LAUSR

Whole oat has been described as an important healthy food for humans due to its beneficial nutritional components. The positive health benefits of consuming oats as a whole-grain food are attributed in part to β-glucan, which has outstanding functional and nutritional properties. Near infrared reflectance spectroscopy is a powerful, fast, accurate and non-destructive analytical tool that can be substituted for some traditional chemical analysis. A total of 1728 single intact groats of six different oat varieties were scanned by near infrared spectroscopy to develop non-destructive predictions for (1,3;1,4)-β-D-glucan (β-glucan), protein and oil content in groats. Prediction models for single kernels were developed using partial least squares regression. Regression parameters between the chemical values, determined by wet-lab reference methods, and the predicted values determined from near infrared spectra, were verified by cross-validation and against data from a set of independent samples. The cross-validation correlation coefficients (R2CV) for β-glucan, protein and oil were 0.83, 0.72 and 0.92, respectively, the root-mean-square error ranged from 0.25% to 0.60% for all compounds. Independent validation data had r2 values ranging from 0.69 to 0.95; root-mean-square error of prediction values (RMSEP) values were equal to or less than 0.52%, 0.62% and 0.27% for β-glucan, protein and oil, respectively. The data indicated that non-destructive screening of β-glucan, protein and oil contents in single kernels of dehulled oat grains from their near infrared spectra could be successfully used in breeding programs.