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OPLS methodology fo...
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Gabrielsson, JonUmeå universitet,Kemiska institutionen
(författare)
OPLS methodology for analysis of pre-processing effects on spectroscopic data
- Artikel/kapitelEngelska2006
Förlag, utgivningsår, omfång ...
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Elsevier BV,2006
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Nummerbeteckningar
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LIBRIS-ID:oai:DiVA.org:umu-12380
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https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-12380URI
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https://doi.org/10.1016/j.chemolab.2006.03.013DOI
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Språk:engelska
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Sammanfattning på:engelska
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Pre-processing of spectroscopic data is commonly applied to remove unwanted systematic variation. Possible loss of information and ambiguity regarding discarded variation are issues that complicate pre-treatment of data. In this paper, OPLS methodology is applied to evaluate different techniques for pre-processing of spectroscopic data gathered from a batch process. The objective is to present a rational scheme for analysis of pre-processing in order to understand the influence and effect of pre-treatment.O2PLS uses linear regression to divide the systematic variation in X and Y into three parts; one part with joint X–Y covariation, i.e. related to both X and Y, one part of X with Y-orthogonal variation and one part of Y with X-orthogonal variation.All of the investigated pre-treatment methods removed an additive baseline as expected. In the analysis of raw and differentiated data variation associated with the baseline was found in the Y-orthogonal part of X. Orthogonal information was also found in Y, which suggests that this pre-processing procedure not only removed variation. This would have been more difficult to detect without the O2PLS model since both raw and differentiated data must be analysed simultaneously.Development of a knowledge based strategy with OPLS methodology is an important step towards eliminating trial and error approaches to pre-processing.
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Biuppslag (personer, institutioner, konferenser, titlar ...)
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Jonsson, HansUmeå universitet,Kemiska institutionen
(författare)
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Airiaub, Christian
(författare)
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Schmidt, Bernd
(författare)
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Escott, Richard
(författare)
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Trygg, JohanUmeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)(Swepub:umu)jotr0001
(författare)
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Umeå universitetKemiska institutionen
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:Chemometrics and Intelligent Laboratory Systems: Elsevier BV84:1-2, s. 153-80169-7439
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