Philippe Faverdin

Digestion of fresh perennial ryegrass fertilized at two levels of nitrogen by lactating dairy cows

Two fertilizer levels (LN = 0 and HN = 80 kg N ha−1 before and after the first cut in spring 1991) were compared on a second cut (30 days old) of perennial ryegrass using a cross-over design with four fistulated cows producing 20 kg of milk at the beginning of the experiment. Grass was cut daily and given ad libitum in three meals per day. The absence of nitrogen fertilizer resulted in a reduction in the nitrogen content of grass from 24 to 17 g kg−1 dry matter. In addition, nitrogen intake was reduced from 367 to 263 g day−1, whereas organic matter intake (14 kg day−1) and milk output were not affected. When LN grass was fed, organic matter digestibility was slightly reduced, from 0.81 to 0.79 (P < 0.05) but the site of digestion was unaffected. Organic matter truly digested in the rumen was 0.94 of digestible organic matter intake. Fibre digestibility was reduced by 0.06 unit (P < 0.01) using the unfertilized grass. Non ammonia nitrogen supplied to the duodenum (366 and 349 g day−1 for HN and LN grass respectively) was slightly different (P < 0.05) between diets. Lower nitrogen fertilization affected neither microbial synthesis (21.2 g kg−1 digestible organic matter intake) nor microbial nitrogen flow and did not lead to any significant change in the amount of feed nitrogen escaping rumen degradation. Non ammonia nitrogen flow was equal to nitrogen intake in the fertilized grass but was substantially higher than nitrogen intake (+ 86 g day−1) in the unfertilized grass. This difference in net nitrogen recycling between the two diets matched the quantity of urea-nitrogen excreted in urine, which was reduced by 81 g day−1 using the unfertilized grass. The results suggest that although lowering the amount of nitrogen fertilizer alone has only a minor effect on dairy cow nutrition, it has a great effect on nitrogen metabolism, thus producing a much lower urinary nitrogen output.

An open platform to build, evaluate and simulate integrated models of farming and agro-ecosystems

Due to significant changes in agro-ecological contexts, farmers need new solutions to produce goods. Modelling complements field experiments in the design of new farming systems. French researchers involved in such design issues developed a specific modelling platform to help model, simulate and evaluate cropping systems. After testing several existing environments, the RECORD platform was developed under the VLE environment, allowing the design of atomic and coupled models. It integrates different time steps and spatial scales and proposes some standard formalisms used to model agro-ecosystems (e.g. difference equations, differential equations, state charts...). A graphic user interface was designed to simplify coding tasks. A variety of research projects already use this platform. Examples are given showing the ability to recode simple models, encapsulate more complex models, link with GIS and databases, and use the R statistical package to run models and analyse simulation outputs. The option to use web interfaces enables application by non-scientist end-users. As the models follow a given standard, they can be placed in a repository and used by other researchers. Linking RECORD to other international platforms is now a compelling issue.

Effect of different feeding strategies on lactation performance of Holstein and Normande dairy cows

The dairy farming systems of Western Europe are based on a simple feeding system composed of grazed and preserved grass, maize silage and concentrates in variable proportions. There is, nevertheless, a great diversity of feeding strategies between dairy farms. Over 5 years, we studied the direct and delayed effects of four feeding strategies on the lactation and reproduction performances of Holstein and Normande dairy cows. The four feeding strategies (denoted Hh, Hl, Lh and Ll) correspond to two total mixed rations applied in winter from calving to turnout (maize silage with 30% concentrate or grass silage with 15% concentrate), which were subsequently crossed with two levels of concentrate supplementation at grazing to 210 days. Each year, 72 dairy cows managed in grouped winter calving were assigned to the four strategies. Finally, the results of 325 lactations and 295 inseminated cows were analysed. The four strategies resulted in considerable variation in nutrient intake and, in particular, in differences in concentrates consumed, with values of 1407, 1026, 773 and 392 kg dry matter per cow for strategies Hh, Lh, Hl and Ll, respectively. Total milk production (7567, 7015, 6720 and 6238 kg per cow for treatments Hh, Lh, Hl and Ll, respectively), milk fat content (39.0, 37.1, 40.3 and 38.5 g/kg, respectively), milk protein content (33.0, 31.8, 33.1 and 31.6 g/kg, respectively), and the character of the lactation and body condition curves were all highly sensitive to the strategies applied. While no significant interaction was detected on total lactation yield, the Holstein cows reacted more dramatically to each dietary change at each period, compared with the Normande cows. Winter feeding did not affect the production of milk at pasture whereas, at pasture, the milk from the cows of the H groups in winter was higher in milk fat and protein content. Reproduction performance was unaffected by feeding strategy. The Holstein cows, well fed and producing the most milk (Hh and Hb), had the lowest rate of success at first artificial inseminations (21.5%). The dual-purpose Normande cows had a pregnancy rate 10 points higher than Holstein cows. This comparison of strongly contrasting feeding strategies confirms the immediate reactivity of dairy cows (in terms of milk performance and body condition) to variations of nutritive intake throughout lactation, with a weak carryover effect from feeding levels early in lactation. In contrast, reproduction performance was less sensitive to variation in nutrient supply.

