Phenolics and Tannin Assays for Practical Use in

Phenolics and Tannin Assays for Practical Use in Winemaking Giovanni Colantuoni John Thorngate Research and Development

Outline Introduction Ø Grape and Wine Phenolics Ø Measuring Phenolics Adams-Harbertson Assays Ø Gage R&R Analysis Ø Creating a Standardized SOP The UV-Vis Predictive Model Ø Chemometrics — Model Calibration and Deployment Ø Comparison to Skogerson-Downey-Boulton Ø 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tools, i. e. , current problems are attacked with methods which are inadequate and to that extent are already out of date.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? ØImportant for: ØColor ØTaste ØMouthfeel ØWine aging Research and Development

Introduction Why measure phenolics? ØIdentify higher quality lots more easily ØUse phenolic data for: ØPress decisions ØHeavy press additions ØBlend balancing ØEvaluation 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 Research and Development

Phenolic Acids Kennedy, 2008 Research and Development

Flavonoids Quercetin A. L. Waterhouse, Wine Phenolics, Annals of the New York Academy of Sciences 957: 21 -36, 2002 Research and Development

Anthocyanins Kennedy, 2008 Research and Development

Tannins Schofield et al. , Analysis of Condensed Tannins: A Review Animal Feed Science and Technology 91: 21 -40, 2001 Research and Development

Polymeric Pigments Kennedy, 2008 Research and Development

Phenolic Levels in Wine Waterhouse, 2002 Research and Development

Measuring Phenolics Total Phenolics Ø A 280 Ø Folin-Ciocalteu Tannins Ø Acid Butanolysis Ø Aldehyde Pigments Nota bene: unless you are chromatographically separating discrete compounds 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 A 280 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 SO 2; 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) Ø e. g. , A 520, A 420 and all their permutations Research and Development

Adams-Harbertson Assays Functional assays providing quantitative information on various phenolic classes Ø Total iron-reactive phenols Ø Analogous to Folin-Ciocalteu Ø Caveat: doesn’t measure monohydroxylated phenols or anthocyanins Ø Protein (BSA) precipitable tannins Ø Tetrameric tannins and larger Ø Polymeric pigments Ø Non-SO 2 bleachable pigmented fractions Ø Non-protein precipitable: small polymeric pigment Ø Protein precipitable: large polymeric pigment Ø Free Anthocyanins Research and Development

Adams-Harbertson Assays Benefits Ø Can run the analyses in-house IF you have a Visible spectrophotometer, a microcentrifuge, a vortexer and the necessary micropipettes Ø The IRP is a measure of total phenolics (minus anthocyanins) and doesn’t generate hazardous waste Ø The protein-precipitable tannin is highly correlated to perceptual astringency Research and Development

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

Running the A-H Assay Ø Sets of up to 24 samples Ø 4/5 segments, 9 sets of readings, ~ 3 hours Ø 5 results: anthocyanins, tannins, IRP, SPP, LPP Research and Development

Gage R & R OBJECTIVE: Quantify Measurement Error in Measurement Systems Ø Integral Part of SIX SIGMA Methodology Ø Quality Systems… Zero Defects… ISO Standards… Ø Goal: less than 3. 4 defects in a million opportunities Ø Early adapters: Motorola & Allied Signal (early 90’s) Ø General Electric Co. – most successful implementer Ø Two components Ø Standard Deviation of Measured Values Ø Assessment of Source of Variability Ø Contributors to Measurement Variation Ø Repeatability – Single Operator, Same Equipment Ø Reproducibility – Operators, Protocol, Equipment, … Research and Development

Gage R & R Study Conducted in April-June 2008 Ø Design of Experiments - DOE Ø 3 wineries, 5 wines, 4 technicians, 4 repetitions Ø full-factorial, randomized – 80 test results Ø Resulting Standard Deviations Ø (free-) Anthocyanins Ø SPP Ø LPP Ø Tannins Ø IRP 3. 02% 2. 01% 4. 86% 2. 79% 3. 78% Ø But… observed spikes of 7. 6, 11. 7, … 27. 5% Ø 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) Research and Development

