The Experts below are selected from a list of 19137 Experts worldwide ranked by ideXlab platform
Georges Corrieu - One of the best experts on this subject based on the ideXlab platform.
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pH prediction and Final Fermentation time determination in lactic acid batch Fermentations
Computers & Chemical Engineering, 2002Co-Authors: Eric Latrille, Georges Corrieu, Jules ThibaultAbstract:Abstract For the control of lactic acid batch Fermentations, the prediction of the pH over a long time horizon and the determination of the Final Fermentation time are very useful information. Lactic acid batch Fermentations, with uncontrolled pH, are modelled with a feedforward neural network to generate the model (pH versus time) of a reference Fermentation of Streptococcus thermophilus strain on skim milk. In essence, the feedforward neural network is used as a general nonlinear model to store the information of a series of well-behaved Fermentations. This neural network stores the information of previous Fermentations and defines a reference Fermentation. This reference Fermentation is used to perform a comparison with the actual Fermentation for the on-line prediction of future pH values and of the Final Fermentation time. This time, which occurs at a predetermined pH, is predicted with an accuracy of less than 20% at the onset of Fermentation and with a much better accuracy as the Fermentation proceeds. The future pH values are predicted with a mean error of 0.05 pH for a 3 hour prediction horizon. The prediction is obtained with four geometrical methods by sliding the curve of the reference Fermentation along the curve of the actual Fermentation. The procedure for sliding the reference curve depends on the geometrical method used. The distinct advantage of neural networks over other class of models is the plasticity of its structure which allows to easily capture the shape of the Fermentation curve.
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Combined Effects of Culture Conditions and Storage Time on Acidification and Viscosity of Stirred Yogurt
Journal of Dairy Science, 1999Co-Authors: Catherine Béal, Eric Latrille, J. Skokanova, Nathalie Martin, Georges CorrieuAbstract:This work aims to study the effects of culture conditions and storage time on stirred yogurt acidity and texture and to determine relationships in order to better control product viscosity. A four-factor experimental design was carried out to display the simple and combined effects of the ratio of two Streptococcus thermophilus strains, incubation temperature, Final Fermentation pH, and storage time on bacterial concentrations, acidification activity (determined by the time corresponding to the maximum acidification rate), texture (determined by the flowing time coefficient measured with a modified Posthumus funnel), and postacidification. The development of viscosity was influenced by all four factors studied and by some two-factor interactions. The acidification activity was affected by temperature and strain association. Greater viscosity was correlated to lower acidification activity, thus indicating that Fermentation time affects the development of texture. As a consequence, linear relationships between the flowing time coefficient and Final Fermentation time were established. Finally, the most viscous yogurt was obtained by low temperature and Fermentation at a low Final pH with a texturing strain of S. thermophilus, which required the longest Fermentation time.
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INFLUENCE OF Fermentation AND STORAGE CONDITIONS ON THE SENSORY PROPERTIES OF PLAIN LOW FAT STIRRED YOGURTS
Journal of Sensory Studies, 1999Co-Authors: Nathalie Martin, Eric Latrille, Catherine Béal, J. Skokanova, Georges CorrieuAbstract:Influence of strain association, temperature, pH and storage on the sensory properties of low fat stirred yogurt was studied through a factorial design including three associations of thermophilic lactic acid bacteria (one Lactobacillus delbrueckii subsp. bulgaricus, one ropy and one nonropy Streptococcus thermophilus strains), three incubation temperatures (39C, 42C and 45C), two Final Fermentation pH (4.4 and 4.8) and two storage times (7 and 21 days). The 36 formulated yogurts were assessed by Quantitative Descriptive Analysis and by instrumental measurements: apparent viscosity (modified funnel of Posthumus), lactate and pH. Texture perceptions and acid taste, rather than other flavor properties, gave the best discrimination between samples according to strain association, temperature and Final pH. Significant two-factor interaction displayed the concomitant influence of strain association and temperature on the sample texture properties. Instrumental parameters correlated best with thickness and acid taste (pH and lactate) and mouthcoating (apparent viscosity).
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Neural network models for Final process time determination in fermented milk production
Computers & Chemical Engineering, 1994Co-Authors: Eric Latrille, Georges Corrieu, Jules ThibaultAbstract:Abstract For the control of lactic acid batch Fermentations, the prediction of pH over a long time horizon and the determination of the Final Fermentation time are very useful information. Fermented milks with pure and mixed cultures of lactic acid bacteria are modelled with a feedforward neural network. For isothermal Fermentations (42°C), a static model is sufficient to define the one and only reference curve. This reference Fermentation combined with four sliding geometrical methods is used to perform a comparison with the actual Fermentation. The Final Fermentation time, which occurs at a predetermined pH, is predicted with an accuracy of less than 20%. For Fermentations conducted at various temperatures, a dynamical model is obtained as a recurrent neural network. Small order architectures are tested, and directed and semi-directed learning procedures are evaluated. The advantages of the semi-directed mode are shown and the resulting neural net is capable of predicting the Final Fermentation time with a mean relative error of 7.7% in the temperature range of 40°C–48°C.
