Authors: Hanamantray R. Horaginamani, Prakash R. Khedad, Shreyas Suresh Rathod, Varun S. Naik, Prof. Gopinath Rathod
Abstract: Agricultural pesticide spraying is an essential crop-protection operation, but conventional hand-operated, engine-driven and battery-dependent sprayers can impose operator effort, fuel dependence, inconsistent application and chemical loss. The 21 studies reviewed in this paper collectively cover photovoltaic sprayers, multi-nozzle systems, remote and robotic platforms, autonomous aerial spraying, air-assisted atomization, spray-drift management, variable-rate application and machine-vision control. The literature indicates a progression from replacing manual or fossil-fuel power with photovoltaic electric pumping toward systems that also adapt spray delivery to crop geometry and target conditions. Solar-powered trolley and knapsack systems demonstrate the feasibility of photovoltaic operation and reductions in operator burden; remote and robotic systems provide greater separation between the operator and spray plume; and precision systems demonstrate substantial reductions in applied chemical when spray rate is matched to the target. At the same time, solar intermittency, battery capacity, machine mass, nozzle calibration, pressure control, spray uniformity, drift and sensing cost remain important limitations. This review synthesizes the 21 studies through a transparent corpus-based review methodology and identifies design principles relevant to a practical solar-powered multifaceted sprayer. Based on the synthesis, a modular machine architecture is proposed in which solar PV, battery storage, an efficient DC pump, pressure regulation, a filtered multi-nozzle boom and a stable wheeled chassis form the basic platform, while remote control, flow/pressure sensing and machine vision can be added progressively. The review concludes that the most practical development pathway is a layered system that combines renewable energy, mechanical simplicity, adjustable spraying and provision for future precision automation.
DOI: http://doi.org/10.5281/zenodo.22055698
