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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Nur Nabilah Abu Mangshor
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Cawangan Melaka
Computer Science & IT Engineering

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Nutrient deficiency detection in Maize (Zea mays L.) leaves using image processing Nurbaity Sabri; Nurul Shafekah Kassim; Shafaf Ibrahim; Rosniza Roslan; Nur Nabilah Abu Mangshor; Zaidah Ibrahim
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (658.346 KB) | DOI: 10.11591/ijai.v9.i2.pp304-309

Abstract

Maize is one of the world's leading food supplies. Therefore, the crop's production must continue to reproduce to fulfill the market demand. Maize is an active feeder, therefore, it need to be adequately supplied with nutrients. The healthy plants will be in deep green color to indicate it consist of adequate nutrient. Current practice to identify the nutrient deficiency on maize leaf is throught a laboratory test. It is time consuming and required agriculture knowledge. Therefore, an image processing approach has been done to improve the laboratory test and eliminate a human error in identification process. The purpose of this research is to help agriculturist, farmers and researchers to identify the type of maize nutrient deficiency to determine an action to be taken. This research using image processing techniques to determine the type of nutrient deficiency that occurs on the plant leaf. A combination of Gray-Level Co-Occurrence Matrix (GLCM), hu-histogram and color histogram has been used as a parameter for further classification process. Random forest technique was used as classifiers manage to achive 78.35% of accuracy. It shows random forest is a suitable classifier for nutrient deficiency detection in maize leaves. More machine learning algorithm will be tested to increase current accuracy.
Co-Authors Nurbaity Sabri Nurul Shafekah Kassim Rosniza Roslan Shafaf Ibrahim Zaidah Ibrahim