基于文献计量学的智慧果园研究进展与热点分析

为了宏观掌握智慧果园在国内外的研究动态、前沿和热点，更好地推动智慧果园乃至智慧农业的发展，该研究采用文献计量分析方法，以Web of science核心论文集为检索平台分析了智慧果园2002年1月1日-2022年8月累计20年的时空分布、主要研究内容以及前沿热点。主要结论如下：智慧果园的研究自2014年起步入正轨，2018年起在人工智能技术推动下发展迅猛，2018－2021年总发文量占比37.5%；总体而言，作者（Lan Yubin、Chen Chao、Tang Yu等）、机构（华南农业大学、中国农业大学和佛罗里达大学等）、地域（中国、美国、西班牙等国）交流和合作均较为密切；中国、美国是开展智慧果园研究的主要国家，总发文量共占比58.2%；当前主要研究集中在果树长势和病虫害识别和预警、无人化或智能化农机作业。根据研究目的细分的技术主要包含人工智能模型/算法、传感、物联和精准农业等。自2007年以来，研究热点由柑橘病害、产量预估等对象研究逐步过渡到技术研究上，深度学习、无人机、人工智能的研究是当今智慧果园的发展前沿。智慧果园研究深受技术推动尤其在当前人工智能技术背景下方兴未艾，而当前的环境复杂度高、种植欠规范等问题依旧制约着其进一步发展。星-空-地立体化果园感知、空-地协同无人化精准作业、水果采摘、果品的可视化溯源等方面将是未来智慧果园主要研究方向。

Research progress and hotspots of smart orchard based on bibliometrics

In order to better promote the development of smart agriculture, this review aims to analyze the research trends, frontiers, and hotspots of the smart orchard at home and abroad using bibliometric analysis. The commonly-used tool (Citespace) of quantitative literature analysis was adopted as the bibliometric analysis in the fields of science and technology. Web of science was selected as the retrieval platform to analyze the temporal and spatial distribution of research publications, main research contents, and frontier hotspots of smart orchards published from January 2002 to August 2022. Keywords of crop mainly included the longan, citrus, lychee, and peach. In addition, the keyword "orchard" was added for spare. 579 documents were finally obtained after screening and preprocessing using the following retrieval items: " TI=(longan or citrus or litchi or peach or orchard) And AB=(growth or disease or growing or pest or insect or tree or fruit) And AK=(drone or UAV or AI or intelligent or detection or segmentation or precision or spray or unmanned or robot or sensor or "deep learning" or "machine learning" or "agricultural machinery") . The retrieved data was used to conduct the following steps: The data processing software (Excel) and the bibliometric analysis tool (CiteSpace) were selected to conduct the quantitative analysis. The annual publication from 2002 to 2022 were counted using Excel and the built-in Web of science database. The collinear knowledge map of core authors, institutions, regions, and keywords was then obtained using Citespace and Excel statistical analysis tools. The analysis was also performed on the institutional cooperation network, literature co-citation, high-frequency word clustering, keyword co-occurrence, and keyword emergence. The development history, research regions, institutions, and spatial information, research technologies, and application hotspots of smart orchards were sorted out and summarized over the past 20 years using knowledge graphs. The main conclusions were as follows: The research on smart orchards was on the right track since 2014. There was the rapid development under the promotion of artificial intelligence technology since 2018. Reports published from 2018 to 2021 accounted for 37.5% of the total. In general, there were a relatively close exchange and cooperation between the authors (Lan YB, Chen C, and Tang Y), institutions (South China Agricultural University, China Agricultural University, and Univ of Florida), and regions (China, the United States, and Spain). China and the United States were the major countries in the smart orchard research, accounting for 58.2% of the total. The current research topics were focused mainly on fruit tree growth monitoring, pest identification, and early warning, unmanned or intelligent agricultural machinery operation. The technologies were adopted, including artificial intelligence models/algorithms, sensing, Internet of Things, and Precision control, according to the subdivision of research purposes. The research of deep learning, UAV, and artificial intelligence was the frontier of smart orchard development. The development of smart orchards was deeply promoted by advanced technology, especially artificial intelligence. However, the current limiting steps were determined by the high complexity of the environment and the lack of standard planting in further development. The research directions of smart orchards can be expected as the star-sky-ground three-dimensional orchard perception, air-ground collaborative unmanned precision operation, fruit picking, and visual traceability of fruit products in the future.