Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Statistics
  • Help & Advice
University of Warwick

The Library

  • Login

Predicting organoleptic scores of sub-ppm flavour notes - Part 2. Computational analysis and results

Tools
- Tools
+ Tools

UNSPECIFIED (1998) Predicting organoleptic scores of sub-ppm flavour notes - Part 2. Computational analysis and results. ANALYST, 123 (10). pp. 2057-2066. ISSN 0003-2654

Full text not available from this repository.

Abstract

In Part 1 of this paper (T. C. Pearce and J. W. Gardner, Analyst, 1998, 123, 2047 we describe a novel method for predicting the organoleptic scores of complex odours using an array of non-specific chemosensors. The application of this method to characterising beer flavour is demonstrated here by way of predicting a single organoleptic score as defined under the joint EBC/ASBC/MBAA international flavour wheel for beer. An experimental study was designed to test the accuracy of the odour mapping technique for this prediction of organoleptic scores of added reference compounds within a chemically complex lager beer background. Using the flow injection analyser (FIA) system comprising 24 conducting polymer sensors, also described in Part 1, sampling was conducted on spiked lager beers. A dimethyl sulfide spike was added at the 20-80 ppb v/v level to simulate a range of organoleptic scores (0-5.5 out of 10) for flavour note no. 0730-"cooked vegetable". A certain amount of sensor drift was observed over the 12 d testing period which is shown to account for significant variance in the data-set as a whole. The effect of the sensor drift was reduced by applying a linear drift model, which may be generally applied when the between-class variance due to the difference in odours is small when compared with the within-class variance due to the drift, which increases approximately linearly over time. Careful use of this drift compensation model, coupled with judicious selection of pre-processing and pattern recognition techniques, maximised the between-class variance and so improved the overall classification performance of the system. After applying detailed exploratory data analysis, statistical, and neural classifier techniques, the organoleptic score was predicted with an accuracy of +/-1.4 tout of 10) and 95% confidence. Our results show that it is possible to generate subjectively defined organoleptic flavour information, using multi-sensor arrays and associated data-processing that is comparable in accuracy to sensory and GC-based techniques.

Item Type: Journal Article
Subjects: Q Science > QD Chemistry
Journal or Publication Title: ANALYST
Publisher: ROYAL SOC CHEMISTRY
ISSN: 0003-2654
Date: October 1998
Volume: 123
Number: 10
Number of Pages: 10
Page Range: pp. 2057-2066
Publication Status: Published
URI: http://wrap.warwick.ac.uk/id/eprint/15289

Data sourced from Thomson Reuters' Web of Knowledge

Request changes to a record

Actions (login required)

View Item View Item
twitter

Email us: publications@warwick.ac.uk
Contact Details
About Us