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Phenolics and Tannin Assays for Practical Use in Winemaking Giovanni Colantuoni John Thorngate. Outline. Introduction Grape and Wine Phenolics Measuring Phenolics Adams-Harbertson Assays Gage R&R Analysis Creating a Standardized SOP The UV-Vis Predictive Model - PowerPoint PPT Presentation
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Research and Development
Phenolics and Tannin Assays for Practical Use in
Winemaking
Giovanni ColantuoniJohn Thorngate
Research and Development
Outline
Introduction Grape and Wine Phenolics Measuring Phenolics
Adams-Harbertson Assays Gage R&R Analysis Creating a Standardized SOP
The UV-Vis Predictive Model Chemometrics — Model Calibration and Deployment Comparison to Skogerson-Downey-Boulton Using the Model
Summary
Research and Development
Chemists interested in polyphenols, in common with the majority of scientists, tackle today’s problems with yesterday’s tools, i.e., current problems are attacked with methods which are inadequate and to that extent are already out of date.
The discovery and quick application of new methods or developments and extensions of existing methods is therefore of first importance.
B.R.Brown, In Methods of Polyphenol Chemistry, 1964
Research and Development
Introduction
Why focus on phenolics?
Important for:ColorTasteMouthfeelWine aging
Research and Development
Introduction
Why measure phenolics?
Identify higher quality lots more easily
Use phenolic data for:Press decisionsHeavy press additionsBlend balancingEvaluation of processing
Research and Development
Grape and Wine Phenolics
Phenolic compounds of interest to the winemaker:
Phenolic acids
Flavonoids
Anthocyanins
Tannins
Polymeric Pigment
J.A. Kennedy, Grape and wine phenolics: Observations and recent findings,Ciencia e Investigación Agraria 35:77-90, 2008
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Phenolic Acids
Kennedy, 2008
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Flavonoids
Quercetin
A.L. Waterhouse, Wine Phenolics, Annals of the New York Academy of Sciences 957:21-36, 2002
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Anthocyanins
Kennedy, 2008
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Tannins
Schofield et al., Analysis of Condensed Tannins: A ReviewAnimal Feed Science and Technology 91:21-40, 2001
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Polymeric Pigments
Kennedy, 2008
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Phenolic Levels in Wine
Waterhouse, 2002
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Measuring Phenolics
Total PhenolicsA280
Folin-Ciocalteu
TanninsAcid ButanolysisAldehyde
Pigments
Nota bene: unless you are chromatographically separating discretecompounds all measures of phenolics are methodologically defined
Research and Development
Total Phenolics
Absorbance at 280 nm
Pro’s: Simple; just requires UV-transparent cuvette and a UV-capable spectrophotometer (express as A280 in AU)
Con’s: Subject to interferences from other aromatic ring containing compounds (e.g., nucleotides, aromatic amino acids)
Nota bene. . .these are relatively small effects
Research and Development
Total Phenolics
Folin-Ciocalteu
Pro’s: Measures all mono- and dihydroxylated phenolics; automatable
Con’s: Subject to interferences from fructose and SO2; spent reagent has to be disposed of as hazardous waste
Research and Development
Tannins
Acid Butanolysis
Pro’s: Specific for tannins; anthocyanidin color measured with spectrophotometer (relative abundance)
Con’s: Low reaction yields; highly dependent upon reaction conditions and the tannin structure
Research and Development
Tannins
Aldehydes (Vanillin, DMCA*)
Pro’s: Measures flavan-3-ols and polymers (m-dihydroxy’s); color measured with spectrophotometer
Con’s: Rate and extent of color development solvent dependent; vanillin adduct absorbs at 500 nm (problematic for red wines)
