Institute of Sciences of Food Production (ISPA), CNR-National Research Council of Italy, Bari, Italy.
Department of Chemistry, University of Bari "Aldo Moro", Bari, Italy.
J Sci Food Agric. 2019 Mar 15;99(4):1946-1953. doi: 10.1002/jsfa.9392. Epub 2018 Nov 14.
Deoxynivalenol (DON) is the most common Fusarium mycotoxin occurring in wheat and wheat-derived products, with several adverse and toxic effects in animals and humans. Although bran fractions produced by milling wheat have numerous health benefits, cereal bran is the part of the grain with the highest concentration of DON, thus representing a risk for consumers. Increased efforts have been made to develop analytical methods suitable for rapid DON screening.
The applicability of Fourier transform near-infrared (FTNIR), or mid-infrared (FTMIR) spectroscopy, and their combination for rapid analysis of DON in wheat bran, was investigated for the classification of samples into compliant and non-compliant groups regarding the EU legal limit of 750 µg kg . Partial least squares-discriminant analysis (PLS-DA) and principal component-linear discriminant analysis (PC-LDA) were employed as classification techniques using a cutoff value of 400 µg kg DON to distinguish the two classes. Depending on the classification model, overall discrimination rates were from 87% to 91% for FTNIR and from 86% to 87% for the FTMIR spectral range. The FTNIR spectroscopy gave the highest overall classification rate of wheat bran samples, with no false compliant samples and 18% false noncompliant samples when the PC-LDA classification model was applied. The combination of the two spectral ranges did not provide a substantial improvement in classification results in comparison with FTNIR.
Fourier transform near-infrared spectroscopy in combination with classification models was an efficient tool to screen many DON-contaminated wheat bran samples and assess their compliance with EU regulations. © 2018 Society of Chemical Industry.
脱氧雪腐镰刀菌烯醇（DON）是最常见的小麦及小麦制品中出现的镰刀菌毒素，对动物和人类具有多种不良和毒性作用。虽然制粉过程中产生的麦麸具有许多健康益处，但麦麸是谷物中 DON 浓度最高的部分，因此对消费者构成了风险。人们已经做出了更多努力来开发适合快速 DON 筛选的分析方法。
研究了傅里叶变换近红外（FTNIR）或中红外（FTMIR）光谱及其组合在快速分析小麦麸中 DON 方面的适用性，以便将样品分类为符合和不符合欧盟 750μg/kg 法定限量的组。使用 DON 含量为 400μg/kg 的截止值，采用偏最小二乘判别分析（PLS-DA）和主成分线性判别分析（PC-LDA）作为分类技术，对近红外和中红外光谱范围进行分类。根据分类模型的不同，FTNIR 的总体判别率为 87%至 91%，FTMIR 的总体判别率为 86%至 87%。当应用 PC-LDA 分类模型时，FTNIR 光谱法对小麦麸样品的总体分类率最高，没有假合格样品，而假不合格样品为 18%。与 FTNIR 相比，两个光谱范围的组合并未在分类结果上提供实质性的改善。
傅里叶变换近红外光谱结合分类模型是筛选大量 DON 污染的小麦麸样品并评估其是否符合欧盟法规的有效工具。© 2018 化学工业协会。
