Journal of Animal Science and Technology

Korean Society of Animal Sciences and Technology (한국축산학회)
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Quality Prediction of Eggs Treated in Combination with Gamma Irradiation and Chitosan Coating Using Response Surface Methodology

  • Lee, Kyung-Heang (Department of Food and Nutrition, Chungju National University) ;
  • Jung, Samooel (Department of Animal Science and Biotechnology, Chungnam National University) ;
  • Ham, Jun-Sang (Quality Control and Utilization Division, National Institute of Animal Science, RDA) ;
  • Lee, Jun-Heon (Department of Animal Science and Biotechnology, Chungnam National University) ;
  • Lee, Soo-Kee (Department of Animal Science and Biotechnology, Chungnam National University) ;
  • Jo, Cheo-Run (Department of Animal Science and Biotechnology, Chungnam National University)
  • Received : 2011.05.10
  • Accepted : 2011.06.10
  • Published : 2011.06.30
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Abstract

The aim of this work was to determine the method and predict the optimum conditions for egg quality stored for 7 days when combination treatments of irradiation and chitosan coating were applied using response surface methodology (RSM). A central composite design was chosen for the RSM in this study and the factors were irradiation dose (0~2 kGy) and concentration of chitosan coating material (0~2%). Performance of the irradiation and chitosan coating were evaluated by analyzing the egg quality and functional property factors. The predicted maximum level of Haugh units and foaming ability calculated by a developed model were 74.19 at 0 kGy of irradiation with coating by 0.96% chitosan solution and 50.83 mm at 2.0 kGy with 1.01%, respectively. The predicted minimum value of foam stability and 2-thiobarbituric acid reactive substances (TBARS) value were 2.97 mm at 0.39 kGy with 0.21% and 0.54 mg malonaldehyde/kg egg yolk at 0 kGy with 0.90% of chitosan solution, respectively. Results clearly showed that gamma irradiation negatively affected the Haugh unit and TBARS but positively affected the foaming capacity. The estimated value from the developed model by RSM was verified by no statistical difference with observed value. Therefore, RSM can be a good tool for optimization and prediction of egg quality when 2 or more treatments are combined. However, one should decide the target quality first to achieve a successful implementation of this technology.

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References

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