Strawberry Color Feature Analysis Dataset

The agricultural sector currently faces challenges in detecting the quality and maturity of fruits, especially in high-value crops like strawberries. Accurately assessing the maturity and quality of fruits is key to improving market competitiveness. However, existing manual detection methods are inefficient and highly subjective, often leading to inconsistent and inaccurate results. Therefore, this dataset aims to address technical issues related to color extraction and fruit maturity and quality correlation analysis in AI training by collecting samples of strawberries with different colors. Data collection is done using professional photographic equipment in a greenhouse with uniform lighting to ensure sample diversity and representativeness. Quality control measures include multiple rounds of annotation, consistency checks, and expert review to ensure data accuracy and reliability. Data is stored in JPG format and organized by image path for easy subsequent processing and analysis.