Supplementary Materials: Systematic Review of AI/ML Applications in Precision Agriculture (2013–2023)

Supplementary Materials: Systematic Review of AI/ML Applications in Precision Agriculture (2013–2023) Description This repository contains supplementary files, data, and analysis scripts accompanying the systematic review: “Applications of Artificial Intelligence and Machine Learning in Precision Agriculture: A Systematic Review of Quantitative Impacts and Adoption Barriers (2013–2023).” The repository ensures reproducibility, transparency, and open access of all data and methods. Contents Appendix A – Search StrategiesOne-line search strings (PubMed, Scopus, Web of Science) with filters and search dates. Appendix B – Data Extraction Sheet (Excel/CSV)Includes bibliographic information, crop/system studied, AI/ML details, dataset size, validation type, evaluation metrics, outcomes, adoption barriers, and funding source for all 95 included studies. Appendix C – Risk of Bias Ratings (Excel/Word)Domain-level risk of bias ratings (adapted ROBINS-I + PROBAST/QUADAS-2/ML reproducibility domains). Analysis Scripts R scripts (meta-analysis, inter-rater reliability using irr package). Python scripts (visualisations using pandas and matplotlib). FiguresForest plots, summary charts, and risk-of-bias heatmaps. README.md (this file) with instructions for reproducibility. Software & Versions Microsoft Excel v.16.80 — data entry, descriptive summaries R v.4.3.2 — meta-analysis (meta v.6.5, metafor v.4.5), inter-rater reliability (irr v.0.84) Python v.3.11 — data processing and figures (pandas v.2.1, matplotlib v.3.8) How to Reproduce Analyses Clone/download the repository. Open extraction_table.csv for raw extracted data. Run analysis.R to reproduce inter-rater reliability and bias analyses. Run figures.py to generate summary plots. Risk-of-bias assessments are available in bias_ratings.xlsx. Data & Code Availability All materials are released under a CC-BY 4.0 license. Users may reuse, adapt, and build upon these materials with attribution. Protocol Registration The review protocol (search strategy, extraction scheme, and analysis plan) has been retrospectively registered at [OSF link — insert once uploaded]. Citation If you use these materials, please cite as: Author(s). Supplementary Materials: Systematic Review of AI/ML Applications in Precision Agriculture (2013–2023). OSF/GitHub/Zenodo.