Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T18:35:59.091Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic model of milk production responses to grass-based diet variations during grazing and indoor housing

Published online by Cambridge University Press:  28 January 2015

A. -L. JACQUOT ,
L. DELABY ,
D. POMIÉS ,
G. BRUNSCHWIG  and
R. BAUMONT
A. -L. JACQUOT*
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France Clermont Université, VetAgro Sup, UMR1213 Herbivores, BP 10448, F-63000, Clermont-Ferrand, France INRA, UMR1348 Pegase, F-35590 Saint-Gilles, France Agrocampus Ouest, UMR1348 Pegase, F-35000 Rennes, France
L. DELABY
Affiliation:
INRA, UMR1348 Pegase, F-35590 Saint-Gilles, France Agrocampus Ouest, UMR1348 Pegase, F-35000 Rennes, France
D. POMIÉS
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France Clermont Université, VetAgro Sup, UMR1213 Herbivores, BP 10448, F-63000, Clermont-Ferrand, France
G. BRUNSCHWIG
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France Clermont Université, VetAgro Sup, UMR1213 Herbivores, BP 10448, F-63000, Clermont-Ferrand, France
R. BAUMONT
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France Clermont Université, VetAgro Sup, UMR1213 Herbivores, BP 10448, F-63000, Clermont-Ferrand, France
*
*To whom all correspondence should be addressed. Email: anne-lise.jacquot@agrocampus-ouest.fr
Get access Rights & Permissions [Opens in a new window]

Summary

Dairy cow systems based on grassland utilization are characterized by a variation of harvested forage quality from 1 year to another and a fluctuation of grass availability and quality during the pasture season. Consequently, the energy supplied by the diet – i.e., concentrates plus hay or silage in winter and grazing in summer, may not always match animal requirements. A modelling approach enables a representation of the complex relationships between the cow and pasture as they interact. A dynamic model of intake and milk production, focused on grassland utilization by the dairy cow, has been developed. The model operates in a deterministic fashion with a daily time step and is capable of dealing with a day-to-day variation in grass availability and quality at grazing as well as a constant feeding regime during the winter. The model has been built based on the theory that milk production is a result of (i) the energy requirements defined by the potential milk production and physiological status of dairy cows; (ii) the variation of energy supply by the diet; (iii) the ability of dairy cows to mobilize or store body reserves. The model was validated by comparing milk production predictions with experimental data (two groups of dairy cows in the winter time and one group at grazing). The model demonstrates a satisfactory range of accuracy (root-mean-square deviation equal to 1·8, 2·1 and 1·4 kg/cow/day). Model validations indicate that milk production predictions are sensitive to the diet offered (forage, grass and concentrate supply) and depend on dairy cow characteristics and their requirements (pMP). This model can be connected to a grass growth model in order to develop whole farm simulations.

Type
Modelling Animal Systems Research Papers
Information
The Journal of Agricultural Science , Volume 153 , Issue 4 , May 2015 , pp. 689 - 707
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

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

REFERENCES

Auldist, M. J., Marett, L. C., Greenwood, J. S., Hannah, M., Jacobs, J. L. & Wales, W. J. (2013). Effects of different strategies for feeding supplements on milk production responses in cows grazing a restricted pasture allowance. Journal of Dairy Science 96, 1218–1231.Google Scholar
