An early asymptomatic diagnosis method for cork spot disorder in 'Akizuki' pear Nakai) using micro near infrared spectroscopy.

The early symptoms of cork spot disorder in 'Akizuki' pear ( Nakai) are challenging to distinguish from those in healthy fruits, hindering early identification in production. In this study, samples of cork-browned 'Akizuki' pears, asymptomatic fruits and healthy fruits were examined to determine the content of relevant mineral elements. A micro near-infrared spectrometer collected spectral information, and various pretreatment methods were applied to the near-infrared spectral data. Support vector machine (SVM) modelling using the original data achieved the highest overall recognition accuracy of 84.65% and an F1 value of 84.06%. For identifying fruits without cork spot disease, Autokeras modelled data processed with the SG method, achieving the best accuracy of 90%. These findings establish a reliable basis for the early identification and diagnosis of cork spot disorder in 'Akizuki' pear, enhancing pear production management.