Future foods protection: Supervised chemometric approaches for the determination of adulterated insects’ flours for human consumption by means of ATR-FTIR spectroscopy

• Published in: Microchemical journal 2022-12, Vol.183, p.108021, Article 108021
• Main Authors: Foschi, Martina, D'Addario, Anna, Antonio D'Archivio, Angelo, Biancolillo, Alessandra
• Format: Article
• Language: English
• Subjects: Adulteration; ATR-FTIR; Classification; Edible insects; Insects’ flour; SIMCA
• ISSN: 0026-265X; 1095-9149
• DOI: 10.1016/j.microc.2022.108021

[Display omitted] •Pure and adulterated insect flours for human consumption were analyzed.•Pure flours were made of crickets (CF) or buffalo worms (BWF).•Analysis was conduced by ATR-FT-IR and samples classified by SPORT and SIMCA.•SPORT on CF provided 100% correct classification rate (on test set).•SIMCA on BWF provided 90% correct classification rate (on test set). In recent years, the possibility of reintroducing edible insects in the human diet in the areas where this habit had fallen in disuse has been revaluated. The reasons lie in the noticeable nutritional properties of some edible insects (generally rich in protein, vitamins, mineral elements, polyphenols and fatty acids) and their sustainable breeding which requires a moderate amount of water, and no peculiar exigencies. Consequently, insect-based snacks, insect flours, and derived products are currently spreading on the market all over the world. Although “future foods” have been a hot and debated topic in the last years, research has not kept pace with the times, and, in the literature, only a few studies on the characterization and the authentication of edible insects (and their derived products) have been published. In the light of this, the present work aims at developing a non-destructive infrared spectroscopy (IR)-based tool for detecting adulterations in insects’ flours for human consumption. Mixtures of cricket and buffalo worm flours, prepared to mimic adulterated samples, together with pure flours of the same insects, have been analysed by FT-IR spectroscopy. Eventually, classification tools for discriminating between pure and adulterated samples, i.e., Sequential Preprocessing through ORThogonalization Discriminant Analysis (SPORT-DA) and Soft Independent Modelling of Class Analogy (SIMCA), have been employed. Both discriminant and class-modelling approaches demonstrated to be suitable for the purpose. The highest correct classification rate on cricket flour was achieved by means of SPORT-DA, which correctly predicted 100% of test samples; whereas, the most accurate predictions on the buffalo worm flour data set were obtained using SIMCA, which allowed the erroneous classification of only three (over thirty) test objects.