Review about emerging technologies to detect pre and postharvest diseases

In several countries like India, Agriculture is the most important source, which furnishes the national income. Diseases in crops are serious issues that degrade the quantity together with the quality of production, which in turn leads to losses in the financial system. There are numerous technologies that have been emerged to minimize the effects of plant diseases (PDs). Gas sensors along with image analysis tools are often incorporated into smart devices for Plant Disease Detection (PDD). These disease detection (DD) methodologies are classified into 2 groups: (I) pre-harvest DD and (II) post-harvest DD. In this work, the existing DD methods are reviewed together with that; these methodologies are contrasted with the recently innovated smart devices that characterize visible imaging, profiling, and hyper-spectral (HS) images.Additionally, the attempts to automate imaging methodologies that augmented the DD systems were also reviewed in this work. The novel Feature Extraction (FE) methodologies are evaluated for detecting those that perform well enclosing wheat accompanied by rice classes. This survey would aid the scholars in getting knowledge about the utilization of computer vision in PDD or Plant Disease Classification (PDC). ? SourcePandey, S., Yogi, K.K., Ranjan, A. (2023). A Review of Disease Detection Emerging Technologies of Pre and Post harvest Plant Diseases: Recent Developments and Future Prospects. In: Shukla, P.K., Singh, K.P., Tripathi, A.K., Engelbrecht, A. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-7892-0_3First Online: 28 April 2023Part of the?Algorithms for Intelligent Systems?book series (AIS)https://link.springer.com/chapter/10.1007/978-981-19-7892-0_3