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Characterisation of Position-Dependant Ripening Dynamics of Nectarines Using Near-Infrared Spectroscopy and ASCA

  • Identification data

    Identifier: imarina:9371404
    Authors:
    Ezenarro, JokinSchorn-Garcia, DanielPalou, AnnaMestres, MontserratAcena, LauraAbadias, MaribelAguilo-Aguayo, IngridBusto, OlgaBoque, Ricard
    Abstract:
    Nectarines, a popular pit fruit closely related to peaches, are renowned for their nutritional value and associated health benefits. However, challenges arise in maintaining optimal organoleptic properties during harvest and handling, eventually leading to production waste and heterogeneous quality in the fruit that arrives to the consumer. This study investigates the impact of nectarine position on trees during the whole ripening process using non-destructive near-infrared (NIR) spectroscopy. Nectarines exposed to more sunlight mature faster and this influences sugar content and acidity, emphasising the significance of considering height, prominence and orientation in ripening dynamics of the fruit. Different data unfolding strategies were compared, using ANOVA-Simultaneous Component Analysis (ASCA) to reveal the significance of in-tree position factors at different ripening stages, and observing high significance at harvest. This underscores the necessity for growers and handlers to consider these factors for reducing waste. NIR spectroscopy, with adequate data analysis, is a valuable tool for the holistic analysis of fruit ripening, providing crucial insights for maintaining optimal fruit organoleptic properties from harvest to consumer.
  • Others:

    e-ISSN: 1099-128X
    Project code: PID2019-104269RR-C33 and PID2019-104269RR-C31 / MICIU / AEI / 10.13039/501100011033
    Keywords: Variability sources Variability source Soluble solids concentration Precision agriculture Peach (prunus) Peach Harves Fruit-quality Design of experiments (doe) Anova-simultaneous component analysis (asca)
    Record's date: 2025-03-08
    Paper version: info:eu-repo/semantics/publishedVersion
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Paper original source: Journal Of Chemometrics. 38 (9): e3576-
    APA: Ezenarro, Jokin; Schorn-Garcia, Daniel; Palou, Anna; Mestres, Montserrat; Acena, Laura; Abadias, Maribel; Aguilo-Aguayo, Ingrid; Busto, Olga; Boque, R (2024). Characterisation of Position-Dependant Ripening Dynamics of Nectarines Using Near-Infrared Spectroscopy and ASCA. Journal Of Chemometrics, 38(9), e3576-. DOI: 10.1002/cem.3576
    Acronym: ALLFRUIT4ALL
    Publication Type: Journal Publications
    Project code 3: 2021PMF-BS-12
    Author, as appears in the article.: Ezenarro, Jokin; Schorn-Garcia, Daniel; Palou, Anna; Mestres, Montserrat; Acena, Laura; Abadias, Maribel; Aguilo-Aguayo, Ingrid; Busto, Olga; Boque, Ricard
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Aceña Muñoz, Laura / Boqué Martí, Ricard / Busto Busto, Olga / EZENARRO GARATE, JOKIN / Mestres Solé, Maria Montserrat / Schorn García, Daniel
    Abstract: Nectarines, a popular pit fruit closely related to peaches, are renowned for their nutritional value and associated health benefits. However, challenges arise in maintaining optimal organoleptic properties during harvest and handling, eventually leading to production waste and heterogeneous quality in the fruit that arrives to the consumer. This study investigates the impact of nectarine position on trees during the whole ripening process using non-destructive near-infrared (NIR) spectroscopy. Nectarines exposed to more sunlight mature faster and this influences sugar content and acidity, emphasising the significance of considering height, prominence and orientation in ripening dynamics of the fruit. Different data unfolding strategies were compared, using ANOVA-Simultaneous Component Analysis (ASCA) to reveal the significance of in-tree position factors at different ripening stages, and observing high significance at harvest. This underscores the necessity for growers and handlers to consider these factors for reducing waste. NIR spectroscopy, with adequate data analysis, is a valuable tool for the holistic analysis of fruit ripening, providing crucial insights for maintaining optimal fruit organoleptic properties from harvest to consumer.
    Thematic Areas: Statistics & probability Química Mathematics, interdisciplinary applications Matemática / probabilidade e estatística Interdisciplinar Instruments & instrumentation Engenharias iv Engenharias iii Engenharias ii Computer science, artificial intelligence Ciências agrárias i Ciência da computação Chemistry, analytical Biotecnología Biodiversidade Automation & control systems Astronomia / física Applied mathematics Analytical chemistry
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 0886-9383
    Author's mail: jokin.ezenarro@estudiants.urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat daniel.schorn@urv.cat montserrat.mestres@urv.cat ricard.boque@urv.cat olga.busto@urv.cat laura.acena@urv.cat
    Author identifier: 0000-0001-9234-7877 0000-0003-0997-2191 0000-0003-0997-2191 0000-0003-0997-2191 0000-0001-9805-3482 0000-0001-7311-4824 0000-0002-2318-6800 https://orcid.org/0000-0001-5942-9424 0000-0001-5942-9424
    Founding program action 3: Universitat Rovira i Virgili - Banco Santander
    Project code 2: 2020 FISDU 00221
    Founding program 2: Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya
    Funding program: Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema de I+D+i y de I+D+i Orientada a los Retos de la Sociedad. Proyectos de I+D+i Retos Investigación 2017-2020
    Founding program 3: Contratos de personal investigador predoctoral en formación
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2024
    Funding program action: Ciencias y tecnologías de alimentos
  • Keywords:

    Analytical Chemistry,Applied Mathematics,Automation & Control Systems,Chemistry, Analytical,Computer Science, Artificial Intelligence,Instruments & Instrumentation,Mathematics, Interdisciplinary Applications,Statistics & Probability
    Variability sources
    Variability source
    Soluble solids concentration
    Precision agriculture
    Peach (prunus)
    Peach
    Harves
    Fruit-quality
    Design of experiments (doe)
    Anova-simultaneous component analysis (asca)
    Statistics & probability
    Química
    Mathematics, interdisciplinary applications
    Matemática / probabilidade e estatística
    Interdisciplinar
    Instruments & instrumentation
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Computer science, artificial intelligence
    Ciências agrárias i
    Ciência da computação
    Chemistry, analytical
    Biotecnología
    Biodiversidade
    Automation & control systems
    Astronomia / física
    Applied mathematics
    Analytical chemistry
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