Authors:
Pedro Silva
1
;
Regina Braga
1
;
José David
1
;
Valdemar Neto
2
;
Wagner Arbex
1
;
3
and
Victor Stroele
1
Affiliations:
1
Federal University of Juiz de Fora, Juiz de Fora, MG, Brazil
;
2
Federal University of Goias, Goiania, GO, Brazil
;
3
Embrapa Dairy Cattle, Juiz de Fora, MG, Brazil
Keyword(s):
Software Ecosystem, Support Decision, Enteric Fermentation, Carbon Emission.
Abstract:
Global concerns about agriculture’s impact, mainly related to the livestock enteric fermentation producing methane Greenhouse Gas (GHG) emissions, demand solutions to mitigate these impacts. The CarbonSECO platform, tailored for carbon credit generation in Brazilian rural areas, responds to the popularity of carbon credits to offset GHG emissions. However, additional solutions related to GHG need to be conceived. This article extends the CarbonSECO platform, focusing on quantifying, monitoring, and controlling carbon emissions from livestock enteric fermentation. Intelligent techniques, including ontologies and machine learning, provide emissions management solutions for assessing and managing the environmental impact of livestock farming. These techniques address the research question of mitigating carbon emissions from Brazilian dairy farming. The article explores strategies, reviews related works, and proposes platform extensions. A feasibility study using data from an intelligent
farm showcases the platform’s ability to predict and assess changes for carbon emission reduction. As a result, this work enhances the CarbonSECO platform, offering emissions management for dairy farming. Integrating ontologies and machine learning can promote standardization, aiding property owners in better planning.
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