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Worku D. Unraveling the genetic basis of methane emission in dairy cattle: a comprehensive exploration and breeding approach to lower methane emissions. Anim Biotechnol 2024; 35:2362677. [PMID: 38860914 DOI: 10.1080/10495398.2024.2362677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
Ruminant animals, such as dairy cattle, produce CH4, which contributes to global warming emissions and reduces dietary energy for the cows. While the carbon foot print of milk production varies based on production systems, milk yield and farm management practices, enteric fermentation, and manure management are major contributors togreenhouse gas emissions from dairy cattle. Recent emerging evidence has revealed the existence of genetic variation for CH4 emission traits among dairy cattle, suggests their potential inclusion in breeding goals and genetic selection programs. Advancements in high-throughput sequencing technologies and analytical techniques have enabled the identification of potential metabolic biomarkers, candidate genes, and SNPs linked to methane emissions. Indeed, this review critically examines our current understanding of carbon foot print in milk production, major emission sources, rumen microbial community and enteric fermentation, and the genetic architecture of methane emission traits in dairy cattle. It also emphasizes important implications for breeding strategies aimed at halting methane emissions through selective breeding, microbiome driven breeding, breeding for feed efficiency, and breeding by gene editing.
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Affiliation(s)
- Destaw Worku
- Department of Animal Science, College of Agriculture, Food and Climate Science, Injibara University, Injibara, Ethiopia
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2
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Carroll AL, Spangler ML, Morris DL, Kononoff PJ. Partitioning among-animal variance of energy utilization in lactating Jersey cows. J Dairy Sci 2024:S0022-0302(24)00861-0. [PMID: 38825139 DOI: 10.3168/jds.2024-24740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 04/18/2024] [Indexed: 06/04/2024]
Abstract
Animals vary in the way in which they utilize energy due to diet, genetics, and management. Energy consumed by the animal supports milk production, but considerable variation among-animals in energy utilization is thought to exist. The study objective was to estimate the among-animal variance in energy utilization in data collected from Jersey cows using indirect calorimetry. Individual animal-period data from 15 studies (n = 560) were used. The data set included 115 animals from 44 to 410 DIM producing 11.5 to 39.1 kg/d of milk. On average, the 63 treatments in the data set ranged 14.8 to 19.5% CP, 21.4 to 43.0% NDF, 16.2 to 33.3% starch, and 2.21 to 6.44% crude fat. Data were analyzed with the Glimmix procedure of SAS (9.4) with random effects of cow, treatment nested within period, square, and experiment. The percentage of among-animal, dietary treatment, and experimental variance was calculated as the variance associated with each fraction divided by the sum of variance from animal, dietary treatment, experiment, and residual which was considered the total variance. The percentage of among-animal variance was characterized as high or low when the value was greater than or less than the mean value of 29.2%. Among-animal variance explained approximately 29.3 - 42.5% of the total variance in DM intake (DMI), gross energy (GE), digestible energy (DE), metabolizable energy (ME), and net energy of lactation (NEL) in Mcal/d. When energetic components of feces, urine, and heat in Mcal/d were expressed per unit of DMI the among-animal variance decreased by 20.4, 4.82, and 9.55% units, respectively. However, among-animal variance explained 4.80, 8.78, and 5.02% units more of the total variation for methane energy, lactation energy, and tissue energy in Mcal/d when expressed per unit of DMI. Variance in energetic efficiencies of DE/GE, ME/GE, and ME/DE were explained to a lesser extent by among-animal variance (averaging 17.8 ± 1.95%). The among-animal contribution to total variance in milk energy was 28.8%. Milk energy was a large proportion of the energy efficiency calculation which included milk energy plus corrected tissue energy over net energy intake which likely contributed to the 22.2% of total among-animal variance in energy efficiency. Results indicate that among-animal variance explains a large proportion of the total variation in DMI. This contributes to the variance observed for energy fractions as well as energy components when expressed in Mcal/d. Variation in energetic loss associated with methane was primarily explained by differences among-animals and was increased when expressed per unit of DMI highlighting the role of inherent animal differences in these losses.
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Affiliation(s)
- A L Carroll
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE 68583
| | - M L Spangler
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE 68583
| | - D L Morris
- Perdue Agribusiness, Salisbury, MD 21804
| | - P J Kononoff
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE 68583.
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3
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Wanapat M, Dagaew G, Sommai S, Matra M, Suriyapha C, Prachumchai R, Muslykhah U, Phupaboon S. The application of omics technologies for understanding tropical plants-based bioactive compounds in ruminants: a review. J Anim Sci Biotechnol 2024; 15:58. [PMID: 38689368 PMCID: PMC11062008 DOI: 10.1186/s40104-024-01017-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 02/29/2024] [Indexed: 05/02/2024] Open
Abstract
Finding out how diet impacts health and metabolism while concentrating on the functional qualities and bioactive components of food is the crucial scientific objective of nutritional research. The complex relationship between metabolism and nutrition could be investigated with cutting-edge "omics" and bioinformatics techniques. This review paper provides an overview of the use of omics technologies in nutritional research, with a particular emphasis on the new applications of transcriptomics, proteomics, metabolomics, and genomes in functional and biological activity research on ruminant livestock and products in the tropical regions. A wealth of knowledge has been uncovered regarding the regulation and use of numerous physiological and pathological processes by gene, mRNA, protein, and metabolite expressions under various physiological situations and guidelines. In particular, the components of meat and milk were assessed using omics research utilizing the various methods of transcriptomics, proteomics, metabolomics, and genomes. The goal of this review is to use omics technologies-which have been steadily gaining popularity as technological tools-to develop new nutritional, genetic, and leadership strategies to improve animal products and their quality control. We also present an overview of the new applications of omics technologies in cattle production and employ nutriomics and foodomics technologies to investigate the microbes in the rumen ecology. Thus, the application of state-of-the-art omics technology may aid in our understanding of how species and/or breeds adapt, and the sustainability of tropical animal production, in the long run, is becoming increasingly important as a means of mitigating the consequences of climate change.
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Affiliation(s)
- Metha Wanapat
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Gamonmas Dagaew
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Sukruthai Sommai
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Maharach Matra
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Chaichana Suriyapha
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Rittikeard Prachumchai
- Department of Animal Science, Faculty of Agricultural Technology, University of Technology Thanyaburi, Rajamangala Pathum Thani, 12130, Thailand
| | - Uswatun Muslykhah
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Srisan Phupaboon
- Tropical Feed Resources Research and Development Center (TROFREC), Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand.
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van Staaveren N, Rojas de Oliveira H, Houlahan K, Chud TCS, Oliveira GA, Hailemariam D, Kistemaker G, Miglior F, Plastow G, Schenkel FS, Cerri R, Sirard MA, Stothard P, Pryce J, Butty A, Stratz P, Abdalla EAE, Segelke D, Stamer E, Thaller G, Lassen J, Manzanilla-Pech CIV, Stephansen RB, Charfeddine N, García-Rodríguez A, González-Recio O, López-Paredes J, Baldwin R, Burchard J, Parker Gaddis KL, Koltes JE, Peñagaricano F, Santos JEP, Tempelman RJ, VandeHaar M, Weigel K, White H, Baes CF. The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions. J Dairy Sci 2024; 107:1510-1522. [PMID: 37690718 DOI: 10.3168/jds.2022-22951] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 08/03/2023] [Indexed: 09/12/2023]
Abstract
The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.
