Hostname: page-component-76fb5796d-dfsvx Total loading time: 0 Render date: 2024-04-26T17:53:34.397Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimation of dry-matter intake and digestibility in group-fed dairy cows using near infrared reflectance spectroscopy

Published online by Cambridge University Press:  18 August 2016

P. C. Garnsworthy  and
Y. Unal
P. C. Garnsworthy
Affiliation:
University of Nottingham, Division of Agricultural and Environmental Sciences, School of Biosciences, Sutton Bonington Campus, Loughborough LE12 5RD, UK
Y. Unal
Affiliation:
University of Nottingham, Division of Agricultural and Environmental Sciences, School of Biosciences, Sutton Bonington Campus, Loughborough LE12 5RD, UK
Get access

Abstract

This study was designed to obtain information on predicting intake and digestibility from near infrared reflectance spectroscopy (NIRS) scans of faeces in dairy cows given different diets and levels of intake. Comparisons were made between using NIRS to predict alkanes in faeces and direct calibration of NIRS for intake and digestibility. Faecal samples were obtained from 91 cows in five experiments where dry-matter intake (DMI) had been measured for individual cows. All samples were scanned by NIRS and concentrations of alkanes C32, C33 and C36 were determined in 32 samples. DMI (mean 19-4, s.d. 5-06 kg/day) was estimated with standard errors of 0-36 and 0-44 kg/day from C32 and C36 alkanes determined by gas chromatography, and with standard errors of 1-17 and 1-42 kg/day when DMI was estimated from C32 and C36 alkanes predicted by NIRS. When DMI was predicted directly by NIRS, the standard error of prediction was 0-48 kg/day (R2 = 0-97). Prediction of dry matter digestibility by NIRS was not accurate (standard error of cross validation = 0-032; R2= 0-68), probably because of the limited variation in digestibility values within the data set. It is concluded that using NIRS to predict alkane concentrations of faeces does not give accurate estimates of DMI but direct prediction of DMI by NIRS gives estimates with similar accuracy to estimates derived from the traditional alkane technique.

Keywords

dairy cowsdry-matter intakenear infrared reflectance spectroscopy
Type
Ruminant nutrition, behaviour and production
Information
Animal Science , Volume 79 , Issue 2 , October 2004 , pp. 327 - 334
Copyright
Copyright © British Society of Animal Science 2004

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Acamovic, T., Murray, I. and Paterson, R. M. 1992. The use of NIR in predicting chromic oxide in diets. In Making light work. Advances in near infrared spectroscopy (ed. Murray, I. and Cowe, I. A.), pp. 250–252. Ian Michael Publications, Chichester.Google Scholar
Baker, C. W., Givens, D. I. and Deaville, E. R. 1994. Prediction of organic matter digestibility in vivo of grass silage by near infrared reflectance spectroscopy: effect of calibration method, residual moisture and particle size. Animal Feed Science and Technology 50:17–26.Google Scholar
Biston, R., Bartiaux-Thill, N., Thewis, A., Francois, E., Limbourg, P., Gielen, M. and Dardenne, P. 1988. Prevision de la quantite d'herbe ingeree par la vache laitiere au paturage. Comparison des methods d'estimation de la digestibilite et du mode d'echantillonnage des feces. Reproduction, Nutrition, Developpement 28: (suppl. 1) 61–62.Google Scholar
Clark, D. H., Mayland, H. F. and Lamb, R. C. 1987. Mineral analysis of forages with near infrared reflectance spectroscopy. Agronomy Journal 79:485–490.CrossRefGoogle Scholar
De Boever, J. L., Eeckhout, W. and Boucque, C. V. 1994. The possibilities of near infrared reflection spectroscopy to predict total-phoshorus, phytate-phosphorus and phytase activity in vegetable feedstuffs. Netherlands Journal of Agricultural Science 42:357–369.Google Scholar
Dove, H. and Mayes, R. W. 1991. The use of plant wax alkanes as markers substances in studies of the nutrition of herbivores: a review. Australian Journal of Agricultural Research 42: 913–952.Google Scholar
Gordon, F. J., Cooper, K. M., Park, R. S. and Steen, R. W. J. 1998. The prediction of intake potential and organic matter digestibility of grass silages by near infrared spectroscopy analysis of un-dried samples. Animal Feed Science and Technology 70: 339–351.Google Scholar
Lawes Agricultural Trust. 2002. Genstat 6 version 6-1. Rothamsted Experimental Station, Harpenden.Google Scholar
Lyons, R. K. and Stuth, J. W. 1992. Fecal NIRS equations for predicting diet quality of free-ranging cattle. Journal of Range Management 45: 238–244.Google Scholar
Mayes, R. W., Lamb, C. S. and Colgrove, P. M. 1986. The use of dosed and herbage n-alkanes as markers for the determination of herbage intake. Journal of Agricultural Science, Cambridge 107:161–170.Google Scholar
O'Keefe, M., Downey, G. and Brogan, J. C. 1987. The use of near infrared reflectance spectroscopy for predicting the quality of grass silage. Journal of the Science of Food and Agriculture 38:209–216.Google Scholar
Osborne, B. G., Fearn, T. and Hindle, P. H. 1993. Practical NIR spectroscopy with applications in food and beverage analysis. Longman Scientific and Technical, Harlow, UK.Google Scholar
Park, R. S., Gordon, F. J., Agnew, R. E., Barnes, R. J. and Steen, R. W. J. 1997. The use of near infrared reflectance spectroscopy on dried samples to predict biological parameters of grass silage. Animal Feed Science and Technology 68: 235–246.Google Scholar
Piasentier, E., Bovolenta, S., Malossini, F. and Susmel, P. 1995. Comparison of n-alkanes or chromium oxide methods for estimation of herbage intake by sheep. Small Ruminant Research 18:27–32.Google Scholar
Redshaw, E. S., Mathison, G. W., Milligan, L. P. and Weisenburger, R. D. 1986. Near infrared reflectance spectroscopy for predicting forage composition and voluntary consumption and digestibility in cattle and sheep. Canadian Journal of Animal Science 66:103–115.Google Scholar
Unal, Y. and Garnsworthy, P. C. 1999. Estimation of intake and digestibility of forage-based diets in group-fed dairy cows using alkanes as markers. Journal of Agricultural Science, Cambridge 133:419–425.Google Scholar
Windham, W. R., Mertens, D. R. and Barton, F. E. 1989. Protocol for NIRS calibration, sample selection and equation development and validation. In Near infrared reflectance spectroscopy (NIRS). Analysis of forage quality (ed. Marten, G. C., Shenk, J. S. and Barton, F. E.), pp. 96–103. Agricultural handbook no. 643, USDA-ARS, Washington, DC.Google Scholar