Dairy Cow Response to Heat Stress Modeled with a System Dynamics Approach.

Abstract Modeling the individual animal response to heat stress (HS) conditions is challenging because of the complex interactions that characterize the system behavior. In explaining the resulting animal behavior, the dynamicity, nonlinearity, and delays in the HS response are often unaccounted for or misinterpreted. The system dynamics (SD) methodology, a mathematical modeling approach based on feedback loop structures, allows for modeling and understanding the behavior of complex systems over time. By applying SD methodology, this study developed a preliminary conceptual model to capture the cow response and observed milk yield (MY) under HS. The data on the temperature-humidity index (THI) and MY used for model development were collected from a dairy cattle farm in August 2021. The parameters related to the HS response of 20 selected cows were used for calibration and parameterization of the model. To minimize the effect of the lactation stage on milk production and model results, 20 cows were selected for days in milk (DIM) to be between 70 and 220 d. After the parameter calibration using MY data, it was found that the historical data pattern of 13 out of 20 cows followed the expected behavioral pattern generated by the model. In contrast, the behavior of the remaining seven cows did not align with that generated by the model. Therefore, based on their patterns, the cows were identified as fitting or non-fitting the model’s structure. The structure of the model captured the effect of HS on fitting cows with high accuracy (mean absolute percentage error, MAPE < 5%; R2 > 0.6; concordance correlation coefficient, CCC > 0.6). At the same time, the behavior of the non-fitting cows could not be explained by the defined parameter space. We believe they either had heat-resistant behavior or experienced different biological delays than average. Based on the obtained results, the evaluation of parameter values should be done only for the fitting cows, as the work aimed to develop a model to understand the HS response. The behaviors generated by the model can help farmers and decision-makers distinguish heat-sensitive from heat-tolerant cows and quantify the animal response in terms of MY so that mitigation strategies can be implemented.