scholarly journals The Verification of the Usefulness of Electronic Nose Based on Ultra-Fast Gas Chromatography and Four Different Chemometric Methods for Rapid Analysis of Spirit Beverages

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Paulina Wiśniewska ◽  
Magdalena Śliwińska ◽  
Jacek Namieśnik ◽  
Waldemar Wardencki ◽  
Tomasz Dymerski
Keyword(s):  
Gas Chromatography ◽  
Data Analysis ◽  
Statistical Methods ◽  
Electronic Nose ◽  
Fast Gas Chromatography ◽  
Analysis Methods ◽  
Selection Of Variables ◽  
Fast Gc ◽  
Rapid Discrimination ◽  
Data Analysis Methods

Spirit beverages are a diverse group of foodstuffs. They are very often counterfeited which cause the appearance of low quality products or wrongly labelled products on the market. It is important to find a proper quality control and botanical origin method enabling the same time preliminary check of the composition of investigated samples, which was the main goal of this work. For this purpose, the usefulness of electronic nose based on ultra-fast gas chromatography (fast GC e-nose) was verified. A set of 24 samples of raw spirits, 33 samples of vodkas, and 8 samples of whisky were analysed by fast GC e-nose. Four data analysis methods were used. The PCA was applied for the visualization of dataset, observation of the variation inside groups of samples, and selection of variables for the other three statistical methods. The SQC method was utilized to compare the quality of the samples. Both the DFA and SIMCA data analysis methods were used for discrimination of vodka, whisky, and spirits samples. The fast GC e-nose combined with four statistical methods can be used for rapid discrimination of raw spirits, vodkas, and whisky and in the same for preliminary determination of the composition of investigated samples.

Data analysis methods for gas chromatography

2021 ◽  
pp. 525-546
Author(s):  
Karisa M. Pierce ◽  
Timothy J. Trinklein ◽  
Jeremy S. Nadeau ◽  
Robert E. Synovec
Keyword(s):  
Gas Chromatography ◽  
Data Analysis ◽  
Analysis Methods ◽  
Data Analysis Methods

scholarly journals Objective assessment of SERS thin films: comparison of silver on copper via galvanic displacement with commercially available fabricated substrates

2017 ◽  
Vol 9 (33) ◽  
pp. 4783-4789 ◽  
Author(s):  
Samuel Mabbott ◽  
Yun Xu ◽  
Royston Goodacre
Keyword(s):  
Thin Films ◽  
Data Analysis ◽  
Objective Assessment ◽  
Galvanic Displacement ◽  
Sers Signal ◽  
Analysis Methods ◽  
Data Analysis Methods

Reproducibility of SERS signal acquired from thin films developed in-house and commercially has been assessed using seven data analysis methods.

Omaha System Public Health Data: Analysis Methods

2010 ◽  
Vol 58 (2) ◽  
pp. e22-e23
Author(s):  
Karen A. Monsen ◽  
Karen S. Martin ◽  
Bonnie L Westra
Keyword(s):  
Public Health ◽  
Data Analysis ◽  
Health Data ◽  
Public Health Data ◽  
Analysis Methods ◽  
Omaha System ◽  
Data Analysis Methods

Peak detection in sediment - charcoal records: impacts of alternative data analysis methods on fire-history interpretations

2010 ◽  
Vol 19 (8) ◽  
pp. 996 ◽  
Author(s):  
Philip E. Higuera ◽  
Daniel G. Gavin ◽  
Patrick J. Bartlein ◽  
Douglas J. Hallett
Keyword(s):  
Data Analysis ◽  
Fire History ◽  
Threshold Value ◽  
Decomposition Methods ◽  
Peak Detection ◽  
Detection Methods ◽  
Statistical Framework ◽  
Analysis Methods ◽  
Decomposition Models ◽  
Data Analysis Methods

Over the past several decades, high-resolution sediment–charcoal records have been increasingly used to reconstruct local fire history. Data analysis methods usually involve a decomposition that detrends a charcoal series and then applies a threshold value to isolate individual peaks, which are interpreted as fire episodes. Despite the proliferation of these studies, methods have evolved largely in the absence of a thorough statistical framework. We describe eight alternative decomposition models (four detrending methods used with two threshold-determination methods) and evaluate their sensitivity to a set of known parameters integrated into simulated charcoal records. Results indicate that the combination of a globally defined threshold with specific detrending methods can produce strongly biased results, depending on whether or not variance in a charcoal record is stationary through time. These biases are largely eliminated by using a locally defined threshold, which adapts to changes in variability throughout a charcoal record. Applying the alternative decomposition methods on three previously published charcoal records largely supports our conclusions from simulated records. We also present a minimum-count test for empirical records, which reduces the likelihood of false positives when charcoal counts are low. We conclude by discussing how to evaluate when peak detection methods are warranted with a given sediment–charcoal record.

scholarly journals Weighing the Giants – I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images

2014 ◽  
Vol 439 (1) ◽  
pp. 2-27 ◽  
Author(s):  
Anja von der Linden ◽  
Mark T. Allen ◽  
Douglas E. Applegate ◽  
Patrick L. Kelly ◽  
Steven W. Allen ◽  
...  
Keyword(s):  
Data Analysis ◽  
Galaxy Clusters ◽  
Weak Lensing ◽  
Analysis Methods ◽  
Massive Galaxy ◽  
Data Analysis Methods

A Survey of FMRI Data Analysis Methods

2018 ◽  
Author(s):  
Anahid Ehtemami ◽  
Rollin Scott ◽  
Shonda Bernadin
Keyword(s):  
Data Analysis ◽  
Fmri Data ◽  
Analysis Methods ◽  
Fmri Data Analysis ◽  
Data Analysis Methods
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