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Affiliation(s)
- Nienke van Staaveren
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Hinayah Rojas de Oliveira
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada; Lactanet Canada, Guelph, ON N1K 1E5, Canada
| | - Kerry Houlahan
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Tatiane C S Chud
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Gerson A Oliveira
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Dagnachew Hailemariam
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | | | - Filippo Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada; Lactanet Canada, Guelph, ON N1K 1E5, Canada
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Ronaldo Cerri
- Applied Animal Biology, Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada V6T 1Z4
| | - Marc Andre Sirard
- Department of Animal Sciences, Laval University, Qubec G1V 0A6, QC, Canada
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Jennie Pryce
- School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia; Agriculture Victoria Research, LaTrobe University, Bundoora, Victoria 3083, Australia
| | | | | | - Emhimad A E Abdalla
- Vereinigte Informationssysteme Tierhaltung w.V. (vit), Heinrich-Schröder-Weg 1, 27283, Verden, Germany
| | - Dierck Segelke
- Vereinigte Informationssysteme Tierhaltung w.V. (vit), Heinrich-Schröder-Weg 1, 27283, Verden, Germany; Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, 24098, Kiel, Germany
| | | | - Georg Thaller
- Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, 24098, Kiel, Germany
| | - Jan Lassen
- Viking Genetics, Ebeltoftvej 16, 8960 Assentoft, Denmark
| | | | - Rasmus B Stephansen
- Center for Quantitative Genetics and Genomics, Aarhus University, DK-8830 Tjele, Denmark
| | - Noureddine Charfeddine
- Spanish Holstein Association (CONAFE), Ctra. Andalucía km 23600 Valdemoro, 28340 Madrid, Spain
| | - Aser García-Rodríguez
- Department of Animal Production, NEIKER-Basque Institute for Agricultural Research and Development, 01192 Arkaute, Spain
| | - Oscar González-Recio
- Department of Animal Breeding, Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA-CSIC), 28040 Madrid, Spain
| | - Javier López-Paredes
- Federación Española de Criadores de Limusín, C/Infanta Mercedes, 31, 28020 Madrid, Spain
| | - Ransom Baldwin
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705
| | | | | | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA 50011
| | - Francisco Peñagaricano
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706
| | | | - Robert J Tempelman
- Department of Animal Science, Michigan State University, East Lansing, MI 48824
| | - Michael VandeHaar
- Department of Animal Science, Michigan State University, East Lansing, MI 48824
| | - Kent Weigel
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706
| | - Heather White
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706
| | - Christine F Baes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada; Vetsuisse Faculty, Institute of Genetics, University of Bern, 3012 Bern, Switzerland.
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5
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Lopes LSF, Schenkel FS, Houlahan K, Rochus CM, Oliveira GA, Oliveira HR, Miglior F, Alcantara LM, Tulpan D, Baes CF. Estimates of genetic parameters for rumination time, feed efficiency, and methane production traits in first lactation Holstein cows. J Dairy Sci 2024:S0022-0302(24)00055-9. [PMID: 38310964 DOI: 10.3168/jds.2023-23751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 12/26/2023] [Indexed: 02/06/2024]
Abstract
The large-scale recording of traits such as feed efficiency and methane emissions for use in genetic improvement programs is complex, costly, and time-consuming. Therefore, heritable traits that can be continuously recorded in dairy herds and are correlated to feed efficiency and methane emission traits could provide useful information for genetic evaluation. Rumination time has been suggested to be associated with feed efficiency, methane production (methane emission in g/day), and production traits at the phenotypic level. Therefore, the objective of this study was to investigate the genetic relationships among rumination time, feed efficiency, methane and production traits using 7,358 records from 656 first lactation Holstein cows. The estimated heritabilities were moderate for rumination time (0.45 ± 0.14), methane production (0.36 ± 0.12), milk yield (0.40 ± 0.08), fat yield (0.29 ± 0.06), protein yield (0.32 ± 0.07), and energy corrected milk (0.28 ± 0.07), while low and non-significant for feed efficiency (0.15 ± 0.07), which was defined as the residual of the multiple linear regression of DMI on ECM and MBW. A favorable negative genetic correlation was estimated between rumination time and methane production (-0.53 ± 0.24), while a positive favorable correlation was estimated between rumination time and energy corrected milk (0.49 ± 0.11). The estimated genetic correlation of rumination time with feed efficiency (-0.01 ± 0.17) was not significantly different from zero but showed a trend of a low correlation with dry matter intake (0.21 ± 0.13, P = 0.11). These results indicate that rumination time is genetically associated with methane production and milk production traits, but high standard errors indicate that further analyses should be conducted to verify these findings when more data for rumination time, methane production and feed efficiency become available.
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Affiliation(s)
- L S F Lopes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada;.
| | - F S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - K Houlahan
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - C M Rochus
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - G A Oliveira
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - H R Oliveira
- Lactanet Canada, Guelph, Ontario, Canada, N1K 1E5
| | - F Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada;; Lactanet Canada, Guelph, Ontario, Canada, N1K 1E5
| | - L M Alcantara
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - D Tulpan
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada
| | - C F Baes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Rd E, N1G 2W1, Guelph, Ontario, Canada;; Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland..
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6
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Wellmann R, Gengler N, Bennewitz J, Tetens J. Defining valid breeding goals for animal breeds. Genet Sel Evol 2023; 55:80. [PMID: 37990149 PMCID: PMC10664641 DOI: 10.1186/s12711-023-00855-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 11/06/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND The objective of any valid breeding program is to increase the suitability of a breed for its future purposes. The approach most often followed in animal breeding for optimizing breeding goals assumes that the sole desire of the owners is profit maximization. As this assumption is often violated, a generalized approach is needed that does not rely on this assumption. RESULTS The generalized approach is based on the niche concept. The niche of a breed is a set of environments in which a small population of the breed would have a positive population growth rate. Its growth rate depends on demand from prospective consumers and supply from producers. The approach involves defining the niche that is envisaged for the breed and identifying the trait optima that maximize the breed's adaptation to its envisaged niche within the set of permissible breeding goals. The set of permissible breeding goals is the set of all potential breeding goals that are compatible with animal welfare and could be reached within the planning horizon of the breeding program. In general, the breed's adaptation depends on the satisfaction of the producers with the animals and on the satisfaction of the consumers with the products produced by the animals. When consumers buy live animals, then the breed needs to adapt to both the environments provided by the producers, and the environments provided by the consumers. The profit function is replaced by a more general adaptedness function that measures the breed's adaptation to its envisaged niche. CONCLUSIONS The proposed approach coincides with the traditional approach if the producers have the sole desire to maximize their income, and if consumer preferences are well reflected by the product prices. If these assumptions are not met, then the traditional approach to breeding goal optimization is unlikely to result in a valid breeding goal. Using the example of companion breeds, this paper shows that the proposed approach has the potential to fill the gap.
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Affiliation(s)
- Robin Wellmann
- Department of Animal Genetics and Breeding, University of Hohenheim, 70599, Stuttgart, Germany.
| | - Nicolas Gengler
- TERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech, 5030, Gembloux, Belgium
| | - Jörn Bennewitz
- Department of Animal Genetics and Breeding, University of Hohenheim, 70599, Stuttgart, Germany
| | - Jens Tetens
- Department of Animal Sciences, Georg-August-University Göttingen, 37077, Göttingen, Germany
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Kumar P, Abubakar AA, Verma AK, Umaraw P, Adewale Ahmed M, Mehta N, Nizam Hayat M, Kaka U, Sazili AQ. New insights in improving sustainability in meat production: opportunities and challenges. Crit Rev Food Sci Nutr 2023; 63:11830-11858. [PMID: 35821661 DOI: 10.1080/10408398.2022.2096562] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of conventional meat production by various experts and scientists. Sustainably in the meat sector is a big challenge which requires a multifaced and holistic approach. Novel tools like digitalization of the farming system and livestock market, precision livestock farming, application of remote sensing and artificial intelligence to manage production and environmental impact/GHG emission, can help in attaining sustainability in this sector. Further, improving nutrient use efficiency and recycling in feed and animal production through integration with agroecology and industrial ecology, improving individual animal and herd health by ensuring proper biosecurity measures and selective breeding, and welfare by mitigating animal stress during production are also key elements in achieving sustainability in meat production. In addition, sustainability bears a direct relationship with various social dimensions of meat production efficiency such as non-market attributes, balance between demand and consumption, market and policy failures. The present review critically examines the various aspects that significantly impact the efficiency and sustainability of meat production.
