Raman spectroscopy and chemometric modeling to predict physical-chemical honey properties from Campeche, Mexico
Anguebes Franceschi, Francisco [autor] | Abatal, Mohamed [autor] | Pat Fernández, Lucio Alberto | Flores, Aaron [autor] | Córdova Quiroz, Atl Víctor [autor] | Ramírez Elías, Miguel Ángel [autor] | San Pedro, Liliana [autora] | May Tzuc, Oscar [auor] | Bassam, Ali [autor].
Tipo de material: Artículo en línea Tema(s): Miel de abejas | Espectroscopía de Raman | Propiedades físico química de la miel | Control de calidadTema(s) en inglés: Honey | Raman spectroscopy | Physical-chemical honey properties | Quality controlDescriptor(es) geográficos: Campeche (México) Nota de acceso: Acceso en línea sin restricciones En: Molecules. volumen 24, número 22, e-4091 (November 2019), páginas 1-18. --ISSN: 1420-3049Número de sistema: 60304Resumen:Tipo de ítem | Biblioteca actual | Colección | Signatura | Estado | Fecha de vencimiento | Código de barras |
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Artículos | Biblioteca Electrónica Recursos en línea (RE) | ECOSUR | Recurso digital | ECO400603047006 |
Acceso en línea sin restricciones
In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total acidity, electrical conductivity, Redox potential, hydroxymethylfurfural (HMF), and ash content. These proprieties were obtained according to the methods described by the Association of Official Analytical Chemists, Codex Alimentarius, and the International Honey Commission. For the construction of the chemometric models, 189 honey samples were collected and analyzed in triplicate using Raman spectroscopy to generate the matrix data [X], which were correlated with each of the physicochemical properties [Y]. The predictive capacity of each model was determined by cross validation and external validation, using the statistical parameters: standard error of calibration (SEC), standard error of prediction (SEP), coefficient of determination of cross-validation (R2 cal), coefficient of determination for external validation (R2 val), and Student's t-test. The statistical results indicated that the chemometric models satisfactorily predict the humidity, TSS, free acidity, lactonic acidity, total acidity, and Redox potential. However, the models for electric conductivity and pH presented an acceptable prediction capacity but not adequate to supply the conventional processes, while the models for predicting ash content and HMF were not satisfactory. The developed models represent a low-cost tool to analyze the quality of honey, and contribute significantly to increasing the honey distribution and subsequently the economy of the region. eng
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