*dimethylaminocinnamaldehyde
Research and Development
Pigments
Any number of spectrophotometric assays for pigments are available
These procedures have been extensively researched by Chris Somers in Australia (e.g., The Wine Spectrum, Winetitles: Marleston, SA, 1998)
e.g., A520, A420 and all their permutations
Research and Development
Adams-Harbertson Assays
Functional assays providing quantitative information on various phenolic classesTotal iron-reactive phenols
Analogous to Folin-CiocalteuCaveat: doesn’t measure monohydroxylated phenols
or anthocyaninsProtein (BSA) precipitable tannins
Tetrameric tannins and largerPolymeric pigments
Non-SO2 bleachable pigmented fractions Non-protein precipitable: small polymeric pigment Protein precipitable: large polymeric pigment
Free Anthocyanins
Research and Development
Adams-Harbertson Assays
BenefitsCan run the analyses in-house IF you have a
Visible spectrophotometer, a microcentrifuge, a vortexer and the necessary micropipettes
The IRP is a measure of total phenolics (minus anthocyanins) and doesn’t generate hazardous waste
The protein-precipitable tannin is highly correlated to perceptual astringency
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Tannin vs. Astringency
Kennedy et al., Analysis of Tannins in Red Wine Using Multiple Methods:Correlation with Perceived Astringency, AJEV 57:481-485, 2006
Research and Development
Sets of up to 24 samples
4/5 segments, 9 sets of readings, ~ 3 hours5 results: anthocyanins, tannins, IRP, SPP, LPP
Running the A-H Assay
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Gage R & R
OBJECTIVE: Quantify Measurement Error in Measurement Systems
Integral Part of SIX SIGMA MethodologyQuality Systems… Zero Defects… ISO Standards…Goal: less than 3.4 defects in a million opportunitiesEarly adapters: Motorola & Allied Signal (early 90’s)General Electric Co. – most successful implementer
Two componentsStandard Deviation of Measured ValuesAssessment of Source of Variability
Contributors to Measurement VariationRepeatability – Single Operator, Same EquipmentReproducibility – Operators, Protocol, Equipment,…
Research and Development
Gage R & R
Study Conducted in April-June 2008
Design of Experiments - DOE3 wineries, 5 wines, 4 technicians, 4 repetitionsfull-factorial, randomized – 80 test results
Resulting Standard Deviations(free-) Anthocyanins 3.02%SPP 2.01%LPP 4.86%Tannins 2.79% IRP 3.78%
But… observed spikes of 7.6, 11.7,… 27.5% ANOVA analysis needed – Used MINITAB
Research and Development
Gage R & R
Operator Contribution 3.3 %, # of Categories* 7
* Automotive Industry Action Group (AIAG) Measurement Systems Analysis (June 1998)
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Gage R & R
Operator Contribution 34.4 %, # of Categories* 1
* Automotive Industry Action Group (AIAG) Measurement Systems Analysis (June 1998)
Research and Development
Standard Procedure
The Assay Protocol – Essential KEY to Repeatability & Reproducibility
Sources of Adams-Harbertson Assay Protocol Technical literature and journals UC Davis Department of Viticulture & Enology website Trade publications Individual laboratory adaptations
In practice… a multitude of ways of running the Assay Consequently,
Large variations in reported results And even declarations of intrinsic invalidity
Moreover, A closer look at the assay reveals significant potential for
improving its repeatability and reducing time of execution
Research and Development
Standard Procedure
Road to the Adams-Harbertson Assay SOP
Initial documented procedure in place at Rubicon Estate Set up with the assistance of Dr. Harbertson & Dr. Adams Base documents from UC Davis Department of V & E website Modifications introduced and validated over time Salient results shared with Dr. Adams
Jointly with Dr. Thorngate determined need for SOP Now working with the Gold Standard Group
