Model based decision support system of operating settings for MMAT nozzles

Droplet size, which is affected by nozzle type, nozzle setups and operation, and spray solution, is one of the most critical factors influencing spray performance, environment pollution, food safety, and must be considered as part of any application scenario. Characterizing spray nozzles can be a timely and expensive proposition if the entire operational space (all combinations of spray pressure and orifice size, what influence flow rate) is to be evaluated. This research proposes a structured, experimental design that allows for the development of computational models for droplet size based on any combination of a nozzle’s potential operational settings. The developed droplet size determination model can be used as Decision Support System (DSS) for precise selection of sprayer working parameters to adapt to local field scenarios. Five nozzle types (designs) were evaluated across their complete range of orifice size (flow rate*) and spray pressures using a response surface experimental design. Several of the models showed high level fits of the modeled to the measured data while several did not as a result of the lack of significant effect from either orifice size (flow rate*) or spray pressure. The computational models were integrated into a spreadsheet based user interface for ease of use. The proposed experimental design provides for efficient nozzle evaluations and development of computational models that allow for the determination of droplet size spectrum and spraying classification for any combination of a given nozzle’s operating settings. The proposed DSS will allow for the ready assessment and modification of a sprayers performance based on the operational settings, to ensure the application is made following recommendations in plant protection products (PPP) labels.