SUMMARY
Submitted 2020-07-20 | Accepted 2020-08-31 | Available 2020-12-01https://doi.org/10.15414/afz.2020.23.mi-fpap.258-264The dichotomy between developed and developing countries was observed not only in asymmetric human population growth, but also in increasing demand for animal products revolving around poultry and pigs in developing World. Modern livestock industry has adopted innovative technologies to improve the biological efficiency of animal production and feeding, and for this purpose different mathematical models have been applied. In this review, the authors summarize the growth models, briefly introduce the principles of precision feeding and provide evidence that models are key elements of these systems. Modelling is an excellent tool to help in understanding and to predict the animal’s response to different farm conditions. Models comprise of equations set describing nutrient flows and animal response. They are essential elements of precision livestock farming system being the basis of the decision support tool since, from yesterday’s data, they provide today what happens tomorrow. Precision farming adopts real-time monitoring systems collecting serial data about individual or group of animals. However, without a well-defined goal-oriented data process, data by itself are not useful to farmers. Available and newly recorded data can be converted to valuable information for management purposes through models applied in farming systems. Nutritional models are integrated part of those systems; therefore, growth modelling is a key tool to improve the efficiency and sustainability of livestock production systems.Keywords: precision feeding, mathematical models, pig, broiler, production efficiencyReferencesBaldwin, R. L. and Gill, M. (1987). Metabolism of the lactating cow: I. Animal elements of a mechanistic model. Journal of Dairy Research, 54, 77-105. https://doi.org/10.1017/S002202990002522XBanhazi, T. M. et al. (2012). Precision Livestock Farming: Precision feeding technologies and sustainable livestock production. International Journal of Agricultural and Biological Engineering, 5(4), 54-61. http://dx.doi.org/10.3965/j.ijabe.20120504.006Berckmans, D. (2015). Precision livestock farming technologies for welfare management in intensive livestock systems. Revue scientifique et technique (International Office of Epizootics), 33(1),189-196. Retrieved August 15, 2020 from https://tice.agrocampus-ouest.fr/pluginfile.php/55014/mod_resource/content/17/res/u324_Berckmans_RevSciTechOffIntEpiz.PDFBerger, Q. et al. (2019). Using high throughput phenotyping of growth and feed intake to improve adaptation of chickens to sustainable diets. 11th European Symposium on Poultry Genetics, 23–25 October 2019, Prague, Czech Republic. Retrieved August 15, 2020 from https://hal.inrae.fr/hal-02737886Black, J. L. (2014). Brief history and future of animal simulation models for science and application. Animal Production Science, 54, 1883-1895. http://dx.doi.org/10.1071/AN14650Black, J. L. et al. (1986). Simulation of energy and amino acid utilisation in the pig. Research and Development in Agriculture, 3, 121-145. Retrieved August 15, 2020 from https://www.researchgate.net/publication/273524971_Simulation_of_energy_and_amino_acid_utilisation_in_pigs.Coles, L. T. et al. (2013). A model to predict the ATP equivalents of macronutrients absorbed from food. Food & Function, 4, 432-442. https://doi.org/10.1039/C2FO30239Jde Lange, C. F. M. and Schreurs, H. (1995). Principles of model applications. In P. J. Moughan, M. W. A. Verstegen and M. I. Visser-Reyneveld (Eds.), Modelling growth in the pig. Wageningen Pers, Wageningen, (pp. 187-208).de Lange, C. F. M. et al. (2001). Application of pig growth models in commercial pork production. Canadian Journal of Animal Science, 81, 1-8. https://doi.org/10.4141/A00-006Dukhta, G. et al. (2019). Use of a dynamic mechanistic broiler model to reduce environmental footprint. 