Study of Approaches followed for Identification of Cotton Crop Diseases

Parag J. Mondhe, Manisha P. Satone

Abstract


Abstract— One of the most significant cash crops worldwide is cotton. It is also known as white gold and it is grown in tropical and subtropical areas. The cash crop cotton benefits many developing nations' agriculture-based economies in addition to the textile industry. Over time, the cotton yield has been steadily falling. Pests and illnesses of all kinds have a significant impact on cotton production. Seed-borne, soil-borne, foliar, and potentially caused by bacterial, fungal, and viral pathogens are the diseases that harm cotton plants. The methods used to identify illnesses in cotton crops are studied in this paper.

References


Food and Agriculture Organization of the United Nations. [Online].

Available: https://www.fao.org. (Accessed on 1 October 2023).

The Cotton Corporation of India Limited, The Government of India

Undertaking. [Online]. Available: https://cotcorp.org.in/. (Accessed

on 2 October 2023).

P. Revathi and M. Hemalatha, "Classification of cotton leaf spot

diseases using image processing edge detection techniques," 2012

International Conference on Emerging Trends in Science,

Engineering and Technology (INCOSET), Tiruchirappalli, India,

, pp. 169-173, doi: 10.1109/INCOSET.2012.6513900.

Y. K. Dubey, M. M. Mushrif and S. Tiple, Superpixel based

roughness measure for cotton leaf diseases detection and

classification, 2018 4th International Conference on Recent

Advances in Information Technology (RAIT), Dhanbad, India,

, pp. 1-5, doi: 10.1109/RAIT.2018.8388993.

B. N. Pandey, R. P. Singh, M. S. Pandey and S. Jain, "Cotton Leaf

Disease Classification Using Deep Learning based Novel

Approach," 2023 International Conference on Disruptive

Technologies (ICDT), Greater Noida, India, 2023, pp. 559-561, doi:

1109/ICDT57929.2023.10150884.

S. Dhage and V. K. Garg, "Cotton Plant Fungal Disease

Classification using Deep Learning Models," 2023 11th

International Conference on Emerging Trends in Engineering &

Technology - Signal and Information Processing (ICETET - SIP),

Nagpur, India, 2023, pp. 1-5, doi: 10.1109/ICETETSIP58143.2023.10151608.

Md. Manowarul Islam, Md. Alamin Talukder, Md. Ruhul Amin

Sarker, Md Ashraf Uddin, Arnisha Akhter, Selina Sharmin, Md.

Selim Al Mamun, Sumon Kumar Debnath, “A deep learning model

for cotton disease prediction using fine-tuning with smart web

application in agriculture”, Intelligent Systems with Applications,

Volume 20, 2023, 200278, ISSN 2667-3053,

https://doi.org/10.1016/j.iswa.2023.200278.

M. S. Memon, P. Kumar, and R. Iqbal, “Meta Deep Learn Leaf

Disease Identification Model for Cotton Crop,” MDPI Computers,

vol. 11, no. 7, p. 102, Jun. 2022, doi: 10.3390/computers11070102.

Available: http://dx.doi.org/10.3390/computers11070102

P. R. Rothe and R. V. Kshirsagar, "Cotton leaf disease identification

using pattern recognition techniques," 2015 International

Conference on Pervasive Computing (ICPC), Pune, India, 2015, pp.

-6, doi: 10.1109/PERVASIVE.2015.7086983.

V. A. Gulhane and M. H. Kolekar, "Diagnosis of diseases on cotton

leaves using principal component analysis classifier," 2014 Annual

IEEE India Conference (INDICON), Pune, India, 2014, pp. 1-5, doi:

1109/INDICON.2014.7030442.


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