Literature DB >> 18389223

Relationship between wine scores and visible-near-infrared spectra of Australian red wines.

D Cozzolino1, G Cowey, K A Lattey, P Godden, W U Cynkar, R G Dambergs, L Janik, M Gishen.   

Abstract

Sensory analysis of wine involves the measurement, interpretation and understanding of human responses to the properties perceived by the senses such as sight, smell and taste. The sensory evaluation of wine is often carried out by wine judges, winemakers and technical staff, and allows characterization of the quality of the wine. However, this method is lengthy, expensive, and its results depend on panel training and the specific vocabulary used by the panel. A robust, rapid, unbiased and inexpensive method to assist in quality assessment purposes will therefore be beneficial for the modern wine industry. This study aims to investigate the relationship between sensory analysis, visible (VIS) and near-infrared (NIR) spectroscopy to assess sensory properties of commercial Australian wine varieties. For the purposes of this study 118 red wine samples (Cabernet Sauvignon, Shiraz, Pinot Noir, Tempranillo, Nebbiolo and blends) graded by a panel of experienced tasters and scored according to the Australian wine show system were scanned in transmission in the VIS and NIR range (400-2,500 nm). Partial least squares regression models were developed between the overall score given by the judges and the combined VIS-NIR spectra, using full cross validation (leave-one-out method). The results showed that NIR spectroscopy was able to predict wine quality scores in red wine samples (R = 0.61 and standard error of prediction of 0.81). The practical implication of this study is that instrumental methods such as VIS-NIR spectroscopy can be used to complement sensory analysis and can facilitate the task at early stages of product development, making high-throughput screening of novel products feasible or maintaining the consistency of the product.

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Year:  2008        PMID: 18389223     DOI: 10.1007/s00216-008-2071-3

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  1 in total

1.  An efficient method to reduce grain angle influence on NIR spectra for predicting extractives content from heartwood stem cores of Toona. sinensis.

Authors:  Yanjie Li; Xin Dong; Yang Sun; Jun Liu; Jingmin Jiang
Journal:  Plant Methods       Date:  2020-06-01       Impact factor: 4.993

  1 in total

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