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Affiliation(s)
- Pavan Kumar
- Laboratory of Sustainable Animal Production and Biodiversity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Department of Livestock Products Technology, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India
| | - Abubakar Ahmed Abubakar
- Laboratory of Sustainable Animal Production and Biodiversity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Akhilesh Kumar Verma
- Department of Livestock Products Technology, College of Veterinary and Animal Sciences, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh, India
| | - Pramila Umaraw
- Department of Livestock Products Technology, College of Veterinary and Animal Sciences, Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh, India
| | - Muideen Adewale Ahmed
- Department of Animal Science, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Nitin Mehta
- Department of Livestock Products Technology, College of Veterinary Science, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India
| | - Muhammad Nizam Hayat
- Department of Animal Science, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Ubedullah Kaka
- Department of Companion Animal Medicine and Surgery, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Awis Qurni Sazili
- Laboratory of Sustainable Animal Production and Biodiversity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Department of Animal Science, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
- Halal Products Research Institute, Putra Infoport, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
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8
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Diavão J, Silva AS, Sguizzato ALL, da Silva CS, Tomich TR, Pereira LGR. How does reproduction account for dairy farm sustainability? Anim Reprod 2023; 20:e20230066. [PMID: 37638256 PMCID: PMC10449240 DOI: 10.1590/1984-3143-ar2023-0066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 06/27/2023] [Indexed: 08/29/2023] Open
Abstract
Sustainability - the new hype of the 21st century has brought discomfort for the government and society. Sustainable agriculture is essential to face our most concerning challenges: climate change, food security, and the environmental footprint, all of which add to consumers' opinions and choices. Improvements in reproductive indexes can enhance animal production and efficiency, guaranteeing profit and sustainability. Estrus detection, artificial insemination (AI), embryo transfer (ET), estrus synchronization (ES), and multiple ovulations are some strategies used to improve animal reproduction. This review highlights how reproductive strategies and genetic selection can contribute to sustainable ruminant production. Improved reproductive indices can reduce the number of nonproductive cows in the herd, reducing methane emissions and land use for production while preserving natural resources.
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9
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Gonzalez-Recio O, Scrobota N, López-Paredes J, Saborío-Montero A, Fernández A, López de Maturana E, Villanueva B, Goiri I, Atxaerandio R, García-Rodríguez A. Review: Diving into the cow hologenome to reduce methane emissions and increase sustainability. Animal 2023; 17 Suppl 2:100780. [PMID: 37032282 DOI: 10.1016/j.animal.2023.100780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/18/2023] Open
Abstract
Interest on methane emissions from livestock has increased in later years as it is an anthropogenic greenhouse gas with an important warming potential. The rumen microbiota has a large influence on the production of enteric methane. Animals harbour a second genome consisting of microbes, collectively referred to as the "microbiome". The rumen microbial community plays an important role in feed digestion, feed efficiency, methane emission and health status. This review recaps the current knowledge on the genetic control that the cow exerts on the rumen microbiota composition. Heritability estimates for the rumen microbiota composition range between 0.05 and 0.40 in the literature, depending on the taxonomical group or microbial gene function. Variables depicting microbial diversity or aggregating microbial information are also heritable within the same range. This study includes a genome-wide association analysis on the microbiota composition, considering the relative abundance of some microbial taxa previously associated to enteric methane in dairy cattle (Archaea, Dialister, Entodinium, Eukaryota, Lentisphaerae, Methanobrevibacter, Neocallimastix, Prevotella and Stentor). Host genomic regions associated with the relative abundance of these microbial taxa were identified after Benjamini-Hoschberg correction (Padj < 0.05). An in-silico functional analysis using FUMA and DAVID online tools revealed that these gene sets were enriched in tissues like brain cortex, brain amigdala, pituitary, salivary glands and other parts of the digestive system, and are related to appetite, satiety and digestion. These results allow us to have greater knowledge about the composition and function of the rumen microbiome in cattle. The state-of-the art strategies to include methane traits in the selection indices in dairy cattle populations is reviewed. Several strategies to include methane traits in the selection indices have been studied worldwide, using bioeconomical models or economic functions under theoretical frameworks. However, their incorporation in the breeding programmes is still scarce. Some potential strategies to include methane traits in the selection indices of dairy cattle population are presented. Future selection indices will need to increase the weight of traits related to methane emissions and sustainability. This review will serve as a compendium of the current state of the art in genetic strategies to reduce methane emissions in dairy cattle.
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Affiliation(s)
| | - Natalia Scrobota
- Departamento de Mejora Genética Animal, INIA-CSIC, 28040 Madrid, Spain; Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Javier López-Paredes
- Confederación de Asociaciones de Frisona Española (CONAFE), Ctra. de Andalucía km 23600 Valdemoro, 28340 Madrid, Spain
| | - Alejandro Saborío-Montero
- Escuela de Zootecnia y Centro de Investigación en Nutrición Animal, Universidad de Costa Rica, 11501 San José, Costa Rica; Posgrado Regional en Ciencias Veterinarias Tropicales, Universidad Nacional de Costa Rica, 40104 Heredia, Costa Rica
| | | | - Evangelina López de Maturana
- Universidad San Pablo-CEU, CEU Universities, Madrid, Spain; Institute of Applied Molecular Medicine (IMMA), Department of Basic Medical Sciences. Facultad de Medicina. Universidad San Pablo-CEU, CEU Universities, ARADyAL, Madrid, Spain; Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Idoia Goiri
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - Raquel Atxaerandio
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
| | - Aser García-Rodríguez
- NEIKER - Instituto Vasco de Investigación y Desarrollo Agrario, Basque Research and Technology Alliance (BRTA), Campus Agroalimentario de Arkaute s/n, 01192 Arkaute, Spain
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10
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Kamalanathan S, Houlahan K, Miglior F, Chud TCS, Seymour DJ, Hailemariam D, Plastow G, de Oliveira HR, Baes CF, Schenkel FS. Genetic Analysis of Methane Emission Traits in Holstein Dairy Cattle. Animals (Basel) 2023; 13:ani13081308. [PMID: 37106871 PMCID: PMC10135250 DOI: 10.3390/ani13081308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 04/08/2023] [Indexed: 04/29/2023] Open
Abstract
Genetic selection can be a feasible method to help mitigate enteric methane emissions from dairy cattle, as methane emission-related traits are heritable and genetic gains are persistent and cumulative over time. The objective of this study was to estimate heritability of methane emission phenotypes and the genetic and phenotypic correlations between them in Holstein cattle. We used 1765 individual records of methane emission obtained from 330 Holstein cattle from two Canadian herds. Methane emissions were measured using the GreenFeed system, and three methane traits were analyzed: the amount of daily methane produced (g/d), methane yield (g methane/kg dry matter intake), and methane intensity (g methane/kg milk). Genetic parameters were estimated using univariate and bivariate repeatability animal models. Heritability estimates (±SE) of 0.16 (±0.10), 0.27 (±0.12), and 0.21 (±0.14) were obtained for daily methane production, methane yield, and methane intensity, respectively. A high genetic correlation (rg = 0.94 ± 0.23) between daily methane production and methane intensity indicates that selecting for daily methane production would result in lower methane per unit of milk produced. This study provides preliminary estimates of genetic parameters for methane emission traits, suggesting that there is potential to mitigate methane emission in Holstein cattle through genetic selection.
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Affiliation(s)
- Stephanie Kamalanathan
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Kerry Houlahan
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Filippo Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
- Lactanet Canada, Guelph, ON N1K 1E5, Canada
| | - Tatiane C S Chud
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Dave J Seymour
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
- Centre for Nutrition Modelling, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Dagnachew Hailemariam
- Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Graham Plastow
- Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Hinayah R de Oliveira
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
- Lactanet Canada, Guelph, ON N1K 1E5, Canada
| | - Christine F Baes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstr. 109a, 3012 Bern, Switzerland
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada
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11
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Belay Mekonnen G. Technology for Carbon Neutral Animal Breeding. Vet Med Sci 2023. [DOI: 10.5772/intechopen.110383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023] Open
Abstract
Animal breeding techniques are to genetically select highly productive animals with less GHG emission intensity, thereby reducing the number of animals required to produce the same amount of food. Shotgun metagenomics provides a platform to identify rumen microbial communities and genetic markers associated with CH4 emissions, allowing the selection of cattle with less CH4 emissions. Moreover, breeding is a viable option to make real progress towards carbon neutrality with a very high rate of return on investment and a very modest cost per tonne of CO2 equivalents saved regardless of the accounting method. Other high technologies include the use of cloned livestock animals and the manipulation of traits by controlling target genes with improved productivity.
