Sampling requirements for predicting cattle diet quality using faecal near-infrared reflectance spectroscopy (F.NIRS) in heterogeneous tropical rangeland pastures
I. A. White A B D , L. P. Hunt B , D. P. Poppi A and S. R. Petty C
+ Author Affiliations
- Author Affiliations
A Schools of Animal Studies and Veterinary Science, University of Queensland, Gatton, Qld 4343, Australia.
B CSIRO Ecosystem Sciences, PMB 44, Winnellie, NT 0822, Australia.
C Northern Development Company, PO Box 447, Kununurra, WA 6743, Australia.
D Corresponding author. Email: G-sec@hotmail.com
The Rangeland Journal 32(4) 435-441 https://doi.org/10.1071/RJ09021
Submitted: 26 March 2009 Accepted: 26 October 2010 Published: 26 November 2010
Abstract
Faecal near-infrared reflectance spectroscopy (F.NIRS) provides predictive information on cattle diets and nutritional levels, useful for livestock management or for research purposes. Potential errors exist throughout the entire F.NIRS process, including the collection method. The accepted collection method involves aggregating equal amounts of faecal material from 5 to 15 animals, mixing and removing a single sample for analysis. The adequacy of this method was tested by collecting and analysing up to 70 samples from individual cattle in different paddocks. Two methods were used to determine sample size based on observed variability in dietary attributes. Variability of dietary non-grass material and crude protein content increased with paddock size, so required sample size also increased. For dietary F.NIRS predictions to be used for research, our results suggest from 20 to 51 samples are needed in small to large paddocks to accurately predict the proportion of dietary non-grass material, from 12 to 50 samples for crude protein content and from 6 to 34 samples for dry matter digestibility. Composite samples from 15 cattle provided representative means in less than 50% of the situations investigated using biologically significant precision levels, but would be adequate for management of animal nutrition. Analysis of individual samples provided additional measures of range and variability which were also informative.
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