ArticleHeliyon2024
Unveiling temporal and spatial research trends in precision agriculture: A BERTopic text mining approach.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- The Evolution of Data-Driven Management Zone Delineation: A Systematic Review.Sensors (Basel, Switzerland) · 2026Review
- Shifts in dental trauma research (2000-2025): a literature-based thematic analysis using topic modeling.BMC oral health · 2026Article
- An evaluation of machine learning for soil analysis in internet of things-enabled smart farming.Scientific reports · 2026Article
- What drives EBSA across contexts? evidence from China using BERTopic.Frontiers in child and adolescent psychiatry · 2026Article
- Beyond writing machines: A Kano model analysis of researchers' hierarchical needs for AIGC services across the research lifecycle.PloS one · 2026Article
- The IoT and AI in Agriculture: The Time Is Now-A Systematic Review of Smart Sensing Technologies.Sensors (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study leverages the BERTopic algorithm to analyze the evolution of research within precision agriculture, identifying 37 distinct topics categorized into eight subfields: Data Analysis, IoT, UAVs, Soil and Water Management, Crop and Pest Management, Livestock, Sustainable Agriculture, and Technology Innovation. By employing BERTopic, based on a transformer architecture, this research enhances topic refinement and diversity, distinguishing it from traditional reviews. The findings highlight a significant shift towards IoT innovations, such as security and privacy, reflecting the integration of smart technologies with traditional agricultural practices. Notably, this study introduces a comprehensive popularity index that integrates trend intensity with topic proportion, providing nuanced insights into topic dynamics across countries and journals. The analysis shows that regions with robust research and development, such as the USA and Germany, are advancing in technologies like Machine Learning and IoT, while the diversity in research topics, assessed through information entropy, indicates a varied global research scope. These insights assist scholars and research institutions in selecting research directions and provide newcomers with an understanding of the field's dynamics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.