Grape seed characterization by NIR hyperspectral imaging
Currently, the time of grape harvest is normally determined according to the sugar level in the pulp of the berry. Nonetheless, the stage of maturation in grape seeds should be taken into account more frequently to decide the appropriate harvest period. There are chemical and sensory analyses availa...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/155947 |
| Acceso en línea: | https://hdl.handle.net/11441/155947 https://doi.org/10.1016/j.postharvbio.2012.09.007 |
| Access Level: | acceso abierto |
| Palabra clave: | Grape seeds Hyperspectral imaging Partial least squares regression Principal components analysis Vitis vinifera |
| Sumario: | Currently, the time of grape harvest is normally determined according to the sugar level in the pulp of the berry. Nonetheless, the stage of maturation in grape seeds should be taken into account more frequently to decide the appropriate harvest period. There are chemical and sensory analyses available to assess stage of maturation of grape seeds but they are destructive and time-consuming. Hyperspectral imaging is an alternative technology to characterize the grape seeds according to their chemical attributes, and the current work aimed to non-destructively characterize grape seeds in regard of the variety and stage of maturation. For this purpose, 56 samples of seeds from two red grape varieties (Tempranillo and Syrah) and one white variety (Zalema) in two kinds of soil were selected to assess their features based on the reflectance in the near-infrared (NIR) spectra by using prediction models (partial least squares regression) and multivariate analysis methods (principal component analysis and general discriminant analysis). In this study, a reliable methodology for predicting the stage of maturation was developed, and it was shown that it was possible to distinguish the variety of grape and even the type of soil from hyperspectral images of grape seeds. |
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