Rapid Wine and Grape Chemistry and Classification Analysis Using Simultaneous Absorbance-Transmission and Fluorescence Excitation Emission Matrix (A-TEEM) Spectroscopy
Instructor: Adam Gilmore, HORIBA Instruments Inc.
Thursday, August 17, 2023 ◉ 1:00 pm to 3:00 pm EST
Cost: $250
Track: Food Science & Agriculture
Categories: Data Analysis/Statistics, Food Science/Agriculture, Molecular Spectroscopy, Quality/QA/QC
Course Level: Beginner
Course Description: Fast, precise and affordable analytical methods are vital for QC of grapes and wines to optimize growing conditions and timing for harvest as well as to meet targeted product quality specifications. The conventional chromatographic and wet chemistry methods are however, slow, expensive and complex. This course will introduce the patented Absorbance-Transmittance fluorescence Excitation Emission matrix (A-TEEM) spectroscopy using the HORIBA Aqualog® for rapid (< 1min) and precise wine chemistry analysis. The A-TEEM course will address many key quality-determining compounds including phenolics, anthocyanins and polymeric pigments as well as basic chemistry paramters including sulfites, total and volatile acids and pH as well as optical properties including Chomraticity, Hue and Intensity. Core topics of the course will include grape and wine sample preparation methods, the A-TEEM instrument theory and operation as well as key machine learning methods, including their automated application, for compound quantification and product classification and authentication.
There will be an introductory 60 min theory presentation including 30 min to cover the major wine quality determining compounds as well as regional, varietal and blending classification/authentication. Following this will be a 30 min introduction to the theory and operation of the A-TEEM and machine learning tools with select documented case studies of wine/grape chemistry and classification applications. The second section of the course will be a 90 min live demonstration incuding wine sample preparation and batch data acquisition This section will include examples of compound quantification and chemical and optical parameter evaluation from different wine varieties as well as an example of varietal classification and varietal blending quantification. The A-TEEM machine-learning based data analysis and automated reporting will be followed by a hands-on opportunity then final question and answer period.
Target Audience: Chemometricians, Contract Testing Lab Managers & Technicians, Food & Beverage Manufacturers, Food and Beverage Product Managers, Food Science & Agriculture Researchers, Oenologists, Quality Assurance, Quality Control, R&D scientists, Viticulturists, Winemakers
Learning Objectives:
1. Theory and operation of Simultaneous Absorbance-Transmittance fluorescence Excitation Emission Matrix (A-TEEM) spectroscopy and machine learning analysis.
2. Grape and wine quality compound chemistry and optical characteristics.
3. Sample preparation for grape berry extracts and finished wines.
4. Machine-learning methods and for analytical QA & QC of grapes and wine products including quality-marker compound concentrations, classifying wine varieties and and authenticating varietal blends.
I. Introductory Theory Section (60 min)
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A. Grape and Wine Chemistry
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1. Key Quality Determining Compounds
2. Basic Chemistry and Optical Characteristics
3. Effects of Chemistry and Optical Properties on Quality Characteristics
4. Varietal and Regional Effects on Grape Chemistry
B. A-TEEM Spectroscopy and Machine Learning Tools
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1. A-TEEM Optical Bench and Accessories for Batch Acquisition
2. Theory of A-TEEM Data and Analysis
3. Wine Sample Preparation for A-TEEM
4. Machine Learning Toolbox
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a) Regression: Concentrations and Values
b) Classification: Product ID and Condition
c) Calibration, Validation and Automating Application
II. A-TEEM Data Acquisition and Analysis Demonstration
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A. Wine Sample Preparation
B. Batch Acquisition: Different Wine Varieties
C. Complete Quality-Compound and Chemistry Profile
D. Batch Acquisition: Varietal Blends
E. Classification: Varietal Authentication
F. Regression: Blend Authentication
G. Hands-on
H. Questions and Answers
About the Instructor
Bio coming soon
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