Abstract

Agricultural production is essential to the economic development of any country. That's why disease identification in plants is critical in the agricultural sector, as a disease in plants is a regular occurrence. If reasonable precautions are not taken on time, plants can significantly affect the environment, affecting product quality, quantity, and productivity. Lemons, grapes, limes, oranges, etc., are common citrus fruits grown the entire world. About 50% of citrus fruits are wasted each year because of diverse plant sicknesses. This paper offers a survey of various approaches for detecting and classifying diseases in citrus plant leaves. A comprehensive taxonomy of citrus leaf diseases is also presented. A study of automatic illness recognition and classification methods are also discussed. We explore different methods for pre-processing, segmentation, extraction of features and grouping. Discuss also the relevance of functional extraction and techniques of deep learning.

Details

Title
Detection and Classification Techniques of Citrus Leaves Diseases: A Survey
Author
Saini, Ashok Kumar 1 ; Bhatnagar, Roheet 1 ; Srivastava, Devesh Kumar 2 

 Department of Computer Science & Engineering, Manipal University Jaipur, Rajasthan (India) 
 Department of Information and Technology, Manipal University Jaipur, Rajasthan (India) 
Pages
3499-3510
Section
Research Article
Publication year
2021
Publication date
2021
Publisher
Ninety Nine Publication
e-ISSN
13094653
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2623926868
Copyright
© 2021. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.