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Publication
Multiresponse and multiobjective latent variable optimization of modern analytical instrumentation for the quantification of chemically related families of compounds: case study—Solid‐phase microextraction (SPME) applied to the quantification of analytes with impact on wine aroma
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Advisor(s)
Abstract(s)
The optimized operation of modern analytical instrumentation is a critical but
complex task. It involves the simultaneous consideration of a large number of
factors, both qualitative and quantitative, where multiple responses should be
quantified and several goals need to be adequately pondered, such as global
quantification performance, selectivity, and cost. Furthermore, the problem is
highly case specific, depending on the type of instrument, target analytes,
and media where they are dispersed. Therefore, an optimization procedure
should be conducted frequently, which implies that it should be efficient
(requiring a low number of experiments), as simple as possible (from experi mental design to data analysis) and informative (interpretable and conclusive).
The success of this task is fundamental for achieving the scientific goals and to
justify, in the long run, the high economic investments made and significant
costs of operation. In this article, we present a systematic optimization proce dure for the prevalent class of situations where multiple responses are available
regarding a family of chemical compounds (instead of a single analyte). This
class of problems conducts to responses exhibiting mutual correlations, for
which, furthermore, several goals need to be simultaneously considered. Our
approach explores the latent variable structure of the responses created by
the chemical affinities of the compounds under analysis and the orthogonality
of the interpretable extracted components to conduct their simultaneous opti mization with respect to different analysis goals. The proposed methodology
was applied to a real case study involving the quantification of a family of
analytes with impact on wine aroma.
Description
Keywords
Definitive screening designs Design of experiments HS‐SPME Latent variable modeling Optimizing analytical instrumentation Principal component analysis Wine production . Faculdade de Ciências da Vida Faculdade de Ciências Exatas e da Engenharia Escola Superior de Tecnologias e Gestão
Citation
Reis, M. S., Pereira, A. C., Leça, J. M., Rodrigues, P. M., & Marques, J. C. (2019). Multiresponse and multiobjective latent variable optimization of modern analytical instrumentation for the quantification of chemically related families of compounds: case study—solid‐phase microextraction (SPME) applied to the quantification of analytes with impact on wine aroma. Journal of Chemometrics, 33(3), e3103. DOI: 10.1002/cem.3103
Publisher
John Wiley and Sons