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…

H-NMR metabolic profiling of wines from three cultivars, three soil types and two contrasting vintages

Differences in wine flavour proceed primarily from grape quality. Environmental factors determined by the climate, soil and training systems modify many grape and wine quality traits. Metabolic profiling based on proton nuclear magnetic resonance (1H-NMR) spectra has been proved to be useful to study multifactorial effects of the vine environment on intricate grape quality traits. The capacity of this method to discriminate the environmental effects on wine has to be demonstrated.

Optimized grape seed protein extraction for wine fining

The extraction of proteins from grape seeds represents a promising strategy to revalorize wine industry by-products. As a natural endogenous fining agent, grape seed protein (GSE) offers an effective solution for wine clarification [1] without requiring label declaration.

Pharmacological basis of the J-shaped curve in biological effects of wine

The classical pharmacological model assumes that the effect of a drug is proportional to the fraction of receptors occupied by the drug. In the simplest circumstances, the relationship between dose of a drug and response, when plotted on a logarithmic scale for drug concentration, is described by a sigmoidal curve. It presumes the existence of a threshold dose, below which no biological effect appears, and a maximal response in the form of a plateau, when a further increase in the dose of drug has no effect.

The Baco Blanc, the Armagnac hybrid variety adapted to the viticultural challenges of tomorrow

Today in the wine industry, a lot of alternatives are available for reducing phytosanitary inputs. Among these, prophylaxis, the use of biocontrol products and the deployment of pathogen-resistant vines are the most promising. eugenol (2-methoxy-4-(2-propenyl)-phenol), a molecule with recognised antifungal properties, can contribute to the last two alternatives. This molecule has been identified as an endogenous compound in the baco blanc hybrid variety used in armagnac pdo, which is at least tolerant to botrytis cinerea.

Revisiting the effect of subsurface irrigation and partial rootzone drying on canopy size and yield of Cabernet Sauvignon using remote sensing techniques

Irrigation is an essential tool for grape production, especially where rainfall does not meet the optimal water requirements needed to achieve yield and quality targets. Increased evaporative demand of grapevines due to changing climate conditions, and a growing awareness for sustainable farming, require the improvement of irrigation techniques to maximize water use efficiency, i.e. using less water to achieve the same yields or the same water but larger yields. In this study, the performance of Cabernet Sauvignon vines was compared under three irrigation techniques: conventional aboveground drip irrigation, subsurface irrigation installed directly under the vine row, and partial rootzone drying in which two subsurface lines were buried in the middle of the two interrow spacings on each side of the vine row with irrigation alternated between the two lines based on soil moisture content.