Modelling impacts of precision livestock farming tools on carbon footprints of average suckler beef and dairy systems at grazing
The use of precision livestock farming (PLF) technologies can support management decisions to improve animal health, welfare and production, and its use is increasing globally. Whilst these technologies are not designed to directly reduce greenhouse gas (GHG) emissions, they can do so by increasing the productivity of the animal and resource use efficiency, reducing the overall carbon footprint of the farm. This work modelled the impact of PLF technologies on whole farm and product emissions from predominantly grazing beef and dairy enterprises in Scotland using a well established carbon footprining tool (Agrecalc1). Data was taken from the Cattle Tracing System (CTS; online database of all bovine animals in GB) and used to define baseline average farms for Scotland for an spring calving upland suckler system (beef) and 8000L all year-round calving system (dairy). Agrecalc was used to model impacts of technology introduction on whole farm emissions and emissions intensities expressed as emissions per unit of product (beef and dairy) compared to the baseline enterprise. Modelling activities focussed on adoption of technologies to improve health and welfare, fertility and production. Emissions reductions were observed over all scenarios showing potential carbon saving which could be achieved. This work demonstrates the potential of using precision technologies to improve technical efficiencies and aid in achieving net-zero targets. 1https://www.agrecalc.com/
This work utilised a pre-existing, commercially available carbon footprinting tool, Agrecalc, to model and demonstrate impacts of the application of PLF tools on the animal parameters, product and farm greenhouse gas (GHG) emissions of an average Scottish dairy and beef grazing system. Agrecalc is a farm carbon footprinting tool which estimates the GHG emissions source and extent for an enterprise, considering carbon dioxide (CO2) from fossil fuels, methane (CH4) from ruminant digestion and manures and nitrous oxide (N2O) from fertiliser application and manures. Data for Scotland from the Cattle Tracing System (CTS) were collated and utilised to create a baseline average dairy farm of an 8000L, 225 cow, all year-round (AYR) calving system with pasture access and a baseline spring calving upland suckler beef system beef. Baseline farms and scenarios based on the effects of PLF technology introduction were modelled using Agrecalc, for whole farm and product emissions, and each scenario compared to the baseline. This is a novel use of Agrecalc to model impacts of technology introduction using various scenarios. Scenarios included improved fertility, improved health and welfare and improved production levels (both yield for dairy and growth rates for beef). Those parameters expected to be affected by introduction of technology (e.g., calving interval, animal performance, replacement rate, mortality, yield and slaughter weight/age) and associated feed, bedding and land requirement changes were considered in the model.
Livestock farming systems are facing increasing pressure to produce meat and dairy products in a more environmentally friendly way, with higher animal welfare and decreased antimicrobial usage (due to increasing risk of antimicrobial resistance). There are considerable inefficiencies within beef and dairy systems, particularly when animals are grazing. This is driven by low performance (compared to housed animals) and increased morbidity and mortality as animals are not subject to same levels of monitoring/management as housed animals. In addition, greenhouse gases from grazing cattle are generally higher and more variable than those from housed cattle because of variability in herbage, increased fibre contents of herbage, and reduced opportunity to monitor and manage diets. Adoption of PLF tools is increasing globally. When these solutions are fully exploited, they can help improve health, welfare and productivity and support more effective decision-making on-farm. Whilst technologies are not designed to directly reduce greenhouse gases, they can do so by improving technical efficiencies, both at the animal and farm level. The use of farm carbon calculators is increasing and enables farms to benchmark progress of carbon reduction (expressed as CO2 equivalence) against previous year’s performance, however, these calculators are not typically used on farm to forecast emissions associated with technology use. It is vital to fully understand the carbon savings which can be achieved through the adoption of technology. Increased technology use and associated data-driven management will support agriculture in achieving government targets of net zero (2045 in Scotland) and will support COP26’s Global Methane Pledge of reducing global methane emissions by at least 30% by 2030 relative to 2020 levels. In addition, detailed information of how technology use impacts emissions may help increase its uptake across the beef and dairy sector.
Whilst not intended to influence greenhouse gas emissions directly, precision technologies can do so by improving the efficiency of the animals and therefore the farm. The use of PLF tools and techniques on farm not only improves the health, welfare, and production of the animals themselves, but reduces the overall carbon footprint of the enterprise. This is achieved through resource optimisation from improving animal production efficiency. There is a direct link between emission intensities and animal efficiencies, i.e., the more efficient and productive, the lower environmental impact per unit of product (e.g., meat or milk). Three broad categories can describe the technologies commonly used in the beef and dairy sectors. These include technology solutions designed to: • Improve health and welfare, for example through use of a leg-mounted pedometer. • Improve fertility (and yield in the case of dairy), for example using a neck-mounted accelerometer (collar). • Improve animal productivity by closely monitoring performance, for example the use of an automatic weigh crate to monitor growth and performance. The work evaluated the use of an established and commercially available carbon footprinting tool, Agrecalc (developed by SAC Consulting, part of SRUC), to model impacts of technology introduction on whole farm emissions and emissions intensities (emissions per unit of product) on a predominantly grazing dairy and beef farm. Full results on reduction potential using PLF can be found in Bowen et al, 2022a, b, and Ferguson et al. 2022.
Agrecalc is a commercially available farm carbon footprinting tool. Whilst our work did not alter the offering Agrecalc provides, it showed that it is possible to use the existing tool in a way beyond the standard benchmarking of enterprises, to demonstrate potential carbon savings which could be obtained by introduction of PLF tools on farm. Other research groups or industry could use this method to model their own scenarios on farm, using Agrecalc to demonstrate benefits to farmers and further improve uptake of precision technologies or other farm interventions. Further use of Agrecalc commercially, and in research settings globally, will improve the pre-existing algorithms, provide greater datasets for research, and improve understanding of the impacts of different interventions on different farming enterprises globally. Increased datasets and increased range of system types entered into the model mean that the algorithm, and therefore outputs, can be more precise and provide a more accurate prediction of the types of emission changes which may be observed on farm. Increased usage of tools like Agrecalc for modelling interventions on farm globally by farm consultants and farmers will support more farmers in making informed decisions about their enterprise which could lead to increased reductions of GHG emissions from farm. The ability to demonstrate clear changes in animal parameters and GHG emissions per kg/product and per enterprise of an average beef and dairy farm, due to PLF introduction, may improve uptake of these types of precision technologies by farmers. Technology uptake may also be furthered by the use of average farm data in this exercise which made the outputs more relatable, allowing farmers an understanding of changes which may be feasible for them to achieve in a real farm setting.
