About Sensitivity and specificity of PLS-class modelling for five sensory characteristics of dry-cured ham using visible and near infrared spectroscopy [An article from: Analytica Chimica Acta] detail
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Sensitivity and specificity of PLS-class modelling for five sensory characteristics of dry-cured ham using visible and near infrared spectroscopy [An article from: Analytica Chimica Acta] Description
This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
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The two objectives of this work were to evaluate near infrared reflectance spectroscopy (NIR) as a tool for on-line classification of dry-cured ham samples according to their sensory characteristics and propose a method for obtaining a set of qualified class models that enables accurate decisions to be taken. With these aims, 117 dry-cured ham samples were classified by expert judges as compliant or non-compliant concerning sensory variables as pastiness, colour, crusting, marbling and ring colour. These samples were also scanned using a remote reflectance fiber optic probe. Each class model built for each sensory variable is evaluated for its sensitivity and specificity, parameters related with the probability of false non-compliance (@a) and false compliance (@b) of ''H"0: the sample is compliant'' hypothesis test. With the five sets of PLS-class modelling the five risk curves, graphs @b versus @a, are estimated. It is therefore possible to choose the risks of false compliance and false non-compliance for each sensorial variable according to the needs of the decision-maker.
