Prediction of the chemical composition of winter grain and maize with near infrared reflectance spectroscopy

Abstract

Near infrared reflectance spectroscopy (NIRS) was evaluated as a tool for the fast and inexpensive prediction of nutritional values of feedstuffs. NIRS calibrations were developed for winter grain samples collected over three years in the Western Cape region of South Africa. Winter grains used in the study include oats, barley, triticale and wheat. Calibrations were also developed for maize samples collected throughout South Africa. Win- ter grain samples were analysed for ash, dry matter (DM), crude protein content (CP), fat content, acid detergent fibre (ADF), neutral detergent fibre (NDF), in vitro organic matter digestibility (IVOMD), lysine and methionine. The digestible energy (DE) content of winter grain samples was determined by the mobile nylon bag technique on pigs. Maize samples were analysed for ash, DM, CP, IVOMD and TDN (total digestible nutrients). Standard errors of prediction (SEP) and multiple correlation coefficients (r) for the different winter grain constituents were respectively; ash (0.22%; 0.87), DM (0.67%; 0.68), CP (0.60%; 0.93); fat (0.19%; 0.99), ADF (0.88%; 0.98), NDF (2.13%; 0.97), IVOMD (2.06%; 0.97), DE (0.76%; 0.91), lysine (0.04%; 0.93) and methionine (0.01%; 0.90). SEP and r values for the maize calibrations were, ash (0.08%; 0.49), DM (0.12%; 0.95), CP (0.12%; 0.95), IVOMD (0.55%; 0.92) and TDN (0.39%; 0.92). These results suggested that NIRS can be developed as a rapid and accurate tool for the prediction of the nutritional value of feedstuffs, which makes it an attractive technique for routine quality control in the industry.