Hostname: page-component-848d4c4894-hfldf Total loading time: 0 Render date: 2024-06-12T04:19:20.438Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting feed digestibility from NIRS analysis of pig faeces

Published online by Cambridge University Press:  23 December 2014

D. Bastianelli ,
L. Bonnal ,
Y. Jaguelin-Peyraud  and
J. Noblet
D. Bastianelli*
Affiliation:
CIRAD, UMR SELMET, Baillarguet TA C-112/A, F-34398 Montpellier Cedex 05, France
L. Bonnal
Affiliation:
CIRAD, UMR SELMET, Baillarguet TA C-112/A, F-34398 Montpellier Cedex 05, France
Y. Jaguelin-Peyraud
Affiliation:
INRA, UMR1348 PEGASE, F-35590 Saint-Gilles, France
J. Noblet
Affiliation:
INRA, UMR1348 PEGASE, F-35590 Saint-Gilles, France
*
†E-mail: denis.bastianelli@cirad.fr
Get access

Abstract

Digestibility is a key parameter in the evaluation of feeds; however, the measurements on animals require heavy experimental trials, which are hardly feasible when large numbers of determinations are required – for example, in genetic studies. This experiment aimed at investigating the possibility to predict digestibility from NIRS spectra measured on faeces. A total of 196 samples were available from a digestibility experiment investigating the effects of age and genetic background of Large White pigs fed the same diet, rich in fibre (NDF=21.4% DM). Digestibility of dry matter (dDM), organic matter (dOM), nitrogen content (dN), energy (dE) and apparent digestible energy content (ADE) were calculated, as well as total N content of faeces (N). The faeces samples were submitted to reflectance NIRS analysis after freeze-drying and grinding. Calibration errors and validation errors were, respectively, 0.08 and 0.13% DM for total N in faeces, 0.97% and 1.08% for dDM, 0.79% and 1.04% for dOM, 1.04% and 1.47% for dN, 0.87% and 1.12% for dE and 167 and 213 kJ/kg DM for ADE. These results indicate that NIRS can account for digestibility differences due to animal factors, with an acceptable accuracy. NIRS appears to be a promising tool for large-scale evaluations of digestibility. It could also be used for the study of digestibility of different feeds, after appropriate calibration based on a wide range of feed types.

Keywords

pigfaecesdigestibilityNIR spectroscopy
Type
Research Article
Information
animal , Volume 9 , Supplement 5 , May 2015 , pp. 781 - 786
Copyright
© The Animal Consortium 2014 

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

Bastianelli, D 2013. NIRS as a tool to assess digestibility in feeds and feedstuffs. International Congress on Advancements in Poultry Production in the Middle East and African Countries. 21–25 October , Antalya, Turkey.Google Scholar
Bastianelli, D, Carré, B, Mignon-Grasteau, S, Bonnal, L and Davrieux, F 2007. Direct prediction of energy digestibility from poultry faeces using near infrared spectroscopy. In Proceedings of the 12th International Conference on Near Infrared Spectroscopy (ed. GR BurlingClaridge, SE Holroyd and RMW Sumner), pp. 626–629. NZ NIRS Society Inc., Hamilton, New Zealand.Google Scholar
Bastianelli, D, Bonnal, L, Juin, H, Mignon-Grasteau, S, Davrieux, F and Carré, B 2010. Prediction of the chemical composition of poultry excreta by near infrared spectroscopy. Journal of Near Infrared Spectroscopy 18, 69–77.Google Scholar
Boval, M, Coates, DB, Lecomte, P, Decruyenaere, V and Archimède, H 2004. Faecal near infrared reflectance spectroscopy (NIRS) to assess chemical composition, in vivo digestibility and intake of tropical grass by Creole cattle. Animal Feed Science and Technology 114, 19–29.Google Scholar
Carré, B, Lessire, M and Juin, H 2013. Prediction of metabolisable energy value of broiler diets and water excretion from dietary chemical analyses. Animal 7, 1246–1258.Google Scholar
Coates, DB and Dixon, RM 2011. Developing robust faecal near infrared spectroscopy calibrations to predict diet dry matter digestibility in cattle consuming tropical forages. Journal of Near Infrared Spectroscopy 19, 507–519.Google Scholar
Coulibaly, I, Métayer, JP, Chartrin, P, Mahaut, B, Bouvarel, I, Hogrel, P and Bastianelli, D 2013. La combinaison des informations issues des aliments et des fientes améliore la prédiction par SPIR de la digestibilité chez le poulet. In Dixièmes Journées de la Recherche Avicole et Palmipèdes à Foie Gras, pp. 640–644. Institut Technique de l’Aviculture, Paris, France.Google Scholar
Decruyenaere, V, Lecomte, P, Demarquilly, C, Aufrere, J, Dardenne, P, Stilmant, D and Buldgen, A 2009. Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): developing a global calibration. Animal Feed Science and Technology 148, 138–156.CrossRefGoogle Scholar
Le Goff, G and Noblet, J 2001. Comparative digestibility of dietary energy and nutrients in growing pigs and adult sows. Journal of Animal Science 79, 2418–2427.Google Scholar
Li, H, Tolleson, D, Stuth, J, Bai, K, Mo, F and Kronberg, S 2007. Faecal near infrared reflectance spectroscopy to predict diet quality for sheep. Small Ruminant Research 68, 263–268.Google Scholar
Meineri, G, Peiretti, PG and Masoero, G 2009. Appraisal of ingestion and digestibility in growing rabbits using near infrared reflectance spectroscopy (NIRS) of feeds and faeces. Italian Journal of Animal Science 8, 75–82.Google Scholar
Mignon-Grasteau, S, Muley, N, Bastianelli, D, Gomez, J, Sellier, N, Millet, N, Besnard, J, Hallouis, JM and Carré, B 2004. Wheat based regimen digestibility is highly heritable in growing chickens. Poultry Science 83, 860–867.Google Scholar
Naes, T, Isaksson, T, Fearn, T and Davies, T 2002. Validation. In Chapter 13 - Validation, In A user-friendly guide to multivariate calibration and classification. NIR Publications, Charlton, Chichester, UK.Google Scholar
Núñez-Sánchez, N, Martínez Marín, AL, Pérez Hernández, M, Carrion, D, Gómez Castro, G and Pérez Alba, LM 2012. Faecal near infrared spectroscopy (NIRS) as a tool to assess rabbit’s feed digestibility. Livestock Science 150, 386–390.Google Scholar
Noblet, J, Gilbert, H, Jaguelin-Peyraud, Y and Lebrun, T 2013. Evidence of genetic variability for digestive efficiency in the growing pig fed a fibrous diet. Animal 7, 1259–1264.CrossRefGoogle ScholarPubMed
Wold, S, Ruhe, A, Wold, H and Dunn, WJ 1984. The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. SIAM Journal on Scientific and Statistical Computing 5, 735–743.Google Scholar
Yang, Z, Han, L and Fan, X 2006. Rapidly estimating nutrient contents of fattening pig manure from floor scrapings by near infrared reflectance spectroscopy. Journal of Near Infrared Spectroscopy 14, 261–268.Google Scholar
Zijlstra, RT, Swift, ML, Wang, LF, Scott, TA and Edney, MJ 2011. Near infrared reflectance spectroscopy accurately predicts the digestible energy content of barley for pigs. Canadian Journal of Animal Science 91, 301–304.Google Scholar
Supplementary material: PDF

Bastianelli Supplementary Material

Figure S1

Download Bastianelli Supplementary Material(PDF)
PDF 40.2 KB