Articles producció científica> Enginyeria Química

Water stress assessment on grapevines by using classification and regression trees

  • Datos identificativos

    Identificador: imarina:9244717
  • Autores:

    Sanchez-Ortiz, Antoni
    Mateo-Sanz, Josep M.
    Nadal, Montserrat
    Lampreave, Miriam
  • Otros:

    Autor según el artículo: Sanchez-Ortiz, Antoni; Mateo-Sanz, Josep M.; Nadal, Montserrat; Lampreave, Miriam;
    Departamento: Enginyeria Química
    Autor/es de la URV: Lampreave Figueras, Míriam / Mateo Sanz, Josep Maria / NADAL ROQUET-JALMAR, MONTSERRAT / Sánchez Ortiz, Antoni
    Palabras clave: Wine Water stress Transport Leaf hydraulics Isohydric Expression Classification and regression trees Carignan Berry development Aquaporins Anthocyanins Anisohydric Accumulation Abscisic-acid Aba
    Resumen: Multiple factors, such as the vineyard environment and winemaking practices, are known to affect the development of vines as well as the final composition of grapes. Water stress promotes the synthesis of phenols and is associated with grape quality as long as it does not inhibit production. To identify the key parameters for managing water stress and grape quality, multivariate statistical analysis is essential. Classification and regression trees are methods for constructing prediction models from data, especially when data are complex and when constructing a single global model is difficult and models are challenging to interpret. The models were obtained by recursively partitioning the data space and fitting a simple prediction model within each partition. The partitioning can be represented graphically as a decision tree. This approach permitted the most decisive variables for predicting the most vulnerable vineyards and wine quality parameters associated with water stress. In Priorat AOC, Carignan grapevines had the highest water potential and abscisic acid concentration in the early growth plant stages and permitted vineyards to be classified by mesoclimate. This information is useful for identifying which measurements could most easily differentiate between early and late-ripening vineyards. LWP and T-s during an early physiological stage (pea size) permitted warm and cold areas to be differentiated.
    Áreas temáticas: Plant sciences Plant science Ecology, evolution, behavior and systematics Ecology Biochemistry, genetics and molecular biology (miscellaneous)
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: miriam.lampreave@urv.cat josepmaria.mateo@urv.cat josepmaria.mateo@urv.cat
    Identificador del autor: 0000-0002-6352-9863 0000-0002-6352-9863
    Fecha de alta del registro: 2024-07-20
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://onlinelibrary.wiley.com/doi/10.1002/pld3.319
    URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Plant Direct. 5 (4): e00319-
    Referencia de l'ítem segons les normes APA: Sanchez-Ortiz, Antoni; Mateo-Sanz, Josep M.; Nadal, Montserrat; Lampreave, Miriam; (2021). Water stress assessment on grapevines by using classification and regression trees. Plant Direct, 5(4), e00319-. DOI: 10.1002/pld3.319
    DOI del artículo: 10.1002/pld3.319
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Biochemistry, Genetics and Molecular Biology (Miscellaneous),Ecology,Ecology, Evolution, Behavior and Systematics,Plant Science,Plant Sciences
    Wine
    Water stress
    Transport
    Leaf hydraulics
    Isohydric
    Expression
    Classification and regression trees
    Carignan
    Berry development
    Aquaporins
    Anthocyanins
    Anisohydric
    Accumulation
    Abscisic-acid
    Aba
    Plant sciences
    Plant science
    Ecology, evolution, behavior and systematics
    Ecology
    Biochemistry, genetics and molecular biology (miscellaneous)
  • Documentos:

  • Cerca a google

    Search to google scholar