Wheat gluten structure and (non-)covalent network formation during deep-fat frying.

The aim of this work was to investigate wheat gluten protein network structure throughout the deep-frying process and evaluate its contribution to frying-induced micro- and macrostructure development. Gluten polymerization, gluten-water interactions, and molecular mobility were assessed as a function of the deep-frying time (0 - 180 s) for gluten-water model systems of differing hydration levels (40 - 60 % moisture content). Results showed that gluten protein extractability decreased considerably upon deep frying (5 s) mainly due to glutenin polymerization by disulfide covalent cross-linking. Stronger gliadin and glutenin protein-protein interactions were attributed to the formation of covalent linkages and evaporation of water interacting with protein chains. Longer deep-frying (> 60 s) resulted in progressively lower protein extractabilities, mainly due to the loss in gliadin protein extractability, which was associated with gliadin co-polymerization with glutenin by thiol-disulfide exchange reactions. The mobility of gluten polymers was substantially reduced during deep-frying (based on the lower T2 relaxation time of the proton fraction representing the non-exchanging protons of gluten) and gluten proteins gradually transitioned from the rubbery to the glassy state (based on the increased area of said protons). The sample volume during deep-frying was strongly correlated to the reduced protein extractability (r = -0.792, p < 0.001) and T2 relaxation time of non-exchanging protons of gluten proteins (r = -0.866, p < 0.001) thus demonstrating that the extent of gluten structural expansion as a result of deep-frying is dictated both by the polymerization of proteins and the reduction in their molecular mobility.

Predicting the dynamic impact behaviour of spray droplets on flat plant surfaces.

The dynamic impact behaviour of water droplets on plant surfaces was investigated based on a multiphase computational fluid dynamics (CFD) model. The study was conducted using the Volume Of Fluid (VOF) approach. The static contact angle of water droplets on leaf surfaces of different plants (apple, pear, leek and cabbage) was measured and found to vary between 54.9 and 138.2°. Impact experiments were conducted by monitoring the flow and impact characteristics of water droplets on leaves in still air with a high speed camera. Droplets were generated by an agricultural flat fan spray nozzle moving across the leaf at constant speed. The nozzle produced droplets with diameters ranging from 20.6 up to 550.8 µm, and droplet velocity values near the impact between 0.03 and 13.2 m s(-1). The CFD model was capable of predicting the observed dynamic impact behaviour of droplets on the plant surfaces. The fate of the droplets after the impact process for adhesion, bouncing or splashing was accurately predicted for Weber numbers (We) in the range of 0.007 to 1096 and droplet Reynolds numbers (Re) between 5 to 8000. The process was highly dependent on the surface and droplet flow characteristics during the impact. Combinations of We, Re and Ohnesorge (Oh) numbers defined the droplet maximum spread factor, the number of secondary droplets generated as a result of the splashing process and the transition between the different impact outcomes. These criteria can then be used in field scale spray deposition and drift models to better understand agricultural spray operations.

The metabolic response of cultured tomato cells to low oxygen stress.

The storage of fruits and vegetables under a controlled atmosphere can induce low oxygen stress, which can lead to post-harvest losses through the induction of disorders such as core breakdown and browning. To gain better understanding of the metabolic response of plant organs to low oxygen, cultured tomato cells (Lycopersicum esculentum) were used as a model system to study the metabolic stress response to low oxygen (0 and 1 kPa O2). By adding 13C labelled glucose, changes in the levels of polar metabolites and their 13C label accumulation were quantified. Low oxygen stress altered the metabolite profile of tomato cells, with the accumulation of the intermediates of glycolysis in addition to increases in lactate and sugar alcohols. 13C label data showed reduced label accumulation in almost all metabolites except lactate and some sugar alcohols. The results showed that low oxygen stress in tomato cell culture activated fermentative metabolism and sugar alcohol synthesis while inhibiting the activity of the TCA cycle and the biosynthesis of metabolites whose precursors are derived from central metabolism, including fluxes to most organic acids, amino acids and sugars.

Microscale mechanisms of gas exchange in fruit tissue.

* Gas-filled intercellular spaces are considered the predominant pathways for gas transport through bulky plant organs such as fruit. Here, we introduce a methodology that combines a geometrical model of the tissue microstructure with mathematical equations to describe gas exchange mechanisms involved in fruit respiration. * Pear (Pyrus communis) was chosen as a model system. The two-dimensional microstructure of cortex tissue was modelled based on light microscopy images. The transport of O(2) and CO(2) in the intercellular space, cell wall network and cytoplasm was modelled using diffusion laws, irreversible thermodynamics and enzyme kinetics. * In silico analysis showed that O(2) transport mainly occurred through intercellular spaces and less through the intracellular liquid, while CO(2) was transported at equal rates in both phases. Simulations indicated that biological variation of the apparent diffusivity appears to be caused by the random distribution of cells and intercellular spaces in tissue. Temperature does not affect modelled gas exchange properties; it rather acts on the respiration metabolism. * This modelling approach provides, for the first time, detailed information about gas exchange mechanisms at the microscopic scale in bulky plant organs, such as fruit, and can be used to study conditions of anoxia.

