Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-14T17:27:43.038Z Has data issue: false hasContentIssue false

Modelling interactions between farmer practices and fattening pig performances with an individual-based model

Published online by Cambridge University Press:  16 November 2017

A. Cadéro*
Affiliation:
IFIP – Institut du porc, 35651 Le Rheu, France PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
A. Aubry
Affiliation:
IFIP – Institut du porc, 35651 Le Rheu, France
L. Brossard
Affiliation:
PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
J. Y. Dourmad
Affiliation:
PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
Y. Salaün
Affiliation:
IFIP – Institut du porc, 35651 Le Rheu, France
F. Garcia-Launay
Affiliation:
PEGASE, Agrocampus Ouest, INRA, 35590 Saint-Gilles, France
*
Get access

Abstract

European pig production continues to encounter economic and environmental challenges. To address these issues, methods have been developed to assess performances of pig production systems. Recent studies indicate that considering variability in performances among pigs improves the accuracy and reliability of results compared with modelling an average animal. Our objective was to develop a pig fattening unit model able to (i) simulate individual pig performances, including their variability in interaction with farmers’ practices and management, and (ii) assess their effects on technical, economic and environmental performances. Farmer practices included in the model were chosen from a typology generated from on-farm surveys focused on batch management, pig allocation to pens, pig feeding practices, practices of shipping to the slaughterhouse, and management of the remaining pigs. Pigs are represented using an individual-based model adapted from the InraPorc® model. To illustrate the model’s abilities, four scenarios were simulated that combine two feed rationing plans (ad libitum, restricted to 2.5 kg/day) and two feed sequence plans (two-phase, 10-phase). Analysis of variance was performed on the simulated technical, economic and environmental indicators (calculated via Life Cycle Assessment). The feed rationing plan and feed sequence plan significantly affected all indicators except for the premium per pig, for which the feed sequence plan did not have a significant effect. The ‘restricted 10-phase’ scenario maximised gross margin of the fattening unit (14.2 €/pig) and minimised environmental impacts per kg of pig produced. In contrast, the ‘ad libitum two-phase’ scenario generated the lowest margin (8.20 €/pig) and the highest environmental impacts. The model appears to be a promising tool to assess effects of farmers’ practices, pig characteristics and farm infrastructure on technical, economic and environmental performances of the fattening unit, and to investigate the potential of improvement. However, further work is needed, based on virtual experiments, in order to evaluate the effects of a larger diversity of practices.

