Discriminative Spectral Regions for Detecting Huanglongbing in Citrus Plants through Statistical Analysis

Abstract. This study aims to characterize the spectral reflectance of healthy and huanglongbing (HLB)-infected citrus individuals at both the leaf and plant levels using a statistical approach. Our main contribution is to assess the extent to which hyperspectral measurements can differentiate disease status. Spectral data were collected from 1,912 leaves belonging to 89 citrus plants, of which 29 were found to be infected with HLB and 60 were healthy. A statistical protocol—including Shapiro-Wilk, Welch’s t-tests, ANOVA, and Z- tests—was applied to estimate the mean and standard deviation of spectral reflectance for each class, evaluate the spectral variance across bands at the plant level, determine differences between HLB-positive and HLB-negative groups at both hierarchical levels (leaf and plant), and identify the spectral bands with the highest discriminatory power. The findings reveal substantial intra-plant spectral variability in HLB-positive citrus, indicating that individual leaf reflectance may not reliably represent whole-plant disease status. This reinforces the need for plant-level spectral aggregation in remote sensing models. Discriminative spectral intervals were consistently identified in the 400–431 nm, 488–752 nm, 1132–1830 nm, and 1890–2500 nm ranges, spanning the visible to shortwave infrared (SWIR) spectrum.