Detection of green pepper impurities based on hyperspectral imaging technology

文献类型： 外文期刊

第一作者： Zhang, Jian

作者： Zhang, Jian;Xia, Weihai;Liu, Haijun;Zhang, Jian;Gou, Yujiang;Chang, Xiangyu;An, Ting;Ma, Lingkai;An, Ting

作者机构：

关键词： Green pepper; Quality; Impurity; Hyperspectral imaging technology

期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.6； 五年影响因子：4.3 ）

ISSN： 1386-1425

年卷期： 2025 年 338 卷

页码：

收录情况： SCI

摘要： To date, the intelligent assessment of green pepper quality remains an open question, particularly in aspects of color, as impurities closely resemble green peppers. Here, the hyperspectral imaging technology was employed to acquire the original spectral and image information of green and impurities. Subsequently, the original information was processed, and then trained using the super vector machine (SVM), to construct the green pepper impurity detection model. After training, the constructed model achieved 100% accuracy in the training set and 89.7% accuracy in the testing set, which generally met the application requirements. Visualization images of the constructed model in the application of identification green pepper impurity were prepared and optimized, which significantly achieved relatively satisfactory outcomes. Findings of this case study revealed that the presented strategy would provide a theoretical basis for the intelligent processing of green pepper, especially accelerate the development of impurity detection technology.

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