Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit

文献类型： 外文期刊

第一作者： Liu, Changhong

作者： Liu, Changhong;Chen, Wei;Zheng, Lei;Liu, Wei;Yang, Jianbo;Zheng, Lei

作者机构：

关键词： Multispectral imaging;Tomato fruit;Bioactive compounds;Non-destructive determination;Chemometric

期刊名称：FOOD CHEMISTRY （ 影响因子：7.514； 五年影响因子：7.516 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (Rp(2)) = 0.938 and 0.965, residual predictive deviation (RPD) = 4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading. (C) 2014 Elsevier Ltd. All rights reserved.

分类号： TS2`TS201.2

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