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Multivariate data analysis applied to spectroscopy: Potential application to juice and fruit quality

journal contribution
posted on 2018-08-08, 00:00 authored by Daniel 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.

Funding

Category 2 - Other Public Sector Grants Category

History

Volume

44

Issue

7

Start Page

1888

End Page

1896

Number of Pages

9

ISSN

0963-9969

Publisher

Pergamon Press

Peer Reviewed

  • Yes

Open Access

  • No

Acceptance Date

2011-01-17

External Author Affiliations

Australian Wine Research Institute

Era Eligible

  • Yes

Journal

Food Research International

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