Articles producció científica> Química Analítica i Química Orgànica

Multivariate Classification of Prunus Dulcis Varieties using Leaves of Nursery Plants and Near Infrared Spectroscopy

  • Identification data

    Identifier: imarina:6069421
    Authors:
    Borraz-Martinez, SergioSimo, JoanGras, AnnaMestre, MariangelaBoque, Ricard
    Abstract:
    The emergence of new almond tree (Prunus dulcis) varieties with agricultural interest is forcing the nursery plant industry to establish quality systems to keep varietal purity in the production stage. The aim of this study is to assess the capability of near-infrared spectroscopy (NIRS) to classify different Prunus dulcis varieties as an alternative to more expensive methods. Fresh and dried-powdered leaves of six different varieties of almond trees of commercial interest (Avijor, Guara, Isabelona, Marta, Pentacebas and Soleta) were used. The most important variables to discriminate between these varieties were studied through of three scientifically accepted indicators (Variable importance in projection, selectivity ratio and vector of the regression coefficients). The results showed that the 7000 to 4000 cm(-1) range contains the most useful variables, which allowed to decrease the complexity of the data set. Concerning to the classification models, a high percentage of correct classifications (90-100%) was obtained, where dried-powdered leaves showed better results than fresh leaves. However, the classification rate of both kinds of leaves evidences the capacity of the near-infrared spectroscopy to discriminate Prunus dulcis varieties. We demonstrate with these results the capability of the NIRS technology as a quality control tool in nursery plant industry.
  • Others:

    Author, as appears in the article.: Borraz-Martinez, Sergio; Simo, Joan; Gras, Anna; Mestre, Mariangela; Boque, Ricard;
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Boqué Martí, Ricard
    Keywords: Nir spectroscopy Geographical origin Discrimination Coffee
    Abstract: The emergence of new almond tree (Prunus dulcis) varieties with agricultural interest is forcing the nursery plant industry to establish quality systems to keep varietal purity in the production stage. The aim of this study is to assess the capability of near-infrared spectroscopy (NIRS) to classify different Prunus dulcis varieties as an alternative to more expensive methods. Fresh and dried-powdered leaves of six different varieties of almond trees of commercial interest (Avijor, Guara, Isabelona, Marta, Pentacebas and Soleta) were used. The most important variables to discriminate between these varieties were studied through of three scientifically accepted indicators (Variable importance in projection, selectivity ratio and vector of the regression coefficients). The results showed that the 7000 to 4000 cm(-1) range contains the most useful variables, which allowed to decrease the complexity of the data set. Concerning to the classification models, a high percentage of correct classifications (90-100%) was obtained, where dried-powdered leaves showed better results than fresh leaves. However, the classification rate of both kinds of leaves evidences the capacity of the near-infrared spectroscopy to discriminate Prunus dulcis varieties. We demonstrate with these results the capability of the NIRS technology as a quality control tool in nursery plant industry.
    Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Psicología Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Letras / linguística Interdisciplinar Geografía Geociências Farmacia Engenharias iv Engenharias iii Engenharias ii Enfermagem Educação física Educação Economia Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Biotecnología Biodiversidade Astronomia / física
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 20452322
    Author's mail: ricard.boque@urv.cat
    Author identifier: 0000-0001-7311-4824
    Record's date: 2023-02-22
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.nature.com/articles/s41598-019-56274-5
    Papper original source: Scientific Reports. 9 (19810): 19810-
    APA: Borraz-Martinez, Sergio; Simo, Joan; Gras, Anna; Mestre, Mariangela; Boque, Ricard; (2019). Multivariate Classification of Prunus Dulcis Varieties using Leaves of Nursery Plants and Near Infrared Spectroscopy. Scientific Reports, 9(19810), 19810-. DOI: 10.1038/s41598-019-56274-5
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1038/s41598-019-56274-5
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2019
    Publication Type: Journal Publications
  • Keywords:

    Multidisciplinary,Multidisciplinary Sciences
    Nir spectroscopy
    Geographical origin
    Discrimination
    Coffee
    Zootecnia / recursos pesqueiros
    Saúde coletiva
    Química
    Psicología
    Odontología
    Nutrição
    Multidisciplinary sciences
    Multidisciplinary
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Letras / linguística
    Interdisciplinar
    Geografía
    Geociências
    Farmacia
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Enfermagem
    Educação física
    Educação
    Economia
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
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