ANALYSIS OF HAY, HAYLAGE AND CORN SILAGE SAMPLES BY NEAR INFRARED REFLECTANCE SPECTROSCOPY

Abstract

Separate calibrations for hay, haylage and corn silage were developed to predict chemical composition by near infrared reflectance spectroscopy (NIR). A scanning type of NIR instrument was used to select the best set of wavelengths (λ) while a filter type was used to evaluate the calibrations. Reflectance (R) was recorded as log (1/R). Bias (nonrandom error) was corrected for each set of samples before the NIR analysis. Percent crude protein (CP), acid detergent fiber (ADF), calcium (Ca) and phosphorus (P) were studied in the hay samples. In addition, potassium (K) and magnesium (Mg) were included for the haylage and corn silage samples. Six hundred samples, including calibration (C) and prediction sets (PRE1 and PRE2) were used. PRE1 samples came from the same population as the C samples, whereas PRE2 samples were obtained in a different year. Accuracy of the predictions was assessed by the coefficients of determination (r2), standard error of the estimate (SEE), and coefficients of variation (CV). Crude protein was the parameter best predicted by NIR with r2, SEE and CV ranging from 0.72 to 0.96, 0.43 to 1.17 and 5.6 to 10.4, respectively. The highest SEE for crude protein were associated with the PRE2 samples for haylage and hay samples (1.09 and 1.17), respectively. NIR predictions of ADF had r2, SEE and CV values ranging from 0.21 to 0.92, 1.44 to 2.53 and 5.3% to 7.9%, respectively. Corn silage had the lowest SEE for ADF in both C and PRE1 sets. Predicting mineral contents by NIR gave high CV (10.5%–34.5%) and low r2 values (0.02–0.75). Calcium predictions had the highest variability, and P and Mg predictions the lowest.These results indicate that CP was successfully predicted by NIR. The higher SEE values for ADF may have been due to variation in the wet chemistry values of some samples. Minerals were not adequately predicted by NIR as assessed by r2, SEE and CV values. Key words: Near infrared reflectance spectroscopy, forage, chemical analysis