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Refrigerated transport and storage of mango fruit are essential to maintain quality, reduce food waste and the associated embodied energy losses. Refrigeration is also key to enable successful transcontinental export to distant markets. To minimize the environmental impact of the cold chain and to optimize logistics, a better knowledge of the fruit quality evolution within individual shipments would be extremely valueable. For this purpose, a digital fruit twin is developed, based on mechanistic modeling. This digital twin simulates the thermal behavior of mango fruit throughout the cold chain, based on the measured environmental temperature conditions, namely the air temperature in the vicinity of the fruit. At the same time, the evolution of associated quality attributes, due to enzymatically-driven, temperature-dependent biochemical degradation reactions, is quantified. Also, a biophysical counterpart of real mango fruit – an innovative fruit simulator sensing device – was developed and used for model validation of fruit pulp temperatures. We identified – in-silico – the impact of the unique delivery air temperature history and cold chain length on fruit quality evolution for actual maritime vs. airfreight transport pathways. Digital twins were found to provide complementary insights in the thermophysical behavior of fruit, particularly in supply chains of very perishable species, and for storage at low airflow rates. Such mechanistic modeling enabled to understand, record, and predict where temperature-dependent fruit quality loss occurs in each supply chain. In that way, digital twins can help to improve refrigeration processes and logistics to reduce food losses, thereby making the refrigerated supply chain greener.

Molecular modelling, histochemistry, and micro-computed tomography reveal that the apoplastic pore size is dynamically regulated during bud burst in grapevine, and associated with oxygenation of the meristematic core., The physiological constraints on bud burst in woody perennials, including vascular development and oxygenation, remain unresolved. Both light and tissue oxygen status have emerged as important cues for vascular development in other systems; however, grapevine buds have only a facultative light requirement, and data on the tissue oxygen status have been confounded by the spatial variability within the bud. Here, we analysed apoplastic development at early stages of grapevine bud burst and combined molecular modelling with histochemical techniques to determine the pore size of cell walls in grapevine buds. The data demonstrate that quiescent grapevine buds were impermeable to apoplastic dyes (acid fuchsin and eosin Y) until after bud burst was established. The molecular exclusion size was calculated to be 2.1 nm, which would exclude most macromolecules except simple sugars and phytohormones until after bud burst. We used micro-computed tomography to demonstrate that tissue oxygen partial pressure data correlated well with structural heterogeneity of the bud and differences in tissue density, confirming that the primary bud complex becomes rapidly and preferentially oxygenated during bud burst. Taken together, our results reveal that the apoplastic porosity is highly regulated during the early stages of bud burst, suggesting a role for vascular development in the initial, rapid oxygenation of the primary bud complex.

Frozen vegetables are often exposed to dynamic temperature conditions during cold storage and distribution chain. The resulting ice recrystallization leads to microstructural changes, which is directly linked to the final vegetable quality. To this end, X-ray µCT was applied to visualize and quantify 3D ice crystal changes in carrot over a period of two months of frozen storage with dynamically changing temperature. The studied conditions revealed a significant increase in ice crystal size during the storage period. The mean equivalent diameter of the ice crystals increased from 246 ± 15.9 µm, to 342 ± 13.2 µm, 394 ± 18.5 µm, 525 ± 28.0 µm and 578 ± 27.6 µm at 0 d, 7 d, 14 d, 30 d and 60 d of storage, respectively, while the number of ice crystals decreased. The 3D data on the ice crystals and image analysis presented within this paper provide an insight making it possible to describe microstructure evolution, and for better control cold storage sector of frozen vegetables. ispartof: Journal Of Food Engineering vol:246 pages:232-241 status: published

Fruit and vegetables have a considerable variability in porosity affecting transfer phenomena caused by respiration during postharvest storage. In this study, a validated and reproducible method to calculate and map the porosity distribution in fruit and vegetable organs based on a grayscale-porosity correlation model is introduced. The method requires a water phantom for proper evaluation of X-ray computed tomography (CT) images and juices of scanned plant products for 0% porosity references. A strong correlation was found between grayscale values and porosity (R2 = 0.99) enabling to estimate the complete 3-D porosity distribution of eggplant, turnip, apple and pear using a single correlation function. The porosity maps well depicted the heterogeneity of tissue microstructure either in the individually intact product or among the samples. Porosity differences in structural details such as different tissues, seeds and vascular bundles could be clearly distinguished. In average, eggplant exhibited the most porous structure (41.8 ± 1.0%) followed by turnip (23.3 ± 3.4%), apple (19.7 ± 1.1%) and pear (4.0 ± 1.6%). The developed method allows to predict porosity distribution of other plant products non-destructively by only including juice scans. A normalization procedure make the method effortlessly adaptable to other CT systems and products.

Optical Coherence Tomography (OCT) is an established non-destructive and contactless photonic technique which has now been shown to be suitable for monitoring the near-surface internal structure of tissues in stored fruit and vegetables. Such real-time cross-sectional imaging allows for better visualisation and understanding of the temporal changes in internal structure. However, despite these advantages, problems persist around the trade-off between imaging resolution and penetration depth, image analysis and data processing, and the applicability of in situ studies outside of the laboratory setting. This review summarises previous postharvest OCT research and assesses resulting mechanistic outcomes, and future potential.

