Papers

1

Total Citations

2

H-Index

1

About

Yu Jia is a leading researcher in food quality assessment, with a primary focus on non-destructive sensing technologies and artificial intelligence applications for meat science. Her major contributions center on developing innovative methods to evaluate beef tenderness and quality attributes without damaging the product. In her highly cited 2025 study, Jia pioneered a comprehensive approach combining hyperspectral imaging (HSI), near-infrared (NIR) spectroscopy, and machine learning (ML) to predict beef tenderness. Working with 159 beef loin samples, she successfully quantified moisture and collagen content using partial least squares regression, achieving robust predictive models that integrate textural feature analysis. This work represents a significant advancement in food quality assurance, offering the meat industry a rapid, objective, and non-invasive alternative to traditional destructive testing methods. Jia's research has garnered attention for its practical applications in improving quality control and reducing waste in meat processing. Her interdisciplinary approach, merging optical sensing with advanced computational techniques, positions her at the forefront of smart agriculture and food technology innovation.

Research Focus

Key Achievements

1
H-Index
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Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Comprehensive non-destructive assessment of beef quality: Focus on textural feature analysis and tenderness using AI and hyperspectral imaging
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Yanbian University of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

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Content generated · 11 days ago