A Review of Plant Disease Prediction Methods for Agricultural Applications
Nirmala Shinde1, Guddi Singh2

1Nirmala Shinde, Ph.D Research Scholar, Department of Computer Science and Engineering, Kalinga University, Naya Raipur (Chhattisgarh), India.
2Dr. Guddi Singh, Faculty, Department of Computer Science and Engineering, Kalinga University, Naya Raipur (Chhattisgarh), India.
Manuscript received on 30 September 2022 | Revised Manuscript received on 07 October 2022 | Manuscript Accepted on 15 October 2022 | Manuscript published on 30 October 2022 | PP: 98-103 | Volume-12 Issue-1, October 2022 | Retrieval Number: 100.1/ijeat.A38561012122 | DOI: 10.35940/ijeat.A3856.1012122

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Due to the decrease in plant quality and productivity, plant diseases seem to be responsible for significant economic losses in the world. As a result, farmers nowadays consider plant disease prediction to be an important area of research. To help an accurate prediction of plant disease, numerous techniques have been detailed in the literature. To highlight the many issues with current approaches for problem-solving predictions, we will evaluate various literary works that are focused on plant disease prediction in the agricultural industry. Based on several variables, including different datasets, year of publication and journals, performance metrics, and other considerations, the analyses of various approaches are enhanced in this case, and include the advantages and disadvantages based on the analysis of the methods. Finally, the paper concludes by discussing future research areas and difficulties in improving prediction performance for the plant disease prediction techniques used in the growing agricultural process. 
Keywords: Plant Disease Prediction, Agricultural Application 
Scope of the Article: Agricultural Informatics and Communication