Mid infrared spectroscopy and multivariate analysis: A tool to discriminate between organic and non-organic wines grown in Australia

Daniel Cozzolino, Matt Holdstock, Robert Dambergs, Wies Cynkar, Paul A Smith

Research output: Contribution to journalArticlepeer-review

83 Citations (Scopus)

Abstract

The combination of mid infrared (MIR) spectroscopy and multivariate analysis was explored as a tool to classify commercial wines sourced from organic (ORG) and non-organic (NORG) production systems. Commercial ORG (n = 57) and NORG (n = 115) red and white wine samples from 13 growing regions in Australia were analysed using a MIR spectrophotometer. Discriminant models based on MIR spectra were developed using principal component analysis (PCA), discriminant partial least squares (DPLS) regression and linear discriminant analysis (LDA). Overall, the LDA models based on the PCA scores correctly classified on average, more than 75% of the wine samples while the DPLS models correctly classified more than 85% of the wines belonging to ORG and NORG production systems, respectively. These results showed that MIR combined with discriminant techniques might be a suitable method that can be easily implemented by the wine industry to classify wines produced under organic systems.
Original languageEnglish
Pages (from-to)761-765
Number of pages5
JournalFood Chemistry
Volume116
Issue number3
DOIs
Publication statusPublished - 01 Oct 2009

Fingerprint

Dive into the research topics of 'Mid infrared spectroscopy and multivariate analysis: A tool to discriminate between organic and non-organic wines grown in Australia'. Together they form a unique fingerprint.

Cite this