Fatty acids-encoded orthogonal partial least squares classifier for authentication of organic beef

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Authors: Sherif Shaheen, Solenne BENARD, Nicholas Birse, Ruth M. Hamill, Raquel Cama‐Moncunill, Peter G. Dunne, Simona Grasso
Cited by: 1
References: 39

Abstract

Organic beef is a growing market segment due to its well-appreciated health and eco-compatible merits relative to conventional beef produced under mainstream systems. Verifying the authenticity of organic beef is essential to ensure compliance with production regulations and prevent fraudulent mislabeling; however, developing a robust authentication technique is challenging. Here we developed a chemically-informed orthogonal partial least squares classifier, encoding fatty acids (FA) information of intra-muscular fat, with potential for authentication of organic beef. The model successfully achieved a high discriminatory performance between organic and conventional beef (accuracy rates of 99% and 93% for cross and external validation, respectively). Levels of C18:3 n -3, followed by C20:3 n- 3 c 11,14,17, C18:2 n -6, and C22:2 n -6 c 13,16 were the chief discriminant FA that associated with the dietary background of cattle, particularly the amount of forage input. Additionally, levels of C18:2 c 9 t 11, C20:5 n -3 c 5,8,11,14,17, and C22:5 n -3 c 7,10,13,16,19 were significantly higher in organic beef. The approach can contribute to validation of provenance claims associated with organic beef.

Fields of Study & Subjects

Identification and Quantification in Food Spectroscopy and Chemometric Analyses Advanced Chemical Sensor Technologies

Publication details

Journal / source
Food Control
Publisher
Elsevier BV
Volume
190
Pages
112376–112376
Publication date
9 June 2026
Language
EN