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12
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Cojkic A, Morrell JM. Animal Welfare Assessment Protocols for Bulls in Artificial Insemination Centers: Requirements, Principles, and Criteria. Animals (Basel) 2023; 13:ani13050942. [PMID: 36899799 PMCID: PMC10000089 DOI: 10.3390/ani13050942] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/01/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Animal welfare is a complex subject; as such, it requires a multidimensional approach with the main aim of providing the animals with the "five freedoms". The violations of any one of these freedoms could have an influence on animal wellbeing on different levels. Over the years, many welfare quality protocols were developed in the EU thanks to the Welfare Quality® project. Unfortunately, there is a lack of such summarized information about bull welfare assessment in artificial insemination stations or about how disturbed welfare can be reflected in their productivity. Animal reproduction is the basis for the production of meat and milk; therefore, factors contributing to reduced fertility in bulls are not only indicators of animal welfare but also have implications for human health and the environment. Optimizing the reproductive efficiency of bulls at an early age can help to reduce greenhouse gas emissions. In this review, welfare quality assessment will be evaluated for these production animals using reproduction efficiency as a key area, focusing on stress as a main effect of poor animal welfare and, thereby, reduced fertility. We will address various welfare aspects and possible changes in resources or management to improve outcomes.
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13
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Invited Review: Novel methods and perspectives for modulating the rumen microbiome through selective breeding as a means to improve complex traits: implications for methane emissions in cattle. Livest Sci 2023. [DOI: 10.1016/j.livsci.2023.105171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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14
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Invited Review: Genetic decision tools for increasing cow efficiency and sustainability in forage-based beef systems. APPLIED ANIMAL SCIENCE 2022. [DOI: 10.15232/aas.2022-02306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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15
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Strandén I, Kantanen J, Lidauer MH, Mehtiö T, Negussie E. Animal board invited review: Genomic-based improvement of cattle in response to climate change. Animal 2022; 16:100673. [PMID: 36402112 DOI: 10.1016/j.animal.2022.100673] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 10/18/2022] [Accepted: 10/20/2022] [Indexed: 12/24/2022] Open
Abstract
Climate change brings challenges to cattle production, such as the need to adapt to new climates and pressure to reduce greenhouse emissions (GHG). In general, the improvement of traits in current breeding goals is favourably correlated with the reduction of GHG. Current breeding goals and tools for increasing cattle production efficiency have reduced GHG. The same amount of production can be achieved by a much smaller number of animals. Genomic selection (GS) may offer a cost-effective way of using an efficient breeding approach, even in low- and middle-income countries. As climate change increases the intensity of heatwaves, adaptation to heat stress leads to lower efficiency of production and, thus, is unfavourable to the goal of reducing GHG. Furthermore, there is evidence that heat stress during cow pregnancy can have many generation-long lowering effects on milk production. Both adaptation and reduction of GHG are among the difficult-to-measure traits for which GS is more efficient and suitable than the traditional non-genomic breeding evaluation approach. Nevertheless, the commonly used within-breed selection may be insufficient to meet the new challenges; thus, cross-breeding based on selecting highly efficient and highly adaptive breeds may be needed. Genomic introgression offers an efficient approach for cross-breeding that is expected to provide high genetic progress with a low rate of inbreeding. However, well-adapted breeds may have a small number of animals, which is a source of concern from a genetic biodiversity point of view. Furthermore, low animal numbers also limit the efficiency of genomic introgression. Sustainable cattle production in countries that have already intensified production is likely to emphasise better health, reproduction, feed efficiency, heat stress and other adaptation traits instead of higher production. This may require the application of innovative technologies for phenotyping and further use of new big data techniques to extract information for breeding.
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Affiliation(s)
- I Strandén
- Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland.
| | - J Kantanen
- Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland
| | - M H Lidauer
- Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland
| | - T Mehtiö
- Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland
| | - E Negussie
- Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland
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16
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Manzanilla-Pech C, Difford G, Løvendahl P, Stephansen R, Lassen J. Genetic (co-)variation of methane emissions, efficiency, and production traits in Danish Holstein cattle along and across lactations. J Dairy Sci 2022; 105:9799-9809. [DOI: 10.3168/jds.2022-22121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 07/24/2022] [Indexed: 11/17/2022]
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17
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Neculai-Valeanu AS, Ariton AM. Udder Health Monitoring for Prevention of Bovine Mastitis and Improvement of Milk Quality. Bioengineering (Basel) 2022; 9:608. [PMID: 36354519 PMCID: PMC9687184 DOI: 10.3390/bioengineering9110608] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 08/05/2023] Open
Abstract
To maximize milk production, efficiency, and profits, modern dairy cows are genetically selected and bred to produce more and more milk and are fed copious quantities of high-energy feed to support ever-increasing milk volumes. As demands for increased milk yield and milking efficiency continue to rise to provide for the growing world population, more significant stress is placed on the dairy cow's productive capacity. In this climate, which is becoming increasingly hotter, millions of people depend on the capacity of cattle to respond to new environments and to cope with temperature shocks as well as additional stress factors such as solar radiation, animal crowding, insect pests, and poor ventilation, which are often associated with an increased risk of mastitis, resulting in lower milk quality and reduced production. This article reviews the impact of heat stress on milk production and quality and emphasizes the importance of udder health monitoring, with a focus on the use of emergent methods for monitoring udder health, such as infrared thermography, biosensors, and lab-on-chip devices, which may promote animal health and welfare, as well as the quality and safety of dairy products, without hindering the technological flow, while providing significant benefits to farmers, manufacturers, and consumers.
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18
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Ryan CV, Pabiou T, Purfield DC, Conroy S, Kirwan SF, Crowley JJ, Murphy CP, Evans RD. Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system. J Anim Sci 2022; 100:6765323. [PMID: 36268991 PMCID: PMC9733524 DOI: 10.1093/jas/skac349] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/20/2022] [Indexed: 12/15/2022] Open
Abstract
Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.
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Affiliation(s)
- Clodagh V Ryan
- Irish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland,Department of Biological Sciences, Munster Technological University, Bishopstown, Co. Cork, Ireland
| | - Thierry Pabiou
- Irish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland
| | - Deirdre C Purfield
- Department of Biological Sciences, Munster Technological University, Bishopstown, Co. Cork, Ireland
| | - Stephen Conroy
- Irish Cattle Breeding Federation, Ballincollig, Co. Cork, Ireland
| | - Stuart F Kirwan
- Animal Bioscience Research Centre, Teagasc Grange, Dunsany, Co. Meath, Ireland
| | - John J Crowley
- AbacusBio Ltd., Dunedin 9016, New Zealand,Department of Agriculture, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G2R3, Canada
| | - Craig P Murphy
- Department of Biological Sciences, Munster Technological University, Bishopstown, Co. Cork, Ireland
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19
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Lima-Verde I, Hurri E, Ntallaris T, Johannisson A, Stålhammar H, Morrell JM. Sperm Quality in Young Bull Semen Can Be Improved by Single Layer Centrifugation. Animals (Basel) 2022; 12:ani12182435. [PMID: 36139296 PMCID: PMC9494988 DOI: 10.3390/ani12182435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 09/09/2022] [Accepted: 09/12/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary Genomic selection enables bulls with desirable genes to be identified early in life. Livestock producers need to use the semen from young bulls as early as possible for efficient milk and meat production with fewer greenhouse gas emissions. However, semen from young bulls is often of lower quality than needed for freezing for commercial artificial insemination. Colloid centrifugation selects spermatozoa with the desirable characteristics needed for fertilization from the rest of the ejaculate. In this study, split ejaculates from young bulls were prepared with or without colloid centrifugation. Using this technique, sperm doses of acceptable quality for artificial insemination could be produced from ejaculates that would otherwise be discarded. Thus, the semen from young bulls would be usable for artificial insemination sooner than is currently the case. Abstract Interest in using semen from young bulls is increasing due to identifying promising animals by genomic selection. However, sperm quality in these ejaculates may not reach currently accepted standards for the cattle breeding industry. The purpose of this study was to determine if centrifugation of semen from young bulls through the Bovicoll colloid could improve sperm quality sufficiently for the frozen semen to be acceptable for artificial insemination. Ejaculates from 19 young bulls were split and either processed by Single-Layer Centrifugation (SLC) or not (CON) before freezing. After thawing, sperm quality was evaluated by determination of membrane integrity, mitochondrial membrane potential, DNA integrity, production of reactive oxygen species, sperm morphology and motility. Approximately half of the CON samples reached acceptable post-thaw quality (membrane integrity ≥ 40%) despite being below the breeding company´s desired sperm concentration threshold pre-freezing. In the remaining samples, sperm quality was improved by SLC such that 45% of them reached acceptable quality post-thaw. Almost 75% of the young bull sperm samples could have produced usable frozen semen doses by adjusting the breeding company´s current processing protocols. Since lowering the generation interval has a direct effect on the genetic gain per year, SLC could aid genetic progress in cattle breeding.
