Every day, millions of tons of temperature-sensitive goods are produced, transported, stored or distributed worldwide, thus making their temperature and humidity control essential. Quality control ...and monitoring of goods during the cold chain is an increasing concern for producers, suppliers, logistic decision makers and consumers. In this paper we present the results of a combination of RFID and WSN devices in a set of studies performed in three commercial wholesale chambers of 1848 m3 with different set points and products. Up to 90 semi-passive RFID temperature loggers were installed simultaneously together with seven motes, during one week in each chamber. 3D temperature mapping charts were obtained and also the psychrometric data model from ASABE was implemented for the calculation of enthalpy changes and the absolute water content of air. Thus thank to the feedback of data, between RFID and WSN it is possible to estimate energy consumption in the cold room, water loss from the products and detect any condensation over the stored commodities.
Cold chain disruption and refrigeration failures are common issues in the logistics of perishable food products. In these cases, the use of pallet covers should be very useful, delaying the increase ...of product temperatures inside the pallets until cooling conditions are restored. However, there are no studies about the performance of pallet covers in these types of situations, which could persist for hours. This paper evaluates the performance of three different types of cold chain covers versus having no cover for three different types of vegetables (chard, cucumbers, and carrots). A refrigeration failure during the cold chain was simulated. The three covers presented an improvement in temperature loss compared to the no-cover situation, with the average time for the temperature to increase from 4 to 10 °C with a cover being a range of 214 to 506 min, while for no cover, from 162 to 211 min. Relative humidity (RH) always presented improved preservation with a cover than with no cover, except for one case. The correlation between the thermal images and sensor temperatures was also studied.
Food security is both a complex and challenging issue to resolve as it cannot be characterized or limited by geography nor defined by a single grouping, i.e., demography, education, geographic ...location or income. Currently, approximately one billion people (16% of global population) suffer from chronic hunger in a time when there is more than enough food to feed everyone on the planet. Therein lies the Food security challenge to implement an ability to deal with increasing food shortages, caused by a combination of waste and an ever expanding world population. At current levels prediction state that we must increase global food production by 70% on already over exploited finite infrastructures before 2050.
This review paper firstly introduces the concept of Food Security with an overview of its scale and depth in the context of the global food industry. It then highlights the main sources. The readership is then introduced to the key factors affecting food security and highlights the many national and international measures adopted to tackle the problem at both policy and technological level.
Food experts indicate that no one single solution will provide a sustainable food security solution into the future. Collective stakeholder engagement will prove essential in bringing about the policy changes and investment reforms required to achieve a solution. Achieving truly sustainable global food security will require a holistic systems-based approach, built on a combination of policy and technological reform, which will utilize existing systems combined with state-of-the-art technologies, techniques and best practices some of which are outlined herein.
•222 millions of tons are annually wasted in developed countries.•Increasing pressure is being placed on shrinking finite resources produce our food.•The European commission has recently committed to decrease food waste 50% by 2025, as well as the US who have adopted a national waste reduction goal by the year 2030.•We must adopt a fully coordinated global effort to achieve sustainable food security.•Technology has a significant role to play in global food security.
Shelf life of fresh fruits and vegetables is greatly influenced by environmental conditions. Increasing temperature usually results in accelerated loss of quality and shelf-life reduction, which is ...not physically visible until too late in the supply chain to adjust logistics to match shelf life. A blackberry study showed that temperatures inside pallets varied significantly and 57% of the berries arriving at the packinghouse did not have enough remaining shelf life for the longest supply routes. Yet, the advanced shelf-life loss was not physically visible. Some of those pallets would be sent on longer supply routes than necessary, creating avoidable waste. Other studies showed that variable pre-cooling at the centre of pallets resulted in physically invisible uneven shelf life. We have shown that using simple temperature measurements much waste can be avoided using 'first expiring first out'. Results from our studies showed that shelf-life prediction should not be based on a single quality factor as, depending on the temperature history, the quality attribute that limits shelf life may vary. Finally, methods to use air temperature to predict product temperature for highest shelf-life prediction accuracy in the absence of individual sensors for each monitored product have been developed. Our results show a significant reduction of up to 98% in the root-mean-square-error difference between the product temperature and air temperature when advanced estimation methods are used.
Improving the capability and resolution of monitoring perishable products during their transportation and storage is essential, but there is a key requirement it is not to increase costs or the ...number monitoring devices. Currently there lies a knowledge gap in studies on the spatial prediction and mapping of determinant parameters (e.g. temperature) for the shelf life of perishable products. Through the viewpoint of different refrigeration failure scenarios this paper investigates and compares three data estimation tools (artificial neural networks, Kriging and capacitive heat transfer) for improved food safety. Results indicate that using these techniques makes it possible to reduce the number of sensors (through estimation of temperature distribution) within an industrial scale fully loaded strawberry-shipping container, thus reducing the overall commercial cost. Using a set of eight source sensors, an average error of 0.1 °C was achieved, which represents an improvement of 97.14% in regards to the absolute error between the ambient and product temperatures. Even when using only a single container sensor as a source for prediction, with an average error of 1.49 °C there still was an improvement of 62% with regards to the same baseline. This paper demonstrates that the adoption of these technologies not only presents significant industrial value-added potential but also the data obtained can further improve cold chain strategies and reduce product losses through more accurate shelf life calculations.
•Temperature mapping and prediction is a potent tool in cold chain strategies.•ANN is the most accurate with the lowest RMSE vs other predictor methods.•Best estimation represents 97.14% of improvement vs only the ambient sensor.
Shelf life of fresh fruits and vegetables is greatly influenced by environmental conditions. Increasing temperature usually results in accelerated loss of quality and shelf-life reduction, which is ...not physically visible until too late in the supply chain to adjust logistics to match shelf life. A blackberry study showed that temperatures inside pallets varied significantly and 57% of the berries arriving at the packinghouse did not have enough remaining shelf life for the longest supply routes. Yet, the advanced shelf-life loss was not physically visible. Some of those pallets would be sent on longer supply routes than necessary, creating avoidable waste. Other studies showed that variable pre-cooling at the centre of pallets resulted in physically invisible uneven shelf life. We have shown that using simple temperature measurements much waste can be avoided using 'first expiring first out'. Results from our studies showed that shelf-life prediction should not be based on a single quality factor as, depending on the temperature history, the quality attribute that limits shelf life may vary. Finally, methods to use air temperature to predict product temperature for highest shelf-life prediction accuracy in the absence of individual sensors for each monitored product have been developed. Our results show a significant reduction of up to 98% in the root-mean-square-error difference between the product temperature and air temperature when advanced estimation methods are used.
•RFID and WSN are used for monitoring cold chain, fast temperature changes may occur.•There is no previous studies of the dynamic behavior of the devices.•This study proves that the dynamic response ...is influenced by the sensor housing.•180s is the time response difference in aerial mount vs to motherboard soldering.•Some of these devices are not able to track temperature changes faster than 308s.
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.
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