Preliminary study to determine the phenolic maturity stage of grape seeds by computer vision
The applications of computer vision technology for acquiring and analysing images have been extended to the quality evaluation in food industry. This technique involves great advantages for the objective, rapid, non-contact and automated quality inspection and control. The aim of this work was to ev...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/156108 |
| Acceso en línea: | https://hdl.handle.net/11441/156108 https://doi.org/10.1016/j.aca.2012.01.005 |
| Access Level: | acceso abierto |
| Palabra clave: | Colour Grape seeds Image analysis Phenolics Vitis vinifera |
| Sumario: | The applications of computer vision technology for acquiring and analysing images have been extended to the quality evaluation in food industry. This technique involves great advantages for the objective, rapid, non-contact and automated quality inspection and control. The aim of this work was to evaluate the potential of the computer vision to determine the phenolic maturity stage of grape seeds. Up to 21 phenolic compounds were determined by HPLC-DAD-MS in order to obtain reference values to develop the model. The CIELAB parameters, area, aspect, roundness, length, width and heterogeneity of seeds were analysed using a DigiEye ® system. The technique reported in this work can be a good and rapid tool for taking decisions at harvest time. Notwithstanding, a comprehensive study should be made in order to develop more robust models. |
|---|