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Modelling methane emissions from remotely collected liveweight data and faecal near-infrared spectroscopy in beef cattle

González, L. A., Charmley, E., Henry, B. K.
Animal production science 2014 v.54 no.12 pp. 1980-1987
accounting, beef cattle, body weight, business enterprises, carbon markets, digestibility, emissions, feed intake, grazing, inventories, methane, methane production, models, near-infrared spectroscopy, prediction, rain, tropical pastures, wet season, Australia
The objective of the present study was to develop a model-data fusion approach using remotely collected liveweight (LW) data from individual animals (weighing station placed at the water trough) and evaluate the potential for these data from frequent weighing to increase the accuracy of estimates of methane emissions from beef cattle grazing tropical pastures. Remotely collected LW data were used to calculate daily LW change (LWC), i.e. growth rate on a daily basis, and then to predict feed intake throughout a 342-day grazing period. Feed intake and diet dry matter digestibility (DMD) from faecal near-infrared spectroscopy analysis were used to predict methane emissions using methods for both tropical and temperate cattle as used in the Australian national inventory (Commonwealth of Australia 2014). The remote weighing system captured both short- and long-term environmental (e.g. dry and wet season, and rainfall events) and management effects on LW changes, which were then reflected in estimated feed intake and methane emissions. Large variations in all variables, measured and predicted, were found both across animals and throughout the year. Methane predictions using the official national inventory model for tropical cattle resulted in 20% higher emissions than those for temperate cattle. Predicted methane emissions based on a simulation using only initial and final LW and assuming a linear change in LW between these two points were 7.5% and 5.8% lower than those using daily information on LW from the remote weighing stations for tropical and temperate cattle, respectively. Methane emissions and feed intake can be predicted from remotely collected LW data in near real-time on a daily basis to account for short- and long-term variations in forage quality and intake. This approach has the potential to provide accurate estimates of methane emissions at the individual animal level, making the approach suitable for grazing livestock enterprises wishing to participate in carbon markets and accounting schemes.