Work

Prediction of fat content in edible insect powders using handheld FT-IR spectroscopic devices

Year: 2024

Type: article

Abstract: The present study describes a new approach to predict the level of crude fat present in commercial edible Tenebrio molitor and Alphitobius diaperinus powders partially defatted using mid and near infrared spectral data combined with multivariate analysis. Insect powders were partially defatted using three organic solvents and CO2 in supercritical conditions to obtain samples with fat content ranging from 0 to 28.7% (n=46). Lipid content and fatty acid profile were determined by using Soxhlet and fatty acid methyl esters (FAME) methods, respectively. Spectral data was acquired using two handheld FT-NIR devices (1350 to 2550 nm) and two pieces of portable FT-MIR equipment (4000–630 cm–1) equipped with ATR crystals. Partial least squares regression (PLSR) model was used to easily predict insect fat content. Ethanol had significantly lower lipid extraction yields, especially for T. molitor. Fatty acid (FA) composition was affected by the solvent used. PLSR results exhibited good linearity, predicting crude fat content with strong correlation (Rcv≥0.9) and low standard error of cross-validation (SECV=1.06-3.22). Nonetheless, the FT-NIR devices tested showed higher performance for fat content prediction in insect powders, reaching values of 0.99 in coefficient of correlation (RP) and 1.05% in standard error in prediction (SEP).

Source: LWT

DOI: 10.1016/j.lwt.2024.116652