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				<publisherName>ZIBELINE INTERNATIONAL PUBLISHING</publisherName>
				<title type="subject" xml:lang="en" sort="Acta Mechanica Malaysia">Acta Mechanica Malaysia</title>
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			<titleGroup>
				<title type="title">THE STUDY OF THE CURRENT STATUS AND FUTURE TREND OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE: BIBLIOMETRIC ANALYSIS</title>
			</titleGroup>
			
			<copyright ownership="publisher">Copyright © 2017 Zibeline International Publishing</copyright>
			<doi origin="zibeline international publishing" registered="yes">http://doi.org/10.26480/amm.02.2025.79.87</doi>
			<issn type="online">2616-4302</issn>
           
			<eventGroup>
				<event type="publication_date" date="23-07-2025"/>
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			<creators>
				<creator xml:id="nz" creatorRole="editor">
					<personName>
						<editorNames>Nadeem Zubair</editorNames>
					</personName>
				</creator>
                <creator xml:id="cy" creatorRole="editor">
					<personName>
						<editorNames>Chuanhua Yang</editorNames>
					</personName>
				</creator>
                <creator xml:id="ak" creatorRole="editor">
					<personName>
						<editorNames>Aftab Khaliq</editorNames>
					</personName>
				</creator>
                <creator xml:id="ha" creatorRole="editor">
					<personName>
						<editorNames>Hamza Ali</editorNames>
					</personName>
				</creator>
                <creator xml:id="as" creatorRole="editor">
					<personName>
						<editorNames>Abdulaziz S</editorNames>
					</personName>
				</creator>
                <creator xml:id="b" creatorRole="editor">
					<personName>
						<editorNames>Bamahel</editorNames>
					</personName>
				</creator>
                <creator xml:id="sl" creatorRole="editor">
					<personName>
						<editorNames>Siyuan Li</editorNames>
					</personName>
				</creator>
                <creator xml:id="qx" creatorRole="editor">
					<personName>
						<editorNames>Qi Xi</editorNames>
					</personName>
				</creator>
                <creator xml:id="mih" creatorRole="editor">
					<personName>
						<editorNames>Muhammad Imran Haider</editorNames>
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		<citation_keywords>
		    <keyword>Artificial Intelligence; Machine learning, Precision agriculture; bibliometric analysis</keyword>
		</citation_keywords>
			
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		     <pdf_url>https://www.actamechanicamalaysia.com/archives/2amm2025/2amm2025-79-87.pdf</pdf_url>
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	   <citation_volume>
	       <volume>8</volume>
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	   <citation_issue>
	        <issue>2</issue>
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	   <citation_pages>
	      <pages>79-87</pages>
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	       <fulltext_html>https://actamechanicamalaysia.com/02-2025-79-87/</fulltext_html>
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			<title type="main">Summary</title>
			
					<p>Artificial Intelligence (AI) is one of the relevant areas of technology that is transforming the agriculture sector by reducing the consumption and use of resources. This research shows the development and directions of agricultural AI research between 2000 and 2024. The study analyzes the total 2,245 research papers from Scopus and the Science Citation Index Expanded (SCIE), a sub-database of the Web of Science Core Collection (WoSCC) using bibliometric analysis, with a focus on AI applications in fields including crop monitoring, irrigation optimization, and precision farming. The study found that the number of AI-related agricultural studies has increased significantly since 2017 with China, India, and the United States leading in research output. AI technologies like machine learning and remote sensing play a significant role in enhancing agricultural productivity and sustainability. However, challenges remain, including data privacy and the need for stronger collaborations between researchers globally. This study highlights key research clusters and suggests future directions for AI integration in sustainable agriculture.</p>
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