Mathematical Modeling of the antioxidant capacity of propolis

Yalçınkaya M., Kolaylı S., Yıldız O.

I. INTERNATIONAL APITHERAPY AND NATURE CONGRESS, Nakhchivan, Azerbaijan, 1 - 03 June 2023, vol.1, no.1, pp.48-56

  • Publication Type: Conference Paper / Full Text
  • Volume: 1
  • City: Nakhchivan
  • Country: Azerbaijan
  • Page Numbers: pp.48-56
  • Karadeniz Technical University Affiliated: Yes



Regression Analysis is the most popular method that determines the relationship between an

independent variable and more than one dependent variable with a mathematical function. In

the regression analysis, the parameters are usually calculated by the Least Squares Method

(Least Squares) Method. In general, the regression equation created according to the parameters

is solved with the SPSS package program and the model coefficients are determined. However,

mismatched measures close to the random error limits in the data affect the parameter

estimation. In this context, the model to be created in the study will be solved according to the

EKK Method, and incompatible measures will be determined and removed from the data set.

Thus, parameters and mean errors will be calculated more realistically with the remaining

compatible measures. In addition, the significance of the calculated parameters will also be

tested statistically. Raw propolis composition consists of water, moisture, phenolic substances,

flavonoids, waxes, and balsam. A quality propolis should have high antioxidant capacity. In

this mathematical modeling study, the quality of propolis is calculated according to the Least

Squares Method (EKKY) method. In this preliminary study, the quality properties of propolis

were determined by mathematical modeling, taking into account the total polyphenol (TP), total

flavonoid (TF), total wax, and moisture and balsamic substance amounts were used in the 40

propolis samples from Anatolia of Turkey. In this context, operators will be able to determine

the most suitable sales price by predicting the quality of their propolis.

Keywords: Propolis, Mathematical modelling, FRAP