Assessing agro-morphological variability in foxtail millet [Setaria italica (L.) Beauv.] genotypes using multivariate analysis
Description
The data set consists of averaged quantitative data taken from sample of population from three replications and fifteen treatments on the population. Different characters were recorded as per the descriptor established by IBPGR and UPOV. 10 random plants from each treatment in a row were taken for recording data of various characters. Averages of the data from the sampled plants were used for various statistical analyses. The analysis of these indicators allows us to identify the variation among accessions and identify traits which contribute to the variation and to group the accessions into different clusters and to identify potential parents for hybridization using Mahalanobis distance.
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The study was conducted at Agronomy Farm of the Institute of Agriculture and Animal Science (IAAS), Lamjung Campus, Lamjung district of Nepal fromMarch-July 2021. Lamjung Campus is located between 28° 7' North latitude and 84° 25' East longitude, with an altitude of 632 m above sea level and a sub-tropical climate. Total of 15 accessions of foxtail millet were collected from Ghanpokhara community seed bank, Ghanpokhara, Lamjung, and National Genetic Resource Centre, Khumaltar, Lalitpur, Nepal.Data entry and processing were done using Microsoft Excel 2016. For Principal Component Analysis and Cluster Analysis, R Studio 4.1.1 was used. ‘FactoMineR’ packages were used for Principal Component Analysis, Eigenvalues, Eigenvectors and creation of 2D biplots. Mahalanobis distance was calculated, and cluster analysis was completed by Tocher’s method as suggested by Vasconcelos et al. (2007) by using ‘biotools’ package.Mahalanobis' theory of generalized distance is based on multivariate analysis of quantitative features. It is employed to determine the degree of genetic divergence and to divide the genetic stock into various subgroups.