Evaluation and optimization of high-throughput enzymatic assays for fast l-ascorbic acid quantification in fruit and vegetables.

In this paper, we compare and evaluate the applicability of three UV-VIS absorbance based assays for high-throughput quantification of ascorbic acid in horticultural products. All the methods involve the use of a common enzyme (ascorbate oxidase) in combination with a different indicator molecule. The three methods were retrieved from literature: a direct oxidase-method, an OPDA coupled oxidase-method and a PMS-method, which is commercially available. The analysis in high-throughput context involved the analysis in microplates in combination with the use of an automated liquid handling system. We checked (i) the performance factors of the selected methods on standard solutions, (ii) the applicability of the defined methods in high-throughput context, and, (iii) the accuracy of the methods on real samples using HPLC as a reference technique. The OPDA-method was found to be the most appropriate method for the quantification of ascorbic acid in high-throughput context with a linear range between 7.0 and 950 mgL(-1) and excellent correlation parameters (slopes close to 1, intercepts close to 0, R(2)>0.91) with the reference technique when real samples were analyzed. Finally, this method was optimized for assay cost and assay time. Hereto the enzymatic reaction was mathematically described using a model for enzyme kinetics, which was then used to calculate the optimal concentrations of ascorbate oxidase and OPDA. As a result of the modeling the amount of enzyme in the assay could be reduced with a factor 2.5 without affecting significantly the reaction time. In a last step the optimal concentrations were used for a successful validation with the HPLC-reference technique.

Microplate differential calorimetric biosensor for ascorbic acid analysis in food and pharmaceuticals.

In this paper we report on the development of a label-free low-volume (12.5 microL), high-throughput microplate calorimetric biosensor for fast ascorbic acid quantification in food and pharmaceutical products. The sensor is based on microplate differential calorimetry (MiDiCal) technology in which the heat generation, due to the exothermic reaction between ascorbic acid and ascorbate oxidase, is differentially monitored between two neighboring wells of an IC-built wafer. A severe discrepancy is found between expected and observed sensor readings. To investigate the underlying mechanisms of these findings a mathematical model, taking into account the biochemical reactions and diffusion properties of oxygen, ascorbic acid, and ascorbate oxidase, is developed. This model shows that oxygen depletion in the microliter reaction volumes, immediately after injection of sample (ascorbic acid) into the well, causes the enzymatic reaction to slow down. Calibration experiments show that the sensor's signal is linearly correlated to the area under the output versus time profile for the ascorbic acid concentration range from 2.4 to 350 mM with a limit of detection of 0.8 mM. Validation experiments on fruit juice samples, food supplements, and a pain reliever supplemented with ascorbic acid reveal that the designed method correlates well with HPLC reference measurements. The main advantages of the presented biosensor are the low analysis cost due to the low amounts of enzyme and reagents required and the possibility to integrate the device in fully automated laboratory analysis systems for high-throughput screening and analysis.

High-throughput microplate enzymatic assays for fast sugar and acid quantification in apple and tomato.

In this article, we report on the use of miniaturized and automated enzymatic assays as an alternative technology for fast sugar and acid quantification in apples and tomatoes. Enzymatic assays for d-glucose, d-fructose, sucrose, D-sorbitol/xylitol, L-malic acid, citric acid, succinic acid, and L-glutamic acid were miniaturized from the standard 3 mL assays in cuvettes into assays of 200 microL or lower in 96 or 384 well microplates. The miniaturization and the automation were achieved with a four channel automatic liquid handling system in order to reduce the dispensing errors and to obtain an increased sample throughput. Performance factors (limit of detection, linearity of calibration curve, and repeatability) of the assays with standard solutions were proven to be satisfactory. The automated and miniaturized assays were validated with high-pressure liquid chromatography (HPLC) analyses for the quantification of sugars and acids in tomato and apple extracts. The high correlation between the two techniques for the different components indicates that the high-throughput microplate enzymatic assays can serve as a fast, reliable, and inexpensive alternative for HPLC as the standard analysis technique in the taste characterization of fruit and vegetables. In addition to the analysis of extracts, the high-throughput microplate enzymatic assays were used for the direct analysis of centrifuged and filtered tomato juice with an additional advantage that the sample preparation time and analysis costs are reduced significantly.

