158 Predicting Intake and Digestibility of Nutrients in Beef Cattle fed High Forage Diets Using Near Infrared Spectroscopy (Nirs) of Feces and Internal Markers

Abstract

Abstract Objectives of this study were to determine the potential of near infrared-spectroscopy (NIRS) scanning of feces to predict diet digestibility and intake in beef cattle fed high forage diets, and to investigate the use of acid detergent lignin (ADL) and undigestible neutral detergent fiber (uNDF) as internal markers to determine digestibility. Beef heifers were fed 12 different forage-based diets ( > 95% forage dry matter basis) in 3 total collection studies, resulting in individual fecal samples and related spectra (n = 135) corresponding to apparent total tract digestibility (aTTD) and intake data. Dried and ground fecal samples were scanned using a FOSS DS2500 scanning monochromator (FOSS, Eden Prairie, MN). Modified partial least squares (MPLS) regression was performed to develop equations to predict digestibility [dry matter (DM), organic matter (OM), NDF, and nitrogen (N)], and intake [DM, OM, NDF, N, uNDF]. Digestibility prediction equations for DM, OM, NDF, and N resulted in R2CV or 0.72, 0.65, 0.74 and 0.69, respectively, and standard error of cross validation (SECV) between 2.20 to 2.82. Intake calibrations for DM, OM, N, NDF, ADL and uNDF resulted in R2CV values between 0.59 and 0.91, SECV for intake (kg/d) of 1.12, 1.10, 0.02, 0.69, 0.06, 0.24, respectively, SECV for intake % body weight (BW) between 0.00 and 0.16; and SECV for g/kg BW0.75 between 0.60 and 0.86. Significant correlations (P < 0.01) were identified between NDFD determined by aTTD and by the internal marker ADL (r = 0.72) or uNDF (r = 0.57). Developed calibrations predicting marker calculated digestibility resulted in R2CV(SECV) values of 0.85(2.70) and 0.80(2.46) for lignin and uNDF, respectively. We confirm the potential of NIRS to predict digestibility and intake of cattle fed high forage diets. Future steps include further validation of the intake calibration equations using internal marker and energetics modeling.