<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oliveira, Vanda</style></author><author><style face="normal" font="default" size="100%">Knapic, Sofia</style></author><author><style face="normal" font="default" size="100%">Pereira, Helena</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Classification modeling based on surface porosity for the grading of natural cork stoppers for quality wines</style></title><secondary-title><style face="normal" font="default" size="100%">Food and Bioproducts Processing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">Discriminant analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">image analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">natural cork stoppers</style></keyword><keyword><style  face="normal" font="default" size="100%">Porosity</style></keyword><keyword><style  face="normal" font="default" size="100%">quality classes</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">Submitted</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract></record></records></xml>