Exploring Indicators of Genetic Selection Using the Sniffer Method to Reduce Methane Emissions from Holstein Cows

Overview

Journal Anim Biosci

Specialty Veterinary Medicine

Date 2023 Aug 29

PMID 37641824

Authors

Yoshinobu Uemoto

Tomohisa Tomaru

Masahiro Masuda

Kota Uchisawa

Kenji Hashiba

Yuki Nishikawa

Kohei Suzuki

Takatoshi Kojima

Tomoyuki Suzuki

Fuminori Terada

Affiliations

Soon will be listed here.

Abstract

Objective: This study aimed to evaluate whether the methane (CH4) to carbon dioxide (CO2) ratio (CH4/CO2) and methane-related traits obtained by the sniffer method can be used as indicators for genetic selection of Holstein cows with lower CH4 emissions.

Methods: The sniffer method was used to simultaneously measure the concentrations of CH4 and CO2 during milking in each milking box of the automatic milking system to obtain CH4/CO2. Methane-related traits, which included CH4 emissions, CH4 per energy-corrected milk, methane conversion factor (MCF), and residual CH4, were calculated. First, we investigated the impact of the model with and without body weight (BW) on the lactation stage and parity for predicting methane-related traits using a first on-farm dataset (Farm 1; 400 records for 74 Holstein cows). Second, we estimated the genetic parameters for CH4/CO2 and methane-related traits using a second on-farm dataset (Farm 2; 520 records for 182 Holstein cows). Third, we compared the repeatability and environmental effects on these traits in both farm datasets.

Results: The data from Farm 1 revealed that MCF can be reliably evaluated during the lactation stage and parity, even when BW is excluded from the model. Farm 2 data revealed low heritability and moderate repeatability for CH4/CO2 (0.12 and 0.46, respectively) and MCF (0.13 and 0.38, respectively). In addition, the estimated genetic correlation of milk yield with CH4/CO2 was low (0.07) and that with MCF was moderate (-0.53). The on-farm data indicated that CH4/CO2 and MCF could be evaluated consistently during the lactation stage and parity with moderate repeatability on both farms.

Conclusion: This study demonstrated the on-farm applicability of the sniffer method for selecting cows with low CH4 emissions.

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References

Pszczola M, Rzewuska K, Mucha S, Strabel T . Heritability of methane emissions from dairy cows over a lactation measured on commercial farms. J Anim Sci. 2018; 95(11):4813-4819. PMC: 6292309. DOI: 10.2527/jas2017.1842. View

Tyrrell H, Reid J . Prediction of the energy value of cow's milk. J Dairy Sci. 1965; 48(9):1215-23. DOI: 10.3168/jds.S0022-0302(65)88430-2. View

Olijhoek D, Difford G, Lund P, Lovendahl P . Phenotypic modeling of residual feed intake using physical activity and methane production as energy sinks. J Dairy Sci. 2020; 103(8):6967-6981. DOI: 10.3168/jds.2019-17489. View

Pickering N, Chagunda M, Banos G, Mrode R, McEwan J, Wall E . Genetic parameters for predicted methane production and laser methane detector measurements. J Anim Sci. 2014; 93(1):11-20. DOI: 10.2527/jas.2014-8302. View

de Haas Y, Pszczola M, Soyeurt H, Wall E, Lassen J . Invited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying. J Dairy Sci. 2016; 100(2):855-870. DOI: 10.3168/jds.2016-11246. View

Bell M, Potterton S, Craigon J, Saunders N, Wilcox R, Hunter M . Variation in enteric methane emissions among cows on commercial dairy farms. Animal. 2014; 8(9):1540-6. DOI: 10.1017/S1751731114001530. View

Lassen J, Difford G . Review: Genetic and genomic selection as a methane mitigation strategy in dairy cattle. Animal. 2020; 14(S3):s473-s483. DOI: 10.1017/S1751731120001561. View

Tedeschi L, Abdalla A, Alvarez C, Anuga S, Arango J, Beauchemin K . Quantification of methane emitted by ruminants: a review of methods. J Anim Sci. 2022; 100(7). PMC: 9261501. DOI: 10.1093/jas/skac197. View

Shibata M, Terada F . Factors affecting methane production and mitigation in ruminants. Anim Sci J. 2010; 81(1):2-10. DOI: 10.1111/j.1740-0929.2009.00687.x. View

10.

Suzuki T, Kamiya Y, Oikawa K, Nonaka I, Shinkai T, Terada F . Prediction of enteric methane emissions from lactating cows using methane to carbon dioxide ratio in the breath. Anim Sci J. 2021; 92(1):e13637. PMC: 9285552. DOI: 10.1111/asj.13637. View

11.

Stranden I, Kantanen J, Lidauer M, Mehtio T, Negussie E . Animal board invited review: Genomic-based improvement of cattle in response to climate change. Animal. 2022; 16(12):100673. DOI: 10.1016/j.animal.2022.100673. View

12.

Yin T, Pinent T, Brugemann K, Simianer H, Konig S . Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle. J Dairy Sci. 2015; 98(8):5748-62. DOI: 10.3168/jds.2014-8618. View

13.

Johnson K, Johnson D . Methane emissions from cattle. J Anim Sci. 1995; 73(8):2483-92. DOI: 10.2527/1995.7382483x. View

14.

de Haas Y, Windig J, Calus M, Dijkstra J, de Haan M, Bannink A . Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. J Dairy Sci. 2011; 94(12):6122-34. DOI: 10.3168/jds.2011-4439. View

15.

Manzanilla-Pech C, L Vendahl P, Mansan Gordo D, Difford G, Pryce J, Schenkel F . Breeding for reduced methane emission and feed-efficient Holstein cows: An international response. J Dairy Sci. 2021; 104(8):8983-9001. DOI: 10.3168/jds.2020-19889. View

16.

van Engelen S, Bovenhuis H, van der Tol P, Visker M . Genetic background of methane emission by Dutch Holstein Friesian cows measured with infrared sensors in automatic milking systems. J Dairy Sci. 2018; 101(3):2226-2234. DOI: 10.3168/jds.2017-13441. View

17.

Lassen J, Lovendahl P, Madsen J . Accuracy of noninvasive breath methane measurements using Fourier transform infrared methods on individual cows. J Dairy Sci. 2012; 95(2):890-8. DOI: 10.3168/jds.2011-4544. View

18.

Kandel P, Vanrobays M, Vanlierde A, Dehareng F, Froidmont E, Gengler N . Genetic parameters of mid-infrared methane predictions and their relationships with milk production traits in Holstein cattle. J Dairy Sci. 2017; 100(7):5578-5591. DOI: 10.3168/jds.2016-11954. View

19.

van Breukelen A, Aldridge M, Veerkamp R, de Haas Y . Genetic parameters for repeatedly recorded enteric methane concentrations of dairy cows. J Dairy Sci. 2022; 105(5):4256-4271. DOI: 10.3168/jds.2021-21420. View

20.

van Engelen S, Bovenhuis H, Dijkstra J, van Arendonk J, Visker M . Short communication: Genetic study of methane production predicted from milk fat composition in dairy cows. J Dairy Sci. 2015; 98(11):8223-6. DOI: 10.3168/jds.2014-8989. View