The global population is predicted to reach 9 Billion by 2050. As a consequence, increasing competition for land resource against a backdrop of climate change agricultural practices are presenting farmers with a range of challenges to improve operational efficiency and reduce greenhouse emissions.
In Europe, agriculture contributes approximately 10.4% of GHG emission, with enteric emission accounting for 30% of this value. The dominant emission is in the form of enteric methane and accurately quantifying individual emissions would allow greater understanding and subsequent manipulation of systems and genetics to reduce overall GHG production. However, presently there is no effective measurement method for quantifying emissions on individual animals. Traditional respiration chambers have been used to measure total enteric emissions, and are considered accurate if properly calibrated during the testing phase and appropriate protocols are implemented. However, these chambers are not transferable to production settings, particularly where grazing cattle are concerned. The current standard method for estimating methane emissions from individual grazing cattle requires that a sulphur hexafluoride (SF6) tracer gas is administered to the animal using a controlled release bolus. A gas collection systems aspirates breath from a grazing cow into a cylinder. The concentration of SF6 in the cylinder is used to calibrate the volume of air that has been collected from the animal versus that from the surrounding environment to facilitate calibration of measured methane levels. The technique (Johnson et al., 1994), is laborious, imprecise and provides a single point of measurement per day. These difficulties mean that there remains significant uncertainty about methane emissions from grazing cattle – both the natural variation and effects of additives designed to reduce emissions.
A wide range of technologies for measuring CH4 and CO2 are well understood but at present there is no effective means of targeting these measurements to individual animals. This project will research and implement miniaturised CH4 and CO2 sensors that can be deployed on individuals. It is anticipated that optical methods other than standard NDIR measurements will be required to obtain the required measurement sensitivity. Photo-acoustic gas sensors are considered likely candidates in this regard building upon a significant body of research within the Centre for Micro-Photonics by Dr M Lengden and Dr R Bauer. An animal-mounted sensor (‘Methcollar’) will be designed and calibrated to measure concentrations of methane and carbon dioxide in real-time. Carbon dioxide output will also be related to daily milk energy output (energy intake).
Significant challenges are presented in the proposed research. Effective aspiration of animals, optimisation of ratiometric analysis between CH4 and CO2 to obtain precise measurements of CH4 and to estimate the calorific output of individuals. The sensors will be designed, prototyped for deployment on individual animals, feed troughs and in milking robots to optimize design. They will be used in conjunction with selective Ion Mass Flow Spectroscopy to analyse breath for volatile organic compounds as diagnostic tools to facilitate the calculation of feed conversion efficiency. The outputs from the measurements will support the analysis of the nutrient efficiency of cattle and the effect of feed additives. Such additives can lead to significant reductions in methane emissions but run the risk of causing rumen dysfunction which will impair nutrient efficiency. If informed changes in management practice as a result of implementation of this technique reduced GHG emissions by 0.1% this could amount to as much as 1.1MT CO2 equiv. reduction globally across the cattle population.
Johnson, K., Huyler, M., Westberg, H., Lamb, B. and Zimmerman, P. (1994). Measurement of methane emissions from ruminant livestock using a SF6 tracer technique. Environmental Science & Technology 28: 359-362.
Masters level degree in Physics, either an MPhys at minimum 2.1 classification, or an MSc at minimum Merit classification. Candidates with a BSc at 1st class classification and with additional research experience will also be considered.
Programming in C#, Python. Ideally someone with an agricultural background.
The student will work between the Technology Innovation Centre (TIC) at Strathclyde and on farm at SRUC Barony campus. A range of state of the art experimental laboratory facilities in the TIC will be available to students undertaking the gas sensor research. These will be deployed within operational test facilities at SRUC Barony campus and other facilities that are appropriate. It is anticipated that use will also be made state of the art respiration chambers at SRUC’s GreenCow facility, which are used to measure gas emissions from cattle and sheep. These chambers facilitate the measurement of energy expenditure and methane emissions.
Flexible Research Working
We are happy to have discussions in this context.