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Digital twins enable the quantification of the trade-offs in maintaining citrus quality and marketability in the refrigerated supply chain
Nature Food ( IF 23.2 ) Pub Date : 2022-06-02 , DOI: 10.1038/s43016-022-00497-9
Chandrima Shrivastava 1, 2 , Tarl Berry 3 , Paul Cronje 3 , Seraina Schudel 1 , Thijs Defraeye 1
Affiliation  

Supply chains of fresh fruit must maintain a very narrow window of hygrothermal conditions after harvest. Any excursions outside this range can markedly lower the consumer acceptability of the fruit. However, the loss in fruit quality and marketability largely remains invisible to stakeholders throughout the supply chain. Here we developed a physics-based digital twin of citrus fruit to pinpoint when, why and to what extent fruit quality and marketability are reduced. Sensor data on 47 commercial shipments are thereby translated into actionable metrics for supply chain stakeholders by mapping the variability using principal component analysis. We unveiled a large spread (between 3% and 60%) in the shipments for different metrics of quality and marketability. Half of the shipments currently lie outside the ideal trade-off range between maintaining quality, killing fruit fly larvae and avoiding chilling injury. The digital twin technology opens the possibility to obtain the real-time coupling with sensor data to monitor food quality and marketability.



中文翻译:

数字孪生能够量化在冷藏供应链中保持柑橘质量和适销性的权衡

新鲜水果的供应链必须在收获后保持非常窄的湿热条件窗口。超出此范围的任何偏差都会显着降低消费者对水果的接受度。然而,整个供应链的利益相关者在很大程度上仍然看不到水果质量和适销性的损失。在这里,我们开发了一个基于物理学的柑橘类水果数字双胞胎,以查明水果质量和适销性下降的时间、原因和程度。通过使用主成分分析映射可变性,从而将 47 次商业货运的传感器数据转化为供应链利益相关者可操作的指标。我们公布了不同质量和适销性指标的出货量差异很大(在 3% 到 60% 之间)。目前有一半的货物处于保持质量、杀死果蝇幼虫和避免冷害之间的理想权衡范围之外。数字孪生技术开启了与传感器数据实时耦合以监控食品质量和适销性的可能性。

更新日期:2022-06-02
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