Bargo, F., Muller, L. D., Kolver, E. S. & Delahoy, J. E. (2003). Invited review: production and digestion of supplemented dairy cows on pasture. Journal of Dairy Science 86, 1–42.Google Scholar
Baudracco, J., Lopez-Villalobos, N., Holmes, C. W., Comeron, E. A., Macdonald, K. A., Barry, T. N. & Friggens, N. C. (2012). e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding. Animal 6, 980–993.Google Scholar
Baumont, R., Cohen-Salmon, D., Prache, S. & Sauvant, D. (2004). A mechanistic model of intake and grazing behaviour in sheep integrating sward architecture and animal decisions. Animal Feed Science and Technology 112, 5–28.CrossRefGoogle Scholar
Baumont, R., Dulphy, J. -P., Sauvant, D., Meschy, F., Aufrère, J. & Peyraud, J. -L. (2007). Valeur alimentaire des fourrages et des matières premières: tables et prévision. In Alimentation des Bovins, Ovins et Caprins - Besoins des Animaux - Valeur des Aliments - Tables INRA 2007 (Ed. Agabriel, J.), pp. 150–180. Paris, France: Editions Quae.Google Scholar
Bernuès, A., Ruiz, R., Olaizola, A., Villalba, D. & Casasus, I. (2011). Sustainability of pasture-based livestock farming systems in the European Mediterranean context: synergies and trade-offs. Livestock Science 139, 44–57.CrossRefGoogle Scholar
Beukes, P. C., Palliser, C. C., Macdonald, K. A., Lancaster, J. A. S., Levy, G., Thorrold, B. S. & Wastney, M. E. (2008). Evaluation of a whole-farm model for pasture-based dairy systems. Journal of Dairy Science 91, 2353–2360.Google Scholar
Bocquier, F. & González-García, E. (2009). Sustainability of ruminant agriculture in the new context: feeding strategies and features of animal adaptability into the necessary holistic approach. Animal 4, 1258–1273.Google Scholar
Brun-Lafleur, L., Delaby, L., Husson, F. & Faverdin, P. (2010). Predicting energy x protein interaction on milk yield and milk composition in dairy cows. Journal of Dairy Science 93, 4128–4143.Google Scholar
Brun-Lafleur, L., Cutullic, E., Faverdin, P., Delaby, L. & Disenhaus, C. (2013). An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows. Animal 7, 1332–1343.CrossRefGoogle ScholarPubMed
Buttchereit, N., Stamer, E., Junge, W. & Thaller, G. (2010). Evaluation of five lactation curve models fitted for fat: protein ratio of milk and daily energy balance. Journal of Dairy Science 93, 1702–1712.Google Scholar
Chardon, X., Rigolot, C., Baratte, C., Espagnol, S., Raison, C., Martin-Clouaire, R., Rellier, J. P., Le Gall, A., Dourmad, J. Y., Piquemal, B., Leterme, P., Paillat, J. M., Delaby, L., Garcia, F., Peyraud, J. L., Poupa, J. C., Morvan, T. & Faverdin, P. (2012). MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops. Animal 6, 1711–1721.CrossRefGoogle Scholar
Chilliard, Y., Remond, B., Agabriel, J., Robelin, J. & Verite, R. (1987). Variations du contenu digestif et des réserves corporelles au cours du cycle gestation–lactation. Bulletin Technique C.R.Z.V. Theix 70, 117–131.Google Scholar
Coulon, J. B. & Rémond, B. (1991). Variations in milk output and milk protein-content in response to the level of energy supply to the dairy-cow – a review. Livestock Production Science 29, 31–47.Google Scholar
Cros, M. -J., Duru, M., Garcia, F., Grasset, M., Legall, A., Martin-Clouaire, R., Peyre, D., Delaby, L., Fiorelli, J. -L. & Peyraud, J. -L. (2000). Evaluation d'un simulateur de stratégies de pâturage de vaches laitières. 3R (Rencontres autour des Recherches sur les Ruminants) 7, 333–336.Google Scholar
Delaby, L., Faverdin, P., Michel, G., Disenhaus, C. & Peyraud, J. L. (2009). Effect of different feeding strategies on lactation performance of Holstein and Normande dairy cows. Animal 3, 891–905.CrossRefGoogle ScholarPubMed
Delaby, L., Leurent, S., Gallard, Y. & Schmitt, T. (2010). Effet de la race, de la parité, du potentiel laitier et de l’état au vêlage sur l’évolution de l’état corporel des vaches laitières au cours de la lactation. 3R (Rencontres autour des Recherches sur les Ruminants) 17, 260.Google Scholar