Long term storage is required to deliver high quality pear fruit year-round. Under suboptimal storage conditions, internal disorders, such as internal browning and cavity formation, can develop and are often invisible from the outside. We present a non-destructive inspection method to quantify internal disorders in X-ray CT scans of pear fruit using a deep neural network for semantic segmentation. Herein, a U-net based model was trained to automatically indicate healthy tissue, core and regions affected by internal disorders, i.e., cavity formation and internal browning. The quantitative data resulting from the segmentations was used to measure the severity of internal disorders. Excellent classification accuracies of 99.4 and 92.2% were obtained for the classification of “consumable” vs “non-consumable” fruit on the one hand and “healthy” vs “defect but consumable” vs “non-consumable” fruit on the other hand. The identification of “defect but consumable” fruit showed to be the most difficult.

Additive manufacturing or 3D printing can be applied in the food sector to create food products with personalized properties such as shape, texture, and composition. In this article, we introduce a computer aided engineering (CAE) methodology to design 3D printed food products with tunable mechanical properties. The focus was on the Young modulus as a proxy of texture. Finite element modelling was used to establish the relationship between the Young modulus of 3D printed cookies with a honeycomb structure and their structure parameters. Wall thickness, cell size, and overall porosity were found to influence the Young modulus of the cookies and were, therefore, identified as tunable design parameters. Next, in experimental tests, it was observed that geometry deformations arose during and after 3D printing, affecting cookie structure and texture. The 3D printed cookie porosity was found to be lower than the designed one, strongly influencing the Young modulus. After identifying the changes in porosity through X-ray micro-computed tomography, a good match was observed between computational and experimental Young&rsquo, s modulus values. These results showed that changes in the geometry have to be quantified and considered to obtain a reliable prediction of the Young modulus of the 3D printed cookies.

Food process modeling has matured with the development of multiscale, multiphase and multi-physics approaches. More comprehensive numerical tools and software platforms for improving insights and optimizing designs and processes have emerged. In the context of industrial digitalization and the advent of the Internet of Things, the concept of the digital twin has recently emerged as a means for more versatile process operational management. The digital twin is defined as a virtual replica of the real process operation, which is connected to the real world by sensor data and advanced big data analytical tools. While all elements are available for implementing digital twins, with the different types of models playing a central role, it will require a multidisciplinary approach for successful implementation and operation. The first agrofood applications still need to be demonstrated. This paper mainly focusses on the role more physics-based models can play, in addition to data-driven and hybrid models.

Ice recrystallization occurring in vegetables during frozen storage causes changes in crystal morphology, and, thus, may affect product microstructure and quality. A mathematical model to describe the evolution of the crystal number density in frozen carrot tissue during dynamically changing temperatures was introduced to get a more comprehensive insight into microstructural changes. The model was based on a population balance equation that incorporated the ice crystal size distribution and a lumped heat transfer model, which assumed ice recrystallization via Ostwald ripening. Ice recrystallization was governed first by the dissolution of small crystals and then by redeposition at the surface of large crystals. This was observed mainly at the beginning of storage and gradually decreased as storage time proceeded. Sensitivity analysis showed that the activation energy is the most important model parameter, followed by the growth and dissolution coefficients. The model was validated based on measurements of the ice crystal size distribution and mean ice crystal size of carrot tissue to describe ice recrystallization during a two-month storage period under dynamically changing temperature condition. The PBE model was then applied to simulate ice recrystallization in carrots under industrial relevant conditions. The simulation results indicate that PBE model may be used to improve storage of frozen vegetables with respect to microstructure and quality. ispartof: JOURNAL OF FOOD ENGINEERING vol:278 status: published

Powder-based 3D printing was employed to produce porous, capillarity-based devices suitable for passive microfluidics. Capillary imbibition in such devices was visualized in situ through dynamic synchrotron X-ray microtomography performed at the European Synchrotron Radiation Facility (ESRF) with sub-second time resolution. The obtained reconstructed images were segmented to observe imbibition dynamics, as well as to compute the system effective contact angle and to generate a pore-network to model capillary imbibition. A contact angle gradient was observed resulting in a preferential wicking direction, with the central portion of the microfluidic channel filling faster than the edge areas. The contact angle analysis and the pore-network model results suggest that this is due to spatial variations in the material surface properties arising from both the 3D printing and the subsequent drying processes.

