[Database] Advancements in Agricultural Ground Robots for Specialty Crops: An Overview of Innovations, Challenges, and Prospects

Published: 12 November 2024| Version 4 | DOI: 10.17632/482j99rfpz.4
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Description

Robotic technologies are bringing opportunities to revolutionize the production of specialty crops, offering the potential to automate tasks and save inputs such as labor, fertilizer, and pesticides. Considering the prominence of agricultural robots and their recent expansion into specialty crops, we aimed to develop a state-of-the-art review to scientifically contribute to the understanding of: i) the primary areas of robots’ application for specialty crops; ii) the specific benefits they offer; iii) their current limitations; and iv) opportunities for future investigation. We formulated a comprehensive search strategy, leveraging Scopus® and Web of ScienceTM as databases, and selecting "robot" and "specialty crops" as the main keywords. To follow a critical screening process, only peer-reviewed papers and original research were considered, resulting in the inclusion of 907 papers covering the period from 1988 to 2024. Each paper was thoroughly evaluated based on its title, abstract, keywords, methods, conclusions, and declarations. Our analysis revealed that interest in agricultural robots for specialty crops has significantly increased over the past decade, driven by advancements in vision and recognition systems. Harvesting robots have arisen as the primary focus. Robots for spraying, pruning, weed control, pollination, transplanting, and fertilizing are emerging subjects to be addressed in further research and development strategies. Ultimately, our findings serve to reveal the dynamics of agricultural robots in the world of specialty crops, while supporting suitable practices for more sustainable and resilient agriculture, indicating a new era of innovation and efficiency in agriculture.

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Our review was conducted by an in-depth examination of the scientific literature on agricultural robots and specialty crops following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The databases Scopus® and Web of Science™ were selected for the retrieval of scholarly items. A representative search strategy was constructed by combining indexing terms and Boolean operators. The resulting search string was: [title-abstract-keyword = (robot* OR unmanned ground vehicle OR UGV) AND (specialty crops OR fruits OR vegetables OR tree nuts OR dried fruits OR horticulture OR nursery crops)]. The selected indexing terms are comprehensive and ensure the representativeness of the relevant literature. It should be noted, however, that some relevant papers may have been excluded due to the specific emphasis on the term "robot". Nevertheless, this level of specificity is consistent with the primary objective of our review, which is centered on the applications of ground robots. Furthermore, the review encompasses the period between 1988 and 2024. As the year 2024 is still in progress, the review encompasses all papers published up to October 21, 2024. This approach ensured the inclusion of a comprehensive bibliographic collection, encompassing literature from the advent of robots in the field of specialty crops to the most recent publications. The initial search produced 4,011 potential studies. However, our reviewers (M.R.B.J, R.G.d.S, and L.d.A.S.) conducted an independent assessment of the studies for consistency and eligibility. They selected only peer-reviewed research papers that fit within our scope, which included research on agricultural robots for specialty crops. Therefore, we excluded experiments on duplicates to prevent bias, conference papers, review papers, non-English language, and any “grey literature” to the soundness of our approach. As a result, 3,104 studies were removed and 907 were eligible. The 907 eligible studies were classified according to the following criteria: year of publication, journal, country, crops, and subject. Furthermore, to enhance the depth of our analysis, we obtained qualitative data via the SciVal platform, including the number of citations, the field-weighted citation impact (FWCI) associated with the studies, and performance indicators, namely Outputs in Top 10% Citation Percentiles and Publications in Top 10% Journal Percentiles. The results are presented in independent sections.

Institutions

University of Georgia

Categories

Robotics, Fruit, Vegetable, Literature Review, Precision Agriculture, Horticultural Crops

Funding

Georgia Commodity Commission for Vegetables

FP00031584

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