Modeling homeorhetic trajectories of milk component yields, body composition and dry-matter intake in dairy cows: Influence of parity, milk production potential and breed

J. B. Daniel1,2†, N. C. Friggens1, H. van Laar2, K. L. Ingvartsen3 and D. Sauvant1

1 UMR 0791 Modélisation Systémique Appliquée aux Ruminants, INRA, AgroParisTech, Université Paris-Saclay, 75005 Paris, France;
2 Trouw Nutrition R&D, PO Box 220, 5830 AE Boxmeer, The Netherlands;
3 Faculty of Agricultural Sciences, Research Center Foulum, University of Aarhus, PO Box 50, DK-8830 Tjele, Denmark
Author to whom correspondence should be addressed.

Animal. 2018 Jun;12(6):1182-1195. doi: 10.1017/S1751731117002828. Epub 2017 Nov 3.

  • Ruminants
  • Open Access
  • 2023
N. C. Friggens, H. van Laar, K. L. Ingvartsen and D. Sauvant

by J. B. Daniel on
Read more

Abstract

The control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level.

Keywords: dairy cow; dynamic model; energy; milk composition.

Related articles

  • Unlocking the limitations of urea supply in ruminant diets
    Ruminants have evolved with the capability to recycle endogenous urea to the gastrointestinal tract (GIT). Ruminal ammonia derived from urea recycling makes a net contribution to digestible N flow if it is used to synthesise microbial protein. The dynamics of urea recycling and its quantitative importance to the N economy of ruminants are affected by dietary and physiological factors. In general, the transfer of endogenous urea to the GIT is related positively to blood urea concentration and rumen-fermentable energy supply and negatively to ruminal ammonia concentration. After consumption of a meal rich in rumen-degradable N, ruminal ammonia concentrations peak and can exceed the rate of carbohydrate fermentation, resulting in inefficient ammonia capture by microbes. These periods are characterised by greater ruminal ammonia efflux and reduced urea influx. A low ruminal ammonia concentration over time can stimulate recycling of endogenous urea-N to the rumen and its capture into microbial protein and reduce N excretion.
    by K. Nichols on
    High solubility of certain trace minerals (TM) in the rumen can alter nutrient digestibility and fermentation. The objectives of the present studies were to determine the effects of TM source on 1) nutrient digestibility and ruminal fermentation, 2) concentrations of soluble Cu, Zn, and Mn in the rumen following a pulse dose of TM, and 3) Cu, Zn, and Mn binding strength on ruminal digesta using dialysis against a chelating agent in steers fed a diet formulated to meet the requirements of a high producing dairy cow. Twelve Angus steers fitted with ruminal cannulae were adapted to a diet balanced with nutrient concentrations similar to a diet for a high producing lactating dairy cow for 21 d. Steers were then randomly assigned to dietary treatments consisting of 10 mg Cu, 40 mg Mn, and 60 mg Zn/kg DM from either sulfate (STM), hydroxychloride (HTM) or complexed trace minerals (CTM). The experimental design did not include a negative control (no supplemental Cu, Mn, or Zn) because the basal diet did not meet the National Research Council requirement for Cu and Zn. Copper, Mn, and Zn are also generally supplemented to lactating dairy cow diets at concentrations
    by O.Guimaraes on
  • Mineral and glycerol concentrations in water
    Situations in which cattle are feed-deprived over extensive periods of time are common in the context of transport and is an animal welfare concern which may also compromise growth and carcass yield grade. This study investigated how the main components of an oral rehydration solution would affect BW loss and blood parameters in feed-deprived bulls. Three dose–response experiments were performed with 24 bulls each (n = 6 per treatment) to study the effect of mineral concentration in Study I (0, 100, 200 and 300 mOsm/kg), the K+ to Na+ ratio in Study II (25:75, 40:60, 60:40 and 75:25), and glycerol concentration in Study III (0%, 1%, 2% and 4% of the final solution). The blocking factor was initial BW and treatments were randomly assigned within each block. Measurements included fluid intakes, BW, and blood parameters at 0, 24 and 48 h relative to the start of feed deprivation. In Study I, increasing mineral concentration in solution linearly decreased BW losses at 48 h. At 24 and 48 h, serum urea linearly decreased with increasing mineral concentration. At 48 h, blood K+ and Na+ linearly increased, resulting in increased blood osmolarity. Additionally, at 24 h feed deprivation, blood pH linearly increased with increasing osmolality. In Study II, BW losses decreased with i
    by J. N. Wilms on