Abstract
Indirect calorimetry (IC) is a widely used method to study animal energy metabolism by measuring gas exchange. The accuracy of IC depends on detecting variations in signals reflecting the metabolic response, which can be challenging due to measurement noise and external factors. This study proposes a methodology to validate IC systems, including an easy-to-use spreadsheet for data computing, to verify accuracy and detect whole-system leaks. We conducted a recovery test using a simulation of CO(2) dynamics in MS Excel and injecting a known CO(2) concentration into four respirometry chambers. The thought flow rate of CO(2) was observed and compared to the expected rate from the simulation. Data filtering and computing, including a detailed calculation of signals calibration, Bartholomew transformation, and noise reduction, was developed to obtain the gas exchange and heat production parameters using an open-circuit IC system. The results from the recovery test in our system show that the proposed methodology is accurate and precise. The proposed methodology and recovery test can be used to standardize the validation of IC systems together with adequate data computing, providing accurate measurements of animal energy metabolism in different environmental conditions and energy utilization from feeds.