TRSRD

TRSRD integrates research on harmful substances in tea into a Neo4j knowledge graph to enable systematic analysis of relationships among tea risk substances and associated studies.

Key Features:

• Knowledge graph-based integration: Uses knowledge mapping techniques to construct a Neo4j graph database tailored for tea risk substance research.
• Extensive data repository: Contains 4189 nodes and 9400 correlations, including relations such as research category–PMID, risk substance category–PMID, and risk substance–PMID.
• Comprehensive substance coverage: Includes nine main types of tea risk substances: inclusion pollutants, heavy metals, pesticides, environmental pollutants, mycotoxins, microorganisms, radioactive isotopes, plant growth regulators, and other related substances.
• Diverse research categories: Categorizes publications into six types: reviews; safety evaluations/risk assessments; prevention and control measures; detection methods; residual/pollution situations; and data analysis/data measurement.

Scientific Applications:

• Risk Assessment: Supports comprehensive safety evaluations and hazard assessment associated with tea consumption.
• Prevention Strategies: Informs development of prevention and control measures to reduce contamination during tea production and processing.
• Detection Techniques: Supports analysis and comparison of detection methods for identifying risk substances in tea products.
• Standards Development: Provides evidence from residual pollution situations and measurement data to support establishment of safety standards.

Methodology:

Correlates research data via knowledge mapping techniques to construct a Neo4j graph database that captures relationships among tea risk substances, research categories, and PMIDs.