Cécile M. Levrault , Peter W.G. Groot Koerkamp , Carel F.W. Peeters , Nico W.M. Ogink
{"title":"Evaluation of the cubicle hood sampler for monitoring methane production of dairy cows under barn conditions","authors":"Cécile M. Levrault , Peter W.G. Groot Koerkamp , Carel F.W. Peeters , Nico W.M. Ogink","doi":"10.1016/j.biosystemseng.2025.02.008","DOIUrl":null,"url":null,"abstract":"<div><div>Monitoring methane production from individual cows is necessary to evaluate the success of greenhouse gas reduction strategies. However, monitoring methane production rates (<strong>MPR</strong>) under practical conditions remains challenging. In this paper, we investigate the performance of a potential solution to this challenge.</div><div>The cubicle hood sampler (<strong>CHS</strong>) is an on-barn monitoring device placed in cubicles that collects the air exhaled by the animals while they lie down. The MPR of 28 dairy cows were measured by four CHS devices and compared to the levels measured by climate respiration chambers (<strong>CRC</strong>). A linear regression showed no strong correlation between the two sets of estimates (<em>r</em> = 0.24). The estimates made by the CHS appeared to be inaccurate due to a sampling bias (insufficient breath recovery), which could not be corrected for. Using Bayesian modelling, information was pooled across individuals to model complete methane production curves and potentially improve the accuracy of the MPR estimates. However, the model was unable to compensate for the biased observations used for fitting, and accuracy levels did not improve. An under-recovery of the breath samples by the hood is suspected. These issues must be resolved. Nevertheless, the CHS ranked cows satisfactorily, with Kendall W values of 0.625 (<em>p</em> = 0.201) in the original dataset, and 0.659 (<em>p</em> = 0.214) after using the model. Resolving the bias issue is expected to have a simultaneous positive effect on the agreement between the two MPR rankings. We recommend to keep using the model to convert discrete measurements into methane production curves.</div></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"252 ","pages":"Pages 115-125"},"PeriodicalIF":4.4000,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1537511025000340","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Monitoring methane production from individual cows is necessary to evaluate the success of greenhouse gas reduction strategies. However, monitoring methane production rates (MPR) under practical conditions remains challenging. In this paper, we investigate the performance of a potential solution to this challenge.
The cubicle hood sampler (CHS) is an on-barn monitoring device placed in cubicles that collects the air exhaled by the animals while they lie down. The MPR of 28 dairy cows were measured by four CHS devices and compared to the levels measured by climate respiration chambers (CRC). A linear regression showed no strong correlation between the two sets of estimates (r = 0.24). The estimates made by the CHS appeared to be inaccurate due to a sampling bias (insufficient breath recovery), which could not be corrected for. Using Bayesian modelling, information was pooled across individuals to model complete methane production curves and potentially improve the accuracy of the MPR estimates. However, the model was unable to compensate for the biased observations used for fitting, and accuracy levels did not improve. An under-recovery of the breath samples by the hood is suspected. These issues must be resolved. Nevertheless, the CHS ranked cows satisfactorily, with Kendall W values of 0.625 (p = 0.201) in the original dataset, and 0.659 (p = 0.214) after using the model. Resolving the bias issue is expected to have a simultaneous positive effect on the agreement between the two MPR rankings. We recommend to keep using the model to convert discrete measurements into methane production curves.
期刊介绍:
Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.