Bitter Gourd (Ampalaya) Leaf Dataset for NPK Deficiency Detection || Lipa City Philippines

This dataset contains leaf images of <b>bitter gourd (Ampalaya, </b><b><i>Momordica charantia L.</i></b><b>)</b> collected for the detection and classification of <b>soil nutrient deficiencies</b> using computer vision and deep learning techniques. The dataset was developed to support research on identifying <b>Nitrogen (N), Phosphorus (P), and Potassium (K) deficiencies</b> through visual symptoms observed on bitter gourd leaves.Images were obtained from two sources:<b>Internet-sourced images</b> gathered from publicly available agricultural and plant pathology resources.<b>Locally captured images</b> collected from bitter gourd plants under field conditions.All images were <b>validated by the Department of Agriculture Region IV-A</b> to ensure that the visual symptoms correspond to the correct nutrient deficiency classes.The dataset includes four classes:<b>Healthy</b> – leaves showing normal growth and coloration<b>Nitrogen (N) Deficiency</b> – characterized by yellowing leaves, reduced leaf size, and stunted growth<b>Phosphorus (P) Deficiency</b> – characterized by darkened leaves, deformation, and necrotic spots<b>Potassium (K) Deficiency</b> – characterized by scorched or burned leaf edges and marginal chlorosisThe dataset was designed for training and evaluating <b>machine learning and deep learning models</b>, particularly convolutional neural networks (CNNs), for automated nutrient deficiency detection in crops.<b>Dataset Composition</b>ClassFrom Internet From LocalTotalHealthy8072941,101Nitrogen (N) Deficiency1,0375181,555Phosphorus (P) Deficiency0506506Potassium (K) Deficiency5665161,082<b>Total</b><b>2,410</b><b>1,834</b><b>4,244</b><b>Total Images:</b> <b>4,244</b><b>Intended Use</b>This dataset is intended for:Plant disease and nutrient deficiency detection researchTraining and benchmarking <b>deep learning models</b> for agricultural applicationsComputer vision studies in <b>precision agriculture</b>Development of <b>AI-assisted crop monitoring systems</b>The dataset was used in research integrating <b>Convolutional Neural Networks (CNN)</b> and <b>IoT-based soil nutrient sensing</b> to support automated nutrient deficiency monitoring for bitter gourd cultivation.<b>Keywords:</b><br>Bitter gourd, Ampalaya, Momordica charantia, NPK deficiency, Nitrogen deficiency, Phosphorus deficiency, Potassium deficiency, Plant nutrient detection, Computer vision in agriculture, Deep learning dataset, Precision agriculture.