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Description
  • The purpose of the presented study is to verify applicability of Raman spectroscopy for the thermal degradation screening of edible oils and their identification. The statistical method Principal component analysis was performed for large spectral datasets evaluation as well as Partial least square regression. Raman spectroscopy as an effective tool for material identification offers benefits that are required for the process control of oils quality, both in terms of food technology and in terms of maintaining the nutritional value of edible oils. These are rapidity, independence on the number of chemicals, portability and possibility of automation of measurements – advantages over the conventional laboratory procedures. For the degradation process the most common types of oils used in the Czech Republic were used: sunflower, olive and canola oils. For the identification fourteen vegetable oils and oils from seeds and nuts were used. Mathematically processed spectral data indicate the worst effect of thermal load in terms of degradation process products formation and the loss of cis double bonds, i.e. the unsaturation for sunflower oils. Olive oils as the best and canola oil represent lesser risk due to a greater content of antioxidants. However, longer heat load leads to undesired decomposition and unsafe and unhealthy products generation even in these oils.
  • The purpose of the presented study is to verify applicability of Raman spectroscopy for the thermal degradation screening of edible oils and their identification. The statistical method Principal component analysis was performed for large spectral datasets evaluation as well as Partial least square regression. Raman spectroscopy as an effective tool for material identification offers benefits that are required for the process control of oils quality, both in terms of food technology and in terms of maintaining the nutritional value of edible oils. These are rapidity, independence on the number of chemicals, portability and possibility of automation of measurements – advantages over the conventional laboratory procedures. For the degradation process the most common types of oils used in the Czech Republic were used: sunflower, olive and canola oils. For the identification fourteen vegetable oils and oils from seeds and nuts were used. Mathematically processed spectral data indicate the worst effect of thermal load in terms of degradation process products formation and the loss of cis double bonds, i.e. the unsaturation for sunflower oils. Olive oils as the best and canola oil represent lesser risk due to a greater content of antioxidants. However, longer heat load leads to undesired decomposition and unsafe and unhealthy products generation even in these oils. (en)
Title
  • Spectroscopic screening of degradation process in edible oils and its mathematical evaluation
  • Spectroscopic screening of degradation process in edible oils and its mathematical evaluation (en)
skos:prefLabel
  • Spectroscopic screening of degradation process in edible oils and its mathematical evaluation
  • Spectroscopic screening of degradation process in edible oils and its mathematical evaluation (en)
skos:notation
  • RIV/70883521:28140/14:43872423!RIV15-MSM-28140___
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  • P(ED2.1.00/03.0089)
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  • 1
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  • 46592
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  • RIV/70883521:28140/14:43872423
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  • Identification, PCA, Raman spectroscopy, thermal degradation, vegetable oils (en)
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  • GB - Spojené království Velké Británie a Severního Irska
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  • [FEF317AD4CC8]
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  • International Journal of Mathematical Models and Methods in Applied Sciences
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  • 8
http://linked.open...iv/tvurceVysledku
  • Vašková, Hana
  • Křesálek, Vojtěch
  • Tobolová, Marie
  • Bučková, Martina
issn
  • 1998-0140
number of pages
http://localhost/t...ganizacniJednotka
  • 28140
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