Proteomics based approach for edible insect fingerprinting in novel food: Differential efficiency according to selected model species. (June 2020)

• Record Type: Journal Article
• Authors: Francis, F.; Mazzucchelli, G.; Baiwir, D.; Debode, F.; Berben, G.; Caparros Megido, R.
• Is Part Of: Food control. Volume 112(2020)
• Publication Date: 2020-06
• Subjects: Proteomics -- Edible insect -- Food control; 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.2020.107135
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: For insect-based formulations, food analysis is essential to ensure authenticity. According to the spread of the real-time-polymerase chain reaction technique, it started to be tested for entomological occurrence in food with limited success according to the insect species to be detected. Mass spectrometry-based proteomic methods are increasingly being used for the specific detection of trace amounts in food products. Here, we focused on the potential use of proteomic analyses to detect four edible insect species namely Tenebrio molitor, Hermetia illucens, Alphitobius diaperinus and Gryllus assimilis in insect commercial flours. Reproducible results were obtained from liquid chromatography-mass spectrometry with heterogenous efficiency rates on insect identification according to the target species. Indeed, Tenebrio molitor and Gryllus assimilis were identified at species and genus level respectively whereas no efficient results at these taxonomic levels could be found for Hermetia illucens . Future applications of proteomics for edible insect detection in food are discussed in relation to available data and model. Graphical abstract: Image 1 Highlights: Growing need in insect identification techniques in food and feed. Proteomics application was performed on four whole and insect flours. Replicable LC-MS analysis achievement with heterogenous rates of identification. Tenebrio molitor and Gryllus assimilis identification at species and genus level. No efficient identification on Hermetia illucens.