Revisión bibliográfica del análisis sensorial de mieles monoflorales españolas
[EN] Sensory analysis is a useful analytical technique to classify monofloral honeys (orange blossom, rosemary, thyme, etc.) since it allows defining their organoleptic profile. To do this, it is necessary to identify and quantify the sensory attributes that characterize them and build specific orga...
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| Formato: | tesis de maestría |
| Fecha de publicación: | 2020 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | español |
| OAI Identifier: | oai:riunet.upv.es:10251/151578 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/151578 |
| Access Level: | acceso abierto |
| Palavra-chave: | Miel monofloral Evaluación sensorial Propiedades sensoriales Monofloral honey Sensory evaluation Sensory properties TECNOLOGIA DE ALIMENTOS Máster Universitario en Ciencia e Ingeniería de los Alimentos-Màster Universitari en Ciència i Enginyeria dels Aliments |
| Resumo: | [EN] Sensory analysis is a useful analytical technique to classify monofloral honeys (orange blossom, rosemary, thyme, etc.) since it allows defining their organoleptic profile. To do this, it is necessary to identify and quantify the sensory attributes that characterize them and build specific organoleptic profiles. In this sense, the main objective of the present work has been to carry out a review of the published information on the methods most used in the sensorial characterization of honey, with special attention to Spanish monofloral honeys and the attributes that define them. In general, in recent years both classic descriptive methods that require trained panelists (Quantitative descriptive analysis "QDA" or qualitative descriptive sensory analysis), and modern methods (Free Choice Profiling (FCP), Check -all-that-apply “CATA” or Flash Profiling “FP”). Even though the latter have the advantage of being more flexible and saving time since they especially use habitual consumers of the product, the most used method for the characterization of honeys continues to be the classic QDA. Commonly, the attributes selected to describe honeys are: visual or appearance, aroma, flavour and texture. Among the statistical tools most used in data processing, the analysis of variance (ANOVA) stands out, together with a multiple comparison test (Duncan's Test or Tukey's HSD Test), both useful to differentiate between individual samples for each sensory attribute. The Principal Component Analysis (PCA) also stands out (it allows visualizing the relationships between honeys and sensory attributes), as well as the Generalized Procrustes Analysis (GPA), because it provides a consensual image of the data of each panelist in a two-dimensional or three-dimensional space. |
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