AI-Powered Monitoring of Medicinal Plant Resources to Advance Precision Healthcare and Sustainable Conservation: A Review of Developments to 2020
DOI:
https://doi.org/10.69980/ajpr.v24i1-2.950Keywords:
Medicinal plants, Machine learning, Remote sensing, Leaf-image classification, Species-distribution models, Hyperspectral quality assessment, Environmental sensorsAbstract
Medicinal plants have long formed the backbone of traditional healthcare systems and continue to supply leads for modern pharmaceuticals. Rising demand, combined with habitat degradation, overharvesting and climate pressures, has placed many species under severe threat. By 2020, machine learning, remote sensing and sensor-based monitoring had begun to offer practical tools for mapping distributions, identifying species from images, assessing habitat suitability and supporting quality control of plant material. This review examines the literature published up to 2020 on these approaches. It covers classical and early deep-learning methods for leaf-image classification, maximum-entropy and related species-distribution models, hyperspectral and spectroscopic quality assessment, and the first applications of environmental sensors in cultivation settings. Emphasis is placed on how these technologies can simultaneously reduce pressure on wild populations and improve the consistency of raw materials required for evidence-based herbal medicine. Remaining limitations in data availability, model transferability and field deployment are discussed, together with priorities that were already evident by the end of the decade.
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11. Feasibility studies on near-infrared hyperspectral imaging for Cannabis identification (circa 2020).
12. Classical texture and shape feature papers for plant leaves (e.g., using GLCM, LBP, 2005–2018).
13. Random-forest and SVM applications to multi-feature leaf classification (various, pre-2020).
14. NDVI and satellite-derived predictors in medicinal-plant SDMs (Egyptian and Asian case studies, 2015–2020).
15. Early greenhouse sensor and climate-control trials for high-value herbs (2015–2020).
16. Chemometric authentication of traditional Chinese medicinal materials by infrared spectroscopy (multiple reviews and primary studies to 2020).
17. Presence-only modelling best-practice discussions (Phillips, Elith and co-authors).
18. Public leaf-image database descriptions and benchmarking studies (Flavia, Swedish Leaf and early medicinal subsets).
19. Studies linking cultivation environment to secondary-metabolite variation (pre-2020 controlled-environment work).
20. Reviews of remote-sensing applications in plant ecology and conservation up to 2020.
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