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Affiliation(s)
- Isabel Lima-Verde
- Clinical Sciences, Swedish University of Agricultural Sciences, Almas Allé 8, 750 07 Uppsala, Sweden
| | | | - Theodoros Ntallaris
- Clinical Sciences, Swedish University of Agricultural Sciences, Almas Allé 8, 750 07 Uppsala, Sweden
| | - Anders Johannisson
- Clinical Sciences, Swedish University of Agricultural Sciences, Almas Allé 8, 750 07 Uppsala, Sweden
| | | | - Jane M. Morrell
- Clinical Sciences, Swedish University of Agricultural Sciences, Almas Allé 8, 750 07 Uppsala, Sweden
- Correspondence:
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20
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Host genetics associated with gut microbiota and methane emission in cattle. Mol Biol Rep 2022; 49:8153-8161. [PMID: 35776394 DOI: 10.1007/s11033-022-07718-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 06/15/2022] [Indexed: 10/17/2022]
Abstract
In livestock sector, dairy animals alone produce 18% of the total greenhouse gas emissions globally as methane (CH4). This Enteric methane is the largest component of total carbon footprints produced by livestock production system and its reduction is today's new challenge to make livestock farming sustainable for earth's environment. The production of enteric methane in ruminants is a complex phenomena involving different host factors like host genotype, rumen microbiome, host physiology along with dietary factors. Efforts have been made to reduce methane emissions largely through nutritional interventions and dietary supplements, but permanent reductions can be obtained through genetic means by selecting and breeding of low methane emitting animals. From genome-wide association studies, many important genomic QTL regions and single nucleotide polymorphisms involved in shaping the composition of the ruminal microbiome and thus their carbon footprints have been recognised, implying that methane emission traits are quantitative traits. The major bottleneck in implementation of reduced methane emission traits in the breeding programs is wide variation at phenotypic level, lack of precise methane measurements at individual level. Overall, the heritability for CH4 production traits is moderate, and it can be used in breeding programmes to target changes in microbial composition to reduce CH4 emission in the dairy industry for far-reaching environmental benefits at the cost of a minor reduction in genetic gain in production traits.
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21
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Zhao Y, Zhao G. Decreasing ruminal methane production through enhancing the sulfate reduction pathway. ANIMAL NUTRITION 2022; 9:320-326. [PMID: 35600554 PMCID: PMC9097629 DOI: 10.1016/j.aninu.2022.01.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/28/2021] [Accepted: 01/25/2022] [Indexed: 11/17/2022]
Abstract
Methane (CH4) production from ruminants accounts for 16% of the global greenhouse gas emissions and represents 2% to 12% of feed energy. Mitigating CH4 production from ruminants is of great importance for sustainable development of the ruminant industry. H2 is the primary substrate for CH4 production in the processes of ruminal methanogenesis. Sulfate reducing bacteria are able to compete with methanogens for H2 in the rumen, and consequently inhibit the methanogenesis. Enhancing the ruminal sulfate reducing pathway is an important approach to mitigate CH4 emissions in ruminants. The review summarized the effects of sulfate and elemental S on ruminal methanogenesis, and clarified the related mechanisms through the impacts of sulfate and elemental S on major ruminal sulfate reducing bacteria. Enhancing the activities of the major ruminal sulfate reducing bacteria including Desulfovibrio, Desulfohalobium and Sulfolobus through dietary sulfate addition, elemental S and dried distillers grains with solubles can effectively decrease the ruminal CH4 emissions. Suitable levels of dietary addition with different S sources for reducing the ruminal CH4 production, as well as maintaining the performance and health of ruminants, need to be investigated in the future.
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22
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Manzanilla-Pech CIV, Stephansen RB, Difford GF, Løvendahl P, Lassen J. Selecting for Feed Efficient Cows Will Help to Reduce Methane Gas Emissions. Front Genet 2022; 13:885932. [PMID: 35692829 PMCID: PMC9178123 DOI: 10.3389/fgene.2022.885932] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
In the last decade, several countries have included feed efficiency (as residual feed intake; RFI) in their breeding goal. Recent studies showed that RFI is favorably correlated with methane emissions. Thus, selecting for lower emitting animals indirectly through RFI could be a short-term strategy in order to achieve the intended reduction set by the EU Commission (-55% for 2030). The objectives were to 1) estimate genetic parameters for six methane traits, including genetic correlations between methane traits, production, and feed efficiency traits, 2) evaluate the expected correlated response of methane traits when selecting for feed efficiency with or without including methane, 3) quantify the impact of reducing methane emissions in dairy cattle using the Danish Holstein population as an example. A total of 26,664 CH4 breath records from 647 Danish Holstein cows measured over 7 years in a research farm were analyzed. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available. Methane traits were methane concentration (MeC, ppm), methane production (MeP; g/d), methane yield (MeY; g CH4/kg DMI), methane intensity (MeI; g CH4/kg ECM), residual methane concentration (RMeC), residual methane production (RMeP, g/d), and two definitions of residual feed intake with or without including body weight change (RFI1, RFI2). The estimated heritability of MeC was 0.20 ± 0.05 and for MeP, it was 0.21 ± 0.05, whereas heritability estimates for MeY and MeI were 0.22 ± 0.05 and 0.18 ± 0.04, and for the RMeC and RMeP, they were 0.23 ± 0.06 and 0.16 ± 0.02, respectively. Genetic correlations between methane traits ranged from moderate to highly correlated (0.48 ± 0.16–0.98 ± 0.01). Genetic correlations between methane traits and feed efficiency were all positive, ranging from 0.05 ± 0.20 (MeI-RFI2) to 0.76 ± 0.09 (MeP-RFI2). Selection index calculations showed that selecting for feed efficiency has a positive impact on reducing methane emissions’ expected response, independently of the trait used (MeP, RMeP, or MeI). Nevertheless, adding a negative economic value for methane would accelerate the response and help to reach the reduction goal in fewer generations. Therefore, including methane in the breeding goal seems to be a faster way to achieve the desired methane emission reductions in dairy cattle.
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Affiliation(s)
| | | | - Gareth Frank Difford
- Department of Animal and Aquacultural Sciences, Faculty of Biosciences, Norwegian University of Life Sciences, As, Norway
| | - Peter Løvendahl
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
| | - Jan Lassen
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark
- Viking Genetics, Assentoft, Randers, Denmark
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23
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Altermann E, Reilly K, Young W, Ronimus RS, Muetzel S. Tailored Nanoparticles With the Potential to Reduce Ruminant Methane Emissions. Front Microbiol 2022; 13:816695. [PMID: 35359731 PMCID: PMC8963448 DOI: 10.3389/fmicb.2022.816695] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/21/2022] [Indexed: 11/13/2022] Open
Abstract
Agricultural methane produced by archaea in the forestomach of ruminants is a key contributor to rising levels of greenhouse gases leading to climate change. Functionalized biological polyhydroxybutyrate (PHB) nanoparticles offer a new concept for the reduction of enteric methane emissions by inhibiting rumen methanogens. Nanoparticles were functionalized in vivo with an archaeal virus lytic enzyme, PeiR, active against a range of rumen Methanobrevibacter species. The impact of functionalized nanoparticles against rumen methanogens was demonstrated in pure cultures, in rumen batch and continuous flow rumen models yielding methane reduction of up to 15% over 11 days in the most complex system. We further present evidence of biological nanoparticle fermentation in a rumen environment. Elevated levels of short-chain fatty acids essential to ruminant nutrition were recorded, giving rise to a promising new strategy combining methane mitigation with a possible increase in animal productivity.
