Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection
Germplasm evaluation, classification, characterization, and preservation are the initial requirements for any crop genetic improvement programs meant to promote economically important traits. Mean performance and range of different expressible traits through ANOVA showed highly significant differenc...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/12/8/1921 |
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| author | Davinder Singh Tarsem Singh Dhillon Talha Javed Rajinder Singh Jalpa Dobaria Surender Kumar Dhankhar Farzad Kianersi Baber Ali Peter Poczai Uttam Kumar |
| author_facet | Davinder Singh Tarsem Singh Dhillon Talha Javed Rajinder Singh Jalpa Dobaria Surender Kumar Dhankhar Farzad Kianersi Baber Ali Peter Poczai Uttam Kumar |
| author_sort | Davinder Singh |
| collection | DOAJ |
| description | Germplasm evaluation, classification, characterization, and preservation are the initial requirements for any crop genetic improvement programs meant to promote economically important traits. Mean performance and range of different expressible traits through ANOVA showed highly significant differences within the various genotypes and helped to evaluate several promising carrot genotypes. The multivariate analysis method was used in this study, which was helpful in resolving different phenotypic and genotypic parameters/measurements of big collections into easy interpretable dimensions.The research work was carried out with eighty-one genotypes to evaluate genetic diversity in a germplasm collection through multivariate analysis.The divergence analysis grouped all eighty-one genotypes into ten clusters and cluster VI was found to be the biggest, comprised of 30 genotypes, followed by IV, which was comprised of 16 genotypes. Cluster X exhibited a high mean value for root weight and anthocyanin content; cluster III showed high value for days to 1st root harvest and root girth, and cluster V for dry matter content, total sugar content, and carotene content; respectively. The maximum distance between clusters was recorded among II and X cluster (43,678.5) follow by I and X (43,199.7), and it indicated that genotypes from these far away clusters could be used efficiently in breeding programs to obtain superior hybrids. Total sugar content (36.14%) contributed most to genetic divergence, followed by anthocyanin content (35.74%). Out of four principal components, PC1 largely contributed towards total variation, followed by PC2. The partial variances (%) from the first to fourth PC-axes were 36.77, 25.50, 12.67, and 10.17, respectively. Genotypes like PC-161, PC-173, PAU-J-15, PC-103, and PC-43 were considered superior with respect to marketable yield and its associated traits such as root length and root weight, and hence can be released directly as a variety. |
| first_indexed | 2024-03-09T10:02:39Z |
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| id | doaj.art-8dd3ef1e77224c2e9f06d72ad381439f |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-09T10:02:39Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-8dd3ef1e77224c2e9f06d72ad381439f2023-12-01T23:18:25ZengMDPI AGAgronomy2073-43952022-08-01128192110.3390/agronomy12081921Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm CollectionDavinder Singh0Tarsem Singh Dhillon1Talha Javed2Rajinder Singh3Jalpa Dobaria4Surender Kumar Dhankhar5Farzad Kianersi6Baber Ali7Peter Poczai8Uttam Kumar9Department of Vegetable Science, CCS Haryana Agricultural University, Hisar 125004, IndiaDepartment of Vegetable Science, Punjab Agricultural University, Ludhiana 141004, IndiaCollege of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaDepartment of Vegetable Science, Punjab Agricultural University, Ludhiana 141004, IndiaDepartment of Biochemistry, Anand Agricultural University, Anand 388110, IndiaDepartment of Vegetable Science, CCS Haryana Agricultural University, Hisar 125004, IndiaSchool of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, CanadaDepartment of Plant Sciences, Quaid-i-Azam University, Islamabad 45320, PakistanBotany Unit, Finnish Museum of Natural History, University of Helsinki, FI-00014 Helsinki, FinlandCollege of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou 350002, ChinaGermplasm evaluation, classification, characterization, and preservation are the initial requirements for any crop genetic improvement programs meant to promote economically important traits. Mean performance and range of different expressible traits through ANOVA showed highly significant differences within the various genotypes and helped to evaluate several promising carrot genotypes. The multivariate analysis method was used in this study, which was helpful in resolving different phenotypic and genotypic parameters/measurements of big collections into easy interpretable dimensions.The research work was carried out with eighty-one genotypes to evaluate genetic diversity in a germplasm collection through multivariate analysis.The divergence analysis grouped all eighty-one genotypes into ten clusters and cluster VI was found to be the biggest, comprised of 30 genotypes, followed by IV, which was comprised of 16 genotypes. Cluster X exhibited a high mean value for root weight and anthocyanin content; cluster III showed high value for days to 1st root harvest and root girth, and cluster V for dry matter content, total sugar content, and carotene content; respectively. The maximum distance between clusters was recorded among II and X cluster (43,678.5) follow by I and X (43,199.7), and it indicated that genotypes from these far away clusters could be used efficiently in breeding programs to obtain superior hybrids. Total sugar content (36.14%) contributed most to genetic divergence, followed by anthocyanin content (35.74%). Out of four principal components, PC1 largely contributed towards total variation, followed by PC2. The partial variances (%) from the first to fourth PC-axes were 36.77, 25.50, 12.67, and 10.17, respectively. Genotypes like PC-161, PC-173, PAU-J-15, PC-103, and PC-43 were considered superior with respect to marketable yield and its associated traits such as root length and root weight, and hence can be released directly as a variety.https://www.mdpi.com/2073-4395/12/8/1921carrotgenetic diversitycharacterizationcluster analysisprincipal component analysis |
| spellingShingle | Davinder Singh Tarsem Singh Dhillon Talha Javed Rajinder Singh Jalpa Dobaria Surender Kumar Dhankhar Farzad Kianersi Baber Ali Peter Poczai Uttam Kumar Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection Agronomy carrot genetic diversity characterization cluster analysis principal component analysis |
| title | Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection |
| title_full | Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection |
| title_fullStr | Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection |
| title_full_unstemmed | Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection |
| title_short | Exploring the Genetic Diversity of Carrot Genotypes through Phenotypically and Genetically Detailed Germplasm Collection |
| title_sort | exploring the genetic diversity of carrot genotypes through phenotypically and genetically detailed germplasm collection |
| topic | carrot genetic diversity characterization cluster analysis principal component analysis |
| url | https://www.mdpi.com/2073-4395/12/8/1921 |
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