Soil and Organic Matter Content Identification Dataset

The current agricultural sector faces challenges of insufficient soil quality monitoring and difficulty in identifying organic matter content. Traditional soil testing methods are often time-consuming and costly, leading to inefficiencies in agricultural production. Existing solutions largely rely on manual testing and laboratory analysis, which are inefficient and yield inconsistent results. This dataset aims to enhance the efficiency of soil organic matter content detection through image recognition technology, meeting the needs of precision agriculture. The data collection process involves capturing images using high-resolution cameras in various soil environments, ensuring data diversity and representativeness. Data quality control includes multiple rounds of tagging, consistency checks, and expert reviews, ensuring the accuracy and consistency of annotations. Data is stored in JPEG format accompanied by structured JSON files, facilitating subsequent analysis and processing.