Articles producció científica> Química Analítica i Química Orgànica

Development of new NIR-spectroscopy method combined with multivariate analysis for detection of adulteration in camel milk with goat milk

  • Datos identificativos

    Identificador: imarina:3654644
    Autores:
    Mabood F., Jabeen F., Ahmed M., Hussain J., Al Mashaykhi S.A.A., Al Rubaiey Z.M.A., Farooq S., Boqué R., Ali L., Hussain Z., Al-Harrasi A., Khan A.L., Naureen Z., Idrees M., Manzoor S.
    Resumen:
    New NIR spectroscopy combined with multivariate analysis for detection and quantification of camel milk adulteration with goat milk was investigated. Camel milk samples were collected from Aldhahira and Sharqia regions of Sultanate of Oman and were measured using NIR spectroscopy in absorption mode in the wavelength range from 700 to 2500 nm, at 2 cm−1 resolution and using a 0.2 mm path length CaF2 sealed cell. The multivariate methods like PCA, PLS-DA and PLS regression were used for interpretation of NIR spectral data. PLS-DA was used to detect the discrimination between the pure and adulterated milk samples. For PLSDA model the R-square value obtained was 0.974 with 0.08 RMSE. Furthermore, PLS regression model was used to quantify the levels of adulteration from, 0%, 2%, 5%, 10%, 15% and 20%. The PLS model showed the RMSEC = 1.10% with R2 = 94%. This method is simple, reproducible, having excellent sensitivity. The limit of detection was found 0.5%, while the limit of quantification was 2%.
  • Otros:

    Autor según el artículo: Mabood F., Jabeen F., Ahmed M., Hussain J., Al Mashaykhi S.A.A., Al Rubaiey Z.M.A., Farooq S., Boqué R., Ali L., Hussain Z., Al-Harrasi A., Khan A.L., Naureen Z., Idrees M., Manzoor S.
    Departamento: Química Analítica i Química Orgànica
    Autor/es de la URV: Boqué Martí, Ricard
    Palabras clave: Pls-da Pls regression Pca Nir-spectroscopy Multivariate analysis Food adulteration Espectroscopía nir Camel milk adulteration pls regression pca nir-spectroscopy camel milk adulteration
    Resumen: New NIR spectroscopy combined with multivariate analysis for detection and quantification of camel milk adulteration with goat milk was investigated. Camel milk samples were collected from Aldhahira and Sharqia regions of Sultanate of Oman and were measured using NIR spectroscopy in absorption mode in the wavelength range from 700 to 2500 nm, at 2 cm−1 resolution and using a 0.2 mm path length CaF2 sealed cell. The multivariate methods like PCA, PLS-DA and PLS regression were used for interpretation of NIR spectral data. PLS-DA was used to detect the discrimination between the pure and adulterated milk samples. For PLSDA model the R-square value obtained was 0.974 with 0.08 RMSE. Furthermore, PLS regression model was used to quantify the levels of adulteration from, 0%, 2%, 5%, 10%, 15% and 20%. The PLS model showed the RMSEC = 1.10% with R2 = 94%. This method is simple, reproducible, having excellent sensitivity. The limit of detection was found 0.5%, while the limit of quantification was 2%.
    Áreas temáticas: 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
    ISSN: 03088146
    Direcció de correo del autor: ricard.boque@urv.cat
    Identificador del autor: 0000-0001-7311-4824
    Página final: 750
    Fecha de alta del registro: 2024-09-07
    Volumen de revista: 221
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S0308814616319586
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Food Chemistry. 221 746-750
    Referencia de l'ítem segons les normes APA: Mabood F., Jabeen F., Ahmed M., Hussain J., Al Mashaykhi S.A.A., Al Rubaiey Z.M.A., Farooq S., Boqué R., Ali L., Hussain Z., Al-Harrasi A., Khan A.L., (2017). Development of new NIR-spectroscopy method combined with multivariate analysis for detection of adulteration in camel milk with goat milk. Food Chemistry, 221(), 746-750. DOI: 10.1016/j.foodchem.2016.11.109
    DOI del artículo: 10.1016/j.foodchem.2016.11.109
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2017
    Página inicial: 746
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Analytical Chemistry,Chemistry, Applied,Food Science,Food Science & Technology,Medicine (Miscellaneous),Nutrition & Dietetics
    Pls-da
    Pls regression
    Pca
    Nir-spectroscopy
    Multivariate analysis
    Food adulteration
    Espectroscopía nir
    Camel milk adulteration
    pls regression
    pca
    nir-spectroscopy
    camel milk adulteration
    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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