Simple Screening Method of Maize Disease using Machine Learning

Chyntia Jaby, Entuni and Tengku Mohd Afendi, Zulcaffle (2019) Simple Screening Method of Maize Disease using Machine Learning. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 9 (1). pp. 464-467. ISSN 2278-3075

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Abstract

Plant leaf diseases are significant issue in agriculture field. Some of the common plant leaf diseases are powdery mildew, dark spot and rust. They are a noteworthy wellspring of an immense number of dollar worth of setbacks to farmers on a yearly premise. Plant breeders frequently need to screen countless number of plant leaves to find the stage of diseases of their crops to perform an early treatments. Therefore, a robust method for field screening is needed in order to spare the farmers and the environment as well. Inappropriate used of treatments such as impulsive pesticides can imperil the environment. Hence, this paper present a simple and efficient machine learning method which is Fuzzy C-Means algorithm to screen leaf disease severity in maize. Fuzzy C-Means is a new algorithm and very efficient to be used in object detection. Therefore, it is applicable to detect disease spot in plant leaf and measure the diseases severity. This field screening method help the farmer to identify the progression of the diseases in their crops quicker and easier than the other field screening techniques.

Item Type: E-Article
Uncontrolled Keywords: Plant leaf disease, Field screening, Machine learning, Fuzzy C-Means, Maize
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
S Agriculture > S Agriculture (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Engineering
Depositing User: CHYNTIA JABY AK ENTUNI
Date Deposited: 20 Jan 2020 05:13
Last Modified: 20 Jan 2020 06:45
URI: http://ir.unimas.my/id/eprint/28774

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