993, EC 915975, EC 915903, EC 915898 and EC 915959 in PC1 and this indicated that these genotypes have high values for traits such as 100 Fresh pod weight and 100 Fresh seed weight. https://journal.environcj.in/index.php/ecj/article/view/1453Eigen valuesGenotypesMiracle cropScreeplot |
| spellingShingle | Devi Sri Dunna Nanita Devi Heisnam Renuka Devi Thokchom Bireswar Sinha Okendro Singh Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) Environment Conservation Journal Eigen values Genotypes Miracle crop Screeplot |
| title | Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) |
| title_full | Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) |
| title_fullStr | Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) |
| title_full_unstemmed | Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) |
| title_short | Principal component analysis among vegetable soybean genotypes (Glycine max L. Merrill) |
| title_sort | principal component analysis among vegetable soybean genotypes glycine max l merrill |
| topic | Eigen values Genotypes Miracle crop Screeplot |
| url | https://journal.environcj.in/index.php/ecj/article/view/1453 |
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