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Nutrient Management with Automated Leaf Color Level Assessment and Ambient Light Neutralizer using SVM Classifier

Abstract:

Philippine's agro-industrial economy is dependent on farming. One of the identified factors contributory to Inefficient Farming Practices is ineffective fertilizer application. The study developed an Automated Leaf Color Chart (LCC) assessment with the aid of Support Vector Machine classification algorithm, exploiting the built-in camera and high computing capability of the mobile device. An Ambient light neutralizer module was added in order for the mobile phone to be used in all lighting conditions. Results from the test of the study affirmed its functionality. The field tests showed no significant difference with regards to the ability of both assessment (Automated LCC Assessment vs. Manual LCC Assessment) in identifying the nutrient deficiencies of rice plants. Further validation with more samples from different rice fields could improve the performance of the classification algorithm and provide better nutrient management solutions.