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RAPID DISCRIMINATION OF HIGH-QUALITY WATERMELON SEEDS BY MULTISPECTRAL IMAGING COMBINED WITH CHEMOMETRIC METHODS

文献类型： 外文期刊

作者： Liu, Wei 1 ; Xu, Xue 3 ; Liu, Changhong 1 ; Zheng, Lei 1 ;

作者机构： 1.Hefei Univ Technol, Sch Food Sci & Engn, Hefei 230009, Anhui, Peoples R China

2.Hefei Univ, Intelligent Control & Compute Vis Lab, Hefei 230601, Anhui, Peoples R China

3.Anhui Acad Agr Sci, Rice Res Inst, Hefei 230031, Anhui, Peoples R China

关键词： watermelon seeds; multispectral imaging; nondestructive

期刊名称：JOURNAL OF APPLIED SPECTROSCOPY （ 影响因子：0.741； 五年影响因子：0.718 ）

ISSN： 0021-9037

年卷期： 2019 年 85 卷 6 期

页码：

收录情况： SCI

摘要： This study focuses on the feasibility of nondestructive discrimination of high-quality watermelon seeds with a multispectral imaging system combined with chemometrics. Principal component analysis (PCA), least squares-support vector machines (LS-SVM), back propagation neural network (BPNN), and random forest (RF) were applied to determine the seed quality. The results demonstrate that both the spectral and the morphological features are essential for discrimination of the quality of watermelon seeds. Clear differences between high-quality watermelon seeds and other watermelon seeds including dead seeds and low-vigor seeds were visualized, and an excellent classification (with accuracies of 92% in the LS-SVM model for Julong and 91% in the RF model for Xiali, respectively) was achieved. These results indicate that multispectral imaging could be used for rapid and efficient nondestructive quality control of watermelon seeds.

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