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Affiliation(s)
- Eric Altermann
- AgResearch Ltd., Palmerston North, New Zealand
- Riddet Institute, Massey University, Palmerston North, New Zealand
- School of Veterinary Science, Massey University, Palmerston North, New Zealand
- *Correspondence: Eric Altermann,
| | | | - Wayne Young
- AgResearch Ltd., Palmerston North, New Zealand
- Riddet Institute, Massey University, Palmerston North, New Zealand
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24
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Trokhymenko V, Kovalchuk Т, Bidenko V, Zakharin V, Pylypchuk О. The prolonged effect of GLUTAM 1M biologically active preparation on dairy productivity and milk quality of cows. POTRAVINARSTVO 2022. [DOI: 10.5219/1739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
We have studied the effect of biologically active preparation of metabolic-neurotropic action “Glutam 1M” on milk productivity of cows and quality indicators of raw milk. This preparation was used for dry cows in the last trimester of pregnancy. Studies were performed in the private agricultural enterprise “Savertsi” of Popilnyansky district of Zhytomyr region on cows of Holstein breed. The biologically active preparation “Glutam 1M” has been administered to the cows of the experimental groups under the skin behind the shoulder blade in an amount of 20 ml, starting from 270 and 265 days of gestation, once a day for three consecutive days. Cows of control groups were injected with saline in the same dose. Using the biologically active preparation “Glutam 1M”, a milk yield decreased slightly by 2% (91.9 kg). The milk yield increased by 2.9% (141.5 kg) in the control group. 305-days milk yield in the control group of cows was almost the same as in the previous lactation period. During the experiment, the experimental group of cows – has decreased by 2.9% (136.5 kg). A similar situation has been observed during the biologically active preparation “Glutam 1M” on the 270 – 272th days of pregnancy. Milk yield in the experimental group of animals for the previous lactation and after the use of preparation remained almost at the same level in the control group – decreased by 4.7% (207.1 kg). 305-days milk yield in the control group of cows for the previous and post-lactation experiment period was almost the same. In the experimental group of animals, there was an increase in this indicator by 2.7% (128.7 kg). The use of the “Glutam 1M” preparation did not affect milk quality, namely the mass fraction of fat and protein; fluctuations of the above indicators stayed within the error.
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Richardson C, Amer P, Quinton C, Crowley J, Hely F, van den Berg I, Pryce J. Reducing greenhouse gas emissions through genetic selection in the Australian dairy industry. J Dairy Sci 2022; 105:4272-4288. [DOI: 10.3168/jds.2021-21277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 12/22/2021] [Indexed: 11/19/2022]
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Pereira AM, de Lurdes Nunes Enes Dapkevicius M, Borba AES. Alternative pathways for hydrogen sink originated from the ruminal fermentation of carbohydrates: Which microorganisms are involved in lowering methane emission? Anim Microbiome 2022; 4:5. [PMID: 34991722 PMCID: PMC8734291 DOI: 10.1186/s42523-021-00153-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/17/2021] [Indexed: 12/25/2022] Open
Abstract
Agriculture is responsible for a great share of the anthropogenic sources of greenhouse gases that, by warming the earth, threaten its biodiversity. Among greenhouse gas emissions, enteric CH4 from livestock is an important target to slow down climate changes. The CH4 is originated from rumen fermentation and its concentration is affected by several factors, including genetics and nutrition. Ruminants have an extraordinary symbiosis with microorganisms (bacteria, fungi, and protozoa) that ferment otherwise indigestible carbohydrates, from which they obtain energy to grow and continue actively producing, among other products, volatile fatty acids, CO2 and H2. Detrimental ruminal accumulation of H2 is avoided by methanogenesis carried out by Archaea methanogens. Importantly, methanogenesis is not the only H2 sink pathway. In fact, other bacteria can reduce substrates using metabolic hydrogen formed during carbohydrate fermentation, namely propionate production and reductive acetogenesis, thus lowering the CH4 produced. Although the complexity of rumen poses challenges to mitigate CH4 production, the emergence of sequencing techniques that allow the study of microbial communities, gene expression, and metabolome are largely contributing to unravel pathways and key players in the rumen. Indeed, it is now recognized that in vivo emissions of CH4 are correlated to microbial communities, and particularly with the abundance of methanogens, several bacterial groups, and their genes. The goal of CH4 mitigation is to work in favor of the natural processes, without compromising rumen function, animal health, and productivity. Notwithstanding, the major challenge continues to be the feasibility and affordability of the proposed solutions.
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Affiliation(s)
- Ana Margarida Pereira
- Faculdade de Ciências Agrárias e do Ambiente, Instituto de Investigação em Tecnologias Agrárias e do Ambiente (IITAA), Universidade dos Açores, Campus de Angra do Heroísmo, rua Capitão João d’Ávila, 9700-042 Açores Angra do Heroísmo, Portugal
| | - Maria de Lurdes Nunes Enes Dapkevicius
- Faculdade de Ciências Agrárias e do Ambiente, Instituto de Investigação em Tecnologias Agrárias e do Ambiente (IITAA), Universidade dos Açores, Campus de Angra do Heroísmo, rua Capitão João d’Ávila, 9700-042 Açores Angra do Heroísmo, Portugal
| | - Alfredo E. S. Borba
- Faculdade de Ciências Agrárias e do Ambiente, Instituto de Investigação em Tecnologias Agrárias e do Ambiente (IITAA), Universidade dos Açores, Campus de Angra do Heroísmo, rua Capitão João d’Ávila, 9700-042 Açores Angra do Heroísmo, Portugal
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Reisinger A, Clark H, Cowie AL, Emmet-Booth J, Gonzalez Fischer C, Herrero M, Howden M, Leahy S. How necessary and feasible are reductions of methane emissions from livestock to support stringent temperature goals? PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200452. [PMID: 34565223 PMCID: PMC8480228 DOI: 10.1098/rsta.2020.0452] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/02/2021] [Indexed: 05/05/2023]
Abstract
Agriculture is the largest single source of global anthropogenic methane (CH4) emissions, with ruminants the dominant contributor. Livestock CH4 emissions are projected to grow another 30% by 2050 under current policies, yet few countries have set targets or are implementing policies to reduce emissions in absolute terms. The reason for this limited ambition may be linked not only to the underpinning role of livestock for nutrition and livelihoods in many countries but also diverging perspectives on the importance of mitigating these emissions, given the short atmospheric lifetime of CH4. Here, we show that in mitigation pathways that limit warming to 1.5°C, which include cost-effective reductions from all emission sources, the contribution of future livestock CH4 emissions to global warming in 2050 is about one-third of that from future net carbon dioxide emissions. Future livestock CH4 emissions, therefore, significantly constrain the remaining carbon budget and the ability to meet stringent temperature limits. We review options to address livestock CH4 emissions through more efficient production, technological advances and demand-side changes, and their interactions with land-based carbon sequestration. We conclude that bringing livestock into mainstream mitigation policies, while recognizing their unique social, cultural and economic roles, would make an important contribution towards reaching the temperature goal of the Paris Agreement and is vital for a limit of 1.5°C. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.
