Articles producció científica> Química Analítica i Química Orgànica

ATR-MIR spectroscopy to predict commercial milk major components: A comparison between a handheld and a benchtop instrument

  • Identification data

    Identifier: imarina:6285540
    Authors:
    Gorla, GiuliaMestres, MontserratBoque, RicardRiu, JordiSpanu, DavideGiussani, Barbara
    Abstract:
    There is a growing need of measurement technologies that can be used close to the sample source and optical spectroscopy is an excellent example of this genre of technology: from the lab to the field. This study investigates the possibility to quantify the major components and to detect the presence or absence of lactose in commercial milks with ATR-MIR spectroscopy. We explored the possibility to use a portable and economical ATR-MIR instrument, comparing the results with a benchtop system. Commercial milk samples from Italy, Switzerland and Spain were chosen covering the maximum range of variation for protein, carbohydrate and fat content. The analytical protocol was optimized to make it as fast and useable as possible for both instruments, from the sample pretreatment to the instrumental parameters. Multivariate calibration was used to correlate the recorded spectra to the content of the major milk components, while a classification was done in order to classify samples with or without lactose. A comparison was performed between the predictive capabilities of the models built with different data pretreatments, different variable selection methods and different validation systems to obtain the best results and to assure robust models.
  • Others:

    Author, as appears in the article.: Gorla, Giulia; Mestres, Montserrat; Boque, Ricard; Riu, Jordi; Spanu, Davide; Giussani, Barbara;
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Boqué Martí, Ricard / Giussani, Barbara / Mestres Solé, Maria Montserrat / RIU RUSELL, MARC
    Project code: CTQ2016-77128-R
    Keywords: Proteins determination in milk Milk major constituents Milk Fatty acids determination in milk Carbohydrates determination in milk Atr-mir
    Abstract: There is a growing need of measurement technologies that can be used close to the sample source and optical spectroscopy is an excellent example of this genre of technology: from the lab to the field. This study investigates the possibility to quantify the major components and to detect the presence or absence of lactose in commercial milks with ATR-MIR spectroscopy. We explored the possibility to use a portable and economical ATR-MIR instrument, comparing the results with a benchtop system. Commercial milk samples from Italy, Switzerland and Spain were chosen covering the maximum range of variation for protein, carbohydrate and fat content. The analytical protocol was optimized to make it as fast and useable as possible for both instruments, from the sample pretreatment to the instrumental parameters. Multivariate calibration was used to correlate the recorded spectra to the content of the major milk components, while a classification was done in order to classify samples with or without lactose. A comparison was performed between the predictive capabilities of the models built with different data pretreatments, different variable selection methods and different validation systems to obtain the best results and to assure robust models.
    Thematic Areas: 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
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 01697439
    Author's mail: barbara.giussani@urv.cat ricard.boque@urv.cat montserrat.mestres@urv.cat
    Author identifier: 0000-0001-7311-4824 0000-0001-9805-3482
    Record's date: 2023-12-16
    Papper version: info:eu-repo/semantics/acceptedVersion
    Funding program: Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad (Agencia Estatal de Investigación - Ministerio de Economía, Industria y Competitividad)
    Papper original source: Chemometrics And Intelligent Laboratory Systems. 200 (103995):
    APA: Gorla, Giulia; Mestres, Montserrat; Boque, Ricard; Riu, Jordi; Spanu, Davide; Giussani, Barbara; (2020). ATR-MIR spectroscopy to predict commercial milk major components: A comparison between a handheld and a benchtop instrument. Chemometrics And Intelligent Laboratory Systems, 200(103995), -. DOI: 10.1016/j.chemolab.2020.103995
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Acronym: HOMESENS
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2020
    Funding program action: Proyecto de I+D
    Publication Type: Journal Publications
  • Keywords:

    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
    Proteins determination in milk
    Milk major constituents
    Milk
    Fatty acids determination in milk
    Carbohydrates determination in milk
    Atr-mir
    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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