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Author Spotlight: Understanding Riverine Nitrogen Impacts and Primary Productivity for Effective Nutrient Management

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Perspective: A Comprehensive Evaluation of Data Quality in Nutrient Databases.

Zhaoping Li¹, Shavawn Forester², Emily Jennings-Dobbs²

¹Center for Human Nutrition, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States.

Advances in Nutrition (Bethesda, Md.)

|February 27, 2023

Summary

This summary is machine-generated.

Current nutrient databases lack completeness and FAIRness (findable, accessible, interoperable, reusable) for precision nutrition (PN) research. Improving data quality and adhering to data science principles are crucial for advancing nutritional science and PN applications.

Keywords:

anthropometrics data quality essential nutrients food composition data human nutrition nutrient data omics personalized dietary recommendations phytonutrients precision nutrition

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Area of Science:

Nutrition science
Data science
Bioinformatics

Background:

Nutrient databases are foundational for nutrition science and precision nutrition (PN) research.
Existing databases face challenges in data quality, specifically completeness and FAIRness (findable, accessible, interoperable, reusable).

Conclusions:

Current food and nutrient databases are not comprehensively complete or FAIR.
Incorporating data science principles, focusing on data quality and FAIRness, is essential to improve foundational nutrient databases for PN research and applications.