Cauliflower Plant Health Image Dataset for Smart Agriculture Applications

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Authors: Phani Prasanthi Parvathaneni, unnam Koteswara rao
Cited by: 0

Abstract

Dataset Description: This dataset comprises RGB images of cauliflower plants collected under real field conditions for the purpose of plant health assessment and smart agriculture research. The images were acquired from a local agricultural field located in Penamaluru village, near Vijayawada, Andhra Pradesh, India. Data collection was carried out during daytime under natural lighting conditions using a high-resolution mobile phone camera, ensuring realistic environmental variability. The dataset is organized into two distinct classes: Healthy and Damaged. The Healthy class contains images of visually healthy cauliflower plants without observable symptoms of disease or stress. The Damaged class includes images of plants exhibiting visible signs of pest infestation, disease, discoloration, or physiological stress. All images were manually reviewed and labeled to ensure accurate class representation.

Fields of Study & Subjects

Smart Agriculture and AI Remote Sensing in Agriculture Industrial Vision Systems and Defect Detection

Publication details

Journal / source
Mendeley Data
Publication date
14 January 2026
Document type
Dataset