دورية أكاديمية

A Novel Methodology for Determining Effectiveness of Preprocessing Methods in Reducing Undesired Spectral Variability in Near Infrared Spectra

التفاصيل البيبلوغرافية
العنوان: A Novel Methodology for Determining Effectiveness of Preprocessing Methods in Reducing Undesired Spectral Variability in Near Infrared Spectra
المؤلفون: Buendia Garcia, Jhon, Gornay, Julien, Lacoue-Negre, Marion, Mas Garcia, Sílvia, Er-Rmyly, Jihane, Bendoula, Ryad, Roger, Jean-Michel
المساهمون: IFP Energies nouvelles (IFPEN), CHEMHOUSE RESEARCH GROUP MONTPELLIER FRA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Technologies et Méthodes pour les Agricultures de demain (UMR ITAP), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
المصدر: ISSN: 0967-0335.
بيانات النشر: HAL CCSD
NIR Publications
سنة النشر: 2022
مصطلحات موضوعية: Spectral variability, Hierarchical Clustering Analysis (HCA), Principal Components Analysis (PCA), Preprocessing effectiveness, outliers, Qresidual, Hotelling's T², reproducibility, repeatability, sample temperature, [CHIM]Chemical Sciences, [CHIM.ANAL]Chemical Sciences/Analytical chemistry
الوصف: International audience ; This study uses a novel analysis methodology based on the Hierarchical Clustering Analysis (HCA) to determine the effectiveness of different preprocessing methods in minimizing undesired spectral variability in near infrared spectroscopy due to both the consecutive and repetitive acquisition of the spectrum and the sample temperature. Nine preprocessing methods and different combinations of them were evaluated in four case studies: reproducibility, repeatability, sample temperature, and combination of the before mentioned cases. Eighty-four spectra acquired on seven different hydrocarbon samples from catalytic conversion processes have been selected as the real case study to illustrate the potential of the mentioned methodology. The approach proposed allows a more detailed discriminatory analysis compared to the classical methods for comparing the between-class and the within-class variances, such as the Wilks’ lambda criterion, and hence constitutes a powerful tool to determine adequate spectral preprocessing strategies. This study also proves the potential of the discrimination analysis methodology as a general scheme to identify atypical behaviors either in the spectrum acquisition or in the measured samples.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: hal-03685527; https://ifp.hal.science/hal-03685527Test; https://ifp.hal.science/hal-03685527/documentTest; https://ifp.hal.science/hal-03685527/file/A%20Novel%20Methodology%20for%20Determining%20Effectiveness%20of%20Preprocessing%20Methods%20in%20Reducing%20Undesired%20Spectral%20Variability%20in%20Near%20Infrared%20Spectra.pdfTest; WOS: 000759901600001
DOI: 10.1177/09670335211047959
الإتاحة: https://doi.org/10.1177/09670335211047959Test
https://ifp.hal.science/hal-03685527Test
https://ifp.hal.science/hal-03685527/documentTest
https://ifp.hal.science/hal-03685527/file/A%20Novel%20Methodology%20for%20Determining%20Effectiveness%20of%20Preprocessing%20Methods%20in%20Reducing%20Undesired%20Spectral%20Variability%20in%20Near%20Infrared%20Spectra.pdfTest
حقوق: info:eu-repo/semantics/OpenAccess
رقم الانضمام: edsbas.C50391E7
قاعدة البيانات: BASE