THE INFLUENCE OF COW GENETIC MERIT FOR MILK PRODUCTION ON RESPONSE TO LEVEL OF CONCENTRATE SUPPLEMENTATION IN A GRASS-BASED SYSTEM

The objective of this study was to investigate if there is a genotype ✕ feeding system interaction for milk production in Holstein-Friesian dairy cows. For this purpose, 48 high genetic merit (HM) and 48 medium genetic merit (MM) dairy cows, were used in a two (genotypes) ✕ three (levels of concentrate feeding) randomized-block design experiment in three consecutive years. In year 1, all animals were in their first lactation, while in year 2 and year 3, 18 and 12 first lactation cows replaced animals culled at the end of the previous lactation. A total of 66 cows remained in the study in the same feeding system for the 3-year duration of the study. Concentrate feeding levels were 376, 810 and 1540 kg per cow per lactation; these were identified as the LC, MC and HC feeding systems respectively. There was a separate farmlet for each feeding system; farmlets were managed so that pre-grazing and post-grazing herbage height were similar for all three feeding systems. When compared on treatment means there was a significant genotype ✕ feeding system interaction for fat yield, while for mean solid-corrected milk yield the interaction was close to statistical significance (P = 0·07). However, regression coefficients of both milk and protein yield on pedigree index for milk and protein yield were significantly different between the LC and the HC. The interaction between feeding system and the regression of both on pre-experimental milk and protein yield were close to statistical significance (P = 0·08 and P = 0·09 respectively). Outputs of milk, fat, protein and lactose were greater for the HM than the MM cows. Feeding system had a significant effect on milk, fat, protein and lactose yields. There was a significant genotype ✕ feeding system interaction for body condition score (BCS) at the end of lactation; the MM cows had a higher rate of body tissue repletion than the HM cows especially in the HC system. The results suggest that there is a genotype ✕ concentrate feeding level interaction and that feeding systems developed in the past for animals of lower genetic merit may require adaptation if they are to be optimal for higher genetic merit animals.

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time.

In recent years, it has become increasingly clear that understanding nutrient partitioning is central to a much broader range of issues than just being able to predict productive outputs. The extent to which nutrients are partitioned to other functions such as health and reproduction is clearly important, as are the efficiency consequences of nutrient partitioning. Further, with increasing environmental variability, there is a greater need to be able to predict the ability of an animal to respond to the nutritional limitations that arise from the environment in which it is placed. How the animal partitions its nutrients when resources are limited, or imbalanced, is a major component of its ability to cope, that is, its robustness. There is mounting evidence that reliance on body reserves is increased and that robustness of dairy cows is reduced by selection for increased milk production. A key element for predicting the partition of nutrients in this wider context is to incorporate the priorities of the animal, that is, an explicit recognition of the role of both the cows genotype (genetic make-up), and the expression of this genotype through time on nutrient partitioning. Accordingly, there has been a growing recognition of the need to incorporate in nutritional models these innate driving forces that alter nutrient partitioning according to physiological state, the genetically driven trajectories. This paper summarizes some of the work carried out to extend nutritional models to incorporate these trajectories, the genetic effects on them, as well as how these factors affect the homeostatic capacity of the animal. At present, there are models capable of predicting the partition of nutrients throughout lactation for cows of differing milk production potentials. Information concerning genotype and stage of lactation effects on homeostatic capacity has not yet been explicitly included in metabolic models that predict nutrient partition, although recent results suggest that this is achievable. These developments have greatly extended the generality of nutrient partitioning models with respect to the type of animal and its physiological state. However, these models remain very largely focussed on predicting partition between productive outputs and body reserves and, for the most part, remain research models, although substantial progress has been made towards developing models that can be applied in the field. The challenge of linking prediction of nutrient partitioning to its consequences on health, reproduction and longevity, although widely recognized, is only now beginning to be addressed. This is an important perspective for future work on nutrient partitioning.

