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Modelling the consensus and differences between assessors inspecting the colour quality of apples by ‘tree‐based modelling’
Author(s) -
Paulus Ingrid,
Coppenolle Hans,
Schrevens Eddie
Publication year - 2000
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/1097-0010(200010)80:13<1953::aid-jsfa716>3.0.co;2-s
Subject(s) - grading (engineering) , malus , quality assessment , quality (philosophy) , statistics , computer science , artificial intelligence , mathematics , evaluation methods , horticulture , engineering , reliability engineering , biology , philosophy , civil engineering , epistemology
Abstract This research investigated the consensus and differences between different quality inspectors assessing the colour quality classification of a two‐coloured apple variety ( Malus domestica Borkh cultivar ‘Jonagold’). An image analysis system measured the colour characteristics objectively. These objective measures formed the basic reference to compare the grading behaviour. Different quality inspectors were asked to assess the colour quality of different sets of apples applying the commercial quality standards. Agreement and association measures of the intra‐inspector contingency tables indicated a moderate ability of the inspectors to reconstruct their own quality classification. If the intra‐agreement and intra‐association were lower than a threshold, the repeatability of the inspector's assessments was considered as too poor and his classification results were omitted from the model development that simulated the apple colour classification behaviour. The statistical method ‘tree‐based modelling’ was applied to connect the individual quality assignments with the objective apple colour measurements. These models indicated that the blush colour was more important than the blush area for the quality assessment.The individual grading decision models were compared by correspondence analysis. Four different grading archetypes were detected and simulated. The predictive power of the four archetypal models was much higher than the predictive power of a consensus model including all inspectors. These results underlined the fact that poorly defined commercial standards lead to different quality interpretation. © 2000 Society of Chemical Industry