Mango leaf disease recognition using neural network and support vector machine
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ORIGINAL ARTICLE
Mango leaf disease recognition using neural network and support vector machine Md. Rasel Mia1 · Sujit Roy1,2 · Subrata Kumar Das2
· Md. Atikur Rahman1
Received: 4 February 2019 / Accepted: 21 March 2020 © Springer Nature Switzerland AG 2020
Abstract The mango tree is affected by different diseases and it is very difficult to detect disease in naked eye. This paper presents a neural network ensemble (NNE) for mango leaf disease recognition (MLDR) that help to identify diseases easily and correctly instead of traditional system. This study intends to detect the diseases of mango leaf with machine learning monitoring different symptoms of leaves. Here, trained data are produced by classification technique collecting images of leaves that were various disease affected. A machine learning system is designed to identify the symptom of mangoes’ leaf diseases automatically uploading and matching new images of affected leaf with trained data. The proposed system could successfully detect and classify the examined disease with average accuracy of 80%. This proposed solution would clinch the mango plants. The system will help to detect disease without the presence of agriculturist that would save time to identify disease with machine instead of manual system. It would also ease to treat the affected mango leaf disease properly, increase the production of mango, and meet the demand of global market. Keywords Artificial neural network (ANN) · Disease · K-nearest neighbor (KNN) · Mango plant · Pattern recognition · Support vector machine (SVM)
1 Introduction Mango plants are very important to keep biodiversity and it is a major source of fruits. That is why, Mango plant cultivation has been a growing awareness over the world for promoting fruit production in a sustainable agricultural practices. However, Mango plants disease is a great barrier to produce enough fruits to meet the people demand. There are many diseases, such as Mango malformation disease, Anthracnose,
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Subrata Kumar Das [email protected] https://jkkniu.edu.bd/teachers_personal_page/?t=106 Md. Rasel Mia [email protected] Sujit Roy [email protected] Md. Atikur Rahman [email protected]
1
Department of CSE, Gono Bishwabidyalay, Dhaka, Bangladesh
2
Department of CSE, Jatiya Kabi Kazi Nazrul Islam University, Dhaka, Bangladesh
Bacterial flower disease, Golmachi, Moricha disease, Shutimold, Bacterial black spot, Apical bud necrosis, Red rust, Lichens, Powdery mildew, Root rot and damping off, and Ganoderma root rot, which affect the mango trees. Numerous Mango trees of majority countries over the world are suffered by Powdery mildew and damaged up to 23% unsprayed trees [5,15]. Losses of mango trees are caused up to 39% worldwide by Anthracnose [23]. Kumar and Beniwal cited that Mango malformation affects over 50% trees in India including Egypt, Africa, Mexico, America, Sudan, Cuba, Australia, and Bangladesh [13]. Mango Bacterial Canker is a fatal disease which causes 10–100% loss to mango yield in the field as well as
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