Chemometric techniques to protect the traditional Austrian pumpkin seed oil. Issue 11 (26th May 2017)
- Record Type:
- Journal Article
- Title:
- Chemometric techniques to protect the traditional Austrian pumpkin seed oil. Issue 11 (26th May 2017)
- Main Title:
- Chemometric techniques to protect the traditional Austrian pumpkin seed oil
- Authors:
- Zettl, Daniela
Bandoniene, Donata
Meisel, Thomas
Wegscheider, Wolfhard
Rantitsch, Gerd - Abstract:
- Abstract : The aim of this work was to establish suitable chemometric techniques for establishing provenance of pumpkin seed and pumpkin seed oil from the regions of Austria, China and Russia, in order to protect the authentic Austrian products from fraud and mislabelling. To achieve this goal, three different chemometric approaches, projection to latent structures (PLS), soft independent modelling of class analogy (SIMCA) and support vector machines (SVM) were applied on two different trace element data sets. To evaluate the reliability of the classification achieved, the results were validated on an independent test set. PLS and SVM performed similarly in many situations. Also the prediction of the discriminating techniques was in accordance with the modelling technique SIMCA. But PLS alone can be used to separate Austrian from non‐Austrian pumpkin seed and pumpkin seed oil samples based on trace element data. Practical applications: For various reasons, more and more consumers prefer local products with a defined geographical origin. Producers also advertise the geographical origin and are trying to increase the value of their products by praising the quality of their products through a geographical designation. Unfortunately, there is an increases of abuse in these products which also comprise the 'Styrian pumpkin seed oil PGI' with falsely declared geographical origin. The demand for an analytical approach how to counteract the falsification of origin of Styrian pumpkinAbstract : The aim of this work was to establish suitable chemometric techniques for establishing provenance of pumpkin seed and pumpkin seed oil from the regions of Austria, China and Russia, in order to protect the authentic Austrian products from fraud and mislabelling. To achieve this goal, three different chemometric approaches, projection to latent structures (PLS), soft independent modelling of class analogy (SIMCA) and support vector machines (SVM) were applied on two different trace element data sets. To evaluate the reliability of the classification achieved, the results were validated on an independent test set. PLS and SVM performed similarly in many situations. Also the prediction of the discriminating techniques was in accordance with the modelling technique SIMCA. But PLS alone can be used to separate Austrian from non‐Austrian pumpkin seed and pumpkin seed oil samples based on trace element data. Practical applications: For various reasons, more and more consumers prefer local products with a defined geographical origin. Producers also advertise the geographical origin and are trying to increase the value of their products by praising the quality of their products through a geographical designation. Unfortunately, there is an increases of abuse in these products which also comprise the 'Styrian pumpkin seed oil PGI' with falsely declared geographical origin. The demand for an analytical approach how to counteract the falsification of origin of Styrian pumpkin seed oil has increased considerably. The aim of this work is to establish an analytical method with suitable chemometric techniques for establishing the provenance of pumpkin seed oil from the regions of Austria, China and Russia, in order to protect the authentic Austrian products from fraud and mislabelling. PLS, SIMCA and SVM chemometric techniques are applied for establishing the provenance of pumpkin seed and pumpkin seed oil. PLS and SVM perform similarly in most situations and are in accordance with SIMCA models. However, the classification task can be solved by PLS only. Abstract : PLS, SIMCA and SVM chemometric techniques are applied for establishing the provenance of pumpkin seed and pumpkin seed oil. PLS and SVM perform similarly in most situations and are in accordance with SIMCA models. However, the classification task can be solved by PLS only. … (more)
- Is Part Of:
- European journal of lipid science and technology. Volume 119:Issue 11(2017)
- Journal:
- European journal of lipid science and technology
- Issue:
- Volume 119:Issue 11(2017)
- Issue Display:
- Volume 119, Issue 11 (2017)
- Year:
- 2017
- Volume:
- 119
- Issue:
- 11
- Issue Sort Value:
- 2017-0119-0011-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2017-05-26
- Subjects:
- Chemometric techniques -- Geographical origin -- Pumpkin seed -- Pumpkin seed oil -- PLS -- SIMCA -- SVM
Oils and fats, Edible -- Periodicals
Lipids -- Periodicals
660.63 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1438-9312 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ejlt.201600468 ↗
- Languages:
- English
- ISSNs:
- 1438-7697
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.730975
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5336.xml