PS1-28. Validation of an Method to Determine Individual Grazing Dry Matter Intake at Scale in Beef Cattle.

Abstract Knowing the accurate dry matter intake (DMI) is vital in order for cattle farmers to optimize farm management. DMI is affected by various factors including forage quality, environmental conditions, and individual animal characteristics. This study aims to validate an AI tool that can predict individual, daily DMI to identify efficient animals from prospective herd replacements. The data was collected from a sample of one hundred thirteen beef females over a period of fifty days. Variables measured include forage nutrient composition, pasture biomass, animal-specific characteristics (including bodyweight and breed), individual water intake, and environmental parameters (such as temperature and humidity). Weather data includes hourly dry bulb temperature, precipitation, relative humidity, station pressure, and wind speed which were all collected from NOAA stations located near the research site. DMI was determined using body weight, water intake and climatic variables. Ground truth DMI was determined by providing 20 g/day titanium dioxide for six days and collecting fecal samples twice a day for the last three days. Given the amount of titanium dioxide in feces, the DMI was determined and measured. The RMSE of determined and ground truth DMI for the days that both were determined was 1.35 kg. The AI tool appears to be a very good measure of individual, daily DMI for this external validation dataset. These results created an approach to determining feed intake in cattle that captures interaction between the environment and animal.