## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Sample** & **L** & **a\({}^{\textbf{*}}\)** & **b\({}^{\textbf{*}}\)** & **C\({}^{\textbf{*}}\)** & \({}^{\textbf{c}}\)**h** & \(\Delta\)**E** \\ \hline MD6 & 80.073 \(\pm\) 0.27 b & 6.007 \(\pm\) 0.43 ab & 22.723 \(\pm\) 0.404 cd & 23.720 \(\pm\) 0.468 cd & 75.180 \(\pm\) 0.865 e & 17.875 \(\pm\) 0.45 c \\ GA6 & 75.433 \(\pm\) 1.032 cd & 5.497 \(\pm\) 0.403 b & 24.557 \(\pm\) 0.543 ab & 25.033 \(\pm\) 0.545 ab & 77.377 \(\pm\) 0.756 cd & 21.867 \(\pm\) 0.114 ab \\ CMC6 & 78.943 \(\pm\) 0.105 b & 3.743 \(\pm\) 0.045 s & 22.453 \(\pm\) 0.215 d & 22.837 \(\pm\) 0.315 e & 81.650 \(\pm\) 1.897 a & 18.025 \(\pm\) 0.193 c \\ MD22:2 & 83.253 \(\pm\) 0.430 a & 3.787 \(\pm\) 0.012 e & 19.170 \(\pm\) 0.06 e & 19.570 \(\pm\) 0.108 f & 78.443 \(\pm\) 0.653 b & 12.842 \(\pm\) 0.190 d \\ MD4 GA2 & 73.107 \(\pm\) 0.528 d & 6.197 \(\pm\) 0.024 a & 24.960 \(\pm\) 0.592 a & 25.400 \(\pm\) 0.066 a & 75.863 \(\pm\) 0.093 d & 24.101 \(\pm\) 0.100 a \\ MD4 CMC2 & 77.703 \(\pm\) 0.528 b & 4.071 \(\pm\) 0.071 d & 23.873 \(\pm\) 0.07 d & 24.010 \(\pm\) 0.265 b & 78.173 \(\pm\) 0.274 b & 20.022 \(\pm\) 0.848 b \\ GA4 CMC2 & 74.900 \(\pm\) 1.975 d & 5.207 \(\pm\) 0.284 c & 23.607 \(\pm\) 0.823 b & 24.200 \(\pm\) 0.884 b & 24.207 \(\pm\) 0.820 s & 21.750 \(\pm\) 1.939 ab \\ MD2 GA4 & 77.810 \(\pm\) 0.626 b & 5.593 \(\pm\) 0.099 ab & 24.187 \(\pm\) 0.482 ab & 24.827 \(\pm\) 0.475 ab & 76.967 \(\pm\) 0.333 c & 20.294 \(\pm\) 0.742 b \\ MD2 CMC4 & 79.113 \(\pm\) 0.641 b & 4.103 \(\pm\) 0.093 b & 22.272 \(\pm\) 0.239 cd & 23.097 \(\pm\) 0.246 b & 79.757 \(\pm\) 0.172 b & 18.163 \(\pm\) 0.515 c \\ GA2 CMC4 & 78.387 \(\pm\) 0.798 b & 4.687 \(\pm\) 0.257 e & 24.253 \(\pm\) 0.551 ab & 24.700 \(\pm\) 0.589 abc & 79.077 \(\pm\) 0.359 b & 19.868 \(\pm\) 0.551 b \\ \hline \hline \end{tabular} Values are expressed as mean \(\pm\) standard deviation where different letters within the same column represent significant differences at \(p\) \(<\) 0.05. MD—Matlodektrin, GA—Gum Arabic, CMC—Carboxymethylcellulose, A\({}_{\textbf{w}}\)—water activity, WAI—water absorption index, WSI—water solubility index.  
\end{table} 
Table 3: CIELab colour parameters of the citrus byproduct encapsulates. The encapsulation efficiency (calculated from total phenol content and surface phenols content) is shown in Figure 1. Encapsulation efficiency could be defined as the ability of the carrier material to encapsulate bioactive compounds. Also, it can be used as a determining factor for the integrity and porosity of produced encapsulates [34]. The encapsulation efficiency is affected by various parameters including carrier concentration, carrier solubility, as well as the rate of solvent evaporation during drying. The encapsulation efficiency of prepared encapsulates in this study ranged from 50.909% to 84.000%. Differences in encapsulation efficiency could be a result of polyphenol-carrier complex formation. According to [PERSON] et al. [35] and [PERSON] and [PERSON] [36], the formation of complex structures between phenolics and carriers (polysaccharides) depends on the molecular size and solubility of the carrier material. The highest encapsulation efficiency had an encapsulate prepared with all three carriers in the same proportions (MD2 GA2 CMC2), while the lowest had a sample prepared with pure MD. Additionally, a positive correlation between EE and WAI (r = 0.72, \(p\) = 0.01) and a negative between EE and WSI was observed, which could be explained by the CMC content in the carrier material. Namely, a slight positive correlation between CMC content and encapsulation efficiency was also observed (r = 0.69, \(p\) = 0.01). Surprisingly, there was no correlation between total color changes and encapsulation efficiency. However, upon comparing individual color properties a significant dependence between redness value (a) and encapsulation efficiency was observed. With an increase in the redness of the sample, a decrease in encapsulation efficiency was observed with a negative correlation of (r = \(-\)0.78, \(p\) = 0.01).