绿豆优良基因型(Vigna radiata, L.)的筛选Wilczek)通过食品和营养安全的多变量分析

Sanhita Ghosh, Anindita Roy, S. Kundagrami
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引用次数: 0

摘要

为适应不断增长的人口而不断推进的城市化大大减少了农业用地,但对满足人类健康所需的适当营养构成了威胁。绿豆[Vigna radiata [L.]Wilczek]是大自然赐予人类的独特礼物,它具有以低廉的成本弥补蛋白质短缺缺口的潜力,但由于其生产水平和生产力较低,间接影响了人们的营养状况,导致营养不良。因此,不允许增加绿豆种植总面积,而必须提高单位面积的总生产力。因此,筛选和评价高产改良基因型对于确保粮食安全是必要的。但同时,种子产量是一个复杂的性状,受其他几个贡献性状的支配,性状的选择证明是相当具有挑战性的。作为任何旨在提高产量的育种计划的先决条件,在给定群体中存在显著的遗传多样性是非常重要的。在本调查中进行了主成分分析,结果揭示了两个主成分对总体方差的贡献。PC1以产量及其归因性状为主,而PC2则以生长相关性状为主。采用标准化数据进行UPGMA聚类分析,将52个绿豆基因型分为4个聚类,其中2个主要聚类,1个次要聚类,1个异常聚类。其中,集群II最引人注目,因为它的个体具有高产量的植物- 1和相关性状。本研究表明,通过多变量分析鉴定高产绿豆基因型对未来的育种计划具有良好的前景,从粮食和营养安全的角度考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Screening of Elite Mungbean Genotypes (Vigna radiata (L.) Wilczek) through Multivariate Analysis for Food and Nutritional Security
The ever-increasing urbanization to accommodate the growing population reduces substantially the agricultural land but poses a threat to meeting the requirement of proper nutrition for human health. Mungbean [Vigna radiata (L.) Wilczek] is a unique gift bestowed by nature to mankind, which has the potency to make up the gap of protein shortage with an inexpensive cost, but due to its low level of production as well as productivity, which in a roundabout way influences the nutritional status of people resulting in malnutrition. Therefore, enhancement of the total area under mungbean cultivation is not permissible, and an increase in the total productivity per unit area is necessary. In this manner, screening and evaluation of improved genotypes for high yield are necessary to ensure food security. But at the same time seed yield being a complex character governed by several other contributing traits, selection for the characters proves to be quite challenging. As a prerequisite for any breeding program aimed at yield enhancement presence of significant genetic diversity in a given population is highly important. In the present investigation principal component analysis was performed and the results revealed two principal components contributing to the total variance in the population. While the PC1 was predominated by yield and its attributing traits, the PC2 was mainly comprised of growth-related traits. The hierarchical (UPGMA) cluster analysis using standardized data classified the fifty-two mungbean genotypes into 4 clusters, which showed 2 major, 1 minor and one outlier. Among them, cluster II is the most fascinating, as its individual had high seed yield plant–1 and related traits. The present work concluded that the identification of promising high-yielding mungbean genotypes through multivariate analysis has a good promise for future breeding programs with a view of food and nutritional security.
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