Assessing Genetic Diversity in Bread Wheat (Triticum aestivum L.) using D2 Statistical Analysis

B. A. Yasin, S. Shubhra, Misbahu Abdu, Garome Shiferaw, Dula Teshome, Gada Gudina, Legessu Girshe, Tesfaye Dugasa
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Abstract

Background: Genetic diversity is one of the potent components used to develop improved cultivars with a broad genetic base and wider adaptability. Genetic diversity between two parents of diverse origin generally displays greater heterosis and yields transgressive segregants. Therefore, knowledge of genetic diversity is the prerequisite for the genetic improvement of crop plants including wheat. D2 statistical analysis is one of the potent biometrical techniques used for the assessment of genetic diversity. Methods: The essence of the current experiment involved 40 providential bread wheat lines that were arranged and laid down in a randomized block design (RBD) with three replications at the experimental research farm of Suresh Gyan Vihar University, Jagatpura, Jaipur, during the rabi crop season (2020-21). The bread wheat lines of the same geographical range were assessed to determine the genetic diversity using D2 statistical analysis and heritability estimate in apropos to ten quantitative/qualitative characters. Result: Based on D2 analysis, the 40 promising wheat strains were lined up into ten different clusters to estimate the average distance at intra and inter-cluster levels. The uttermost intra-cluster distance was recorded in cluster X, whereas, the appreciative inter-cluster distance pertained among cluster-VI and cluster-X pursued by cluster-IX and cluster-X. Entrenched to the mean or average performance, most of the bread wheat lines were spotted to disclose appreciable distinctions concerning to their cluster means. It was perceived that the maximum percent contribution towards total divergence was exhibited by grain yield plant-1, followed by spike length, effective tiller plant-1, 1000 grain weight and plant height. Moreover, the number of effective tillers plant-1, spike length, harvest index ,1000 grain weight, number of grains spike-1 and protein content were quite substantial since these traits exhibit high heritability estimate together with high genetic advance as percent of mean.
利用 D2 统计分析评估面包小麦(Triticum aestivum L. )的遗传多样性
背景:遗传多样性是用于培育具有广泛遗传基础和更强适应性的改良栽培品种的有力因素之一。来源不同的两个亲本之间的遗传多样性通常会表现出更大的异质性,并产生转基因分离株。因此,了解遗传多样性是包括小麦在内的农作物遗传改良的先决条件。D2 统计分析是用于评估遗传多样性的有效生物计量学技术之一。方法:本次实验的主要内容是在斋浦尔 Jagatpura 的 Suresh Gyan Vihar 大学的实验研究农场,于 2020-21 年小麦蕾季期间,以随机区组设计(RBD)的方式安排和布置了 40 个具有三个重复的天赐面包小麦品系。利用 D2 统计分析和遗传率估算,对同一地理范围内的面包小麦品系进行了评估,以确定十个定量/定性特征的遗传多样性。结果根据 D2 分析,将 40 个有潜力的小麦品系分成 10 个不同的聚类,以估算聚类内部和聚类之间的平均距离。簇内距离最大的是簇 X,而簇间距离最大的是簇 VI 和簇 X,其次是簇 IX 和簇 X。根据平均值或平均表现,大多数面包小麦品系的聚类平均值都有明显差异。结果表明,对总差异贡献最大的是植株-1 谷粒产量,其次是穗长、植株-1 有效分蘖数、千粒重和株高。此外,有效分蘖株数-1、穗长、收获指数、千粒重、穗粒数-1 和蛋白质含量也相当可观,因为这些性状表现出较高的遗传力估计值和较高的遗传进展(占平均值的百分比)。
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