Missing Data Calculation Using the Antioxidant Activity in Selected Herbs

Abstract

In this paper, a model has been developed that can estimate the composition of the phenol compounds, based on censored data and the total equivalent antioxidant capacity (TEAC) measured by three different methods. A contingency of 32 plants was analyzed: total phenolic content (TPC), caffeic acid, p-coumaric acid, ferulic acid, neochlorogenic acid and TEAC. They were measured by three different methods: ABTS (2,20-azinobis-(3-ethylbenzthiazoline- 6-sulfonic acid)), DPPH (1,1-diphenyl-2-picrylhydrazyl radical) and FRAP (ferric reducing/antioxidant power). Five values of caffeic-, thirteen of p-coumaric-, seven of ferulic-, and nineteen neochlorogenic acids were missing. Due to the complexity of the compounds, data mining and computational methods are required to determine the missing data. The method developed for independent variables was used to estimate the missing data. The contingency was filled with the calculated values obtained with all alternatives. The performance of each approach is shown in the estimation and/or prediction of the phenolic composition compared to the approaches used. The results indicated a strong correlation and mutual influence between the data analyzed.