2023 Volume 59 Issue 11 Pages 462-471
Ginger rhizome rot is one of the most damaging plant diseases that occur in ginger. In this study, we proposed a method of detecting diseased ginger plants by using leaf motion to identify diseased ginger plants at an early stage of rhizome rot. We found a tendency for inoculated plants intentionally inoculated with the rhizome rot pathogen to have less leaf motion than uninoculated plants. Hereby, we proposed a method based on ExG (Excess Green) and SVM (Support Vector Machine) to quantify leaf motion and evaluated whether these methods could discriminate between inoculated and uninoculated plants using ROC (Receiver Operator Characteristic) curves and AUC (Area Under the Curve). As a result, the AUC was 0.989, and the accuracy for discrimination by the best threshold in Youden's Index was 96.08%. The true positive rate was 92.59%. The false positive rate was 0% when the inoculated plants were considered positive. When the threshold value was set so that the true positive rate was 100%, the minimum false positive rate was 16.67%.
