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      <ref-type name="Journal Article">17</ref-type>
      <contributors>
        <authors>
          <author>H. S. Park</author>
          <author>K. C. Choi</author>
          <author>J. H. Kim</author>
          <author>M. J. So</author>
          <author>S.-H. Lee</author>
          <author>K.-W. Lee</author>
        </authors>
      </contributors>
      <titles>
        <title>DISCRIMINATION AND QUANTIFICATION BETWEEN ANNUAL RYEGRASS AND PERENNIAL RYEGRASS SEEDS BY NEAR-INFRARED SPECTROSCOPY</title>
        <secondary-title>Journal of Animal and Plant Sciences</secondary-title>
        <alt-title>JAPS</alt-title>
      </titles>
      <dates><year>2016</year><pub-dates><date>2016/10/01</date></pub-dates></dates>
      <volume>26</volume>
      <number>5</number>
      <pages>1278-1283</pages>
      <isbn>1018-7081</isbn>
      <electronic-resource-num>NA</electronic-resource-num>
      <abstract>&lt;p&gt;Contamination of annual ryegrass with perennial ryegrassby physical seed mixing or gene flow can result in a significant reduction in forage production.Therefore, this study aimed to develop a suitable technique using near-infrared spectroscopy (NIRS) for discriminating and quantifying adulteration of annual ryegrass seeds with perennial ryegrass. A partial least squares regression for discriminating analysis using visible and NIR region was developed using a calibration set(n=120), including 60 samples each of pure annual ryegrass seeds and those contaminated with perennial ryegrass at levels ranging from 10 to 990 g/kg. An independent validation set, consisting of 40 pure samples and 39 adulterated samples, was used to validate the calibration model.In all, 105 samples were used to develop the quantitative analysis model; with each sample subsequently spiked (10&amp;ndash;990 g/kg; standard deviation: 294.2 g/kg). A discriminant analysis model developed with mathematic pretreatment 1,4,4,1 in NIR region (1100&amp;ndash;2500 nm) successfully discriminated annual ryegrass adulterated with perennial ryegrass seed. A quantitative model developed with mathematic pretreatment 1,4,4,1 in NIR region (1100&amp;ndash;2500 nm)also accurately predicted the adulteration with a standard error of cross validation of 76.91 g/kg and a ratio of performance deviationof 3.82. These results demonstrate the usefulness of NIRS combined with chemometrics as a rapid method for discrimination and quantification of perennial ryegrass in adulterated annual ryegrass seedsamples.&lt;/p&gt;</abstract>
      <keywords><keyword>Near-infrared Spectroscopy, Quantitative, Annual Ryegrass, Perennial Ryegrass, Seed</keyword></keywords>
      <publisher>Pakistan Agricultural Scientists Forum</publisher>
      <urls><related-urls><url>https://thejaps.org.pk/AbstractView.aspx?mid=2016-JAPS-167</url></related-urls></urls>
    </record>
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