Classification modeling based on surface porosity for the grading of natural cork stoppers for quality wines

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.