Articles producció científica> Química Analítica i Química Orgànica

Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy

  • Dades identificatives

    Identificador: imarina:5695833
    Autors:
    Sergio Borraz-Martínez, Ricard Boqué, Joan Simó, Mariàngela Mestre, Anna Gras
    Resum:
    Near-infrared spectroscopy (NIRS) can be a faster and more economical alternative to traditional methods for screening varietal mixtures of nursery plants during the propagation process to ensure varietal purity and to avoid errors in the dispatch batches. The global objective of this work was to develop and optimize a NIR spectral collection method for construction of robust multivariate discrimination models. Three different varieties of Prunus dulcis (Avijor, Guara, and Pentacebas) of agricultural interest were used for this study. Sources of variation were investigated, including the position of the leaves on the trees, differences among trees of the same variety, and differences at the varietal level. Three types of processed samples were investigated. Fresh leaves, dried leaves, and dried leaves in powder form were included in each analysis. A study of spectral pre-treatment methods was also performed, and multivariate methods were applied to analyze the influence of different factors on classification. These included principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and ANOVA simultaneous component analysis (ASCA). The results indicated that variety was the most important factor for classification. The spectral pre-treatment that provided the best results was a combination of standard normal variate (SNV), Savitzky-Golay first derivative, and mean-centering methods. With regard to the type of processed sample, the highest percentages of correct classifications were obtained with fresh and dried powdered leaves at both the training set and test set validation levels. This study represents the first step towards the consolidation of NIRS as a method to identify Prunus dulcis varieties.Copyright © 2019 Elsevier B.V. All rights
  • Altres:

    Autor segons l'article: Sergio Borraz-Martínez, Ricard Boqué, Joan Simó, Mariàngela Mestre, Anna Gras
    Departament: Química Analítica i Química Orgànica
    Autor/s de la URV: Boqué Martí, Ricard
    Paraules clau: Varietal purity Reflectance spectroscopy Pls-da Optimization Nir Leaf analysis Discrimination Component analysis Asca Almond trees pls-da optimization nir leaf analysis almond trees
    Resum: Near-infrared spectroscopy (NIRS) can be a faster and more economical alternative to traditional methods for screening varietal mixtures of nursery plants during the propagation process to ensure varietal purity and to avoid errors in the dispatch batches. The global objective of this work was to develop and optimize a NIR spectral collection method for construction of robust multivariate discrimination models. Three different varieties of Prunus dulcis (Avijor, Guara, and Pentacebas) of agricultural interest were used for this study. Sources of variation were investigated, including the position of the leaves on the trees, differences among trees of the same variety, and differences at the varietal level. Three types of processed samples were investigated. Fresh leaves, dried leaves, and dried leaves in powder form were included in each analysis. A study of spectral pre-treatment methods was also performed, and multivariate methods were applied to analyze the influence of different factors on classification. These included principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and ANOVA simultaneous component analysis (ASCA). The results indicated that variety was the most important factor for classification. The spectral pre-treatment that provided the best results was a combination of standard normal variate (SNV), Savitzky-Golay first derivative, and mean-centering methods. With regard to the type of processed sample, the highest percentages of correct classifications were obtained with fresh and dried powdered leaves at both the training set and test set validation levels. This study represents the first step towards the consolidation of NIRS as a method to identify Prunus dulcis varieties.Copyright © 2019 Elsevier B.V. All rights reserved.
    Àrees temàtiques: Zootecnia / recursos pesqueiros Spectroscopy Saúde coletiva Química Nutrição Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Interdisciplinar Geociências General medicine General chemistry Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Chemistry, analytical Chemistry (miscellaneous) Biotecnología Biodiversidade Biochemistry Astronomia / física Analytical chemistry Administração pública e de empresas, ciências contábeis e turismo
    ISSN: 00399140
    Adreça de correu electrònic de l'autor: ricard.boque@urv.cat
    Identificador de l'autor: 0000-0001-7311-4824
    Pàgina final: 328
    Data d'alta del registre: 2023-02-22
    Volum de revista: 204
    Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
    Referència a l'article segons font original: Talanta. 204 320-328
    Referència de l'ítem segons les normes APA: Sergio Borraz-Martínez, Ricard Boqué, Joan Simó, Mariàngela Mestre, Anna Gras (2019). Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy. Talanta, 204(), 320-328. DOI: 10.1016/j.talanta.2019.05.105
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2019
    Pàgina inicial: 320
    Tipus de publicació: Journal Publications
  • Paraules clau:

    Analytical Chemistry,Biochemistry,Chemistry (Miscellaneous),Chemistry, Analytical,Spectroscopy
    Varietal purity
    Reflectance spectroscopy
    Pls-da
    Optimization
    Nir
    Leaf analysis
    Discrimination
    Component analysis
    Asca
    Almond trees
    pls-da
    optimization
    nir
    leaf analysis
    almond trees
    Zootecnia / recursos pesqueiros
    Spectroscopy
    Saúde coletiva
    Química
    Nutrição
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Interdisciplinar
    Geociências
    General medicine
    General chemistry
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Chemistry, analytical
    Chemistry (miscellaneous)
    Biotecnología
    Biodiversidade
    Biochemistry
    Astronomia / física
    Analytical chemistry
    Administração pública e de empresas, ciências contábeis e turismo
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