Non-Destructive Identification of Naturally Aged Alfalfa Seeds via Multispectral Imaging Analysis.

ABSTRACT: Seed aging detection and viable seed prediction are of great significance in alfalfa seed production, but traditional methods are disposable and destructive. Therefore, the establishment of a rapid and non-destructive seed screening method is necessary in seed industry and research. In this study, we used multispectral imaging technology to collect morphological features and spectral traits of aging alfalfa seeds with different storage years. Then, we employed five multivariate analysis methods, i.e., principal component analysis (PCA), linear discrimination analysis (LDA), support vector machines (SVM), random forest (RF) and normalized canonical discriminant analysis (nCDA) to predict aged and viable seeds. The results revealed that the mean light reflectance was significantly different

SUBMITTER: Wang X 

PROVIDER: S-EPMC8434479 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature