Rapid and nondestructive quantification of deoxynivalenol in individual wheat kernels using near-infrared hyperspectral imaging and chemometrics
Rapid and nondestructive quantification of deoxynivalenol in individual wheat kernels using near-infrared hyperspectral imaging and chemometrics
复制标题
使用近红外高光谱成像和化学计量学快速、无损地定量单个小麦籽粒中的脱氧雪腐镰刀菌烯醇
DOI：
10.1016/j.foodcont.2021.108420
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发表时间：
2022
期刊：
影响因子：
6
通讯作者：
Yin-Won Lee
中科院分区：
文献类型：
--
作者：
Guanghui Shen;Yaoyao Cao;Xianchao Yin;Fei Dong;Jianhong Xu;Jianrong Shi;Yin-Won Lee
本研究旨在探讨近红外高光谱成像技术（NIR-HSI）和化学计量学技术定量测定小麦籽粒中脱氧雪腐镰刀菌烯醇（DON）含量的可行性。采用HPLC-MS/MS分析了严重受损、中度受损和无症状小麦籽粒（分别为SDKs、MDKs和AKs）共120粒的DON含量，并采用偏最小二乘（PLS）、支持向量机（SVM）和基于全局PLS得分的局部PLS（LPLS-S）算法建立了DON定量模型。结果表明，SDKs和MDKs可能含有低或不含DON，而AKs可能具有高DON含量。比较3种建模策略，LPLS-S混合光谱法对玉米籽粒的建模效果最好，RMSEP为40.25 mg/kg，RPD为2.24，表明近红外-高分辨率光谱法可用于玉米籽粒中DON的监测，并可在进入食物链前去除高污染玉米籽粒。
The present study aimed to evaluate the feasibility of using near-infrared hyperspectral imaging (NIR-HSI) and chemometrics for quantifying deoxynivalenol (DON) in individual wheat kernels. In total, 120 wheat kernels of severely damaged kernels, moderately damaged kernels and asymptomatic kernels (SDKs, MDKs and AKs, respectively) were collected, and the DON content in the individual wheat kernels was analyzed by HPLC-MS/MS. Partial least squares (PLS), support vector machine (SVM) and local PLS based on global PLS scores (LPLS-S) algorithms were employed for building quantification models of DON. The results showed that SDKs and MDKs might contain low or no DON, while AKs could have a high DON content. Comparing the three modeling strategies, LPLS-S using mixed spectra achieved the best performance for kernels withRMSEPof 40.25 mg/kg andRPDof 2.24, which confirmed that NIR-HSI could be a feasible method for monitoring DON in individual kernels and removing highly contaminated kernels prior to food chain entry.
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