Zhang Yali, Zhao Dehua, Liu Hanchao, Huang Xinrong, Deng Jizhong, Jia Ruichang, He Xiaoping, Tahir Muhammad Naveed, Lan Yubin
College of Engineering, South China Agricultural University, Guangzhou, China.
National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou, China.
Front Plant Sci. 2022 Aug 11;13:955340. doi: 10.3389/fpls.2022.955340. eCollection 2022.
Multispectral technology has a wide range of applications in agriculture. By obtaining spectral information during crop production, key information such as growth, pests and diseases, fertilizer and pesticide application can be determined quickly, accurately and efficiently. The scientific analysis based on Web of Science aims to understand the research hotspots and areas of interest in the field of agricultural multispectral technology. The publications related to agricultural multispectral research in agriculture between 2002 and 2021 were selected as the research objects. The softwares of CiteSpace, VOSviewer, and Microsoft Excel were used to provide a comprehensive review of agricultural multispectral research in terms of research areas, institutions, influential journals, and core authors. Results of the analysis show that the number of publications increased each year, with the largest increase in 2019. Remote sensing, imaging technology, environmental science, and ecology are the most popular research directions. The journal is one of the most popular publishers, showing a high publishing potential in multispectral research in agriculture. The institution with the most research literature and citations is the USDA. In terms of the number of papers, Mtanga is the author with the most published articles in recent years. Through keyword co-citation analysis, it is determined that the main research areas of this topic focus on remote sensing, crop classification, plant phenotypes and other research areas. The literature co-citation analysis indicates that the main research directions concentrate in vegetation index, satellite remote sensing applications and machine learning modeling. There is still a lot of room for development of multi-spectrum technology. Further development can be carried out in the areas of multi-device synergy, spectral fusion, airborne equipment improvement, and real-time image processing technology, which will cooperate with each other to further play the role of multi-spectrum in agriculture and promote the development of agriculture.
多光谱技术在农业领域有着广泛的应用。通过在作物生产过程中获取光谱信息，可以快速、准确且高效地确定诸如生长、病虫害、肥料和农药施用等关键信息。基于科学网（Web of Science）的科学分析旨在了解农业多光谱技术领域的研究热点和关注领域。选取2002年至2021年间农业领域与农业多光谱研究相关的出版物作为研究对象。使用CiteSpace、VOSviewer和Microsoft Excel软件，从研究领域、机构、有影响力的期刊和核心作者等方面对农业多光谱研究进行全面综述。分析结果表明，出版物数量逐年增加，2019年增长幅度最大。遥感、成像技术、环境科学和生态学是最热门的研究方向。该期刊是最受欢迎的出版商之一，在农业多光谱研究方面显示出很高的出版潜力。拥有最多研究文献和引用次数的机构是美国农业部（USDA）。就论文数量而言，姆坦加是近年来发表文章最多的作者。通过关键词共被引分析，确定该主题的主要研究领域集中在遥感、作物分类、植物表型等研究领域。文献共被引分析表明，主要研究方向集中在植被指数、卫星遥感应用和机器学习建模。多光谱技术仍有很大的发展空间。可以在多设备协同、光谱融合、机载设备改进和实时图像处理技术等领域进一步开展研究，这些领域将相互协作，进一步发挥多光谱技术在农业中的作用，推动农业发展。
