Institute of Analytical Chemistry and Radiochemistry, University of Innsbruck, Innrain 80/82, 6020 Innsbruck, Austria.
Molecules. 2021 Oct 22;26(21):6390. doi: 10.3390/molecules26216390.
Future food supply will become increasingly dependent on edible material extracted from insects. The growing popularity of artisanal food products enhanced by insect proteins creates particular needs for establishing effective methods for quality control. This study focuses on developing rapid and efficient on-site quantitative analysis of protein content in handcrafted insect bars by miniaturized near-infrared (NIR) spectrometers. Benchtop (Büchi NIRFlex N-500) and three miniaturized (MicroNIR 1700 ES, Tellspec Enterprise Sensor and SCiO Sensor) in hyphenation to partial least squares regression (PLSR) and Gaussian process regression (GPR) calibration methods and data fusion concept were evaluated via test-set validation in performance of protein content analysis. These NIR spectrometers markedly differ by technical principles, operational characteristics and cost-effectiveness. In the non-destructive analysis of intact bars, the root mean square error of cross prediction (RMSEP) values were 0.611% (benchtop) and 0.545-0.659% (miniaturized) with PLSR, and 0.506% (benchtop) and 0.482-0.580% (miniaturized) with GPR calibration, while the analyzed total protein content was 19.3-23.0%. For milled samples, with PLSR the RMSEP values improved to 0.210% for benchtop spectrometer but remained in the inferior range of 0.525-0.571% for the miniaturized ones. GPR calibration improved the predictive performance of the miniaturized spectrometers, with RMSEP values of 0.230% (MicroNIR 1700 ES), 0.326% (Tellspec) and 0.338% (SCiO). Furthermore, Tellspec and SCiO sensors are consumer-oriented devices, and their combined use for enhanced performance remains a viable economical choice. With GPR calibration and test-set validation performed for fused (Tellspec + SCiO) data, the RMSEP values were improved to 0.517% (in the analysis of intact samples) and 0.295% (for milled samples).
未来的食物供应将越来越依赖于从昆虫中提取的可食用材料。昆虫蛋白增强的手工食品产品的日益普及,对建立有效的质量控制方法提出了特殊要求。本研究旨在通过微型近红外(NIR)光谱仪对手工昆虫棒的蛋白质含量进行快速有效的现场定量分析。台式(Büchi NIRFlex N-500)和三种微型(MicroNIR 1700 ES、Tellspec 企业传感器和 SCiO 传感器)通过偏最小二乘回归(PLSR)和高斯过程回归(GPR)校准方法和数据融合概念进行了评估,通过测试集验证评估了蛋白质含量分析的性能。这些 NIR 光谱仪在技术原理、操作特性和成本效益方面有显著差异。在对完整棒进行非破坏性分析时,PLSR 的 RMSEP 值分别为 0.611%(台式)和 0.545-0.659%(微型),GPR 校准的 RMSEP 值分别为 0.506%(台式)和 0.482-0.580%(微型),而分析的总蛋白质含量为 19.3-23.0%。对于研磨样品,PLSR 的 RMSEP 值提高到 0.210%,但微型的 RMSEP 值仍在 0.525-0.571%的较差范围内。GPR 校准提高了微型光谱仪的预测性能,RMSEP 值分别为 0.230%(MicroNIR 1700 ES)、0.326%(Tellspec)和 0.338%(SCiO)。此外,Tellspec 和 SCiO 传感器是面向消费者的设备,它们的组合使用对于提高性能仍然是一个可行的经济选择。对于融合(Tellspec+SCiO)数据进行 GPR 校准和测试集验证,RMSEP 值分别提高到 0.517%(分析完整样本)和 0.295%(分析研磨样本)。