Delaby, L., Peyraud, J. L. & Faverdin, P. (2001). Pâtur'IN: le pâturage des vaches laitières assistés par ordinateur. Fourrages 167, 385–398.Google Scholar
Delaby, L., Peyraud, J. -L., Foucher, N. & Michel, G. (2003 a). The effect of two contrasting grazing managements and level of concentrate supplementation on the performance of grazing dairy cows. Animal Research 52, 437–460.Google Scholar
Delaby, L., Peyraud, J. L. & Delagarde, R. (2003 b). Is it necessary to supplement dairy cows at grazing? INRA Productions Animales 16, 183–195.CrossRefGoogle Scholar
Delagarde, R., Faverdin, P., Baratte, C. & Peyraud, J. L. (2011 a). GrazeIn: a model of herbage intake and milk production for grazing dairy cows. 2. Prediction of intake under rotational and continuously stocked grazing management. Grass and Forage Science 66, 45–60.Google Scholar
Delagarde, R., Valk, H., Mayne, C. S., Rook, A. J., González-Rodríguez, A., Baratte, C., Faverdin, P. & Peyraud, J. L. (2011 b). GrazeIn: a model of herbage intake and milk production for grazing dairy cows. 3. Simulations and external validation of the model. Grass and Forage Science 66, 61–77.Google Scholar
Dillon, P., Crosse, S., Stakelum, G. & Flynn, F. (1995). The effect of calving date and stocking rate on the performance of spring-calving dairy cows. Grass and Forage Science 50, 286–299.CrossRefGoogle Scholar
Dillon, P., Crosse, S. & O'Brien, B. (1997). Effect of concentrate supplementation of grazing dairy cows in early lactation on milk production and milk processing quality. Irish Journal of Agricultural and Food Research 36, 145–159.Google Scholar
Dulphy, J., Faverdin, P. & Jarrige, R. (1989). Feed intake: the fill unit systems. In Ruminant Nutrition: Recommended Allowances and Feed Tables (Ed. Jarrige, R.), pp. 61–71. Paris, France: INRA & John Libbey Eurotext.Google Scholar
Farruggia, A., Pomies, D., Bethier, D., Troquier, O., Le Bec, G., Paccard, P., Baumont, B. & Pradel, P. (2010). Balance between production and biodiversity in two upland dairy grazing systems. In Grassland in a Changing World: Proceedings of the 23rd General Meeting of the European Grassland Federation (Eds Schnyder, H., Isselstein, J., Taube, F., Auerswald, K., Schellberg, J., Wachendorf, M., Herrmann, A., Gierus, M., Wrage, N. & Hopkins, A.), pp. 940–942. Grassland Science in Europe no. 15. Kiel, Germany: European Grassland Federation and Arbeitsgemeinschaft Grünland und Futterbau der Gesellschaft für Pflanzenbauwissenschaften.Google Scholar
Faverdin, P., Delaby, L. & Delagarde, R. (2007 a). L'ingestion d'aliments par les vaches laitières et sa prévision au cours de la lactation. INRA Productions Animales 20, 151–162.Google Scholar
Faverdin, P., Delagarde, R., Delaby, L. & Meschy, F. (2007 b). Alimentation des vaches laitières. In Alimentation des Bovins, Ovins et Caprins - Besoins des Animaux - Valeur des Aliments - Tables INRA 2007 (Ed. Agabriel, J.), pp. 23–57. Paris, France: Editions Quae.Google Scholar
Faverdin, P., Baratte, C., Delagarde, R. & Peyraud, J. L. (2011). GrazeIn: a model of herbage intake and milk production for grazing dairy cows. 1. Prediction of intake capacity, voluntary intake and milk production during lactation. Grass and Forage Science 66, 29–44.Google Scholar
Faverdin, P., Delagarde, R., Delaby, L. & Meschy, F. (2010). Alimentation des vaches laitières. In Alimentation des Bovins, Ovins et Caprins - Besoins des Animaux - Valeur des Aliments – Tables INRA 2010 (Ed. Agabriel, J.), pp. 23–59. Versailles: Editions Quae.Google Scholar
Friggens, N. C. & Newbold, J. R. (2007). Towards a biological basis for predicting nutrient partitioning: the dairy cow as an example. Animal 1, 87–97.Google Scholar
