Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria
Genotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or a...
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| author | Uchenna Noble Ukwu Onno Muller Matthias Meier-Gruell Michael Ifeanyi Uguru |
| author_facet | Uchenna Noble Ukwu Onno Muller Matthias Meier-Gruell Michael Ifeanyi Uguru |
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| description | Genotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or across multiple environments. In many nations of the world, where the drive to achieve a net-zero CO<sub>2</sub> emission by 2030 has spurred significant investments in clean energy sources such as photovoltaics with a resultant conversion of some agricultural lands to photovoltaic facilities, there is a need to find the right balance between addressing the food and energy crises. Agri-photovoltaics (APV) offer a sustainable solution by allowing crops to grow underneath photovoltaic panels. However, selection efficiency and repeatability of APV experimental results could be marred by the presence of G × E interaction. The study objective was to identify mungbean genotype(s) with a high yield potential and broad adaptability across APV environments. Five mungbean (<i>Vigna radiata</i> L.) genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83, were assessed under six contrasting APV environments, EPV-R, EPV-D, NPV-R, NPV-D, WPV-R, and WPV-D, at the Agri-PV Food and Energy Training Center, University of Nigeria, Nsukka. The experiment was a split-plot design, with the environment as the whole-plot factor while genotype was the sub-plot factor with five replications. The additive main effects and multiplicative interaction (AMMI) and the Finlay and Wilkinson joint regression analysis confirmed significant genotype, environment, and G × E interaction effects for mungbean seed yield. Two genotypes, Tvr28 and Tvr83 expressed broad adaptability to the APV environments with higher yields (2.60 and 2.50 t ha<sup>−1</sup>), ranking first and second, respectively. In contrast, the Tvr79 genotype displayed the highest sensitivity (2.95) to environmental variation and was unstable across the environments with higher IPCA1 and ASV scores of −1.17 and 1.39, respectively. The EPV-R recorded the highest yield (2.61) with low interaction effect (0.38), whereas the WPV-D environment had the least yield (1.71) and was the most unstable (−0.48). Conclusively, the Tvr28 and Tvr83 genotypes and the EPV-R environment were the ideal genotypes and environment, respectively, and are therefore recommended for use in APV facilities. |
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| spelling | doaj-art-1f6cfd13cfc44ecbbacbab5020b4e1a42025-08-20T01:49:18ZengMDPI AGPlants2223-77472025-04-01149132610.3390/plants14091326Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical NigeriaUchenna Noble Ukwu0Onno Muller1Matthias Meier-Gruell2Michael Ifeanyi Uguru3Department of Crop Science, University of Nigeria Nsukka, Nsukka 410001, Enugu State, NigeriaInstitute of Bio-and Geosciences (IBG-2), Plant Sciences, Forschungszentrum Julich GmbH, 52425 Julich, GermanyInstitute of Bio-and Geosciences (IBG-2), Plant Sciences, Forschungszentrum Julich GmbH, 52425 Julich, GermanyDepartment of Crop Science, University of Nigeria Nsukka, Nsukka 410001, Enugu State, NigeriaGenotype by environment (G × E) interaction is a magnitude change in the performance of a genotype when grown in contrasting environments. The sensitivity of a genotype to different environmental conditions is an important determinant of its suitability for cultivation in a specific environment or across multiple environments. In many nations of the world, where the drive to achieve a net-zero CO<sub>2</sub> emission by 2030 has spurred significant investments in clean energy sources such as photovoltaics with a resultant conversion of some agricultural lands to photovoltaic facilities, there is a need to find the right balance between addressing the food and energy crises. Agri-photovoltaics (APV) offer a sustainable solution by allowing crops to grow underneath photovoltaic panels. However, selection efficiency and repeatability of APV experimental results could be marred by the presence of G × E interaction. The study objective was to identify mungbean genotype(s) with a high yield potential and broad adaptability across APV environments. Five mungbean (<i>Vigna radiata</i> L.) genotypes, Tvr18, Tvr28, Tvr65, Tvr79, and Tvr 83, were assessed under six contrasting APV environments, EPV-R, EPV-D, NPV-R, NPV-D, WPV-R, and WPV-D, at the Agri-PV Food and Energy Training Center, University of Nigeria, Nsukka. The experiment was a split-plot design, with the environment as the whole-plot factor while genotype was the sub-plot factor with five replications. The additive main effects and multiplicative interaction (AMMI) and the Finlay and Wilkinson joint regression analysis confirmed significant genotype, environment, and G × E interaction effects for mungbean seed yield. Two genotypes, Tvr28 and Tvr83 expressed broad adaptability to the APV environments with higher yields (2.60 and 2.50 t ha<sup>−1</sup>), ranking first and second, respectively. In contrast, the Tvr79 genotype displayed the highest sensitivity (2.95) to environmental variation and was unstable across the environments with higher IPCA1 and ASV scores of −1.17 and 1.39, respectively. The EPV-R recorded the highest yield (2.61) with low interaction effect (0.38), whereas the WPV-D environment had the least yield (1.71) and was the most unstable (−0.48). Conclusively, the Tvr28 and Tvr83 genotypes and the EPV-R environment were the ideal genotypes and environment, respectively, and are therefore recommended for use in APV facilities.https://www.mdpi.com/2223-7747/14/9/1326Agri-photovoltaicsFinlay and Wilkinson analysisgenotype × environment interactionAMMIPV orientationstability |
| spellingShingle | Uchenna Noble Ukwu Onno Muller Matthias Meier-Gruell Michael Ifeanyi Uguru Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria Plants Agri-photovoltaics Finlay and Wilkinson analysis genotype × environment interaction AMMI PV orientation stability |
| title | Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria |
| title_full | Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria |
| title_fullStr | Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria |
| title_full_unstemmed | Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria |
| title_short | Yield Sensitivity of Mungbean (<i>Vigna radiata</i> L.) Genotypes to Different Agrivoltaic Environments in Tropical Nigeria |
| title_sort | yield sensitivity of mungbean i vigna radiata i l genotypes to different agrivoltaic environments in tropical nigeria |
| topic | Agri-photovoltaics Finlay and Wilkinson analysis genotype × environment interaction AMMI PV orientation stability |
| url | https://www.mdpi.com/2223-7747/14/9/1326 |
| work_keys_str_mv | AT uchennanobleukwu yieldsensitivityofmungbeanivignaradiatailgenotypestodifferentagrivoltaicenvironmentsintropicalnigeria AT onnomuller yieldsensitivityofmungbeanivignaradiatailgenotypestodifferentagrivoltaicenvironmentsintropicalnigeria AT matthiasmeiergruell yieldsensitivityofmungbeanivignaradiatailgenotypestodifferentagrivoltaicenvironmentsintropicalnigeria AT michaelifeanyiuguru yieldsensitivityofmungbeanivignaradiatailgenotypestodifferentagrivoltaicenvironmentsintropicalnigeria |