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Decreased O2 and slightly increased CO2 partial pressures of controlled atmosphere (CA) storage slow down the postharvest respiration processes of pear and apple fruit and, therefore, ensure their year round availability. While the O2 partial pressures of the storage atmosphere can be precisely controlled, gas diffusion resistance of the fruit tissue and O2 consumption may create too low O2 levels inside the fruit, potentially leading to the development of internal physiological disorders. To understand the effect of hypoxic storage on the physiology of the fruit, the O2 level inside the fruit needs to be known. A modeling approach is so far the best option since the direct measurement of internal gas concentration of fruit is destructive and not practical. Available gas transport models for O2 typically assume a homogeneous gas transport parameter. However, there is now evidence that fruit tissue microstructure is quite heterogeneous over the entire fruit and this would likely result in a heterogeneous gas diffusivity. In this dissertation, the heterogeneity of the tissue microstructure is mapped based on X-ray computed tomography (CT) images and integrated into existing respiratory gas exchange models to investigate its effect on the O2 concentration inside the fruit.A method was developed to create three dimensional (3D) porosity maps. The method was based on a regression model between the grayscale intensity of low resolution CT images and the actual tissue porosity at identical locations. The latter was calculated from high resolution CT images of the same tissue in which pores and cells could be distinguished. The model was constructed for four products that have considerably different tissue microstructures; pear, apple, eggplant and turnip. Grayscale values of juice of the sample and air representing 0 and 100 % porosity, respectively, were included in the data as extreme values. Using the model, the porosity distribution could be mapped based on juice scans only. The constructed porosity maps reflect the heterogeneity of the tissue microstructure both within and between products.The porosity mapping method was then extended to create effective O2 diffusivity maps. A model for relating the effective O2 diffusivity to the total porosity was developed for the same products. The model did not predict the O2 diffusivity well in regions with low connectivity and/or high tortuosity of the pore microstructure. The relationship between the O2 diffusivity and the open porosity and tortuosity was, therefore, also explored. The O2 diffusivity was calculated based on a microscale gas transport model; the total and open porosity and tortuosity were derived from segmented high resolution images of tissues sampled along radial direction of the product. The O2 diffusivity correlated better with the open than total porosity. The addition of the tortuosity in the model did not improve the fit of the correlation. For eggplant and turnip the model based on total porosity was sufficiently accurate as these products consist of more open and less tortuous pores. On the other hand, better results were obtained with the model based on open porosity for pear and apple which have less open channels. An open porosity map was, therefore, estimated for intact apple and pear fruit using a regression model between total porosity and open porosity. Finally, maps of effective O2 diffusivity coefficients were calculated for apple, pear, eggplant and turnip based on the previously created porosity maps.The O2 diffusivity maps were then used to study gas transport in 'Conference' pear and its impact on internal browning. Late harvested pear fruit were stored under CA with browning-inducing conditions: no pre-cooling period, 0.5 kPa O2, 0.7 kPa CO2 at 1 oC. Porosity and effective O2 diffusivity distributions were mapped in pears before and after storage using the developed methods. The effective CO2 diffusivity were used in respiratory gas exchange calculations to obtain the spatial distribution of the O2 and CO2 concentration and the respiratory quotient (RQ) in the fruit. The resulting concentration contours were quite heterogeneous and the low oxygen concentrations and high RQ values found in the core region of the fruit indicated the occurrence of fermentation. Moreover, the gas concentration and RQ contours corresponded well with tissue that was affected by browning and cavities after 8-months storage. In contrast, when homogeneous O2 and CO2 diffusivities were used for computing the internal gas and RQ distributions, smooth contours were obtained that did not correspond to contours of the tissue affected by browning and cavities; nowhere the thresholds indicative for the development of browning were exceeded.In future research, the porosity mapping technique may be integrated into inline systems of fruit quality sorting based on X-ray radiography and tomography, although this will require significant further research in terms of optimizing speed and cost of the systems and development of adequate processing algorithm for inline applications. For the diffusivity mapping, more complex multiphase transport models and orthotropic diffusivity tensors should be considered to describe gas transport more appropriately, compared to a local isotropic diffusivity. Furthermore, the gas transport models should be validated using appropriate methods. The developed and validated models can then be extended to other respiration-related gasses. Finally, browning-related change of respiration, tissue microstructure and, inherently, effective tissue diffusivity during storage should be further investigated to explore the dynamic change of internal gas distribution.

