Early plant disease diagnosis through handheld UV–Vis transmittance spectrometer with DD-SIMCA one-class classification and MCR-ALS bilinear decomposition

• DD-SIMCA as one-class classification was applied to UV-Vis spectra for healthy tissue. • Healthy tissue UV-Vis spectra were classified as a target class by DD-SIMCA. • Diseased tissue UV-Vis spectra were identified as a non-target class by DD-SIMCA. • MCR-ALS retrieved pure UV-Vis spectral profiles for healthy and diseased tissues. A novel non-destructive analytical method for early diagnosis of two bacterial diseases, Pseudomonas syringae and Xanthomonas euvesicatoria , in tomato plants, using ultraviolet-visible (UV-Vis) transmittance spectroscopy and chemometric tools, is developed. Plant-pathogen interactions caused tissue damage that generated non-linear data patterns compared to the control set (healthy samples), which complicates traditional discrimination models, even when employing non-linear discriminant approaches. Alternatively, an authentication task to conduct one-class classification relying on a data-driven version of soft independent modeling of class analogy (DD-SIMCA) is a wise choice due to its quadratic approach, proper to deal with non-linear data. DD-SIMCA detached the target class (control healthy plant leaflet tissues) from all other samples (target class and non-target class of plant leaflet tissues inoculated with two bacteria, even before the manifestation of macroscopic lesions associated with the diseases) by capturing the main similarities within the samples of the target class through the full distance that acts as a classification analytical signal , reaching 100% sensitivity in the training and validation sets. Multivariate curve resolution constrained analysis allowed the description of the bacterial inoculation process on diseased tissues through pure spectral signatures. DD-SIMCA results indicate that non-target class of samples with higher proximity to the acceptance boundary suggested that they were at earlier stages of infection compared to more distant ones, presenting lower full distance values. These findings reveal that a handheld UV-Vis transmittance spectrometer is sufficiently sensitive to be used in acquiring biological data with suitable chemometric modeling for early disease diagnosis and prompt intervention.