Literature DB >> 28161178

Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions.

E Negussie1, Y de Haas2, F Dehareng3, R J Dewhurst4, J Dijkstra5, N Gengler6, D P Morgavi7, H Soyeurt6, S van Gastelen5, T Yan8, F Biscarini9.   

Abstract

Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH4) emissions from individual cows. Several techniques have been developed to measure CH4 in a research setting but most are not suitable for large-scale recording on farm. Several groups have explored proxies (i.e., indicators or indirect traits) for CH4; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH4 proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The proxies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbiome profiling. Proxies based on rumen samples are generally poor to moderately accurate predictors of CH4, and are costly and difficult to measure routinely on-farm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH4 emission in dairy cows. No single proxy was found to accurately predict CH4, and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of variation in CH4 and one proxy can correct for shortcomings in the other(s). The most important applications of CH4 proxies are in dairy cattle management and breeding for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavorable correlated responses. Finally, although combinations of proxies appear to provide the most accurate estimates of CH4, the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Entities:  

Keywords:  breeding; dairy cattle; enteric methane; management; proxy

Mesh:

Substances:

Year:  2017        PMID: 28161178     DOI: 10.3168/jds.2016-12030

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


  23 in total

1.  Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle.

Authors:  Adrián López-García; Alejandro Saborío-Montero; Mónica Gutiérrez-Rivas; Raquel Atxaerandio; Idoia Goiri; Aser García-Rodríguez; Jose A Jiménez-Montero; Carmen González; Javier Tamames; Fernando Puente-Sánchez; Magdalena Serrano; Rafael Carrasco; Cristina Óvilo; Oscar González-Recio
Journal:  Gigascience       Date:  2022-01-25       Impact factor: 6.524

2.  Eating Time as a Genetic Indicator of Methane Emissions and Feed Efficiency in Australian Maternal Composite Sheep.

Authors:  Boris J Sepulveda; Stephanie K Muir; Sunduimijid Bolormaa; Matthew I Knight; Ralph Behrendt; Iona M MacLeod; Jennie E Pryce; Hans D Daetwyler
Journal:  Front Genet       Date:  2022-05-11       Impact factor: 4.772

3.  Effects of dietary forage-to-concentrate ratio on nutrient digestibility and enteric methane production in growing goats (Capra hircus hircus) and Sika deer (Cervus nippon hortulorum).

Authors:  Youngjun Na; Dong Hua Li; Sang Rak Lee
Journal:  Asian-Australas J Anim Sci       Date:  2017-03-21       Impact factor: 2.509

4.  Rumen microbiome in dairy calves fed copper and grape-pomace dietary supplementations: Composition and predicted functional profile.

Authors:  Filippo Biscarini; Fiorentina Palazzo; Federica Castellani; Giulia Masetti; Lisa Grotta; Angelo Cichelli; Giuseppe Martino
Journal:  PLoS One       Date:  2018-11-29       Impact factor: 3.240

5.  Genome-wide association identifies methane production level relation to genetic control of digestive tract development in dairy cows.

Authors:  M Pszczola; T Strabel; S Mucha; E Sell-Kubiak
Journal:  Sci Rep       Date:  2018-10-11       Impact factor: 4.379

6.  Polyomic tools for an emerging livestock parasite, the rumen fluke Calicophoron daubneyi; identifying shifts in rumen functionality.

Authors:  Kathryn M Huson; Russell M Morphew; Nathan R Allen; Matthew J Hegarty; Hillary J Worgan; Susan E Girdwood; Eleanor L Jones; Helen C Phillips; Martin Vickers; Martin Swain; Daniel Smith; Alison H Kingston-Smith; Peter M Brophy
Journal:  Parasit Vectors       Date:  2018-12-04       Impact factor: 3.876

Review 7.  Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

Authors:  Esté van Marle-Köster; Carina Visser
Journal:  Front Genet       Date:  2018-08-23       Impact factor: 4.599

8.  Bacterial direct-fed microbials fail to reduce methane emissions in primiparous lactating dairy cows.

Authors:  Jeyamalar Jeyanathan; Cécile Martin; Maguy Eugène; Anne Ferlay; Milka Popova; Diego P Morgavi
Journal:  J Anim Sci Biotechnol       Date:  2019-05-02

9.  Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets.

Authors:  Marc D Auffret; Robert Stewart; Richard J Dewhurst; Carol-Anne Duthie; John A Rooke; Robert J Wallace; Tom C Freeman; Timothy J Snelling; Mick Watson; Rainer Roehe
Journal:  Front Microbiol       Date:  2018-01-09       Impact factor: 5.640

10.  Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database.

Authors:  Mutian Niu; Ermias Kebreab; Alexander N Hristov; Joonpyo Oh; Claudia Arndt; André Bannink; Ali R Bayat; André F Brito; Tommy Boland; David Casper; Les A Crompton; Jan Dijkstra; Maguy A Eugène; Phil C Garnsworthy; Md Najmul Haque; Anne L F Hellwing; Pekka Huhtanen; Michael Kreuzer; Bjoern Kuhla; Peter Lund; Jørgen Madsen; Cécile Martin; Shelby C McClelland; Mark McGee; Peter J Moate; Stefan Muetzel; Camila Muñoz; Padraig O'Kiely; Nico Peiren; Christopher K Reynolds; Angela Schwarm; Kevin J Shingfield; Tonje M Storlien; Martin R Weisbjerg; David R Yáñez-Ruiz; Zhongtang Yu
Journal:  Glob Chang Biol       Date:  2018-03-08       Impact factor: 10.863

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.