May, 2023

May, 2024

Information and communication technologies

Software

Ing. Cristian Gabriel Zambrano Vega PhD. - Director
Ing. Washington Alberto Chiriboga Casanova M.Sc.

czambrano@uteq.edu.ec

$ 1000

In progress

Agriculture is one of the main factors that determines the economic growth of any country. In Ecuador, over 64% of the national agricultural production is in the hands of small farmers. Cocoa is one of the most exported agricultural products, with the cocoa sector being the second most exported after bananas. Unfortunately, due to various seasonal conditions, crops become infected with various types of diseases, leading to a high rate of production losses due to a lack of early and timely detection in pod growth.

The objective of this research project is to develop computer solutions based on Artificial Vision techniques for the rapid and effective detection of two of the main diseases present in Cocoa pods (Theobroma cacao L.), "Moniliasis" (Moniliophthora roreri) and "Phytophthora" (Phytophthora palmivora), thus providing a free and easy-to-use tool for farmers in the region and the country, especially for those who have not yet developed the necessary skills for disease identification.

The main Artificial Vision techniques, including Deep Learning, will be studied; a computational model will be built using the best-performing technique on a set of images captured from diseased and healthy pods in various orchards in the area, and finally, the computational model will be implemented in an easy-to-use mobile application to provide farmers with a new scientific tool to aid in the detection of these diseases in their cocoa crops.