Morphological Dataset of Indian Mango Leaf Varieties (MIT-WPU Campus)

Mango Leaf Morphological Dataset (Version 1.0) 1. Project Overview and Site Context This dataset comprises a systematic morphological study of 16 different mango (Mangifera indica) cultivars. All samples were collected from the MIT World Peace University (MIT-WPU) Campus, Kothrud, Pune, Maharashtra, India ($18.5177^\circ\text{ N}, 73.8148^\circ\text{ E}$). The site is situated at an altitude of 560m in a tropical wet and dry climate zone, with soil composed primarily of weathered Deccan Trap basalt. 2. Sampling and Acquisition Sample Size: 160 independent leaf samples (10 leaves per tree across 16 trees). Selection Criteria: Mature, healthy leaves were selected from the middle of the tree canopy to ensure representative varietal characteristics. Standardisation: Leaves were photographed against a flat, neutral background to minimise parallax error and distortion. 3. Highlight: Biological Ground Reference and Calibration To achieve high metric accuracy without specialised laboratory equipment, this dataset utilises a Human Hand Ground Reference system: Calibration Protocol: Every image contains a human hand placed in the same focal plane as the leaf sample. Metric Standard: The average adult male palm width measured at 82–85 mm serves as the fixed calibration constant. Accuracy: By calculating the pixel-to-millimetre ratio based on the reference hand, the Length and Breadth measurements provided in the metadata are physically accurate representations of the leaf’s true scale. This methodology allows for the training of Computer Vision models for Real-World Size Estimation. 4. Morphological Parameters Recorded The accompanying CSV metadata includes the following botanically significant data points: Leaf Length (mm): From the petiole base to the tip of the apex. Leaf Breadth (mm): The maximum width of the leaf blade perpendicular to the midrib. Variety Identification: Cross-referenced with local agricultural experts and IBPGR descriptors. Visual Markers: Capture of specific traits including marginal undulation (waviness), apex shape (acute vs. acuminate), and venation angles. 5. Technical Validation for Researchers The dataset is intended for use in: Plant Phenotyping: Using morphological data to differentiate between similar cultivars (such as Alphonso vs. Kesar). Deep Learning: Training Convolutional Neural Networks (CNNs) for automated variety classification. Agricultural AI: Developing mobile-based tools for farmers to identify varieties in the field using relative scale (hand-reference).