GuavaTech: Guava Leaf Disease and Fruit Maturity Detector

Abstract


GuavaTech is a mobile-android application that uses a smartphone camera to capture images of Guapple variety of guava and identifies the different guava leaf diseases specifically the algal leaf spot, pseudocercospora leaf spot, and sooty mold that currently exist here in the Philippines. Also, it provides possible remedies or treatments of the above-mentioned diseases, automatically determines the guava fruit maturity state if it is green, ripe, and overripe through its fruit sample. And lastly, saves the result of guava leaf disease’s screenshot directly in the android phone’s gallery.

The developers used the Android Studio IDE for the development of the project. The application requires an Android phone with at least a 5MP camera and a minimum of 5.0 Marshmallow Android OS Version.

In order to develop this system, a set of tools and modeling techniques were used throughout its development. The developers followed the Mobile Application Development Lifecycle methodology in developing the system. As for the modeling of this study, Use Case, Data Flow, Context Flow, and Physical Data Flow were the diagrams used.

After several testing of the system, the developers observed that the project’s objectives were met. The application was able to identify guava diseases based on its leaf specifically algal leaf spot, pseudocercospora leaf spot, and sooty mold. It can also provide information guide for each guava disease specified. The application can determine the guava fruit maturity and save results of guava leaf disease sample through screenshot function present in the application.

However, the developers observed that it is advisable for the application to be used outdoor having pure daylight illumination. Conclusions and recommendations were highlighted for future improvements of the project.



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