Abstract

Abstract Pathogen infection can damage agricultural products, thereby reducing their economic value. Fusarium spp. is a fungal pathogen that infects potatoes (Solanum tuberosum L.) and causes dry rot. In this study, we utilized visible–near-infrared (Vis–NIR) and shortwave–near-infrared (SW–NIR) spectroscopy for the early detection of Fusarium spp. infection in potato tubers. The spectrometer used in this study analyzed the Vis–NIR (400–1,000 nm) and SW–NIR (970–1,700 nm) regions. A total of 183 potato (G2 “Granola L.” variety) samples were used. Among these, 93 samples were artificially inoculated with Fusarium solani mycelia, while 90 samples were left uninfected and considered the control group. The potato samples were stored at two different temperatures (12 and 25°C). Vis–NIR and SW–NIR spectra were analyzed by a chemometric method, namely principal component analysis with linear discriminant analysis (PCA–LDA), to differentiate healthy and infected potatoes. The PCA–LDA model based on Vis–NIR spectra exhibited a calibration accuracy of 80.26% and a reliability of 65%. Meanwhile, the PCA–LDA model based on SW–NIR spectra exhibited a calibration accuracy of 100% and a reliability of 97.30%. Overall, both methods demonstrated their suitability for differentiating potato tubers with Fusarium spp. fungal infection and healthy ones; however, the results suggest that SW–NIR spectroscopy is more effective than Vis–NIR spectroscopy.

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