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Review Papers | Computer Science | India | Volume 12 Issue 12, December 2023 | Popularity: 5.7 / 10

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Advances in Rice Plant Disease Detection: A Survey of Machine Learning and Deep Learning Approaches

D. Felicia Rose Anandhi, S. Sathiamoorthy

Abstract: Rice is the major crop worldwide, which provides sustenance for a substantial part of the world's population. But the rice plant is prone to different diseases that seriously damage the quality and crop yield. Accurate and earlier detection of this disease is crucial to implement effective and timely disease management strategy. Recently, the incorporation of machine learning (ML) and deep learning (DL) approaches has exposed great potential to automate and enhance the uncovering of crop diseases. This survey paper's aim is to provide a detailed study of the present research on crop disease recognition using ML and DL algorithms. We begin by deliberating the significance of earlier disease recognition in rice plants and the challenges related to the conventional technique. Consequently, we presented a review of the challenges and need to be associated with the crop disease recognition system. Moreover, we analyze and review the present study that utilizes ML and DL approaches for detecting rice plant diseases. Furthermore, we inspect the evaluation methodologies, performance metrics, and datasets applied in this case for evaluating the efficiency of the presented method. Additionally, we highlight the emerging trends and recent advancements in this field, such as the incorporation of image augmentation approaches, transfer learning, and ensemble algorithms.

Keywords: Plant disease detection, Rice, Computer vision, Deep learning, Machine learning

Edition: Volume 12 Issue 12, December 2023

Pages: 1408 - 1414

DOI: https://www.doi.org/10.21275/SR231218142714

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