Compound-specific δ13C and δ15N analyses of fatty acids and amino acids for discrimination of organic, pesticide-free, and conventional rice (Oryza sativa L.)

• Published in: Food chemistry 2019-06, Vol.283, p.305-314
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: Chemometric model; Compound-specific isotope analysis; Conventional rice; Organic rice; Pesticide-free rice
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2018.12.129

•This work focuses on the detection of incorrect or fraudulent organic rice labeling.•Compound-specific isotope analysis was employed for organic rice authentication.•Best results were achieved by OPLS-DA combined with δ13C/δ15N amino acid analysis.•δ13Clysine was identified as the greatest contributor (VIP > 1) for all OPLS-DA models. Herein, we improve the procedure for organic rice authentication using compound-specific δ13C and δ15N 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 δ15Nbulk 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 δ13Camino-acid and δ15Namino-acid values. δ13Cbulk was correlated with most δ13Cfatty-acid (r ≥ 0.596) values, and δ15Nbulk was strongly correlated with most δ15Namino-acid (r ≥ 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 (Q2Y = 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.