Award details

PrecisionBeef

Reference	BB/M027392/1
Principal Investigator / Supervisor	Professor Carol-Anne Duthie
Co-Investigators / Co-Supervisors	Professor Richard Dewhurst, Dr James Hyslop, Dr John Rooke, Dr David Ross
Institution	SRUC
Department	Research
Funding type	Research
Value (£)	345,859
Status	Completed
Type	Research Grant
Start date	01/04/2015
End date	30/06/2018
Duration	39 months

Abstract

Optimising animal productivity is critical to maintaining a competitive and sustainable UK beef industry with production efficiency the greatest single opportunity to reduce primary production costs. There is considerable inefficiency in the beef sector which increases variable farm costs, reduces the yearly capacity of finishing units, and reduces profitability due to sub-optimal marketing of animals. The reduced revenue associated with these inefficiencies arise for 3 main reasons; (1) retaining cattle on-farm beyond the optimum point of marketability leading to extra feed, bedding and fixed costs; (2) reductions in sale revenue due to these over-finished cattle being out of desired specification; (3) loss of productivity and efficiency due to poor animal health. The aim is to develop a state-of-the art solution for beef farmers to optimise their business efficiency. At the core of the project is the development of a near infra-red (NIR) system to characterise feed (dry matter content, nutritional composition) as it exits a feeder wagon. Also pivotal to the project is the development of animal-mounted sensors to measure feeding behaviour (eating and rumination patterns). The bulk feed characteristics will be integrated with the feeding behaviour data with a target of providing a robust, accurate and innovative method of determining individual animal feed intake. The final solution will be a cloud-based decision support platform integrating individual animal feed intake and behaviour data, with measures of animal performance. This will provide the support tools necessary to quantify performance and efficiency of individual animals and improve the sustainability of the production process. It is anticipated that by closely monitoring individual animals using the proposed system, the finishing period of the animal will be reduced on average by 14 days, while animals performing poorly dues to illness will be flagged up to the farmer allowing for earlier intervention.

Summary

There is ever-increasing financial pressure in the UK beef sector due to volatile feed prices, consumer requirements for cheaper produce and competitive beef imports from abroad. Optimising animal productivity is critical to maintaining a competitive and sustainable UK beef industry with production efficiency the greatest single opportunity to reduce primary production costs. At present, there is considerable inefficiency in the UK beef sector which increases variable farm costs, reduces the yearly capacity of beef finishing units, and reduces profitability due to sub-optimal marketing of animals. These inefficiencies are estimated to reduce overall profitability of the UK beef production industry by approximately £500M per year (Morrisons estimate based on their experience from their integrated beef supply chain). The reduced revenue associated with these inefficiencies arise for three main reasons: (1) retaining cattle on-farm beyond the optimum point of marketability leading to extra feed, bedding and fixed costs; (2) reductions in sale revenue due to these over-finished cattle being out of desired specification (i.e. too fat) and (3) loss of productivity and efficiency due to poor animal health. From a biological perspective it has been shown that there is a large between-animal variation in feed efficiency; early results from the TSB-funded Net Feed Efficiency project (BIG/NFE), have suggested a variance of up to 30 percent in feed efficiency of groups of growing and finishing cattle of the same age/breed/sex. The differences between groups of more divergent genotypes might reasonably be expected to be greater still. Profitability and efficiency are also inhibited by illness, with efficiency often dropping well in advance of any clinical signs of illness. In practice, it is difficult for farmers to measure the performance efficiency of individual animals. Currently, animal growth and performance is determined through visual assessment or by weighing theanimals. However, growth rates alone are not a measure of efficiency; in order to calculate efficiency of individual animals an accurate measurement of feed input is also required. The project addresses some of the key challenges facing the sustainable intensification of beef. The overall aim is to develop a state-of-the art solution for beef farmers to optimise the efficiency of their businesses. At the core of the project is the development of a near infra-red (NIR) system to characterise feed (dry matter content, nutritional composition) as it exits a feeder wagon. Also pivotal to the project is the development of animal-mounted sensors to measure feeding behaviour (eating and rumination patterns). The bulk feed characteristics will be integrated with the feeding behaviour data with a target of providing a robust, accurate and innovative method of determining individual animal feed intake. The final solution will be a cloud-based decision support platform integrating individual animal feed intake and behaviour data, with measures of animal performance e.g. growth rates. This will provide the support tools necessary to quantify performance and efficiency of individual animals and improve the sustainability of the production process. It is anticipated that by closely monitoring individual animals using the system proposed in this project, the finishing period of the animal will be reduced on average by 14 days, while animals performing poorly due to illness will be flagged up to the farmer allowing for earlier intervention.

Impact Summary

The following areas will benefit from the proposed research: 1. UK beef producers a. The proposed system will allow farmers to identify inefficient and poorly performing animals and help them to make informed decisions to increase the overall efficiency of their beef production unit. b. The system will allow farmers to accurately measure the composition of the diet given to each group of animals and allow for more accurate formation of diets to fulfil the nutritional requirements of the animals. c. Use of the proposed system will allow the farmer to optimally market their animals (i.e. to meet optimum market specification). This will reduce the number of animals kept on farm beyond their optimal point of marketability, thus reducing finishing times on average. This will reduce the variable costs associated with beef production (such as feeding and bedding) and allow for a higher throughput of animals through finishing units, thus optimising the productive output and improving the economics of their business. It will also prevent abattoir cost-penalties associated with over-finished (i.e. too fat) animals. d. As the UK commercial partners will have first access to the technology they will be the first to benefit. Reducing farm costs should increase the competitiveness of the UK beef industry and make their products more competitive against foreign competitors. 2. Meat processers a. By sourcing animals from producers using the proposed system, meat processers will receive animals which are optimally finished, with more desirable carcass conformation and fat grades and killing-out percentage. This will lead to more efficient processing with reduced labour requirements to trim fat from over-fat animals and reduce costs associated with fat disposal. b. Sourcing animals finished using this system will also allow for increased uniformity of the product for retail, as the animals will be marketed at the optimal market specification. 3. Consumers a. The use of this system will likely result in cheaper beef being available to the consumer as variable costs during the production process will be reduced. b. Cheaper UK beef will make it easier for consumers to choose local products over foreign alternatives. 4. The UK a. The technological systems proposed will enhance the economic efficiency of UK beef production, thus increasing the sectors competitiveness over imported beef and guaranteeing the sustainability of the UK beef industry. b. Reduced production costs and efficient production methods could enhance the reputation of UK beef and increase the value of UK beef exports. c. There will be a reduced environmental footprint from more efficient beef production, reduced farm resources and reduced abattoir waste. The quantity of beef produced per unit of greenhouse gas will be reduced. d. Increasing the profitability of the UK beef farming sector will lead to social benefits including enhanced rural employment. 5. Animal welfare a. Increased monitoring of animal performance will allow for poorly performing animals to be identified earlier. Poor performance often manifests through ill health, often before the clinical signs of illness become apparent. Therefore, the use of this system will allow for illnesses to be detected and treated earlier, thus reducing the negative impacts of illness (in cost and waste).

Committee	Research Committee B (Plants, microbes, food & sustainability)
Research Topics	Animal Health
Research Priority	X – Research Priority information not available
Research Initiative	Agri-Tech Catalyst (ATC) [2013-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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