Towards Highly Intelligent Image Processing Techniques for Rice Diseases
Identification: A Review

R.      Manavalan
doi:10.2174/2665997202666220608125036
Abstract

Background: Rice is cultivated worldwide as one of the primary food crops. The responsible factors that rigorously affect rice crops' production are pests and various rice plant diseases, leading to considerable reduction in the agrarian and global economy. More sustainable farming methods for determining disease levels and the quality of paddy plants will be essential in the future.
Objective: The disease discovery in rice crops by naked eyes may result in erroneous pesticide measurements. Therefore, early diagnosis of rice diseases can expedite disease control by properly selecting pest management methods to maximize the rice yield to cope with the demand of the world's growing population. A literature search is conducted and identifies 68 peer-reviewed research studies published in the period between 2007 and 2021, focusing on early disease detection of rice crops to maximize productivity.
Conclusion: This study has identified several key issues that must be resolved at each step of the computer-assisted diagnostic system to recognize diseases in paddy crops. Study results show that automated disease diagnosing techniques are still immature for rice plants. Hence, the ingenious design and evolution of a novel fully-automated farming system are widely essential as innovative methods for addressing and resolving diseases in the paddy crop to offer sustainability and productivity benefits to the agrarian sector.
Keywords: Rice crop, paddy, plant disease, computational approaches, image processing, plant pathology, classification.
Graphical Abstract

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DOI https://dx.doi.org/10.2174/2665997202666220608125036	Print ISSN 2665-9972
Publisher Name Bentham Science Publisher	Online ISSN 2665-9964
Current Chinese Computer Science

Towards Highly Intelligent Image Processing Techniques for Rice Diseases Identification: A Review

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