A Review of Image Processing Techniques for Pest and Disease Early Identification Systems on Modern Cocoa Plantation

Abstract

This study presents a potential approach to applying image processing to the cocoa farming industry. Industry 4.0 is changing how technology is applied in cocoa cultivation. Research shows that pests and diseases are major factors that can reduce productivity, especially in the upstream and downstream industries. This study aims to conduct a literature review of several related studies, including previous research. Based on relevant references related to previous research, it is found that the case of disease attack in cocoa is most often studied. This study shows that the color analysis model is more inclined to the case of disease image patterns. The performance pattern of the existing approaches, the average accuracy is 82.85%. More challenges in image processing and efforts are made to improve accuracy but with lower processing complexity. This study also recommends a model that supports the implementation of image processing with machine learning technology in the upstream cocoa cultivation industry. The study results show that the proposed modeling framework can be the following reference for research development towards artificial intelligence technology to support industry 4.0, particularly in cocoa cultivation.