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Oxidative Stability and Quality Characteristics of Duck, Chicken, Swine and Bovine Skin Fats Extracted by Pressurized Hot Water Extraction.

Dong-Min ShinDo Hyun KimJong Hyeok YuneHyuk-Cheol KwonHyo Juong KimHan-Geuk SeoSung-Gu Han
Published in: Food science of animal resources (2019)
The aim of this study was to investigate the oxidative status and quality characteristics of four animal skin-derived fats extracted using an identical extraction method. Pressurized hot water extraction, a green extraction method, was used to extract animal skin fats (duck, chicken, swine, and bovine skin). Multiple experiments were performed during accelerated storage at 60°C for 90 days. Quality characteristics, such as extraction yield, iodine value (IV), fatty acid composition, and fat viscosity were determined. In addition, indicators for oxidative status, including acid value (AV), peroxide value (PV), p-anisidine value (p-AV), thiobarbituric acid reactive substances (TBARS), conjugated dienes (CD), and total oxidation (totox) values were evaluated. The fat extraction yield was highest in bovine fat, followed by duck, swine, and chicken fats. The IV was higher in duck and chicken fats. Duck fats contained the most unsaturated fats and the least saturated fats. Fat oxidation indicators, such as PV, TBARS, and totox values, were relatively higher in duck fats during storage compared to the other fats. Other indicators, including AV, p-AV, and CD, were similar in duck, chicken, and swine fats. Viscosity was similar in all the tested fats but markedly increased after 70 days of storage in duck fats. Our data indicate that duck skin fat was more vulnerable to oxidative changes in accelerated storage conditions and this may be due to its higher unsaturated fatty acid content. Supplementation with antioxidants might be a reasonable way to solve the oxidation issue in duck skin fats.
Keyphrases
  • fatty acid
  • adipose tissue
  • soft tissue
  • wound healing
  • hydrogen peroxide
  • magnetic resonance imaging
  • oxidative stress
  • machine learning
  • quality improvement
  • nitric oxide
  • drinking water