A computational fluid dynamics (CFD) simulation was developed to simulate an industrial cheese chilling process. Forced air chilling experiments were performed on blocks of agar (cheese analogue) to simulate the airflow and product arrangement in a section of an industrial cheese chilling tunnel. The flow field was solved at steady-state and decoupled from the heat transfer processes. The six blocks of agar were placed in a polystyrene test chamber that was in turn placed in an environmental testing chamber. Temperatures were measured at the surfaces and the geometric centre of the tested blocks of agar. Good agreement was observed between predicted and experimental data. Having been validated, the model was used to generate simple correlation models for predicting the volume-averaged temperature of blocks of cheddar cheese and mozzarella cheese during industrial chilling

Thermal properties are essential parameters for performing heat transfer calculations. The thermal properties of foods can have a strong dependence on temperature during thermal processing, particularly during freezing, which has posed a challenge to those attempting to develop generic models that can be applied to a wide range of foods. Ideally, thermal property models should not incorporate any parameters whose value would need to be determined by a physical measurement (since this may defeat the purpose of the model). Instead it is preferable to perform a prediction based only on composition data, in terms of the major food components. This study presents an evaluation of thermal property models requiring only composition data as inputs. It is recommended that the Additive model incorporating a new correlation equation of the specific heat capacity of water should be used for effective specific heat capacity predictions. The thermal conductivity predictions from a little-known model developed by Dul'nev and Novikov provided more accurate predictions on average than more widely known models that have been recommended in previous studies.

This study presents a 3D computational fluid dynamics (CFD) model to predict the temperature profile of bulk-packed whole chickens during forced-air freezing based on 3D computed tomography (CT) images of the chicken. The model was validated against experimental cooling data. By using the temperature-dependent thermal properties of chicken meat, the mean differences between the predicted average drumstick temperatures with corresponding experimental results were less than 1.3 degrees C for all tested conditions. Based on the validated model, a correlation was proposed to estimate the effect of operating conditions on freezing time and that correlation may be used to optimise the design of the freezing tunnel for chicken products. (C) 2020 Elsevier Ltd and IIR. All rights reserved.

The cooling of polylined bulk-packed drumsticks during forced-air freezing was examined experimentally and numerically. The experiments showed that, when contained within the liner bag, the packing arrangement of the chicken drumsticks within the tray did not have a significant impact on freezing rate. However, the presence of the liner bag had a significant impact on freezing times, increasing them by more than a factor of three. A 3D computational fluid dynamics (CFD) model to predict the temperature profile of bulk-packed drumsticks, based on 3D computed tomography images of the chicken, was also developed and validated against the experimental cooling data. By using temperature-dependent thermal properties of chicken meat, the mean differences between the predicted average drumstick temperatures and corresponding experimental results were less than 1.1°C for all tested conditions. Based on the validated model, a correlation was proposed to estimate the effect of operating conditions on freezing time and that correlation may be used to optimise the design of the freezing tunnel for chicken products.

Meat is a major component of the diets of many people around the world. Animals slaughtered for meat traditionally were immediately distributed, sold, and consumed. Preservation was unnecessary, but as surpluses began to be produced, preservation methods were required so that excess product could be held and used at a later time or at some distant location. Cooling meat with ice was an early method of preservation that did not change the form or state of the product. Freezing, a logical progression, made longer preservation possible. In many countries, locally produced frozen meat is not commercially available. However, a large proportion of the meat consumed in developed countries may have been frozen for transportation. Aging is a proteolytic breakdown of myofibrillar proteins by endogenous enzymes and is most rapid at high temperatures, a situation that arises with electrical stimulation. Temperature fluctuations during storage cause recrystallization, and this affects the subsequent drip.

A computational fluid dynamics (CFD) simulation was developed to model heat transfer of six blocks of agar in a forced air chilling process. The flow field was solved at steady-state and decoupled from the heat transfer processes. The six blocks of agar were placed in a polystyrene test chamber that mimics the airflow and product arrangement in an industrial cheese chilling tunnel. Temperatures were measured at the surfaces and the geometric centre of the tested blocks of agar. Good agreement was observed between predicted and experimental data. The local heat transfer coefficient across blocks of agar surface varied by a factor of five at the high air velocity.

Accounting for voids within food packages remains a significant challenge for designers of industrial refrigeration equipment. The aim of this work was to assess the impact of the packing arrangement (regular arrangement versus random/irregular arrangement) and the presence of a carton liner bag on freezing rates of trays of chicken legs ('drumsticks'). The freezing experiments showed that when contained within the liner bag, the packing arrangement of the chicken drumsticks within the tray did not have a significant impact on freezing rate for any of the air velocities investigated based on a 95 % confidence interval. However, the presence of the liner bag had a significant impact on freezing times, increasing them by more than a factor of three at high air velocity (4.3 m s(-1)).

Optimisation of the refrigerating system for cheese processing requires an accurate prediction of chilling time, product temperature distributions and heat flow. Many existing CFD models can provide the best predictions by directly solving the three-dimensional heat transfer problem within the product and for air flow around the product; however, they are time-consuming and not suitable for routine use. A one-dimensional numerical solution proposed by Ghraizi, Chumak, Onistchenko, and Terziev (1996) has been used to provide the quick answer to food processing engineers with a good accuracy. In this method, the partial differential equation describing one-dimensional non-linear unsteady heat conduction inside the product has been solved by a finite difference technique. The method can take into account the temperature-dependence of thermal properties of foods and a general shape factor was used to reflect the product geometry. The model was applied to a single block of cheese, and agar. Predicted results are compared to experimentally-measured temperature profiles as well as to results generated by the Food Product Modeller, FPM, software.

Microbial cross-feeding is essential for a healthy commensal bacteria community in the human gut. Here we present mathematical models that account for the various types of cross-feeding by human commensal intestinal bacteria. The model bacteria include a mixed but unknown microbial community (fecal slurry), Eubacterium hallii, Roseburia intestinalis, Roseburia inulinivorans, and Anaserostipes caccae. These mathematical models demonstrate that a carbon balance approach together with chemical kinetic analysis and parameters estimated from model fitting can be used to determine which of several potential metabolic pathways are employed by cross-feeding bacterial communities to produce their metabolites. The approach can be used to estimate growth kinetics either if the population of bacteria is known, or if the population is mixed and unknown. Based on chemical kinetic analysis, an alternative view of the metabolic pathway of E. hallii is proposed. The modeling suggested that the production of butyrate by E. hallii from lactate and acetate was a second rather than a third-order reaction. Furthermore, the process by which both R. inulinivorans and R. intestinalis degraded carbohydrates and acetate was a second order reaction, and the consumption ratio was found to be approximately 1mM FE oligofructose to 1mM acetate for both Roseburia strains. As well as estimating metabolic parameters, the approach has also suggested candidate metabolic pathways for those systems that could be tested experimentally.

This article discusses the refrigeration process models relevant to meat processing, focusing on models to predict chilling time, freezing time, and heat load, with examples of the simpler models that apply to each of these three situations. These models are used to provide essential input data for temperature-dependent processes such as microbial growth and meat aging, and to assist in designing meat processing operations and equipment.

The thermophysical properties of meat are important for many calculations in designing and operating meat processing plants. Key properties include the density of the meat, its freezing temperature, glass transition, heat capacity, enthalpy, latent heat, thermal conductivity, and moisture diffusivity. Where thermophysical properties are not readily available and a certain amount of error is acceptable, they may be estimated from composition and other data.

Pastoral farmers seek to continue to increase on-farm productivity, and to do this they need new forage options that they can adopt into their current management strategies. Four case studies show that New Zealand farmers have rapidly adopted new technologies that include forage herbs, white clovers with improved stolon growing point densities, and novel endophyte technologies. The less disruptive these technologies are to accepted farmer management strategies the greater the likelihood of adoption.

AbstractIn agro-ecosystem simulation models involving a farm, management is usually controlled through some combination of calendar- and logic-based rules. This approach has been quite successful but despite their apparent naturalness and simplicity, rules do present some difficulties in use and implementation. Even relatively simple rule sets can become quite large and difficult to follow, and they are based on the current state of the system rather than anticipating the likely future state of the system. Systems based on alternative approaches may have the capability to improve on the performance of rule-based systems and here we describe the implementation of such an alternative, called the general planner for agro-ecosystem models (GPAM), and discuss how the GPAM makes decisions in the presence of complex interactions. The GPAM works by constructing a decision tree of all possible decisions up to some defined point in the future, assessing which pathway through the decision tree leads to the best outcome, and then passing set of decisions defining that pathway to the simulation model to implement. To test its capabilities, the GPAM was instructed to control a grazing rotation in a very simple agro-ecosystem model. Tests were conducted to examine the reaction of the GPAM's performance to a range of parameters, including how far forward in time it looked when optimising the rotation length, how often it revised the rotation length plan, and how often it was allowed to change the rotation length. In all of these tests the GPAM reacted as expected and, without being provided with any prior knowledge, decided to implement the long winter rotation lengths normally used by farm managers in year-round grazing systems to make best use of limited pasture. The highest levels of animal production were obtained when the GPAM was able to make swift changes in the rotation length, when it looked further into the future when optimising the rotation length, and when it re-planned often. Initial testing indicated that the GPAM showed promise as a new way of emulating the manager in simulation models. More work is needed to assess the performance and potential of the GPAM when it is provided with imperfect or biased information on the likely future states and to allow the GPAM to manage multi-objective systems, such as when balancing production and environmental goals.