Enteric methane emission can be reliably measured by the GreenFeed monitoring unit

P. Huhtanen, M. Ramin, A. N. Hristov

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Ruminants contribute to global warming by releasing methane (CH4) gas to the atmosphere. This has increased interest among animal scientists to develop and improve methods measuring CH4 production in dairy cows. The GreenFeed emission monitoring unit (GEM) was introduced to estimate CH4 production by measuring gas concentration and flux when cattle visit a GEM. The objective of the present study was to compare CH4 production measured by the GEM with equations predicting CH4 production. Evaluation was based on 83 treatment means from dairy (n = 65) and growing cattle (n = 18) studies, in which CH4 production was measured by GEM. Methane production was predicted from intake and nutrient composition data with 18 empirical equations derived mainly from respiration chamber (RC) datasets. A comparison of observed and predicted values were performed for all equations using fixed and mixed regression models. The evaluation was based on root mean squared prediction error (RMSPE) expressed as a proportion of observed mean. All equations were precise in terms of high R2 values (in most cases > 0.90), but there were considerable differences in RMSPE. Generally, the equations based on CH4 yield and dry matter or gross energy intake resulted in the smallest RMSPE. When expressed as a proportion of observed mean, RMSPE for the 18 equations was 11.2%, and it ranged from 6.9 to 28.4%. Twelve equations had RMSPE less than 10% of observed mean. Ranking of the models remained rather similar when the relationships between predicted and measured CH4 production was estimated using the mixed model regression analysis. Following the exclusion of 2 equations with large mean bias, RMSPE adjusted from random study effects was on average 6.2% of observed mean. Root MSPE were smaller than the corresponding errors in development of the equations, probably reflecting more standardized calibrations of the GEM system between laboratories compared with RC. In direct comparisons (n = 20) there was a good relationship in CH4 production measured by RC and GEM (R2 = 0.92). Root MSPE was 35.7 g/d (12.9% of the observed) with mean bias, slope bias and random error being 12, 0 and 88% of MSPE, respectively. Results from the current analysis indicated that CH4 emissions measured by the GEM system agreed well with values predicted by empirical models derived from RC data suggesting indirectly that enteric CH4 emission can be reliably measured by the GEM system.

Original languageEnglish (US)
Pages (from-to)31-40
Number of pages10
JournalLivestock Science
Volume222
DOIs
StatePublished - Apr 2019

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Methane
methane
Respiration
methane production
monitoring
Gases
prediction
Global Warming
Ruminants
breathing
Energy Intake
Atmosphere
Calibration
Regression Analysis
Food
gases
cattle
global warming
ruminants
dairies

All Science Journal Classification (ASJC) codes

  • Animal Science and Zoology
  • veterinary(all)

Cite this

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title = "Enteric methane emission can be reliably measured by the GreenFeed monitoring unit",
abstract = "Ruminants contribute to global warming by releasing methane (CH4) gas to the atmosphere. This has increased interest among animal scientists to develop and improve methods measuring CH4 production in dairy cows. The GreenFeed emission monitoring unit (GEM) was introduced to estimate CH4 production by measuring gas concentration and flux when cattle visit a GEM. The objective of the present study was to compare CH4 production measured by the GEM with equations predicting CH4 production. Evaluation was based on 83 treatment means from dairy (n = 65) and growing cattle (n = 18) studies, in which CH4 production was measured by GEM. Methane production was predicted from intake and nutrient composition data with 18 empirical equations derived mainly from respiration chamber (RC) datasets. A comparison of observed and predicted values were performed for all equations using fixed and mixed regression models. The evaluation was based on root mean squared prediction error (RMSPE) expressed as a proportion of observed mean. All equations were precise in terms of high R2 values (in most cases > 0.90), but there were considerable differences in RMSPE. Generally, the equations based on CH4 yield and dry matter or gross energy intake resulted in the smallest RMSPE. When expressed as a proportion of observed mean, RMSPE for the 18 equations was 11.2{\%}, and it ranged from 6.9 to 28.4{\%}. Twelve equations had RMSPE less than 10{\%} of observed mean. Ranking of the models remained rather similar when the relationships between predicted and measured CH4 production was estimated using the mixed model regression analysis. Following the exclusion of 2 equations with large mean bias, RMSPE adjusted from random study effects was on average 6.2{\%} of observed mean. Root MSPE were smaller than the corresponding errors in development of the equations, probably reflecting more standardized calibrations of the GEM system between laboratories compared with RC. In direct comparisons (n = 20) there was a good relationship in CH4 production measured by RC and GEM (R2 = 0.92). Root MSPE was 35.7 g/d (12.9{\%} of the observed) with mean bias, slope bias and random error being 12, 0 and 88{\%} of MSPE, respectively. Results from the current analysis indicated that CH4 emissions measured by the GEM system agreed well with values predicted by empirical models derived from RC data suggesting indirectly that enteric CH4 emission can be reliably measured by the GEM system.",
author = "P. Huhtanen and M. Ramin and Hristov, {A. N.}",
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Enteric methane emission can be reliably measured by the GreenFeed monitoring unit. / Huhtanen, P.; Ramin, M.; Hristov, A. N.

