Work

Optimizing air-assistance for an electrostatic sprayer integrated with intelligent spray control in a greenhouse environment

Year: 2026

Type: article

Abstract: An electrostatic spraying system integrated with air-assistance was evaluated to enhance canopy deposition in a wind tunnel and a greenhouse environment under varying air speeds and droplet charge-to-mass ratios. Experimental results in a wind tunnel revealed that under still-air conditions, an air-assistance speed of 10 m s-1 optimized spray performance, achieving a peak average canopy coverage of 15.4% and deposition of 1.52 µg cm-2. Under moderate wind conditions of 2.24 m s-1, the optimal operational parameters shifted; maximum canopy deposition was observed at an air-assistance speed of 15 m s-1, while maximum coverage occurred at 20 m s-1. Subsequent greenhouse experiments compared conventional and variable-rate ‘intelligent’ spraying systems, both electrostatically and non-electrostatically, to quantify canopy coverage, spray uniformity, and overspray potential. Electrostatic sprays relatively enhanced average coverage by 21.5% and 26.8% for conventional and intelligent systems, respectively, compared to the non-electrostatic counterparts. When combined with air-assistance, electrostatic charging relatively increased coverage by 49.1% for the conventional system and 35.5% for the intelligent variable-rate system relative to the conventional non-electrostatic system. Additionally, the intelligent system significantly improved the spray uniformity index and minimized overspray potential. These findings demonstrate that integrating intelligent control with the air-assisted electrostatic spraying system could provide optimal applications with maximized canopy penetration and minimized off-target waste in a greenhouse environment.

Source: Smart Agricultural Technology

DOI: 10.1016/j.atech.2026.102190

Authors: Matthew Herkins, Heping Zhu, Hongyoung Jeon, Lingying Zhao

Institutions: Agricultural Research Service, United States Department of Agriculture, The Ohio State University

Language: English

Topic: Agricultural Engineering and Mechanization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,770