Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-28T06:39:12.776Z Has data issue: false hasContentIssue false

Introducing efficiency into the analysis of individual lifetime performance variability: a key to assess herd management

Published online by Cambridge University Press:  24 August 2010

L. Puillet*
Affiliation:
INRA, UMR 1048 SADAPT, F- 75231 Paris, France AgroParisTech, UMR 1048 SADAPT, F- 75231 Paris, France INRA, UMR 791 MoSAR, F-75231 Paris, France AgroParisTech, UMR 791 MoSAR, F-75231 Paris, France
O. Martin
Affiliation:
INRA, UMR 791 MoSAR, F-75231 Paris, France AgroParisTech, UMR 791 MoSAR, F-75231 Paris, France
D. Sauvant
Affiliation:
INRA, UMR 791 MoSAR, F-75231 Paris, France AgroParisTech, UMR 791 MoSAR, F-75231 Paris, France
M. Tichit
Affiliation:
INRA, UMR 1048 SADAPT, F- 75231 Paris, France AgroParisTech, UMR 1048 SADAPT, F- 75231 Paris, France
*
Get access

Abstract

Lifetime performance variability is a powerful tool for evaluating herd management. Although efficiency is a key aspect of performance, it has not been integrated into existing studies on the variability of lifetime performance. The goal of the present article is to analyse the effects of various herd management options on the variability of lifetime performance by integrating criteria relative to feed efficiency. A herd model developed for dairy goat systems was used in three virtual experiments to test the effects of the diet energy level, the segmentation of the feeding plan and the mean production potential of the herd on the variability of lifetime performance. Principal component analysis showed that the variability of lifetime performance was structured around the first axis related to longevity and production and the second related to the variables used in feed efficiency calculation. The intra-management variability was expressed on the first axis (longevity and production), whereas the inter-management variability was expressed on the second axis (feed efficiency) and was mainly influenced by the combination of the diet energy level and the mean production potential. Similar feed efficiencies were attained with different management options. Still, such combinations relied on different biological bases and, at the level of the individual, contrasting results were observed in the relationship between the obtained pattern of performance (in response to diet energy) and the reference pattern of performance (defined by the production potential). Indeed, our results showed that over-feeding interacted with the feeding plan segmentation: a high level of feeding plan segmentation generated a low proportion of individuals at equilibrium with their production potential, whereas a single ration generated a larger proportion. At the herd level, the diet energy level and the herd production potential had marked effects on production and efficiency due to dilution of fixed production costs (i.e. maintenance requirements). Management options led to similar production and feed efficiencies at the herd level while giving large contrasts in the proportions of individuals at equilibrium with their production potential. These results suggested that analysing individual variability on the basis of criteria related to production processes could improve the assessment of herd management. The herd model opens promising perspectives in studying whether individual variability represents an advantage for herd performance.

