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- Title
Classification modeling based on surface porosity for the grading of natural cork stoppers for quality wines.
- Authors
Oliveira, Vanda; Knapic, Sofia; Pereira, Helena
- Abstract
The natural cork stoppers are commercially graded into quality classes according with the homogeneity of the external surface. The underlying criteria for this classification are subjective without quantified criteria and standards defined by cork industry or consumers. Image analysis was applied to premium, good and standard quality classes to characterize the surface of the cork stoppers and stepwise discriminant analysis (SDA) was used to build predictive classification models. The final goal is to analyze the contribution of each porosity feature and propose an algorithm for cork stoppers quality class classification. This study provides the knowledge based on a large sampling to an accurate grading of natural cork stoppers. In average all the models presented accuracy in relation to the commercial classification over 68% with a higher mismatch in the mid-quality range. Color showed an important discriminating power, increasing the accuracy in 10%. The main discriminant features were porosity coefficient and color variables, calculated for the lateral surface. A quality classification algorithm was presented based on a simplified model with an accuracy of 75%. The classification based on color vision systems can ensure improved quality class uniformity and a higher transparency in trade.
- Subjects
POROSITY; CORK industry; IMAGE analysis; GRAPE products; DISCRIMINANT analysis; WINES
- Publication
Food & Bioproducts Processing: Transactions of the Institution of Chemical Engineers Part C, 2015, Vol 93, Issue 1, p69
- ISSN
0960-3085
- Publication type
Article
- DOI
10.1016/j.fbp.2013.11.004