Authors

Abstract

Smartphone has become a convenient tool in agriculture because their mobility suits the nature of farming, their cost-effectiveness, and their ability to identify the detect plant species, including MATAG variety identification. The characteristics of MATAG variety are challenging to differentiate macroscopically, but reflectance values can be generated using a spectral signature graph. This review aims to discuss and elaborate on developing an intelligent identification system for MATAG variety based on spectral signature analysis using a smartphone device. The first section of this paper describes the characterization of MATAG. Then, based on spectral signature differences between each coconut species, this study provides an overview of MATAG variety detection based on spectral signature libraries by including the current trend of research for coconut variety detection using a smartphone. The advantages and disadvantages of traditional methods such as manual inspection and laboratory analysis were compared with smartphone-spectral signature based approaches. Mechanisms of MATAG variety detection based on spectral signature analysis using a smartphone were identified in this review. Case studies and testimonials from farmers on how smartphone devices have revolutionized crop monitoring practices were also discussed, together with the economic impact of using this technology to the agricultural industry. This review also elaborates on the challenges of detecting MATAG variety using smartphone devices, which will be a useful resource for researchers and app developers to solve the problems in future research, whereby the new knowledge contribution come in. As a user-friendly approach, the smartphone is crucial for farmers to capture MATAG data from its sensor, with all processing power to the server could eventually help farmers in the plantation.

Abstract in English

Smartphone has become a convenient tool in agriculture because their mobility suits the nature of farming, their cost-effectiveness, and their ability to identify the detect plant species, including MATAG variety identification. The characteristics of MATAG variety are challenging to differentiate macroscopically, but reflectance values can be generated using a spectral signature graph. This review aims to discuss and elaborate on developing an intelligent identification system for MATAG variety based on spectral signature analysis using a smartphone device. The first section of this paper describes the characterization of MATAG. Then, based on spectral signature differences between each coconut species, this study provides an overview of MATAG variety detection based on spectral signature libraries by including the current trend of research for coconut variety detection using a smartphone. The advantages and disadvantages of traditional methods such as manual inspection and laboratory analysis were compared with smartphone-spectral signature based approaches. Mechanisms of MATAG variety detection based on spectral signature analysis using a smartphone were identified in this review. Case studies and testimonials from farmers on how smartphone devices have revolutionized crop monitoring practices were also discussed, together with the economic impact of using this technology to the agricultural industry. This review also elaborates on the challenges of detecting MATAG variety using smartphone devices, which will be a useful resource for researchers and app developers to solve the problems in future research, whereby the new knowledge contribution come in. As a user-friendly approach, the smartphone is crucial for farmers to capture MATAG data from its sensor, with all processing power to the server could eventually help farmers in the plantation.