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利用AMMI模型分析克什米尔喜马拉雅地区开放授粉番茄品种的产量稳定性及基因型与环境互作

Analysis of yield stability and genotype-environment interaction for open-pollinated tomato varieties in the Kashmir Himalaya using the AMMI model.

作者信息

Masoodi Ummyiah H, Shah Immad A, Emam Walid, Tashkandy Yusra, Mishra Pradeep, Mishra Neha, Matuka Adelajda

机构信息

Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Shalimar, Srinagar, J&K, 190025, India.

Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia.

出版信息

Sci Rep. 2025 Jul 2;15(1):23107. doi: 10.1038/s41598-025-07621-2.

Abstract

This study investigates the yield stability and adaptability of sixteen open-pollinated tomato (Solanum lycopersicum Mill.) genotypes across multiple environments in the Kashmir Valley, employing Additive Main Effect and Multiplicative Interaction (AMMI) analysis to examine genotype-environment interactions (GEI). A Randomized Complete Block Design (RCBD) with three replications was implemented at six locations over two years, representing the region's diverse environmental conditions. Analysis of variance indicated that the effects of environment (E), genotype (G), and GEI were all highly significant (p < 0.001) in influencing yield per hectare, with the environment contributing 47.5% of the total variation, underscoring the impact of local conditions on performance. Key stability indicators, including Weighted Average of Absolute Scores (WAAS) and Multi-Trait Stability Index (MTSI), assessed genotype stability and yield, with Arka Meghali and NDF-9 emerging as top-performing varieties across locations. Arka Meghali achieved the highest yield, while NDF-9 showed remarkable adaptability. The consistent rankings provided by stability indices reinforced the reliability of WAAS and MTSI as selection tools in multi-environment trials. Based on multi-environment stability analysis, Arka Meghali and NDF-9 were identified as superior open-pollinated tomato genotypes combining high yield and stability across diverse environments. These varieties are recommended for cultivation in the Kashmir Valley to enhance tomato productivity under variable agro-climatic conditions.These findings underscore the utility of GEI analysis in identifying tomato genotypes with robust yield and stability, providing valuable insights for breeding programs and crop management in ecologically sensitive regions like the Northern Himalayas. This research establishes a foundation for future studies on environmental adaptability in crop improvement, highlighting the potential of selected genotypes for sustainable cultivation in Kashmir.

摘要

本研究调查了16个开放授粉番茄(Solanum lycopersicum Mill.)基因型在克什米尔山谷多个环境中的产量稳定性和适应性,采用加性主效应和乘性互作(AMMI)分析来检验基因型与环境互作(GEI)。在两年内于六个地点实施了具有三次重复的随机完全区组设计(RCBD),代表了该地区多样的环境条件。方差分析表明,环境(E)、基因型(G)和GEI对每公顷产量的影响均极显著(p < 0.001),其中环境贡献了总变异的47.5%,突出了当地条件对表现的影响。包括绝对得分加权平均值(WAAS)和多性状稳定性指数(MTSI)在内的关键稳定性指标评估了基因型稳定性和产量,Arka Meghali和NDF - 9在各地点成为表现最佳的品种。Arka Meghali产量最高,而NDF - 9表现出显著的适应性。稳定性指数提供的一致排名增强了WAAS和MTSI作为多环境试验选择工具的可靠性。基于多环境稳定性分析,Arka Meghali和NDF - 9被确定为优良的开放授粉番茄基因型,在不同环境中兼具高产和稳定性。推荐在克什米尔山谷种植这些品种,以在多变的农业气候条件下提高番茄产量。这些发现强调了GEI分析在识别具有稳健产量和稳定性的番茄基因型方面的实用性,为喜马拉雅北部等生态敏感地区的育种计划和作物管理提供了有价值的见解。本研究为未来作物改良中环境适应性研究奠定了基础,突出了所选基因型在克什米尔可持续种植的潜力。

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