A novel multi trait genotype ideotype distance index (MGIDI) for genotype selection in plant breeding: Application, prospects, and limitations

Pinki Debnath , Kakon Chakma , M. Shafi Ullah Bhuiyan , Reshma Thapa , Ronghui Pan , Delara Akhter
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Abstract

The Multitrait Genotype Ideotype Distance Index (MGIDI) is a strong and adaptable technique for choosing superior genotypes of diverse crops based on numerous attributes. It is a multivariate selection indicator that incorporates different characteristic information into a single value and ranks genotypes based on their distance from an ideal genotype. Breeders can use variable selection criteria including weighting traits and assessing genetic strengths and weaknesses. It organizes attributes into components and chooses optimal genotypes based on many traits using principal component analysis. This review covered the available information regarding the background, applications, prospects, and limitations of MGIDI for crop improvement and breeding in this research. We discussed the significant discoveries and consequences of several studies that used MGIDI to enhance the productivity, excellence, and flexibility of numerous crops, such as bush yam, barley, cassava, cucumber, guar, lentil, maize, rice, bean, soybean, wheat, etc. Additionally, we talked about some of the potential applications of MGIDI for breeding and crop improvement, such as tolerance to salinity, stability analysis, tolerance to waterlogging, mechanism of drought response, performance in agronomy and tuber quality, nutritional value and productivity, adaptability, increased yield, early maturity, and stress resistance etc. Following the upward trend, MGIDI can be considered as a valuable index technique for selection of crop genotypes that can address food security, climate change, and nutritional quality problems worldwide. We expect that this study will spark more research and use of MGIDI in different crops characteristics, contributing to the improvement of plant breeding science.

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用于植物育种中基因型选择的新型多性状基因型表意型距离指数(MGIDI):应用、前景和局限性
多性状基因型表型距离指数(MGIDI)是一种基于多种属性选择不同作物优良基因型的强大而适用的技术。它是一种多变量选择指标,将不同的特征信息整合到一个值中,并根据基因型与理想基因型的距离对基因型进行排序。育种者可以使用不同的选择标准,包括加权性状和评估遗传优缺点。它将属性组织成成分,并利用主成分分析法根据许多性状选择最佳基因型。本综述涵盖了有关本研究中用于作物改良和育种的 MGIDI 的背景、应用、前景和局限性的现有信息。我们讨论了一些研究的重大发现和结果,这些研究利用多元智能提高了许多作物的产量、品质和灵活性,如山药、大麦、木薯、黄瓜、瓜尔豆、扁豆、玉米、水稻、豆类、大豆、小麦等。此外,我们还讨论了多元智能在育种和作物改良方面的一些潜在应用,如耐盐性、稳定性分析、耐涝性、抗旱机制、农艺性能和块茎质量、营养价值和生产力、适应性、增产、早熟和抗逆性等。随着这一趋势的发展,MGIDI 可被视为一种有价值的指标技术,用于选择能解决全球粮食安全、气候变化和营养质量问题的作物基因型。我们期待这项研究能引发更多关于 MGIDI 在不同作物特性方面的研究和应用,为提高植物育种科学水平做出贡献。
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