Developed a Smooth Support Vector Machine to Predict the Crop Production in Alluvial Soil and Red Soil Regions of Tamil Nadu, India

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R. Tamilselvi, K. S. Mohanasathiya, S. Prasath


Crop production in Tamil Nadu, India, is influenced by various factors including soil type, climate, and agricultural practices. This study presents a comparative analysis of crop production in two prevalent soil types found in Tamil Nadu: alluvial soil and red soil. Alluvial soil, primarily located in river delta regions such as the Cauvery and Vaigai deltas, is known for its high fertility and good drainage properties, allowing it to be utilized for a variety of crops including rice, sugarcane, cotton, and various pulses and vegetables. On the other hand, red soil, predominant in central and western regions of Tamil Nadu, is less fertile but supports crops like millets, pulses, oilseeds, and certain fruits such as mangoes and guavas. Farmers in Tamil Nadu employ mixed cropping and crop rotation techniques to optimize the use of both soil types and enhance crop productivity. Soil type significantly impacts crop growth and yield, making it a critical factor in agricultural planning and management. By leveraging Smooth Support Vector Machine (SSVM), a powerful machine learning technique, this study aims to analyse historical crop yield data, soil properties, climate variables, and other relevant factors to identify patterns and relationships between crop production and soil types. The SSVM model will be trained and validated using datasets from both alluvial and red soil regions, enabling the classification and prediction of crop productivity in different soil types. Modern agricultural practices including soil testing, irrigation management, and the use of fertilizers and pesticides are also adopted to improve crop yields in both alluvial and red soil regions. Understanding the unique characteristics and suitability of each soil type is crucial for sustainable crop production and agricultural development in Tamil Nadu. The facts identifiedby this research will enhance comprehension of the comparative appropriateness of red and alluvial soils for various crops, providing valuable insights for agricultural decision-making and resource allocation in Tamil Nadu, India.

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