@article {Ahmed661249, author = {Ben Abdelkrim Ahmed and Puillet Laurence and Gomes Pierre and Martin Olivier}, title = {Lactation curve model with explicit representation of perturbations as a phenotyping tool for dairy livestock precision farming}, elocation-id = {661249}, year = {2019}, doi = {10.1101/661249}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Background Understanding the effects of environment on livestock provides valuable information on how farm animals express their production potential, and on their welfare. Ruminants often face perturbations that affect their performance. Evaluating the effect of these perturbations on animal performance could provide metrics to quantify how animals cope with their environment and therefore, better manage them. In dairy systems, milk production records can be used to evaluate perturbations because (1) they are easily accessible, (2) the overall dynamics throughout the lactation process have been widely described, and (3) perturbations often occur and cause milk loss. In this study, a lactation curve model with explicit representation of perturbations was developed.Methods The perturbed lactation model is made of two components. The first one describes a theoretical unperturbed lactation curve (unperturbed lactation model), and the second describes deviations from the unperturbed lactation model. The model was fitted on 319 complete lactation data from 181 individual dairy goats allowing for the characterization of individual perturbations in terms of their starting date, intensity, and shape.Results The fitting procedure detected a total of 2,354 perturbations with an average of 7.40 perturbations per lactation. Loss of production due to perturbations varied between 2\% and 19\%. Results show that the number of perturbations is not the major factor explaining the loss in milk yield over the lactation, suggesting that there are different types of animal response to challenging factors.Conclusions By incorporating explicit representation of perturbations, the model allowed the characterization of potential milk production, deviations induced by perturbations (loss of milk), and thereby comparison between animals. These indicators are likely to be useful to move from raw data to decision support tools in dairy production.}, URL = {https://www.biorxiv.org/content/early/2019/08/05/661249}, eprint = {https://www.biorxiv.org/content/early/2019/08/05/661249.full.pdf}, journal = {bioRxiv} }