Digital technology enablers for resilient and customer driven food value chains

Food production chains have to respond to disrupted global markets and dynamic customer demands. They are coming under pressure to move from a supply to a demand-driven business model. The inherent difficulties in the lifecycle management of food products, their perishable nature, the volatility in global and regional supplier and customer markets, and the mix of objective and subjective drivers of customer demand and satisfaction, compose a challenging food production landscape. Businesses need to navigate through dynamically evolving operational risks and ensure targeted performance in terms of supply chain resilience and agility, as well as transparency and product assurance. While the industrial transition to digitalised and automated food production chains is seen as a response to such challenges, the contribution of industry 4.0 technology enablers towards this aim is not sufficiently well understood. This paper outlines the key features of high performing food production chains and performs a mapping between them and enabling technologies. As digitalisation initiatives gain priority, such mapping can help with the prioritisation of technology enablers on delivering key aspects of high performing food production chains

Food traceability: New trends and recent advances. A review

Current traceability systems are characterized by the inability to link food chains records, inaccuracy and errors in records and delays in obtaining essential data, which are fundamental in case of food outbreak disease; these systems should address the recall and withdraw of non-consumable products. The present paper provides a review of the various latest technological advancements such as innovative implementations of RFID that can make to increase the sales of wheat flour, or allowing the consumer to know the full record of the IV range products through the smartphone knowing the food authenticity with an isotope analysis or by analysing the DNA sequences. There are also presented some conceptual advancements in the field of food traceability such as the development of a common framework towards unifying the present technical regulations, the interconnectivity between agents, environment loggers and products, all of them in the form of Internet of things system as well as the development of intelligent traceability, where it is possible to retrieve the temperature of a product or its remaining shelf-life.These new techniques and concepts provide new opportunities for enhancing the efficiency and compatibility of the present traceability systems

Explorative study of using infrared imaging for temperature measurement of pallet of fresh produce

Food industry is currently using thermal imaging to measure temperature of fresh produce, but there is no comparative study between temperatures measured traditionally by temperature probes and the temperatures measured by thermal imaging reported in the literature. This paper is exploring the possibility to use surface temperature measured by infrared (IR) thermal imaging versus temperatures measured by a network of temperature sensors. Two different types of vegetables (chard and cucumber) were covered with three different types of covers (Tyvek material, Metalized PET and Metalized PET with bubble wrap layer) which are designed to protect shipments of produce against temperature abuses. Each cover/produce combination was exposed to a temperature warm up regime in order to simulate a break in the cold chain during distribution, and it was monitored with the thermal IR camera and temperature sensors for comparisons. Results of temperature measured by thermal imaging showed a differential between 1.9 and 6 °C compared to temperature measured by thermal sensors. These found differences are unacceptable for fresh produce temperature control. The high emissivity of metalized PET produced significant reading errors when using the IR camera. Tyvek cover had more consistent results due to a higher emissivity value that is closer to the value used by the IR camera. This study is of great value since it is giving instructions of how the thermal camera should be used for temperature measurements for covered pallets.The authors would like to express their thanks for the help of Jose Luis Pellon Gonzalez, and the Laboratory of Refrigeration, in the ETSIAAB (School of Agricultural, Food and Biosystems Engineering). Also, we would like to thank the farmers of Villa del Prado (Madrid) for providing the cucumbers, and the Agricultural Research Center of Marchamalo (Guadalajara) for providing the chard.Peer Reviewe

New trends in cold chain monitoring applications - A review

Current global food supply chains are faced with an ever increasing variety of modern day societal challenges. As a direct result of these challenges many of these supply chains are operating in a “below ideal” state, resulting in approximately one third of the food produced for human consumption being wasted across the globe. A key contributory factor to such high waste is an inability to control/monitor temperature across global food supply networks. This is an issue that needs to be addressed both nationally and internationally to meet the complex challenges surrounding modern day food security, safety and integrity. There is no one single “one solution fits all” approach when it comes to addressing cold chain inefficiencies. Latest cold chain technologies, their respective advantages and disadvantages, applied to the industry are presented in the present work. Technological solutions including Radio Frequency (RF) technologies and Wireless Sensor Networks (WSN) are discussed within this manuscript. Their key success metric is their strategic complementarity, give the fact WSN lacks robustness and Radio Frequency Identification (RFID) lacks reading range and possess limited sensing systems. Other solutions discussed include temperature estimation methods for reducing the numbers of sensors deployed, when comparing them, Neural Networks showed better approximations than Kriging and Capacitor methods given the non-linear relationship between the temperature target and the temperature source. Computational Fluid Dynamics is also presented as a commercial method to correct inefficiencies at pre-cooling stages. Thermal imaging (thermal infra-red camera) have proven to be a good temperature source for the Neural Network in temperature estimation. This article also focuses on and emphasizes the importance of a technological Internet-of-Things approach, given the fact it is key in facilitating the information exchange between items in the cold chain, RF technologies and WSN can interconnect the data and those items, and make them accessible in databases associating hardware and software. There are a number of challenges to consider when adopting any/all of the systems outlined in this manuscript. It is important to highlight however, as with all solutions there exists no single “out of the box” solution due to the fact that the composition of product, transport route, method of transport and process efficiency varies greatly across products around the globe. Each technology, in isolation, is limited in its impact and challenged in both functional capabilities and performance, however when adopted in combination these technologies offer significant value add improvement in supply chain management.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland under Grant Number 16/IFB/4439.Peer Reviewe

Assessing the dynamic behavior of WSN motes and RFID semi-passive tags for temperature monitoring

Wireless Sensor Networks (WSN) and Radio Frequency Identification (RFID) are two wireless technologies that are being used for cold chain monitoring and tracking. Several applications in this field have been reported in the last few years. However, there are no studies about the the dynamic behavior of this hardware and how this affects the measurements. Therefore the purpose of this study is to evaluate the dynamic behavior of the sensors. A series of trials were designed and performed, covering temperature steps between cold chamber (5°C), room temperature (23°C) and heated environment (35°C). Three WSN motes, with different sensor configurations, and four RFID tags (with and without housing), were compared. In order to assess the dynamic behavior two alternative methods have been applied for adjusting experimental data to a first order dynamic response that allows extracting the time response (τ) and corresponding determination coefficient (r2). The shortest response time (10.4s) is found for one of the RFID semi-passive tags. Its encapsulated version provides a significantly higher response (60.0s), both times are obtained with the same method. The longest τ corresponds to one of the sensors embedded in a WSN mote (308.2s). We found that the dynamic response of temperature sensors within wireless and RFID nodes is dramatically influenced by the way they are housed (to protect them from the environment); its characterization is basically to allow monitoring of high rate temperature changes and to certify the cold chain. © 2014 Elsevier B.V.Peer Reviewe