您好，欢迎访问黑龙江省农业科学院 机构知识库！
黑龙江省农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Rapid identification of adulterated rice based on data fusion of near-infrared spectroscopy and machine vision

文献类型： 外文期刊

作者： Song, Chenxuan 1 ; Liu, Jinming 1 ; Wang, Chunqi 2 ; Li, Zhijiang 2 ; Zhang, Dongjie 2 ; Li, Pengfei 4 ;

作者机构： 1.Heilongjiang Bayi Agr Univ, Coll Informat & Elect Engn, Daqing 163319, Peoples R China

2.Heilongjiang Bayi Agr Univ, Coll Food Sci, Daqing 163319, Peoples R China

3.Natl Coarse Cereals Engn Technol Ctr, Daqing 163319, Peoples R China

4.Heilongjiang Acad Agr Sci Postdoctoral Workstat, Harbin 150086, Peoples R China

关键词： Adulterated rice; Near-infrared spectroscopy; Machine vision; Successive projection algorithm; Principal component analysis; Support vector classification

期刊名称：JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION （ 影响因子：3.4； 五年影响因子：3.2 ）

ISSN： 2193-4126

年卷期： 2024 年

页码：

收录情况： SCI

摘要： Rice is susceptible to mold and mildew during storage. Metabolites such as aflatoxin produced during mildew have great harm to the health of consumers. A rapid identification approach of contaminated rice was developed based on data fusion of near-infrared spectroscopy and machine vision to satisfy the need for rapid detection of normal rice adulterated with moldy rice. The successive projection algorithm (SPA) was merged with principal component analysis (PCA) and support vector classification (SVC) to create the SPA-PCA-SVC method, which was based on variable selection, feature extraction, and nonlinear modeling methodologies. K-fold cross-validation and the sum of predicted residual squares were used to find the optimal number of main components. The model parameters were tuned using a genetic algorithm. Identification models of adulterated rice was established based on NIR spectroscopy, machine vision, and their fusion data using this method. The identification accuracy of the training set was 92.81%, 86.27%, and 99.35%, and the identification accuracy of the test set was 69.23%, 82.69%, and 96.15%, respectively. Compared to near-infrared spectroscopy and machine vision alone, the identification performance of the model built by fusion data is significantly improved. The findings demonstrate the viability of the near-infrared spectroscopy and machine vision data fusion method for the detection of contaminated rice, providing a theoretical foundation for the creation of online adulterated rice identification tools.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：黑龙江省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台