POMEGRANATE DISEASE DETECTION AND PESTICIDES SUGGESTION

نویسندگان

چکیده

Abstract: Pomegranate is a valuable fruit crop that widely cultivated in various regions. However, its production often threatened by diseases can significantly affect yield and quality. In this project, we propose method for pomegranate disease detection pesticides suggestion using the gray-level co-occurrence matrix (GLCM) algorithm. The proposed approach utilizes GLCM to extract texture features from leaf images classify them into healthy or diseased categories. Moreover, suggest most effective control detected performance of evaluated dataset with different symptoms. experimental results demonstrate effectiveness our detecting classifying high accuracy. Furthermore, suggested show promising controlling diseases. Overall, assist farmers identifying at an early stage provide appropriate suggestions pesticide selection, which reduce losses enhance productivity. Keywords: classification, detection,

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ژورنال

عنوان ژورنال: Indian Scientific Journal Of Research In Engineering And Management

سال: 2023

ISSN: ['2582-3930']

DOI: https://doi.org/10.55041/ijsrem18487