Estimating deoxynivalenol content of ground oats using VIS-NIR spectroscopy

The potential of VIS-NIR spectroscopy as a rapid screening method for resistance of Fusarium-inoculated oats to replace the costly chemical measurements of deoxynivalenol (DON) was investigated. Partial least squares (PLS) regression was conducted on second-derivative spectra (400-2,350 nm) of 166 DON-contaminated samples (0.05-28.1 ppm, mean = 13.06 ppm) with separate calibration and test set samples. The calibration set had 111 samples, and the test set had 55 samples. The best model developed had three PLS components and a root mean square error of prediction (RMSEP) of 3.16 ppm. The residual predictive deviation (RPD) value of the prediction model was 2.63, an acceptable value for the purpose of rough screening. Visual inspection and the VIS spectra of the samples revealed that high-DON samples tended to be darker in color and coarser in texture compared with low-DON samples. The second-derivative spectra showed that low-DON samples tended to have more water and fat content than high-DON samples. With an RMSEP value of 3.16 and RPD of value of 2.63, it seems possible to use VIS-NIR spectroscopy to semiquantitatively estimate DON content of oats and discard the worst genotypes during the early stages of screening.