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ISHS Acta Horticulturae 566: II International Symposium on Application of Modelling as an Innovative Technology in the Agri-Food Chain; MODEL-IT

USING MULTIVARIATE MODELS TO DESCRIBE AND PREDICT THE SENSORY QUALITY OF COOKED POTATOES

Authors:   A.K. Thybo, F. van den Berg
Keywords:   agronomic influences, texture, Low-Field 1H NMR, uniaxial compression, multivariate data analysis
DOI:   10.17660/ActaHortic.2001.566.70
Abstract:
Multivariate modelling of quality is meaningful due to the fact that 1) quality is a multifaceted concept, 2) multiple agricultural parameters affect quality and 3) current instrumental measurements are often multidimensional. Usually, several sensory attributes and/or physical and chemical variables are needed to describe quality of agricultural products. This paper will review some of the agronomic parameters affecting potato quality by using multivariate analysis and also prediction of final sensory texture quality from rapid instrumental measurements on raw material.

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