An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows

To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rate

A milk urea model to better assess nitrogen excretion and feeding practice in dairy systems

A milk urea model to better assess nitrogen excretion and feeding practice in dairy systems. 20. Nitrogen Worksho

Predicting energy x 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

A model-based assessment of C storage potential of French grasslands: a national study

International audienceFrom a climate change perspective, grassland soils have the ability to sequester C. However, there are still uncertainties on the magnitude of C sequestration potential, and their use in climate initiatives (i.e. 4p1000). Average values (± standard error) of 0.7±0.1 Mg C ha‑1 yr‑1 for permanent grassland (PG), and 0.4 to 0.8 Mg C ha‑1 yr‑1 for grass-ley (temporary grassland, TG), have been cited by different studies, while soil inventory reports only 0.05±0.3 Mg C ha‑1 yr‑1. These discrepancies can be attributed to differences in pedo-climatic conditions, intensity and type of management, but also to age and lifetime of temporary grasslands (TG). To analyse in detail C sequestration potential of French grasslands, a national study ‘4p1000 France’ was conducted to identify (1) C ‘storing’ practices; (2) their potential to be adopted as mitigation option; and (3) their cost of implementation. Along with a literature review, a modelling approach at fine spatial-scale resolution (1 km2) was used to simulate key grassland managements for PG and TG identified from agricultural statistics. Results showed that insertion of TG gained additional +0.47 Mg C ha‑1 yr‑1, while the replacement of mowing by grazing of intensively used PGs added +0.3 Mg C ha‑1 yr‑1 to soil, compared to baseline (0.26 and 0.21 Mg C ha‑1 yr‑1 for TG and PG). C storage under baseline and mitigation practices was able to offset field-based greenhouse gas emissions over French grassland areas

A model-based assessment of C storage potential of French grasslands: a national study

International audienceFrom a climate change perspective, grassland soils have the ability to sequester C. However, there are still uncertainties on the magnitude of C sequestration potential, and their use in climate initiatives (i.e. 4p1000). Average values (± standard error) of 0.7±0.1 Mg C ha‑1 yr‑1 for permanent grassland (PG), and 0.4 to 0.8 Mg C ha‑1 yr‑1 for grass-ley (temporary grassland, TG), have been cited by different studies, while soil inventory reports only 0.05±0.3 Mg C ha‑1 yr‑1. These discrepancies can be attributed to differences in pedo-climatic conditions, intensity and type of management, but also to age and lifetime of temporary grasslands (TG). To analyse in detail C sequestration potential of French grasslands, a national study ‘4p1000 France’ was conducted to identify (1) C ‘storing’ practices; (2) their potential to be adopted as mitigation option; and (3) their cost of implementation. Along with a literature review, a modelling approach at fine spatial-scale resolution (1 km2) was used to simulate key grassland managements for PG and TG identified from agricultural statistics. Results showed that insertion of TG gained additional +0.47 Mg C ha‑1 yr‑1, while the replacement of mowing by grazing of intensively used PGs added +0.3 Mg C ha‑1 yr‑1 to soil, compared to baseline (0.26 and 0.21 Mg C ha‑1 yr‑1 for TG and PG). C storage under baseline and mitigation practices was able to offset field-based greenhouse gas emissions over French grassland areas