Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants

The temperature-time profiles of 22 Australian industrial ultra-high-temperature (UHT) plants and 3 pilot plants, using both indirect and direct heating, were surveyed. From these data, the operating parameters of each plant, the chemical index C*, the bacteriological index B* and the predicted changes in the levels of beta-lactoglobulin, alpha-lactalbumin, lactulose, furosine and browning were determined using a simulation program based on published formulae and reaction kinetics data. There was a wide spread of heating conditions used, some of which resulted in a large margin of bacteriological safety and high chemical indices. However, no conditions were severe enough to cause browning during processing. The data showed a clear distinction between the indirect and direct heating plants. They also indicated that degree of denaturation of alpha-lactalbumin varied over a wide range and may be a useful discriminatory index of heat treatment. Application of the program to pilot plants illustrated its value in determining processing conditions in these plants to simulate the conditions in industrial UHT plants. (C) 2008 Elsevier Ltd. All rights reserved.

Serpa cheese: technological, biochemical and microbiological characterisation of a PDO ewe's milk cheese coagulated with Cynara cardunculus L

Portugal has a strong tradition of cheesemaking from raw ewe's milk; most of these cheeses are still made on a traditional farmhouse scale. Their production is protected by Protected Designation of Origin (PDO) but the specific biochemical aspects of the majority still need to be characterised. Two different cheesemaking procedures, traditional and semi-industrial, were compared technologically, biochemically and microbiologically. It was observed that, despite the highly significant difference between artisanal and semi-industrial cheeses (P < 0.001), both products were within the limits of national regulations for most parameters except maturation temperature, humidity and the value for the maturation index. Although the present study was not fully representative of the region, the results obtained suggest that the specific regulations for Serpa cheese should be revised and that other parameters, such as moisture and salt-in-moisture content, which are very much dependent on the cheesemaking process, should be included in order to characterise better this traditional cheese.

Predicting the thermal inactivation of bacteria in a solid matrix: simulation studies on the relative effects of microbial thermal resistance parameters and process conditions

A combined mathematical model for predicting heat penetration and microbial inactivation in a solid body heated by conduction was tested experimentally by inoculating agar cylinders with Salmonella typhimurium or Enterococcus faecium and heating in a water bath. Regions of growth where bacteria had survived after heating were measured by image analysis and compared with model predictions. Visualisation of the regions of growth was improved by incorporating chromogenic metabolic indicators into the agar. Preliminary tests established that the model performed satisfactorily with both test organisms and with cylinders of different diameter. The model was then used in simulation studies in which the parameters D, z, inoculum size, cylinder diameter and heating temperature were systematically varied. These simulations showed that the biological variables D, z and inoculum size had a relatively small effect on the time needed to eliminate bacteria at the cylinder axis in comparison with the physical variables heating temperature and cylinder diameter, which had a much greater relative effect. (c) 2005 Elsevier B.V All rights reserved.

Changes in selected biochemical and sensory parameters as affected by the superficial inoculation of Penicillium camemberti on dry fermented sausages

An atoxigenic strain of Penicillium camemberti was superficially inoculated on fermented sausages in an attempt to improve their sensory properties. The growth of this mould on the surface of the sausages resulted in an intense proteolysis and lipolysis, which caused an increase in the concentration of free amino acids, free fatty acids (FFA) and volatile compounds. Many of these were derived from amino acid catabolism and were responsible for the "ripened flavour", i.e. branched aldehydes and the corresponding alcohols, acids and esters. The development of the fungal mycelia on the surface of the sausages also protected lipids from oxidation, resulting in both lower 2-thiobarbituric acid (TBARS) values and lipid oxidation-derived compounds, such as aliphatic aldehydes and alcohols. The sensory analysis of superficially inoculated sausages showed clear improvements in odour and flavour and, as a consequence, in the overall quality of the sausages. Therefore, this strain is proposed as a potential starter culture for dry fermented sausage production. (C) 2002 Elsevier Science B.V All rights reserved.

