Predicting fecal composition, intake, and nutrient digestibility in beef cattle consuming high forage diets using near infrared spectroscopy

Jenilee F Peters; Mary L Swift; Gregory B Penner; Herbert A Lardner; Tim A McAllister; Gabriel O Ribeiro

doi:10.1093/tas/txad043

Predicting fecal composition, intake, and nutrient digestibility in beef cattle consuming high forage diets using near infrared spectroscopy

Transl Anim Sci. 2023 May 2;7(1):txad043. doi: 10.1093/tas/txad043. eCollection 2023 Jan.

Authors

Jenilee F Peters^{1

2}, Mary L Swift², Gregory B Penner¹, Herbert A Lardner¹, Tim A McAllister^{1

3}, Gabriel O Ribeiro¹

Affiliations

¹ Department of Animal and Poultry Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaS7N 5A8.
² Trouw Nutrition Canada, Okotoks, Alberta, CanadaT1S 1A2.
³ Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, CanadaT1J 4B1.

Abstract

The objective of this study was to develop near infrared spectroscopy (NIRS) calibrations to predict fecal nutrient composition, intake, and diet digestibility from beef cattle fed high forage diets. Heifers were fed 12 different forage-based diets (>95% forage dry matter basis) in 3 total collection digestibility studies, resulting in individual fecal samples and related spectra (n = 135), corresponding nutrient intake, and apparent total tract digestibility (aTTD) data. Fecal samples were also collected from steers grazing two annual and two perennial forage mixtures over two growing seasons. Samples (n = 13/paddock) were composited by paddock resulting in 30 samples from year 1, and 24 from year 2. The grazing fecal spectra (n = 54) were added to the existing fecal composition spectral library. Dried and ground fecal samples were scanned using a FOSS DS2500 scanning monochromator (FOSS, Eden Prairie, MN). Spectra were mathematically treated for detrend and scatter correction and modified partial least squares (MPLS) regression was performed. The coefficient of determination for cross validation (R²_cv) and standard error of cross validation (SECV) were used to evaluate the quality of calibrations. Prediction equations were developed for fecal composition [organic matter (OM), nitrogen (N), amylase-treated ash-corrected neutral detergent fiber (aNDFom), acid detergent fiber (ADF), acid detergent lignin (ADL), undigestible NDF after 240 h of in vitro incubation (uNDF), calcium (Ca), and phosphorus (P)], digestibility [DM, OM, aNDFom, N], and intake [DM, OM, aNDFom, N, uNDF]. The calibrations for fecal OM, N, aNDFom, ADF, ADL, uNDF, Ca, P resulted in R²_cv between 0.86 and 0.97 and SECV of 1.88, 0.07, 1.70, 1.10, 0.61, 2.00, 0.18, and 0.06, respectively. Equations predicting intake of DM, OM, N, aNDFom, ADL, and uNDF resulted in R²_cv values between 0.59 and 0.91, SECV values of 1.12, 1.10, 0.02, 0.69, 0.06, 0.24 kg·d^-1, respectively, and SECV values between 0.00 and 0.16 when expressed as % body weight (BW). Digestibility calibrations for DM, OM, aNDFom, and N resulted in R²_cv ranging from 0.65 to 0.74 and SECV values from 2.20 to 2.82. We confirm the potential of NIRS to predict fecal chemical composition, digestibility, and intake of cattle fed high forage diets. Future steps include validation of the intake calibration equations for grazing cattle using forage internal marker and modelling energetics of grazing growth performance.

Keywords: digestibility; fecal composition; feces; grazing cattle; intake; near infrared spectroscopy.