CacaoNetic 

CacaoNetic is an artificial intelligence-based platform designed to quickly, accurately, and consistently classify cocoa clones based on plant images. The system utilizes computer vision and machine learning technologies to analyze the visual characteristics of cocoa leaves, fruit, and beans as the basis for clone identification. CacaoNetic presents real-time classification results with confidence scores, providing users with transparent and reliable information. The platform is designed as a digital tool for cocoa nurseries, research, and plantation management, supporting practical, data-driven decision-making in the field and at the managerial level.

 Specification

Analytical Capabilities

• Image-based cocoa clone classification using AI

• Identification of superior cocoa clones

• Rapid analysis with confidence scores for each prediction result

• Supports input of cocoa leaf, fruit, and bean images

• Serves as an initial reference for clone identification for research and plantation management

Software & Platform

• Web-based application

• Data processing using machine learning and computer vision

• Modern user interface for image upload and result visualization

• Dataset management and classification result history

• Clone distribution visualization in graphs and dashboards

• Data export support for advanced analysis and documentation

• Designed for research, breeding, and cocoa plantation management

Dashboard Website

For inquiry please contact : 085190097654