To preserve the quality of fresh pear fruit after harvest and deliver quality fruit year-round a controlled supply chain and long-term storage are applied. During storage, however, internal disorders can develop due to suboptimal storage conditions that may not cause externally visible symptoms. This makes them impossible to be detected by current commercial quality grading systems in a reliable and non-destructive way. A combination of a Support Vector Machine coupled with a feature extraction algorithm and X-ray Computed Tomography is proposed to successfully detect internal disorders in ‘Conference’ and ‘Cepuna’ pear fruit nondestructively. Classifiers were able to distinguish defective from sound fruit with classification accuracies ranging between 90.2 and 95.1% depending on the cultivar and number of used features. Moreover, low false positive and negative rates were obtained, respectively ranging between 0.0 and 6.7%, and 5.7 and 13.3%. Classifiers trained on ‘Conference’ data were transferred effectively to the ‘Cepuna’ cultivar, suggesting generalizability to other cultivars as well. With continuing developments in both hardware and software to increase inspection speed and reduce equipment costs, the method can be implemented in industrial applications, e.g., inline translational X-ray CT.

Powder-based 3D printing was employed to produce porous, capillarity-based devices suitable for passive microfluidics. Capillary imbibition in such devices was visualized in situ through dynamic synchrotron X-ray microtomography performed at the European Synchrotron Radiation Facility (ESRF) with sub-second time resolution. The obtained reconstructed images were segmented to observe imbibition dynamics, as well as to compute the system effective contact angle and to generate a pore-network to model capillary imbibition. A contact angle gradient was observed resulting in a preferential wicking direction, with the central portion of the microfluidic channel filling faster than the edge areas. The contact angle analysis and the pore-network model results suggest that this is due to spatial variations in the material surface properties arising from both the 3D printing and the subsequent drying processes. ispartof: Lab On A Chip vol:20 issue:13 pages:2403-2411 ispartof: location:England status: published

We present a passive heating system that allows controlled and localized on-chip heating, showing a huge potential for point-of-care (POC) diagnostic applications in low-resource settings. By coupling the thermal regulation properties of organic phase change materials (PCMs) to the exothermic crystallization reaction of supercooled sodium acetate trihydrate (SAT), on-chip temperature control is achieved without requiring external power supply. This enables the performance of sensitive and specific diagnostic tests in the field, which are currently restricted to laboratory environments. The presented system consists of 3 stacked microfluidic chambers (SAT, PCM, reagent), fabricated by means of a simple layer-by-layer manufacturing method using low-cost plastics. We showed that the SAT heat source was tunable between 35 and 55 °C by varying the salt fraction in the solution. A PCM was integrated between the SAT and reagent chamber to maintain temperature constant over time. Additionally, the introduction of this thermal buffer layer, increased the system its robustness to fluctuating ambient temperatures. Moreover, to facilitate the PCM and SAT chamber design optimization, a finite element model (FEM) was built to simulate the heat generation and transfer through the chip. With the optimized PCM-SAT system, a constant temperature between 37 and 42 °C was maintained for at least 15 min at different ambient temperatures (25 to 35 °C), typical conditions for a recombinase polymerase amplification assay. The ability to have simple control over both the heat release from the heat source and the regulation temperature of the PCM combined with the developed FEM, makes this system flexible to a variety of isothermal assay requirements. Moreover, the low-cost and simple fabrication method makes the system compatible with most passive microfluidic technologies (i.e., paper-based and capillary microfluidics), opening up many opportunities for integrated POC platforms. ispartof: Applied Thermal Engineering vol:173 status: Published online

We used statistical correlation functions (CFs) to describe food microstructure and to reconstruct their 3D complexity by using limited information coming from single 2D microtomographic images. Apple fleshy parenchyma tissue and muffin crumb were chosen to test the ability of the reconstructions to mimic structural diversities. Several metrics based on morphological measures and cluster functions were utilized to analyze the fidelity of reconstructions. For the apple, reconstructions are accurate enough proving that lineal, L2, and two-point, S2, functions sufficiently describe the complexity of apple tissue. Muffin structure is isotropic but statistically inhomogeneous showing at least two different porosity domains which reduced the fidelity of reconstructions. Further improvement could be obtained by using more CFs as input data and by implementation of the techniques dealing with statistical non-stationarity. Novel stochastic reconstruction and CF-based characterization methods could improve the fidelity of reconstruction and future advances of this technology will allow estimating macroscopic food properties based on (limited) 2/3D input information.

BACKGROUND The ripening of mango involves changes in texture, flavor, and color, affecting the quality of the fruit. Previous studies have investigated the physiology on the evolution of quality during ripening but only a few have looked at microstructural changes during ripening. None of them has provided an insight into the relationhip between 3-D microstructure and the evolution of quality during ripening. As the 3-D microstructure of fruit tissue determines its mechanical and gas-transport properties, it is likely to affect fruit texture, respiratory metabolism, and other ripening processes. RESULTS The present study focuses on the role of 3-D microstructural changes in relation to quality changes during mango ripening. Microstructural imaging using X-ray micro-computed tomography suggested the incidence of cell leakage, which was confirmed by the measurement of electrolyte leakage from the fruit peel. Due to cell leakage, porosity, pore connectivity, and pore local diameter were decreased whereas the tissue local diameter and pore specific area were increased. The decline in respiration and respiratory quotient during ripening followed the microstructural changes observed. Meanwhile, changes in aroma were observed such as a decrease in monoterpenes and an increase in esters and other fermentative metabolites. CONCLUSION Overall, the results provide a complete, integrated picture of microstructural changes during ripening accompanying the evolution of fruit quality, suggesting functional relationships between the two. © 2020 Society of Chemical Industry.

