terclim by ICS banner
IVES 9 IVES Conference Series 9 NIR based sensometric approach for consumer preference evaluation

NIR based sensometric approach for consumer preference evaluation

Abstract

Climate change has had a global impact on grape production, and as a result, developing table grape varieties that can withstand climate-related threats has become a significant goal. However, it is equally important to ensure that these new grape varieties meet the preferences of consumers. To achieve this goal, a procedure has been developed that combines sensory analysis with spectroscopic data collected in the NIR region. Each sample was analyzed using both traditional analytical techniques and non-destructive NIR spectroscopy. The FT-NIR spectrophotometer used for this purpose is a TANGO (Bruker, Germany). The chemometric analyses were performed using the statistical software R version 4.1.2. The hedonic testing was performed using a 9-point hedonic scale which is the most widely used scale for measuring food acceptability. The NIR data sets were combined with the chemical, textural, and sensorial data to create multivariate models using interval partial least squares (iPLS) regressions or artificial neural networks (ANNs). The models produced in this way are applied to the spectra of samples that have undergone sensory analysis to predict their composition. This procedure enables non-destructive sensory analysis of new samples, as a single NIR spectrum is sufficient to quantify consumer appreciation and determine the chemical and physical characteristics of each berry. This information can then be used to identify the most suitable combinations for each target panel. Consumers could access this information via a QR code on the grape box, allowing them to select the perfect grape for their preferences.

Download the abstract

DOI:

Publication date: June 14, 2024

Issue: Open GPB 2024

Type: Poster

Authors

Teodora Basile1*, Lucia Rosaria Forleo1, Rocco Perniola1, Flavia Angela Maria Maggiolini1, Margherita D’Amico1, Carlo Bergamini1, Maria Francesca Cardone1

1 Research Centre for Viticulture and Enology, Council for Agricultural Research and Economics (CREA-VE), via Casamassima 148, 70010 Turi (BA), Italy

Contact the author*

Keywords

Vitis vinifera, NIR machine learning; prediction model, sensory analysis

Tags

IVES Conference Series | Open GPB | Open GPB 2024

Citation

Related articles…

LARGE-SCALE PHENOTYPIC SCREENING OF THE SPOILAGE YEAST BRETTANOMYCES BRUXELLENSIS: UNTANGLING PATTERNS OF ADAPTATION AND SELECTION, AND CONSEQUENCES FOR INNOVATIVE WINE TREATMENTS

Brettanomyces bruxellensis is considered as the main spoilage yeast in oenology. Its presence in red wine leads to off-flavour due to the production of volatile phenols such as 4-vinylphenol, 4-vinylguaiacol, 4-ethylphenol and 4-ethylguaiacol, whose aromatic notes are unpleasant (e.g. animal, leather, horse or pharmaceutical). Beside wine, B. bruxellensis is commonly isolated from beer, kombucha and bioethanol production, where its role can be described as negative or positive. Recent genomic studies unveiled the existence of various populations.

Read More

About validation of a method for the determination of volatile compounds in spirituous beverages using contained ethanol as a reference substance

The paper proposes an algorithm for validating a modified internal standard method using ethyl alcohol contained in the test sample as a reference substance.

Read More

Measurement of grape vine growth for model evaluation

Within a research project for simulating the nitrogen turnover in vineyard soils and the nitrogen uptake by the grape vine, a previously developed plant growth model (Nendel and Kersebaum 2004) had to be evaluated. A dataset was obtained from a monitoring experiment at three vineyard sites with different soil types, conducted in the years 2003 and 2004.

Read More

Evaluating South African Chenin blanc wine styles using an LC-MS screening method

Sorting Chenin blanc is one of the most important white wine cultivars in South Africa. It has received a lot of attention and accolades in the past years and more research than ever is dedicated to this versatile cultivar. According to the Chenin blanc association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded
(RRU), and Rich and Ripe Wooded (RRW). They are traditionally established with the aid of expert sensory evaluation, but the cost and the (subjective) human factor are aspects to be taken into account. A more objective and possibly robust way of assessing and attributing these styles can be the use of chemical analysis.

Read More

Screening of aroma metabolites within a set of 90 Saccharomyces strains

Currently, the main demand in the global wine market relies on products with unique flavour profiles, character, and typicity, and the metabolism of yeasts greatly influences the organoleptic properties of wines. Therefore, the natural diversity of Saccharomyces strains rises in interest over the last decade, but a large part of this phenotypic diversity remains unexplored

Read More