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Assessing wine sensory attributes using Vis/NIR

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Abstract

The quality of wine involves the presence and intensity of many flavors and nuances. The assessment by tasting panels of the sensory quality of wine and by measuring the intensity of their attributes or defects is more difficult than assessing the global score of wine quality, which is a single value for each wine. This research focused on the feasibility of the visible and near-infrared spectroscopy for assessing wine sensory attributes. Predictive models of sensory attributes such as positive and negative for red and white wines have been developed, based on their spectra and reference values from a specialized tasting panel. The results indicate that the technique is feasible for predicting some of the most characteristic sensory attributes of red and white wines such as Flavor intensity, Astringency, Color intensity, Length, Persistency, Pleasantness and Balance. Their correlation coefficients of validations were about 0.9 in most cases. The technique was also suitable for predicting some important defects such as Oxidation, Unclean, Ethyl acetate and Acetic acid. The main potential use of this technique is for contrasting or confirming the assessment of wine for the positive and negative sensory attributes, determined by the sensory analysis of tasting panels. This can be particularly useful in cases where there is discrepancy in the assessments of a sensory panel. It is reasonable to consider the possibility of tuning the technique for detection in routine analysis of some negative attributes.

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Abbreviations

CSIC:

Spanish Council for Scientific Research

IFAPA:

Institute Research and Training Agricultural and Fisheries

MN:

Mean normalization

NIRS:

Near-infrared spectroscopy

PC:

Principal components

R C :

Coefficient of calibration

r :

Correlation coefficient between the analyzed and predicted values in the external validation exercises

R CV :

Coefficient of cross-validation

RPD:

Residual predictive deviation

SD:

Standard deviation

SEC:

Standard error of calibration

SEP:

Standard error of performance

Vis/NIR:

Visible and near infrared

Vis/NIRS:

Visible and near-infrared spectroscopy

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Author information

Authors and Affiliations

  1. CSIC-IG, Fisilogía y Tecnología de Productos Vegetales, Seville, Spain

    José Antonio Cayuela

  2. Instituto de Investigación y Formación Agraria y Pesquera (IFAPA) Rancho de la Merced, Ctra Trebujena, km 2.1, 11471, Jerez de la Frontera, Spain

    Belén Puertas & Emma Cantos-Villar

Authors
  1. José Antonio Cayuela
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  2. Belén Puertas
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  3. Emma Cantos-Villar
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Correspondence to José Antonio Cayuela.

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Cayuela, J.A., Puertas, B. & Cantos-Villar, E. Assessing wine sensory attributes using Vis/NIR. Eur Food Res Technol 243, 941–953 (2017). https://doi.org/10.1007/s00217-016-2807-9

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  • DOI: https://doi.org/10.1007/s00217-016-2807-9

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