<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2d1 20170631//EN" "JATS-journalpublishing1.dtd">
      <JournalTitle>Journal of Agriculture Research and Technology</JournalTitle>
      <Volume-Issue>47 (2)</Volume-Issue>
      <ArticleType>Agricultural Engineering</ArticleType>
      <ArticleTitle>Delineating the Genetic Diversity in Oat Genotypes through Multivariate Analysis for Utilization in Breeding Program</ArticleTitle>
          <FirstName>Rukoo Chawla1 D. S. Phogat</FirstName>
          <FirstName>Surina Bhadu and Atman</FirstName>
      <Abstract>Oat (Avena sativa L.) is an important multi-purpose crop, cultivated for fodder, feed and grain purpose. Earlier oat was used for forage purpose but now with increasing health related issues as well as food security under changing climatic conditions; this crop has been emerged as sustainable dual purpose crop. Oat has emerged as a beneficial grain cereal for human consumption. Generally diverse individuals are likely to produce more heterotic effects during the crossing programme and desirable segregants are also produced. Therefore, in this present research, a total of 56 genotypes were evaluated for sixteen yield and yield contributing traits. K-means clustering and principal component analysis was done using R studio software. From clustering the genotypes were grouped in 4 cluster. Out of which cluster 1 and cluster 3 were most diverse. Highest cluster mean value for maximum traits was observed for cluster 3 as well. Principal component analysis showed that PF-1 and PF-2 was regarded as most important for yield factors. It was seen that PF-1 was loaded on seed yield, axis length and days to 50% flowering while PF-2 on green fodder yield, dry matter yield and plant height. Biplot depicted that variation in traits dry matter yield, green fodder yield, days to 50% flowering, seed yield and plant height was contributed by both principal component. Genotypes selected from diverse clusters can be incorporated in hybridization crop improvement programme.</Abstract>
      <Keywords>Cluster analysis, oat, PCA analysis, grain, fodder.</Keywords>
        <Abstract>https://jart.co.in/ubijournal-v1copy/journals/abstract.php?article_id=14458&amp;title=Delineating the Genetic Diversity in Oat Genotypes through Multivariate Analysis for Utilization in Breeding Program</Abstract>