Systematic Review and Meta-Analysis: Identification of Factors Influencing Milking Frequency of Cows in Automatic Milking Systems Combined with Grazing.

Abstract

Simple SummaryNumerous publications have investigated the possibility of combining automatic milking systems (AMS) with grazing. Milking frequency (MF) was usually considered as an indicator of robot performance and researchers focused on ways to optimize it. It seems pertinent to compile the published results. By using principal component analysis, we discriminated four agricultural exploitation systems (clusters). These systems differed from low—less than two milkings per day—to MF similar to those recorded at barn (2.7 milkings/cow per day). The description of clusters allowed for the identification of parameters influencing MF: concentrate supply, minimum milking interval, pasture dry matter intake and stage of lactation. By pair-wise analysis, we quantified the relationship between each parameter and MF. In a second step, we identified the relationship between MF and milk production (MY). These analyses allowed us to understand in which context these parameters could be efficient. For example, concentrate supply in full grazing has limited efficiency but in early lactation, increases MF. High percentage of grazed grass in a cow’s diet seems to limit MF. The impact of MF on MY was confirmed. In conclusion, several strategies can be implemented to combine grazing and AMS with an impact on productivity and on production costs. More dairy farms (up to more than one in four in some countries) are equipped with automatic milking systems (AMS) worldwide. Because of the positive impacts of grazing, e.g., on animal welfare or on production costs, numerous researchers have published papers on the combination of AMS with grazing. However, pasture-based AMS usually causes a reduction in milking frequency (MF) compared to indoors systems. The objectives of this meta-analysis were to review publications on the impacts of pasture-based AMS on MF and mitigation strategies. First, data from 43 selected studies were gathered in a dataset including 14 parameters, and on which a Principal Component Analysis (PCA) was performed, leading to the description of four clusters summarizing different management practices. Multiple pairwise comparisons were performed to determine the relationship between the highlighted parameters of MF on milk yield (MY). From these different analyses, the relationship between MF and MY was confirmed, the systems, i.e., Clusters 1 and 2, that experienced the lowest MF also demonstrated the lowest MY/cow per day. In these clusters, grazed grass was an essential component of the cow’s diet and low feeding costs compensated MY reduction. The management options described in Clusters 3 and 4 allowed maintenance of MF and MY by complementing the cows’ diets with concentrates or partial mixed ration supplied at the AMS feeding bin or provided at barn. The chosen management options were closely linked to the geographical origin of the papers indicating that other factors (e.g., climatic conditions or available grasslands) could be decisional key points for AMS management strategies.