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Pome fruit, as well as all other fruit and vegetables, are a source of vital food constituents such as proteins, vitamins, polysaccharides, phenolics and minerals. In 2018, the trade of apple and pear at the auctions of the Association of Belgian Horticultural Cooperatives (VBT) amounted to 100 000 and 180 000 tons, respectively, corresponding to a collective turnover of 130 million EUR.Since fruit start to deteriorate after harvest due to respiration and associated metabolic processes, they are commonly stored under conditions of low temperature, decreased O2 partial pressure and slightly increased CO2 partial pressure (controlled atmosphere storage, CA) to optimally maintain their quality. When the O2 partial pressure during storage becomes too low, however, the fermentation pathway becomes dominant which leads to off-flavors and the development of storage disorders. For this reason, O2 and CO2 levels during CA are kept at safe and steady, but suboptimal setpoints that may be above or below the critical levels. The application of CA storage, however, causes an important challenge towards fruit batches from different origins and seasons. Respiration rate, fruit size and tissue structure may be different between fruit and batches, affecting internal gas gradients. In general, more ripe, larger and more dense fruit are more sensitive to low O2 partial pressures compared to less ripe, smaller and porous fruit. Computer models are available to study the effect of these parameters on the physiology of fruit stored under CA and to optimize the storage protocol. These models assume material properties such as gas diffusivities that are homogenous throughout the fruit. However, the microstructure of fruit tissue is quite heterogeneous and this may very well affect gas transport considerably. So far, however, no model is available that takes into account the complete heterogeneity of tissue microstructure. The objective of this dissertation was, therefore, to quantify the heterogeneity of apple tissue and to incorporate it into existing models for gas transport in apple.Existing models to describe gas transport in pome fruit use a single phase formulation. This formulation uses an effective diffusivity, either obtained from experiments or from a microscale simulation of gas transfer through cells and pores in small tissue samples. This single phase formulation in essence also assumes equilibrium between pores and cells everywhere in the apple. Still, the rate of gas transport is significantly different in these two phases and, therefore, a two-phase multicomponent multiscale model may be more appropriate, solving gas transport in the pores and cells with separate equations, and interphase transport between them. In a first step towards achieving such a model, a two-phase formulation was proposed in Chapter 3. The two-phase formulation contains two effective diffusivity values per gas species, one for pores and one for cells, and an additional interphase transfer term that is a function of microstructural parameters obtained from micro-CT analysis. It was assumed that the effective diffusivity values, like in the single phase model, can be obtained from 3D microscale simulations on the tissue geometries of the micro-CT scans. This model in principle allows also non-equilibrium conditions between the two phases inside apples. Previously developed models for similar applications showed that, besides the interphase transfer term, additional terms occur in the two-phase model that describe diffusion phenomena at the interface of pores and cells. Based on what was suggested in literature, these additional terms were lumped into the effective diffusivities of the separate phases. The proposed two-phase multiscale model was evaluated for steady-state conditions using in silico experiments and was found sufficiently accurate for the purposes of this dissertation. O2 diffusion in 'Jonagold' apples stored in CA conditions was evaluated with the two-phase model and results showed that equilibrium conditions were satisfied. Afterwards, the sensitivity of the two-phase model was checked towards: (i), open porosity in the cortex samples; (ii), tissue respiration; and (iii), interphase resistance. The former two had significant effects on the O2 distribution inside the apple. Increasing the interphase resistance significantly, on the other hand, had a small effect on the average O2 distribution, but resulted in non-equilibrium O2 concentrations between the pore and cell phase.In Chapter 4, X-ray CT scans of intact 'Braeburn' apples with unprecedented resolution were made to visualize the internal microstructure of an entire apple fruit. A high microstructural variability was observed, both between different apples as well as within a single fruit. To optimize controlled atmosphere storage conditions, the effect of this heterogeneity on transport of metabolic gasses (O2, CO2) needed to be clarified. 'Braeburn' apples, who are highly susceptible to internal browning during storage, were characterized in terms of porosity distribution throughout the whole apple. These scans were used to identify different tissue compartments inside the apples. Based on the 3D connectivity of the pores, the cortex tissue was divided into a region with high porosity (HPC) and low porosity (LPC). The HPC had a porosity of 30.4 ± 2.1 % and featured relatively larger pores compared to the LPC, which had a porosity of 13.2 ± 3.3 %. On the internal boundary of the HPC and LPC, around a relative radius of 0.4, the porosity reached minimal values. A barrier to gas transport was identified at this position, where the exocarp and the main vascular tissue of the apple are situated. Furthermore, results showed that in two out of four tested apples the ovary was connected to the environment due to incomplete growth.Chapter 5 incorporated these compartments in the developed two-phase multiscale model. For each compartment, effective diffusivities were estimated and microstructural parameters were calculated. The relationship between gas diffusivity and microstructural parameters was studied and results showed that the gas diffusivity of a tissue sample did not always scale with the porosity of said sample, but rather with the ratio of the open porosity over the tortuosity. Macroscale simulations in commercial CA storage conditions showed that the O2 concentration profiles were highly variable between and within 'Braeburn' apples. Internal microstructure, and, most importantly, the open porosity, seems to vary between the apples in order to provide sufficient O2 throughout the apple. Furthermore, the results of the macroscale simulations with multiple compartments also showed that minimal O2 concentrations are not necessarily reached in the center of the 'Braeburn' apple, which can potentially have a relationship with the position of internal brown development in the cortex tissue.To further include structural heterogeneity in the modelling of gas transport, an alternative modeling approach to the two phase model was required. Hereto, a network modelling approach was studied in Chapter 6. The network model translated the pore and cell phase of the apple into individual cells and pores, represented as nodes, which made up a nodal network of the apple tissue. Compared to the multicompartment multiscale model, more detailed results towards O2 concentration profiles were found: a larger concentration gradient was found in the radial direction of 'Braeburn' apples when using the network model. Network modelling, therefore, provided a good and computationally efficient alternative to multiscale modelling to further investigate the transport of gasses in heterogeneous porous fruit such as apples.Concerning future prospects, a relatively new approach for storing fruit based on a dynamically controlled atmosphere (DCA) has triggered significant interest from the horticultural sector in Flanders and beyond. Instead of a constant setpoint for O2, the lowest O2 setpoint below which fermentation occurs is continuously searched based on the stress response of the fruit. With DCA, the occurrence of disorders and quality losses are further minimized compared to CA. The dynamic nature of the method, however, means that gas concentrations are time-dependent and can be continuously changing. In this respect, the models presented in this thesis will need to be elaborated and evaluated for transient conditions. Future work should focus on a comparison of the proposed two-phase model with the more elaborate two-phase model formulations in literature, and experimental results obtained with needle oxygen sensors or gas scattering spectroscopy measurements.

