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SCOUT: An in-vivo Methane Sensing System for Real-time Monitoring of Enteric Emissions in Cattle with ex-vivo Validation (2508.04056v1)

Published 6 Aug 2025 in cs.RO and q-bio.QM

Abstract: Accurate measurement of enteric methane emissions remains a critical bottleneck for advancing livestock sustainability through genetic selection and precision management. Existing ambient sampling approaches suffer from low data retention rates, environmental interference, and limited temporal resolution. We developed SCOUT (Smart Cannula-mounted Optical Unit for Trace-methane), the first robust in-vivo sensing system enabling continuous, high-resolution monitoring of ruminal methane concentrations through an innovative closed-loop gas recirculation design. We conducted comprehensive validation with two cannulated Simmental heifers under contrasting dietary treatments, with cross-platform comparison against established ambient sniffer systems. SCOUT achieved exceptional performance with 82% data retention compared to 17% for conventional sniffer systems, while capturing methane concentrations 100-1000x higher than ambient approaches. Cross-platform validation demonstrated strong scale-dependent correlations, with optimal correlation strength (r = -0.564 $\pm$ 0.007) at biologically relevant 40-minute windows and 100% statistical significance. High-frequency monitoring revealed novel behavior-emission coupling, including rapid concentration changes (14.5 $\pm$ 11.3k ppm) triggered by postural transitions within 15 minutes, insights previously inaccessible through existing technologies. The SCOUT system represents a transformative advancement, enabling accurate, continuous emission phenotyping essential for genomic selection programs and sustainable precision livestock management. This validation framework establishes new benchmarks for agricultural sensor performance while generating unprecedented biological insights into ruminal methane dynamics, contributing essential tools for sustainable livestock production in climate-conscious agricultural systems.

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