Kim Tae-Hyeon, Jung Jae-Min, Lee Wang-Hee
Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Republic of Korea.
Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.
Foods. 2025 Jan 13;14(2):227. doi: 10.3390/foods14020227.
According to the concept of smart postharvest management, an information and communication technology sensor-based monitoring system is required in the juicing process to reduce losses and improve process efficiency. Such technologies are considered economically burdensome and technically challenging for small-scale enterprises to adopt. From this perspective, this study aimed to develop a smart monitoring system for the juicing processes in small-scale enterprises and to identify the optimal operating conditions based on the monitoring data. The system developed is equipped with two weight sensors attached to the twin-screw juice extractor, allowing for the automatic measurement of the weight of the raw material and the resulting juice product. The measured data are automatically transmitted and stored on a computer. Additionally, the system was designed to remotely control the speeds of the juicing and feeding screws, which are the primary controlling factors of the twin-screw juicer. Juice yield and processing time were optimized using carrots and pears. The optimal juicing and feeding speeds for pear yield were found to be 167.4 rpm and 1557 rpm, respectively; carrots achieved an optimal yield at a juicing speed of 502.2 rpm and feeding speed of 1211 rpm. In contrast, the processing time was minimized at juicing-feeding speeds of 6-6 and 7-5 for pears and carrots, respectively. Consequently, it was challenging to determine the optimal conditions for simultaneously optimizing the yield and processing time. This also suggests that the juicing process is affected by the properties of the fruits and vegetables being processed. By developing a system capable of accumulating the data necessary for the digitization of postharvest management and food processing, this research offers a valuable platform for the smart monitoring and optimization of the juicing process.
根据智能采后管理的概念,在榨汁过程中需要一个基于信息通信技术传感器的监测系统,以减少损失并提高加工效率。对于小规模企业来说,采用此类技术在经济上被认为负担沉重,在技术上也具有挑战性。从这个角度来看,本研究旨在开发一个针对小规模企业榨汁过程的智能监测系统,并根据监测数据确定最佳操作条件。所开发的系统在双螺杆榨汁机上安装了两个重量传感器,能够自动测量原材料和所得果汁产品的重量。测量数据会自动传输并存储在计算机上。此外,该系统设计用于远程控制榨汁螺杆和进料螺杆的速度,这两个螺杆是双螺杆榨汁机的主要控制因素。使用胡萝卜和梨对出汁率和加工时间进行了优化。发现梨的最佳榨汁速度和进料速度分别为167.4转/分钟和1557转/分钟;胡萝卜在榨汁速度为502.2转/分钟和进料速度为1211转/分钟时达到最佳出汁率。相比之下,梨和胡萝卜分别在榨汁-进料速度为6-6和7-5时加工时间最短。因此,要确定同时优化出汁率和加工时间的最佳条件具有挑战性。这也表明榨汁过程受所加工水果和蔬菜特性的影响。通过开发一个能够积累采后管理和食品加工数字化所需数据的系统,本研究为榨汁过程的智能监测和优化提供了一个有价值的平台。