A Survey on Plant Disease Detection and Classification Using Different Machine Learning Algorithms

Authors

  • Tadmare S Department of Computer Engineering, PCCOE, Pune University, Pune, India
  • Mahalakshmi B Department of Computer Engineering, PCCOE, Pune University, Pune, India

DOI:

https://doi.org/10.26438/ijcse/v7i2.338341

Keywords:

agricultural science, image processing, machine learning, classification, disease detection and classification

Abstract

Plant diseases takes place when an organism infects a plant and disrupts its normal growth habits. Diseases have many cause including fungi, bacteria and viruses. Fungi are identified mostly from their morphology, with importance placed on their reproductive structures. Bacteria are measured more primitive than fungi and usually have simpler life cycles. With few exceptions, bacteria are as single cells and increase in numbers by dividing into two cells during a process called binary fission. Viruses are tremendously tiny particles consisting of protein and genetic material with no related protein. The term disease is usually used only for the damage of live plants. Detection of these symptoms with visual aid is matter of time and inconsistent results. Even the experts from related areas have found this visual approach of detection to be erroneous. So by using image processing techniques and machine learning algorithms we can detect and classify diseases of plants.

References

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Published

2019-02-28
CITATION
DOI: 10.26438/ijcse/v7i2.338341
Published: 2019-02-28

How to Cite

[1]
S. Tadmare and B. Mahalakshmi, “A Survey on Plant Disease Detection and Classification Using Different Machine Learning Algorithms”, Int. J. Comp. Sci. Eng., vol. 7, no. 2, pp. 338–341, Feb. 2019.

Issue

Vol. 7 No. 2 (2019): IJCSE February Edition

Section

Survey Article

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