Assessing Impact of Nitrogen Deficiency on Paddy Field Yield Estimation: A Hierarchical Segmentation and SVM Approach

Abstract

In the agriculture sector, it's crucial to provide detailed explanations and methodically work towards predicting crop yields. This involves making informed decisions to enhance the quality of the analysis. Crop yield largely depends on the health of the crops, influenced significantly by key nutrients like nitrogen (N). A lack of nitrogen can lead to yellowish fields, potassium deficiency might result in leaf blotches, and phosphorus scarcity can turn fields brownish. Identifying these nutrient-deficient areas in paddy fields is a major challenge in estimating total yield. To address this, we use an efficient hierarchical model to segment these problem areas accurately. This approach has demonstrated impressive results in system accuracy.