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The using of bibliometric analysis to classify trends and future directions on “smart farm”

机译:使用文献计量分析对“智能农场”的趋势和未来方向进行分类

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Climate change has affected the cultivation in all countries with extreme drought, flooding, higher temperature, and changes in the season thus leaving behind the uncontrolled production. Consequently, the smart farm has become part of the crucial trend that is needed for application in certain farm areas. The aims of smart farm are to control and to enhance food production and productivity, and to increase farmers' profits. The advantages in applying smart farm will improve the quality of production, supporting the farm workers, and better utilization of resources. This study aims to explore the research trends and identify research clusters on smart farm using bibliometric analysis that has supported farming to improve the quality of farm production. The bibliometric analysis is the method to explore the relationship of the articles from a co-citation network of the articles and then science mapping is used to identify clusters in the relationship. This study examines the selected research articles in the smart farm field. The area of research in smart farm is categorized into two clusters that are soil carbon emission from farming activity, food security and farm management by using a VOSviewer tool with keywords related to research articles on smart farm, agriculture, supply chain, knowledge management, traceability, and product lifecycle management from Web of Science (WOS) and Scopus online database. The major cluster of smart farm research is the soil carbon emission from farming activity which impacts on climate change that affects food production and productivity. The contribution is to identify the trends on smart farm to develop research in the future by means of bibliometric analysis.
机译:气候变化影响了所有国家的干旱,洪涝,高温和季节变化,从而影响了耕种,从而导致产量不受控制。因此,智能农场已成为某些农场区域中应用所必需的关键趋势的一部分。智慧农场的目标是控制和提高粮食产量和生产力,并增加农民的利润。应用智能农场的优势将提高生产质量,支持农场工人并更好地利用资源。这项研究旨在探索研究趋势,并使用文献计量分析确定智能农场的研究集群,该研究支持了农业提高农场生产质量。文献计量分析是从文章的共同引用网络中探索文章之间关系的方法,然后使用科学制图来识别关系中的聚类。本研究检查了智能农场领域中的精选研究文章。使用VOSviewer工具将智能农场的研究领域分为两个类别,分别是农业活动,食品安全和农场管理中的土壤碳排放,关键词与智能农场,农业,供应链,知识管理,可追溯性等研究文章相关,以及来自Web of Science(WOS)和Scopus在线数据库的产品生命周期管理。智慧农场研究的主要集群是农业活动产生的土壤碳排放,它影响气候变化,从而影响粮食生产和生产力。其贡献在于通过文献计量分析来识别智能农场的趋势,以在将来开展研究。

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