Type
Research Article
Copyright
© The Animal Consortium 2017 

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

Andersen, JM, Poulsen, HD, Børsting, CF, Rom, HB, Sommer, SG and Hutchings, NJ 2001. ‘Ammoniakemission fra landbruget siden midten af 80’erne [Ammonia emission from agriculture since the mid eighties. In Danish with summary in English.]. Report 353, National Environmental Research Institute, Roskilde, Denmark.Google Scholar
Andretta, I, Pomar, C, Rivest, J, Pomar, J, Lovatto, PA and Neto, JR 2014. The impact of feeding growing-finishing pigs with daily tailored diets using precision feeding techniques on animal performance, nutrient utilization, and body and carcass composition. Journal of Animal Science 92, 39253936.Google Scholar
Aubry, A, Lescot, M, Cadéro, A, Garcia, F, Correge, I and Quiniou, N 2016. Within-herd final management of batches for optimal marketing of slaughter pigs: analysis of strategies and associated economic issues. Journées Recherche Porcine 48, 225230.Google Scholar
Bourdon, D, Dourmad, JY and Henry, H 1995. Réduction des rejets azotés chez le porc en croissance par la mise en œuvre de l’alimentation multiphase, associée à l’abaissement du taux azoté. Journées de la Recherche Porcine, Paris 27, 269278.Google Scholar
Brossard, L, Dourmad, JY, Rivest, J and van Milgen, J 2009. Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy. Animal 3, 11141123.CrossRefGoogle ScholarPubMed
Brossard, L, Vautier, B, van Milgen, J, Salaun, Y and Quiniou, N 2014. Comparison of in vivo and in silico growth performance and variability in pigs when applying a feeding strategy designed by simulation to control the variability of slaughter weight. Animal Production Science 54, 19391945.Google Scholar
Chardon, X, Rigolot, C, Baratte, C, Espagnol, S, Raison, C, Martin-Clouaire, R, Rellier, J-P, Le Gall, A, Dourmad, JY, Piquemal, B, Leterme, P, Paillat, JM, Delaby, L, Garcia, F, Peyraud, JL, Poupa, JC, Morvan, T and Faverdin, P 2012. MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops. Animal 6, 17111721.CrossRefGoogle Scholar
Dammgen, U and Hutchings, NJ 2008. Emissions of gaseous nitrogen species from manure management: a new approach. Environmental Pollution 154, 488497.Google Scholar
Douglas, B, Martin, M, Ben, B and Steve, W 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67, 148 .Google Scholar
Dourmad, JY, Sève, B, Latimier, P, Boisen, S, Fernandez, J, van der Peet-Schwering, C and Jongbloed, AW 1999. Nitrogen consumption, utilisation and losses in pig production in France, the Netherlands and Denmark. Livestock Production Science 58, 261264.CrossRefGoogle Scholar
Ferguson, NS 2015. Commercial application of integrated models to improve performance and profitability in finishing pigs. In Nutritional modelling for pigs and poultry (ed. NK Sakomura, RM Gous, I Kyriazakis and L Hauschild), pp. 141156, Wallingford, Oxfordshire, UK: CABI.Google Scholar
Garcia-Launay, F, van der Werf, HMG, Nguyen, TTH, Le Tutour, L and Dourmad, JY 2014. Evaluation of the environmental implications of the incorporation of feed-use amino acids in pig production using life cycle assessment. Livestock Science 161, 158175.Google Scholar
Garcia-Launay, F, Wilfart, A, Dusart, L, Nzalli, C, Gaudré, D, Dronne, Y and Espagnol, S 2016. Multi-objective formulation is an efficient methodology to reduce environmental impacts of pig feeds. In Proceedings of 10th International Conference on Life Cycle Assessment in the Agri-Food Sector, Dublin, Ireland, pp. 539–546.Google Scholar
IFIP 2016. Porc Performances 2015 – Résultats de gestion des élevages de porcs. IFIP, Le Rheu, France.Google Scholar
InraPorc® 2006. A model and decision support tool for the nutrition of growing pigs. INRA – UMR SENAH, Saint-Gilles, France.Google Scholar
IPCC 2006. Emissions from livestock and manure management. In Guidelines for national greenhouse gas inventories: agriculture, forestry and other land use, volume 4, Prepared by the National Greenhouse Gas Inventories Programme, (ed. HS Eggleston, L Buendia, K Miwa, T Ngara and K Tanabe), Japan, pp. 10.1-10.87.Google Scholar
Koch, P and Salou, T 2015. AGRIBALYSE®: methodological report – Version 1.2. ADEME, Angers, France. 385pp.Google Scholar