Validation of predictive growth models describing superatmospheric oxygen effects on Pseudomonas fluorescens and Listeria innocua on fresh-cut lettuce.

Two microbial growth models predicting the growth of Pseudomonas fluorescens and Listeria innocua at superatmospheric oxygen and carbon dioxide concentrations at 7 degrees C were validated on fresh-cut butterhead lettuce. Cut lettuce was inoculated with the same strain of L. innocua as the in vitro experiments. The P. fluorescens strain was tagged with a gene encoding green fluorescent protein (GFP) in order to distinguish the inoculated strain from contaminating Pseudomonaceae. Also growth of aerobic mesophilic and lactic acid bacteria was monitored during the experiments. The suggested P. fluorescens model was appropriate to predict growth on cut lettuce. L. innocua on the other hand, grew considerably slower under in vivo circumstances than predicted. CO(2) had a growth promoting effect on L. innocua growing on cut lettuce, whereas in vitro an inhibiting effect was observed. Validation parameters are calculated and hypotheses to explain the discrepancy between predicted and observed growth of L. innocua are provided.

Predictive modelling and validation of Listeria innocua growth at superatmospheric oxygen and carbon dioxide concentrations.

The effect of superatmospheric oxygen and carbon dioxide concentrations on the growth of Listeria innocua, which was used as a model organism for the pathogen Listeria monocytogenes, was evaluated. The bacteria were grown on a nutrient agar surface at 7 degrees C. Three carbon dioxide levels (0%, 12.5% and 25%) were combined with different levels of high oxygen concentrations (above 20%) based on a mixture design. The applied oxygen concentrations did not significantly influence the growth. High CO2 concentrations, on the contrary, reduced the maximum specific growth rate and prolonged the lag time. An overall model to describe the growth of L. innocua under high carbon dioxide conditions was constructed based on nine growth experiments, using a weighted one-step regression procedure. The influence of carbon dioxide on lag time and maximum specific growth rate was described using Ratkowsky-type models and inserted in the Baranyi equation. The model described the growth very well. To assess the validity of the model, 14 additional experiments were carried out. There was a good correlation of the model predictions and observed validation data.

Analysis of a novel class of predictive microbial growth models and application to coculture growth.

In this paper, a novel class of microbial growth models is analysed. In contrast with the currently used logistic type models (e.g., the model of Baranyi and Roberts [Baranyi, J., Roberts, T.A., 1994. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23, 277-294]), the novel model class, presented in Van Impe et al. (Van Impe, J.F., Poschet, F., Geeraerd, A.H., Vereecken, K.M., 2004. Towards a novel class of predictive microbial growth models. International Journal of Food Microbiology, this issue), explicitly incorporates nutrient exhaustion and/or metabolic waste product effects inducing stationary phase behaviour. As such, these novel model types can be extended in a natural way towards microbial interactions in cocultures and microbial growth in structured foods. Two illustrative case studies of the novel model types are thoroughly analysed and compared to the widely used model of Baranyi and Roberts. In a first case study, the stationary phase is assumed to be solely resulting from toxic product inhibition and is described as a function of the pH-evolution. In the second case study, substrate exhaustion is the sole cause of the stationary phase. Finally, a more complex case study of a so-called P-model is presented, dealing with a coculture inhibition of Listeria innocua mediated by lactic acid production of Lactococcus lactis.

Spectroscopic evaluation of the surface quality of apple.

Different spectroscopic techniques based on infrared and Raman were used to evaluate the natural wax and related surface quality of apple fruit. Transmission near-infrared (NIR) spectroscopy was applied to solutions of single wax components and extracted apple wax. Fourier transform infrared (FTIR) spectroscopy was used for transmission measurements of wax films on NaCl crystals, diffuse reflectance spectroscopy (DRIFTS) was used to analyze wax powders, and FT-Raman spectroscopy was explored to examine intact wax layers on whole fruit. The natural wax layers of apple fruit from a maximum of three different cultivars (Jonagold, Jonagored, and Elshof) from three picking dates (early, commercial, and late), three controlled atmosphere storage durations (0, 4, and 8 months), and three shelf life periods (0, 1, and 2 weeks) within each storage duration were examined. Canonical discriminant analysis was carried out on the first derivative NIR and FTIR spectra to describe the information contained in the spectra. Discrimination between cultivars and between storage duration based on wax layer properties was achieved with reasonable accuracy from both of the techniques. Information contained in the spectra of apples from different picking dates and shelf life periods was not significant. Differences between cultivars and storage periods in this analysis mostly related to differences in the number of aliphatic chains (e.g., alkanes and esters) and the presence of alpha-farnesene. No satisfactory results were obtained by means of Raman spectroscopy and DRIFTS.