Mobile application devices for MATAG coconut variety detection based on spectral signature analysis: A review

Abstract

A smartphone is a high-speed technology with many new features available. Users can install games, education, health, financial, safety, and even agriculture apps. Some smartphones can detect plant species based on the processed images from RGB and its algorithm. MATAG hybrid process including fermentation is being described. This review also shows the current trend of MATAG variety identification based on spectral signature differences between MATAG hybrid. It can be linked via mobile applications to detect the species. This review then elaborates the image segmentation in the smartphone for the segregation of digital images into several segments and locates the objects and the bounding lines of the pictures. Applications of computer vision techniques such as machine learning and support vector machine to identify MATAG variety based on spectral analysis is being reviewed. As a user-friendly approach, the mobile application is essential for farmers to capture the MATAG information from smartphones' cameras with all the processing links to the server and finally will help farmers identify the species using the mobile apps.