PSXVI-4 Modelling Response to Heat Stress in a Northeastern USA Dairy Facility Using Robotic Voluntary Milking System Data

Abstract

Abstract Heat stress represents a major concern in the US dairy industry. It negatively affects profitability by reducing production and reproductive efficiency. One efficient way to study heat stress is to associate production losses with weather data. The objective of this study is to use data from a voluntary milking system and a local weather station to study the impact of heat stress on a dairy facility in the Northeast. Data from 124 Holsteins and Jersey cows, with daily milking records from June of 2020 to February of 2022 at the Kellogg Dairy Center at the University of Connecticut, in Storrs, CT, were used. The first approach consisted in fitting a heat load function to model the daily changes in milk production. Additionally, the total milk production and number of days under potential heat stress per lactation were associated. Finally, the residuals of a nonlinear model for lactation curve computed using the Wilmink equations were modeled as a function of the heat load values. Results suggested that a temperature-humidity index above 60 may reduce milk production significantly (p < 0.05). In addition, a better fit was obtained when the heat load was calculated as the average between the day of the heat event and the day before. The correlations between the days under potential heat stress and total milk yield were not significant. Finally, the effect of heat load on daily yield was significant and negative (p < 0.05). Taken together, the results suggest that milk yield of cows in the Northeast is affected by heat stress. Moreover, the voluntary milking system provides appropriate data for evaluating response to weather events in dairy cattle production. Such an approach evaluates animals under normal production circumstances and does not limit the number of individuals to be studied.