Due to the challenges in (near-)real-time disease detection on dairy farms, sick cows are often found late in practice, decreasing the chance of successful treatment and recovery of the animal. Ultimately, this leads to impaired animal welfare and economic losses. Therefore, real-time, non-invasive monitoring tools are continuously being studied in research and implemented on the dairy farms. When we think of gases emitted through the nose and mouth of cows, we typically think of methane emissions. Should we stop here, or should we investigate a little further? In the dairy use-case of the AGROS project (financed by TKI Agro & Food, IMEC/OnePlanet, and Melkveefonds) we have been working on broadening the scope of breath analysis. In this journey beyond methane emissions, one particular area of interest is disease detection.
In order to have an overview of the state of the art knowledge and methods, we systematically reviewed the literature on using breath analysis to distinguish diseased cattle from the not diseased ones. From an initial pool of more than 200 research papers, we narrowed down the body of research to be investigated in depth. Some of the main results were presented last year at the Welfare Quality Network Seminar in Wageningen. Research on breath analysis to detect diseased cattle focused mostly on cows before the year 2000, however, calves have been studied more frequently since then. Ketosis has been the most studied cattle disease using breath analysis so far, but the results show potential to detect more than only ketosis events.
Furthermore, we participated in an experiment in collaboration with HAS green academy, to evaluate the potential of breath acetone concentration to follow ketosis status in Holstein cows. We found that the rise in serum β-hydroxybutyrate (one of the main biomarkers of ketosis in cows) was related to a rise in breath acetone concentration. We also showed that longitudinal records would be necessary to detect increasing breath acetone levels within individual cows, instead of single spot measurements.
This year we will continue our work to further explore the capabilities of breath analysis as a real-time, non-invasive monitoring tool on the dairy farm of the future.