Printing food consists of translating any idea of shape, dimension and internal architecture into a digital model, which may be replicated to get tangible food products. An intriguing and novel approach to use 3D printing – already used in the medical fields – is the mimicking of morphological properties of biological tissues aiming to replicate their unique functionalities. For the first time, we explored this approach and by utilizing the main morphological information of apple tissue contained in the microtomographic images we have generated innovative 3D printed snacks inspired by the plant tissues. While the morphologies of the printed sample satisfactorily matched the virtual model, the porosity fraction significantly changes from ∼15% of the apple tissue to 14.4%–18.2% for printed dough and to 41.93%–45.90% for the baked snacks. Hardness increased from 0.69 N to 11.25 as a function of the number of layers while the Young's modulus did not change significantly from 20.73 to 31.84 MPa for 2 to 6 layers. Our results proved the capability of 3D printing to reproduce the salient features of apple tissue microstructure; also, after defining the main mechanical properties of the reference materials, we modelled the texture properties of 3D printed samples with sufficient agreement with the estimated and experimental data. Our results proved the capability of 3D printing to reproduce the salient features of apple tissue microstructure; also, after defining the main mechanical properties of the reference materials, we modelled the texture properties of 3D printed samples with sufficient agreement with the estimated and experimental data.

An accurate understanding of the dehydration kinetics of biological materials is essential to optimize their dehydration processes and to produce high-quality dried products. For a soft, cellular material like fruit, the underlying mass transport and deformation mechanisms at the cellular scale play a key role here. To improve our insight into the cellular scale dehydration kinetics, a 3D model is developed to quantify the impact of the changes in the cellular structure of apple (parenchyma) cells during dehydration on the tissue sorption isotherm and water permeability. As a step beyond the current state-of-the-art models, the model incorporates the changes in the cellular structure over entire dehydration process, starting from a turgid cell down to the occurrence of (free) shrinkage, plasmolysis (detachment of the cell membrane from the cell wall) or lysis (rupture of the cell membrane). Regarding the tissue sorption isotherm, plasmolysis induced a reduction in the equilibrium water content (up to 60%) compared to the free-shrinkage or lysis cases at the same water activity level. On the other hand, the tissue water permeability was found to increase up to five times when lysis occurs, compared to free shrinkage or plasmolysis. A parametric study also quantified the dependency of tissue permeability on the cell wall thickness, the cell membrane permeability, the cell size and the elongation aspect ratio of the cell. We identified that the dehydrated, shrunken cellular tissue reduces the outgoing water flux compared to fresh tissue for the same water potential gradient. As such, dehydrated tissue forms a barrier against further moisture removal from the fresh tissue below.

This study presents a novel methodology to model the cooling processes of horticultural produce using realistic product shapes rather than commonly used simplified 3D shapes, such as spheres. Variable 3D apple and pear models were created by means of a validated geometric model generator based on X-ray computed tomography images. The fruit were randomly stacked into a geometrical model of a corrugated fibreboard box using the Discrete Element Method. A forced-air cooling process was simulated for three such apple filling patterns using CFD and the results were compared to those obtained with fruit represented by equivalent spheres. No significant difference in average aerodynamic resistance between the real apple shape and its spherical representation was found. The main contributor to the overall pressure drop was the package design rather than product shape. However, large differences in local air velocity and convective heat transfer coefficients were found between the two representations. The degree of cooling uniformity between individual fruit was overestimated when using simplified product shapes: real apple fruit shapes cooled less uniform. This difference between real and simplified product shapes was even larger for a box filled with pear fruit that are more different from a spherical shape. These results demonstrate that improved computer-aided design approaches help in simulating more accurate convective cooling processes. In a next step, such simulations will be used for multiobjective optimization of packaging in terms of cold chain efficiency and cooling uniformity. ispartof: Food and Bioprocess Technology vol:11 issue:11 status: Published online

An Eulerian-Lagrangian 3D computational fluid dynamics (CFD) model of pesticide dust drift from precision vacuum planters in field conditions was developed. Tractor and planter models were positioned in an atmospheric computational domain, representing the field and its edges. Physicochemical properties of dust abraded from maize seeds (particle size, shape, porosity, density, a.i. content), dust emission rates and exhaust air velocity values at the planter fan outlets were measured experimentally and implemented in the model. The wind profile, the airflow pattern around the machines and the dust dispersion were computed. Various maize sowing scenarios with different wind conditions, dust properties, planter designs and vacuum pressures were simulated. Dust particle trajectories were calculated by means of Lagrangian particle tracking, considering nonspherical particle drag, gravity and turbulent dispersion. The dust dispersion model was previously validated with wind tunnel data. In this study, simulated pesticide concentrations in the air and on the soil in the different sowing scenarios were compared and discussed. The model predictions were similar to experimental literature data in terms of concentrations and drift distance. Pesticide exposure levels to bees during flight and foraging were estimated from the simulated concentrations. The proposed CFD model can be used in risk assessment studies and in the evaluation of dust drift mitigation measures.

