Use of computerized models to reduce the consequences of major outbreaks of food-borne illness

Food-borne outbreak modelling is a technique by which statistical methodologies and data are used to model various aspects of food contamination outbreaks, with the primary goal of helping to reduce the threat of food-borne illness. There are two primary approaches to such modelling: risk ranking and pathway analysis. These two approaches fulfil different needs and are used side by side to help mitigate the risks of food-borne outbreaks. The increasing severity and impact of food poisoning outbreaks are increasing the need for new techniques to enable rapid detection and response to outbreaks whilst they are still in process. One such novel technique is implemented in the 'Consequence Management System', a computerized model that uses a structured, phased form of pathway analysis to model the entire evolution of food-borne illnesses involving scenarios of contamination of specific food products with various agents. The results of these models help in the evaluation of the probable consequences of the scenarios, the optimal ways to intervene in their evolution to reduce these consequences, and the overall risk associated with different products and agents.     

Multiresponse modelling of the caramelisation reaction

Multiresponse modelling is a powerful tool for studying complex kinetics of reactions occurring in food products. This modelling technique uses information of reactants and products involved, allowing insightful kinetic parameters estimation and helping in clarifying reaction mechanisms. One example of a complex reaction that occurs in food processing is the caramelisation reaction. Caramelisation is the common name for a group of reactions observed when carbohydrates are exposed to high temperatures.The objective of this work was to apply multiresponse regression in developing a mathematical mechanistic model that describes sucrose thermal degradation and caramelisation products formation in highly concentrated sucrose solutions, with different water contents and under various temperatures.Results demonstrated the usefulness of multiresponse modelling in understanding reaction mechanisms in food matrices. A mechanistic model for the caramelisation reaction was proposed, which successfully described the experimental data of concentrated solutions in the 30.03 to 12.20% (w/w) water content range. Furthermore, good predictions of temperature and water content effects were achieved. For extremely low water content systems (3.58% (w/w)), the proposed mechanistic model failed to describe experimental data, indicating different reaction pathways.Industrial relevanceCaramelisation is one reaction occurring during heat treatment in high sugar content food products. Understanding the mechanism of caramelisation reaction and the effect of the environmental conditions on different reaction steps may help in the design of products and processes, in order to prevent or promote such occurrence. This work also uses an advanced modelling technique that can be used in any food system for any reaction occurring during processing.     

High-resolution, continuous method for measurement of acidity in ice cores

The acid content of ice core samples provides information regarding the history of volcanism, biogenic activity, windblown dust, forest fires, and pollution-induced acid rain. A continuous ice core analysis allows for collection of high-resolution data in a very efficient manner, but this technique has not been readily applied to the measurement of pH and acidity in ice cores. The difficulty arises because the sample is highly undersaturated with respect to carbon dioxide (CO(2)) immediately after melting, making it difficult to maintain stable concentrations of dissolved carbon dioxide and carbonic acid (H(2)CO(3)). Here, we present a solution to this problem in the form of a small flow-through bubbling chamber that is supplied with a known concentration of CO(2). The bubbling action allows for quick equilibration while the small size of the chamber limits sample mixing in order to maintain high resolution. Thorough error analysis provides a measurement uncertainty of ±0.20 μM or ±5% of the acidity value, whichever is greater, and the T95 signal response time is determined to be 1.25 min. The performance of the technique is further evaluated with data from a 63-year ice core from northwest Greenland for which all major ion species were also measured. The measured acidity closely matches the acidity derived from a charge balance calculation, indicating that all of the analytes were measured accurately. The performance specifications that we provide are applicable to ice cores with low concentrations of alkaline dust (<500 ppb), which includes the vast majority of ice cores that are collected. To date, the method has not been evaluated with samples containing high alkaline dust concentrations, such as Greenland cores from the last glacial period, where measurement could be made difficult by memory effects as particles coat the internal surfaces of the sample stream.     

A further investigation of the influence of dietary protected lipid supplements on the characteristics of cows' milk fat

Dairy cows were offered diets containing three commercially available lipid supplements to determine their effect on milk fat composition and melting properties. Changes in fatty acid composition were observed. These were similar irrespective of supplement and agreed with the general trends reported in the literature. Changes in triglyceride composition were also found and these again were similar irrespective of supplement. However, the melting behaviour of the milk fats was different and may possibly be explained by changes in triglyceride structure. Compatibility of the dietary modified milk fats in mixtures with cocoa butter was examined using iso-solid diagrams produced by a computer-aided modelling technique. The differences in compatibility observed were small in magnitude but may still be important to the chocolate manufacturer.     

