Building of prediction models by using Mid-Infrared spectroscopy and fatty acid profile to discriminate the geographical origin of sheep milk. (January 2017)
- Record Type:
- Journal Article
- Title:
- Building of prediction models by using Mid-Infrared spectroscopy and fatty acid profile to discriminate the geographical origin of sheep milk. (January 2017)
- Main Title:
- Building of prediction models by using Mid-Infrared spectroscopy and fatty acid profile to discriminate the geographical origin of sheep milk
- Authors:
- Caredda, Marco
Addis, Margherita
Ibba, Ignazio
Leardi, Riccardo
Scintu, Maria Francesca
Piredda, Giovanni
Sanna, Gavino - Abstract:
- Abstract: Geographical authentication of sheep milk is an issue related to the production of cheeses labelled with a Protected Designation of Origin (PDO). To this purpose we investigated both the capability of the fatty acid composition and the capability of the Mid-InfraRed (MIR) spectra of 250 samples of sheep milk (gathered in different areas of the region Sardinia) to discriminate the samples as what regards their geographical origin. Genetic Algorithms (GA) were applied to the fatty acid profile and to the spectra to select the informative variables for developing discriminant models able to correctly classify the samples. The models were validated on unknown samples obtaining correct predictions of 96% using the selected fatty acids and of 99% using the selected MIR spectral regions. For routine control analysis, MIR spectroscopy is preferred for being a non-destructive, cheap and real-time analytical method. Highlights: Predictive models of the geographical origin of sheep milk were built. Predictive models were based either on fatty acid composition or on MIR spectra. Genetic Algorithms were used to select the informative fatty acids and MIR regions. All models correctly predict the geographical origin of sheep milk. MIR models can routinely be used to attribute the geographical origin of sheep milk.
- Is Part Of:
- Lebensmittel-Wissenschaft + Technologie =. Volume 75(2017)
- Journal:
- Lebensmittel-Wissenschaft + Technologie =
- Issue:
- Volume 75(2017)
- Issue Display:
- Volume 75, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 75
- Issue:
- 2017
- Issue Sort Value:
- 2017-0075-2017-0000
- Page Start:
- 131
- Page End:
- 136
- Publication Date:
- 2017-01
- Subjects:
- Geographical authentication -- Chemometrics -- IR spectroscopy -- Genetic algorithm -- Linear discriminant
PDO Protected Designation of Origin -- MIR Mid-InfraRed spectroscopy -- FT-MIR Fourier-Transform Mid-InfraRed spectroscopy -- FID Flame Ionization Detector -- PCA Principal Components Analysis -- GA Genetic Algorithms -- FAME Fatty Acid Methyl Esters -- CLA Conjugated Linoleic Acid -- MUFA MonoUnsaturated Fatty Acids -- SFA Saturated Fatty Acids -- UFA Unsaturated Fatty Acids -- PUFA PolyUnsaturated Fatty Acids -- LDA Linear Discriminant Analysis -- SNV Standard Normal Variate
Food industry and trade -- Periodicals
Food -- Composition -- Periodicals
Microbiology -- Periodicals
Nutrition -- Periodicals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00236438 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.lwt.2016.08.053 ↗
- Languages:
- English
- ISSNs:
- 0023-6438
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3983.070000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7380.xml