Journal
ANIMAL FEED SCIENCE AND TECHNOLOGY
Volume 144, Issue 1-2, Pages 65-81Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.anifeedsci.2007.10.002
Keywords
Fourier-transform infrared spectroscopy; principal component analysis; multinomial regression; heathland plants; herbivory
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Funding
- Biotechnology and Biological Sciences Research Council [BBS/E/G/00003009] Funding Source: researchfish
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To investigate the relationships between plant composition in a complex diet mixture and intake by sheep, blood and faeces were analysed by Fourier transform mid-infrared (FIF-IR) spectroscopy. Each of four mature Welsh Mountain ewes was maintained, for a period of 9 days, on one of three diets comprising a mixture of heathland plants containing either 100 g/kg (H100), 200 g/kg (11200) or 300 g/kg (H300) heather (Calluna vulgaris) in the fresh matter. Spectra of blood and faeces from each animal were acquired and the data analysed using principal component analysis (PCA) and hierarchical cluster analysis (HCA). We also investigated multinomial regression as an extension beyond the pattern recognition state. Animals offered the H300 diet could be consistently separated from animals fed on the H 100 and H200 diets by PCA and HCA of plasma data, and these results were consistent with animals on the H300 diet consuming greater quantities of heather. Using faecal spectra, PCA and HCA discriminated between animals on the H200 diet and those on the 14100 and H300 diets. Analysis of the plasma and faecal data by the multinomial model indicated that when PCs 4, 5 and 6 of the plasma data and PCs 3 and 4 of the faecal data were selected as covariates, leave-one-out cross-validation (LOO-CV) achieved an accurate dietary classification for 9 out of the 11 animals. In the present study, we have shown the ability to discriminate animals offered closely related diets on the basis of metabolic fingerprints of plasma and faeces. (c) 2007 Elsevier B. V. All rights reserved.
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