Fuentes-Pila, J., DeLorenzo, M. A., Beede, D. K., Staples, C. R. & Holter, J. B. (1996). Evaluation of equations based on animal factors to predict intake of lactating Holstein cows. Journal of Dairy Science 79, 1562–1571.Google Scholar
García, S. C. & Holmes, C. W. (2001). Lactation curves of autumn- and spring-calved cows in pasture-based dairy systems. Livestock Production Science 68, 189–203.CrossRefGoogle Scholar
Gauch, H. G., Hwang, J. T. G. & Fick, G. W. (2003). Model evaluation by comparison of model-based predictions and measured values. Agronomy Journal 95, 1442–1446.Google Scholar
Gross, J., van Dorland, H. A., Bruckmaier, R. M. & Schwarz, F. J. (2011). Performance and metabolic profile of dairy cows during a lactational and deliberately induced negative energy balance with subsequent realimentation. Journal of Dairy Science 94, 1820–1830.Google Scholar
Grossman, M. & Koops, W. J. (2003). Modeling extended lactation curves of dairy cattle: a biological basis for the multiphasic approach. Journal of Dairy Science 86, 988–998.Google Scholar
Hoden, A., Peyraud, J. L., Muller, A., Delaby, L. & Faverdin, P., with Peccatte, J. R. & Fargetton, M. (1991). Simplified rotational grazing management of dairy-cows – effects of rates of stocking and concentrate. Journal of Agricultural Science, Cambridge 116, 417–428.Google Scholar
Jarrige, R. (1989). Ruminant Nutrition: Recommended Allowances and Feed Tables. London: John Libbey Eurotext.Google Scholar
Jacquot, A. L., Baumont, R. & Brunschwig, G. (2012). Dynamilk: a farming system model to explore the balance between forage and milk production in grassland based systems. In Producing and Reproducing Farming Systems: New Modes of Organization for Sustainable Food Systems of Tomorrow, The 10th European IFSA Symposium, 1–4 July 2012 in Aarhus, Denmark pp. 1–11. Aarhus, Denmark: IFSA Europe and the Swedish University of Agricultural Sciences. Available online from: http://ifsa.boku.ac.at/cms/index.php?id=132 (accessed October 2014).Google Scholar
Jouven, M., Carrère, P. & Baumont, R. (2006 a). Model predicting dynamics of biomass, structure and digestibility of herbage in managed permanent pastures. 1. Model description. Grass and Forage Science 61, 112–124.Google Scholar
Jouven, M., Carrère, P. & Baumont, R. (2006 b). Model predicting dynamics of biomass, structure and digestibility of herbage in managed permanent pastures. 2. Model evaluation. Grass and Forage Science 61, 125–133.Google Scholar
Kondo, S. (2011). Recent progress in the study of behavior and management in grazing cattle. Animal Science Journal 82, 26–35.Google Scholar
Konggaard, S. P. (1977). Comparison between conventional tie-barn and loose housing systems with respect to milk production, feed conversion and reproductive performance of dairy cows. Livestock Production Science 4, 69–77.Google Scholar
Langlands, J. P. & Sutherland, H. A. M. (1968). An estimate of the nutrients utilized for pregnancy by Merino sheep. British Journal of Nutrition 22, 217–227.Google Scholar
Martin, O. & Sauvant, D. (2010 a). A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling. Animal 4, 2030–2047.Google Scholar
Martin, O. & Sauvant, D. (2010 b). A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 2. Voluntary intake and energy partitioning. Animal 4, 2048–2056.Google Scholar
McCall, D. G. & Clark, D. A. (1999). Optimized dairy grazing systems in the Northeast United States and New Zealand. II. System analysis. Journal of Dairy Science 82, 1808–1816.CrossRefGoogle ScholarPubMed
McCarthy, B., Delaby, L., Pierce, K. M., Journot, F. & Horan, B. (2011). Meta-analysis of the impact of stocking rate on the productivity of pasture-based milk production systems. Animal 5, 784–794.Google Scholar
