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Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality
journal contributionposted on 2018-08-08, 00:00 authored by Daniel CozzolinoDaniel Cozzolino, WU Cynkar, N Shah, P Smith
The goal of building a multivariate calibration model is to predict a chemical or physical property from a set of predictor variables, for example the analysis of sugar concentration in fruits using near infrared (NIR) spectroscopy. Effective multivariate calibration models combined with a rapid analytical method should be able to replace laborious and costly reference methods. The quality of a calibration model primarily depends on its predictive ability. In order to build, interpret and apply NIR calibrations not only the quality of spectral data but also other properties such as effect of reference method, sample selection and interpretation of the model coefficients are also important. The objective of this short review is to highlight the different steps, methods and issues to consider when calibrations based on NIR spectra are developed for the measurement of chemical parameters in both fruits and fruit juices. The same principles described in this paper can be applied to other rapid methods like electronic noses, electronic tongues, and fluorescence spectroscopy. © 2011 Elsevier Ltd.
Category 2 - Other Public Sector Grants Category
Number of Pages9
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External Author AffiliationsAustralian Wine Research Institute