Global food security faces severe pressures from population growth, climate change and resource shortages. Traditional agricultural monitoring relies on manual sampling and offline laboratory testing, which involve considerable time delays and cannot realize continuous, in situ dynamic tracking of crop physiological status, field environment and agricultural product quality. Among the various sensing platforms for agriculture, flexible wearable sensors represent an important branch, featuring light weight, conformability, low power consumption and real-time response. It should be noted that rigid-substrate and silicon-based sensors remain indispensable in many agricultural applications, and this review focuses specifically on flexible wearable sensors while acknowledging the broader landscape of agricultural sensing technologies. Through conformal contact with plant surfaces or wearable integration, they can convert physical, chemical and biological signals of agroecosystems into readable electrical/optical signals via specific sensing transduction mechanisms. This review systematically categorizes wearable sensors for smart agriculture into two main types, optical and electrical, and elaborates their intrinsic sensing principles, summarizes typical application scenarios covering crop growth monitoring, post-harvest harvesting and agricultural product safety detection, and introduces the full-flow signal preprocessing, feature extraction and intelligent analysis technologies matched with wearable sensing data. Finally, the bottlenecks restricting large-scale field deployment of current wearable sensors are summarized, and the development directions of multi-modal integrated wearable sensing, biomimetic nanosensors inspired by natural plant sensing systems, and artificial intelligence (AI)-assisted agricultural monitoring platforms are prospected, aiming to provide a theoretical reference for the design optimization and popularization of agricultural wearable sensing equipment.
No takes yet. Share an insight, caveat, or question.
Qiu et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: