Rapid discrimination and classification of edible insect powders using ATR-FTIR spectroscopy combined with multivariate analysis

Abstract

Insects are being proposed as an alternative way to ensure world’s food and feed security. Methods to determine edible insect powder’s origin and species will be needed for quality control purposes. Infrared spectroscopy has been extensively used in rapid chemical fingerprinting of food products. The present research explores a new approach to discriminate and classify commercial edible insect powders using attenuated total reflectance mid-infrared spectroscopy combined with multivariate analysis. Infrared spectra of seven commercial edible insect powders from different species (Tenebrio molitor, Alphitobius diaperinus, Gryllodes sigillatus, Acheta domesticus andLocusta migratoria) and origins (the Netherlands and New Zealand) were collected to build up soft independent modelling of class analogy (SIMCA) models. SIMCA models clearly discriminated insects by their species and origin linking their differences to lipids and chitin. SIMCA models performance was tested using five spectra of each class not used to build up the training set. 100% correct predictions were obtained for all the samples analysed with the exception of one sample ofAlphitobius diaperinus. Infrared spectroscopy coupled to multivariate analysis provided a powerful method for the assurance of insect powder’s authenticity.