Predicting energy × protein interaction on milk yield and milk composition in dairy cows

Feed management is one of the principal levers by which the production and composition of milk by dairy cows can be modulated in the short term. The response of milk yield and milk composition to variations in either energy or protein supplies is well known. However, in practice, dietary supplies of energy and protein vary simultaneously, and their interaction is still not well understood. The objective of this trial was to determine whether energy and protein interacted in their effects on milk production and milk composition and whether the response to changes in the diets depended on the parity and potential production of cows. From the results, a model was built to predict the response of milk yield and milk composition to simultaneous variations in energy and protein supplies relative to requirements of cows. Nine treatments, defined by their energy and protein supplies, were applied to 48 cows divided into 4 homogeneous groups (primiparous or multiparous x high or low milk potential) over three 4-wk periods. The control treatment was calculated to cover the predicted requirements of the group of cows in the middle of the trial and was applied to each cow. The other 8 treatments corresponded to fixed supplies of energy and protein, higher or lower than those of the control treatment. The results highlighted a significant energy x protein interaction not only on milk yield but also on protein content and yield. The response of milk yield to energy supply was zero with a negative protein balance and increased with protein supply equal to or higher than requirements. The response of milk yield to changes in the diet was greater for cows with high production potential than for those with low production potential, and the response of milk protein content was higher for primiparous cows than for multiparous cows. The model for the response of milk yield, protein yield, and protein content obtained in this trial made it possible to predict more accurately the variations in production and composition of milk relative to the potential of the cow because of changes in diet composition. In addition, the interaction obtained was in line with a response corresponding to the more limiting of 2 factors: energy or protein.

MELODIE: a whole-farm model to study the dynamics of nutrients in dairy and pig farms with crops.

In regions of intensive pig and dairy farming, nutrient losses to the environment at farm level are a source of concern for water and air quality. Dynamic models are useful tools to evaluate the effects of production strategies on nutrient flows and losses to the environment. This paper presents the development of a new whole-farm model upscaling dynamic models developed at the field or animal scale. The model, called MELODIE, is based on an original structure with interacting biotechnical and decisional modules. Indeed, it is supported by an ontology of production systems and the associated programming platform DIESE. The biotechnical module simulates the nutrient flows in the different animal, soil and crops and manure sub-models. The decision module relies on an annual optimization of cropping and spreading allocation plans, and on the flexible execution of activity plans for each simulated year. These plans are examined every day by an operational management sub-model and their application is context dependent. As a result, MELODIE dynamically simulates the flows of carbon, nitrogen, phosphorus, copper, zinc and water within the whole farm over the short and long-term considering both the farming system and its adaptation to climatic conditions. Therefore, it is possible to study both the spatial and temporal heterogeneity of the environmental risks, and to test changes of practices and innovative scenarios. This is illustrated with one example of simulation plan on dairy farms to interpret the Nitrogen farm-gate budget indicator. It shows that this indicator is able to reflect small differences in Nitrogen losses between different systems, but it can only be interpreted using a mobile average, not on a yearly basis. This example illustrates how MELODIE could be used to study the dynamic behaviour of the system and the dynamic of nutrient flows. Finally, MELODIE can also be used for comprehensive multi-criterion assessments, and it also constitutes a generic and evolving framework for virtual experimentation on animal farming systems.

Prediction of water intake and excretion flows in Holstein dairy cows under thermoneutral conditions

The increase in the worldwide demand for dairy products, associated with global warming, will emphasize the issue of water use efficiency in dairy systems. The evaluation of environmental issues related to the management of animal dejections will also require precise biotechnical models that can predict effluent management in farms. In this study, equations were developed and evaluated for predicting the main water flows at the dairy cow level, based on parameters related to cow productive performance and diet under thermoneutral conditions. Two datasets were gathered. The first one comprised 342 individual measurements of water balance in dairy cows obtained during 18 trials at the experimental farm of Méjussaume (INRA, France). Predictive equations of water intake, urine and fecal water excretion were developed by multiple regression using a stepwise selection of regressors from a list of seven candidate parameters, which were milk yield, dry matter intake (DMI), body weight, diet dry matter content (DM), proportion of concentrate (CONC) and content of crude protein (CP) ingested with forage and concentrate (CPf and CPc, g/kg DM). The second dataset was used for external validation of the developed equations and comprised 196 water flow measurements on experimental lots obtained from 43 published papers related to water balance or digestibility measurements in dairy cows. Although DMI was the first predictor of the total water intake (TWI), with a partial r(2) of 0.51, DM was the first predictive parameter of free water intake (FWI), with a partial r(2) of 0.57, likely due to the large variability of DM in the first dataset (from 11.5 to 91.4 g/100 g). This confirmed the compensation between water drunk and ingested with diet when DM changes. The variability of urine volume was explained mainly by the CPf associated with DMI (r.s.d. 5.4 kg/day for an average flow of 24.0 kg/day) and that of fecal water was explained by the proportion of CONC in the diet and DMI. External validation showed that predictive equations excluding DMI as predictive parameters could be used for FWI, urine and fecal water predictions if cows were fed a well-known total mixed ration. It also appeared that TWI and FWI were underestimated when ambient temperature increased above 25°C and possible means of including climatic parameters in future predictive equations were proposed.

