Get in shape for smart farming

status: publishe

A 3D contour based geometrical model generator for complex-shaped horticultural products

A novel geometric model generator for horticultural products is presented, which generates 3D models of fruits using shape description techniques based on shapes obtained experimentally from a measured dataset of fruits by non-destructive X-ray CT imaging. For this purpose, the 3D contour of each fruit in the scanned dataset was represented with a 2D shape signature, obtained after applying the spherical coordinate transformation. After normalisation, these signatures were described with 2D Fourier descriptors. Statistical analysis of these descriptors for all scanned fruits allowed automatic generation of new geometric fruit models, representative of the measured dataset. The accuracy of the generator was validated by means of the distributions of volumes and surface area to volume ratios of fruit scans and the newly generated shapes. This 3D shape description and generation method allows to process the entire 3D contour of the observed objects and can be applied to all star-shaped objects (shapes that do not curve back on themselves with respect to the centre of mass). This way, more accurate geometrical models can be produced compared to similar model generators based on shape description using 2D cross-sections. This generator enables fast generation of geometrical models to be used in numerical simulations of heat or mass transport phenomena within horticultural products or their exchange processes with the surrounding environment.publisher: Elsevier articletitle: A 3D contour based geometrical model generator for complex-shaped horticultural products journaltitle: Journal of Food Engineering articlelink: http://dx.doi.org/10.1016/j.jfoodeng.2015.02.006 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved.status: publishe

Stochastic modelling for virtual engineering of controlled atmosphere storage of fruit

© 2015 Elsevier Ltd. Long term storage of pear fruit requires low temperature and conventionally uses controlled atmosphere (CA) conditions to reduce respiration and consequent quality loss. Sub-optimal storage conditions may lead to physiological disorders and loss of product. Stochastic variability of the properties of fruit introduces uncertainty in storage design and operations and could result in severe quality loss. Taking such variability into account in simulation models for virtual engineering will allow to assess the uncertainty of the process and determine confidence limits for the operation. Gas exchange in pear fruit during controlled atmosphere storage was studied using a continuum diffusion-respiration model, taking into account stochastic variation of the 3D morphology, the diffusivity of oxygen and carbon dioxide and the maximal respiration rate. Different geometries were generated using a statistical shape generation algorithm for 3D morphology, that was automatically incorporated into the gas exchange model. Similarly, tissue diffusivity was computed using a 3D tissue microstructure database. Simulation results showed that internal O2 and CO2 gas profiles in fruit were highly affected by variation of diffusivities, maximal respiration rate and the 3D morphology of fruit. The model was further used to evaluate incidence to fermentation at different reduced O2 levels of storage condition. The risk of fermentation inside the fruit predicted by the gas exchange model rapidly increased in response to decreasing external O2 levels. The virtual simulation tool confirms that picking time and fruit size are important criteria for proper control of CA storage. While applied here to pear fruit, it can easily be extended to other commodities.publisher: Elsevier articletitle: Stochastic modelling for virtual engineering of controlled atmosphere storage of fruit journaltitle: Journal of Food Engineering articlelink: http://dx.doi.org/10.1016/j.jfoodeng.2015.07.003 content_type: article copyright: Copyright © 2015 Elsevier Ltd. All rights reserved.status: publishe

A Novel Methodology To Model The Cooling Processes Of Packed Horticultural Produce Using 3D Shape Models

Freshly harvested horticultural produce require a proper temperature management to maintain their high economic value. Towards this end, low temperature storage is of crucial importance to maintain a high product quality. Optimizing both the package design of packed produce and the different steps in the postharvest cold chain can be achieved by numerical modelling of the relevant transport phenomena. This work presents a novel methodology to accurately model both the random filling of produce in a package and the subsequent cooling process. First, a cultivar-specific database of more than 100 realistic CAD models of apple and pear fruit is built with a validated geometrical 3D shape model generator. To have an accurate representation of a realistic picking season, the model generator also takes into account the biological variability of the produce shape. Next, a discrete element model (DEM) randomly chooses surface meshed bodies from the database to simulate the gravitational filling process of produce in a box or bin, using actual mechanical properties of the fruit. A computational fluid dynamics (CFD) model is then developed with the final stacking arrangement of the produce to study the cooling efficiency of packages under several conditions and configurations. Here, a typical precooling operation is simulated to demonstrate the large differences between using actual 3D shapes of the fruit and an equivalent spheres approach that simplifies the problem drastically. From this study, it is concluded that using a simplified representation of the actual fruit shape may lead to a severe overestimation of the cooling behaviour.status: publishe

Online Tomato Inspection Using X-ray Radiographies and 3-dimensional Shape Models

