Genetic identification of flax, chia and sesame seeds in processed foods. (December 2020)

• Record Type: Journal Article
• Authors: Bruno, María Cecilia; Posik, Diego Manuel; Zappa, María Eugenia; Baroni, Veronica; Wunderlin, Daniel; Giovambattista, Guillermo; García, Pilar Peral
• Is Part Of: Food control. Volume 118(2020)
• Publication Date: 2020-12
• Subjects: Chia -- Sesame -- Flax -- High-resolution melting analysis (HRM) -- Species identification -- Complex food matrix; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2020.107374
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Chia, sesame and flax seeds are becoming increasingly more frequent components of functional foods because of their proven health benefits. The identification of plant components in complex matrices is generally performed using DNA typing. This method is a fast and economic tool widely applied to assess the genetic origin and authenticity of products from the food supply chain. The aim of this study was to compare two DNA-based methods, quantitative polymerase chain reaction high-resolution melting (qPCR-HRM) and endpoint PCR, used to identify chia, flax and sesame seeds in laboratory-made and commercial products. For this purpose, an endpoint PCR and qPCR-HRM methods were developed. DNA was extracted from chia, sesame and flax seeds, laboratory-made and commercial products. The analysis of flax, chia and sesame melting profiles using HRM post-PCR analysis allowed the identification of chia, sesame and flax in processed foods. The results obtained showed that qPCR-HRM is a cost-effective and efficient method for the identification, authentication and/or detection of seeds in processed food and complex matrices containing chia, sesame and flax. Highlights: Two DNA-based methods to identify chia, flax and sesame species were conducted. An endpoint PCR and qPCR-HRM post-PCR analysis was developed and compared. Unspecific PCR product reduced the efficiency of endpoint PCR. The three species could be identified with qPCR-HRM. HRM was useful in different food matrices (seeds, laboratory-made and commercial products).