Document Detail


Recognition of the bouquet of Chinese spirits by artificial neural network analysis.
MedLine Citation:
PMID:  11601479     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Forty-six samples of Chinese spirits, whose bouquets were determined by sensory evaluations, and 17 compounds characteristic of the flavors determined by gas chromatography/gas chromatography-mass spectrometry (GC/GC-MS), were subjected to neural network analysis and their corresponding factor scores developed. To make the bouquet recognition more efficient, an improved artificial back-propagation neural network (BPNN) was applied. In each kind of data, the BPNN was trained repeatedly until the error rate was less than the predetermined threshold error; then the trained network was applied to the test set that was not involved in the training process to establish the validity of the network, and a correct prediction rate of 100% was obtained. The BPNN provided a correlation between the data offered from sensory evaluations and the data of chemical compositions determined by instrumental analysis. The BPNN approach is feasible regardless of whether the crude data or the factor scores are used; however, recognition results were better with the latter than with the former. In a comparison of all the results obtained by BPNN, cluster analysis, and discriminant analysis, the method of artificial neural network analysis appeared to be the optimal technique for recognizing the bouquet of Chinese spirits.
Authors:
H Chen; Z Yu; G Zhu
Related Documents :
18925629 - Evaluation of different internal-diameter column combinations in comprehensive two-dime...
10048199 - On-line coupling of immunoaffinity-based solid-phase extraction and gas chromatography ...
11358249 - Chemical derivatization of amino acids for in situ analysis of martian samples by gas c...
2503529 - Rapid analysis of sorbitol, galactitol, mannitol and myoinositol mixtures from biologic...
16525879 - (z)-7-tricosene and monounsaturated ketones as sex pheromone components of the australi...
18272439 - Validation of a gas chromatography-mass spectrometry method for the analysis of sterol ...
25799 - Rapid assays of urinary estriol in pregnant women.
18193409 - Mspd procedure for determining buprofezin, tetradifon, vinclozolin, and bifenthrin resi...
10211189 - Occurrence of aflatoxins b1, b2, g1, and g2 in peanuts and their products marketed in t...
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of AOAC International     Volume:  84     ISSN:  1060-3271     ISO Abbreviation:  J AOAC Int     Publication Date:    2001 Sep-Oct
Date Detail:
Created Date:  2001-10-16     Completed Date:  2002-03-05     Revised Date:  2008-03-17    
Medline Journal Info:
Nlm Unique ID:  9215446     Medline TA:  J AOAC Int     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1579-85     Citation Subset:  IM    
Affiliation:
Renmin University of China, Department of Commodity Science, Beijing, People's Republic of China.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Alcoholic Beverages / analysis*
China
Data Interpretation, Statistical
Fuzzy Logic
Neural Networks (Computer)*
Pattern Recognition, Automated
Taste

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Estimation of measurement uncertainty in pesticide residue analysis.
Next Document:  Enzyme immunoassay of staphylococcal enterotoxins in dairy products with cleanup and concentration b...