Good and Bad classification of Amaranthus Leaf Red (Amaranthus cruentus) )

Published: 1 July 2024| Version 1 | DOI: 10.17632/vzx64zbkny.1
Contributors:
Chandan gope Braja gopal Gope, Tanmay Sarkar

Description

Data Description: Good and Bad Classification of Amaranthus Leaf (Amaranthus cruentus) This project involves a dataset aimed at classifying Amaranthus Leaf (Amaranthus cruentus) into "good" and "bad" categories. The dataset comprises a total of 1000 samples, evenly divided into 500 good samples and 500 bad samples. The classification is based on specific criteria related to the health and quality of the leaves. Dataset Overview Total Samples: 1000 Good Samples: 500 Bad Samples: 500 Data Attributes Each sample in the dataset consists of several attributes that provide detailed information about the characteristics and conditions of the Amaranthus leaves. These attributes include both visual and measurable properties that are crucial for determining the quality of the leaves. 1. Visual Attributes Color: A descriptor or numerical representation of the leaf color, indicating chlorophyll content and overall health. Texture: A qualitative or quantitative measure of the leaf surface, indicating smoothness or roughness. Shape: Geometric properties of the leaf, such as length, width, and edge irregularities. Damage Marks: Presence of any physical damage, such as holes, tears, or discoloration spots. Uniformity: Consistency in the appearance of the leaf surface, indicating uniform growth and health. 2. Measurable Attributes Leaf Area: The total surface area of the leaf, typically measured in square centimeters. Moisture Content: The percentage of water content within the leaf, indicating hydration levels. Nutrient Levels: Concentrations of essential nutrients, such as nitrogen, phosphorus, and potassium. Pest Damage: Indicators of pest infestation, such as bite marks or presence of pests. Disease Symptoms: Signs of disease, such as wilting, yellowing, or mold growth. Good vs. Bad Classification Criteria The classification of leaves into good and bad categories is based on a combination of the above attributes. Here are the general criteria used: Good Leaves Color: Vibrant green, indicating high chlorophyll content. Texture: Smooth and uniform texture without rough patches. Shape: Regular shape without significant deformities. Damage Marks: Minimal or no physical damage. Uniformity: High consistency in appearance. Leaf Area: Optimal size for the species. Moisture Content: Adequate hydration. Nutrient Levels: Balanced nutrient levels. Pest Damage: Little to no signs of pest damage. Disease Symptoms: No visible signs of disease. Bad Leaves Color: Pale, yellow, or brown, indicating low chlorophyll content. Texture: Rough or irregular texture. Shape: Deformed or irregular shape. Damage Marks: Visible physical damage, such as holes or tears. Uniformity: Inconsistent appearance. Leaf Area: Smaller or larger than the optimal size. Moisture Content: Low hydration levels. Nutrient Levels: Imbalanced nutrient levels. Pest Damage: Visible signs of pest damage.

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Biological Classification, Characterization of Food

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