Comparison of Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) Methods for Protein and Hardness Predictions using the Near-Infrared (NIR) Hyperspectral Images of Bulk Samples of Canadian Wheat

标题
Comparison of Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) Methods for Protein and Hardness Predictions using the Near-Infrared (NIR) Hyperspectral Images of Bulk Samples of Canadian Wheat
作者
关键词
Hyperspectral imaging, Wheat, Protein, Hardness, Mean square errors of prediction, Standard error of cross-validation, Correlation coefficient
出版物
Food and Bioprocess Technology
Volume 8, Issue 1, Pages 31-40
出版商
Springer Nature
发表日期
2014-08-01
DOI
10.1007/s11947-014-1381-z

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