CEMASU Coffee and Sugarcane: Development of an Automated System for Identification and Quantification of Nematode Genera in Coffee and Sugarcane Plantations Using Image Processing and Machine Learning

• Grant number: 25/09891-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2025
• End date: February 28, 2026
• Field of knowledge: Agronomical Sciences - Agronomy - Plant Health
• Principal Investigator: Mário Eidi Sato
• Grantee: Israel Nascimento de Oliveira
• Host Institution: Instituto Biológico (IB). Agência Paulista de Tecnologia dos Agronegócios (APTA). Secretaria de Agricultura e Abastecimento (São Paulo - Estado). São Paulo , SP, Brazil
• Associated research grant: 21/11965-3 - Center for the sustainable management of pests, diseases and weeds, AP.CCD

Abstract

The efficient management of phytopathogenic nematodes, such as Meloidogyne, Pratylenchus and Helicotylenchus, represents a critical challenge for agriculture, especially in economically important crops such as coffee and sugarcane. This project aims to develop an automated system for nematode detection and identification using computer vision, integrating high-resolution image processing techniques and convolutional neural networks (CNN). The proposal seeks to capture and process microscopic images of isolated nematodes, using a Raspberry Pi HQ camera connected to a compound optical microscope. The deep learning model will be trained to classify and identify the different genera accurately, optimizing the laboratory analysis process. The proposed system is expected to significantly increase the efficiency and accuracy in nematode identification, contributing to the agility of the process and mitigating errors resulting from the manual process, bringing greater reliability to nematological prognosis reports in coffee, as well as in other crops, to reduce agricultural losses and increase productivity. The methodology will be tested on samples collected from sugarcane and coffee plantations, covering a period of 12 months. (AU)