Detection of Peak Intensity Using an Integrated Optical Modeling Method for Identifying Defective Apple Leaves †

The identification of defects in apple leaf specimens is crucial for mitigating crop loss and maintaining harvest quality. This study investigates the applicability of an intensity detection simulation-integrated optical cross-sectional modeling method for detecting defective apple leaf specimens. The technique utilizes a customized 840 nm optical coherence tomography (OCT). The method involved using a peak-intensity detection technique to analyze OCT signal intensity variations in multi-layered leaf structures. Results demonstrate the potential of the method to identify morphological differences between leaf specimens from healthy and infected trees and, specifically, healthy leaf specimens from infected trees. Implementing this method enables cost saving through timely interventions to reduce the impact of leaf defects on crop production.