Multi-objective optimization of storage temperature of apple to minimise energy use

Low temperature storage is widely employed to increase the storage life of apples. However, the use of refrigeration accounts for up to 15% of the global use of electricity. Increasing the storage temperature by 1°C can significantly reduce the total cost of electricity during apple storage. In this study, a multi-objective optimization approach is used to suggest new storage temperature of apple, taking into consideration the cost of electricity and the quality of the apple at the end of storage. Energy use was calculated using vapor pressure compression cycle models. Apple firmness was selected as the most important quality indicator for apple grading. The quality of the apple at the end of storage was converted to money value in €, based on the current grading system of apples in Belgium. Firmness was calculated using the firmness model developed by Gwanpua et al. (2012).The objective was to optimize storage temperature by minimizing the electricity usage, while minimizing quality losses (i.e. by maximizing the money value of the apple at the end of storage). This was done for different storage duration, and also for cool rooms with different storage capacity. New storage temperatures of apple, that will reduce the use of energy, were suggested

Incorporating prior knowledge improves detection of differences in bacterial growth rate

BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate

A quality, energy and environmental assessment tool for the European cold chain

According to 5th Informatory Note on Refrigeration and Food published by the International Institute of Refrigeration, 20% of the global losses in perishable products was due to lack of refrigeration. It is expected that increased use of refrigeration to reduce these losses will help meet the increasing food demands of the growing world population. However, the use of refrigeration already accounts for about 15% of world’s electricity usage. In addition, the use of refrigeration significantly contributes to global warming via emission of CO2. In this paper, a software tool was developed to assess food quality and safety evolution, energy usage and CO2 emission of different refrigeration technologies along the European cold chain. A reference product was chosen for the main different food categories in the European cold chain. Software code to predict the products temperature using the room temperature as input, based on validated heat and mass transfer models, were written in Matlab (The Mathworks Inc., Natick, USA). Also, based on validated kinetic models for the different quality indicators of the reference products, a software code was written to calculate the quality and safety evolutions of the food product, using the predicted product temperature as input. Finally, software code to calculate the energy usage and Total Equivalent Warming Impact (TEWI) value of different refrigeration technologies was also written in Matlab. All three software codes were integrated, and a graphical user interface was developed. Using the graphical user interface, a user can tailor a cold chain scenario by adding different cold chain blocks. Each cold chain block has properties that can be modified. The tool can be used to compare different cold chains with respect to quality, safety, energy usage, and environmental impact

Optimizing precooling of large beef carcasses using a comprehensive computational fluid dynamics model

Precooling has been questioned as a suitable step in the process of beef carcass cooling. Model-based optimization was performed to identify optimum operating conditions for different heavy-muscled beef carcass cooling practices in slaughterhouses with both precooling and cooling stages. The study was conducted using a validated computational fluid dynamics model of the beef carcass cooling process. The precooling practice was optimized based on a weighted impact function taking into account energy consumption, weight loss, cooling time, and heat shortening duration. The values of these output variables were dependent on air temperature, air velocity, and precooling time. The results clearly show the benefit of using a precooling unit that operates with an optimum precooling time, cooling air temperature, and velocity. Using a weighted impact function of energy cost and quality, a precooling time of 4 hr using -30 degrees C but low air velocity (0.58 m s(-1)) appeared more beneficial than precooling using high airflow fans with high energy consumption. The eventual optimum operation conditions depend on the impact variable that the operator wants to minimize and is a trade-off between adverse effects on energy use and meat quality. Practical applications The comprehensive computational fluid dynamics model can be applied to optimize the operation and design of carcass precooling system. Carcass cooling system operators can make a choice of the impact variable they want to minimize and use the approach to determine the optimum operating condition of the cooling system. The approach can be applied to develop carcass cooling procedure that could potentially minimize the energy consumption and maximize the quality of the carcass