A3 PI.C1 Course. Digitization of meteorological data and pest detection

Objective : To understand the use of meteorological data in irrigation and agricultural management. To learn how to digitize and analyze this data to improve decision-making. To learn pest prediction techniques using meteorological data. To apply digital tools to monitor weather conditions and pest outbreaks.

Target audience : Agricultural professionals, students and technicians in the agri-food sector.

Day 1. Monday, April 6

• 9 hours. Module 3: Pest prediction through the digitization of meteorological data. Relationship between meteorological conditions and pest development.
• 12:30 pm. Break
• 13 hours. Module 3: Pest prediction models based on meteorological data. Digital tools for pest monitoring and prediction. Activity: Practical exercise in pest prediction using historical data and available tools. Questions and answers with technical staff about the module.

Day 2. Tuesday, November 18

• 9 hours. Module 1. Importance of meteorological data. Sources of meteorological data (weather stations, satellites, applications). Activity: Review of meteorological data platforms and applications.
• 11:45 a.m. Break
• 12:15 PM. Module 2. Methods for collecting meteorological data (temperature, humidity, precipitation). Data analysis to optimize irrigation. Examples of how meteorological data affects irrigation decisions. Activity: workshop on analyzing a set of meteorological data applied to irrigation.

Matchday 3. Wednesday, November 19

• 9 hours . Module 4. Review of software and applications for the management of meteorological and pest data. Creation of an action plan for the implementation of these tools in the field.
• 12:30 pm . Break
• 13 hours. Module 4. Activity: Design of a monitoring system that integrates meteorological data and pest detection. Summary of learning outcomes. Questions and answers with technical staff.
• 2:30 p.m. Closing of the course, reminder to complete the satisfaction survey and questionnaire.