{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T03:35:27Z","timestamp":1773804927942,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T00:00:00Z","timestamp":1697587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003624","name":"Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry (IPET) through the Smart Farm Innovation Technology Development Program funded by the Ministry of Agriculture, Food, and Rural Affairs (MAFRA)","doi-asserted-by":"publisher","award":["421022-04"],"award-info":[{"award-number":["421022-04"]}],"id":[{"id":"10.13039\/501100003624","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>This study investigated the impact of feeding systems on the determination of enteric methane (CH4) emissions factor in cattle. Real-time feed intake data, a crucial CH4 conversion rate (Ym value) parameter, were obtained using a roughage intake control (RIC) unit within a smart farm system. Greenhouse gas (GHG) emissions, including CH4 and carbon dioxide (CO2), from Holstein steers were monitored using a GreenFeed (GF) 344 unit. The results revealed satisfactory body weight (383 \u00b1 57.19 kg) and daily weight gain (2.00 \u00b1 0.83 kg), which are crucial factors. CO2 production exhibited positive correlations with the initial body weight (r = 0.72, p = 0.027), feed intake (r = 0.71, p = 0.029), and feed conversion ratio (r = 0.69, p = 0.036). Five different emission factors (EFs), EFA (New Equation 10.21A) and Equation 10.21 (EFB, EFC, EFD, and EFE), were used for GHG calculations following the Intergovernmental Panel on Climate Change (IPCC) Tier 2 approach. The estimated CH4 EFs using these equations were 69.91, 69.91, 91.79, 67.26, and 42.60 kg CH4\/head\/year. These findings highlight the potential for further exploration and adoption of smart farming technology, which has the potential to enhance prediction accuracy and reduce the uncertainty in Ym values tailored to specific countries or regions.<\/jats:p>","DOI":"10.3390\/su152014988","type":"journal-article","created":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T09:55:06Z","timestamp":1697622906000},"page":"14988","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Greenhouse Gas (GHG) Emission Estimation for Cattle: Assessing the Potential Role of Real-Time Feed Intake Monitoring"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9694-6145","authenticated-orcid":false,"given":"Janine I.","family":"Berdos","sequence":"first","affiliation":[{"name":"Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea"},{"name":"Department of Animal Science, College of Agriculture and Forestry, Tarlac Agricultural University, Camiling 2306, Tarlac, Philippines"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6638-6730","authenticated-orcid":false,"given":"Chris Major","family":"Ncho","sequence":"additional","affiliation":[{"name":"Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3896-0950","authenticated-orcid":false,"given":"A-Rang","family":"Son","sequence":"additional","affiliation":[{"name":"Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1540-7041","authenticated-orcid":false,"given":"Sang-Suk","family":"Lee","sequence":"additional","affiliation":[{"name":"Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5947-4157","authenticated-orcid":false,"given":"Seon-Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"Ruminant Nutrition and Anaerobe Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,18]]},"reference":[{"key":"ref_1","unstructured":"Ritchie, H., Roser, M., and Rosado, P. (2023, June 21). CO\u2082 and Greenhouse Gas Emissions. Available online: https:\/\/ourworldindata.org\/co2-and-greenhouse-gas-emissions."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1079\/BJN19760053","article-title":"Rates of Production of Methane in the Rumen and Large Intestine of Sheep","volume":"36","author":"Murray","year":"1976","journal-title":"Br. J. Nutr."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Mpofu, I. (2019). Ecosystem Services from Different Livestock Management Systems, Elsevier Inc.","DOI":"10.1016\/B978-0-12-816436-5.00007-X"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"945785","DOI":"10.1155\/2010\/945785","article-title":"Methanogens: Methane Producers of the Rumen and Mitigation Strategies","volume":"2010","author":"Hook","year":"2010","journal-title":"Archaea"},{"key":"ref_5","first-page":"279","article-title":"A Review of Precision Technologies in Pasture-Based Dairying Systems","volume":"59","author":"Shalloo","year":"2021","journal-title":"Ir. J. Agric. Food Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"106610","DOI":"10.1016\/j.compag.2021.106610","article-title":"Predicting Livestock Behaviour Using Accelerometers: A Systematic Review of Processing Techniques for Ruminant Behaviour Prediction from Raw Accelerometer Data","volume":"192","author":"Riaboff","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.anifeedsci.2016.05.018","article-title":"Review of Current in Vivo Measurement Techniques for Quantifying Enteric Methane Emission from Ruminants","volume":"219","author":"Hammond","year":"2016","journal-title":"Anim. Feed Sci. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1021\/es00051a025","article-title":"Measurement of Methane Emissions from Ruminant Livestock Using a SF6 Tracer Technique","volume":"28","author":"Johnson","year":"1994","journal-title":"Environ. Sci. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6077","DOI":"10.3168\/jds.2012-5505","article-title":"Technical Note: Test of a Low-Cost and Animal-Friendly System for Measuring Methane Emissions from Dairy Cows","volume":"95","author":"Hellwing","year":"2012","journal-title":"J. Dairy Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.livsci.2019.01.017","article-title":"Enteric Methane Emission Can Be Reliably Measured by the GreenFeed Monitoring Unit","volume":"222","author":"Huhtanen","year":"2019","journal-title":"Livest. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0168-1591(02)00009-6","article-title":"Relationships between Bunk Attendance, Intake and Performance of Steers and Heifers on Varying Feeding Regimes","volume":"76","author":"Atwood","year":"2002","journal-title":"Appl. Anim. Behav. Sci."},{"key":"ref_12","first-page":"213","article-title":"Patterns of Methane Production and Feed Intake in Ruminants. CSIRO Livestock Industries, Floreat Park Laboratories, Wembley, WA 6014","volume":"25","author":"Baker","year":"2003","journal-title":"Anim. Prod. Aust."},{"key":"ref_13","first-page":"1","article-title":"Chapter 10: Emissions from Livestock and Manure Management","volume":"Volume 10","author":"Dong","year":"2006","journal-title":"2006 IPCC Guidelines for National Greenhouse Gas Inventories"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Islam, M., Kim, S.H., Son, A.R., Lee, S.S., and Lee, S.S. (2022). Breed and Season-Specific Methane Conversion Factors Influence Methane Emission Factor for Enteric Methane of Dairy Steers. Sustainability, 14.","DOI":"10.3390\/su14127030"},{"key":"ref_15","unstructured":"Ministry of Agriculture, Fisheries and Food (MAFF) (2023, May 25). Energy Allowances and Feeding Systems for Ruminants, Available online: https:\/\/wellcomecollection.org\/works\/ey8cqebf."},{"key":"ref_16","unstructured":"NRC (2000). Nutrient Requirements of Beef Cattle: Update 2000, National Academy Press. [7th ed.]."},{"key":"ref_17","unstructured":"R Core Team (2023). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ncho, C., Goel, A., Jeong, C., Gupta, V., and Choi, Y. (2021). Effects of In Ovo Feeding of \u03b3-Aminobutyric Acid on Growth Performances, Plasma Metabolites, and Antioxidant Status in Broilers Exposed to Cyclic Heat Stress. Sustainability, 13.","DOI":"10.3390\/su131911032"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/S0168-1699(98)00013-1","article-title":"A Real-Time Control System for Individual Dairy Cow Food Intake","volume":"20","author":"Halachmi","year":"1998","journal-title":"Comput. Electron. Agric."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"634338","DOI":"10.3389\/fvets.2021.634338","article-title":"A Systematic Review on Commercially Available and Validated Sensor Technologies for Welfare Assessment of Dairy Cattle","volume":"8","author":"Stygar","year":"2021","journal-title":"Front. Vet. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"skab038","DOI":"10.1093\/jas\/skab038","article-title":"Advancements in Sensor Technology and Decision Support Intelligent Tools to Assist Smart Livestock Farming","volume":"99","author":"Tedeschi","year":"2021","journal-title":"J. Anim. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.5713\/ajas.18.0698","article-title":"The Effects of Age and Gender (Bull vs Steer) on the Feeding Behavior of Young Beef Cattle Fed Grass Silage","volume":"32","author":"Puzio","year":"2019","journal-title":"Asian Australas. J. Anim. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7564","DOI":"10.3168\/jds.2022-22066","article-title":"Estimates of Genetic Parameters for Feeding Behavior Traits and Their Associations with Feed Efficiency in Holstein Cows","volume":"105","author":"Cavani","year":"2022","journal-title":"J. Dairy Sci."},{"key":"ref_24","unstructured":"C-Lock Inc (2021). GreenFeed Instruction Manual, C-Lock Inc."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Min, B., Lee, S., Jung, H., and Miller, D.N. (2022). And Beef Cattle Production: Strategies, Opportunities, and Impact of Reducing Emissions. Animals, 12.","DOI":"10.3390\/ani12080948"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3166","DOI":"10.3168\/jds.2011-4605","article-title":"On-Farm Methane Measurements during Milking Correlate with Total Methane Production by Individual Dairy Cows","volume":"95","author":"Garnsworthy","year":"2012","journal-title":"J. Dairy Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5461","DOI":"10.3168\/jds.2016-10897","article-title":"Short Communication: Comparison of the GreenFeed System with the Sulfur Hexafluoride Tracer Technique for Measuring Enteric Methane Emissions from Dairy Cows","volume":"99","author":"Hristov","year":"2016","journal-title":"J. Dairy Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Islam, M., Kim, S.H., Ramos, S.C., Mamuad, L.L., Son, A.R., Yu, Z., Lee, S.S., Cho, Y.-I.L., and Lee, S.S. (2021). Holstein and Jersey Steers Differ in Rumen Microbiota and Enteric Methane Emissions Even Fed the Same Total Mixed Ration. Front. Microbiol., 12.","DOI":"10.3389\/fmicb.2021.601061"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Sauvant, D., Milgen, J., Faverdin, P., and Friggens, N. (2010). Modelling Nutrient Digestion and Utilisation in Farm Animals, Wageningen Academic Publishers.","DOI":"10.3920\/978-90-8686-712-7"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1071\/AN15491","article-title":"Measuring Methane from Grazing Dairy Cows Using GreenFeed","volume":"56","author":"Waghorn","year":"2016","journal-title":"Anim. Prod. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2446","DOI":"10.1038\/s41396-018-0203-0","article-title":"Microbiome Niche Modification Drives Diurnal Rumen Community Assembly, Overpowering Individual Variability and Diet Effects","volume":"12","author":"Shaani","year":"2018","journal-title":"ISME J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6655","DOI":"10.3168\/jds.2017-13536","article-title":"Symposium Review: Uncertainties in Enteric Methane Inventories, Measurement Techniques, and Prediction Models","volume":"101","author":"Hristov","year":"2018","journal-title":"J. Dairy Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"9079","DOI":"10.5194\/acp-12-9079-2012","article-title":"Global Anthropogenic Methane Emissions 2005\u20132030: Technical Mitigation Potentials and Costs","volume":"12","year":"2012","journal-title":"Atmos. Chem. Phys."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Bekele, W., Guinguina, A., Zegeye, A., Simachew, A., and Ramin, M. (2022). Contemporary Methods of Measuring and Estimating Methane Emission from Ruminants. Methane, 1.","DOI":"10.3390\/methane1020008"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zaman, M., Heng, L., and M\u00fcller, C. (2021). Measuring Emission of Agricultural Greenhouse Gases and Developing Mitigation Options Using Nuclear and Related Techniques, Springer International Publishing.","DOI":"10.1007\/978-3-030-55396-8"},{"key":"ref_36","unstructured":"Difford, G.F. (2020). Guidelines for Estimating Methane Emissions from Individual Ruminants Using: GreenFeed, \u2018Snifferd\u2019, Handhels Laser Detector and Portable Accumulation Chambers, New Zealand Agricultural Greenhouse Gas Research Centre."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.agrformet.2006.03.028","article-title":"Livestock Methane Emission: From the Individual Grazing Animal through National Inventories to the Global Methane Cycle","volume":"142","author":"Lassey","year":"2007","journal-title":"Agric. For. Meteorol."},{"key":"ref_38","unstructured":"Smink, W., Van Der Hoek, K.W., Bannink, A., and Dijkstra, J. (2023, June 21). Calculation of Methane Production from Enteric Fermentation in Dairy Cows. SenterNovem. Available online: https:\/\/edepot.wur.nl\/38583."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.tibtech.2015.10.004","article-title":"Measuring Methane Production from Ruminants","volume":"34","author":"Hill","year":"2016","journal-title":"Trends Biotechnol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"160","DOI":"10.3390\/ani2020160","article-title":"Methods for Measuring and Estimating Methane Emission from Ruminants","volume":"2","author":"Storm","year":"2012","journal-title":"Animals"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1093\/jas\/sky033","article-title":"Comparison of 3 Methods for Estimating Enteric Methane and Carbon Dioxide Emission in Nonlactating Cows","volume":"96","author":"Doreau","year":"2018","journal-title":"J. Anim. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"100469","DOI":"10.1016\/j.animal.2022.100469","article-title":"Predicting Enteric Methane Emission in Lactating Holsteins Based on Reference Methane Data Collected by the GreenFeed System","volume":"16","author":"Liu","year":"2022","journal-title":"Animal"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2476","DOI":"10.3168\/jds.2012-6095","article-title":"Development of Equations for Predicting Methane Emissions from Ruminants","volume":"96","author":"Ramin","year":"2013","journal-title":"J. Dairy Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"356","DOI":"10.2527\/jas.2012-5259","article-title":"Enteric Methane Emissions and Efficiency of Use of Energy in Holstein Heifers and Steers at Age of Six Months","volume":"91","author":"Jiao","year":"2013","journal-title":"J. Anim. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1186\/s40064-016-2889-7","article-title":"Comparison of Models for Estimating Methane Emission Factor for Enteric Fermentation of Growing-Finishing Hanwoo Steers","volume":"5","author":"Jo","year":"2016","journal-title":"Springerplus"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1017\/S0007114514000932","article-title":"Hydrogen and Methane Emissions from Beef Cattle and Their Rumen Microbial Community Vary with Diet, Time after Feeding and Genotype","volume":"112","author":"Rooke","year":"2014","journal-title":"Br. J. Nutr."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2708","DOI":"10.3168\/jds.2018-15234","article-title":"Hot Topic: Selecting Cattle for Low Residual Feed Intake Did Not Affect Daily Methane Production but Increased Methane Yield","volume":"102","author":"Flay","year":"2019","journal-title":"J. Dairy Sci."}],"container-title":["Sustainability"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2071-1050\/15\/20\/14988\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:08:42Z","timestamp":1760130522000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2071-1050\/15\/20\/14988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,18]]},"references-count":47,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2023,10]]}},"alternative-id":["su152014988"],"URL":"https:\/\/doi.org\/10.3390\/su152014988","relation":{},"ISSN":["2071-1050"],"issn-type":[{"value":"2071-1050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,18]]}}}