Using The Response Surface Method to Determine Optimum Temperature and Gam Usage in Egg Storage

Can Yavuz, İsmail Keskin

Abstract


Response surface method (RSM) is a form of optimization based on the creation of an empirical model for evaluating the relationship between factor levels and the responses obtained therefrom. RSM is a multivariate analysis created by applying multiple regression and space geometry together. This optimization method can also be used as a preliminary stage of factorial experiments, since factor levels determine the optimum points before a factorial experiment. In this way, since the difference between the factor levels will be less, it provides more healthy results. In other words, optimization is used to increase the significance and sensitivity of factor levels.

In this study, 130 table chicken eggs were divided into 9 groups according to their storage temperatures and percentages of coating gam arabic matter. Weight losses during the 28-day storage period of eggs were calculated. The eggs were weighed on the 7th day, the 14th day, the 21st day, and the 28th day. After the study was completed, the differences of the weights on the first day and 28th day were calculated. While applying RSM, Central Composite Design trial pattern was used.

As a result of the analysis, optimum storage temperature and gam arabic composition were determined for egg storage with RSM. According to the results of the statistical analysis, at the end of the 4th week, it was determined that the optimum storage temperature and gum substance composition for the minimum egg weight loss (1.58 g) were 7.64-8.24 oC and 15%. When the results of the study and the results obtained from the analysis are compared, it is thought that RSM has obtained an intermediate dose estimation for the minimum egg weight loss in optimization of egg preservation conditions and this may be beneficial in the field of animal breeding.

Keywords


Central Composite Design, Face centered composite design, Egg, Optimization, Response surface method

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References


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DOI: http://dx.doi.org/10.15316/SJAFS.2020.213

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