## 3 Results and Discussion  
### Business Flow Analysis for Cold Chain  
As presented in Figure 3, the cold chain process lasted for 16.8 h starting from picking and harvesting in the orchard and ending with on-the-shelf retail with the following stages:  
* S1: Normal transportation (about 4 h). Four boxes of fruit were harvested during non-rainy cooler times of the day (\(<\)25 \({}^{\circ}\)C) and transported from Kasic (near Zadar), Croatia to overnight cold storage in Zagreb. The peaches should be picked when they are fully ripe during dry weather and packed into boxes. The temperature, relative humidity, and CO\({}_{2}\) level varied with the ambient air and respiration heat released by fruit. The fruit quality deteriorates and senesces quickly at ambient temperature after harvest.
* S2: Unloading cargo. This process involved the unloading of the fruit from the car to the refrigerator, which lasted about 40 min. The temperature and relative humidity varied with the ambient temperature. This process should be performed fast and carefully to reduce the handling damage.
* S3: Fresh fruit cold storage (about 11 h). The fruit was stored in the refrigerator overnight. The temperature decreased rapidly and the relative humidity rose quickly in this process, resulting in the complex change of CO\({}_{2}\) levels.
* S4: Loading cargo (40 min). The fruit was loaded from the refrigerator to the car the next morning. The temperature rose, and relative humidity and CO\({}_{2}\) level decreased because of the influence of ambient air in the process.
* S5: Short normal transportation (30 min). Fruit were transported to the market. The temperature was continuously rising to the ambient temperature level, and the relative humidity and CO\({}_{2}\) level were falling continuously.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **Temperature Range** & **Humidity Range** & **Volume of CO\({}_{2}\)** & **GPS Module** \\ \hline Theoretical range & \(-\)2 \({}^{\circ}\)C-36 \({}^{\circ}\)C & 50\%–95\% & 0\%–5\% & Maximum height: 50,000 m \\ Sensor module & AM2322 & AM2322 & ATI & U-BLOX M8030 \\ Sensor range & \(-\)40 \({}^{\circ}\)C-80 \({}^{\circ}\)C & 0\%–99.9\% & 0\%–5\% & WGS-84 \\ Sensor accuracy & \(<\)\(\pm\)0.3 \({}^{\circ}\)C & \(\pm\)2\% & \(\pm\)0.1\% & Speed error \(<\) 0.1 m/s, \\  & & & & direction error \(<\) 0.5 degrees \\ Response time & 5 s & 5 s & \(<\)30 s & Time accuracy: 30 ns \\ Power consumption & \(<\)0.1 mW & \(<\)0.1 mW & \(<\)25 mW & \(<\)35 mW \\ \hline \hline \end{tabular}
\end{table}
Table 1: Monitoring parameters for peach and nectarine cold-chain.  
S6: Display and sale (several days). The fruit were simulated as being displayed and sold by wholesalers or retailers. The temperature, relative humidity, and CO\({}_{2}\) level varied with the ambient temperature.  
The information flow from segment k \(-\) 1 to segment k + 1 is also showed in Figure 3. The output of segment k \(-\) 1 is the input of segment k. The output of segment k is not only significantly affected by temperature, relative humidity, and CO\({}_{2}\) level, but is also affected by the input of the segment. As such, the dynamic changes of temperature, relative humidity, and CO\({}_{2}\) level need to be real-time monitored and analyzed in detail in each of the six stages.