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Affiliation(s)
| | - Harry Clark
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Annette L. Cowie
- New South Wales Department of Primary Industries/University of New England, Armidale, Australia
| | - Jeremy Emmet-Booth
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Carlos Gonzalez Fischer
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
| | - Mario Herrero
- Department of Global Development, College of Agriculture and Life Sciences, and Cornell Atkinson Centre for Sustainability, Cornell University, Ithaca, USA
| | - Mark Howden
- Australian National University, Canberra, Australia
| | - Sinead Leahy
- New Zealand Agricultural Greenhouse Gas Research Centre (NZAGRC), Palmerston North, New Zealand
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Asselstine V, Lam S, Miglior F, Brito LF, Sweett H, Guan L, Waters SM, Plastow G, Cánovas A. The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies. J Anim Sci 2021; 99:6377879. [PMID: 34586400 PMCID: PMC8480417 DOI: 10.1093/jas/skab193] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 07/21/2021] [Indexed: 12/14/2022] Open
Abstract
Ruminant supply chains contribute 5.7 gigatons of CO2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH4), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH4 production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH4 yield in ruminants indicates that genomic selection for reduced CH4 emissions is possible. Although the microbiology of CH4 production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH4 production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH4 emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH4 production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH4 emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH4 production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.
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Affiliation(s)
- Victoria Asselstine
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - Stephanie Lam
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - Filippo Miglior
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - Luiz F Brito
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada.,Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA
| | - Hannah Sweett
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
| | - Leluo Guan
- Livestock Gentec, Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, Alberta, T6G 2C8, Canada
| | - Sinead M Waters
- Animal and Bioscience Research Department, Teagasc Grange, Dunsany, Co. Meath, C15 PW93, Ireland
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, Alberta, T6G 2C8, Canada
| | - Angela Cánovas
- Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada
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Richardson CM, Amer PR, Hely FS, van den Berg I, Pryce JE. Estimating methane coefficients to predict the environmental impact of traits in the Australian dairy breeding program. J Dairy Sci 2021; 104:10979-10990. [PMID: 34334195 DOI: 10.3168/jds.2021-20348] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 06/08/2021] [Indexed: 11/19/2022]
Abstract
The dairy industry has been scrutinized for the environmental impact associated with rearing and maintaining cattle for dairy production. There are 3 possible opportunities to reduce emissions through genetic selection: (1) a direct methane trait, (2) a reduction in replacements, and (3) an increase in productivity. Our aim was to estimate the independent effects of traits in the Australian National Breeding Objective on the gross methane production and methane intensity (EI) of the Australian dairy herd of average genetic potential. Based on similar published research, the traits determined to have an effect on emissions include production, fertility, survival, health, and feed efficiency. The independent effect of each trait on the gross emissions produced per animal due to genetic improvement and change in EI due to genetic improvement (intensity value, IV) were estimated and compared. Based on an average Australian dairy herd, the gross emissions emitted per cow per year were 4,297.86 kg of carbon dioxide equivalents (CO2-eq). The annual product output, expressed in protein equivalents (protein-eq), and EI per cow were 339.39 kg of protein-eq and 12.67 kg of CO2-eq/kg of protein-eq, respectively. Of the traits included in the National Breeding Objective, genetic progress in survival and feed saved were consistently shown to result in a favorable environmental impact. Conversely, production traits had an unfavorable environmental impact when considering gross emissions, and favorable when considering EI. Fertility had minimal impact as its effects were primarily accounted for through survival. Mastitis resistance only affected IV coefficients and to a very limited extent. These coefficients may be used in selection indexes to apply emphasis on traits based on their environmental impact, as well as applied by governments and stakeholders to track trends in industry emissions. Although initiatives are underway to develop breeding values to reduce methane by combining small methane data sets internationally, alternative options to reduce emissions by utilizing selection indexes should be further explored.
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Affiliation(s)
- C M Richardson
- Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia
| | - P R Amer
- AbacusBio Limited, PO Box 5585, Dunedin, New Zealand
| | - F S Hely
- AbacusBio Limited, PO Box 5585, Dunedin, New Zealand
| | - I van den Berg
- Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia
| | - J E Pryce
- Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia.
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de Haas Y, Veerkamp RF, de Jong G, Aldridge MN. Selective breeding as a mitigation tool for methane emissions from dairy cattle. Animal 2021; 15 Suppl 1:100294. [PMID: 34246599 DOI: 10.1016/j.animal.2021.100294] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/21/2021] [Accepted: 01/25/2021] [Indexed: 12/17/2022] Open
Abstract
The global livestock sector, particularly ruminants, contributes substantially to the total anthropogenic greenhouse gases. Management and dietary solutions to reduce enteric methane (CH4) emissions are extensively researched. Animal breeding that exploits natural variation in CH4 emissions is an additional mitigation solution that is cost-effective, permanent, and cumulative. We quantified the effect of including CH4 production in the Dutch breeding goal using selection index theory. The current Dutch national index contains 15 traits, related to milk yield, longevity, health, fertility, conformation and feed efficiency. From the literature, we obtained a heritability of 0.21 for enteric CH4 production, and genetic correlations of 0.4 with milk lactose, protein, fat and DM intake. Correlations between enteric CH4 production and other traits in the breeding goal were set to zero. When including CH4 production in the current breeding goal with a zero economic value, CH4 production increases each year by 1.5 g/d as a correlated response. When extrapolating this, the average daily CH4 production of 392 g/d in 2018 will increase to 442 g/d in 2050 (+13%). However, expressing the CH4 production as CH4 intensity in the same period shows a reduction of 13%. By putting economic weight on CH4 production in the breeding goal, selective breeding can reduce the CH4 intensity even by 24% in 2050. This shows that breeding is a valuable contribution to the whole set of mitigation strategies that could be applied in order to achieve the goals for 2050 set by the EU. If the decision is made to implement animal breeding strategies to reduce enteric CH4 production, and to achieve the expected breeding impact, there needs to be a sufficient reliability of prediction. The only way to achieve that is to have enough animals phenotyped and genotyped. The power calculations offer insights into the difficulties that will be faced in trying to record enough data. Recording CH4 data on 100 farms (with on average 150 cows each) for at least 2 years is required to achieve the desired reliability of 0.40 for the genomic prediction.
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Affiliation(s)
- Y de Haas
- Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, the Netherlands.
| | - R F Veerkamp
- Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, the Netherlands
| | - G de Jong
- CRV, 6800 AL Arnhem, the Netherlands
| | - M N Aldridge
- Animal Breeding and Genomics, Wageningen University & Research, 6700 AH Wageningen, the Netherlands
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Manzanilla-Pech CIV, L Vendahl P, Mansan Gordo D, Difford GF, Pryce JE, Schenkel F, Wegmann S, Miglior F, Chud TC, Moate PJ, Williams SRO, Richardson CM, Stothard P, Lassen J. Breeding for reduced methane emission and feed-efficient Holstein cows: An international response. J Dairy Sci 2021; 104:8983-9001. [PMID: 34001361 DOI: 10.3168/jds.2020-19889] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 04/14/2021] [Indexed: 01/23/2023]
Abstract
Selecting for lower methane (CH4) emitting animals is one of the best approaches to reduce CH4 given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH4, combining data from different countries could help to expedite accurate genetic parameters for CH4 traits and build a future genomic reference population. Additionally, if we want to include CH4 in the breeding goal, it is important to know the genetic correlations of CH4 traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH4. The third aim was to evaluate the expected response of economically important traits by including CH4 traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production.
