Journal of Food Processing & Technology

Quality control of olive oil by computer vision and artificial intelligence

9^th Euro-Global Summit & Expo on Food & Beverages

July 11-13, 2016 Cologne, Germany

Enrique S Pariente, Jose S Torrecilla, John C Cancilla, Regina Aroca-Santos, Gemma Matute and Kacper W Wierzchos

Complutense University of Madrid, Spain
University of South Florida, USA

Posters & Accepted Abstracts: J Food Process Technol

Abstract:

Olive oil in Mediterranean countries is the cornerstone of their popular and healthy diet. Spain is one of the main olive oil producing and exporting countries and it also represents an important pillar of its economy. For these reasons, quality control and protection of these products are relevant aspects of the sector, and new approaches that improve this are always well received. When controlling the quality of olive oil, special attention must be paid during the selection of the olives which will be used, because their quality will directly determine the final product. The use of low quality olives can ruin the outcome of the oil, even if adequate systems are employed. This fruit selection process is the first step carried out in the mill. Based on photographic studies which cataloged different types of olives by quality, a model based on image processing and artificial intelligence, in order to identify the quality of olives directly from the image, has been designed, reaching a high correct classification rate. This rate was 100% when trying to distinguish high quality olives from the rest, because its appearance is substantially different from those of average quality and lower grades. An olive selection process assisted by this system could be useful to predict oil quality. The collection and processing phases of the images could be done in situ, which would pave the road for a possible real-time application of the system.

Biography :

Email: enriquesanriente@gmail.com