A method is proposed that fits a 3-dimensional shape model (SM) on X-ray radiographies of tomatoes on a conveyor belt to allow for inspection of internal tomato quality using X-ray. For the training of the SM a set of computed tomography (CT) scans is used. From these scans, the surfaces of the fruits are extracted. Corresponding points on all these surfaces are located after which the variation in position of every point can be determined using Principal component analysis (PCA). The result of this process is a mean shape with various modes of variation, which represent the variability of the shape. Any shape can then be reconstructed through a linear combination of the mean shape and its modes of variation. During runtime, the contour of every tomato is extracted onto which the SM is fitted. This allows us to accurately estimate tomato volume and 3-dimensional shape, and assess the presence of defects and other unwanted properties from X-ray radiographies in an online application. Results are promising, but show that improvement can be made by simulating radiographs from the shape model and fitting these directly to the easured radiograph.status: publishe

A Geometrical Model Generator for Quasi-Axisymmetric Biological Products

A geometrical model generator for biological products is presented, which uses X-ray computed tomography images of quasi-axisymmetric biological products as input. It was tested with a dataset of 73 scanned Braeburn apples. For each sample, the generator constructed different cross sections. From these sections, contours were extracted and selected. The contours were expressed as a series of shape descriptors. For this purpose, elliptical Fourier descriptors were used. The obtained frequency distributions were transformed to standard normal distributions. On these transformed distributions, the covariance decomposition algorithm was applied. This algorithm generated new sets of descriptors, which opened up a large range of possibilities for generation of representative shape contours. After reverse transformation of the (generated) descriptor distributions, new contours were obtained from the new descriptors. These new contours were converted to 3D geometrical models of biological products by interpolation and revolving. By comparing the volumes of the generated models with those of the scanned fruit, it was shown that the resulting geometrical models have the same variability as the biological variability in the original dataset. This generator is a fast method, which requires minimal user intervention, and creates 3D models including the biological variability as observed in the scanned fruit. Because these 3D geometrical models are directly available as CAD models, they are useful for numerical modelling of transport phenomena in and around biological products.status: publishe

DEM-CFD of cooling of packed fruit using 3D shape models

Cooling of freshly harvested produce is crucial for maintaining a high product quality for a prolonged storage period and to reduce postharvest losses. Modelling the cooling process of packed horticultural produce provides a means for improving package designs and cooling operations. In this work, a methodology to more accurately model the cooling process of randomly stacked produce in packages is presented. First, a validated geometrical 3D shape model generator of apple fruit is used to create realistic CAD models. The generator also considers the biological variability of the produce shape to create a database of more than 100 representative fruits of each cultivar. A discrete element model (DEM) then randomly selects surface meshed bodies from the database to simulate the gravitational packing of produce in a designated box or bin. The resulting stacking pattern of the produce is used to generate a computational fluid dynamics (CFD) model. The CFD model solves the airflow, heat and mass transfer through the packages to evaluate the aerodynamic and cooling performance of packages under different conditions and configurations. The difference between using actual 3D fruit shapes and an approach using equivalent spheres is demonstrated in a simulation study of forced airflow cooling of apple fruit (cv. Braeburn) packed in a “Supervent” telescopic corrugated fibreboard package under typical precooling conditions. The results are analysed in terms of pressure drop characteristics, velocity profiles and distribution of cooling rates expressed by local surface heat transfer coefficients.status: accepte

Modelling cooling of packaged fruit using 3D shape models

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.status: Published onlin

Understanding microstructural deformation of apple tissue from 4D micro-CT imaging

Water transport in plant tissues is often associated with deformation of the tissues. The ability to visualize and model this deformation is an integral part of better understanding of the relevant parameters involved. Traditional imaging techniques are both time consuming and destructive, this makes them unsuitable for visualizing the tissue deformation process, as both time and environmental conditions are critical parameters. However, even with the use of nondestructive imaging techniques such as X-ray micro computed tomography (micro-CT), visualizing the dehydration process is difficult due to the unstable nature of the samples as well as limitations imposed by accuracy of conventional image reconstruction of deforming objects. As a result, micro-CT images of deforming tissues can often not be processed easily. Here, we applied micro-CT with a novel 4D iterative reconstruction algorithm to more accurately visualize the deformation of apple cortex samples during dehydration such that the deformation process can be quantified. Outer cortex samples of Kanzi apples of approximately 5mm in diameter were dehydrated in a controlled environment of 22 °C and 30% RH via a interleaved high resolution micro-CT scanning process along with the advanced reconstruction technique to obtain images at 3 µm voxel size. The reconstructed images allowed us to create a time series of high resolution 3D renderings of the changes in the cellular structure of apple cortex samples through the first six hours of the dehydration process. The differential shrinkage rates of the outer and inner cell layers of the samples were analysed, as well as the size and positional changes of cells within the dehydrating samples in reference to the center axis. We expect such quantitative description of cell and cell layer deformation to be useful in enhancing the accuracy of hygro-mechanical models of plant tissues.status: submitte