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Temperature is one of the most important factors that affect quality and shelf life aspects of meat products. Hence meat industries start controlling temperature of the meat soon after slaughter. A common way of controlling meat temperature for commercial purpose is by chilling the meat at the carcasses stage in a chiller room in which cold air circulates .After slaughter, in muscle cells biochemical reactions continue to produce energy substrates like adenosine triphosphate (ATP) for the postmortem muscle activities. The hydrolysis of ATP in turn produces heat, which can raise muscle temperature a couple of degrees above the initial body temperature of the animal, and hydrogen ions, which reduce the pH of the muscles. Thus in practice, the heat load during beef carcass chilling consists of the original body heat of the carcass and the heat that is produced due to biochemical reactions. To achieve the desired meat quality and shelf life, the rate of heat removal from a carcass during chilling needs to be controlled in such a way that the pH fall has a desired rate, while inhibiting the growth of microorganisms on the surface.At low cooling rates the glycolysis rate remains high for a longer time. The associated production of hydrogen ions favors a faster pH decline than at high cooling rates. The combination of low pH and high temperature has negative consequences on specific meat quality traits such as color. In large beef carcasses, such as is the case for the double-muscled Belgian Blue breed, it has been observed that important temperature gradients can develop during cooling which results in spatial differences in final meat quality of muscles from a single carcass. Due to the complexity of the heat and mass transfer and muscle reaction kinetics during cooling, understanding of the cooling process is limited and it has been difficult to determine experimentally more optimal cooling procedures. The main objective of this thesis was, therefore, to develop a mathematical model that calculates the temperature and pH distribution inside a beef carcass during cooling in a chiller room. The model includes the different relevant heat and mass transfer mechanisms coupled to a simple kinetics model that predicts postmortem glycogen conversion, heat production and pH fall. The model was validated for chilling of Belgian Blue beef carcasses as affected by temperature, relative humidity and air velocity in the chiller room. The coupled model was then used for exploring different cooling scenarios.The kinetics model was developed for the muscle energy metabolism in postmortem conditions. A single equation model described the glycogen conversion using Michaelis-Menten kinetics. The model parameters were identified using pH and temperature measurements conducted on inner and outer positions of M. biceps femoris of large Belgian Blue carcasses at different commercial slaughterhouses and for two distinct cooling rates.The developed kinetics model was then integrated with a computational fluid dynamics model (CFD) to predict changes in temperature, pH and heat generation rate during the chilling of beef carcasses. The chilling model accounted for the slaughter floor environment and chiller room conditions and was solved on the 3D geometry of a beef carcass obtained by digital scanning. A three-step approach was followed for the chiller room simulation. In the first step, a steady state simulation of the airflow and thermal field around the carcass was done. From this simulation, local convective transfer coefficients (CTCs) on the carcass surface were determined in a second step. In the third step, these CTCs were used to perform a transient heat conduction simulation within the carcass itself, including also glucose conversion, pH evolution and internal heat production. The chiller room conditions (velocity, temperature and relative humidity) were measured and used as inputs for the CFD model. The measured carcass temperature at various depths and sections was used for model validation. The temperature predictions agreed with the measured temperature profiles at different positions inside the carcass, with better prediction in deeper positions as compared to near surface positions. The simulations unveiled large differences in cooling rates and pH evolution between different parts of the carcass.The commercial slaughterhouse considered for the above simulations was the conventional chilling system where the carcasses are directly railed from slaughter floor to the chiller room. However, modern slaughterhouses operate by including a pre-chilling stage, for the purpose of extracting the initial heat load and quickly reducing surface temperature. Model based optimization was performed to identify optimum operating conditions for different chilling practices in slaughterhouses with both pre-chilling and chilling stages. The chilling practices were categorized based on the weight given to the output variables (energy consumption, weight loss, cooling time and heat shortening duration) during the chilling operation. The values of these output variables depend on the input variables air temperature, air velocity and pre-chilling time at pre-chilling stage. The study indicated that optimum operation conditions in slaughterhouse depend on the nature of the cost variable that the operator wants to minimize and are a trade-off between adverse effects on energy use and quality.

