Solar energy paper index
AI- and Nano-Enabled Precision Agriculture: Frontier Approaches for Stress Tolerance in Plants
One-line summary
A solar energy research paper on AI- and Nano-Enabled Precision Agriculture: Frontier Approaches for Stress Tolerance in Plants.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
Increasing climatic variability and the intensifying biotic and abiotic stresses pose major challenges to global crop productivity, emphasising the urgent need for resource-efficient and sustainable agricultural strategies. Artificial intelligence (AI) and nanotechnology have emerged as complementary technologies capable of enhancing precision agriculture through early stress detection, predictive analytics, and targeted agro-input delivery. This review uniquely integrates recent advances in AI-driven predictive analytics and nano-enabled delivery systems within an agricultural framework of closed-loop precision. It highlights their synergistic role in improving plant stress tolerance and climate-resilient crop production. AI approaches to integrating machine learning, deep learning, and multimodal data fusion enable real-time stress monitoring, hotspot detection, and prediction of stress–risk windows for timely site-specific interventions. Concurrently, nano-engineered formulations enhance the efficiency of the use of nutrients, stabilise bioactive compounds, and enable controlled release mechanisms while reducing environmental losses. The convergence of these technologies supports adaptive crop management systems that integrate stress sensing, predictive decision-making, targeted delivery, and response verification. Despite significant progress, challenges remain regarding field-scale validation, nanoparticle environmental fate, AI model generalisation, and regulatory governance. Future priorities include biodegradable nano formulations, uncertainty-aware AI systems, standardised dosimetry, and adaptive multimodal AI platforms for diverse agroecosystems. Overall, the integration of AI and nanotechnology offers a scalable and sustainable pathway towards climate-resilient agriculture by improving yield stability, optimising resource usage, and minimising ecological impacts.
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