Lurette, A, Belloc, C, Touzeau, S, Hoch, T, Seegers, H and Fourichon, C 2008. Modelling batch farrowing management within a farrow-to-finish pig herd: influence of management on contact structure and pig delivery to the slaughterhouse. Animal 2, 105116.Google Scholar
McAuliffe, GA, Chapman, DV and Sage, CL 2016. A thematic review of life cycle assessment (LCA) applied to pig production. Environmental Impact Assessment Review 56, 1222.Google Scholar
Monteiro, ANTR, Garcia-Launay, F, Brossard, L, Wilfart, A and Dourmad, JY 2016. Effect of feeding strategy on environmental impacts of pig fattening in different contexts of production: evaluation through life cycle assessment. Journal of Animal Science 94, 48324847.Google Scholar
Morel, PCH, Sirisatien, D and Wood, GR 2012. Effect of pig type, costs and prices, and dietary restraints on dietary nutrient specification for maximum profitability in grower-finisher pig herds: a theoretical approach. Livestock Science 148, 255267.Google Scholar
Mullan, BP, Moore, KL, Payne, HG, Trezona-Murray, M, Pluske, JR and Kim, JC 2011. Feed efficiency in growig pigs – what’s possible ? Recent Advances in Animal Nutrition 18, 1722.Google Scholar
Nemecek, T and Kägi, T 2007. Life cycle inventories of Swiss and European agricultural production systems. Final report ecoinvent, volume 2.0, no. 15. Agroscope Reckenholz-Taenikon Research Station ART. Swiss Centre for Life Cycle Inventories, Zurich and Dübendorf, Switzerland.Google Scholar
Nguyen, TLT, Hermansen, JE and Mogensen, L 2010. Fossil energy and GHG saving potentials of pig farming in the EU. Energy Policy 38, 25612571.CrossRefGoogle Scholar
Nguyen, TLT, Hermansen, JE and Mogensen, L 2012. Environmental costs of meat production: the case of typical EU pork production. Journal of Cleaner Production 28, 168176.CrossRefGoogle Scholar
Niemi, JK, Sevon-Aimonen, ML, Pietola, K and Stalder, KJ 2010. The value of precision feeding technologies for grow-finish swine. Livestock Science 129, 1323.Google Scholar
Pomar, C, Kyriazakis, I, Emmans, GC and Knap, PW 2003. Modeling stochasticity: dealing with populations rather than individual pigs. Journal of Animal Science 81, E178E186.Google Scholar
Pomar, C, Pomar, J, Dubeau, F, Joannopoulos, E and Dussault, JP 2014. The impact of daily multiphase feeding on animal performance, body composition, nitrogen and phosphorus excretions, and feed costs in growing-finishing pigs. Animal 8, 704713.Google Scholar
R Development Core Team 2015. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Rigolot, C, Espagnol, S, Pomar, C and Dourmad, JY 2010a. Modelling of manure production by pigs and NH3, N2O and CH4 emissions. Part I: animal excretion and enteric CH4, effect of feeding and performance. Animal 4, 14011412.Google Scholar
Rigolot, C, Espagnol, S, Robin, P, Hassouna, M, Beline, F, Paillat, JM and Dourmad, JY 2010b. Modelling of manure production by pigs and NH3, N2O and CH4 emissions. Part II: effect of animal housing, manure storage and treatment practices. Animal 4, 14131424.Google Scholar
Sommer, SG, Maahn, M, Poulsen, HD, Hjorth, M and Sehested, J 2008. Interactions between phosphorus feeding strategies for pigs and dairy cows and separation efficiency of slurry. Environmental Technology 29, 7580.Google Scholar
van Milgen, J, Valancogne, A, Dubois, S, Dourmad, JY, Seve, B and Noblet, J 2008. InraPorc: a model and decision support tool for the nutrition of growing pigs. Animal Feed Science and Technology 143, 387405.Google Scholar
Vautier, B, Quiniou, N, van Milgen, J and Brossard, L 2013. Accounting for variability among individual pigs in deterministic growth models. Animal 7, 12651273.Google Scholar
Weidema, BP, Bauer, C, Hischier, R, Mutel, C, Nemecek, T, Reinhard, J, Vadenbo, CO and Wernet, G 2013. Overview and methodology. Data quality guideline for the ecoinvent database version 3. Ecoinvent Report 1, volume 3. The ecoinvent Centre, St. Gallen.Google Scholar
Wilfart, A, Espagnol, S, Dauguer, S, Tailleur, A, Gac, A and Garcia-Launay, F 2016. ECOALIM: a dataset of environmental impacts of feed ingredients used in French animal production. Plos One 11, e0167343.Google Scholar
Supplementary material: File

Cadéro et al supplementary material

Figure S1 and Tables S1-S4

Download Cadéro et al supplementary material(File)
File 112.3 KB