Analysis of the Composition of Different Instars of Tenebrio molitor Larvae using Near-Infrared Reflectance Spectroscopy for Prediction of Amino and Fatty Acid Content

Simple Summary Insects are receiving increasing attention as an important protein source that is being proposed as an alternative to fish and soy meal in livestock feed. The aim of this study was to analyze the composition of mealworm larvae at different stages of larval instar using a spectroscopic method for the prediction of the amino and fatty acid content and to search for the optimal harvesting time. Water, protein and fat content, in particular, as well as the amino acid and fatty acid composition were the focus of these investigations. The results of this research revealed that the composition of the different larval instars varies greatly. Moisture and protein content decreased in line with the developmental stages, and their minimum content was recorded in the last instar. By contrast, fat content was lowest in the first instars and increased with larval development. There is a reduction in growth in later instars, meaning that an earlier instar stage is favorable for harvesting. It was possible to predict the amino acid and fatty acid content of mealworm larvae with high accuracy. This can help insect producers to detect the nutrient composition of the larvae easily and quickly so that they can modify larval composition with regard to the amino and fatty acid content to improve the rearing conditions in terms of feeding, while ensuring a stable product quality. Abstract Insects are a sustainable protein source for food and feed. The yellow mealworm (Tenebrio molitor L.) is a promising candidate for industrial insect rearing and was the focus of this study. This research revealed the diversity of Tenebrio molitor larvae in the varying larval instars in terms of the nutritional content. We hypothesized that water and protein are highest in the earlier instar, while fat content is very low but increases with larval development. Consequently, an earlier instar would be a good choice for harvest, since proteins and amino acids content decrease with larval development. Near-infrared reflectance spectroscopy (NIRS) was represented in this research as a tool for predicting the amino and fatty acid composition of mealworm larvae. Samples were scanned with a near-infrared spectrometer using wavelengths from 1100 to 2100 nm. The calibration for the prediction was developed with modified partial least squares (PLS) as the regression method. The coefficient for determining calibration (R2C) and prediction (R2P) were >0.82 and >0.86, with RPD values of >2.20 for 10 amino acids, resulting in a high prediction accuracy. The PLS models for glutamic acid, leucine, lysine and valine have to be improved. The prediction of six fatty acids was also possible with the coefficient of the determination of calibration (R2C) and prediction (R2P) > 0.77 and >0.66 with RPD values > 1.73. Only the prediction accuracy of palmitic acid was very weak, which was probably due to the narrow variation range. NIRS could help insect producers to analyze the nutritional composition of Tenebrio molitor larvae fast and easily in order to improve the larval feeding and composition for industrial mass rearing.