158 - Predicting Intake and Digestibility of Nutrients in Beef Cattle Fed High Forage Diets Using near Infrared Spectroscopy (NIRS) of Feces and Internal Markers

Tuesday, June 28, 2022

9:30 AM – 9:45 AM CT

Location: Oklahoma City Convention Center, 302A

Presenting Author(s)

Jenilee F. Peters, BSc

Quality Manager
Trouw Nutrition / University of Saskatchewan
High River, Alberta

Author(s)

MS

Mary Lou Swift

Trouw Nutrition
Ponoka, AB
Gregory B. Penner, Ph.D., M.Sc., B.Sc.

Professor
Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A8
Saskatoon, SK
BL

Bart Lardner, n/a

Professor
Department of Animal and Poultry Science, University of Saskatchewan, Saskatoon, SK, Canada, S7N 5A8
Saskatoon, AB
Timothy A. McAllister, PhD, MSc, BSc

Principal Research Scientist
Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada
Lethbridge, AB
Gabriel O. Ribeiro, n/a

Assistant Professor
Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A8
Saskatoon, SK

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 R²_CV 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 R²_CV 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 BW^0.75between 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 R²_CV(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.