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Updated Heat Load Index algorithm for the Australian feedlot sector
The project was designed to develop a draft Heat Load Index algorithm, based on the surface energy balance of the feedlot. Phase 1 of the project was undertaken during the 2014/2015 summer period and consisted of:
Collecting micro-meteorological data at UQ Gatton utilising an Eddy Covariance (EC) system to establish the heat/energy relationships between feedlot cattle and the environment
Monitor animal health, behaviour and consumption
Unfortunately, the data to be collected on animal health, behaviour and consumption was not supplied, with the only data available from UQ being rumen temperature logs for approximately 100 animals. The micro-meteorological dataset collected by Katestone at the Gatton provides a good picture of how the environmental inputs, radiation, momentum and moisture are partitioned. However the lack of data on the cattle energy sources and sinks means the total energy balance cannot be solved and without the cattle behaviour observations and consumption rates there is no certainty whether excessive heat load was experienced during the summer period.
The EC monitoring data provided a physical explanation of the changes in the environment that appear to coincide with increases in the mean maximum herd rumen temperature (HRT) due to a transition from a hot dry climate to a hot and humid one. It also showed that these conditions will persist until the supply of water and/or water vapour is exhausted or no longer available.
Every period in the HRT dataset where the HRT stayed above the mean for more than 2 days coincided with the synoptic and micro-meteorological events described above. The limiting factor in all these events was the availability of moisture, either as water vapour or freely available water following a rain event, to drive the evaporative flux (Q_E).
While installing an EC station at every feedlot is unfeasible the data does suggest that other variables may provide a better understanding of the onset and dissipation of these conditions. For example dew point temperature, is a direct measure of the amount of water vapour present in the atmosphere and the soil/air temperature gradient can be used as a proxy for evaporative fraction (EF) under some circumstances (Gentine et al. 2007).
Phase 2 of the Project will provide the concurrent animal observations required to identify and quantify the environmental conditions that drive the onset and dissipation of heat stress events in feedlot cattle and ultimately lead to a simplified heat stress algorithm that is based on the cattle's reaction the environmental conditions.
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Updated heat load index algorithm for the Australian feedlot industry
This page was last updated on 05/07/2018
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