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Functionalized Graphene-Based Biosensors for Early Detection of Subclinical Ketosis in Dairy Cows
Shannon Chick1, Matin Ataei Kachouei1, Katharine Knowlton1
1School of Animal Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States.
Abstract:
Precision livestock farming utilizing advanced diagnostic tools, including biosensors, can play a key role in the management of livestock operations to improve the productivity, health, and well-being of animals. Detection of ketosis, a metabolic disease that occurs in early lactation dairy cows due to a negative energy balance, is one potential on-farm use of biosensors. Beta-hydroxybutyrate (βHB) is an excellent biomarker for monitoring ketosis in dairy cows because βHB is one of the main ketones produced during this metabolic state. In this report, we developed a low-cost, Keto-sensor (graphene-based sensor) for the detection of βHB concentrations in less than a minute. On this device, graphene nanosheets were layered onto a screen-printed electrode (SPE), and then, a stabilized enzyme (beta-hydroxybutyrate dehydrogenase, NAD+, and glycerol) was used to functionalize the graphene surface enabled by EDC-NHS conjugation chemistry. The Keto-sensor offers an analytical sensitivity of 10 nm and a limit of detection (LoD) of 0.24 nm within a detection range of 0.01 μm-3.00 mm. Spike testing indicates that the Keto-sensor can detect βHB in serum samples from bovines with subclinical ketosis. The Keto-sensor developed in this study shows promising results for early detection of subclinical ketosis on farms.
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