## 3 Results and Discussion  
Most of the product attributes followed a linear trend in the mixture equations, highlighting good equation fits and produced regression coefficients whose higher values correspond to greater effects (Table 2), positive or negative, explicitly illustrated in Figures 2-4. Regarding the chemical set (Figure 2), moisture and protein followed a similar trend of response, i.e., an increase in buffalo meat and decrease in both fat ingredients as their proportions increased individually from the reference blend point (centroid of the mixture design), which consisted of 60% buffalo meat, 20% pork fat and 20% buffalo fat. Inversely, an increasing pattern for the fat concentration of sausages occurred as the proportion of both fat ingredients increased with the model indicating no significant difference between the effects of pork and buffalo fat on total fat content. The increasing trend of protein and moisture content as the fat level of sausages decreased was also observed in the studies of [PERSON] et al. (2011) [25] and [PERSON] et al. (2004) [36]. Unique curvilinear responses of the ash concentration of sausages were formed and depicted in the trace plot, in which the most striking effect was the rapid decline when only the buffalo meat increases in the blend. The textural adhesiveness and chewiness showed a similar pattern of responses (Figure 3): they both increase (in equal rates of change) in higher buffalo meat proportions and decrease in increasing proportions of both fat ingredients with a more reductive effect of the pork fat. The hardness is also enhanced in higher proportions of buffalo meat and is reduced equally when the fat increases indiscriminately in the mixture. The fat is known to play a major role in the final textural quality of sausages and meat emulsion-type products; thus, decreasing the animal fat content and especially pork backfat is correlated with higher textural hardness and chewiness [37; 38]. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Proximate Composition**} & \multicolumn{4}{c}{**Textural Properties**} & \multicolumn{4}{c}{**Sensory Properties**} \\ \cline{2-13}
**Term** & **Moisture** & **Ash** & **Fat** & **Protein** & **Hardness** & **Adhes-iveness** & **Chewiness** & **Hardness** & **Cohesi-veness** & **Elasticity** & **Juciness** \\ \hline Buffalo Meat & 0.679 & 0.012 & \(-\)0.009 & 0.178 & 1.661 & 0.646 & 0.624 & 0.105 & 0.105 & 0.055 & 0.021 \\ Pork Fat & 0.239 & 0.068 & 0.979 & 0.069 & 2.391 & \(-\)0.222 & \(-\)0.318 & \(-\)0.061 & \(-\)0.018 & 0.162 & 0.234 \\ Buffalo Fat & 0.313 & \(-\)0.125 & 0.942 & 0.038 & \(-\)0.613 & 0.061 & 0.158 & 0.159 & 0.17 & 0.082 & 0.12 \\ Buffalo Meat & & & & & \(-\)0.056 & & & & & & & \\ * Fork Fat & & & & & & & & & & & \\ Buffalo Meat & & & & & & & & & & & \\ * Buffalo Fat * & & & \(-\)0.016 & & & & & & & & \\  R2 & 84.6\% & 59.7\% & 85.6\% & 52.1\% & 80.5\% & 72.2\% & 70.4\% & 77.1\% & 61.2\% & 40.2\% & 77.2\% \\  R2 & 80.6\% & 45.0\% & 81.0\% & 39.3\% & 71.0\% & 64.3\% & 60.0\% & 65.0\% & 47.2\% & 20.0\% & 63.6\% \\ \hline \hline \end{tabular}  
* A difference between R2 and R2p lower than 20% generally suggests a better equation fit and prediction. High R2 values indicate better equation fit and prediction.  
\end{table} 
Table 2: Regression coefficients (in amounts) of the statistically significant variables as affected by the mixture of components. Two different patterns of responses are formed regarding the sensory attributes (Figure 4). Firstly, the hardness and cohesiveness increased slightly when both buffalo meat and fat increased. The second pattern refers to the steep decline of the hardness and cohesiveness in higher amounts of pork fat. To better understand this fact, one should consider both the higher polyunsaturated to saturated lipid ratio (P/S) of pork backfat compared to the buffalo and beef fat and the effect of fatty acid composition on the meat's and meat products' firmness, since the melting point lowers as unsaturation increases [39].