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…

Deciphering grapevine trunk early molecular responses to P. minimum and P. chlamydospora in the presence of a commercial biocontrol agent (Trichoderma atroviride, Vintec®)

Esca, one of the main grapevine trunk diseases, is a complex and poorly understood disease. Phaeoacremonium minimum and Phaeomoniella chlamydospora, two of the main pathogens associated to this disease, are thought to be responsible for the first trunk infections. Little is known concerning grapevine trunk defenses during pathogen infection.

Read More

Effect of the addition of polysaccharides extracted for grape pomace and must on sensory and chemical composition of white wines

AIM: The objective of this work is to study the effect of the addition of polysaccharides extracted for grape pomace by-products and musts on sensory and chemical composition of white wines. Much of the waste obtained in the wine sector is not used, and they can have some valuable compounds, such as the polysaccharides (PS).

Read More

Evaluation of intra-vineyard spatial and temporal variability of leaf area index using multispectral images obtained by satellite (Landsat 8, Sentinel-2) and unmanned aerial vehicle platforms

Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information.

Read More

How climate change can modify the flavor of red Merlot and Cabernet-Sauvignon

he main goal of this research was to identify key aroma compounds linked with the maturity of grapes (ripe and overripe) and involved in grapes and wines with an intense dried fruits aroma. Odoriferous zones reminiscent of these aromas were detected by gas chromatography coupled with olfactometry (GC-O).

Read More

Decoupling the effects of water and heat stress on Sauvignon blanc berries

Climate changes have important consequences in viticulture, heat waves accompanied by periods of drought are encountered more and more frequently. This study aims to evaluate the single and combined effect of water deficit and high temperatures on the thiol precursors biosynthesis in Sauvignon blanc grapes. For this purpose, a protocol has been developed for the cultivation of berries on a solid substrate. The berries, collected at three different times starting from veraison and grown in vitro, were subjected to 4 different treatments: control (C), water stress (WS), heat stress (HS), combined water and heat stress (WSHS). Water stress was simulated by adding abscisic acid to the culture medium, while different temperatures, respectively 25°C and 35°C, were managed with two illuminated climatic chambers.

Read More