Daniel Picque

Validation of a new in vitro dynamic system to simulate infant digestion.

Understanding the mechanisms of infant formula disintegration in the infant gastrointestinal tract is a key step for developing new formulas with health benefits for the neonate. For ethical reasons, the access to in vivo data obtained on infants is limited. The use of animal models can be an alternative but these experiments are labour intensive, expensive and results obtained show high inter-individual variability, making their interpretation difficult. The aim of this work was to develop a simple in vitro dynamic gastrointestinal digestion system, for studying infant formula digestion, and to validate it by comparing the kinetics of proteolysis obtained in vitro with in vivo data collected from piglets. Results showed a good correlation between in vitro and in vivo data and confirmed the rapid hydrolysis of caseins in gastric conditions, whereas whey proteins appeared more resistant to digestion.

Monitoring of fermentation processes producing lactic acid bacteria by mid-infrared spectroscopy

Abstract Fourier transform mid-infrared (FT-MIR) spectroscopy was used to determine the concentrations of substrate, major metabolites and lactic acid bacteria in fermentation processes. Partial least-squares regression gave the following standard errors of prediction (SEP): 3.4 g/l for lactose, 1.5 g/l for galactose. 0.9 g/l for lactic acid and 0.9 g/l for bacterial concentration. The principal vibrational assignments for the major compounds are provided. The spectra of filtered and non-filtered culture media containing lactic acid bacteria were not different with ordinary bacterial concentrations (up to 10 g/l) using a transmission cell.

Determination of Major Compounds of Alcoholic Fermentation by Middle-Infrared Spectroscopy: Study of Temperature Effects and Calibration Methods

The potential of Fourier transform middle-infrared spectroscopy has been demonstrated for the quantitative analysis of substrates (glucose and fructose) and metabolites (glycerol and ethanol) involved in alcoholic fermentation. Temperature variations between samples and water background reference caused changes in absorbance, and therefore the prediction of concentrations with partial least-squares (PLS) regressions was affected. The same temperatures for the calibration, validation, and prediction sets gave the smallest standard error of prediction (SEP): SEPglucose = 3.9 g L−1; SEPfructose = 4.3 g L−1; SEPglycerol = 0.5 g L−1; SEPethanol = 1.3 g L−1. In order to take different working temperatures (18, 25, and 35 °C) into account, an artificial neural network was used to create a nonlinear multivariate model. Compared to PLS regression, this method provided better results, especially for glycerol and ethanol, where SEP decreased by 0.3 g L−1 and 0.4 g L−1, respectively.

Characterizing acidification kinetics by measuring pH and electrical conductivity in batch thermophilic lactic fermentations

Abstract On-line measurements of pH and electrical conductivity data have made it possible to access time and rate feature points of thermophilic lactic acid fermentations. Ten feature points characterize curves of acidification and conductivity changes using the main points of inflection observed. The presence or absence of urease also changes the observed kinetics and corresponding feature points. These phenomena and the time patterns of the biomass and products permit an understanding of the meanings of the feature points. These points showed the excellent reproducibility of fermentations conducted in standard conditions, with coefficients of variation lower than 5.1% for nine of them. They were also used to compare the effects of the type of starter, temperature and culture medium. The temperature affects the urease activity and acidification optima. The presence of fat (32 g/l) in the medium does not change any feature point, while the presence of sucrose (90 g/l) results in a decrease in the acidification rate and a longer fermentation time.

Methods for the determination of aroma compounds in dairy products: a comparative study

Several methods used for sample preparation and for the determination of volatile flavour compounds in dairy products were tested. Steam distillation was an advantageous method for isolating volatile substances. The extraction yields for acetaldehyde, ethanol and diacetyl were >90%, and acetoin was partly separated from diacetyl. After steam distillation of the sample, gas-liquid chromatography was found to be a rapid method for the determination of acetaldehyde, ethanol and diacetyl in a wide range of concentrations corresponding to those found in dairy products. However, the lower limits for reproducible measurements were high (250, 1250 and 65 μM respectively). From the same sample, colorimetry was shown to be an accurate method for the detection of low levels of diacetyl and acetoin (12 and 57 μM respectively). Diacetyl interfered in the colorimetrie determination of acetoin. However, the interference was

Effect of temperature on diacetyl and acetoin production by Lactococcus lactis subsp. lactis biovar diacetilactis CNRZ 483

We have investigated the effect of culture temperature on the growth of Lactococcus lactis subsp. lactis biovar diacetilactis , on its acidifying power, on diacetyl and acetoin production, and also on the activities of the principal enzymes involved in the synthesis of these two compounds. The rates of growth and lactic acid production decreased by a factor of ∼ 2 when the temperature decreased from 30 to 18°C. At 18°C, the maximal concentration of diacetyl (0·3mM) was 1·7 times that at 30°C, while that of acetoin was unchanged (5·2 mM). These results are explained by the behaviour of the principal enzymes involved in pyruvate metabolism. The activities of lactic dehydrogenase and acetolactate synthase varied little for culture temperatures between 18 and 30·C. However, the activity of NADH oxidase for a culture temperature of 18°C was 3·7 times that for 30°C, while that of diacetyl reductase for 30°C was 2·7 times that for 18°C. The net effect of temperature on these two activities was an increase in diacetyl production at lower temperature.