A coaxial extrusion printhead was designed for 3D printing of pectin-based food simulants in which the inner flow is the food-ink and the outer a CaCl2 crosslinking solution. A series of cubic-shaped objects was successfully 3D printed by changing the printing parameters including the food-ink composition, the layer height, and the rate and CaCl2 concentration of the outer flow. The printed objects did not necessitate any incubation post-treatment because the gelation of the food-ink occurred during the printing. The mechanical properties of the printed object were correlated to their final Ca2+ concentration which can be controlled by the rate and CaCl2 concentration of the outer flow. A predictive model was established for determining the printing settings to print 3D objects with a priori defined texture. The layer height was recommended to be set in function of the food-ink swelling behavior. Finally, we compared objects printed by coaxial and simple extrusion methods. The compared objects had similar Young's moduli but their other properties including volume and final Ca2+ concentration, were considerably impacted by the printing method.

Characterization of the airflow across food items involves identification of their viscous and inertial resistances. This paper presents an extensive numerical and experimental study to determine the resistances of food items placed in an array. The experimental study used an array of sliced sweet potato with different initial slice diameters. The airflow resistance of the array was determined from a series of wind tunnel measurements. The sliced arrays were dehydrated and digital images were taken to determine the intermediate array-porosity. The numerical study was based on CFD modeling of the airflow across the disc arrays. In the simulations, the size of each individual disc in the array was gradually decreased to reproduce the array-porosity change similar to the experimental dehydration. The airflow resistance of the array was found to be dominated by inertial effects. The influence of geometrical parameters on the inertial resistance coefficient was also studied. Dimensional analysis showed that the inertial resistance was exponentially decaying with array-porosity. To describe this relationship, a model equation was proposed that fitted very well with both the experimental and numerical results. Finally, the findings of the current study were used in a porous media based modeling and simulation of the momentum transport in the dehydration of an array of sliced food items in a solar dryer.

A method was developed to correct real-time measurements of the respiratory quotient (RQ) of pome fruit for gas leakage of a cool room. The method is based on a general leakage model that was simplified by performing sensitivity analysis of the contribution of the pressure driven and concentration driven gas transport terms. The analysis showed that pressure driven leakage was dominant over diffusive leakage. The methodology was validated successfully using an empty storage container at 0.4 kPa O2 and 1.3 kPa CO2. A sensitivity analysis using virtual storage experiments showed that the error of the RQ estimates with leak correction was 0 %, while without leak correction they increased to above 700 %. Finally, the validated model was successfully implemented in an automated RQ-DCA control system using ‘Braeburn’ apple fruit (Malus ×domestica ‘Braeburn’ 2x). RQ estimates without leakage correction were heavily biased when leakage of atmospheric air into the storage container occurred and would lead to erroneous control of the storage atmosphere composition. With the developed leakage correction, RQ measurements were found to be accurate during decreasing as well as increasing atmospheric air pressure. ispartof: Postharvest Biology and Technology vol:136 pages:31-41 status: published

There is a need for more realistic monitoring of fruit pulp temperature history throughout the cold chain at a higher spatial resolution inside the cargo. Particularly solutions that are easy to install in a commercial setting are required. For this purpose, a novel kind of fruit simulator – an artificial fruit – has been designed, manufactured and tested. Using a biomimetic approach, it was engineered specifically to match the thermal response of real fruit as close as possible. The artificial fruit is composed out of a thin plastic shell, which mimics the exterior size, shape, surface texture and color of the fruit of interest. This shell is filled with a mixture that has similar thermal properties as real fruit as it is basically composed out of the same components. Two self-powered data loggers with a built-in sensor are integrated in the artificial fruit. These different components of the artificial fruit were combined successfully into a manufactured prototype. The thermal response of an artificial apple fruit during cooling was evaluated against that of 10 real apples. The cooling time of the artificial fruit was within 5% of that of the real fruits. The artificial fruit also had a more accurate thermal response than that of water-filled fruit simulators, with which differences up to 16% were found. The uniformity in size, shape and sensor location of the artificial fruit also enables it to measure fruit pulp temperature in a much more repeatable manner than with real fruit. A particular advantage of the artificial fruit is that it can be packed directly with the fresh produce in a commercial setting, by which multiple locations inside the cargo can easily be monitored. This novel sensor system thus provides an improved method to identify heterogeneities in cargo cooling, and associated quality issues. The artificial fruit is especially of interest for monitoring fruit pulp in precooling facilities, cold stores, ripening facilities and refrigerated containers.

