876 resultados para Continuous fermentation


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It is now apparent that there is a strong link between health and nutrition and this can be seen clearly when we talk of obesity. The food industry is trying to capitalise on this by adapting high sugar/fat foods to become healthier alternatives. In confectionery food ingredients can be used for a range of purposes including sucrose replacement. Many of these ingredients may also evade digestion in the upper gut and be fermented by the gut microbiota upon entering the colon. This study was designed to screen a range of ingredients and their activities on the gut microbiota. In this study we screened a range of these ingredients in triplicate batch culture fermentations with known prebiotics as controls. Changes in bacteriology were monitored using FISH. SCFA were measured by GC and gas production was assessed during anaerobic batch fermentations. Bacterial enumeration showed significant increases (P ≤ 0.05) in bifidobacteria and lactobacilli with polydextrose and most polyols with no significant increases in Clostridium histolyticum/perfringens. SCFA and gas formation indicated that the substrates added to the fermenters were being utilised by the gut microbiota. It therefore appears these ingredients exert some prebiotic activity in vitro. Further studies, particularly in human volunteers, are necessary.

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Rifaximin, a rifamycin derivative, has been reported to induce clinical remission of active Crohn's disease (CD), a chronic inflammatory bowel disorder. In order to understand how rifaximin affects the colonic microbiota and its metabolism, an in vitro human colonic model system was used in this study. We investigated the impact of the administration of 1800 mg/day of rifaximin on the faecal microbiota of four patients affected by colonic active CD [Crohn's disease activity index (CDAI > 200)] using a continuous culture colonic model system. We studied the effect of rifaximin on the human gut microbiota using fluorescence in situ hybridization, quantitative PCR and PCR–denaturing gradient gel electrophoresis. Furthermore, we investigated the effect of the antibiotic on microbial metabolic profiles, using 1H-NMR and solid phase microextraction coupled with gas chromatography/mass spectrometry, and its potential genotoxicity and cytotoxicity, using Comet and growth curve assays. Rifaximin did not affect the overall composition of the gut microbiota, whereas it caused an increase in concentration of Bifidobacterium, Atopobium and Faecalibacterium prausnitzii. A shift in microbial metabolism was observed, as shown by increases in short-chain fatty acids, propanol, decanol, nonanone and aromatic organic compounds, and decreases in ethanol, methanol and glutamate. No genotoxicity or cytotoxicity was attributed to rifaximin, and conversely rifaximin was shown to have a chemopreventive role by protecting against hydrogen peroxide-induced DNA damage. We demonstrated that rifaximin, while not altering the overall structure of the human colonic microbiota, increased bifidobacteria and led to variation of metabolic profiles associated with potential beneficial effects on the host.

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Multiparous rumen-fistulated Holstein cows were fed, from d 1 to 28 post-calving, an ad libitum TMR containing (g/kg DM) grass silage (196), corn silage (196), wheat (277), soybean meal (100), and other feeds (231) with CP, NDF, starch and water soluble carbohydrate concentrations of 176, 260, 299 and 39 g/kg DM respectively and ME of 12.2 MJ/kg DM. Treatments consisting of a minimum of 1010 cfu Megasphaera elsdenii NCIMB 41125 in 250 ml solution (MEGA) or 250 ml of autoclaved M. elsdenii (CONT) were administered via the rumen cannula on d 3 and 12 of lactation (n=7 per treatment). Mid-rumen pH was measured every 15 minutes and eating and ruminating behavior was recorded for 24 h on d 2, 4, 6, 8, 11, 13, 15, 17, 22 and 28. Rumen fluid for VFA and lactic acid (LA) analysis was collected at 11 timepoints on each of d 2, 4, 6, 13 and 15. Data were analysed as repeated measures using the Glimmix (LA data) or Mixed (all other data) procedures of SAS with previous 305 d milk yield and d 2 measurements as covariates where appropriate. Milk yield was higher (CONT 43.0 vs MEGA 45.4 ±0.75 kg/d, P=0.051) and fat concentration was lower (CONT 45.6 vs MEGA 40.4 ±1.05 g/kg, P=0.005) in cows that received MEGA. Time spent eating (263 ±15 min/d) and ruminating (571 ±13 min/d), DM intake (18.4 ±0.74 kg/d), proportion of each 24 h period with rumen pH below 5.6 (3.69 ±0.94 h) and LA concentrations (2.00 mM) were similar (P>0.327) across treatments. Ruminal total VFA concentration (104 ±3 mM) was similar (P=0.404) across treatments, but a shift from acetate (CONT 551 vs MEGA 524 ±14 mmol/mol VFA, P=0.161) to propionate production (CONT 249 vs MEGA 275 ±11 mmol/mol VFA, P=0.099) meant that the acetate:propionate ratio (CONT 2.33 vs MEGA 1.94 ±0.15) was reduced (P=0.072) in cows that received MEGA. This study provides evidence that supplementation of early lactation dairy cows with MEGA alters rumen fermentation patterns in favour of propionate, with potential benefits for animal health and productivity.