Effect of temperature and salt on the maturation of white-salted cheese

White-salted cheeses were prepared from ultrafiltered (UF) cows' milk and salted to give final salt-in-moisture (SM) levels of 2.5, 3.2 and 4.0%. The cheeses were stored at 5degreesC and 10degreesC for up to 15 weeks. The microflora was dominated by lactic acid bacteria (LAB) but some mould growth was evident within 15 weeks at all SM levels and both temperatures. Levels of water-soluble nitrogen (WSN), attributed to chymosin activity, increased significantly with time, the rate being inversely proportional to the SM level and increasing with storage temperature. Similar effects were noted for trichloroacetic acid-soluble nitrogen (TCA-SN) and free amino acid (FAA) levels, both of which would also be affected by bacterial protease activity. The proteolytic activity was reflected by changes in the hardness and fracturability of the cheeses.

Robust identification for linear-in-the-parameters models

In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

Estimation of Hidden Markov Models parameters using differential evolution

Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.

A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.

Are differences in life history parameters of the pine beauty moth Panolis flammea modified by host plant quality or gender?

Pine beauty moth (Panolis flammea D&S, Lepidoptera: Noctuidae) were reared individually from egg hatch to pupation on one of three host plants, Pinus sylvestris (native host plant), Pinus contorta (Central Interior seed origin - good quality introduced host) and P. contorta (Alaskan seed origin - poor quality introduced host). After emerging from the pupae the adult moths were confined to a Skeena River seed origin of P. contorta. Female pupal weight and adult life span were significantly higher on P. sylvestris than on the two lodgepole pine seed origins. Development time was, however, not significantly different between treatments, but larval mean relative growth rate was found to be negatively correlated with birth weight and positively correlated with pupal weight. The time to emerge from the pupa was also not significantly different between treatments. However, there were marked differences between the genders. Male moths lost a significantly greater proportion of their weight over the pupal stage but lived significantly longer as adults than the females. Female moths emerged from the pupal stage significantly sooner than male moths. There was no apparent advantage of lai-ge birth size when looked at in terms of subsequent performance. These results are discussed in light of current life history theory.

Maturation of limbic corticostriatal activation and connectivity associated with developmental changes in temporal discounting

Temporal discounting (TD) matures with age, alongside other markers of increased impulse control, and coherent, self-regulated behaviour. Discounting paradigms quantify the ability to refrain from preference of immediate rewards, in favour of delayed, larger rewards. As such, they measure temporal foresight and the ability to delay gratification, functions that develop slowly into adulthood. We investigated the neural maturation that accompanies the previously observed age-related behavioural changes in discounting, from early adolescence into mid-adulthood. We used functional magnetic resonance imaging of a hypothetical discounting task with monetary rewards delayed in the week to year range. We show that age-related reductions in choice impulsivity were associated with changes in activation in ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), ventral striatum (VS), insula, inferior temporal gyrus, and posterior parietal cortex. Limbic frontostriatal activation changes were specifically associated with age-dependent reductions in impulsive choice, as part of a more extensive network of brain areas showing age-related changes in activation, including dorsolateral PFC, inferior parietal cortex, and subcortical areas. The maturational pattern of functional connectivity included strengthening in activation coupling between ventromedial and dorsolateral PFC, parietal and insular cortices during selection of delayed alternatives, and between vmPFC and VS during selection of immediate alternatives. We conclude that maturational mechanisms within limbic frontostriatal circuitry underlie the observed post-pubertal reductions in impulsive choice with increasing age, and that this effect is dependent on increased activation coherence within a network of areas associated with discounting behaviour and inter-temporal decision-making.

Single trial BCI operation via Wackermann parameters

Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

Using modelling tools to optimise the calculation and subsequent reduction of cable distortion parameters with application to oil well logging systems

This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.