In: Livestock Science, Vol. 222, 04.2019, p. 31-40.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Enteric methane emission can be reliably measured by the GreenFeed monitoring unit

AU - Huhtanen, P.

AU - Ramin, M.

AU - Hristov, A. N.

PY - 2019/4

Y1 - 2019/4

N2 - Ruminants contribute to global warming by releasing methane (CH4) gas to the atmosphere. This has increased interest among animal scientists to develop and improve methods measuring CH4 production in dairy cows. The GreenFeed emission monitoring unit (GEM) was introduced to estimate CH4 production by measuring gas concentration and flux when cattle visit a GEM. The objective of the present study was to compare CH4 production measured by the GEM with equations predicting CH4 production. Evaluation was based on 83 treatment means from dairy (n = 65) and growing cattle (n = 18) studies, in which CH4 production was measured by GEM. Methane production was predicted from intake and nutrient composition data with 18 empirical equations derived mainly from respiration chamber (RC) datasets. A comparison of observed and predicted values were performed for all equations using fixed and mixed regression models. The evaluation was based on root mean squared prediction error (RMSPE) expressed as a proportion of observed mean. All equations were precise in terms of high R2 values (in most cases > 0.90), but there were considerable differences in RMSPE. Generally, the equations based on CH4 yield and dry matter or gross energy intake resulted in the smallest RMSPE. When expressed as a proportion of observed mean, RMSPE for the 18 equations was 11.2%, and it ranged from 6.9 to 28.4%. Twelve equations had RMSPE less than 10% of observed mean. Ranking of the models remained rather similar when the relationships between predicted and measured CH4 production was estimated using the mixed model regression analysis. Following the exclusion of 2 equations with large mean bias, RMSPE adjusted from random study effects was on average 6.2% of observed mean. Root MSPE were smaller than the corresponding errors in development of the equations, probably reflecting more standardized calibrations of the GEM system between laboratories compared with RC. In direct comparisons (n = 20) there was a good relationship in CH4 production measured by RC and GEM (R2 = 0.92). Root MSPE was 35.7 g/d (12.9% of the observed) with mean bias, slope bias and random error being 12, 0 and 88% of MSPE, respectively. Results from the current analysis indicated that CH4 emissions measured by the GEM system agreed well with values predicted by empirical models derived from RC data suggesting indirectly that enteric CH4 emission can be reliably measured by the GEM system.

AB - Ruminants contribute to global warming by releasing methane (CH4) gas to the atmosphere. This has increased interest among animal scientists to develop and improve methods measuring CH4 production in dairy cows. The GreenFeed emission monitoring unit (GEM) was introduced to estimate CH4 production by measuring gas concentration and flux when cattle visit a GEM. The objective of the present study was to compare CH4 production measured by the GEM with equations predicting CH4 production. Evaluation was based on 83 treatment means from dairy (n = 65) and growing cattle (n = 18) studies, in which CH4 production was measured by GEM. Methane production was predicted from intake and nutrient composition data with 18 empirical equations derived mainly from respiration chamber (RC) datasets. A comparison of observed and predicted values were performed for all equations using fixed and mixed regression models. The evaluation was based on root mean squared prediction error (RMSPE) expressed as a proportion of observed mean. All equations were precise in terms of high R2 values (in most cases > 0.90), but there were considerable differences in RMSPE. Generally, the equations based on CH4 yield and dry matter or gross energy intake resulted in the smallest RMSPE. When expressed as a proportion of observed mean, RMSPE for the 18 equations was 11.2%, and it ranged from 6.9 to 28.4%. Twelve equations had RMSPE less than 10% of observed mean. Ranking of the models remained rather similar when the relationships between predicted and measured CH4 production was estimated using the mixed model regression analysis. Following the exclusion of 2 equations with large mean bias, RMSPE adjusted from random study effects was on average 6.2% of observed mean. Root MSPE were smaller than the corresponding errors in development of the equations, probably reflecting more standardized calibrations of the GEM system between laboratories compared with RC. In direct comparisons (n = 20) there was a good relationship in CH4 production measured by RC and GEM (R2 = 0.92). Root MSPE was 35.7 g/d (12.9% of the observed) with mean bias, slope bias and random error being 12, 0 and 88% of MSPE, respectively. Results from the current analysis indicated that CH4 emissions measured by the GEM system agreed well with values predicted by empirical models derived from RC data suggesting indirectly that enteric CH4 emission can be reliably measured by the GEM system.

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