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ORCID: https://orcid.org/0000-0003-4473-3209, Barreiro Elorza, Pilar
ORCID: https://orcid.org/0000-0003-4702-6059, Ruiz-Altisent, Margarita
ORCID: https://orcid.org/0000-0002-6350-0315, Cubeddu, Rinaldo, Pifferi, Antonio, Taroni, Paola, Torricelli, Alessandro, Valentini, Gianluca, Johnson, David and Dover, Colin
(2005).
Mealiness detection in apples using time resolved reflectance spectroscopy.
"Journal of Texture Studies", v. 36
(n. 4);
pp. 439-458.
ISSN 1745-4603.
https://doi.org/10.1111/j.1745-4603.2005.00026.x.
| Título: | Mealiness detection in apples using time resolved reflectance spectroscopy |
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| Autor/es: |
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| Tipo de Documento: | Artículo |
| Título de Revista/Publicación: | Journal of Texture Studies |
| Fecha: | Agosto 2005 |
| ISSN: | 1745-4603 |
| Volumen: | 36 |
| Número: | 4 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Agrónomos (UPM) [antigua denominación] |
| Departamento: | Ingeniería Rural [hasta 2014] |
| Grupo Investigación UPM: | Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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Mealiness is a textural attribute related to internal fruit disorder that is characterized by the combination of abnormal softness of the fruit and absence of free juiciness in the mouth when eaten by the consumer. Time-resolved laser reflectance spectroscopy was used as a tool to determine mealiness. This new technique in agrofood research may provide physical and chemical information independently and simultaneously, which is relevant to characterize mealiness. Using visible and near infrared lasers as light sources, time-resolved laser reflectance spectroscopy was applied to Golden Delicious and Cox apples (n = 90), to characterize batches of untreated samples and samples that were stored under conditions that promote the development of mealiness (20C & 95% RH). The collected database was clustered into different groups according to their instrumental test values. The optical coefficients were used as explanatory variables to build discriminant functions for mealiness. The performance of the classification models created ranged from 47 to 100% of correctly identified mealy versus nonmealy apples.
| ID de Registro: | 6119 |
|---|---|
| Identificador DC: | https://oa.upm.es/6119/ |
| Identificador OAI: | oai:oa.upm.es:6119 |
| URL Portal Científico: | https://portalcientifico.upm.es/es/ipublic/item/5480987 |
| Identificador DOI: | 10.1111/j.1745-4603.2005.00026.x |
| URL Oficial: | http://onlinelibrary.wiley.com/doi/10.1111/j.1745-... |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 22 Feb 2011 10:44 |
| Ultima Modificación: | 08 May 2026 07:18 |
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