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The seed of most agricultural crops is commonly treated with pesticides before sowing to protect the germinating seed and emerging seedling from pests and diseases. Seed treatment is a very focused chemical crop protection method, since the pesticide is applied directly onto the target, as opposed to spray treatment of the whole field and granule treatment in the furrows. Consequently, the application rates per hectare of seed treatments are relatively low. Furthermore, since sowing and crop protection are combined into one operation, the need for postemergence spraying is reduced. Despite these important advantages, however, a drawback of seed treatments has become evident in recent years. Dust particles containing the active ingredients may be unintentionally abraded from the seed coating layer after the application. This can occur during bagging, transport and handling, but the dust is mainly abraded during sowing due to friction in the planter. When vacuum-based precision planters are used, which employ a centrifugal fan to create a depression in the sowing elements for seed singulation, the abraded dust is emitted along with the exhaust airflow from the fan into the environment, where the pesticide dust can harm nontarget organisms. This phenomenon is known as dust drift. Various acute honeybee poisoning incidents have been linked with dust drift episodes during sowing of treated seed.The main objective of this research was to improve the understanding of the drift of pesticide-laden dust released during sowing, by means of a combination of experimental work and a modelling approach. First, the physicochemical properties of seed treatment dust were fully characterized. Then, a CFD model of the dust aerodynamics in controlled wind tunnel conditions was developed and validated. Ultimately, this model was elaborated for the simulation of dust drift during planting in the field, in order to assess the relative importance of the impact of planter design, dust properties and wind conditions on realistic dust drift patterns.In the first research chapter, the size, shape and internal porosity of abraded dust from treated seeds of various crops (maize, oilseed rape, wheat, rye, barley and pea) were studied by means of 3D X-ray microtomography (micro-CT). The study concluded that these dust properties are crop-dependent, likely because of differences in seed morphology and in the treatment process and recipe. Dust from maize, barley and oilseed rape seed was rather spheroid or disk-shaped, wheat dust particles were needle-shaped, and rye dust particles resembled thin flakes. Porosity increased with particle size and ranged from 0 to 80 %. In addition to the analysis of dust particle shape and porosity with micro-CT, the apparent density of the dust samples was measured with gas pycnometry. The apparent density was corrected with the porosity measurements to calculate the envelope density. The particle size distribution was determined with laser diffraction and was typically in the order of magnitude of tens to hundreds of micrometer. Ultimately, the active ingredient content was quantified with LC-MS/MS. It varied strongly between dust samples and generally decreased with particle size. The quantification of these physicochemical dust properties allowed the development of a CFD model of dust drift in controlled wind tunnel conditions.A 3D CFD model was developed that simulates the trajectories of individual seed dust particles in an airflow by continuously calculating the magnitude of the drag force and the gravitational force that act on them, based on their previously measured size, density and shape. This method is called Lagrangian particle tracking. The model was validated with wind tunnel data from the Julius Kühn-Institut (JKI). In the wind tunnel trials, three size fractions of maize seed dust were released from a point source at three different uniform wind velocities. The deposition of the dust on the ground was measured at six distances from the dust source. The maize seed dust that was used in the wind tunnel experiment was completely characterized according to the previously described methodology. Subsequently, the configurations of the wind tunnel trials were replicated in CFD and the dust deposition patterns were simulated. The agreement between the simulated dust deposition and the experimental results was sufficient for the model to be elaborated in order to simulate dust drift in realistic field conditions.In the final research chapter, 3D CAD models of seed drills were imported into the CFD model. The machine geometries were simplified and experimental air velocity measurements were applied as boundary conditions on the dust outlets. Wind was modelled as a horizontally homogeneous atmospheric boundary layer. A series of steady-state simulations with a stationary planter in the field was performed, with different wind conditions, planter designs and operating parameters, dust emission rates and physicochemical dust properties. The trajectories of the dust particles were calculated from the machine outlets to wherever the particles settled on the soil or left the computational domain. Dust particles were assumed to stick to the soil once they hit it, so secondary dust drift was neglected. Dust deposition in the field edges was calculated in postprocessing by integrating the dust mass flow rates on the soil in the driving direction, dividing the integration by the driving velocity, and considering the multiple passages of the planter in the field.The model simulates pesticide concentrations in the air during drift, and on the soil or on the neighbouring vegetation after deposition. This makes the model particularly suitable for risk assessment studies. The input parameters of the CFD model can be changed in order to compare dust drift patterns in different sowing scenarios. Environmental pesticide concentrations can be simulated in typical sowing conditions and in worst-case conditions. By taking the behaviour of honeybees in the field into account, realistic pesticide exposure levels were estimated from these environmental concentrations. Furthermore, the model can be applied to design dust drift reducing measures, such as seed drill modifications, and to evaluate their effectiveness.