26th International Conference KRMIVA 2019, 5-7 June 2019, Opatija, Croatia. Retrieved August 15, 2020 from https://www.feed-a-gene.eu/sites/default/files/documents/dukhta_2019_KRMIVA_broiler_model_powerpoint.pdfDumas, A. et al. (2008). Mathematical modelling in animal nutrition: a centenary review. The Journal of Agricultural Science, 146(2), 123-142. https://doi.org/10.1017/S0021859608007703Dusart, L. and Meda, B. (2017). Responsable alimentation des volailles et durabilité des systemes. In L’Alimentation de Precision en Poulet de Chair. 12èmes JRA-JRFG, France, Tours, April 2017.Emmans, G. C. (1981). A model of the growth and feed intake of ad libitum fed animals, particularly poultry. In: Hillyer, G.M. et al. (Eds) Computers in Animal Production. Thames Ditton, UK: Occasional Publication No 5., British Society of Animal Production, pp. 103–110. https://doi.org/10.1017/S0263967X00003761Emmans, G. C. and Fisher, C. (1986). Problems in nutritional theory. In Fisher, C. and Boorman, K.N. (Eds.) Nutrient Requirements of Poultry and Nutritional Research. Oxford, UK: Butterworths, 9-39.Emmans, G. C. (1989). The growth of turkeys. Recent advances in turkey science.France, J. et al. (1987). A model of nutrient utilization and body composition in beef cattle. Animal Production, 44, 371-385. https://doi.org/10.1017/S0003356100012307France, J. and Thornley, J. H. (2007). Mathematical models in agriculture: quantitative methods for the plant, animal and ecological sciences. Wallingford, UK: CABI.Gerrits, W. J. J. et al. (1997). Description of a model integrating protein and energy metabolism in preruminant calves. Journal of Nutrition, 127, 1229-1242. https://doi.org/10.1093/jn/127.6.1229Gill, M. et al. (1984). Simulation of the metabolism of absorbed energy-yielding nutrients in young sheep. British Journal of Nutrition, 52, 621-649. https://doi.org/10.1093/jn/117.1.105Halas, V. et al. (2004). Modelling of nutrient partitioning in growing pigs to predict their anatomical body composition. 1. Model description. British Journal of Nutrition, 92: 707-723. http://dx.doi.org/10.1079/BJN20041237Halas, V. et al. (2017). Preliminary model to predict P-requirement of growing pigs. In EAAP, scientific committee (Ed) Book of Abstracts of the 68th Annual Meeting of the European Federation of Animal Science, Wageningen, the Netherlands: Wageningen Academic Publishers, (pp. 320-320). https://doi.org/10.3920/978-90-8686-859-9Halas, V. et al. (2018). Models of feed utilization and growth for monogastric animals. In: P. J. Moughan et al. (Eds.) Feed Evaluation Science, Wageningen, the Netherlands: Wageningen Academic Publishers, (pp. 423-456).Hauschild, L. et al. (2010). Systematic comparison of the empirical and factorial methods used to estimate the nutrient requirements of growing pigs. Animal, 4(5), 714–723. https://doi.org/10.1017/S1751731109991546Johnston, S. A. and Gous, R. (2006). Modelling egg production in laying hens. In Johnston S.A. et al. (Eds.) Mechanistic Modelling in Pig and Poultry Production, Wallingford, UK: CAB International, (pp. 229-259).Kebreab, E. et al. (2009). Development and evaluation of a dynamic model of calcium and phosphorus flows in layers. Poultry Science, 88(3), 680-689. https://doi.org/10.3382/ps.2008-00157NRC. (2012). Nutrient Requirements of Swine. Eleventh Revised Edition. National Academic Press, Washington, D.C. 20418 USA.Meda, B. et al. (2015). INAVI: a practical tool to study the influence of nutritional and environmental factors on broiler performance. In Sakomura, N. K. et al. (Eds.), Nutritional Modelling for Pigs and Poultry, Raleigh, NC, USA: CAB International, (pp. 