Table 1 Comparation of the artificial neural network, support vector machine and linear discriminant analysis algorithms to assess soybean seed quality using autofluorescence-spectral data, and the model performances based on accuracy, kappa, precision, recall and F1.

From: Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality