Ismail Uysal

Reducing food losses by intelligent food logistics

The need to feed an ever-increasing world population makes it obligatory to reduce the millions of tons of avoidable perishable waste along the food supply chain. A considerable share of these losses is caused by non-optimal cold chain processes and management. This Theme Issue focuses on technologies, models and applications to monitor changes in the product shelf life, defined as the time remaining until the quality of a food product drops below an acceptance limit, and to plan successive chain processes and logistics accordingly to uncover and prevent invisible or latent losses in product quality, especially following the first-expired-first-out strategy for optimized matching between the remaining shelf life and the expected transport duration. This introductory article summarizes the key findings of this Theme Issue, which brings together research study results from around the world to promote intelligent food logistics. The articles include three case studies on the cold chain for berries, bananas and meat and an overview of different post-harvest treatments. Further contributions focus on the required technical solutions, such as the wireless sensor and communication system for remote quality supervision, gas sensors to detect ethylene as an indicator of unwanted ripening and volatile components to indicate mould infections. The final section of this introduction discusses how improvements in food quality can be targeted by strategic changes in the food chain.

Shelf life modelling for first-expired-first-out warehouse management.

In the supply chain of perishable food products, large losses are incurred between farm and fork. Given the limited land resources and an ever-growing population, the food supply chain is faced with the challenge of increasing its handling efficiency and minimizing post-harvest food losses. Huge value can be added by optimizing warehouse management systems, taking into account the estimated remaining shelf life of the product, and matching it to the requirements of the subsequent part of the handling chain. This contribution focuses on how model approaches estimating quality changes and remaining shelf life can be combined in optimizing first-expired-first-out cold chain management strategies for perishable products. To this end, shelf-life-related performance indicators are used to introduce remaining shelf life and product quality in the cost function when optimizing the supply chain. A combinatorial exhaustive-search algorithm is shown to be feasible as the complexity of the optimization problem is sufficiently low for the size and properties of a typical commercial cold chain. The estimated shelf life distances for a particular batch can thus be taken as a guide to optimize logistics.

Improvement in fresh fruit and vegetable logistics quality: berry logistics field studies

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.

A Biologically Plausible System Approach for Noise Robust Vowel Recognition

Present day commercial automatic speech recognition (ASR) systems still pale in comparison to the human ability to recognize speech. For decades, people tried to mimic biology for machine recognition tasks and ASR is no exception. Widely used and accepted Mel Frequency Cepstral Coefficients, for example, try to develop better filter banks by looking at the distribution of the hair cells along the basilar membrane. However, all these approaches stem only from topological and anatomical considerations. This research proposes to take this biological inspiration one step further by imitating some of the dynamical computation of our auditory system via describing a biologically plausible algorithm that exclusively utilizes spikes in both the feature extraction and recognition stages. The prototype biological system is demonstrated on voiced phonemes and preliminary results show competitive recognition performance on a vowel dataset in the presence of noise.

Time–Temperature Management Along the Food Cold Chain: A Review of Recent Developments

The cold chain is responsible for the preservation and transportation of perishable foods in the proper temperature range to slow biological decay processes and deliver safe and high-quality foods to consumers. Studies show that the efficiency of the cold chain is often less than ideal, as temperature abuses above or below the optimal product-specific temperature range occur frequently, a situation that significantly increases food waste and endangers food safety. In this work, field studies on time-temperature conditions at each critical stage of the cold chain are reviewed to assess the current state of commercial cold chains. Precooling, ground operations during transportation, storage during display at retail and in domestic refrigerators, and commercial handling practices are identified and discussed as the major weaknesses in the modern cold chain. The improvement in efficiency achieved through the measurement, analysis, and management of time-temperature conditions is reviewed, along with the accompanying technical and practical challenges delaying the implementation of such methods. A combination of prospective experimental and modeling research on precooling uniformity, responsive food inventory management systems, and cold chains in developing countries is proposed for the improvement of the cold chain at the global scale.

Non-thermal effects of radio frequency exposure on biologic pharmaceuticals for RFID applications

Radio frequency identification (RFID) has been an emerging technology over the past decade with applications ranging from simple supply chain utilizations to sensory monitoring of heat and humidity sensitive products during transportation. RFID has direct implications for the area of pharmaceutical distribution especially for temperature sensitive products where they are tagged and tracked in their shipping environment. Per FDA CPG Sec.400.210, Drugs, Radiofrequency Identification, the FDA has not allowed RFID technology to be used for drugs covered under a Biologics License Application or protein drugs covered by a New Drug Application since the potential impact of radio frequency (RF) radiation on biologics and proteins is not well documented. The intent of this study is to determine the non-thermal effects on the protein structures of biopharmaceuticals by constant exposure to radio frequency energy at different wavelengths using twice the equivalent isotropically radiated power (EIRP) allowed by FCC in the United States. As a contribution of this study, the test setup and protocol provide a fundamental and universally applicable methodology which combine the hardware to generate and radiate high power RF signals at different frequencies and a temperature controlled dark anechoic chamber where the temperature and light sensitive products can be exposed to RF radiation. Five different frequencies are used which account for the majority of commercially available RFID systems adopting high frequency (13.56 MHz) or ultra-high frequency (433 MHz, 868 MHz, 915 MHz, and 2.4 GHz) radio waves as well as active or passive tags for communication. Multiple products from different pharmaceutical companies falling under three major protein groups and their integrity after exposure to 8 Watts EIRP RF radiation for a full 24 hours are investigated. The results show that even at twice the EIRP as regulated by FCC, the effects of RF energy on the purity of all the tested biopharmaceutical proteins remain undetectable after purity and potency stability-indicating assays.

Spike-Based Feature Extraction for Noise Robust Speech Recognition Using Phase Synchrony Coding

We propose a noise robust feature extraction technique for speech signals using phase synchrony. The front-end employs a psychoacoustic cochlea model with inner hair cells to transform speech into a parallel stream of spike trains as observed in the auditory nerve fibers. The degree of phase synchrony among nerve fibers with similar characteristic frequencies is calculated to yield a feature vector which shows little degradation in response to increasing levels of noise. As a benchmark, the feature set is used in a biologically plausible model with a spike-based, liquid state machine classifier for a simple acoustic classification task. Though applied to a simplified domain, the results indicate a superior performance when compared to a conventional speech recognition system, especially at very low signal-to-noise ratios.

Tag testing methodology for RFID enabled temperature tracking and shelf life estimation

Recent advances in sensory devices using radio frequency identification (RFID) led to applications such as monitoring the temperature during the transportation of heat sensitive products where recorded data can be used to detect refrigeration equipment failure along the supply chain or estimate remaining shelf life of the product. For the project discussed in this paper, a handheld based portable RFID system is used to track the storage and transportation temperatures of perishable products using battery assisted passive temperature tags. The information from the tags is used in shelf life prediction models to estimate the remaining shelf life based on the recorded temperature data to provide a dynamic expiration date. Instead of the full application development effort, this paper focuses on the unique project requirements and challenges which led to the introduction of three novel concepts related to RFID enabled temperature tracking systems. First, due to absence of a common standard for testing RFID temperature tags, we develop a requirement driven, comprehensive testing protocol combining statistical tools and common industry standards with the help of a uniquely designed test setup to realistically simulate and evaluate the real life performances of different temperature tags. Next, a novel context based accuracy metric is derived for objective and application (such as shelf life prediction) specific comparison of different technologies. Finally, a pallet temperature estimation algorithm is developed to overcome some of the physical difficulties encountered in reading ultra-high frequency tags near the presence of metals and liquids.

Radio Frequency Interactions with Air Cargo Container Materials for Real-Time Cold Chain Monitoring

Transportation is an important part of the supply chain as goods are being transported over thousands of kilometers from their production sites to consumers thanks to increasing globalization. Many perishable items, most of which are temperature sensitive, need to be transported by air due to their short shelf life. Todays regulations do not allow RFID (radio frequency identification) to be utilized inside aircrafts during flight, but the need for real time cold chain management is pushing the air cargo industry to investigate the capabilities of this technology. Since, environmental conditions highly influence the RFID systems outcome, it is mandatory to understand the RF behavior around air cargo materials.

Towards Spike-Based Speech Processing: A Biologically Plausible Approach to Simple Acoustic Classification

Towards Spike-Based Speech Processing: A Biologically Plausible Approach to Simple Acoustic Classification Shortcomings of automatic speech recognition (ASR) applications are becoming more evident as they are more widely used in real life. The inherent non-stationarity associated with the timing of speech signals as well as the dynamical changes in the environment make the ensuing analysis and recognition extremely difficult. Researchers often turn to biology seeking clues to make better engineered systems, and ASR is no exception with the usage of feature sets such as Mel frequency cepstral coefficients, which employ filter banks similar to cochlear filter banks in frequency distribution and bandwidth. In this paper, we delve deeper into the mechanics of the human auditory system to take this biological inspiration to the next level. The main goal of this research is to investigate the computation potential of spike trains produced at the early stages of the auditory system for a simple acoustic classification task. First, various spike coding schemes from temporal to rate coding are explored, together with various spike-based encoders with various simplicity levels such as rank order coding and liquid state machine. Based on these findings, a biologically plausible system architecture is proposed for the recognition of phonetically simple acoustic signals which makes exclusive use of spikes for computation. The performance tests show superior performance on a noisy vowel data set when compared with a conventional ASR system.