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        <dc:title>Phenotypic correlation, path coefficient and multivariate analysis for yield and yield-associated traits in groundnut accessions</dc:title>
        <dc:creator>Mubai, N</dc:creator>
        <dc:creator>Sibiya, J</dc:creator>
        <dc:creator>Mwololo, J</dc:creator>
        <dc:creator>Musvosvi, C</dc:creator>
        <dc:creator>Charlie, H</dc:creator>
        <dc:creator>Munthali, W</dc:creator>
        <dc:creator>Kachulu, L</dc:creator>
        <dc:creator>Okori, P</dc:creator>
        <dc:creator>Tejada Moral, M</dc:creator>
        <dc:subject>Crop Yield</dc:subject>
        <dc:subject>Groundnut</dc:subject>
        <dc:subject>Genetics and Genomics</dc:subject>
        <dc:description>Yield is a complex quantitative trait largely influenced by the environment.&#13;
Direct selection for grain yield is less efficient in improving groundnut productivity.&#13;
The selection efficiency can be enhanced by exploiting the relationship&#13;
between yield and its related traits. Moreover, the use of genetically diverse parents&#13;
is essential to generate genetic variation for successful selection of genotypes in&#13;
a breeding program. Therefore, the study aimed at analysing the relationship&#13;
between grain yield and its related traits and determining the morphological&#13;
diversity among selected groundnut genotypes under natural rosette disease (GRD)&#13;
infestation. The genotypes were evaluated in a 7 × 4 alpha lattice design with three&#13;
replications. Data were collected on yield and yield-related traits. Correlation, path&#13;
coefficient and multivariate analyses were done. The results revealed that yield was&#13;
directly associated with plant height, number of pods per plant, hundred seed&#13;
weight, GRD incidence and number of secondary branches. Therefore, these traits&#13;
should be considered in selection when improving groundnut for yield. Cluster&#13;
analysis revealed existence of diversity among the evaluated groundnut genotypes with no influence of geographical origin to the clustering pattern. The Principal&#13;
Components Analysis (PCA) biplot was effective in showing the genetic distance&#13;
among the genotypes and the results were comparable with those of the cluster&#13;
analysis. Moreover, Shannon-Weaver diversity indices revealed existence of high&#13;
diversity among the genotypes, an implication that groundnut improvement for&#13;
yield is possible through selection in breeding.</dc:description>
        <dc:publisher>Cogent OA</dc:publisher>
        <dc:date>2020-10</dc:date>
        <dc:type>Article</dc:type>
        <dc:type>PeerReviewed</dc:type>
        <dc:format>application/pdf</dc:format>
        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/11682/1/23311932.2020.pdf</dc:identifier>
        <dc:identifier>  Mubai, N and Sibiya, J and Mwololo, J and Musvosvi, C and Charlie, H and Munthali, W and Kachulu, L and Okori, P and Tejada Moral, M  (2020) Phenotypic correlation, path coefficient and multivariate analysis for yield and yield-associated traits in groundnut accessions.  Cogent Food &amp; Agriculture, 6 (1).  pp. 1-22.  ISSN 2331-1932     </dc:identifier>
        <dc:relation>https://doi.org/10.1080/23311932.2020.1823591</dc:relation>
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