OENO IVAS 2019 banner
IVES 9 IVES Conference Series 9 OENO IVAS 9 OENO IVAS 2019 9 Analytical tools using electromagnetic spectroscopy techniques (IR, fluorescence, Raman) 9 Use of Fourier Transform Infrared Spectroscopy (FTIR) to rapidly verify the botanical authenticity of gum arabic

Use of Fourier Transform Infrared Spectroscopy (FTIR) to rapidly verify the botanical authenticity of gum arabic

Abstract

Gum arabic is composed of a polysaccharide rich in galactose and arabinose along with a small protein fraction [1, 2], which gives its stabilizing power with respect to the coloring substances or tartaric precipitation of bottled wine. It is a gummy exudation from Acacia trees; the products used in enology have two possible botanical origins, i.e. Acacia seyal and Acacia senegal, with different chemical-physical features and consequently different technological effects on wines. The aim of this work is to evaluate the feasibility of discrimination of commercial gums Arabic between their two different sources, on the basis of the absorption of the Fourier Transform Infrared (FT-IR) spectra of their aqueous solutions, in order to propose an extremely rapid and cost-saving method for quality control laboratories.

Forty five samples of commercial gum Arabic were collected on the Italian market of enological products and their botanical origin (Acacia seyal, N=30; Acacia senegal, N=15) were established by applying the reference method recommended by the International Organisation of Vine and Wine [1], based on the total nitrogen content and the rotatory power. After a dilution to obtain 5 % of dry matter aqueous solutions, FT-IR spectra of samples were acquired in the 926–5011 cm-1 range with a resolution of 3.8 cm-1, and a statistical approach was applied on the FT-IR spectra to verify the ability to distinguish gums Arabic from the two botanical origins. Standard Discriminant Analysis correctly classified all the samples, providing an optimal distinction between the 2 botanical origins on root 1. The robustness of the model was verified using an external validation. For this aim the entire dataset was divided into a ‘training’ dataset, 80 % of samples for the 2 categories, and a ‘validation’ dataset, the remaining 20 %. The model was built using the training dataset and then the validation samples were classified on it and this process was repeated 3 times. In all cases, 100 % of correct classification was obtained.

references:

[1] OIV-OENO 27-2000, Gum Arabic, COEI-1-GOMARA: 2000.
[2] Lopez-Torrez, L.; Nigen, M.; Williams, P.; Doco, T.; Sanchez, C., Food Hydrocolloids, 2015, 51, 41-53.

DOI:

Publication date: June 23, 2020

Issue: OENO IVAS 2019

Type: Article

Authors

Mario Malacarne, Laura Barp, Daniela Bertoldi, Tiziana Nardin, Roberto Larcher

Technology Transfer Center, Edmund Mach Foundation Via E.Mach, 1, San Michele all’Adige, Italy 

Contact the author

Keywords

gum arabic, FT-IR, botanical origin, authenticity 

Tags

IVES Conference Series | OENO IVAS 2019

Citation

Related articles…

What is the fate of oxygen consumed by red wine? Main processes and reaction products

Oxygen consumed by wine is used to oxidize sulfur dioxide and ethanol to form acetaldehyde wine oxygen consumption rate (OCR) was negatively correlated with the initial acetaldehyde level.

A vine physiology-based terroir study in the AOC-Lavaux region in Switzerland

Understanding how different pedoclimatic conditions interact with vine and berry physiology, and subsequently impact wine quality, is paramount for an good valorization of viticultural terroirs and can help to optimize mitigation strategies in the face of global warming

Combination of NIR multispectral information acquired from a ground moving vehicle with AI methods to assess the vine water status in a Tempranillo (Vitis vinifera L.) commercial vineyard

Increasing water scarcity and unpredictable rainfall patterns necessitate efficient water management in grape production. This study proposes a novel approach for monitoring grapevine water status in a commercial vertically-shoot-positioned Vitis vinifera L. Tempranillo vineyard using non-invasive spectroscopy with a battery of different AI methods to assess vineyard water status, that could drive precise irrigation. A contactless, miniature NIR spectrometer (900-1900 nm) mounted on a moving vehicle (3 Km/h) was employed to collect spectral data from the vines’ northeast side along six dates in season 2021.

Impact of sample size on yield estimation in commercial vineyards

The accurate estimation of yield is a fundamental for suitable viticulture, playing a pivotal role in the planning of logistics, the allocation of resources and the formulation of commercial strategies.

Image based vineyard yield prediction using empirical models to estimate bunch occlusion by leaves

Vineyard yield estimation brings several advantages to the entire wine industry. It can provide useful information to support decision making regarding bunch thinning practices, harvest logistics and marketing strategies, as well as to manage stored wine and cellar tanks allocation. Today, this estimation is performed mainly using manual methods based on destructive bunch sampling.