Articles
CRITICAL EVALUATION OF HORTICULTURAL GRADING SYSTEMS BY QUANTITATIVE IMAGING TECHNIQUES
Article number
536_11
Pages
109 – 120
Language
Abstract
Translation of quality determinants of fruits and vegetables in objective quality criteria results in optimal auction grading systems.
Defining optimal quality standards in combination with an adequate pricing strategy guarantees the income of intensive production systems and ensures consumers a correct price/quality ratio.
In this paper, a methodological concept is proposed to study auction grading systems.
Chicory, a typical Belgian vegetable, serves as a model product.
The visual character of quality makes fruits and vegetables very suitable for investigation by quantitative imaging techniques.
Extraction of external quality features from digital video images of the product results in a quantitative, objective description of product quality.
A computer system based on image sequences is an efficient experimental tool to study visual product quality.
Study of uncertainty and enclosed subjectivity in expert quality classification is a first step towards the definition of optimal quality criteria with high discriminatory power.
Quality classification of chicory by experts from two auctions with relation to the size of the product is evaluated using quantitative imaging techniques.
Between expert misclassification is analysed by correspondence analysis, loglinear models, latent class analysis and tree-based modelling to clarify the true structure of quality classification.
Defining optimal quality standards in combination with an adequate pricing strategy guarantees the income of intensive production systems and ensures consumers a correct price/quality ratio.
In this paper, a methodological concept is proposed to study auction grading systems.
Chicory, a typical Belgian vegetable, serves as a model product.
The visual character of quality makes fruits and vegetables very suitable for investigation by quantitative imaging techniques.
Extraction of external quality features from digital video images of the product results in a quantitative, objective description of product quality.
A computer system based on image sequences is an efficient experimental tool to study visual product quality.
Study of uncertainty and enclosed subjectivity in expert quality classification is a first step towards the definition of optimal quality criteria with high discriminatory power.
Quality classification of chicory by experts from two auctions with relation to the size of the product is evaluated using quantitative imaging techniques.
Between expert misclassification is analysed by correspondence analysis, loglinear models, latent class analysis and tree-based modelling to clarify the true structure of quality classification.
Authors
H. Coppenolle, E. Schrevens
Keywords
chicory, quality, images, classification, agreement
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