| Literature DB >> 32622190 |
Shao-Yan Zheng1, Ze-Shun Wei2, Shuang Li2, Shi-Jia Zhang3, Chun-Fang Xie4, Dong-Sheng Yao5, Da-Ling Liu6.
Abstract
Aflatoxins (AFs) are potent carcinogens present in numerous crops. Access to accurate methods for evaluating contamination is a critical factor in aflatoxin risk assessment. Versicolorin A (Ver A), a precursor of aflatoxin B1 (AFB1), can be used as an indicator for the presence of AFB1, even when the AF is not yet detectable. Currently employed Ver A detection methods are expensive, time consuming, and difficult to apply to numerous samples. Herein, Ver A was detected via near-infrared spectroscopy. Both quantitative and two-grade sorting methods were set-up using the extreme gradient boosting algorithm coupled with a support vector machine. This two-tiered method obtained a root-mean-square error of prediction value of 3.57 μg/kg for the quantitative model, and an accuracy rate of 90.32% for the sorting approach. This novel method is rapid, accurate, solvent free, requires no sample pretreatment, and detects Ver A in maize, making it convenient for practical use.Entities:
Keywords: Aflatoxin monitoring; Near-infrared spectroscopy; Predictive modeling; Versicolorin A detection
Year: 2020 PMID: 32622190 DOI: 10.1016/j.foodchem.2020.127419
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514