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 Ø Sources of Adams-Harbertson Assay Protocol Ø Technical literature and journals Ø UC Davis Department of Viticulture & Enology website Ø Trade publications Ø Individual laboratory adaptations Ø In practice… a multitude of ways of running the Assay Ø Consequently, Ø Large variations in reported results Ø And even declarations of intrinsic invalidity Ø Moreover, Ø 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 Ø Initial documented procedure in place at Rubicon Estate Ø Set up with the assistance of Dr. Harbertson & Dr. Adams Ø Base documents from UC Davis Department of V & E website Ø Modifications introduced and validated over time Ø Salient results shared with Dr. Adams Ø Jointly with Dr. Thorngate determined need for SOP Ø Now working with the Gold Standard Group Ø Created draft for the “Modified A&H Assay SOP” Ø Currently being cast in ISO format Ø Review and finalization to follow Ø Gage R&R planned for mid-year 2010 Ø Expected SOP release date – Fall 2010 Ø 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 / Modeling Linear Curve-fitting A&H Assay Results – Predicted UV-Vis Spectrum anthocyanins MODEL * * * absorbance @ 520 nm Research and Development

UV-Vis Based A-H Assay Multivariate Modeling - Chemometrics Ø Openly-available, widely-used technology Ø Commercial software packages can be purchased Ø Implemented (and in use) in other process industries Ø Applications: lab, virtual sensors, process optimization Ø Expected Impact Ø Implemented locally in the winery laboratory Ø Once in place, no phenolics wet chemistry analyses Ø Essentially no sample preparation Ø Assay time of one-to-two minutes per sample Ø Ideal for real-time vinification decisions Research and Development

UV-Vis Based A-H Assay Ø Development Methodology laboratory analytical instrumentation (lab-based; HPLC, GC/MS, …) MEASURED VALUES MRSEC standardized measurements CALIBRATION SAMPLES (training and testing) process analytical instrumentation (at-line or in-line; UV/Vis, IR, …) model building & deployment (multivariate; PCR, PLS, ANN, … ) SAMPLE RESULTS SPECTRA PC / Notebook Research and Development

UV-Vis Based A-H Assay Ø Validation laboratory analytical instrumentation (lab-based; HPLC, GC/MS, …) MEASURED VALUES standardized measurements FIELD VALIDATION SAMPLES process analytical instrumentation (at-line or in-line; UV/Vis, IR, …) MRSEV or MRSEP model building & deployment (multivariate; PCR, PLS, ANN, … ) SAMPLE RESULTS SPECTRA PC / Notebook TEST SAMPLES Research and Development

UV-Vis Based A-H Assay Ø Deployment process analytical instrumentation (at-line or in-line; UV/Vis, IR, …) model building & deployment (multivariate; PCR, PLS, ANN, … ) SAMPLE RESULTS SPECTRA PC / Notebook TEST SAMPLES 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 Tanninsb Max 0 1419 0 1096 4979 19. 8 2272 0 IRPb Min 72. 6 Anthocyaninsa Max 2667 -8. 1 798 Prediction statistics for the Skogerson et al. (2007) model using our data RMSEP RPD CVpred Anthocyaninsa 466 0. 20 0. 5 105. 0 IRPb 909 0. 38 0. 8 63. 3 Tanninsb amg/L rpred 2 406 0. 33 1. 0 70. 3 malvidin-3 -glucoside equivalents bmg/L catechin equivalents 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 rpred 2 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 There is ample room for improvement! RMSEP: root mean square error of prediction rpred 2: coefficient of determination of the prediction RPD: ratio of standard deviation to standard error of prediction CVpred: coefficient of variation of the prediction amg/L bmg/L malvidin-3 -glucoside equivalents catechin equivalents Research and Development

Summary Ø Ø 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 Research and Development