McEvoy, M., Kennedy, E., Murphy, J. P., Boland, T. M., Delaby, L. & O'Donovan, M. (2008). The effect of herbage allowance and concentrate supplementation on milk production performance and dry matter intake of spring-calving dairy cows in early lactation. Journal of Dairy Science 91, 1258–1269.Google Scholar
Moseley, J. E., Coppock, C. E. & Lake, G. B. (1976). Abrupt changes in forage-concentrate ratios of complete feeds fed ad libitum to dairy cows. Journal of Dairy Science 59, 1471–1483.Google Scholar
Olori, V. E., Brotherstone, S., Hill, W. G. & McGuirk, B. J. (1999). Fit of standard models of the lactation curve to weekly records of milk production of cows in a single herd. Livestock Production Science 58, 55–63.Google Scholar
Peyraud, J. L. & Delaby, L. (2005). Combiner la gestion optimale du pâturage et les performances des vaches laitières: enjeux et outils. INRA Productions Animales 18, 231–240.Google Scholar
Pomiès, D., Baumont, R., Egal, D. & Rémond, B. (2008). L'utilisation d'ensilage d'herbe et de foin de haute qualité chez des vaches en monotraite permet de supprimer le concentré avec une perte de lait limitée. 3R (Rencontres autour des Recherches sur les Ruminants) 15, 179.Google Scholar
Pomiès, D., Caré, S. & Veissier, I. (2010). Monotraite combinée à l'allaitement chez les vaches Prim'Holstein. 3R (Rencontres autour des Recherches sur les Ruminants) 17, 233–236.Google Scholar
Reist, M., Erdin, D., von Euw, D., Tschuemperlin, K., Leuenberger, H., Chilliard, Y., Hammon, H. M., Morel, C., Philipona, C., Zbinden, Y., Kuenzi, N. & Blum, J. W. (2002). Estimation of energy balance at the individual and herd level using blood and milk traits in high-yielding dairy cows. Journal of Dairy Science 85, 3314–3327.Google Scholar
Remppis, S., Steingass, H., Gruber, L. & Schenkel, H. (2011). Effects of energy intake on performance, mobilization and retention of body tissue, and metabolic parameters in dairy cows with special regard to effects of pre-partum nutrition on lactation – a review. Asian-Australasian Journal of Animal Science 24, 540–572.Google Scholar
Roca-Fernández, A., González-Rodríguez, A., Leurent, S., López-Mosquera, M., Gallard, Y. & Delaby, L. (2012). Milk performance of two cow breeds at two levels of supplementation in long residence time grazing paddocks. In Grassland: a European Resource? Proceedings of the 24th General Meeting of the European Grassland Federation, Lublin, Poland, 3–7 June 2012 (Eds Goliński, P., Warda, M. & Stypiński, P.), pp. 267–269. Grassland Science in Europe no. 17. Poznań, Poland: European Grassland Federation and the Polish Grassland Society.Google Scholar
Rook, A. J., Huckle, C. A. & Penning, P. D. (1994). Effects of sward height and concentrate supplementation on the ingestive behaviour of spring-calving dairy cows grazing grass–clover swards. Applied Animal Behaviour Science 40, 101–112.Google Scholar
Rotz, C. A., Mertens, D. R., Buckmaster, D. R., Allen, M. S. & Harrison, J. H. (1999). A dairy herd model for use in whole farm simulations. Journal of Dairy Science 82, 2826–2840.Google Scholar
Schils, R. L. M., de Haan, M. H. A., Hemmer, J. G. A., van den Pol-van Dasselaar, A., De Boer, J. A., Evers, A. G., Holshof, G., van Middelkoop, J. C. & Zom, R. L. G. (2007). DairyWise, a whole-farm dairy model. Journal of Dairy Science 90, 5334–5346.Google Scholar
Tedeschi, L. O., Seo, S., Fox, D. G. & Ruiz, R. (2006). Accounting for energy and protein reserve changes in predicting diet-allowable milk production in cattle. Journal of Dairy Science 89, 4795–4807.Google Scholar
Vayssières, J., Guerrin, F., Paillat, J. -M. & Lecomte, P. (2009). GAMEDE: a global activity model for evaluating the sustainability of dairy enterprises Part I – Whole-farm dynamic model. Agricultural Systems 101, 128–138.Google Scholar