WAC 2022 banner
IVES 9 IVES Conference Series 9 WAC 9 WAC 2022 9 3 - WAC - Oral 9 Accurate Quantification of Quality Compounds and Varietal Classification from Grape Extracts using the Absorbance-Transmittance Fluorescence Excitation Emission Matrix (A-TEEM) Method and Machine Learning

Accurate Quantification of Quality Compounds and Varietal Classification from Grape Extracts using the Absorbance-Transmittance Fluorescence Excitation Emission Matrix (A-TEEM) Method and Machine Learning

Abstract

Rapid and accurate quantification of grape berry phenolics, anthocyanins and tannins, and identification of grape varieties are both important for effective quality control of harvesting and initial processing for wine making. Current reference technologies including High Performance Liquid Chromatography (HPLC) can be rate limiting and too complex and expensive for effective field operations. Secondary calibrated techniques including UV-VIS and Near and Mid Infrared spectroscopy are insensitive to specific quality compounds and unable to make accurate varietal assignments. In this paper we analyze robotically prepared grape extracts from several key varieties (n=Calibration/p=Prediction samples) including Cabernet sauvignon (64/10), Grenache (16/4), Malbec (14/4), Merlot (56/10), Petit syrah (52/10), Pinot noir (54/8), Syrah (20/2), Terlodego (14/2) and Zinfandel (62/12). Key phenolic and anthocyanin parameters measured by HPLC included Catechin, Epicatechin, Quercetin Glycosides, Malvidin 3-glucoside, Total Anthocyanins and Polymeric Tannins. Separate samples diluted 150 fold in 50% EtOH pH 2 were analyzed in parallel using the A-TEEM method following Multiblock Data Fusion of the absorbance and unfolded EEM data. A-TEEM chemical data were calibrated (n=390) using Extreme Gradient Boost (XGB) Regression and evaluated based on the Root Mean Square Error of the Prediction (RMSEP), the Relative Error of Prediction (REP%) and Coefficient of Variation (R2P) of the Prediction data (n=62). The regression results yielded an average REP% value of 6.0±2.4% and R2P of 0.941±0.024. While we consider the REP% values to be in the acceptable range at <10% we acknowledge that both the grape extraction method repeatability and HPLC reference method repeatability likely contributed the major sources of variation; e.g., A-TEEM sample REP%=1.31 for Polymeric Tannins. Varietal classification was analyzed using XGB discrimination analysis of the Multiblock data and evaluated based on the Prediction data. The classification results yielded 100% True Positive and True negative results for the Prediction Data for all varieties. We conclude that the A-TEEM method requires a minimum of sample preparation and rapid acquisition times (<1 min) and can serve as an accurate secondary method for both grape composition and varietal identification. Importantly, the application of the regression and classification models can be effectively automated for operators.

DOI:

Publication date: June 13, 2022

Issue: WAC 2022

Type: Article

Authors

Adam, Gilmore, Qiang, Sui

Presenting author

Adam, Gilmore – HORIBA Instruments Inc.

E & J Gallo Wines

Contact the author

Keywords

Extreme Gradient Boost – Phenolics – Anthocyanins- Tannins-Grape Variety

Tags

IVES Conference Series | WAC 2022

Citation

Related articles…

Red wine oxidation study by accelerating ageing tests and electrochemical method

Red wines can undergo many undesirable changes during the winemaking process and storage, particularly oxidative degradation due to numerous atmospheric oxygen intakes. This spoilage can impact organoleptic properties and color stabilization but this impact depends on the wine composition. Phenolic compounds constitute primary targets to oxidation reactions

Underpinning terroir with data: rethinking the zoning paradigm

Agriculture, natural resource management and the production and sale of products such as wine are increasingly data-driven activities. Thus, the use of remote and proximal crop and soil sensors to aid management decisions is becoming commonplace and ‘Agtech’ is proliferating commercially; mapping, underpinned by geographical information systems and complex methods of spatial analysis, is widely used. Likewise, the chemical and sensory analysis of wines draws on multivariate statistics; the efficient winery intake of grapes, subsequent production of wines and their delivery to markets relies on logistics; whilst the sales and marketing of wines is increasingly driven by artificial intelligence linked to the recorded purchasing behaviour of consumers. In brief, there is data everywhere!

Opinions will vary on whether these developments are a good thing. Those concerned with the ‘mystique’ of wine, or the historical aspects of terroir and its preservation, may find them confronting. In contrast, they offer an opportunity to those interested in the biophysical elements of terroir, and efforts aimed at better understanding how these impact on vineyard performance and the sensory attributes of resultant wines. At the previous Terroir Congress, we demonstrated the potential of analytical methods used at the within-vineyard scale in the development of Precision Viticulture, in contributing to a quantitative understanding of regional terroir. For this conference, we take this approach forward with examples from contrasting locations in both the northern and southern hemispheres. We show how, by focussing on the vineyards within winegrowing regions, as opposed to all of the land within those regions, we might move towards a more robust terroir zoning than one derived from a mixture of history, thematic mapping, heuristics and the whims of marketers. Aside from providing improved understanding by underpinning terroir with data, such methods should also promote improved management of the entire wine value chain.

A methyl salicylate glycoside mapping of monovarietal Italian white wines.

Among the main plant secondary metabolites, glycosides have a key-role in wine chemistry. Glycosides are non-volatile complex composed of a non-sugar component (aglycone) bound to one or more carbohydrates.

Monitoring gas-phase CO2 in the headspace of champagne glasses through diode laser spectrometry

During Champagne or sparkling wine tasting, gas-phase CO2 and volatile organic compounds invade the headspace above glasses [1], thus progressively modifying the chemical space perceived by the consumer. Gas-phase CO2 in excess can even cause a very unpleasant tingling sensation perturbing both ortho- and retronasal olfactory perception [2]. Monitoring as accurately as possible the level of gas-phase CO2 above glasses is therefore a challenge of importance aimed at better understanding the close relationship between the release of CO2 and a collection of various tasting parameters.

IMPACT OF NEW BIO STIMULANTS ON GRAPE SECONDARY METABOLITES UNDER CLIMATE CHANGE CONDITIONS

In a context of climate change and excessive use of agrochemical products, sustainable approaches for environmental and human health such as the use of bio stimulants in viticulture represent a potential option, against abiotic and biotic threats. Bio stimulants are organic compounds, microbes, or a combination of both, that stimulate plant’s vital processes, allowing high yields and good quality products. In vines, may trigger an innate immune response leading to the synthesis of secondary metabolites, key compounds for the organoleptic properties of grapes and wines.