PREDICTION OF CHEMICAL COMPOSITION AND ENERGY VALUE OF GRASS SILAGE BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY

Abstract

One hundred and eighteen grass silage samples with known chemical composition and in vitro determined concentration of net energy for lactation (NEL) were scanned over the wavelength range from 1100 to 2500 nm at 8 nm intervals. Calibration equations for the prediction of crude protein (CP), crude fi bre (CF), crude fat (F), crude ash (A), dry matter of air-dried samples (DM) and NEL were developed by the use of principal component analysis (PCA) and modifi ed partial least squares regression technique (mPLS). NIRS demonstrated high predictive ability for CP (R2 = 0.97), CF (R2 = 0.96) and A (R2 = 0.94). Moderate accuracy was characteristic for F and DM (R2 = 0.81 and 0.79). Crude protein, F and DM deviations from reference methods were comparable to those which are expected by the use of the same reference methods in different laboratories. The determination coeffi cient for in vitro assessed NEL concentration was 0.76. Seventy-seven percent of samples lied within acceptable limits of ± 0.3 MJ NEL kg-1DM. Suboptimal sample distribution, i.e. small number of samples in classes below 4.6 and above 6.0 MJ NEL kg-1DM was observed. It seems that deviations of NIRS predicted values from the reference values were related to the concentration of NEL. It was concluded that NIRS shows the potential for reliable determination of chemical composition and energy value of grass silage.