Prediction of peptides in the fermented cocoa storage protein,with reference to the modelled 3D structure

The amino acid sequence and a model for the three-dimensional (3D) structure of the cocoa storage protein have been combined with available data from protease digestions to aid understanding of factors that contribute to the characteristic cocoa aroma. Data reported for the free amino acids liberated during extensive digestions, modelling the fermentation process, are compared to computer predictions. Since good agreement is obtained between experiment and theory for the free amino acids, the modelling can be used to study properties not yet reported experimentally. In particular, the peptides that remain after digestion are predicted, highlighting those sequences which may play important roles in the production of cocoa aroma. This approach could prove equally useful in understanding other such systems. © 1998 SCI.     

Microbial growth modelling with artificial neural networks

There is a growing interest in modelling microbial growth as an alternative to time-consuming, traditional, microbiological enumeration techniques. Several statistical models have been reported to describe the growth of different microorganisms, but there are accuracy problems. An alternate technique 'artificial neural networks' (ANN) for modelling microbial growth is explained and evaluated. Published data were used to build separate general regression neural network (GRNN) structures for modelling growth of Aeromonas hydrophila, Shigella flexneri, and Brochothrix thermosphacta. Both GRNN and published statistical model predictions were compared against the experimental data using six statistical indices. For training data sets, the GRNN predictions were far superior than the statistical model predictions, whereas the GRNN predictions were similar or slightly worse than statistical model predictions for test data sets for all the three data sets. GRNN predictions can be considered good, considering its performance for unseen data. Graphical plots, mean relative percentage residual, mean absolute relative residual, and root mean squared residual were identified as suitable indices for comparing competing models. ANN can now become a vehicle whereby predictive microbiology can be applied in food product development and food safety risk assessment.     

Application of artificial neural networks to describe the combined effect of pH and NaCl on the heat resistance of Bacillus stearothermophilus

A model for prediction of bacterial spore inactivation was developed. The influence of temperature, pH and NaCl on the heat resistance of Bacillus stearothermophilus spores was described using low-complexity, black box models based on artificial neural networks. Literature data were used to build and train the neural network, and new experimental data were used to evaluate it. The neural network models gave better predictions than the classical quadratic response surface model in all the experiments tried. When the neural networks were evaluated using new experimental data, also good predictions were obtained, providing fail-safe predictions of D values in all cases. The weights and biases values of neurons of the neural network that gave the best results are presented, so the reader can use the model for their own purposes. The use of this non-linear modelling technique makes it possible to describe more accurately interacting effects of environmental factors when compared with classical predictive microbial models.     

A novel area of predictive modelling: describing the functionality of beneficial microorganisms in foods

Predictive microbiology generally focuses on the potential outgrowth of spoilage bacteria and foodborne pathogens in foods. Little attention has been paid to the biokinetics of beneficial foodgrade microorganisms, such as lactic acid bacteria. The latter is commonly used in the food fermentation industry, mainly for the in situ production of the antimicrobial lactic acid to extend the shelf life of the food. Furthermore, many strains show additional industrial potential as novel starter cultures since they produce functional metabolites, such as bacteriocins and exopolysaccharides. The production of these functional metabolites has been demonstrated during in vitro experiments, but in many cases these novel starter cultures seem to be less efficient when applied in a food system. A modelling approach may contribute to a better understanding of the tight relation between the food environment and bacterial functionality. Primary modelling can be applied to fit the experimental data concerning cell growth, sugar metabolism, and the production of functional metabolites for a given set of environmental conditions. This led to conclusions concerning the growth-associated production of bacteriocin and exopolysaccharides, the inactivation of these molecules when cell growth levels off, and a minimum cell concentration to trigger on bacteriocin production. Examples deal with the production of the bacteriocin sakacin K by the natural fermented sausage isolate Lactobacillus sakei CTC 494, and the production of heteropolysaccharides by the yoghurt starter culture Streptococcus thermophilus LY03. Secondary modelling of biokinetic parameters quantifies the production of bacteriocin and exopolysaccharides in function of environmental factors. As an example, the specific bacteriocin production by Lb. sakei CTC 494 decreases with increasing sodium chloride concentrations. Furthermore, since the assessment of functionality is frequently hampered by the nature of the food system, mathematical modelling techniques may help to predict the functional behaviour of novel lactic acid bacteria starter cultures in a food matrix, and hence quantify in situ production. For example, a model may simulate cell growth and exopolysaccharide production of S. thermophilus LY03 in a milk environment, where direct measurements are difficult to perform.     

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R(2)=0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R(2)≥0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate data analysis modelling.     

