HomeIAMURE International Journal of Ecology and Conservationvol. 33 no. 1 (2020)

MaizeCheck: A Web Application for Identifying Maize Foliar Diseases Using Convolutional Neural Network

 

Abstract:

Maize, also called Corn, is the most produced grain in the world. Maize is considered a great source of carbohydrates, iron, vitamin B, and minerals and can be processed into various food and industrial products, such as starch, sweeteners, oil, beverages, glue, industrial alcohol, and fuel ethanol. The researcher then conducted a study regarding foliar diseases of maize to create a technology that would help the farmers and even the concerned organization like the Department of Agriculture (DA) to identify maize foliar diseases as a substitute/addendum of present techniques. The findings revealed that the application’s main feature is the “Uploads” wherein the disease identification is actually done. Other features that were deemed necessary for the application were “Dashboard,” which presents the summary of previous uploads and results; “Profile” which presents the details and password of the user, as well as his/her previous activities, and “Forums” which makes the application interactive. Moreover, the MaizeCheck Web Application in terms of efficiency, affect, helpfulness, control, and learnability were perceived as usable by the respondents. It was recommended to expand the web application’s capability by identifying more types of maize foliar diseases and other high-value crops in the country.