TY - JOUR
T1 - Application of fecal near-infrared spectroscopy and nutritional balance software to monitor diet quality and body condition in beef cows grazing Arizona rangeland
AU - Tolleson, D. R.
AU - Schafer, D. W.
PY - 2014/1
Y1 - 2014/1
N2 - Monitoring the nutritional status of range cows is difficult. Near-infrared spectroscopy (NIRS) of feces has been used to predict diet quality in cattle. When fecal NIRS is coupled with decision support software such as the Nutritional Balance Analyzer (Nutbal Pro), nutritional status and animal performance can be monitored. Approximately 120 Hereford and 90 CGC composite (50% Red Angus, 25% Tarentaise, and 25% Charolais) cows grazing in a single herd were used in a study to determine the ability of fecal NIRS and NutbalPro to project BCS (1 = thin and 9 = fat) under commercial scale rangeland conditions in central Arizona. Cattle were rotated across the 31,000 ha allotment at 10 to 20 d intervals. Cattle BCS and fecal samples (approximately 500 g) composited from 5 to 10 cows were collected in the pasture approximately monthly at the midpoint of each grazing period. Samples were frozen and later analyzed by NIRS for prediction of diet crude protein (CP) and digestible organic matter (DOM). Along with fecal NIRS predicted diet quality, animal breed type, reproductive status, and environmental conditions were input to the software for each fecal sampling and BCS date. Three different evaluations were performed. First, fecal NIRS and Nut-balPro derived BCS was projected forward from each sampling as if it were a "one-time only" measurement. Second, BCS was derived from the average predicted weight change between 2 sampling dates for a given period. Third, inputs to the model were adjusted to better represent local animals and conditions. Fecal NIRS predicted diet quality varied from a minimum of approximately 5% CP and 57% DOM in winter to a maximum of approximately 11% CP and 60% DOM in summer. Diet quality correlated with observed seasonal changes and precipitation events. In evaluation 1, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.1 to 1.1 BCS in Herefords and 0.0 to 0.9 in CGC. In evaluation 2, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.00 to 0.46 in Hereford and 0.00 to 0.67 in CGC. In evaluation 3, the range of differences between observed and projected BCS was 0.04 to 0.28. The greatest difference in projected versus observed BCS occurred during periods of lowest diet quality. Body condition was predicted accurately enough to be useful in monitoring the nutrition of range beef cows under the conditions of this study.
AB - Monitoring the nutritional status of range cows is difficult. Near-infrared spectroscopy (NIRS) of feces has been used to predict diet quality in cattle. When fecal NIRS is coupled with decision support software such as the Nutritional Balance Analyzer (Nutbal Pro), nutritional status and animal performance can be monitored. Approximately 120 Hereford and 90 CGC composite (50% Red Angus, 25% Tarentaise, and 25% Charolais) cows grazing in a single herd were used in a study to determine the ability of fecal NIRS and NutbalPro to project BCS (1 = thin and 9 = fat) under commercial scale rangeland conditions in central Arizona. Cattle were rotated across the 31,000 ha allotment at 10 to 20 d intervals. Cattle BCS and fecal samples (approximately 500 g) composited from 5 to 10 cows were collected in the pasture approximately monthly at the midpoint of each grazing period. Samples were frozen and later analyzed by NIRS for prediction of diet crude protein (CP) and digestible organic matter (DOM). Along with fecal NIRS predicted diet quality, animal breed type, reproductive status, and environmental conditions were input to the software for each fecal sampling and BCS date. Three different evaluations were performed. First, fecal NIRS and Nut-balPro derived BCS was projected forward from each sampling as if it were a "one-time only" measurement. Second, BCS was derived from the average predicted weight change between 2 sampling dates for a given period. Third, inputs to the model were adjusted to better represent local animals and conditions. Fecal NIRS predicted diet quality varied from a minimum of approximately 5% CP and 57% DOM in winter to a maximum of approximately 11% CP and 60% DOM in summer. Diet quality correlated with observed seasonal changes and precipitation events. In evaluation 1, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.1 to 1.1 BCS in Herefords and 0.0 to 0.9 in CGC. In evaluation 2, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.00 to 0.46 in Hereford and 0.00 to 0.67 in CGC. In evaluation 3, the range of differences between observed and projected BCS was 0.04 to 0.28. The greatest difference in projected versus observed BCS occurred during periods of lowest diet quality. Body condition was predicted accurately enough to be useful in monitoring the nutrition of range beef cows under the conditions of this study.
KW - Beef cattle
KW - Feces
KW - Near-infrared spectroscopy
KW - Nutritional balance software
KW - Nutritional monitoring
KW - Rangeland
UR - http://www.scopus.com/inward/record.url?scp=84891639361&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891639361&partnerID=8YFLogxK
U2 - 10.2527/jas.2013-6631
DO - 10.2527/jas.2013-6631
M3 - Article
C2 - 24305871
AN - SCOPUS:84891639361
SN - 0021-8812
VL - 92
SP - 349
EP - 358
JO - Journal of animal science
JF - Journal of animal science
IS - 1
ER -