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Pre-processing Applied to Instrumental Data in Analytical Chemistry: A Brief Review of the Methods and Examples.
Dayananda, B; Owen, S; Kolobaric, A; Chapman, J; Cozzolino, D.
Afiliação
  • Dayananda B; School of Agriculture and Food Sciences, The University of Queensland, Brisbane, Queensland, Australia.
  • Owen S; School of Science, RMIT University, Melbourne, Victoria, Australia.
  • Kolobaric A; School of Science, RMIT University, Melbourne, Victoria, Australia.
  • Chapman J; School of Science, RMIT University, Melbourne, Victoria, Australia.
  • Cozzolino D; Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane, Queensland, Australia.
Crit Rev Anal Chem ; : 1-9, 2023 Apr 13.
Article em En | MEDLINE | ID: mdl-37053040
ABSTRACT
The field of analytical chemistry has been significantly advanced by the availability of state-of-the-art instrumentation, allowing for the development of novel applications in this field. However, in many cases, the direct interpretation of the recorded data is often not straightforward, hence some level of pre-processing is required (e.g., baseline correction, derivatives, normalization, smoothing). These techniques have become a critical first step for the successful analysis of the data recorded, and it is recommended to use them before the application of chemometrics (e.g., classification, calibration development). The aim of this paper is to provide with an overview of the most used pre-processing methods applied to instrumental analytical methods (e.g., spectroscopy, chromatography). Examples of their application in near infrared and UV-VIS spectroscopy as well as in gas chromatography will be also discussed. Overall, this paper provides with a comprehensive understanding of pre-processing techniques in analytical chemistry, highlighting their importance during the analysis and interpretation of data, as well as during the development of accurate and reliable chemometric models.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article