102156 Spatial Analysis of Fungal Diseases Risk for Strawberry in Florida Using Real-Time Mesoscale Analysis Gridded Dataset.

Poster Number 319-713

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)

Tuesday, November 8, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Daniel Dantas Barreto, Clyde W. Fraisse and Eduardo Gelcer, Agricultural and Biological Engineering, University of Florida, Gainesville, FL
Abstract:
The strawberry is an important and profitable crop for Florida growers. The state is the second in production only behind California. Its production has been increasing in the past few years and technology has an important role in keeping production to a high level. One factor that impacts the results of the harvest season is disease, particularly fungal disease. The main fungal diseases in Florida are Anthracnose and Botrytis (fruit rot), which may cause high losses for the farmers. To protect their crops, the growers apply fungicide. Application timing is crucial for controlling disease occurrence and ensure a high yield. Monitoring disease systems based on weather data have been guiding farmers’ decisions in relation to disease control. The Strawberry Advisory System (SAS) from agroclimate.org (http://agroclimate.org/tools/Strawberry-Advisory-System) is a tool that advises the grower about the timing of fungicide application. This tool uses weather station data from Florida Automated Weather Network (FAWN) stations to calculate the risk of Anthracnose and Botrytis for the region immediately surrounding the weather station. Some growers are located too far from these weather stations, and the information provided by the tool is not representative of their area. One way to improve this system is creating a risk map based on high resolution gridded weather data. The objective of this study is to create a risk map of strawberry diseases using the Real-Time Mesoscale Analysis (RTMA) gridded dataset for Florida. The results of this project will allow farmers located far from FAWN weather stations to have access to risk information for their area.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)