Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane, QLD 4072, Australia.
Fight Food Waste Cooperative Research Centre, Wine Innovation Central Building Level 1, Waite Campus, Urrbrae, SA 5064, Australia.
Sensors (Basel). 2023 Aug 4;23(15):6946. doi: 10.3390/s23156946.
The use of black soldier fly larvae (BSFL) grown on different organic waste streams as a source of feed ingredient is becoming very popular in several regions across the globe. However, information about the easy-to-use methods to monitor the safety of BSFL is a major step limiting the commercialization of this source of protein. This study investigated the ability of near infrared (NIR) spectroscopy combined with chemometrics to predict yeast and mould counts (YMC) in the feed, larvae, and the residual frass. Partial least squares (PLS) regression was employed to predict the YMC in the feed, frass, and BSFL samples analyzed using NIR spectroscopy. The coefficient of determination in cross validation (R) and the standard error in cross validation (SECV) obtained for the prediction of YMC for feed were (Rcv: 0.98 and SECV: 0.20), frass (Rcv: 0.81 and SECV: 0.90), larvae (Rcv: 0.91 and SECV: 0.27), and the combined set (Rcv: 0.74 and SECV: 0.82). However, the standard error of prediction (SEP) was considered moderate (range from 0.45 to 1.03). This study suggested that NIR spectroscopy could be utilized in commercial BSFL production facilities to monitor YMC in the feed and assist in the selection of suitable processing methods and control systems for either feed or larvae quality control.
利用在不同有机废物流中生长的黑水虻幼虫（BSFL）作为饲料成分的来源，在全球多个地区变得非常流行。然而，关于监测 BSFL 安全性的易用方法的信息是限制这种蛋白质来源商业化的主要步骤。本研究调查了近红外（NIR）光谱结合化学计量学预测饲料、幼虫和残余粪便中酵母和霉菌计数（YMC）的能力。偏最小二乘（PLS）回归用于预测使用 NIR 光谱分析的饲料、粪便和 BSFL 样品中的 YMC。预测饲料中 YMC 的交叉验证系数（Rcv）和交叉验证标准误差（SECV）分别为（Rcv：0.98 和 SECV：0.20）、粪便（Rcv：0.81 和 SECV：0.90）、幼虫（Rcv：0.91 和 SECV：0.27）和组合集（Rcv：0.74 和 SECV：0.82）。然而，预测标准误差（SEP）被认为是中等的（范围从 0.45 到 1.03）。本研究表明，NIR 光谱可以在商业 BSFL 生产设施中用于监测饲料中的 YMC，并有助于选择合适的加工方法和控制系统，以控制饲料或幼虫的质量。
