Articles producció científica> Química Analítica i Química Orgànica

Detection of several common adulterants in raw milk by MID-infrared spectroscopy and one-class and multi-class multivariate strategies

  • Identification data

    Identifier: imarina:5130937
    Handle: http://hdl.handle.net/20.500.11797/imarina5130937
  • Authors:

    Gondim, Carina de Souza
    Junqueira, Roberto Goncalves
    Carvalho de Souza, Scheilla Vitorino
    Ruisanchez, Itziar
    Pilar Callao, M.
  • Others:

    Author, as appears in the article.: Gondim, Carina de Souza; Junqueira, Roberto Goncalves; Carvalho de Souza, Scheilla Vitorino; Ruisanchez, Itziar; Pilar Callao, M.;
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Callao Lasmarias, María Pilar / Ruisanchez Capelastegui, María Iciar
    Keywords: Sucrose (pubchem cid: 5988). One-class modelling Multivariate simca screening Multi-class modelling Milk adulteration Adulterant detection starch (pubchem cid: 24836924) sodium hypochlorite (pubchem cid: 23665760) sodium hydroxide (pubchem cid: 14798) sodium citrate (pubchem cid: 23666341) sodium chloride (pubchem cid: 5234) sodium carbonate (pubchem cid: 10340) sodium bicarbonate (pubchem cid: 516892) one-class modelling multivariate simca screening multi-class modelling milk adulteration hydrogen peroxide (pubchem cid: 784) formaldehyde (pubchem cid: 712) adulterant detection
    Abstract: A sequential strategy was proposed to detect adulterants in milk using a mid-infrared spectroscopy and soft independent modelling of class analogy technique. Models were set with low target levels of adulterations including formaldehyde (0.074 g.L¿1), hydrogen peroxide (21.0 g.L¿1), bicarbonate (4.0 g.L¿1), carbonate (4.0 g.L¿1), chloride (5.0 g.L¿1), citrate (6.5 g.L¿1), hydroxide (4.0 g.L¿1), hypochlorite (0.2 g.L¿1), starch (5.0 g.L¿1), sucrose (5.4 g.L¿1) and water (150 g.L¿1). In the first step, a one-class model was developed with unadulterated samples, providing 93.1% sensitivity. Four poorly assigned adulterants were discarded for the following step (multi-class modelling). Then, in the second step, a multi-class model, which considered unadulterated and formaldehyde-, hydrogen peroxide-, citrate-, hydroxide- and starch-adulterated samples was implemented, providing 82% correct classifications, 17% inconclusive classifications and 1% misclassifications. The proposed strategy was considered efficient as a screening approach since it would reduce the number of samples subjected to confirmatory analysis, time, costs and errors.
    Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Odontología Nutrition & dietetics Nutrição Medicine (miscellaneous) Medicina veterinaria Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências Food science & technology Food science Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação física Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, applied Biotecnología Biodiversidade Astronomia / física Analytical chemistry Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: itziar.ruisanchez@urv.cat mariapilar.callao@urv.cat
    Author identifier: 0000-0002-7097-3583 0000-0003-2691-329X
    Record's date: 2023-02-18
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/pii/S0308814617303874
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Food Chemistry. 230 68-75
    APA: Gondim, Carina de Souza; Junqueira, Roberto Goncalves; Carvalho de Souza, Scheilla Vitorino; Ruisanchez, Itziar; Pilar Callao, M.; (2017). Detection of several common adulterants in raw milk by MID-infrared spectroscopy and one-class and multi-class multivariate strategies. Food Chemistry, 230(), 68-75. DOI: 10.1016/j.foodchem.2017.03.022
    Article's DOI: 10.1016/j.foodchem.2017.03.022
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2017
    Publication Type: Journal Publications
  • Keywords:

    Analytical Chemistry,Chemistry, Applied,Food Science,Food Science & Technology,Medicine (Miscellaneous),Nutrition & Dietetics
    Sucrose (pubchem cid: 5988).
    One-class modelling
    Multivariate simca screening
    Multi-class modelling
    Milk adulteration
    Adulterant detection
    starch (pubchem cid: 24836924)
    sodium hypochlorite (pubchem cid: 23665760)
    sodium hydroxide (pubchem cid: 14798)
    sodium citrate (pubchem cid: 23666341)
    sodium chloride (pubchem cid: 5234)
    sodium carbonate (pubchem cid: 10340)
    sodium bicarbonate (pubchem cid: 516892)
    one-class modelling
    multivariate simca screening
    multi-class modelling
    milk adulteration
    hydrogen peroxide (pubchem cid: 784)
    formaldehyde (pubchem cid: 712)
    adulterant detection
    Zootecnia / recursos pesqueiros
    Saúde coletiva
    Química
    Odontología
    Nutrition & dietetics
    Nutrição
    Medicine (miscellaneous)
    Medicina veterinaria
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    Food science & technology
    Food science
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Enfermagem
    Educação física
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Chemistry, applied
    Biotecnología
    Biodiversidade
    Astronomia / física
    Analytical chemistry
    Administração pública e de empresas, ciências contábeis e turismo
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