Papers
1
Total Citations
13
H-Index
1
About
Qiang Sui is a leading researcher in precision viticulture and chemometrics, whose work bridges analytical chemistry and machine learning to revolutionize grape and wine quality assessment. His primary research areas include spectroscopic fingerprinting, non-destructive food analysis, and the application of artificial intelligence to agricultural quality control. Sui’s most notable contribution is the development of the absorbance-transmittance fluorescence excitation emission matrix (A-TEEM) method, a rapid, accurate technique that simultaneously quantifies key phenolic compounds—such as anthocyanins and tannins—and classifies grape varieties without destructive sample preparation. This innovation addresses a critical bottleneck in winemaking, enabling real-time quality control during harvest and initial processing. His landmark 2022 paper on this method has already garnered 13 citations, reflecting its immediate impact on the field. By integrating machine learning with advanced spectroscopy, Sui has provided the industry with a powerful tool to replace slower, costlier reference technologies like HPLC. His work stands as a model for how data-driven approaches can enhance both the efficiency and precision of food and beverage production, making him a pivotal figure in modern oenological research.
Research Focus
Key Achievements
Top Papers
- 1