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Maize (Zea mays) kernels are the largest cereal grains, and their endosperm is severely oxygen deficient during grain fill. The causes, dynamics, and mechanisms of acclimation to hypoxia are minimally understood. Here, we demonstrate that hypoxia develops in the small, growing endosperm, but not the nucellus, and becomes the standard state, regardless of diverse structural and genetic perturbations in modern maize (B73, popcorn, sweet corn), mutants (sweet4c, glossy6, waxy), and non-domesticated wild relatives (teosintes and Tripsacum species). We also uncovered an interconnected void space at the chalazal pericarp, providing superior oxygen supply to the placental tissues and basal endosperm transfer layer. Modeling indicated a very high diffusion resistance inside the endosperm, which, together with internal oxygen consumption, could generate steep oxygen gradients at the endosperm surface. Manipulation of oxygen supply induced reciprocal shifts in gene expression implicated in controlling mitochondrial functions (23.6 kDa Heat-Shock Protein, Voltage-Dependent Anion Channel 2) and multiple signaling pathways (core hypoxia genes, cyclic nucleotide metabolism, ethylene synthesis). Metabolite profiling revealed oxygen-dependent shifts in mitochondrial pathways, ascorbate metabolism, starch synthesis, and auxin degradation. Long-term elevated oxygen supply enhanced the rate of kernel development. Altogether, evidence here supports a mechanistic framework for the establishment of and acclimation to hypoxia in the maize endosperm.

Over the last years, deep learning (DL) models have led to an enormous breakthrough in a wide range of computer vision tasks, including the classification and quantification of internal defects in fruit using X-ray CT images. However, developing these models typically requires large annotated datasets. Obtaining such datasets faces multiple challenges as the availability of defect fruit is unpredictable and it is unclear whether the disordered fruit in the dataset are representative of all possible defects. This work proposes a method to circumvent these problems by generating synthetic CT images using a conditional Generative Adversarial Network (cGAN) that learns the underlying distribution of gray values for different classes ("healthy tissue", "internal browning", "background, core and cavities") in manually annotated images of pear fruit. The performance of the predictor was evaluated by quantitative metrics and visual inspection. To generate new synthetic data, operations are suggested and tested on annotated data to create as much variation as possible in the generated pears. The Fre ' chet Inception Distance (FID) and visual observations showed that the cGAN was effective in image-to-image translation, generating CT images of both healthy and disordered fruit based on their annotations. The best performing model obtained a low FID score of 10.2 and produced detailed visual features in the synthetic CT data, such as vascular bundles. The high potential and broad applicability was further demonstrated on augmented image annotations for generating new healthy and disordered pears with different appearances of defects. The proposed method can be used to produce additional training data when datasets are limited and laborious to manually annotate. Furthermore, the robustness of other DL models might increase by including new synthetic samples with a high variety of disorders during training.

Climacteric ripening of tomato fruit is initiated by a characteristic surge of the production rate of ethylene, accompanied by an increase in respiration rate. As both activities consume O2 and produce CO2 , gas concentration gradients develop in the fruit that cause diffusive transport. This may, in turn, affect respiration and ethylene biosynthesis. Gas diffusion in fruit depends on the amount and connectivity of cells and intercellular spaces in 3D. We investigated micromorphological changes in different tomato tissues during development and ripening by visualizing cells and pores based on high-resolution micro-computed tomography, and computed effective O2 diffusivity coefficients based on microstructural features of the tissues. We demonstrated that mesocarp and septa tissues have larger cells but small and more disconnected pores than the placenta and columella, resulting in relatively lower effective O2 diffusivity coefficients. Cell disintegration occurred in the mesocarp and septa during ripening, indicating lysigenous air pore formation and resulting in a gradual increase of the effective O2 diffusivity. The results suggest that hypoxic conditions caused by the increasing size and, hence, diffusion resistance of the growing fruit may induce an increase of tissue porosity that results in a greatly enhanced O2 diffusivity and, thus, helps to alleviate them. ispartof: NEW PHYTOLOGIST vol:232 issue:5 pages:2043-2056 ispartof: location:England status: published

