## 3 Results
Similarly, for a more stringent failure rate of <20% or survival rate > 80% (only 20% of the consumers will reject the product), the sensory shelf life varied as follows: 156 h at 10 \({}^{\circ}\)C (19% failure), 72 h at 20 \({}^{\circ}\)C (18% failure), 36 h at 30 \({}^{\circ}\)C (18.6% failure) and 20 h at 40 \({}^{\circ}\)C (15.5% failure). In other words, it seems that preservation of the orange juice at 10 \({}^{\circ}\)C facilitated an adequate sensory and microbiologically safe shelf life. However, it is very useful and crucial that these data on the sensory failure (rejection) rate assessment of products be linked with objective instrumental measurement [27]. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Temperature Level (\({}^{\circ}\)C)** & **Median Time (h)** & **Days** & **–95\%** & **+95\%** & **25\%** & **75\%** \\
10 & 364 & 15.2 & 312 & 364 & 208 & 364 \\
20 & 144 & 6.0 & 120 & 168 & 96 & 168 \\
30 & 72 & 3.0 & 48 & 84 & 48 & 84 \\
40 & 50 & 2.1 & 40 & 60 & 30 & 70 \\ Combined & 120 & & 84 & 144 & 52 & 312 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Sensory shelf life of pasteurized orange juice at different temperature levels. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Homogeneity** & \(\chi\)**2** & **DF** & \(\mathbf{p}\) \\ \hline Log-rank & 153.12 & 3 & \textless{}0.0001 \\ Kruskal–Wallis & 110.82 & 3 & \textless{}0.0001 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Homogeneity test of survival data between temperature levels. As an alternative approach, various regression models were attempted (exponential, weibull, lognormal), which revealed lognormal as the best fit performed at each temperature level (Figure 2). Although the study points were not scattered equally on either side of the regression lines at all temperature levels (Figure 2), the estimates of the average shelf life in the table of parameters of the lognormal distribution yielded comparatively reliable results. In particular, the lognormal values of the survival times (h) were very close to those of the exponential model and thus indicated a second reliable model for fitting and predicting the sensory shelf-life data (Table 9). After applying the log-normal transformation, the fitted distributions of the analytical characteristics of survival time were obtained (Figure 3): At 80% survival, the shelf-life curves of the two highest temperatures started to differentiate remarkably with a 10-h difference from 40 to 30 \({}^{\circ}\)C, which doubled at 50% survival. Furthermore, at 20 and 10 \({}^{\circ}\)C and at 80% survival rate, the difference was significant (approximately 80 and 180 h, respectively) and became very large at 50% (approximately 175 and 300 h, respectively) (Figure 3a). This is in agreement with the results found by [PERSON] et al. (2016) [16], where it was observed that acceptability rates do not have the same extrapolation with temperature  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Temperature** & & & & & & & \\
**Level (\({}^{\circ}\)C)** & **Sheff Life (h)** & **Survival** & **Failure** & **SE** & **Number** & **Number** & **Passed** & **at Risk** \\ \hline \multirow{9}{*}{10} & 0 & 1 & 0 & 0 & 0 & 0 & 66 \\  & 52 & 0.91 & 0.09 & 0.04 & 6 & 3 & 66 \\  & 104 & 0.86 & 0.14  
levels. In the density distribution graph (Figure 3b), the peak of the 40 \({}^{\circ}\)C density curve was observed at 28 h, and, respectively, at 38, 76 and 150 h at the other temperature levels, showing the strong effect of heat stress on sensory shelf life, the magnitude of which was determined by the area occupied by the distribution spreads in the shelf life, which were very limited at high temperatures (30, 40 \({}^{\circ}\)C) and extended at lower temperatures (Figure 3b). The risk rate showed initially a steep upward trend at higher temperatures and peaked in less than 80 h, in contrast to the lower temperatures that showed a lower rate, which was extremely low at 10 \({}^{\circ}\)C (Figure 3c).