Abstract

This study explores the application of near-infrared (NIR) spectroscopy coupled with multivariate techniques for the rapid and accurate identification of four Fusarium species, with emphasis on the detection of Fusarium circinatum, , the causative agent of "Pitch canker" disease in forests, cultured in vitro under distinct light conditions. The impact of two different incubation conditions, near-ultraviolet (NUV) and warm light, on the spectral characteristics of cultures was used as a strategy to improve the early fungal detection using spectroscopy. Spectral data were acquired using a portable NIR spectrometer at 48, 72, and 96 h post-cultivation from various zones of mycelial growth. The results showed distinct spectral profiles among Fusarium species, with notable variations depending on incubation light conditions and growth zones. NUV light conditions significantly improved species differentiation, especially in the central and middle zones of mycelial growth at 72 h post- cultivation (hpc). Partial least squares- discriminant analysis (PLS-DA) model under NUV light conditions provided the best identification strategy, achieving correct classification rates over 97% for all four species from 72 hpc and 82.5% of correct classification of F. circinatum. . These findings demonstrate the effectiveness of the NIRS methodology supported with multivariate techniques and combined with optimization of light conditions and mycelial growth zone of cultures, for the early and rapid detection of Fusarium species in culture media, with potential implications for plant pathology diagnostics and disease management strategies.