Type
Full Paper
Copyright
Copyright © The Animal Consortium 2010

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

Blanc, F, Bocquier, F, Agabriel, J, D’Hour, P, Chilliard, Y 2006. Adaptive abilities of the females and sustainability of ruminant livestock systems. A review. Animal Research 55, 489510.CrossRefGoogle Scholar
Coquillard, P, Hill, D 1997. Modélisation et simulation d’écosystèmes: des modèles déterministes aux simulations à événements discrets. In Collection Recherche en Ecologie, pp. 5051. Masson, Paris, France.Google Scholar
Coulon, JB, Perochon, L, Lescourret, F 1995. Pattern of milk production and live weight of dairy cows during their successive lactations. Annales de Zootechnie 44, 189199.CrossRefGoogle Scholar
Coulon, JB, Lescourret, F, Faye, B, Landais, E, Troccon, JL, Perochon, L 1993. A description of LASCAR, a database for studying the productive life of dairy cows. INRA Productions Animales 6, 151160.Google Scholar
Cournut, S, Dedieu, B 2004. A discrete events simulation of flock dynamics: a management application to three lambings in two years. Animal Research 53, 383403.CrossRefGoogle Scholar
Darnhofer, I 2009. Navigating the dynamics: resilient farms through adaptive management. In biodiversity and sustainable animal production systems. 60th Annual Meeting of the European Association for Animal Production, August 24–27, 2009, Barcelona, Spain, 289pp.Google Scholar
Duru, M, Cruz, P, Magda, D 2008. La Conduite des couverts prairiaux: source de flexibilité. In L’élevage en mouvement. Flexibilité et adaptation des exploitations d’herbivores (ed. B Dedieu, E Chia, B Leclerc, CH Moulin and M Tichit), pp. 5771. Editions QUAE, Versailles, France.Google Scholar
French Livestock Institute 2008. Hausse du prix des aliments, des pistes pour alléger les charges. Retrieved January 19, 2009, from http://www.inst-elevage.asso.fr/html1/spip.php?article16615Google Scholar
Friggens, NC, Newbold, JR 2007. Toward a biological basis for predicting nutrient partitioning: the dairy cow as an example. Animal 1, 8797.Google Scholar
Gibon, A 1994. Landscape preservation objectives and the sheep flock management in Meditarranean moutains. In Proceedings of a Meeting Held within the Technical Consultation of the FAO-CIHEAM Network on Cooperative Sheep and Goat Research, June 19–22, 1994, Thessaloniki, Greece, 188–193pp.Google Scholar
Guérin, G, Bellon, S 1990. Analysis of the functions of pastoral areas in forage systems in the Mediterranean region. Etudes et Recherches sur les Systèmes Agraires et le Développement 16, 147156.Google Scholar
Landais, E 1987. Recherches sur les systèmes d’élevage. Questions et perspectives. Document de travail INRA SAD, Versailles, 75pp.Google Scholar
Lasseur, J, Landais, E 1992. Mieux valoriser l’information contenue dans les carnets d’agnelages pour évaluer des performances et des carrières de reproduction en élevage ovin-viande. INRA Productions Animales 5, 4358.Google Scholar
Lee, GJ, Atkins, KD, Sladek, MA 2009. Heterogeneity of lifetime reproductive performance, its components and associations with wool production and liveweight of Merino ewes. Animal Production Science 49, 624629.Google Scholar
Lormore, MJ, Galligan, DT 2001. Economics of atypical lactation. Journal of Dairy Science 84, E212E215.CrossRefGoogle Scholar
Mellado, M, Olivares, L, Lopez, R, Mellado, J 2005. Influence of lactation, liveweight and lipid reserves at mating on reproductive performance of grazing goats. Journal of Animal and Veterinary Advances 4, 420423.Google Scholar
Moulin, CH 1993. Performances animales et pratiques d’élevage en Afrique Sahélienne. La diversité du fonctionnement des troupeaux de petits ruminants dans la commune rurale de NDiagné (Sénégal). PhD thesis, INA-PG, Paris, France.Google Scholar
Peyraud, JL, Le Gall, A, Delaby, L, Faverdin, P, Brunschwig, P, Caillaud, D 2009. Quels systèmes fourragers et quels types de vaches laitières demain? Fourrages 197, 4770.Google Scholar
Puillet, L, Martin, O, Tichit, M, Sauvant, D 2008. Simple representation of physiological regulations in a model of lactating female: application to the dairy goat. Animal 2, 235246.Google Scholar
Puillet, L, Martin, O, Sauvant, D, Tichit, M 2010. An individual-based model to simulate individual variability and herd long term performance. Animal (in press).CrossRefGoogle Scholar
Sauvant, D, Giger-Reverdin, S, Meschy, F 2007. Alimentation des caprins. In Alimentation des bovins, ovins et caprins. Besoins des animaux – Valeurs des aliments (ed. INRA), pp. 137148. Editions QUAE, Versailles, France.Google Scholar
Thénard, V, Trommenschlager, JM, Catteau, M 2003. Description of dairy cows careers: herd study during 10 years in an experimental farm. In Proceedings of the 10e Rencontres autour des Recherches sur les Ruminants, December 3–4, Paris, France, 115pp.Google Scholar
Tichit, M, Hubert, B, Doyen, L, Genin, D 2004. A viability model to assess the sustainability of mixed herds under climatic uncertainty. Animal Research 53, 405417.Google Scholar
Tichit, M, Ingrand, S, Moulin, CH, Cournut, S, Lasseur, J, Dedieu, B 2008. Capacités d’adaptation du troupeau: la diversité des trajectoires productives est-elle un atout? In L’élevage en mouvement. Flexibilité et adaptation des exploitations d’herbivores (ed. B Dedieu, E Chia, B Leclerc, CH Moulin and M Tichit), pp. 119133. Editions Quae, Versailles, France.Google Scholar
Vandehaar, MJ 1998. Efficiency of nutrient use and relationship to profitability on dairy farms. Journal of Dairy Science 81, 272282.Google Scholar