Non-destructive imaging techniques have become indispensable to improve insights into the microstructural changes occurring in fruit tissue during freezing. Here, apple cortex tissue samples were frozen using different freezing rates: (i) slow freezing (2.0 °C per min.), (ii) intermediate freezing (12.6 °C per min.) and fast freezing (18.5 °C per min.). Temperature-controlled X-ray micro-CT was optimized and then applied to visualize and quantify the 3D microstructure and ice crystal distribution at a pixel resolution of 3.8 μm. Ice crystal size distributions with mean equivalent diameters of about 41 ± 3.5 μm, 55 ± 7.4 μm and 71 ± 9.6 μm were obtained for the fast, intermediate and slow freezing rates, respectively. A new imaging methodology was developed and validated to allow segmentation of the ice crystals in frozen apple tissue using the X-ray attenuation coefficients of the reference model samples, i.e. frozen pure water and concentrated apple juice.

A model based on enzyme kinetics was developed to predict differences in postmortem pH change in beef muscles as affected by cooling rate. For the calibration and validation of the model, pH and temperature measurements were conducted at different positions in M. biceps femoris following conventional carcass cooling or faster cooling of the muscle after hot boning. The glycogen conversion, and, hence, the pH fall, was observed to significantly vary with position and cooling regime but only during the initial hours of cooling. Comparison of the cooling regimes indicated that fast cooling following hot boning avoids heat shortening induced by the combined effect of high temperature and low pH.

© 2017, Springer Science+Business Media, LLC. A method to build a 3D statistical shape model of horticultural products is described. The framework consists of two parts. First, the surfaces of the horticultural products, which are extracted from X-ray CT scans, are registered to obtain meaningful correspondences between the surfaces. In the second part, a statistical shape model is built from these corresponded surfaces, which maps out the variability of the surfaces and allows to generate new, realistic surfaces. The proposed shape modelling method is applied to 30 Jonagold apples, 30 bell peppers, and 52 zucchini. The average geometric registration error between the original instance and the deformed reference instance is 0.015 ± 0.011 mm for the apple dataset, 0.106 ± 0.026 mm for the bell pepper dataset, and 0.027 ± 0.007 mm for the Zucchini dataset. All shape models are shown to be an excellent representation of their specific population, as they are compact and able to generalize to an unseen sample of the population. ispartof: Food and Bioprocess Technology vol:10 issue:11 pages:2100-2112 status: published

Additive manufacturing is revolutionizing processing in many applications including 3-D food printing. So far the number of suitable printable materials for food is limited and the microstructure and texture properties of 3-D printed food have been characterized poorly. This study introduces the novel concept of customizable water-based porous food simulants by 3-D printing using low methoxylated pectin gel as food-ink. A series of pectin gels was successfully 3-D printed by changing the formulation parameters including stirring rate and pectin, CaCl 2 , bovine serum albumin and sugar syrup concentrations. It was shown that food objects with variable microstructure and texture properties can be 3-D printed by using different pectin based food-inks. The pectin concentration was the main determinant of firmness and strength of the printed object. Sugar and pectin concentrations increased viscosity and affected the build quality. BSA stabilized and promoted the aeration of the food-ink. This resulted in a pore size distribution after printing that was influenced by the viscosity of the food-ink. A predictive model was established for designing the food-ink composition to obtain 3-D printed food simulants with a priori defined microstructure and texture.

Postharvest treatment of fruit inside a cool room is gaining more interest to replace spray applications in the orchard. The efficacy of the application depends on the quality of the spray liquid and its distribution inside fruit bin. This work investigated the effect of different modes and settings of airflow delivery on the deposition amount and uniformity of the cold fogging spray deposition in a single bin. Room air circulation by means of evaporator fans was compared to an air suction configuration using a tunnel and suction fan. Deposition tests were conducted using a mineral chelate tracer solution and filter paper collectors placed on fruit. A computational fluid dynamics (CFD) model of the spraying process was developed to simulate the airflow, droplet particle tracks and spray deposits on fruits. The model predicted well the position of maximum and minimum deposit and the relative differences between the different modes and settings of airflow delivery. Generally, deposition distributions were strongly non-uniform. Spray deposits on fruit using only room air circulation were very low. Using suction airflow that directs the spray through the bin improved spray deposition and uniformity. The effects of spraying under different suction pressures (50, 167, 314 and 500 Pa) across the bin using different droplet diameters (15, 100, 200 and 300 μm) was evaluated. Depending on the size, different effects were observed. Coarse droplets perform best in terms of uniformity of deposition with more lateral dispersion, whereas fine droplets have a very limited lateral dispersion, travels deep to the stack following the high-velocity air (better axial dispersion). By implementing multiple nozzles the poor lateral dispersion of fine droplets can be improved, hence, the desirable characteristics of fine droplets in penetrating into the stack (axial distribution) can be retained. publisher: Elsevier articletitle: Experimental and numerical analysis of the spray application on apple fruit in a bin for postharvest treatments journaltitle: Journal of Food Engineering articlelink: http://dx.doi.org/10.1016/j.jfoodeng.2017.01.026 content_type: article copyright: © 2017 Elsevier Ltd. All rights reserved. ispartof: Journal of Food Engineering vol:202 pages:34-45 status: published