Created draft for the “Modified A&H Assay SOP” Currently being cast in ISO format Review and finalization to follow Gage R&R planned for mid-year 2010
Expected SOP release date – Fall 2010 Preliminary results indicate reduction in error “spikes”,
increased repeatability, and over 1/3 reduction in runtime
Research and Development
UV-Vis Spectroscopy
Early in Primary Fermentation
Research and Development
UV-Vis Spectroscopy
Later in Primary Fermentation
Research and Development
Calibration / ModelingCalibration / Modeling
Linear Curve-fitting
absorbance @ 520 nm
an
thocyan
ins *
*
*
*
**
A&H Assay Results – Predicted UV-Vis Spectrum
MODEL
Research and Development
UV-Vis Based A-H Assay
Multivariate Modeling - Chemometrics
Openly-available, widely-used technologyCommercial software packages can be purchased Implemented (and in use) in other process industriesApplications: lab, virtual sensors, process optimization
Expected Impact Implemented locally in the winery laboratoryOnce in place, no phenolics wet chemistry analysesEssentially no sample preparationAssay time of one-to-two minutes per sample Ideal for real-time vinification decisions
Research and Development
Development Methodology
UV-Vis Based A-H Assay
PC / Notebook
process analytical instrumentation
(at-line or in-line; UV/Vis, IR, …)
standardized measurements
SAMPLERESULTS
CALIBRATIONSAMPLES
(training and testing)
SPECTRA
MEASURED VALUES
laboratory analytical instrumentation
(lab-based; HPLC, GC/MS, …)
model building & deployment(multivariate; PCR, PLS, ANN,…
)
MRSEC
Research and Development
Validation
UV-Vis Based A-H Assay
PC / Notebook
standardized measurements
SAMPLERESULTS
MEASURED VALUES
model building & deployment(multivariate; PCR, PLS, ANN,…
)
SPECTRA
FIELDVALIDATION
SAMPLES
TEST SAMPLES
process analytical instrumentation
(at-line or in-line; UV/Vis, IR, …)
laboratory analytical instrumentation
(lab-based; HPLC, GC/MS, …)
MRSEVor
MRSEP
Research and Development
Deployment
UV-Vis Based A-H Assay
PC / Notebook
SAMPLERESULTS
model building & deployment(multivariate; PCR, PLS, ANN,…
)
SPECTRA
TEST SAMPLES
process analytical instrumentation
(at-line or in-line; UV/Vis, IR, …)
Research and Development
The Predictive Model (Ver. 4)
Research and Development
Model Comparisons
Data ranges of current data and Skogerson data
Current Skogerson et al. 2007
Min Max Min Max
Anthocyaninsa 0 1419 0 1096
IRPb 72.6 4979 19.8 2272
Tanninsb 0 2667 -8.1 798
amg/L malvidin-3-glucoside equivalentsbmg/L catechin equivalents
Prediction statistics for the Skogerson et al. (2007) model using our data
RMSEP rpred2 RPD CVpred
Anthocyaninsa 466 0.20 0.5 105.0
IRPb 909 0.38 0.8 63.3
Tanninsb 406 0.33 1.0 70.3
NOTE: Skogerson data was for Australian wines;Current data was for domestic wines.
Research and Development
That being said. . .
Validation statistics for the prediction of phenolic components (n=248)
RMSEP rpred2 RPD CVpred
Anthocyaninsa 149 0.53 1.4 33.0
IRPb 383 0.76 2.1 25.6
Tanninsb 203 0.78 2.1 33.8
amg/L malvidin-3-glucoside equivalentsbmg/L catechin equivalents
There is ample room for improvement!RMSEP: root mean square error of predictionrpred
2: coefficient of determination of the predictionRPD: ratio of standard deviation to standard error of predictionCVpred: coefficient of variation of the prediction
Research and Development
Summary
The Adams-Harbertson assays measure functional classes of phenolic compounds in wine
The Adams-Harbertson assays are repeatable and reproducible
The Adams-Harbertson assays SOP — a work in progress
The Predictive Model shows great promise — additional work is required
Research and Development
Acknowledgments
Dr. James Harbertson (Assoc. Prof.!) and his laboratory
Dr. Douglas Adams
Gold Standard
Jordan Ferrier
Dr. Roger Boulton, Dr. Mark Downey & Kirsten Skogerson
Tondi Bolkan, Evan Schiff, Karen Moneymaker
Research and Development
Acknowledgments