Mechanical damage of fresh fruit occurs throughout the postharvest supply chain leading to poor consumer acceptance and marketability. In this review, the mechanisms of damage development are discussed first. Mathematical modeling provides advanced ways to describe and predict the deformation of fruit with arbitrary geometry, which is important to understand their mechanical responses to external forces. Also, the effects of damage at the cellular and molecular levels are discussed as this provides insight into fruit physiological responses to damage. Next, direct measurement methods for damage including manual evaluation, optical detection, magnetic resonance imaging, and X-ray computed tomography are examined, as well as indirect methods based on physiochemical indexes. Also, methods to measure fruit susceptibility to mechanical damage based on the bruise threshold and the amount of damage per unit of impact energy are reviewed. Further, commonly used external and interior packaging and their applications in reducing damage are summarized, and a recent biomimetic approach for designing novel lightweight packaging inspired by the fruit pericarp. Finally, future research directions are provided.HIGHLIGHTSMathematical modeling has been increasingly used to calculate damage to fruit.Cell and molecular mechanisms response to fruit damage is an under-explored area.Susceptibility measurement of different mechanical forces has received attention.Customized design of reusable and biodegradable packaging is a hot topic of research. ispartof: CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION ispartof: location:United States status: published

Background Precooling is a critical step in the postharvest cold chain. Studies of the precooling of fruit and vegetables are based on the strong interactions between modelling, engineering, physiology and commercial outcomes. In recent years, new progress in precooling has been achieved. These achievements include different cooling strategies, research into precooling mechanisms, and numerical simulations. This review aims to provide the most recent information about precooling and promote its application in the fruit and vegetable industry. Scope and approach Different precooling strategies are evaluated with respect to the cooling rate, cooling uniformity, and multiscale simulation. An overview of mathematical modeling approaches used to quantitatively describe precooling processes for computer-aided designs is provided. The effect of precooling on fruit quality at the physiological and molecular levels is outlined. Key findings and conclusions Numerical simulations have become widely used to improve the precooling performance. Cooling homogeneity, in particular, has attracted increasing attention in recent studies because of the substantial effects of cooling homogeneity on the precooling efficiency and produce quality. The spatial scale of numerical simulations of the precooling process has started to become more precise and specific. Recent numerical simulations have focused on the bin and package scale. Models of transport processes at multiple spatial scales are investigated using multiscale modeling. Moreover, the effect of precooling on produce quality has recently received increasing attention. In addition, the investigation of the effect of precooling on fruit at the metabolomic and genomic levels has become an emerging trend and has provided deeper insights into the molecular mechanisms underlying the effect of precooling treatments on fruit.

Dynamic models based on non-linear differential equations are increasingly being used in many biological applications. Highly informative dynamic experiments are valuable for the identification of these dynamic models. The storage of fresh fruit and vegetables is one such application where dynamic experimentation is gaining momentum. In this paper, we construct optimal O2 and CO2 gas input profiles to estimate the respiration and fermentation kinetics of pear fruit. The optimal input profiles, however, depend on the true values of the respiration and fermentation parameters. Locally optimal design of input profiles, which uses a single initial guess for the parameters, is the traditional method to deal with this issue. This method, however, is very sensitive to the initial values selected for the model parameters. Therefore, we present a robust experimental design approach that can handle uncertainty on the model parameters., Author summary Fruit and vegetables need to be stored at low temperature and oxygen conditions as well as slightly heightened carbon dioxide conditions so that they remain fresh throughout the entire year. The exact storage conditions are different for each cultivated variety. Optimizing these storage conditions typically requires a lot of experimentation. Traditionally, this was done by independently storing the fruit of vegetable product at many different combinations of temperature as well as oxygen and carbon dioxide conditions, and by tracking the quality of the product and choosing the best of these conditions. This, however, is a very wasteful approach as the quality tracking at certain conditions do not inform us about the quality at different storage conditions. Instead, we adopt a model-based approach, where the product is described as a dynamic system with inputs and outputs. This model has parameters that must be estimated from experimental data. But once the model has been calibrated it can be used to make predictions at any storage condition. We develop the experimental design methodology required to precisely estimate the model parameters. We do this in a robust manner, meaning we are able to discover the true model parameter values no matter their specific value.

