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Rapid and nondestructive determination of deoxynivalenol (DON) content in wheat using multispectral imaging (MSI) technology with chemometric methods.
Analytical Methods ( IF 2.7 ) Pub Date : 2020-06-07 , DOI: 10.1039/d0ay00859a Yule Shi 1 , Wei Liu 2 , Pengguang Zhao 1 , Changhong Liu 1 , Lei Zheng 1, 3
Analytical Methods ( IF 2.7 ) Pub Date : 2020-06-07 , DOI: 10.1039/d0ay00859a Yule Shi 1 , Wei Liu 2 , Pengguang Zhao 1 , Changhong Liu 1 , Lei Zheng 1, 3
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Wheat is susceptible to contamination by deoxynivalenol (DON) which is regarded as a class III carcinogen. In this paper, a rapid and nondestructive method for DON content determination and contamination degree discrimination in wheat was developed by using a multispectral imaging (405–970 nm) system. Genetic algorithm (GA) and principal component analysis (PCA), as preprocessing methods, were used to obtain the best spectral characteristics. The determination model was established by combining preprocessing methods and chemometric methods including partial least squares (PLS), support vector machines (SVM) and back propagation neural network (BPNN). The best quantitative determination result was obtained based on GA-SVM with a correlation coefficient of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) of 0.9988, 365.3 μg kg−1 and 8.6, respectively. Furthermore, the accuracy of contamination degree classification was up to 94.29% in the prediction set by using the PCA-PLS model. The results showed that the combination of multispectral imaging technology and chemometrics was an effective and nondestructive method for the determination of DON in wheat.
中文翻译：
使用化学计量学的多光谱成像（MSI）技术快速，无损地测定小麦中的脱氧雪腐烯醇（DON）含量。
小麦易受被认为是III类致癌物的脱氧雪腐烯（DON）污染。在本文中，通过使用多光谱成像（405-970 nm）系统开发了一种快速无损测定小麦中DON含量和污染程度的方法。遗传算法（GA）和主成分分析（PCA）作为预处理方法，用于获得最佳光谱特性。通过结合预处理方法和化学计量学方法（包括偏最小二乘（PLS），支持向量机（SVM）和反向传播神经网络（BPNN））建立测定模型。基于GA-SVM和预测相关系数（R p），预测均方根误差（RMSEP）和残余预测偏差（RPD）分别为0.9988、365.3μgkg -1和8.6。此外，在使用PCA-PLS模型的预测集中，污染度分类的准确性高达94.29％。结果表明，多光谱成像技术与化学计量学相结合是测定小麦中DON的有效且无损的方法。
更新日期：2020-07-09
中文翻译：
使用化学计量学的多光谱成像（MSI）技术快速，无损地测定小麦中的脱氧雪腐烯醇（DON）含量。
小麦易受被认为是III类致癌物的脱氧雪腐烯（DON）污染。在本文中，通过使用多光谱成像（405-970 nm）系统开发了一种快速无损测定小麦中DON含量和污染程度的方法。遗传算法（GA）和主成分分析（PCA）作为预处理方法，用于获得最佳光谱特性。通过结合预处理方法和化学计量学方法（包括偏最小二乘（PLS），支持向量机（SVM）和反向传播神经网络（BPNN））建立测定模型。基于GA-SVM和预测相关系数（R p），预测均方根误差（RMSEP）和残余预测偏差（RPD）分别为0.9988、365.3μgkg -1和8.6。此外，在使用PCA-PLS模型的预测集中，污染度分类的准确性高达94.29％。结果表明，多光谱成像技术与化学计量学相结合是测定小麦中DON的有效且无损的方法。
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