Literature DB >> 17582129

Prediction of methane production from dairy and beef cattle.

J L Ellis1, E Kebreab, N E Odongo, B W McBride, E K Okine, J France.   

Abstract

Methane (CH4) is one of the major greenhouse gases being targeted for reduction by the Kyoto protocol. The focus of recent research in animal science has thus been to develop or improve existing CH4 prediction models to evaluate mitigation strategies to reduce overall CH4 emissions. Eighty-three beef and 89 dairy data sets were collected and used to develop statistical models of CH4 production using dietary variables. Dry matter intake (DMI), metabolizable energy intake, neutral detergent fiber, acid detergent fiber, ether extract, lignin, and forage proportion were considered in the development of models to predict CH4 emissions. Extant models relevant to the study were also evaluated. For the beef database, the equation CH4 (MJ/d) = 2.94 (+/- 1.16) + 0.059 (+/- 0.0201) x metabolizable energy intake (MJ/d) + 1.44 (+/- 0.331) x acid detergent fiber (kg/d) - 4.16 (+/- 1.93) x lignin (kg/d) resulted in the lowest root mean square prediction error (RMSPE) value (14.4%), 88% of which was random error. For the dairy database, the equation CH4 (MJ/d) = 8.56 (+/- 2.63) + 0.14 (+/- 0.056) x forage (%) resulted in the lowest RMSPE value (20.6%) and 57% of error from random sources. An equation based on DMI also performed well for the dairy database: CH4 (MJ/d) = 3.23 (+/- 1.12) + 0.81 (+/- 0.086) x DMI (kg/d), with a RMSPE of 25.6% and 91% of error from random sources. When the dairy and beef databases were combined, the equation CH4 (MJ/d) = 3.27 (+/- 0.79) + 0.74 (+/- 0.074) x DMI (kg/d) resulted in the lowest RMSPE value (28.2%) and 83% of error from random sources. Two of the 9 extant equations evaluated predicted CH4 production adequately. However, the new models based on more commonly determined values showed an improvement in predictions over extant equations.

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Year:  2007        PMID: 17582129     DOI: 10.3168/jds.2006-675

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  24 in total

1.  Contribution of milk production to global greenhouse gas emissions. An estimation based on typical farms.

Authors:  Martin Hagemann; Asaah Ndambi; Torsten Hemme; Uwe Latacz-Lohmann
Journal:  Environ Sci Pollut Res Int       Date:  2011-07-27       Impact factor: 4.223

2.  Methane emissions from river buffaloes fed on green fodders in relation to the nutrient [corrected] intake and digestibility.

Authors:  Sonali Prusty; Madhu Mohini; Shivlal Singh Kundu; Ajay Kumar; Chander Datt
Journal:  Trop Anim Health Prod       Date:  2013-07-16       Impact factor: 1.559

3.  Measurement and prediction of enteric methane emission.

Authors:  Veerasamy Sejian; Rattan Lal; Jeffrey Lakritz; Thaddeus Ezeji
Journal:  Int J Biometeorol       Date:  2010-09-01       Impact factor: 3.787

4.  Nutritional and ecological evaluation of dairy farming systems based on concentrate feeding regimes in semi-arid environments of Jordan.

Authors:  Othman Alqaisi; Torsten Hemme; Martin Hagemann; Andreas Susenbeth
Journal:  Saudi J Biol Sci       Date:  2013-05-11       Impact factor: 4.219

Review 5.  Methanogens: methane producers of the rumen and mitigation strategies.

Authors:  Sarah E Hook; André-Denis G Wright; Brian W McBride
Journal:  Archaea       Date:  2010-12-30       Impact factor: 3.273

Review 6.  Methods for Measuring and Estimating Methane Emission from Ruminants.

Authors:  Ida M L D Storm; Anne Louise F Hellwing; Nicolaj I Nielsen; Jørgen Madsen
Journal:  Animals (Basel)       Date:  2012-04-13       Impact factor: 2.752

7.  Relationship between the Methane Production and the CNCPS Carbohydrate Fractions of Rations with Various Concentrate/roughage Ratios Evaluated Using In vitro Incubation Technique.

Authors:  Ruilan Dong; Guangyong Zhao
Journal:  Asian-Australas J Anim Sci       Date:  2013-12       Impact factor: 2.509

8.  Effects of Flavonoid-rich Plant Extracts on In vitro Ruminal Methanogenesis, Microbial Populations and Fermentation Characteristics.

Authors:  Eun T Kim; Le Luo Guan; Shin J Lee; Sang M Lee; Sang S Lee; Il D Lee; Su K Lee; Sung S Lee
Journal:  Asian-Australas J Anim Sci       Date:  2015-04       Impact factor: 2.509

9.  Effects of Medicinal Herb Extracts on In vitro Ruminal Methanogenesis, Microbe Diversity and Fermentation System.

Authors:  Eun Tae Kim; Hee Soon Hwang; Sang Min Lee; Shin Ja Lee; Il Dong Lee; Su Kyoung Lee; Da Som Oh; Jung Hwa Lim; Ho Baek Yoon; Ha Yeon Jeong; Seok Ki Im; Sung Sill Lee
Journal:  Asian-Australas J Anim Sci       Date:  2016-03-22       Impact factor: 2.509

10.  Modelling the Effect of Diet Composition on Enteric Methane Emissions across Sheep, Beef Cattle and Dairy Cows.

Authors:  Matt Bell; Richard Eckard; Peter J Moate; Tianhai Yan
Journal:  Animals (Basel)       Date:  2016-09-08       Impact factor: 2.752

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