Rheological characterisation of age thickening with special reference to milk concentrates

Age thickening is a well known phenomenon within the dairy industry, where the apparent viscosity of concentrated dairy solutions increases with storage time under low shear. The objective of the paper is to develop new tools to analyse several aspects of age thickening, including the increases in shear thinning, the degree of thixotropy and the rate of structural build up with time, as well as irreversible structural changes and gelation. The build up of the dispersed phase structure during storage, was captured by a snap shot technique, where concentrated milk samples were stored, and aliquots were taken at periodic intervals and subjected to shear sweep tests to collect flow curves. Rheological modelling using the Herschel-Bulkley model showed an increase in yield stress and consistency, indicating a build up in structure during age thickening. The trend in apparent viscosity with storage time showed two-phases, a slow and steady increase followed by a sharp rise, which could be used to identify the onset of firm gelation. The extrapolated viscosity at infinite shear rate increased with storage time, indicating the build up in irreversible structural components during age thickening.     

Analysis of reduced phosphorus in samples of environmental interest

The combination of ion chromatography (IC) and inductively coupled plasma emission spectroscopy (ICP-ES) was used forthe sensitive and specific detection of hypophosphite (PO2), phosphite (PO3), methylphosphonic acid (MPA), and phosphate (PO4). Application of this technique to a wide range of environmental samples proved that reduced phosphorus was present in some situations including process water from thermal phosphorus plants, drinking water contacting cast iron, and phosphorus corrosion inhibitor used in water treatment and in sewage wastewater. Preliminary testing did not detect high concentrations of reduced phosphorus and phosphine in situations where it was previously reported to be very important, including anaerobic digesters in wastewater treatment plants. The new IC-ICP-ES technique is a promising tool for use in corrosion and soil research where phosphites are likely to be present.     

Sorption equilibrium of a wide spectrum of organic vapors in Leonardite humic acid: experimental setup and experimental data

The environmental fate of volatile and semivolatile organic compounds is determined by their partitioning between air and soil constituents, in particular soil organic matter (SOM). While there are many studies on the partitioning of nonpolar compounds between water and SOM, data on sorption of polar compounds and data for sorption from the gas phase are rather limited. In this study, Leonardite humic acid/air partition coefficients for 188 polar and nonpolar organic compounds at temperatures between 5 and 75 degrees C and relative humidities between < 0.01% and 98% have been determined using a dynamic flow-through technique. To the best of our knowledge, this is by far the largest and most diverse and consistent data set for sorption into humic material published so far. The major results are as follows: the relative humidity affected the experimental partition coefficients by up to a factor of 3; polar compounds generally sorbed more strongly than nonpolar compounds due to H-bonding (electron donor/ acceptor interactions) with the humic acid; no glass transitions in the range of 5-75 degrees C that would be relevant with respect to the sorption behavior of hydrated Leonardite humic acid were observed; our experimental data agree well with experimental partition coefficients from various literature sources.     

Effect of sonication on colour,ascorbic acid and yeast inactivation in tomato juice

Power ultrasound is recognised as a potential non-thermal technique to inactivate micro-organisms pertinent to fruit juices. In this study tomato juice was sonicated at different amplitude levels (24.4–61.0 μm) at a constant frequency of 20 kHz for treatment times (2–10 min) and pulse durations of 5 s on and 5 s off. Hunter colour values (L∗, a∗ and b∗), pH, °Brix, titratable acidity, ascorbic acid and yeast inactivation were measured. No significant differences (p < 0.05) in pH, °Brix or titratable acidity were observed. Regression modelling was used to investigate the main effects of amplitude level and treatment time. Prediction models were found to be significant (p < 0.05) with low standard errors and high coefficients of determination (R²). Model predictions for critical quality parameters of Hunter colour values (L∗, a∗ and b∗), ascorbic acid and yeast inactivation were closely correlated with the experimental results obtained.     

A new rapid technique for detection of microorganisms using bioluminescence and fluorescence microscope method

The MicroStar-RMDS-SPS (RMDS; R apid M icrobe D etection S ystem) enables detection and determination of the number of microorganisms trapped on a membrane filter based on the ATP-bioluminescence method. However, this system could not provide information about the identity of contaminating species based on the measurement results. Therefore, we developed a new technique for observing microcolonies of contaminants using a fluorescence microscope (Micro Scanner). The coordinates in the image data of the RMDS were converted to the coordinates of the sample stage of the microscope, and a microcolony could be easily observed. A single yeast cell and a microcolony consisting of 20-30 lactic acid bacterial cells could be observed on a membrane filter after measurement using the RMDS.     

Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.     

