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        <dc:title>Analysis and Evaluation of Quality Traits of Peanut Varieties with Near&#13;
Infra-red Spectroscopy Technology</dc:title>
        <dc:creator>Liu, H</dc:creator>
        <dc:creator>Pandey, M K</dc:creator>
        <dc:creator>Xu, Z</dc:creator>
        <dc:creator>Rao, D</dc:creator>
        <dc:creator>Huang, Z</dc:creator>
        <dc:creator>Chen, M</dc:creator>
        <dc:creator>Feng, D</dc:creator>
        <dc:creator>Varshney, R K</dc:creator>
        <dc:creator>Hong, Y</dc:creator>
        <dc:subject>Groundnut</dc:subject>
        <dc:description>Peanut kernel and oil quality are the important features which decide the market value of the produce. In order to identify better&#13;
source with good kernel and oil quality for use in breeding program, 21 quality traits of 100 peanut varieties were phenotyped&#13;
under national official field tests in South China. Some of these traits included were contents of crude fat, protein, fatty acids&#13;
and amino acids using near infra-red spectroscopy technology. The average contents of crude fat, protein, amino acids, oleic and&#13;
linoleic in these varieties were found to be 51.37%, 26.31%, 22.611%, 44.84% and 34.05%, respectively. The principal&#13;
component analysis (PCA) identified three component factors representing 74% variation with the clear-cut grouping of 21&#13;
quality traits into these component factors i.e., protein and amino acid (PC1), unsaturated fatty acid (PC2) and crude fat (PC3).&#13;
Furthermore, the cluster analysis divided these 100 peanut varieties into 4 groups with some differences in the quality traits&#13;
between groups. It is an effective way to comprehensively evaluate the peanut quality by principal component analysis and&#13;
cluster analysis, which could not only avoid the bias and the instability of single factor analysis, but also explore a practical&#13;
distinction way for the peanut quality analysis and the quality breeding.</dc:description>
        <dc:date>2019</dc:date>
        <dc:type>Article</dc:type>
        <dc:type>PeerReviewed</dc:type>
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        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/11308/1/887e867601a56cbb1cce7192250d657d569a.pdf</dc:identifier>
        <dc:identifier>  Liu, H and Pandey, M K and Xu, Z and Rao, D and Huang, Z and Chen, M and Feng, D and Varshney, R K and Hong, Y  (2019) Analysis and Evaluation of Quality Traits of Peanut Varieties with Near Infra-red Spectroscopy Technology.  International Journal of Agriculture and Biology.  pp. 1-8.  ISSN 1814–9596    (In Press)  </dc:identifier>
        <dc:relation>10.17957/IJAB/15.0920</dc:relation></oai_dc:dc>
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