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ARS Home » Midwest Area » Wooster, Ohio » Application Technology Research » Research » Research Project #428652

Research Project: Adaptation of intelligent spray application technologies in peach orchards-CFDA # 10.309

Location: Application Technology Research

Project Number: 5082-21620-010-05-A
Project Type: Cooperative Agreement

Start Date: Oct 1, 2015
End Date: Jul 30, 2020

Objective:
The primary objective of this research is to develop and implement an advanced and affordable universal intelligent-decision spray control systems that can be reliably and user-friendly retrofitted onto conventional sprayers to automatically match system operating parameters to crop characteristics, insect/disease pressures and microclimatic conditions during pesticide spray applications for multiple field and greenhouse specialty crop production systems. Specific objectives will be: (a) develop and test a universal intelligent-decision spray control system that is retrofitted to existing sprayers to increase spray application efficiency and reduce off-target losses in nurseries, orchards, grapes, small fruits, tree nuts and other specialty crops; (b) develop and test an automatic greenhouse spray system with integration of the universal intelligent-decision spraying system to apply chemical and biological pesticides; and ultimately (c) integrate the new spray technology into best pest management programs for specialty crop production.

Approach:
A universal spray control system, based on previous models of ARS' intelligent decision spray control systems will be developed with integration of a high-speed laser scanning sensor, an automatic flow rate control unit activated with croprocessors, an embedded computer, a touch screen control and a premixing inline injection module. The automatic flow rate control unit will be designed to process sensor signals and control individual nozzles independently with variable rate functions. The embedded computer along with the touch screen will manage control algorithms and allow communications between sprayer operators and the control system. The algorithms will map crop surface structures and convert the sectional canopy volume and sprayer travel speed into the requisite amount of sprays for each nozzle to discharge in real time. The in-line injection module will mix only the amount of pesticides that are applied to eliminate chemical leftover and excess waste. With these designs, the universal spray control system can be easily integrated or retrofitted onto existing sprayers without changing sprayer components except for nozzles to facilitate widespread adoption. The automatic greenhouse spray system will be designed with retrofit of the universal intelligent-decision spraying system mounted on existing watering booms. The laser sensor will detect the presence and canopy structure of plants to be applied with chemical or bio pesticides. Flow rates discharged from nozzles will be automatically adjusted by a central flow control valve based on the plant structures and presence. In addition, an automated high resolution sampling device for insect scouting will be developed and integrated into the automatic greenhouse spray system. An expert computer subsystem will be developed as part of the universal spray control system for growers to link to local weather stations and use pest predictive models to help make treatment decisions. A spray drift potential model and temperature-based insect phenology models for field applications and climate based pest pressure determination models for greenhouses will be developed as part of the decision support system to manage spraying schedules. The expert system will make recommendations on the need of chemicals and dosages to treat for a particular insect, mite, or disease under different environment conditions. Tests of sprayers with and without intelligent decision control systems will be conducted with randomized complete block designs consisting of field or greenhouse plot replications to compare spray deposition uniformity inside canopies, chemical usage, spray drift, off-target losses, pest control efficacy and application costs for the plants at various growth stages under various environment conditions across the country.