Editorial: AI-driven plant intelligence: bridging multimodal sensing, adaptive learning, and ecological sustainability in precision plant protection
Xiaoyue Lai, Xiaojun Jin · 2026
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Description
Lai and Jin introduce a research collection on AI-driven plant intelligence. Their 2026 editorial frames a problem. Protecting crops is squeezed by food insecurity, climate change, and biodiversity loss. The ecological costs of chemical inputs add pressure. Conventional protection, meanwhile, stays experience-driven and input-heavy. Precision plant protection promises productivity with fewer chemicals but must adapt to fields that vary in space and time.
The collection gathers fifteen papers spanning intelligent sensing, adaptive learning, robotic control, edge computing, federated learning, spectral analysis, pest and disease diagnosis, weed detection, and yield estimation. The editors read them as one transition: agricultural AI moving from isolated recognition tasks toward integrated systems that perceive, learn, and respond within real agroecosystems. Multimodal sensing and ecological sustainability are the twin themes they emphasise for the field's next stage.
Catalog record
| CREATOR | Xiaoyue Lai, Xiaojun Jin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 10 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |