### Abstract

Ruminants contribute to global warming by releasing methane (CH_{4}) gas to the atmosphere. This has increased interest among animal scientists to develop and improve methods measuring CH_{4} production in dairy cows. The GreenFeed emission monitoring unit (GEM) was introduced to estimate CH_{4} production by measuring gas concentration and flux when cattle visit a GEM. The objective of the present study was to compare CH_{4} production measured by the GEM with equations predicting CH_{4} production. Evaluation was based on 83 treatment means from dairy (n = 65) and growing cattle (n = 18) studies, in which CH_{4} 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 R^{2} values (in most cases > 0.90), but there were considerable differences in RMSPE. Generally, the equations based on CH_{4} 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 CH_{4} 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 CH_{4} production measured by RC and GEM (R^{2} = 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 CH_{4} emissions measured by the GEM system agreed well with values predicted by empirical models derived from RC data suggesting indirectly that enteric CH_{4} emission can be reliably measured by the GEM system.

Original language | English (US) |
---|---|

Pages (from-to) | 31-40 |

Number of pages | 10 |

Journal | Livestock Science |

Volume | 222 |

DOIs | |

State | Published - Apr 2019 |

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### All Science Journal Classification (ASJC) codes

- Animal Science and Zoology
- veterinary(all)

### Cite this

*Livestock Science*,

*222*, 31-40. https://doi.org/10.1016/j.livsci.2019.01.017

}

*Livestock Science*, vol. 222, pp. 31-40. https://doi.org/10.1016/j.livsci.2019.01.017

**Enteric methane emission can be reliably measured by the GreenFeed monitoring unit.** / Huhtanen, P.; Ramin, M.; Hristov, A. N.

Research output: Contribution to journal › Article

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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UR - http://www.scopus.com/inward/citedby.url?scp=85061810374&partnerID=8YFLogxK

U2 - 10.1016/j.livsci.2019.01.017

DO - 10.1016/j.livsci.2019.01.017

M3 - Article

AN - SCOPUS:85061810374

VL - 222

SP - 31

EP - 40

JO - Livestock Science

JF - Livestock Science

SN - 1871-1413

ER -