Critical review demonstrates the inadequacy of traditional pest thresholds in intensified rice farming, suggesting a transition to artificial intelligence-driven precision systems.
Key Points
To re-evaluate the relevance of conventional economic threshold models in modern, intensified rice cultivation and investigate the potential of artificial intelligence-driven precision monitoring.
Conducted a PRISMA-guided critical review of literature published between 1951 and 2026 across Web of Science, Scopus, ScienceDirect, and Google Scholar.
Analyzed climate change impacts on host-pest physiology, rhizosphere microbiome modulation of plant defenses, and manual scouting versus emerging AI monitoring technologies.
Elevated carbon dioxide levels and drought stress alter host-herbivore metabolic interactions, accelerating pest population growth.
The rhizosphere microbiome activates jasmonic and salicylic acid pathways, significantly boosting host tolerance against biotic stress.
Manual field scouting lacks real-time predictive capacity, supporting a shift toward precision thresholds that integrate the Internet of Things, drones, and artificial intelligence.