Detection of virus infection in fungal tissue using visible and near infrared spectroscopy

Resumen

Infections with Neotyphodium and Epichloe endophytes are common in grasses and, in turn, virus infection is common in these endophytic genera. The objective of this study was to test the use of visible and near-infrared (Vis-NIR) spectroscopy as a tool to diagnose the presence of viral double-stranded RNA (dsRNA) in strains of the fungal endophyte Epichloe festucae isolated from Festuca rubra plants. Vis-NIR spectroscopy has several advantages when compared to the conventional methods, including environmental friendliness, as no chemical waste is produced. Ground, freeze-dried mycelium samples from virus-infected and virus-free E. festucae isolates were scanned in reflectance mode at 2 nm intervals (range of 400-2498 nm). A total of 124 mean spectra were recorded. Calibration models were developed using partial least-squares discriminant analysis (PLS1-DA). Applying our best regression Model constructed with two sampling years, and using standard normal variate (SNV) combined with first derivative transformation to new validating data set (42 samples), we obtained a correct classification of 75% of the uninfected isolates, and up to 86% of the infected isolates. To conclude, the application of Vis-NIR technology may be considered as a potentially useful technique for the detection of viral infections in grass endophytes.