This work examines the use of stable isotopes and elemental composition for determining geographical origin and authenticity of cow milk from four geographical regions of Slovenian. Samples (277) were collected during summer and winter (2012–2014). It was possible to discriminate milk samples according to the year, season and production region using discriminant analysis (DA). The overall temporal prediction variability was 84.6% and 56.4% for regional differences. It was also possible to discriminate milk from three geographic regions, although Alpine samples overlap with Dinaric and Pannonian ones. Prediction ability was the highest for the Pannonian (82.1%) and lowest (26.9%) for the Alpine region. Pairwise comparison using OPLS-DA also displaying good regional predictability (≥0.77) with δ13Ccas values and Br content carrying the most variance. A model based on DD-SIMCA was also developed and applied to the control of Slovenian milk. The results revealed the mislabeling of three Slovenian milk products.
Geographical verification of Slovenian milk using stable isotope ratio, multi-element and multivariate modelling approaches / Potocnik, Doris; Necemer, Marijan; Perisic, Igor; Jagodic, Marta; Mazej, Darja; Camin, Federica; Eftimov, Tome; Strojnik, Lidija; Ogrinc, Nives. - In: FOOD CHEMISTRY. - ISSN 0308-8146. - 326:(2020), pp. 12695801-12695811. [10.1016/j.foodchem.2020.126958]
Geographical verification of Slovenian milk using stable isotope ratio, multi-element and multivariate modelling approaches
Camin, Federica;
2020-01-01
Abstract
This work examines the use of stable isotopes and elemental composition for determining geographical origin and authenticity of cow milk from four geographical regions of Slovenian. Samples (277) were collected during summer and winter (2012–2014). It was possible to discriminate milk samples according to the year, season and production region using discriminant analysis (DA). The overall temporal prediction variability was 84.6% and 56.4% for regional differences. It was also possible to discriminate milk from three geographic regions, although Alpine samples overlap with Dinaric and Pannonian ones. Prediction ability was the highest for the Pannonian (82.1%) and lowest (26.9%) for the Alpine region. Pairwise comparison using OPLS-DA also displaying good regional predictability (≥0.77) with δ13Ccas values and Br content carrying the most variance. A model based on DD-SIMCA was also developed and applied to the control of Slovenian milk. The results revealed the mislabeling of three Slovenian milk products.| File | Dimensione | Formato | |
|---|---|---|---|
|
Potocnik et al_2020_molecules.pdf
Solo gestori archivio
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
4.33 MB
Formato
Adobe PDF
|
4.33 MB | Adobe PDF | Visualizza/Apri |
|
FOCH-Potocnik-R1-Corrected (1).pdf
accesso aperto
Tipologia:
Post-print referato (Refereed author’s manuscript)
Licenza:
Creative commons
Dimensione
498.75 kB
Formato
Adobe PDF
|
498.75 kB | Adobe PDF | Visualizza/Apri |
|
Potočnik et al (1).pdf
accesso aperto
Tipologia:
Pre-print non referato (Non-refereed preprint)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
498.93 kB
Formato
Adobe PDF
|
498.93 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