Oxygen (O2) diffusion affects respiration of fruit and vegetables and, thus, their behavior under controlled or modified atmosphere storage conditions. Effective gas diffusivity expresses, at a macroscopic level, the overall ability of the tissue to exchange gasses and is determined by the porous structure of the tissue. Variations of the tissue microstructure across the fruit and vegetable organs may result in an effective O2 diffusivity that is position dependent. A method was developed to create three-dimensional (3-D) effective O2 diffusivity maps in fruit and vegetables based on low resolution X-ray computed tomography (CT) images. The effective tissue diffusivity was first calculated for representative small tissue samples of eggplant, turnip, apple, and pear fruit, using microscale diffusion simulations with a finite volume model on high resolution CT images, which served as ground truth. Then the dependence of the effective O2 diffusivity on the total and open porosity and tortuosity of the samples was investigated. The regression model of the diffusivity with respect to total porosity had an RMSE = 6.90 × 10−7 m2 s−1 and R2 = 0.92, while that with respect to open porosity had an RMSE = 5.41 × 10−7 m2 s−1 and R2 = 0.95, for all samples and organs. The incorporation of the pore network tortuosity did not improve the goodness of fit of the correlation. The correlation based on total porosity was found sufficient for eggplant and turnip that has a large porosity, while diffusivity profiles in apple and pear fruit correlated better with the open porosity due to the presence of disconnected (closed) pores in these fruits that contribute less to the effective diffusion. Thereto, open porosity was estimated from a correlation model between total porosity and open porosity with RMSE = 5.76% for apple and RMSE = 0.93% for pear. Porosity profiles of organs computed from low resolution CT grayscale images were translated to O2 diffusivity profiles using the correlation model and tested against the high resolution ground truth values. Finally, effective diffusivity maps were created for intact organs, which for the first time provides insight in the spatial variation in gas exchange capability of different plant species. keywords: Tissue microstructure, Open porosity, Tortuosity, Apple, Pear, Eggplant, Turnip ispartof: Journal Of Food Engineering vol:306 status: Published online

Many studies have focused on the plant hormone ethylene because of its key role in controlling, among others, climacteric fruit ripening and fruit senescence. These processes can be controlled by applying 1-MCP, which tightly binds to the ethylene receptors thereby blocking the ethylene signaling pathway. 1-MCP is known to inhibit the action of ethylene and to delay the climacteric ripening of tomato fruit. Less is known about its long term effect when the inhibitory effect 1-MCP inhibition is eventually released. Our objective was to study this transient 1-MCP inhibition during tomato fruit ripening in terms of fruit quality, ethylene production, respiration rate and the expression and protein abundance of receptors, CTRs and EIN2. For the identification and quantification of proteins, we used an LC–MS based targeted method of Parallel Reaction Monitoring (PRM), while gene expression was done using real time qPCR. Different color stages of tomatoes were harvested and treated with 1-MCP and subsequently stored to follow up postharvest fruit ripening. The difference with previous 1-MCP studies is that we sampled 1-MCP treated tomatoes at different physiological stages during ripening (and not time), matching the color stages of the untreated control fruit. This allows to properly compare the underlying regulation of the ethylene signaling pathway during a 1-MCP-mediated suppression of ripening. We hypothesized that the levels of the ethylene signaling components would be different for 1-MCP treated fruit due to a reduced ethylene-mediated autocatalytic feed-back. Our results showed that fruit treated with 1-MCP at mature green stage showed a lower respiration rate during subsequent ripening as compared to the untreated fruit, suggesting that climacteric ripening was effectively inhibited by 1-MCP. However, these 1-MCP treated fruit showed a higher ethylene production as compared to untreated fruit. The 1-MCP treated fruit also showed lower to equal levels of gene expression and protein abundance of the ethylene receptors, CTRs and EIN2. As receptors and CTRs are negative regulators of ethylene signaling, decreasing the production of new signaling proteins could subsequently activate downstream ethylene signaling and with that expression of downstream genes. This could lead to higher ethylene production levels, which in turn can compensate 1-MCP mediated inhibition of fruit ripening.

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.

3D food printing allows creation of foods by depositing food material according to computer aided designs. However, the number of printable materials for food is still low which limits the possibilities of creating specific structures and textures. A novel approach is tested of using food printing materials incorporating plant cells in order to print foods that resemble plant tissues in various ways. A 3D printing method was developed based on the extrusion of bio-inks composed of a low-methoxylated pectin gel and embedded lettuce leaf cells. Bovine serum albumin was added in order to increase the air fraction in the printed gel matrix. Objects containing up to 5 × 106 cells/mL were successfully 3D printed. The mechanical strength increased by the pectin concentration and decreased with the increase of air fraction and concentration of encapsulated cells. The viability of the encapsulated plant cells depended on the pectin concentration and varied from 50 to 60 %. ispartof: Journal Of Food Engineering vol:263 pages:454-464 status: published

In 1665, Robert Hooke was the first to observe cork cells and their characteristic hexagonal shape, using the first optical microscope, which was invented by him at that time. With the evolution of imaging techniques, the structure of cork has been analysed with greater accuracy over time. This work presents the latest advances in the characterization of this unique material through a multiscale approach. Such investigation brings new insight into the architecture of cork, particularly the differences between the cells of the phellem and those bordering the lenticels. In the latter case, cell differentiation from the lenticular phellogen was restricted to one cell layer, which leads to a cell wall that is 10 times thicker for lenticels. They also displayed a different chemical composition because of unsuberization and a high lignin content in lenticels. Such advances in the knowledge of the structure and composition of cork cells contributes to a better understanding of the macroporosity of cork, down to the nanoscale. ispartof: SCIENTIFIC REPORTS vol:9 issue:1 ispartof: location:England status: published

Hyperspectral imaging (HSI) is a promising technique to evaluate food quality in a rapid and non-destructive way. Several types of HSI sensors are now commercially available. The aim of the current study was to compare one single shot and two line-scanning based HSI sensors in different spectral regions by using two wavelength dispersive devices – a prism-grating-prism monochromator and a mosaic wavelength dispersion unit. The research sample was cured pork meat, which is a popular meat product due to its flavor and long shelf life. Three main chemical compositions of cured pork meat – moisture, protein and fat content – were evaluated. The spectral properties of the three sensors were employed to establish partial least squares regression (PLSR) predictive models by applying different optimal wavelengths selection strategies. The results showed that optimal wavelength selection was more important than the selection of the wavelength dispersion device.

ispartof: pages:121-126 ispartof: Acta Horticulturae vol:1256 pages:121-126 ispartof: 6th International Conference on Postharvest Unlimited location:SPAIN, Madrid date:17 Oct - 20 Oct 2017 status: published

ispartof: EUROPEAN JOURNAL OF HORTICULTURAL SCIENCE vol:84 issue:4 pages:226-236 status: published

© 2019 Elsevier B.V. This study has focussed on the effect of low temperature storage on the postharvest ripening of green tomatoes; more specifically, on the ethylene signal transduction in relation to the ethylene biosynthesis pathway. To this end, the first elements of the ethylene signal transduction, ethylene receptors, CTR and EIN2 have been analysed in tomatoes stored at three different temperatures in terms of both their gene and protein expression levels. These results have been related to quality changes and enzymes and intermediates of the ethylene biosynthesis pathway to better understand the ethylene control of ripening under low temperatures. The first changes observed during low temperature storage took place at the ethylene biosynthesis level, which might enhance changes in the ethylene signal transduction. Although expression of most ethylene signalling genes decreased with chilling, none of the protein levels showed a significant decrease, pointing at a differential regulation at the gene and protein level. ispartof: POSTHARVEST BIOLOGY AND TECHNOLOGY vol:155 pages:1-10 status: published

Aroma is an essential quality aspect of fresh produce and plays an important role in determining consumer liking and the volatile organic compounds (VOCs) can serve as markers for fermentation and postharvest storage disorders. This study suggests Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) as a candidate technique for the rapid, non-destructive and quantitative measurement of VOCs in postharvest quality research. Strawberry was chosen as a model fruit since its aroma is one of its main quality traits. Combining SIFT-MS in full scan mode with multivariate statistics allowed for inter- and intra-cultivar discrimination of strawberry aroma profiles. Further, by combining SIFT-MS with GC–MS it is possible to tentatively identify volatiles. As compared to GC–MS based approaches total analysis time was reduced by a factor 11.

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.

Storing ‘Jonagold’ apple (Malus x domestica Borkh. cv. ‘Jonagold’) closer to their anaerobic compensation point during dynamic controlled atmosphere storage may delay fruit ripening more effectively, but can also induce low-oxygen stress in the fruit leading to the induction of fermentation. Knowledge of the in vivo regulatory mechanism of the fermentative metabolism in plants is still limited. We exposed ‘Jonagold’ apple tissue slices to different oxygen partial pressures (0, 0.3, 0.5, 1, 5 and 21 kPa O2) and temperatures (1 °C and 18 °C) at harvest and after 6 months of storage. A combination of experimental techniques and a kinetic modelling approach was used to translate the in vitro measured enzyme activity into in vivo activities and to provide new insights in the regulation of the fermentative metabolism. The regulation of the fermentative metabolism appeared to be highly flexible as it depends largely on the conditions applied. Temperature is known to increase the overall metabolic reaction rate, which appeared to have a large influence on the induction and regulation of the fermentative metabolism. Furthermore, the model indicated that the in vivo regulation of the fermentative metabolism was different under anoxic (0 kPa O2) and hypoxic conditions (0.3, 0.5 and 1 kPa O2) and that an extra regulation was present after 6 months of storage. Even though fermentation was clearly induced under all the experimental conditions applied, the flux through the fermentative metabolism started to decrease again after prolonged low-oxygen stress.

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.

To preserve the quality of fresh fruit after harvest and to meet the year-round demand for high-quality fruit, pears are stored under a controlled atmosphere. However, due to preharvest events or suboptimal storage conditions, internal disorders might develop resulting in severe quality loss. Examples include internal browning and cavities, which are invisible externally. Here, X-ray radiography is investigated as a technique for internal quality inspection. The detection of defect fruit is approached as an anomaly detection (AD) problem, in which a model is constructed using nominal data and an anomaly score is used to identify defect fruit. In this work, multiple deep AD methods are shown to be effective to detect pears with internal cavity and browning disorders using Xray radiographs (mean area under the receiver operating characteristic curve (AUC) up to 0.962). The best performing methods were found on par with a state-of-the-art multisensor disorder detection method (mean AUC up to 0.966). By investigating AD performance in function of internal disorder severity, it was shown that defect fruit with a cavity volume percentage > 1.0% could be detected 100% accurate using inline X-ray imaging. For lower cavity area percentages, the accuracy depended on the internal browning severity. Additionally, the explainability of the deep AD methods, i.e., how well human interpretable insight can be provided from each method's predictions, were qualitatively evaluated using anomaly heatmaps, which provided useful insight in the execution of the deep learning algorithms.

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.

