Cultivars identification of oat (Avena sativa L.) seed via multispectral imaging analysis.

ABSTRACT: Cultivar identification plays an important role in ensuring the quality of oat production and the interests of producers. However, the traditional methods for discrimination of oat cultivars are generally destructive, time-consuming and complex. In this study, the feasibility of a rapid and nondestructive determination of cultivars of oat seeds was examined by using multispectral imaging combined with multivariate analysis. The principal component analysis (PCA), linear discrimination analysis (LDA) and support vector machines (SVM) were applied to classify seeds of 16 oat cultivars according to their morphological features, spectral traits or a combination thereof. The results demonstrate that clear differences among cultivars of oat seeds could be easily visualized using the multispectra

SUBMITTER: Fu X 

PROVIDER: S-EPMC9941542 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature