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    <titleInfo>
      <title>Development of a rapid and efficient DNA-based method to detect and quantify adulterations in coffee</title>
    </titleInfo>
    <name type="personnal">
      <namePart type="family">Combes</namePart>
      <namePart type="given">Marie-Christine</namePart>
      <role>
        <roleTerm type="text">auteur</roleTerm>
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      <affiliation>IRD</affiliation>
    </name>
    <name type="personnal">
      <namePart type="family">Joët</namePart>
      <namePart type="given">Thierry</namePart>
      <role>
        <roleTerm type="text">auteur</roleTerm>
        <roleTerm type="code" authority="marcrelator">aut</roleTerm>
      </role>
      <affiliation>IRD</affiliation>
    </name>
    <name type="personnal">
      <namePart type="family">Lashermes</namePart>
      <namePart type="given">Philippe</namePart>
      <role>
        <roleTerm type="text">auteur</roleTerm>
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    <abstract>Worldwide appreciated beverage, "Arabica" and "Robusta" coffee produced from Coffea arabica and C. canephora respectively, represents a high economical value product. Arabica coffee is generally sold at a higher price than Robusta coffee. As both intentional and accidental adulterations of Arabica with Robusta are frequent, a reliable, inexpensive, and high-throughput adulteration detection technology is required for the coffee industry. We developed a DNA-based authentication method that overcomes limitations of metabolic profiling of Robusta and Arabica coffees. The identification of Arabica and Robusta coffee species, as well as the quantification of their relative proportion in blends were performed by High Resolution Melting (HRM) analysis on green and roasted coffee products. For a more sensitive detection method, chloroplastic rather than nuclear genetic variations were targeted between Coffea species. By the developed method, the Coffea species of origin can be quickly differentiated and in case of adulteration, the percentage can be determined.</abstract>
    <targetAudience authority="marctarget">specialized</targetAudience>
    <subject authority="local">
      <geographic>FRANCE</geographic>
      <geographic>CAMEROUN</geographic>
      <geographic>VIET NAM</geographic>
      <geographic>INDE</geographic>
      <geographic>BRESIL</geographic>
      <geographic>GUATEMALA</geographic>
    </subject>
    <classification authority="local">076</classification>
    <relatedItem type="host">
      <titleInfo>
        <title>Food Control</title>
      </titleInfo>
      <part>
        <detail type="volume">
          <number>88</number>
        </detail>
        <extent unit="pages">
          <list> 198-206</list>
        </extent>
      </part>
      <originInfo>
        <dateIssued>2018</dateIssued>
      </originInfo>
      <identifier type="issn">0956-7135</identifier>
    </relatedItem>
    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010071469</identifier>
    <identifier type="doi">10.1016/j.foodcont.2018.01.014</identifier>
    <identifier type="issn">0956-7135</identifier>
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      <url usage="primary display" access="object in context">https://www.documentation.ird.fr/hor/fdi:010071469</url>
      <url access="row object">https://www.documentation.ird.fr/intranet/publi/depot/2018-03-07/010071469.pdf</url>
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      <recordContentSource>IRD - Base Horizon / Pleins textes</recordContentSource>
      <recordCreationDate encoding="w3cdtf">2018-03-07</recordCreationDate>
      <recordChangeDate encoding="w3cdtf">2023-07-11</recordChangeDate>
      <recordIdentifier>fdi:010071469</recordIdentifier>
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        <languageTerm authority="iso639-2b">fre</languageTerm>
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