Articles producció científica> Química Analítica i Química Orgànica

ProSpecTool: A MATLAB toolbox for spectral preprocessing selection

  • Datos identificativos

    Identificador: imarina:9364440
    Autores:
    Ezenarro, J.Schorn-García, D.Busto, O.Boqué, R.
    Resumen:
    This paper introduces the ProSpecTool, a MATLAB toolbox for automated selection of preprocessing methods for obtaining optimal PLS regression models in vibrational spectroscopy. Trial-and-error approaches for preprocessing can be time-consuming, and the success of the process relies on the experience of analysts. The ProSpecTool addresses this challenge by using objective criteria analogous to expert judgment to filter and iterate preprocessing methods based on raw data properties. The toolbox quantifies noise, identifies multiplicative and additive scatter-effects, and selects preprocessing algorithms to correct them. Results demonstrate that the ProSpecTool can produce models that resemble those proposed by experienced analysts based on trial-and-error in terms of performance and robustness, making it a valuable exploratory tool for vibrational spectroscopy practitioners.
  • Otros:

    Código de proyecto: PID2019-104269RR-C33 / MCIN / AEI / 10.13039/501100011033
    Palabras clave: Uv–visible Raman Partial least squares regression (plsr) Near-infrared (nir) Mid-infrared (mir) Automatic
    Fecha de alta del registro: 2024-11-16
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Chemometrics And Intelligent Laboratory Systems. 247 105096-
    Referencia de l'ítem segons les normes APA: Ezenarro, J.; Schorn-García, D.; Busto, O.; Boqué, R. (2024). ProSpecTool: A MATLAB toolbox for spectral preprocessing selection. Chemometrics And Intelligent Laboratory Systems, 247(), 105096-. DOI: 10.1016/j.chemolab.2024.105096
    Acrónimo: ALLFRUIT4ALL
    Tipo de publicación: Journal Publications
    Código de projecto 3: 2021PMF-BS-12
    Autor según el artículo: Ezenarro, J.; Schorn-García, D.; Busto, O.; Boqué, R.
    Departamento: Química Analítica i Química Orgànica
    Autor/es de la URV: Boqué Martí, Ricard / Busto Busto, Olga / EZENARRO GARATE, JOKIN / Schorn García, Daniel
    Resumen: This paper introduces the ProSpecTool, a MATLAB toolbox for automated selection of preprocessing methods for obtaining optimal PLS regression models in vibrational spectroscopy. Trial-and-error approaches for preprocessing can be time-consuming, and the success of the process relies on the experience of analysts. The ProSpecTool addresses this challenge by using objective criteria analogous to expert judgment to filter and iterate preprocessing methods based on raw data properties. The toolbox quantifies noise, identifies multiplicative and additive scatter-effects, and selects preprocessing algorithms to correct them. Results demonstrate that the ProSpecTool can produce models that resemble those proposed by experienced analysts based on trial-and-error in terms of performance and robustness, making it a valuable exploratory tool for vibrational spectroscopy practitioners.
    Acción del programa de financiación 2: Departament de Recerca i Universitats, Generalitat de Catalunya
    Áreas temáticas: Statistics & probability Spectroscopy Software Robotics & automatic control Química Process chemistry and technology Mathematics, interdisciplinary applications Matemática / probabilidade e estatística Interdisciplinar Instruments & instrumentation Farmacia Engenharias iv Engenharias iii Engenharias ii Computer science, artificial intelligence Computer science applications Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, analytical Biotecnología Automation & control systems Analytical chemistry
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: jokin.ezenarro@urv.cat jokin.ezenarro@urv.cat daniel.schorn@alumni.urv.cat daniel.schorn@alumni.urv.cat ricard.boque@urv.cat olga.busto@urv.cat
    Identificador del autor: 0000-0001-9234-7877 0000-0001-9234-7877 0000-0003-0997-2191 0000-0003-0997-2191 0000-0001-7311-4824 0000-0002-2318-6800
    Acción del programa de financiació 3: Universitat Rovira i Virgili - Banco Santander
    Codigo del proyecto 2: ref.2021 SGR 00705
    Programa de financiación 2: Chemometrics and Sensorics for Analytical Solutions (CHEMOSENS)
    Programa de financiación: Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i y de I+D+i Orientada a los Retos de la Sociedad. Proyectos de I+D+i Retos Investigación 2017-2020
    Programa de financiación 3: Contratos de personal investigador predoctoral en formación
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2024
    Acción del progama de financiación: Action of the financing program Ciencias y tecnologías de alimentos
  • Palabras clave:

    Analytical Chemistry,Automation & Control Systems,Chemistry, Analytical,Computer Science Applications,Computer Science, Artificial Intelligence,Instruments & Instrumentation,Mathematics, Interdisciplinary Applications,Process Chemistry and Technology,Robotics & Automatic Control,Software,Spectroscopy,Statistics & Probability
    Uv–visible
    Raman
    Partial least squares regression (plsr)
    Near-infrared (nir)
    Mid-infrared (mir)
    Automatic
    Statistics & probability
    Spectroscopy
    Software
    Robotics & automatic control
    Química
    Process chemistry and technology
    Mathematics, interdisciplinary applications
    Matemática / probabilidade e estatística
    Interdisciplinar
    Instruments & instrumentation
    Farmacia
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Computer science, artificial intelligence
    Computer science applications
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Chemistry, analytical
    Biotecnología
    Automation & control systems
    Analytical chemistry
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