Work

Inter-regional characterization of New Zealand pinot noir wines: Assessing geographical origin through mid-FTIR and phenolic profile analysis

Year: 2025

Type: article

Abstract: values ranging from 0.75 to 0.99. Multivariate analyses, including Linear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Artificial Neural Network (ANN) and Random Forest (RF) based on either phenolic data alone, spectral data alone, or a fusion of both, achieved high classification acccuracy. Among these methods, the LDA and ANN models demonstrated superior classification performance compared to PLS-DA and RF. The phenolic profile provides detailed information on key compositional markers, while FTIR spectra offer a holistic chemical representation. This fusion enables a more comprehensive differentiation of wine origins, reducing potential misclassification caused by the limitations of individual datasets. In conclusion, exploratory and multivariate analyses proved to be rapid and efficient methods for tracing the origin of pinot noir wines produced in New Zealand.

Source: Food Research International

DOI: 10.1016/j.foodres.2025.116485

Authors: Yingyue Su, Yi Yang, Paul A. Kilmartin, Leandro Dias Araujo

Institutions: Lincoln University, Northwest A&F University, University of Auckland

Language: English

Topic: Spectroscopy and Chemometric Analyses

Subfield: Analytical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: hybrid

Estimated APC paid: $4,320