RESUMO
The development of modern agriculture has prompted the greater input of herbicides, insecticides, and fertilizers. However, precision release and targeted delivery of these agrochemicals still remain a challenge. Here, a pesticide-fertilizer all-in-one combination (PFAC) strategy and deep learning are employed to form a system for controlled and targeted delivery of agrochemicals. This system mainly consists of three components: (1) hollow mesoporous silica (HMS), to encapsulate herbicides and phase-change material; (2) polydopamine (PDA) coating, to provide a photothermal effect; and (3) a zeolitic imidazolate framework (ZIF8), to provide micronutrient Zn2+ and encapsulate insecticides. Results show that the PFAC at concentration of 5 mg mL-1 reaches the phase transition temperature of 1-tetradecanol (37.5 °C) after 5 min of near-infrared (NIR) irradiation (800 nm, 0.5 W cm-2). The data of corn and weed are collected and relayed to deep learning algorithms for model building to realize object detection and further targeted weeding. In-field treatment results indicated that the growth of chicory herb was significantly inhibited when treated with the PFAC compared with the blank group after 24 h under NIR irradiation for 2 h. This system combines agrochemical innovation and artificial intelligence technology, achieves synergistic effects of weeding and insecticide and nutrient supply, and will potentially achieve precision and sustainable agriculture.
