Artificial intelligence in climate smart in agricultural: toward a sustainable farming future

Inna Gryshova (), Anush Balian (), Iryna Antonik (), Viktoriia Miniailo (), Viktoria Nehodenko () and Yanislava Nyzhnychenko ()
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Inna Gryshova: National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Anush Balian: National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Iryna Antonik: National Academy of Agrarian Sciences of Ukraine, Kyiv, Ukraine
Viktoriia Miniailo: State University of Trade and Economics, Kyiv, Ukraine
Viktoria Nehodenko: State University of Trade and Economics, Kyiv, Ukraine
Yanislava Nyzhnychenko: Odessa National Economic University, Odessa, Ukraine

Access Journal, 2024, vol. 5, issue 1, 125-140

Abstract: This paper explores the connections between artificial intelligence and climate smart agricultural change research as a whole and its usefulness in adaptation efforts in smart agricultural technologies. In article increased attention is currently being paid to the use of smart technologies. The article provides an analysis of the prospects for the use of artificial intelligence technologies and Climate-Smart Agriculture. At the preparatory stage, an analysis of publications in the Woofs network was carried out, which allows specifying the essence and scope of artificial intelligence technologies in climate smart agriculture. The authors considered divided into four important components which include: the management of crops, farms, livestock and aquaculture to achieve a near-term balance in food security and livelihoods; the management of landscapes and ecosystems top reserve ecosystem services that are critical for agricultural development, food security, adaptation, and mitigation; enable better farm and land management by providing services on climate impacts and mitigation actions to managers of these resources; enhancing the derivable benefits of Climate-Smart Agriculture through demand-side measures and value chain interventions. Accordingly, Climate-Smart Agriculture and artificial intelligence aims to achieve the objectives of increasing productivity and incomes sustainably, making agriculture adaptive to the changing climate, and where possible cost-effective.

Keywords: sustainability; artificial intelligence; climate smart in agricultural; machine learning; artificial intelligence technologies (search for similar items in EconPapers)
JEL-codes: O10 Q01 Q10 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:aip:access:v:5:y:2024:i:1:p:125-140

DOI: 10.46656/access.2024.5.1(8)

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