INNOVATIVE TECHNOLOGIES FOR THE MONITORING AND PROTECTION OF PLANTS: FROM MOLECULAR DIAGNOSTICS TO ARTIFICIAL INTELLIGENCE

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Abstract

Pests and pathogens cause losses estimated at 20–40% of global crop production, and the threat is intensifying under climate change and the globalisation of trade. Meanwhile, traditional methods of plant health monitoring, such as visual symptom inspection and pathogen culturing, are time-consuming, dependent on specialised expertise, and often unable to detect harmful organisms before significant damage occurs. The aim of this review is to provide an integrated account of the innovative technologies transforming the monitoring and protection of plants across three converging domains. The methodology is a structured narrative review of the international literature, organising the technologies into molecular diagnostics, digital monitoring, and artificial intelligence, and analysing their principles, applications, advantages, and limitations. The molecular technologies (PCR and its real-time and isothermal variants, and next-generation sequencing) identify harmful organisms from their nucleic acids with high sensitivity and specificity, increasingly at the point of need; the digital technologies (satellite remote sensing, unmanned aerial vehicles, and the agricultural Internet of Things) observe crops across scales from the region to the individual plant; and artificial intelligence (computer vision, machine learning, and predictive modelling) interprets the resulting data, diagnosing disease, identifying pests, and forecasting phytosanitary risks. The principal finding is that these technologies are complementary rather than competing approaches. Their integration into decision-support systems and digital platforms, together with emerging technologies such as CRISPR-based diagnostics and big data analytics, enables a more proactive, precise, and sustainable approach to plant protection that surpasses conventional methods. The value of the review lies in uniting domains usually treated in isolation, and its practical significance is its contribution to the early detection of threats and the reduction of crop losses essential to food security.