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.

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…

Grapevine sensitivity to fungal diseases: use of a combination of terroir cartography and parcel survey

In front of the economic interest and seeking to respect their environment, the wine growers move gradually towards a policy of reasoning their plant health protection. This is why, starting from epidemiologic studies on grapevine pathogens, forecasting models of the risks are developed by research and experimentation bodies.

Characterization of different clone candidates of xinomavro according to their phenolic composition

Context and purpose of the study ‐ The aim of this study is the examination of wines of 9 different clones of a Greek grape variety Xinomavro, (ΧE1, X19, X22, X28, ΧE2 X30, X31, X35, X36, X37), with regards to their phenolic and anthocyanin content and chemical composition.

Consumers’ emotional responses elicited by wines according to organoleptic quality

Wine is often described with emotional terms, such as surprising, disappointing or pleasant. However, very little has been done to really characterize this link between emotions and wine. Can it really bring emotions to wine tasters? Many studies have looked at the extrinsic factors that can improve the emotional

Riesling as a model to irrigate white wine grape varieties in arid climates

Regulated deficit irrigation (RDI) is a common viticultural practice for wine grape production. In addition to the potential improvement of water use efficiency, the adoption of this technique favors smaller canopies with higher levels of fruit sun exposure, enhancing quality attributes associated with red wine grapes such as smaller berries with higher tannins and anthocyanins. However, these quality attributes do not necessarily transfer to white wine grapes. The goal of this project was to assess whether partial rootzone drying (PRD) is more suited than RDI to grow high-end white wine grapes in arid climates, especially aromatic varieties, using Riesling as a model.

Evaluation of uhph treatment as an alternative to heat treatment prior to the use of proteolytic enzymes on must to achieve protein stability in wine

There are currently enzyme preparations on the market with specific protease activities capable of degrading unstable must proteins and preventing turbidity in white and rosé wines. The main drawback is the need to heat the must at 75ºc for 1-2 minutes to denature the proteins and facilitate enzyme action.