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Faecal near-IR spectroscopy to determine the nutritional value of diets consumed by beef cattle in east Mediterranean rangelands

Published online by Cambridge University Press:  01 September 2015

S. Y. Landau ,
L. Dvash ,
M. Roudman ,
H. Muklada ,
D. Barkai ,
Y. Yehuda  and
E. D. Ungar
S. Y. Landau*
Affiliation:
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, the Volcani Center, Bet Dagan 50250, Israel
L. Dvash
Affiliation:
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, the Volcani Center, Bet Dagan 50250, Israel
M. Roudman
Affiliation:
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, the Volcani Center, Bet Dagan 50250, Israel
H. Muklada
Affiliation:
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, the Volcani Center, Bet Dagan 50250, Israel
D. Barkai
Affiliation:
Department of Natural Resources, Gilat Experimental Station, M.P. HaNegev 2, Israel
Y. Yehuda
Affiliation:
Northern R&D, P.O. Box 831, Kiryat Shmona 11016, Israel
E. D. Ungar
Affiliation:
Department of Natural Resources, Institute of Plant Sciences, Agricultural Research Organization, the Volcani Center, Bet Dagan 50250, Israel
*
†E-mail: vclandau@volcani.agri.gov.il
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Abstract

Rapid assessment of the nutritional quality of diets ingested by grazing animals is pivotal for successful cow–calf management in east Mediterranean rangelands, which receive unpredictable rainfall and are subject to hot-spells. Clipped vegetation samples are seldom representative of diets consumed, as cows locate and graze selectively. In contrast, faeces are easily sampled and their near-IR spectra contain information about nutrients and their utilization. However, a pre-requisite for successful faecal near-infrared reflectance spectroscopy (FNIRS) is that the calibration database encompass the spectral variability of samples to be analyzed. Using confined beef cows in Northern and Southern Israel, we calibrated prediction equations based on individual pairs of known dietary attributes and the NIR spectra of associated faeces (n=125). Diets were composed of fresh-cut green fodder of monocots (wheat and barley), dicots (safflower and garden pea) and natural pasture collected at various phenological states over 2 consecutive years, and, optionally, supplements of barley grain and dried poultry litter. A total of 48 additional pairs of faeces and diets sourced from cows fed six complete mixed rations covering a wide range of energy and CP concentrations. Precision (linearity of calibration, R2cal, and of cross-validation, R2cv) and accuracy (standard error of cross-validation, SEcv) were criteria for calibration quality. The calibrations for dietary ash, CP, NDF and in vitro dry matter digestibility yielded R2cal values >0.87, R2cv of 0.81 to 0.89 and SEcv values of 16, 13, 39 and 31 g/kg dry matter, respectively. Equations for nutrient intake were of low quality, with the exception of CP. Evaluation of FNIRS predictions was carried out with grazing animals supplemented or not with poultry litter, and implementation of the method in one herd over 2 years is presented. The potential usefulness of equations was also established by calculating the Mahalanobis (H) distance to the spectral centroid of a calibration population of 796 faecal samples collected throughout 2 years in four herds. Seasonal trends in pasture quality and responses to management practices were identified adequately and H<3.0 for 98% of faecal samples collected. We conclude that the development of FNIRS equations with confined animals is not only unexpensive and ethically acceptable, but their predictions are also sufficiently accurate to monitor dietary composition (but not intake) of beef cattle in east Mediterranean rangelands.

Keywords

nutritionbeef cattleNIRSmonitoringdecision-making
Type
Research Article
Information
animal , Volume 10 , Issue 2 , February 2016 , pp. 192 - 202
Copyright
© The Animal Consortium 2015 

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