基于模糊数学集模型构建的发酵蚝油品质组分评定研究

以牡蛎发酵蚝油为研究对象,对牡蛎不同发酵时间获得的发酵蚝油产品的品质组分进行研究,目的是为蚝油组分的品质评价提供理论依据和新的研究方法,以牡蛎不同发酵时间的蚝油产品的重要指标氨基酸含量、脂肪含量和蛋白质含量为评价因素建立模糊数据集,以模糊测度技术对发酵蚝油进行品质组分评价,通过隶属度矩阵作出客观评价,为模糊测度技术的熟练运用提供了基础,通过和实际测定结果比较,该方法的准确度极高。     

Modelling the effect of UV light at different wavelengths and treatment combinations on the inactivation of Campylobacter jejuni

Application of novel decontamination strategies such as Ultraviolet (UV) irradiation are required to mitigate the risks associated with Campylobacter jejuni in food. This study evaluated the use of a light-emitting diode (LED) based technology to inactivate C. jejuni NCTC 11168 in Maximum Recovery Diluent (MRD) at wavelengths of 280, 300 and 365 nm and combinations. To assess the survival curves, two linear (Log linear (LL) and Linear and Shoulder) and two non-linear models (Weibull and Double Weibull) were fitted. UV exposures showed different antimicrobial effects where a combination of 280/300 nm was the most effective treatment with a 4D_t value of 5 s observed in a bacterial suspension of 5 log CFU/mL. Moreover, the LL model was the most robust model to describe the inactivation kinetics of Campylobacter when exposed to UV and therefore, modelling tools could be applied to predict the efficiency of UV light in a model solution.Industrial relevance: Light-based technologies like UV light are identified in the literature as potential alternatives to assure the decontamination of surfaces, liquids and solid food. However, some of these techniques require further investigation. The present study evaluated the use of a LED system and effect of combined wavelengths in the inactivation of Campylobacter through predictive modelling. This technique was observed to predict and explain kinetics of inactivation of Campylobacter and could be key in the scaling-up process of UV light at industrial level.     

β-Lactoglobulin heat denaturation: A critical assessment of kinetic modelling

Bovine whey protein β-lactoglobulin (β-lg) will denature above 70 °C. Denaturation may contribute positively or negatively to food functionality, so it is important to control the degree of denaturation during milk processing. This work critically examined the kinetic modelling of β-lg denaturation in water, buffer or milk at 70–150 °C using the general rate law for a single-species reaction and the Arrhenius equation. Several published datasets, originally analysed in linearised form, were re-analysed with nonlinear regression, which preserves the error structure of data and estimates the precision of parameters. This work discusses statistical best practice for modelling the heat denaturation of β-lg, explores the criteria for using 2- or 3-parameter regression equations, and proposes new approaches for modelling the concentration- and temperature-dependence of denaturation rates. These new approaches improved the accuracy and precision of kinetic parameter estimates, and revealed new details of how solution conditions influence β-lg denaturation rates.     

Evaluation of A Modified Gradient Feed Culturing System for Growth of Lactobacillus plantarum Sausage Starter Organism

An internally controlled gradient feed culturing technique, where a nutrient gradient was initiated and subsequently controlled by the lactic acid synthesis, was compared to conventional batch culturing for growth of a sausage starter organism, Lactobacillus plantarum. Significantly higher cell densities (p < 0.01) were observed with twice the culturing time for gradient feed culturing compared to batch culturing. Cell yields within batch or gradient feed culturing system were not affected by pH control at 5.8 or 6.0. Significantly higher (p < 0.05) cell yields, however, were obtained for gradient feed cultures (pH 6.0) with NH₄OH addition at 50% theoretical lactic acid (TLA) level than were obtained at 10% TLA or without NH₄OH addition.     

Fitting of colony diameter and ergosterol as indicators of food borne mould growth to known growth models in solid medium

Growth of a range of 14 common food spoilage fungal species was evaluated along time as a function of both colony diameter and ergosterol content on malt extract agar. Growth was assessed under different environmental conditions following a central composite design. The suitability of using either linear, Gompertz's or Baranyi's models for primary modelling of the results was tested. Regarding colony diameters, using either linear or asymptotic Baranyi's function gave better estimations of growth rate and lag phase when no asymptotic trend was observed. When a decrease in growth rate was observed with time, standard Baranyi's model was chosen, although the search for new mechanistic models specific for moulds would probably improve the estimations. The use of Gompertz equation led, in general, to overestimated parameters. Ergosterol showed good performance as a fungal growth indicator for the whole range of species. Finally, significant correlation coefficients were found between ergosterol and colony diameters, suggesting that both parameters may be useful for primary modelling and thus for subsequent secondary modelling.