Challenges in using on-farm animal data for pasture dry matter intake calculations

Abstract

An accurate dry matter intake (DMI) estimation is crucial for on-farm feed management and research, including calculating methane emissions. Since direct measurement of DMI is labour-intensive (e.g., using n-alkanes), researchers and industry organisations have developed predictive energy equations to backcalculate DMI from theoretical energy demand. However, these equations rely on accurate input data for variables such as animal liveweight, milk production, and supplements fed, which can be challenging to obtain. This study explored an alternative methodology for back-calculating the DMI of lactating dairy cows using farm data from a research farm setting and compared the results with observations of on-farm pasture disappearance using a rising plate meter.

While analysis of the alternative approach is ongoing, this paper focuses on the data handling, processing, and quality considerations necessary for applying predictive intake equations in on-farm contexts. Accurately back-calculating DMI remains challenging without high-quality data inputs. Still, the potential of technology in aiding data collection, such as the use of automated processes, holds promise for DMI estimation.