The desert locust, Schistocerca gregaria, is an infamous migrating insect, generally considered to be one of the most dangerous pest species worldwide. In an area that encompasses one fifth of the Earth’s land surface, desert locust swarms can devastate the agricultural production. Consequently, they pose a serious threat to food security and can have a dramatic socio-economic impact. Currently (in 2020), large parts of East Africa, Southwest and South Asia are experiencing the worst desert locust plague in many decades. Exceptionally high rainfall in different regions has caused the favorable environmental conditions for very successful reproduction and population growth. To better understand the molecular mechanisms responsible for this remarkable reproductive capacity, as well as to fill existing knowledge gaps regarding the regulation of male reproductive physiology, we decided to investigate the role of the methoprene-tolerant (Scg-Met) and taiman (Scg-Tai) genes in adult male desert locusts. Methoprene-tolerant and Taiman belong to the basic helix-loop-helix/Per-Arnt-Sim (bHLH/PAS) family of transcription factors and form a complex that is responsible for transducing the Juvenile Hormone (JH) signal. So far, in vivo research has mainly focused on the role of these JH receptor components in post-embryonic development, as well as in the reproductive physiology of adult female insects. In the current study, we show that silencing these components by RNA interference strongly inhibits sexual maturation of gregarious desert locust males, thereby severely disrupting reproduction. This observation is evidenced by the absence of a yellow colored cuticle, the significant reduction in the relative weight of the testes, the inability to show mating behavior, and the drastically reduced phenylacetonitrile (PAN) pheromone levels of the treated males. In addition, we also observed significant reductions of the relative weight, as well as the relative protein content, of the male accessory glands in Scg-Met knockdown locusts. Interestingly, in these animals the size of the corpora allata (CA), the endocrine glands where JH is synthesized, was significantly increased, and a significant rise was observed in the relative transcript levels of JH acid methyltransferase (JHAMT), a rate-limiting enzyme in the JH biosynthesis pathway. Moreover, other endocrine pathways also appeared to be affected by the knockdown, as evidenced by significant changes in the levels of the transcripts coding for the insulin-related peptide and for two neuroparsins in the fat body. Our results demonstrate that JH signaling pathway components play a crucial role in male reproductive physiology. Since they are crucial for a successful reproduction, they may hold great potential as candidate targets for the design of novel strategies for locust population management.Significance statementDesert locusts can form devastating swarms that threaten the livelihood in many of the world’s poorest countries, as demonstrated by the plagues in East Africa, Southwest and South Asia that are currently covered in the news worldwide. Control of this migratory pest mainly relies on the large-scale use of neurotoxic insecticides, also affecting non-target organisms in their already fragile habitats. Therefore, the identification of novel molecular targets for the design of more sustainable and more selective pest management techniques remains of crucial importance. Potential candidate targets in this respect are pathway components that transduce signals of typical insect hormones, such as ecdysteroids and juvenile hormones. By focusing in our current study on the JH receptor components, we showed that the reproductive capacities of desert locust males can be severely inhibited in an early stage, resulting in individuals that display no mating behavior, do not produce an important pheromone and do not show the characteristic yellow color of sexually mature gregarious males. Specifically targeting molecular components of the JH signaling pathway in future, more biorational control strategies could therefore be a very successful way by which expansion of these devastating plagues might be prevented.

In the past two decades, metabolomics has proved to be a valuable tool with many potential applications in different areas of science. However, there are still some challenges that need to be addressed, particularly for multicenter studies. These challenges are mainly attributed to various sources of fluctuation and unwanted variations that can be introduced at pre-analytical, analytical, and/or post-analytical steps of any metabolomics experiment. Thus, this study aimed at using Streptomyces lividans TK24 as the model organism in a cross-laboratory experiment in Manchester and Leuven to evaluate the reproducibility of a standard sample preparation method, and determine the optimal sample format (cell extract or quenched biomass) required to preserve the metabolic profile of the cells during cross-lab sample transportation and storage. Principal component analysis (PCA) scores plot of the gas chromatography-mass spectrometry (GC-MS) data from both laboratories displayed clear growth-dependent clustering patterns which was in agreement with the Procrustes analysis findings. In addition, the data generated in Manchester displayed tight clustering of cell pellets (quenched biomass) and metabolite extracts, confirming the stability of both sample formats during the transportation and storage period. ispartof: METABOLITES vol:10 issue:9 ispartof: location:Switzerland status: published

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.