Quantification of betaglucans, lipid and protein contents in whole oat groats (Avena sativa L.) using near infrared reflectance spectroscopy

Abstract

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.