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Affiliation(s)
- C I V Manzanilla-Pech
- Center for Quantitative Genetics and Genomics, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark.
| | - P L Vendahl
- Center for Quantitative Genetics and Genomics, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark
| | - D Mansan Gordo
- Center for Quantitative Genetics and Genomics, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark
| | - G F Difford
- Center for Quantitative Genetics and Genomics, Aarhus University, PO Box 50, DK-8830 Tjele, Denmark
| | - J E Pryce
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia
| | - F Schenkel
- Centre for Genomic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | | | - F Miglior
- Centre for Genomic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - T C Chud
- Centre for Genomic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - P J Moate
- Centre for Agricultural Innovation, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Victoria 3083, Australia; Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia
| | - S R O Williams
- Agriculture Victoria Research, Ellinbank, Victoria 3820, Australia
| | - C M Richardson
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Victoria 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, Victoria 3083, Australia
| | - P Stothard
- Faculty of Agricultural, Life and Environmental Science, Agriculture, Food and Nutrition Sciences Department, University of Alberta, Edmonton, AB, T6G 2C8, Canada
| | - J Lassen
- Viking Genetics, Ebeltoftvej 16, Assenstoft, 8960 Randers, Denmark
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Modelling the Distribution of the Red Macroalgae Asparagopsis to Support Sustainable Aquaculture Development. AGRIENGINEERING 2021. [DOI: 10.3390/agriengineering3020017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Fermentative digestion by ruminant livestock is one of the main ways enteric methane enters the atmosphere, although recent studies have identified that including red macroalgae as a feed ingredient can drastically reduce methane produced by cattle. Here, we utilize ecological modelling to identify suitable sites for establishing aquaculture development to support sustainable agriculture and Sustainable Development Goals 1 and 2. We used species distributions models (SDMs) parameterized using an ensemble of multiple statistical and machine learning methods, accounting for novel methodological and ecological artefacts that arise from using such approaches on non-native and cultivated species. We predicted the current distribution of two Asparagopsis species to high accuracy around the coast of Ireland. The environmental drivers of each species differed depending on where the response data was sourced from (i.e., native vs. non-native), suggesting that the length of time A. armata has been present in Ireland may mean it has undergone a niche shift. Subsequently, researchers looking to adopt SDMs to support aquaculture development need to acknowledge emerging conceptual issues, and here we provide the code needed to implement such research, which should support efforts to effectively choose suitable sites for aquaculture development that account for the unique methodological steps identified in this research.
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Saborío-Montero A, López-García A, Gutiérrez-Rivas M, Atxaerandio R, Goiri I, García-Rodriguez A, Jiménez-Montero JA, González C, Tamames J, Puente-Sánchez F, Varona L, Serrano M, Ovilo C, González-Recio O. A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding. J Dairy Sci 2021; 104:8135-8151. [PMID: 33896632 DOI: 10.3168/jds.2020-20005] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/15/2021] [Indexed: 01/02/2023]
Abstract
The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.
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Affiliation(s)
- Alejandro Saborío-Montero
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain; Escuela de Zootecnia y Centro de Investigación en Nutrición Animal, Universidad de Costa Rica, 11501 San José, Costa Rica
| | - Adrían López-García
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain
| | - Mónica Gutiérrez-Rivas
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain
| | - Raquel Atxaerandio
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - Idoia Goiri
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - Aser García-Rodriguez
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - José A Jiménez-Montero
- Spanish Holstein Association (CONAFE), Ctra. de Andalucía km 23600 Valdemoro, 28340 Madrid, Spain
| | - Carmen González
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain
| | - Javier Tamames
- Department of Systems Biology, Spanish Center for Biotechnology, CSIC, 28049 Madrid, Spain
| | | | - Luis Varona
- Facultad de Veterinaria, Universidad de Zaragoza, 50013 Zaragoza, Spain
| | - Magdalena Serrano
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain
| | - Cristina Ovilo
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain
| | - Oscar González-Recio
- Departamento de mejora genética animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain; Departamento de Producción Agraria. Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain.
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Black JL, Davison TM, Box I. Methane Emissions from Ruminants in Australia: Mitigation Potential and Applicability of Mitigation Strategies. Animals (Basel) 2021; 11:ani11040951. [PMID: 33805324 PMCID: PMC8066058 DOI: 10.3390/ani11040951] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 02/06/2023] Open
Abstract
Anthropomorphic greenhouse gases are raising the temperature of the earth and threatening ecosystems. Since 1950 atmospheric carbon dioxide has increased 28%, while methane has increased 70%. Methane, over the first 20 years after release, has 80-times more warming potential as a greenhouse gas than carbon dioxide. Enteric methane from microbial fermentation of plant material by ruminants contributes 30% of methane released into the atmosphere, which is more than any other single source. Numerous strategies were reviewed to quantify their methane mitigation potential, their impact on animal productivity and their likelihood of adoption. The supplements, 3-nitrooxypropanol and the seaweed, Asparagopsis, reduced methane emissions by 40+% and 90%, respectively, with increases in animal productivity and small effects on animal health or product quality. Manipulation of the rumen microbial population can potentially provide intergenerational reduction in methane emissions, if treated animals remain isolated. Genetic selection, vaccination, grape marc, nitrate or biochar reduced methane emissions by 10% or less. Best management practices and cattle browsing legumes, Desmanthus or Leucaena species, result in small levels of methane mitigation and improved animal productivity. Feeding large amounts daily of ground wheat reduced methane emissions by around 35% in dairy cows but was not sustained over time.
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Affiliation(s)
- John L. Black
- John L Black Consulting, Warrimoo, NSW 2774, Australia
- Correspondence:
| | - Thomas M. Davison
- Livestock Productivity Partnership, University of New England, Armidale, NSW 2351, Australia;
| | - Ilona Box
- Ilona Box Consulting, Warrimoo, NSW 2774, Australia;
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Bittante G, Cipolat-Gotet C, Cecchinato A. Genetic Parameters of Different FTIR-Enabled Phenotyping Tools Derived from Milk Fatty Acid Profile for Reducing Enteric Methane Emissions in Dairy Cattle. Animals (Basel) 2020; 10:ani10091654. [PMID: 32942618 PMCID: PMC7552146 DOI: 10.3390/ani10091654] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 09/06/2020] [Accepted: 09/11/2020] [Indexed: 01/20/2023] Open
Abstract
This study aimed to infer the genetic parameters of five enteric methane emissions (EME) predicted from milk infrared spectra (13 models). The reference values were estimated from milk fatty acid profiles (chromatography), individual model-cheese, and daily milk yield of 1158 Brown Swiss cows (85 farms). Genetic parameters were estimated, under a Bayesian framework, for EME reference traits and their infrared predictions. Heritability of predicted EME traits were similar to EME reference values for methane yield (CH4/DM: 0.232-0.317) and methane intensity per kg of corrected milk (CH4/CM: 0.177-0.279), smaller per kg cheese solids (CH4/SO: 0.093-0.165), but greater per kg fresh cheese (CH4/CU: 0.203-0.267) and for methane production (dCH4: 0.195-0.232). We found good additive genetic correlations between infrared-predicted methane intensities and the reference values (0.73 to 0.93), less favorable values for CH4/DM (0.45-0.60), and very variable for dCH4 according to the prediction method (0.22 to 0.98). Easy-to-measure milk infrared-predicted EME traits, particularly CH4/CM, CH4/CU and dCH4, could be considered in breeding programs aimed at the improvement of milk ecological footprint.
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Affiliation(s)
- Giovanni Bittante
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 1, 35020 Legnaro, Italy;
| | - Claudio Cipolat-Gotet
- Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy;
| | - Alessio Cecchinato
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 1, 35020 Legnaro, Italy;
- Correspondence:
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López-Paredes J, Goiri I, Atxaerandio R, García-Rodríguez A, Ugarte E, Jiménez-Montero JA, Alenda R, González-Recio O. Mitigation of greenhouse gases in dairy cattle via genetic selection: 1. Genetic parameters of direct methane using noninvasive methods and proxies of methane. J Dairy Sci 2020; 103:7199-7209. [PMID: 32475675 DOI: 10.3168/jds.2019-17597] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 03/20/2020] [Indexed: 12/24/2022]
Abstract
Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH4 production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.
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Affiliation(s)
- J López-Paredes
- Federación Española de Criadores de Limusín, C/Infanta Mercedes, 31, 28020 Madrid, Spain
| | - I Goiri
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - R Atxaerandio
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - A García-Rodríguez
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - E Ugarte
- Department of Animal Production, NEIKER-Tecnalia, Granja Modelo de Arkaute, Apdo. 46, 01080 Vitoria-Gasteiz, Spain
| | - J A Jiménez-Montero
- Spanish Holstein Association (CONAFE), Ctra. de Andalucía km 23600 Valdemoro, 28340 Madrid, Spain
| | - R Alenda
- Departamento de Producción Agraria, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain
| | - O González-Recio
- Departamento de Producción Agraria, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain; Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Crta. de la Coruña km 7.5, 28040 Madrid, Spain.
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