Effects of dietary cation-anion difference on ruminal metabolism and blood acid-base regulation in dairy cows receiving 2 contrasting levels of concentrate in diets

Dietary cation-anion difference [DCAD=Na+K-Cl in mEq/kg of dry matter (DM)] increases DM intake (DMI) in cows fed diets containing rapidly degraded starch. Increased DMI of diets containing rapidly degraded starch could potentially exacerbate subacute acidosis. The objective of this study was to determine metabolic effects of increasing DCAD in low and high starch diets. Six cannulated Holstein cows were blocked into 2 groups of 3 cows and assigned to two 3 x 3 Latin squares in a split-plot design. Each group received a level of concentrate at either 20 or 40% on a DM basis. The diet containing 20% concentrate supplied 4% rapidly degraded starch, whereas the diet containing 40% concentrate supplied 22% rapidly degraded starch. Diets in each square were formulated to provide a DCAD of 0, 150, or 300 mEq/kg of DM. The 3 values were obtained by manipulating Na and Cl contents. Increasing the proportion of rapidly degraded starch decreased rumen pH and the acetate to propionate ratio but did not affect digestibility, blood acid-base status, pH of urine, and strong ion excretion. Increasing DCAD increased DMI, the effect being higher when the cows were fed the 40% concentrate diet. Increasing DCAD did not affect mean ruminal pH, molar proportion of VFA, and fiber digestibility; reduced the range of rumen pH decrease during the meal in cows fed the 40% concentrate diet; and strongly increased blood pH and blood HCO3 concentration. Increasing DCAD increased urine pH and modified the urinary excretion of minerals. With low DCAD, 70% of Cl and only 16% of Na were excreted in urine whereas with high DCAD, 33% of Cl and 53% of Na were excreted. These results suggest that DMI of cows fed diets rich in rapidly degraded starch and low DCAD was limited to maintain the blood pH in a physiological range. Increasing DCAD allowed the cows to increase DMI because of the ability of positive DCAD to maintain blood acid-base status. A localized rumen buffering effect could not be excluded and could be linked with a higher amount of HCO3 recycled into the rumen. Main mechanisms involved in regulating blood pH might be renal excretion of protons and strong ions and renal HCO3 reabsorption.

Effect of a long chain n-3 PUFA-enriched diet on production and reproduction variables in Holstein dairy cows.

The objective of this study was to determine the effect of a rumen-protected fish oil supplement on the production and reproduction variables in postpartum dairy cows. Holstein cows (n=46) were given a basal total mixed diet plus one PUFA supplement: n-3 (n-3; protected fish oil; 1% dry matter intake (DMI); n=23) or control (n-6; toasted soybeans; 1.8% DMI; n=23), in a switchback design over two consecutive lactations. Supplements were added to the diet between calving and 2 months after calving to assess the effect on growth and maturation of ovarian follicles from which ovulation occurred around the day of insemination. Body weight (BW), milk yield (MY) and composition, dry matter intake (DMI), energy balance (EB), subcutaneous fat thickness, plasma fatty acid composition, plasma nonesterified fatty acids (NEFA), glucose and urea concentrations, follicular activity, embryo mortalities and fertility (conception rate after first AI, AI1) were assessed. BW, MY, DMI, plasma NEFA, glucose and urea were unaffected by the diet. There was a trend of an increased number of large follicles (diameter≥10mm) with the n-3 dietary supplementation (P=0.06) and a decrease in infertility or early embryo mortality rate 21 days after AI, 13.5% in the n-3 compared with 38.8% in the n-6 group (P=0.09), with no effect on the conception rate at 35d or 90d after AI1. These data suggest that the effect seen on ovarian variables is not associated with an effect on production and metabolic variables and is specific to n-3 PUFA supplementation. Further studies are necessary to determine whether DHA or EPA enhances fertility in lactating dairy cattle.