Desarrollo de una estación meteorológica en la ESPOCH Sede Orellana para generar una alerta temprana fitosanitaria de la plaga “monilla” en plantaciones de cacao.

Abstract

The main objective of this degree work was to develop a meteorological station located in the ESPOCH Headquarters-Orellana to obtain useful data in order to generate a phytosanitary early warning of the "monilla" pest through an algorithm based on diffuse logics for cocoa plantations. The safety of the teams prevailed in any situation, so it was decided to change the location of the Automatic Meteorological Station to the National Institute of Agricultural Research, which is a strategic ally of the Project for Agricultural Phytosanitary Early Warning Research to which the teams belong. The climate conditions of the Amazon region of Ecuador (Coca), makes the plantations develop various types of diseases and pests, where they stand out: "witch's broom" Moniliophthora perniciosa, "black cob" Phytophthora palmivora and, the case study, the “monilla” Moniliophthora roreri. Random diseased and healthy samples from the same tree were analyzed, characterizing the disease and by analyzing the ideal conditions of presence and growth of the pest. A meteorological station was installed which will obtain information on climatic data about the crops, highlighting humidity, temperature, wind direction, precipitation and solar radiation. The storage system of this data was made directly to the cloud by means of a Raspberry Pi 4. Whit this information, an algorithm was designed which determined the behavior of this pest through fuzzy logic for the generation of the phytosanitary early alarm, which was sent by means of an email. It is concluded that the implementation of the meteorological station provided reliable data to prepare the phytosanitary alarm to alert the entities involved and that preventive actions are taken. For this reason, it is recommended to implement these alarms to avoid losses related to this type of pest in cocoa plantations.