Abstract
In today’s world, due to irregular climatic patterns and other environmental issues various pests will affect the crops. These issues may affect the soil nutrition too. Due to this deficiency in nutrition, several diseases may affect the crops. In large agricultural field farmers feel difficult to monitor the pest in every nook and corner. Before identifying the pests, it may spread over vast area and cause severe damage to crops. Also they may not aware of bacterial disease that may affect the crops and their symptoms. Besides farmers may not know which type of pesticide and chemicals they need to use to prevent the further damage of crops. In some cases excess usage of those pesticides and other chemicals may affect the corn fields. Improper usage of those chemicals may affect the yield. To monitor the field periodically we need more human power. These problems are overcome by our proposed system. In our system diseases/pests are identified at early stages by capturing the images periodically in the agricultural field. Using image processing techniques the captured image will be segmented. For this purpose Texture based Segmentation and Simple Linear Iterative Clustering (SLIC) are used. From the segmented images the features for identifying pests and diseases will be extracted. The extracted features are used for classification. The presence of pest/disease will be identified at the first stage. In second stage the type of pest/disease will be detected. For classification both Binary Support Vector Machine (BSVM) and Multi class Support Vector Machine (MSVM) are used. And also, the pesticides and other chemicals which are needed to protect the field from further damage will be recommended along with the amount of chemicals needed and the method of usage of those chemicals.
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04 July 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s12652-022-04283-0
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Acknowledgements
The authors immensely thank the Management and Principal of Mepco Schlenk Engineering College, Sivakasi (An AUTONOMOUS Institution), TamilNadu, India for their full support to carry out this research work.
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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s12652-022-04283-0
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Mahalakshmi, S.D., Vijayalakshmi, K. RETRACTED ARTICLE: Agro Suraksha: pest and disease detection for corn field using image analysis. J Ambient Intell Human Comput 12, 7375–7389 (2021). https://doi.org/10.1007/s12652-020-02413-0
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DOI: https://doi.org/10.1007/s12652-020-02413-0