Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses
Abstract The current investigation, titled “Genotype x Environment interaction of tomato (Solanum lycopersicum L.) genotypes using GGE biplot analyses,” was carried out 2022-23 across three locations in Himachal Pradesh, India through GGE biplot analysis. Hence, the present investigation was carried...
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Nature Portfolio
2025-08-01
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| author | Nikhil Thakur Deepa Sharma Jasdeep Kaur Vinit Sharma |
| author_facet | Nikhil Thakur Deepa Sharma Jasdeep Kaur Vinit Sharma |
| author_sort | Nikhil Thakur |
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| description | Abstract The current investigation, titled “Genotype x Environment interaction of tomato (Solanum lycopersicum L.) genotypes using GGE biplot analyses,” was carried out 2022-23 across three locations in Himachal Pradesh, India through GGE biplot analysis. Hence, the present investigation was carried out to identify high yielding stable genotypes among various genotypes. The material consists of 10 tomato genotypes including check i.e. Solan Lalima. The experiment was laid out in a RCBD. The data were recorded and analyzed to work out mean performances and the inferences were drawn for parameters of variability, correlation coefficients, path coefficients, stability analysis and GGE biplot. High PCV and GCV were recorded for fruit yield per plant and various other traits. Heritability and genetic advance were recorded maximum for number of fruits per cluster in E1, number of fruit clusters per plant in E2 and number of fruit clusters per plant, number of fruits per cluster were recorded maximum in E3 locations. Correlation coefficients showed that number of fruits per plant and average fruit weight were positively and significantly correlated with fruit yield per plant. Path coefficient analysis in E1, E2 and E3 locations showed that average fruit weight had the highest positive direct effect on fruit yield per plant. The pooled data over environments were analyzed to estimate the interaction effects between genotypes × environment. The mean sum of squares due to genotypes, environments and genotypes × environment interaction were significant for all the traits. Genotypes, namely EC-635,526, EC-687,423, COHF-T-1, COHF-T-2, and COHF-T-3, emerged as the top performers in terms of fruit yield per plant across different environments. By employing the Eberhart and Russell model, these genotypes exhibited broad adaptability and predictability for fruit yield per plant. Additionally, the GGE biplot analysis identified environments E3 (Bajaura) and E2 (Neri) as representative and discriminative, facilitating the selection of genotypes well-suited to specific conditions. Particularly noteworthy were genotypes G3 (EC-687423) in E1 and E3, G6 (COHF-T-1) followed by G8 (COHF-T-3), G9 (COHF-T-4) in E2, as they were positioned on the vertices of the polygon, indicating their reliability and stability across all environments regarding fruit yield per plant in responsive conditions. |
| format | Article |
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| institution | Kabale University |
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| spelling | doaj-art-698ef780eda649929f2f3e817bbb4e672025-08-20T04:03:02ZengNature PortfolioScientific Reports2045-23222025-08-0115111710.1038/s41598-024-83454-9Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analysesNikhil Thakur0Deepa Sharma1Jasdeep Kaur2Vinit Sharma3Department of Vegetable Science, Dr. Yashwant Singh Parmar University of Horticulture and ForestryDepartment of Vegetable Science, College of Horticulture and Forestry, Neri Hamirpur, Dr. Y.S Parmar University of Horticulture and ForestryDepartment of Vegetable Science and Floriculture, CSK Himachal Pradesh Krishi VishvavidyalayaDepartment of Vegetable Science, Dr. Yashwant Singh Parmar University of Horticulture and ForestryAbstract The current investigation, titled “Genotype x Environment interaction of tomato (Solanum lycopersicum L.) genotypes using GGE biplot analyses,” was carried out 2022-23 across three locations in Himachal Pradesh, India through GGE biplot analysis. Hence, the present investigation was carried out to identify high yielding stable genotypes among various genotypes. The material consists of 10 tomato genotypes including check i.e. Solan Lalima. The experiment was laid out in a RCBD. The data were recorded and analyzed to work out mean performances and the inferences were drawn for parameters of variability, correlation coefficients, path coefficients, stability analysis and GGE biplot. High PCV and GCV were recorded for fruit yield per plant and various other traits. Heritability and genetic advance were recorded maximum for number of fruits per cluster in E1, number of fruit clusters per plant in E2 and number of fruit clusters per plant, number of fruits per cluster were recorded maximum in E3 locations. Correlation coefficients showed that number of fruits per plant and average fruit weight were positively and significantly correlated with fruit yield per plant. Path coefficient analysis in E1, E2 and E3 locations showed that average fruit weight had the highest positive direct effect on fruit yield per plant. The pooled data over environments were analyzed to estimate the interaction effects between genotypes × environment. The mean sum of squares due to genotypes, environments and genotypes × environment interaction were significant for all the traits. Genotypes, namely EC-635,526, EC-687,423, COHF-T-1, COHF-T-2, and COHF-T-3, emerged as the top performers in terms of fruit yield per plant across different environments. By employing the Eberhart and Russell model, these genotypes exhibited broad adaptability and predictability for fruit yield per plant. Additionally, the GGE biplot analysis identified environments E3 (Bajaura) and E2 (Neri) as representative and discriminative, facilitating the selection of genotypes well-suited to specific conditions. Particularly noteworthy were genotypes G3 (EC-687423) in E1 and E3, G6 (COHF-T-1) followed by G8 (COHF-T-3), G9 (COHF-T-4) in E2, as they were positioned on the vertices of the polygon, indicating their reliability and stability across all environments regarding fruit yield per plant in responsive conditions.https://doi.org/10.1038/s41598-024-83454-9EnvironmentGGE biplotG × E interactionTomatoStability |
| spellingShingle | Nikhil Thakur Deepa Sharma Jasdeep Kaur Vinit Sharma Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses Scientific Reports Environment GGE biplot G × E interaction Tomato Stability |
| title | Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses |
| title_full | Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses |
| title_fullStr | Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses |
| title_full_unstemmed | Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses |
| title_short | Characterizing tomato genotypes in the varied climates of north-western Himalayas and implications for environmental resilience using GGE Biplot analyses |
| title_sort | characterizing tomato genotypes in the varied climates of north western himalayas and implications for environmental resilience using gge biplot analyses |
| topic | Environment GGE biplot G × E interaction Tomato Stability |
| url | https://doi.org/10.1038/s41598-024-83454-9 |
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