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Chung, Ill-Min,Kim, Jae-Kwang,Yarnes, Christopher T.,An, Yeon-Ju,Kwon, Chang,Kim, So-Yeon,Yang, Yu-Jin,Chi, Hee-Youn,Kim, Seung-Hyun American Chemical Society, Books and Journals Divi 2019 Journal of agricultural and food chemistry Vol.67 No.2
<P>The present study describes compound-specific δ<SUP>13</SUP>C and δ<SUP>15</SUP>N analyses of fatty acids and amino acids for improving the accurate authentication of organic milk (OM) against conventional milk (CM) collected in Korea. Most δ<SUP>13</SUP>C<SUB>fatty-acid</SUB> and δ<SUP>13</SUP>C<SUB>amino-acid</SUB> values were lower in OM than in CM (<I>P</I> < 0.05); however, most δ<SUP>15</SUP>N<SUB>amino-acid</SUB> values displayed weak discriminative power for OM authentication. Higher isotopic fractionation was observed in δ<SUP>13</SUP>C<SUB>fatty-acid</SUB> than in δ<SUP>13</SUP>C<SUB>amino-acid</SUB> and δ<SUP>15</SUP>N<SUB>amino-acid</SUB>, with fractionation trends differing with individual amino acids. In particular, δ<SUP>13</SUP>C<SUB>linoleic-acid</SUB> of −33.5‰ and δ<SUP>13</SUP>C<SUB>myristic-acid</SUB> of −28‰ were determined to be promising year-round threshold values for Korean OM authentication. The δ<SUP>13</SUP>C<SUB>bulk</SUB> was highly correlated with δ<SUP>13</SUP>C<SUB>Ala</SUB> (<I>r</I> = 0.92) and δ<SUP>13</SUP>C<SUB>oleic-acid,<I>trans</I></SUB> (<I>r</I> = 0.77), and strong positive correlations were observed between δ<SUP>13</SUP>C<SUB>Val</SUB> and δ<SUP>13</SUP>C<SUB>Ile</SUB> (<I>r</I> = 0.98) and between δ<SUP>15</SUP>N<SUB>Thr</SUB> and δ<SUP>15</SUP>N<SUB>Ser</SUB> (<I>r</I> = 0.90). Chemometric modeling for OM authentication produced a high quality model (<I>R</I><SUP>2</SUP><I>X</I> = 0.547, <I>R</I><SUP>2</SUP><I>Y</I> = 0.865, and <I>Q</I><SUP>2</SUP> = 0.689) with reliable chemical markers, notably δ<SUP>13</SUP>C<SUB>myristic-acid</SUB>, δ<SUP>13</SUP>C<SUB>linoleic-acid</SUB>, and δ<SUP>13</SUP>C<SUB>stearic-acid</SUB>. Furthermore, the models developed for seasonal separation in OM (<I>Q</I><SUP>2</SUP> = 0.954) and CM (<I>Q</I><SUP>2</SUP> = 0.791) were of good quality. Our findings, based on compound-specific isotope data, improve the reliability of OM authentication in cases where bulk stable isotope ratio analysis alone is insufficient. They also provide valuable insight into the control of fraudulent OM labeling in Korea, with potential application in other countries.</P> [FIG OMISSION]</BR>
Chung, Ill-Min,Kim, Jae-Kwang,An, Yeon-Ju,Kwon, Chang,Kim, So-Yeon,Yang, Yu-Jin,Yarnes, Christopher T.,Chi, Hee-Youn,Kim, Seung-Hyun Elsevier 2019 Food chemistry Vol.283 No.-
<P><B>Abstract</B></P> <P>Herein, we improve the procedure for organic rice authentication using compound-specific δ<SUP>13</SUP>C and δ<SUP>15</SUP>N analyses of fatty acids and amino acids, addressing the increasing demand for accurate methods to confirm organic authenticity. Organic rice (OR) and pesticide-free rice (PFR) featured higher values of δ<SUP>15</SUP>N<SUB>bulk</SUB> than conventional rice (CR), whereas the corresponding differences between OR and PFR were insignificant. Additionally, OR, PFR, and CR could be discriminated based on some δ<SUP>13</SUP>C<SUB>amino-acid</SUB> and δ<SUP>15</SUP>N<SUB>amino-acid</SUB> values. δ<SUP>13</SUP>C<SUB>bulk</SUB> was correlated with most δ<SUP>13</SUP>C<SUB>fatty-acid</SUB> (<I>r</I> ≥ 0.596) values, and δ<SUP>15</SUP>N<SUB>bulk</SUB> was strongly correlated with most δ<SUP>15</SUP>N<SUB>amino-acid</SUB> (<I>r</I> ≥ 0.834) values. The first component in the orthogonal projection to latent structure-discriminant analysis model allowed for a clear separation between OR and PFR, and good predictability (<I>Q</I> <SUP>2</SUP> <I>Y</I> = 0.506). Thus, the present study improves the reliability of organic authentication when bulk stable isotope ratio analysis alone is insufficient for the accurate discrimination of OR, PFR, and CR.</P> <P><B>Highlights</B></P> <P> <UL> <LI> This work focuses on the detection of incorrect or fraudulent organic rice labeling. </LI> <LI> Compound-specific isotope analysis was employed for organic rice authentication. </LI> <LI> Best results were achieved by OPLS-DA combined with δ<SUP>13</SUP>C/δ<SUP>15</SUP>N amino acid analysis. </LI> <LI> δ<SUP>13</SUP>C<SUB>lysine</SUB> was identified as the greatest contributor (VIP > 1) for all OPLS-DA models. </LI> </UL> </P>