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…

MOVING FROM SULFITES TO BIOPROTECTION: WHICH IMPACT ON CHARDONNAY WINE?

Over the last few years, several tools have been developed to reduce the quantity of sulfites used during winemaking, including bioprotection. Although its effectiveness in preventing the development of spoilage microorganisms has been proven, few data are available on the impact of sulfite substitution by bioprotection on the final product. The objective of this study was therefore to characterize Chardonnay wines with the addition of sulfite or bioprotection in the pre-fermentation stage. The effects of both treatments on resulting matrices was evaluated at several scales: analysis of classical oenological parameters, antioxidant capacity, phenolic compounds, non-volatile metabolome and sensory profile.

Read More

Unveiling a hidden link: does time hold the key to altered spectral signatures of grapevines under drought?

Remote sensing technology captures spectral data beyond the visible range, making it useful for monitoring plant stress. Vis-NIR (Visible-Near Infrared) spectroscopy (400-1000 nm) is commonly used to indirectly assess plant status during drought. One example is the widespread use of normalized difference vegetation index (NDVI) that is strongly linked to green biomass. However, a knowledge gap exists regarding the applicability of this method to all the drought conditions and if it is a direct correlation to the water status of the plant.

Read More

Effect of ozone treatments in wine production of young and short-term aged white wines: destructive and non-destructive evaluation of main quality attributes

The main aim of WiSSaTech project (PRIN P2022LXY3A), supported by Italian Ministero dell’Università e della Ricerca and NextGenerationEU program, is to investigate eco-friendly and safe alternatives to sulphur dioxide (SO2) in wine production.

Read More

Optimizing disease management in the Rioja wine region: a study on Erisiphe necator and the Gubler-Thomas model

Erisiphe necator is endemic in the Rioja Appellation of Origin. Vine growers exert significant effort to protect their crops, given the economic losses this disease causes. Different studies have shown that using Gubler-Thomas Model (GTM) can reduce treatments by up to 20% compared to a full-time protection strategy. This reduction is achieved by optimizing applications based on temperature variations in late spring and summer when the disease’s conidial stage is active.

Read More

Which potential for Near Infrared Spectroscopy to characterize rootstock effects on grapevines?

Developing rootstocks adapted to environmental constraints constitutes a key lever for grapevine adaptation to climate change. In this context, Near Infrared Spectroscopy (NIRS) could be used as a high-throughput phenotyping technique to simplify the study of rootstocks in grafted situations. This study is an exploratory analysis to evaluate the potential of NIRS acquired on grafted tissues to reveal rootstock effects as well as the plasticity of combinations of scion/rootstock to better characterize these interactions.
Through the study of 25 combinations (5 scions times 5 rootstocks) in a dedicated experimental vineyard, we showed that NIRS obtained from grafted tissues capture rootstock and scion/rootstock interaction signals, up to 20% of the total variance at specific wavelengths.

Read More