PRODUCTION OF METHYLANTHRANILATE BY THE BASIDIOMYCETE PYCNOPORUS CINNABARINUS (KARST.)

SummaryPyncnoporus cinnabarinus (Polyporaceae) is able to produce methylanthranilate in liquid cultures. Study of the culture conditions of P. cinnabarinus IP I-937 has permitted increase in the aroma productivity by a factor of 16. A low nitrogen concentration, with maltose as carbon source, was required; the culture pH was uncontrolled. The inoculum nature and concentration greatly influence on production: best results were obtained with conidia from a late harvest, used at a rate of 2 × 105 spores/ml. Under these conditions, 18.7 mg methylanthranilate/l was produced after 5 days of culture. Aroma production is probably connected with the biosynthesis of phenoxazinones, which are characteristic pigments of the genus Pycnoporus.

Dynamics of Penicillium camemberti growth quantified by real-time PCR on Camembert-type cheeses under different conditions of temperature and relative humidity

Penicillium camemberti plays a major role in the flavor and appearance of Camembert-type cheeses. However, little is known about its mycelium growth kinetics during ripening. We monitored the growth of P. camemberti mycelium in Camembert-type cheeses using real-time PCR in 4 ripening runs, performed at 2 temperatures (8 and 16°C) and 2 relative humidities (88 and 98%). These findings were compared with P. camemberti quantification by spore concentration. During the first phase, the mycelium grew but no spores were produced, regardless of the ripening conditions. During the second phase, which began when lactose was depleted, the concentration of spores increased, especially in the cheeses ripened at 16°C. Sporulation was associated with a large decrease in the mycelial concentration in the cheeses ripened at 16°C and 98% relative humidity. It was hypothesized that lactose is the main energy source for the growth of P. camemberti mycelium at the beginning of ripening and that its depletion would trigger stress, resulting in sporulation.

Temperature and relative humidity influence the microbial and physicochemical characteristics of Camembert-type cheese ripening

To evaluate the effects of temperature and relative humidity (RH) on microbial and biochemical ripening kinetics, Camembert-type cheeses were prepared from pasteurized milk seeded with Kluyveromyces marxianus, Geotrichum candidum, Penicillium camemberti, and Brevibacterium aurantiacum. Microorganism growth and biochemical changes were studied under different ripening temperatures (8, 12, and 16°C) and RH (88, 92, and 98%). The central point runs (12°C, 92% RH) were both reproducible and repeatable, and for each microbial and biochemical parameter, 2 kinetic descriptors were defined. Temperature had significant effects on the growth of both K. marxianus and G. candidum, whereas RH did not affect it. Regardless of the temperature, at 98% RH the specific growth rate of P. camemberti spores was significantly higher [between 2 (8°C) and 106 times (16°C) higher]. However, at 16°C, the appearance of the rind was no longer suitable because mycelia were damaged. Brevibacterium aurantiacum growth depended on both temperature and RH. At 8°C under 88% RH, its growth was restricted (1.3 × 10(7) cfu/g), whereas at 16°C and 98% RH, its growth was favored, reaching 7.9 × 10(9) cfu/g, but the rind had a dark brown color after d 20. Temperature had a significant effect on carbon substrate consumption rates in the core as well as in the rind. In the rind, when temperature was 16°C rather than 8°C, the lactate consumption rate was approximately 2.9 times higher under 88% RH. Whatever the RH, temperature significantly affected the increase in rind pH (from 4.6 to 7.7 ± 0.2). At 8°C, an increase in rind pH was observed between d 6 and 9, whereas at 16°C, it was between d 2 and 3. Temperature and RH affected the increasing rate of the underrind thickness: at 16°C, half of the cheese thickness appeared ripened on d 14 (wrapping day). However, at 98% RH, the underrind was runny. In conclusion, some descriptors, such as yeast growth and the pH in the rind, depended solely on temperature. However, our findings highlight the fact that the interactions between temperature and RH played a role in P. camemberti sporulation, B. aurantiacum growth, carbon substrate consumption rates, and the thickening of the cheese underrind. Moreover, the best ripening conditions to achieve an optimum between microorganism growth and biochemical kinetics were 13°C and 94% RH.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity.

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system.