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This study examines trends in research productivity, thematic evolution, and knowledge gaps regarding the use of unmanned aerial vehicles (UAVs) equipped with multispectral sensors for nutrient diagnosis in oil palm plantations. A bibliometric analysis was conducted on publications indexed in Web of Science and Scopus over the 2005–2024 period, following four phases: 1) a qualitative exploratory review of 50 scientific articles to identify search terms; 2) a comprehensive systematic search using 83 search equations, without restrictions on language, document type, or research area; 3) temporal delimitation through frequency analysis; and 4) cross-validation through thematic relevance mapping. The extracted data included title, authors, keywords, abstract, publication year, citations, and country.
The bibliometric analysis reveals a substantial knowledge gap in the application of multispectral UAV technology for estimating nutrient concentrations in oil palm. Despite the exponential growth of UAV research during 2017–2024 and plant nutrition studies during 2005–2024, the intersection of these fields in oil palm remains markedly underdeveloped, with only five publications identified. Research is concentrated in Malaysia (30%), consistent with its status as the world’s leading producer. This gap constitutes both a challenge and a promising opportunity for future research, particularly in the development of standardized protocols for non-destructive nutrient diagnosis that could help address production stagnation in plantations.