© 2017 Elsevier B.V. A non-destructive methodology was developed to automatically detect and quantify bruise volumes in the equatorial region of apples, using X-ray CT images. Grey level threshold values were calculated to segment bruises in ‘Jonagold’, ‘Joly Red’ and ‘Kanzi’ apple fruit using the multi-level Otsu's threshold method. Comparisons were made between the CT-based bruise volume estimates and bruise volume estimates that were based on destructive measurements in combination with simple geometric assumptions. Visualisation of the bruises in both 2 and 3D showed that bruises, resulting from a pendulum impact with a spherical impactor, can be highly irregularly shaped which implies that the bruise volume estimations based on simple geometric assumptions cannot deliver accurate results. publisher: Elsevier articletitle: Assessment of bruise volumes in apples using X-ray computed tomography journaltitle: Postharvest Biology and Technology articlelink: http://dx.doi.org/10.1016/j.postharvbio.2017.01.013 content_type: article copyright: © 2017 Elsevier B.V. All rights reserved. ispartof: Postharvest Biology and Technology vol:128 pages:24-32 status: published

BACKGROUND Although considered as a safe pesticide application method, treated seeds can pose environmental risks when abraded pesticide-laden seed particles are expelled during sowing. This dust drift risk is clearly linked with seed coating quality. Seed coating quality is traditionally assessed with Heubach dust meters, and guidelines are established in terms of the ‘Heubach value’. This technique may, however, not take all drift-sensitive particles into account. In this study, results of the Heubach test are compared with two alternative set-ups: mechanical sieving and the individual sowing element. RESULTS The abrasion potential assessed with the Heubach dust meter was much lower than the total dust fraction generated by mechanical sieving and the individual sowing element. The amount of dust produced and the dust particle size distribution of both the other techniques were comparable. CONCLUSION It looks as if the Heubach dust meter underestimates the risk of dust drift. Using one of the alternative methods might be a more appropriate way to assess the abrasion potential of seeds. Given the low investment cost required, mechanical sieving seems to be a good approach for non-specialised labs. The individual sowing element set-up is the most realistic simulation of in-field dust drift generation but requires a higher initial investment. Therefore, this set-up is most suitable for specialised labs and is recommended for further research in this area. © 2017 Society of Chemical Industry

A 3-D computational fluid dynamics (CFD) model of palletised polylined kiwifruit packages undergoing forced-air cooling was used to determine an optimal operating point. Two operating conditions (pressure drop and flowrate across the pallet) were tested and the results evaluated based on cooling rate, uniformity, energy requirement and pallet throughput per week. An optimal operating point of 100 Pa (0.25 L kg −1 s −1 ) ensured relatively rapid cooling of the produce, without incurring excessive operational costs due to the energy requirements. Based on the results an alternative package was designed with the aim of redistributing the incoming refrigerated airflow to channel cool air through the pallet layers before directing it towards the slowest cooling packages, located at the back of the pallet. Evaluating the new design at the optimal conditions for the current package showed that at constant flowrate both pressure drop and energy requirement to achieve half-cooling time (HCT) were reduced by 24%, while improving cooling uniformity and pallet throughput per week. Alternatively, keeping the pressure drop constant required a similar energy input, while further increasing the cooling uniformity and pallet throughput.

Chilling injury (CI) presents a major problem in postharvest preservation and marketing potential of mango. In this study, tissue breakdown caused by chilling injury was investigated using X-ray computed microtomography (X-ray μCT). This provided a unique insight in 3-D changes in tissue structure and pore networks during chilling injury development. Evidence of cell collapse and cavity formation in severely chill injured fruit was apparent. In addition, microstructural evidence supporting the occurrence of intracellular water leakage was found. Quantitative analysis revealed that chilling injury was associated with, first, a decrease in porosity, pore size and pore connectivity due to cell leakage and tissue breakdown, which was followed by an increase in pore size due to cavity formation. Multivariate statistics identified pore connectivity and Euler number as the most important parameter in relation to chilling injury. The results support the hypothesis that changes in tissue and pore structure in mango fruit contribute significantly to the development of postharvest tissue disorders by drastic changes in tissue aeration and water movement, identical to what has been observed in other fruit species.

Model simulations permit to identify and predict the levels of loss arising under different storage temperature and maturity conditions in the supply chain. In this research kinetic model was developed for predicting relationship between storage temperature and mango quality attributes. Three quality attributes of mango (color, firmness and total soluble solids (TSS)) were measured and used for the kinetic modeling by estimating the parameters of the model. Mangoes were stored at 7, 13 °C and room temperature. The measurements were carried out with eight repetitions at one week intervals. From the tested equations exponential model for color and TSS found to be the best fit and logistic model for firmness. The model parameters were estimated by the simulation and also validated with a separate experiment with acceptable standard errors and minimum confidence interval of 87.58% which means that the variation in the measured data could be explained by the model. After developing the model a ripening stage were assigned from 1 to 5 with the corresponding quality values; where 1 is the mature green and 5 is the over ripe stage. The result shows that softening was the limiting quality factor for mangoes stored at 7 °C and color was the limiting quality factor for mangoes stored at 13 °C and room temperature. Equations used in this research could be used to estimate quality loss at different conditions of mango fruit in the supply chain.