106-124). https://doi.org/10.1079/9781780644110.0106Morris, T. R. (2006). An introduction to modelling in the animal sciences. Mechanistic Modelling in Pig and Poultry Production, 1-5.Moughan, P. J. et al. (1987). Description and validation of a model simulating growth in the pig (20-90 kg liveweight). New Zealand Journal of Agricultural Research, 30, 481-489. https://doi.org/10.1080/00288233.1987.10417960Lizardo, R. et al. (2002). A nutritional model of fatty acid composition in the growing-finishing pig. Livestock Production Science, 75, 167-182. https://doi.org/10.1016/S0301-6226(01)00312-8OECD-FAO. (2017). "Meat", in OECD-FAO Agricultural Outlook 2017-2026, OECD Publishing, Paris, https://doi.org/10.1787/agr_outlook-2017-10-en.Oviedo-Rondón, E. O. (2015). Model Applications in Poultry Production and Nutrition. In Sakomura, N. K. et al. (Eds.), Nutritional Modelling for Pigs and Poultry, Raleigh, NC 27695, USA, CAB International, (pp. 125-140). https://doi.org/10.1079/9781780644110.0125Pomar, C. et al. (2009). Applying precision feeding techniques in growing-finishing pig operations. Revista Brasileira de Zootecnia, 38, 226-237. https://doi.org/10.1590/S1516-35982009001300023Pomar, C. et al. (2011). Precision feeding can significantly reduce feeding cost and nutrient excretion in growing animals. In D. Sauvant, J. Van Milgen, P. Faverdin and N. Friggens (Eds.), Modelling Nutrient Digestion and Utilisation in Farm Animals. Wageningen Academic Publishers, Wageningen, the Netherlands.Pomar, C. and Remus, A. (2019). Precision pig feeding: a breakthrough toward sustainability. Animal Frontiers, 9(2), 52-59. https://doi.org/10.1093/af/vfz006Pomar, C. et al. (2019). 18: Precision livestock feeding, principle and practice. In W. H. Hendriks, M. W. A. Verstegen and L. Babinszky (Eds.), Poultry and pig nutrition: Challenges of the 21st century. Wageningen Academic Publishers, (pp. 89-95). https://doi.org/10.3920/978-90-8686-884-1_18Sauvant, D. (1994). Modelling homeostatic and homeorhetic regulations in lactating animals. Livestock Production Science, 39(1), 105-113. https://doi.org/10.1016/0301-6226(94)90162-7Sifri, M. 1997. Precision Nutrition for Poultry. The Journal of Applied Poultry Research, 6(4), 461. https://doi.org/10.1093/japr/6.4.461Schulz, A. R. (1978). Simulation of energy metabolism in the simple-stomached animal. British Journal of Nutrition, 39, 235-254. https://doi.org/10.1079/BJN19780034van Milgen, J. (2002). Modeling biochemical aspects of energy metabolism in mammals. Journal of Nutrition, 132, 3195-3202. https://doi.org/10.1093/jn/131.10.3195van Milgen, J. et al. (2008). InraPorc: A model and decision support tool for the nutrition of growing pigs. Animal Feed Science and Technology, 143, 387-405. https://doi.org/10.1016/j.anifeedsci.2007.05.020Whittemore, C. T. (1987). Simulation modelling: the prediction of growth response to nutrient supply. In: C. T. Whittemore (Ed.), Elements of Pig Science. Harlow, England, UK: Longmann Scientific & Technical, pp. 140-175.Whittemore, C. T. and Fawcett, R. H. (1974). Model responses of the growing pig to the dietary intake of energy and protein. Animal Production, 19, 221-231. https://doi.org/10.1017/S0003356100022789Whittemore, C. T. and Fawcett, R. H. (1976). Theoretical aspects of a flexible model to simulate protein and lipid growth in pigs. Animal Production, 22, 87-96. https://doi.org/10.1017/S0003356100035455Zuidhof, M. J. et al. (2018). Precision feeding of broiler breeders. Zootechnika International. Retrieved July 15, 2020 from https://zootecnicainternational.com/featured/precision-feeding-broiler-breeders/Zuidhof, M. J. (2020). Precision livestock feeding: matching nutrient supply with nutrient requirements of individual animals. Journal of Applied Poultry Research, 29(1), 11-14. https://doi.org/10.1016/j.japr.2019.12.009