Leaf Diffuse Reflectance Spectroscopy for Early Detection of Ceratocystis Wilt in Eucalyptus Cuttings
Journal Article
Overview
abstract
ABSTRACT; ; The increasing global demand for products derived from; Eucalyptus; spp. has stimulated its production in Brazil. However, productivity has declined in recent years due to several factors, with Ceratocystis wilt being one of the most significant. Conventional detection methods rely on visual assessment, histological sections and/or molecular analyses—procedures that are time‐consuming and impractical for large‐scale monitoring. Proximal or remote sensing based on VIS–NIR–SWIR spectroscopy (400–2500 nm) has been proposed as a non‐destructive alternative for characterising plant biochemical and biophysical properties, yet its use for detecting Ceratocystis wilt in; Eucalyptus; spp. remains underexplored. Here, we evaluated whether leaf reflectance measurements in the VIS–NIR–SWIR range, acquired with a proximal non‐imaging sensor, can be used to detect the disease in asymptomatic cuttings (vegetatively propagated plants). For that a greenhouse experiment was established with two; Eucalyptus; clones, one susceptible and another resistant. Plants were visually assessed and tested via the ‘carrot bait’ method for disease incidence, and spectral measurements collected four times between 12 and 60 h after inoculation. Observations for inoculated plants were compared with those from non‐inoculated controls (total; n; = 77). Classification models trained with Partial Least Squares Discriminant Analysis (PLS‐DA), Random Forest with Recursive Feature Elimination (RF + RFE) and Support Vector Machine with Genetic Algorithm (SVM + GA) achieved balanced accuracy of 0.63 ± 0.11, 0.75 ± 0.11 and 0.75 ± 0.13, respectively. Features selected via RFE and GA, or identified as highly important in the PLS‐DA, RF + RFE and SVM + GA models, were predominantly located in the visible, NIR and especially the SWIR regions. This distribution is consistent with absorption features associated with leaf water, cellulose, starch and lignin (near 1100–1200 and 2300 nm), as well as proteins (near 1700, 2200 and 2300 nm). Spectra from the apical canopy layer generally provided better classification performance than those from the basal or middle canopy sections. Despite the relatively small dataset and limited number of clones, our results demonstrate the potential of proximal spectroscopy for detecting Ceratocystis wilt in asymptomatic; Eucalyptus; plants.;