Apple is a seasonal product that is stored for long periods of time, during which fungal‐caused decay can occur. Previous infection experiments of intact ‘Jongaored’ apple with Botrytis cinerea displayed apparent differences in lesion expansion rate with respect to inoculation position on the fruit (on, above or below the equator). The goal of this study was to (i) investigate whether these differences are consistent or not, and, if so, to (ii) relate them to fruit characteristics. We measured the hue angle of the intended inoculation spots prior to inoculation, and firmness and total soluble solids content of fruit from the same batch. Results showed that firmness correlated somewhat (‐0.55 and ‐0.72 for shadow and sun side, respectively) with lesion diameter expansion rate. In a subsequent step, X‐ray imaging was carried out for samples from each position. Analysis of 3D reconstructions by micro computed tomography of these diffraction images showed that cell size was strongly correlated (0.996) to lesion diameter expansion rate. Finally, it was investigated if cell size could also be used to rank different apple cultivars for their susceptibility to B. cinerea. The result shows that there is a clear distinction between ‘Jonagold’ and Golden ‘Delicious’ (non‐blushing variety), which have a smaller cell size, and ‘Braeburn’ and ‘Kanzi’, which have a larger cell size (overall correlation of 0.87). This indicates that cell size may also be an important factor in determining susceptibility across cultivars. ispartof: PLANT PATHOLOGY vol:69 issue:1 pages:60-67 status: published

We combined a virtual leaf tissue generator and a microscale model of gas diffusion. With this tool, we demonstrated that light-saturated photosynthesis could be improved by altering cell growth and development factors., Computational tools that allow in silico analysis of the role of cell growth and division on photosynthesis are scarce. We present a freely available tool that combines a virtual leaf tissue generator and a two-dimensional microscale model of gas transport during C3 photosynthesis. A total of 270 mesophyll geometries were generated with varying degrees of growth anisotropy, growth extent, and extent of schizogenous airspace formation in the palisade mesophyll. The anatomical properties of the virtual leaf tissue and microscopic cross-sections of actual leaf tissue of tomato (Solanum lycopersicum L.) were statistically compared. Model equations for transport of CO2 in the liquid phase of the leaf tissue were discretized over the geometries. The virtual leaf tissue generator produced a leaf anatomy of tomato that was statistically similar to real tomato leaf tissue. The response of photosynthesis to intercellular CO2 predicted by a model that used the virtual leaf tissue geometry compared well with measured values. The results indicate that the light-saturated rate of photosynthesis was influenced by interactive effects of extent and directionality of cell growth and degree of airspace formation through the exposed surface of mesophyll per leaf area. The tool could be used further in investigations of improving photosynthesis and gas exchange in relation to cell growth and leaf anatomy.

Single-use ventilated corrugated cardboard boxes are commonly used in the postharvest apple cold chain but pose significant challenges for optimising cooling efficiency while reducing energy use. The cooling performance of typical corrugated boxes (standard type ‘Mk4’) was compared to that of an alternative reusable plastic crate (RPC). Cooling rates, temperature uniformity, energy consumption and fruit quality were evaluated. Using a computational analysis, trade-offs between cooling rates and energy consumption were captured. Experiments were conducted in similar conditions to successfully verify computations and gain additional insights. A mismatch between the position of vent holes and fruit-supporting trays created isolated regions for the airflow, resulting in large temperature heterogeneities in the standard Mk4 box. Both cooling uniformity and energy use were found to be the best for RPCs, but the high airflow rates might cause chilling injury to the apples. Compared to corrugated boxes, RPCs showed promising features towards more energy-efficient cold chains.

© 2019 Wiley Periodicals, Inc. 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°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. ispartof: JOURNAL OF FOOD PROCESS ENGINEERING vol:42 issue:4 status: published

Stand-alone and portable lab-on-chips (LOC) can be obtained by exploiting capillary flow in porous media. Polymethylmethacrylate (PMMA) platforms obtained through powder-based three-dimensional (3D) printing are appropriate for capillarity-driven LOCs. However, fluid flow in such platforms needs to be characterized well. For this purpose, a 3D pore network (PN) was extracted from high-resolution $\ensuremath{\mu}\mathrm{CT}$ images of printed PMMA through a watershed algorithm and a PN model was developed with the final goal of characterizing material permeability. The effect of all parameters involved in the PN extraction and modeling was investigated. The study focused in particular on the effect of the number of seeds for the watershed segmentation, pore sphericity, and pore-to-pore channel shape that was modeled as a bicylindrical or biconical object. The results proved that all PN extraction and modeling parameters influenced the permeability, which was found to be lower the higher the number of seeds and when using sphericity and biconical channels. Eventually, the Calinski-Harabasz index value was used to identify the optimal number of watershed seeds.