This invention discloses a non-destructive method for detecting
protein content in common bean seeds based on
hyperspectral imaging, relating to the field of non-
destructive testing of agricultural products. It addresses the problems of traditional detection methods being highly destructive, cumbersome, and inefficient, as well as the redundancy, inaccurate
feature extraction, and poor model adaptability of existing hyperspectral detection technologies. The invention includes: screening standardized common bean seeds; acquiring hyperspectral data; extracting the average spectrum of the samples using image preprocessing and spectral extraction techniques; eliminating redundant bands using EDA analysis; extracting relevant features using any one of the SFE, PLS-VIP+Pearson+p-value, or KNN-MI schemes; and constructing and selecting the optimal prediction model. This invention can be applied to the screening of high-
protein single plants in common bean breeding, automated grading of common bean seed quality, or, after parameter adjustment, to the non-destructive detection of
protein content in seeds of other edible
legume crops such as peas, chickpeas, and cowpeas, and the tested seeds can be sown normally.