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A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.

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This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

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This work provides a framework for the approximation of a dynamic system of the form x˙=f(x)+g(x)u by dynamic recurrent neural network. This extends previous work in which approximate realisation of autonomous dynamic systems was proven. Given certain conditions, the first p output neural units of a dynamic n-dimensional neural model approximate at a desired proximity a p-dimensional dynamic system with n>p. The neural architecture studied is then successfully implemented in a nonlinear multivariable system identification case study.

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Population studies have shown a positive correlation between diets rich in whole grains and a reduced risk of developing metabolic diseases, like diabetes, cardiovascular disease, and certain cancers. However, little is known about the mechanisms of action, particularly the impact different fermentable components of whole grains have on the human intestinal microbiota. The modulation of microbial populations by whole grain wheat flakes and the effects of toasting on digestion and subsequent fermentation profile were evaluated. Raw, partially toasted, and toasted wheat flakes were digested using simulated gastric and small intestinal conditions and then fermented using 24-hour, pH-controlled, anaerobic batch cultures inoculated with human feces. Major bacterial groups and production of short-chain fatty acids were compared with those for the prebiotic oligofructose and weakly fermented cellulose. Within treatments, a significant increase (P<.05) in bifidobacteria numbers was observed upon fermentation of all test carbohydrates, with the exception of cellulose. Toasting appeared to have an effect on growth of lactobacilli as only fermentation of raw wheat flakes resulted in a significant increase in levels of this group.

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This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the stationary ARMA(2, 1) model with stock variables (with applications to sunspot data and a short-term interest rate) and one concerning the nonstationary ARMA(2, 1) model with a flow variable (with an application to U.S. nondurable consumers’ expenditure). In all three examples the presence of an MA(1) component in the continuous time system has a dramatic impact on eradicating unaccounted-for serial correlation that is present in the discrete time version of the ARMA(2, 0) specification, even though the form of the discrete time model is ARMA(2, 1) for both models.

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The cheese industry has continually sought a robust method to monitor milk coagulation. Measurement of whey separation is also critical to control cheese moisture content, which affects quality. The objective of this study was to demonstrate that an online optical sensor detecting light backscatter in a vat could be applied to monitor both coagulation and syneresis during cheesemaking. A prototype sensor having a large field of view (LFV) relative to curd particle size was constructed. Temperature, cutting time, and calcium chloride addition were varied to evaluate the response of the sensor over a wide range of coagulation and syneresis rates. The LFV sensor response was related to casein micelle aggregation and curd firming during coagulation and to changes in curd moisture and whey fat contents during syneresis. The LFV sensor has potential as an online, continuous sensor technology for monitoring both coagulation and syneresis during cheesemaking.

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B. subtilis under certain types of media and fermentation conditions can produce surfactin, a biosurfactant which belongs to the lipopeptide class. Surfactin has exceptional surfactant activity, and exhibits some interesting biological characteristics such as antibacterial activity, antitumoral activity against ascites carcinoma cells, and a hypocholesterolemic activity that inhibits cAMP phosphodiesterase, as well as having anti-HIV properties. A cost effective recovery and purification of surfactin from fermentation broth using a two-step ultrafiltration (UF) process has been developed in order to reduce the cost of surfactin production. In this study, competitive adsorption of surfactin and proteins at the air-water interface was studied using surface pressure measurements. Small volumes of bovine serum albumin (BSA) and β-casein solutions were added to the air-water interface on a Langmuir trough and allowed to stabilise before the addition of surfactin to the subphase. Contrasting interfacial behaviour of proteins was observed with β-casein showing faster initial adsorption compared to BSA. On introduction of surfactin both proteins were displaced but a longer time were taken to displace β-casein. Overall the results showed surfactin were highly surface-active by forming a β-sheet structure at the air-water interface after reaching its critical micelle concentration (CMC) and were effective in removing both protein films, which can be explained following the orogenic mechanism. Results showed that the two-step UF process was effective to achieve high purity and fully functional surfactin.