Mobile Computing for Pest and Disease Management Using Spectral Signature Analysis: A Review

Agronomy

Nik Norasma Che’Ya¹  Nor Athirah Roslin¹  Jasmin Arif Shah¹  Wan Fazilah Fazlil Ilahi¹  Nur Adibah Mohidem¹  Norsida Man¹  Mohammad Zakri Tarmidi²  Mohammadmehdi Saberioon³ 

[1] Department of Agriculture Technology, Faculty of Agriculture, University Putra Malaysia, Serdang 43400, Selangor, Malaysia;Department of Geoinformation, Faculty of Built Environment and Surveying, University Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia;Section 1.4 Remote Sensing and Geoinformatics, German Research Centre for Geosciences (GFZ), Telegrafenberg, 14473 Potsdam, Germany;

关键词: crop;    disease;    mobile app;    pest;    spectral signature;   

DOI  :  10.3390/agronomy12040967

来源: DOAJ

【 摘 要 】

The demand for mobile applications in agriculture is increasing as smartphones are continuously developed and used for many purposes; one of them is managing pests and diseases in crops. Using mobile applications, farmers can detect early infection and improve the specified treatment and precautions to prevent further infection from occurring. Furthermore, farmers can communicate with agricultural authorities to manage their farm from home, and efficiently obtain information such as the spectral signature of crops. Therefore, the spectral signature can be used as a reference to detect pests and diseases with a hyperspectral sensor more efficiently than the conventional method, which takes more time to monitor the entire crop field. This review aims to show the current and future trends of mobile computing based on spectral signature analysis for pest and disease management. In this review, the use of mobile applications for pest and disease monitoring is evaluated based on image processing, the systems developed for pest and disease extraction, and the structure of steps outlined in developing a mobile application. Moreover, a comprehensive literature review on the utilisation of spectral signature analysis for pest and disease management is discussed. The spectral reflectance used in monitoring plant health and image processing for pest and disease diagnosis is mentioned. The review also elaborates on the integration of a spectral signature library within mobile application devices to obtain information about pests and disease in crop fields by extracting information from hyperspectral datasets. This review demonstrates the necessary scientific knowledge for visualising the spectral signature of pests and diseases using a mobile application, allowing this technology to be used in real-world agricultural settings.

【 授权许可】

Unknown