Global Trends and Future Directions in Agricultural Remote Sensing for Wheat Scab Detection: Insights from a Bibliometric Analysis

Remote. Sens. Pub Date : 2023-07-06 DOI:10.3390/rs15133431
S. Hussain, Ghulam Mustafa, Imran Haider Khan, Jiayuan Liu, Cheng Chen, Bingtao Hu, Min Chen, Iftikhar Ali, Yuhong Liu
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Abstract

The study provides a comprehensive bibliometric analysis of imaging and non-imaging spectroscopy for wheat scab (INISWS) using CiteSpace. Therefore, we underpinned the developments of global INISWS detection at kernel, spike, and canopy scales, considering sensors, sensitive wavelengths, and algorithmic approaches. The study retrieved original articles from the Web of Science core collection (WOSCC) using a combination of advanced keyword searches related to INISWS. Afterward, visualization networks of author co-authorship, institution co-authorship, and country co-authorship were created to categorize the productive authors, countries, and institutions. Furthermore, the most significant authors and the core journals were identified by visualizing the journal co-citation, top research articles, document co-citation, and author co-citation networks. The investigation examined the major contributions of INISWS research at the micro, meso, and macro levels and highlighted the degree of collaboration between them and INISWS knowledge sources. Furthermore, it identifies the main research areas of INISWS and the current state of knowledge and provides future research directions. Moreover, an examination of grants and cooperating countries shows that the policy support from the People’s Republic of China, the United States of America, Germany, and Italy significantly benefits the progress of INISWS research. The co-occurrence analysis of keywords was carried out to highlight the new research frontiers and current hotspots. Lastly, the findings of kernel, spike, and canopy scales are presented regarding the best algorithmic, sensitive feature, and instrument techniques.
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农业遥感小麦赤霉病检测的全球趋势和未来方向:来自文献计量学分析的见解
本研究利用CiteSpace对小麦痂(INISWS)的成像和非成像光谱进行了全面的文献计量学分析。因此,考虑到传感器、敏感波长和算法方法,我们支持在核、穗和冠层尺度上的全球INISWS检测的发展。该研究使用与INISWS相关的高级关键字搜索组合从Web of Science核心馆藏(WOSCC)中检索原始文章。随后,创建了作者合作、机构合作和国家合作的可视化网络,以对生产性作者、国家和机构进行分类。通过期刊共被引、热门研究论文、文献共被引和作者共被引网络的可视化,识别出最重要的作者和核心期刊。调查审查了研究所研究在微观、中观和宏观层面的主要贡献,并强调了它们与研究所知识来源之间的合作程度。此外,还确定了INISWS的主要研究领域和知识现状,并提出了未来的研究方向。此外,对赠款和合作国家的审查表明,中华人民共和国、美利坚合众国、德国和意大利的政策支助大大促进了研究所的研究进展。通过关键词共现分析,突出新的研究前沿和当前热点。最后,介绍了核尺度、穗尺度和冠尺度在最佳算法、敏感特征和仪器技术方面的研究结果。
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