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The Intelligent Container for Banana Transport Supervision and Ripening

机译：香蕉运输监管与成熟的智能容器

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Bananas differ from other fruits by the fact that a special ethylene treatment is applied in the destination country to turn 'green' into ripe bananas. Moderate differences in bunch age at harvest, transport duration and temperature have no measurableeffect on the fruit quality after ripening as long as the bananas are maintained in a mature green state with no signs of unwanted self-induced ripening (turners) before ethylene treatment. Therefore, systems for automated transport supervision should focus on the detection of turners by higher respiration activity and gas production as well as by the detection of potential hot spots caused by high respiration heat in combination with insufficient air flow through the affected pallet. Under optimal cooling conditions, the subsequent ripening process can be carried out directly in the container. This paper will focus on three topics related to meeting this challenge. Firstly, the technical system of the intelligent container for remote online supervision of transports, which has been tested during three transports of bananas from Costa Rica to Europe, but can also be used for different types of perishable products. Second, a simple heat transfer model is introduced which allows estimating index valuesfor local cooling effects and respiration activity per pallet from the measured temperature curves. The model can thereby predict the risk of hot spots. Finally, we present the first test results for container ripening of bananas. The major obstacle therein is the large amount of heat generated during the process, which is about 5 times higher than during the transportation of green bananas. We applied different modifications in the packing scheme to improve the air flow, which showed clear benefits with regard to the amount of heat removed by cooling.
机译：香蕉与其他水果的不同之处在于，目的地国采用特殊的乙烯处理，将“绿色”变成成熟的香蕉。只要香蕉在乙烯处理前保持成熟的绿色状态且没有任何不希望的自诱导成熟（转向器）的迹象，成熟时束龄的适度差异，运输时间和温度对果实的品质没有可测量的影响。因此，用于自动运输监管的系统应着重于通过提高呼吸活动和产气量来检测车工，以及通过检测高呼吸热以及通过受影响托盘的空气流量不足而引起的潜在热点。在最佳冷却条件下，可以直接在容器中进行后续的熟化过程。本文将重点讨论与应对这一挑战有关的三个主题。首先，用于远程在线运输监控的智能容器技术系统已经在从哥斯达黎加到欧洲的香蕉的三次运输中进行了测试，但也可用于不同类型的易腐产品。其次，引入了一个简单的传热模型，该模型可以根据测得的温度曲线估算局部冷却效果和每个托盘的呼吸活动的指标值。该模型从而可以预测热点的风险。最后，我们提供了香蕉容器成熟的第一个测试结果。其中的主要障碍是在加工过程中产生的大量热量，这比生香蕉运输过程中高出约5倍。我们在包装方案中应用了不同的改进以改善空气流动，这对于通过冷却除去的热量显示出明显的好处。

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