Eric Latrille - One of the best experts on this subject based on the ideXlab platform.
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pH prediction and Final Fermentation time determination in lactic acid batch Fermentations
Computers & Chemical Engineering, 2002Co-Authors: Eric Latrille, Georges Corrieu, Jules ThibaultAbstract:Abstract For the control of lactic acid batch Fermentations, the prediction of the pH over a long time horizon and the determination of the Final Fermentation time are very useful information. Lactic acid batch Fermentations, with uncontrolled pH, are modelled with a feedforward neural network to generate the model (pH versus time) of a reference Fermentation of Streptococcus thermophilus strain on skim milk. In essence, the feedforward neural network is used as a general nonlinear model to store the information of a series of well-behaved Fermentations. This neural network stores the information of previous Fermentations and defines a reference Fermentation. This reference Fermentation is used to perform a comparison with the actual Fermentation for the on-line prediction of future pH values and of the Final Fermentation time. This time, which occurs at a predetermined pH, is predicted with an accuracy of less than 20% at the onset of Fermentation and with a much better accuracy as the Fermentation proceeds. The future pH values are predicted with a mean error of 0.05 pH for a 3 hour prediction horizon. The prediction is obtained with four geometrical methods by sliding the curve of the reference Fermentation along the curve of the actual Fermentation. The procedure for sliding the reference curve depends on the geometrical method used. The distinct advantage of neural networks over other class of models is the plasticity of its structure which allows to easily capture the shape of the Fermentation curve.
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Combined Effects of Culture Conditions and Storage Time on Acidification and Viscosity of Stirred Yogurt
Journal of Dairy Science, 1999Co-Authors: Catherine Béal, Eric Latrille, J. Skokanova, Nathalie Martin, Georges CorrieuAbstract:This work aims to study the effects of culture conditions and storage time on stirred yogurt acidity and texture and to determine relationships in order to better control product viscosity. A four-factor experimental design was carried out to display the simple and combined effects of the ratio of two Streptococcus thermophilus strains, incubation temperature, Final Fermentation pH, and storage time on bacterial concentrations, acidification activity (determined by the time corresponding to the maximum acidification rate), texture (determined by the flowing time coefficient measured with a modified Posthumus funnel), and postacidification. The development of viscosity was influenced by all four factors studied and by some two-factor interactions. The acidification activity was affected by temperature and strain association. Greater viscosity was correlated to lower acidification activity, thus indicating that Fermentation time affects the development of texture. As a consequence, linear relationships between the flowing time coefficient and Final Fermentation time were established. Finally, the most viscous yogurt was obtained by low temperature and Fermentation at a low Final pH with a texturing strain of S. thermophilus, which required the longest Fermentation time.
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INFLUENCE OF Fermentation AND STORAGE CONDITIONS ON THE SENSORY PROPERTIES OF PLAIN LOW FAT STIRRED YOGURTS
Journal of Sensory Studies, 1999Co-Authors: Nathalie Martin, Eric Latrille, Catherine Béal, J. Skokanova, Georges CorrieuAbstract:Influence of strain association, temperature, pH and storage on the sensory properties of low fat stirred yogurt was studied through a factorial design including three associations of thermophilic lactic acid bacteria (one Lactobacillus delbrueckii subsp. bulgaricus, one ropy and one nonropy Streptococcus thermophilus strains), three incubation temperatures (39C, 42C and 45C), two Final Fermentation pH (4.4 and 4.8) and two storage times (7 and 21 days). The 36 formulated yogurts were assessed by Quantitative Descriptive Analysis and by instrumental measurements: apparent viscosity (modified funnel of Posthumus), lactate and pH. Texture perceptions and acid taste, rather than other flavor properties, gave the best discrimination between samples according to strain association, temperature and Final pH. Significant two-factor interaction displayed the concomitant influence of strain association and temperature on the sample texture properties. Instrumental parameters correlated best with thickness and acid taste (pH and lactate) and mouthcoating (apparent viscosity).
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Neural network models for Final process time determination in fermented milk production
Computers & Chemical Engineering, 1994Co-Authors: Eric Latrille, Georges Corrieu, Jules ThibaultAbstract:Abstract For the control of lactic acid batch Fermentations, the prediction of pH over a long time horizon and the determination of the Final Fermentation time are very useful information. Fermented milks with pure and mixed cultures of lactic acid bacteria are modelled with a feedforward neural network. For isothermal Fermentations (42°C), a static model is sufficient to define the one and only reference curve. This reference Fermentation combined with four sliding geometrical methods is used to perform a comparison with the actual Fermentation. The Final Fermentation time, which occurs at a predetermined pH, is predicted with an accuracy of less than 20%. For Fermentations conducted at various temperatures, a dynamical model is obtained as a recurrent neural network. Small order architectures are tested, and directed and semi-directed learning procedures are evaluated. The advantages of the semi-directed mode are shown and the resulting neural net is capable of predicting the Final Fermentation time with a mean relative error of 7.7% in the temperature range of 40°C–48°C.
Maria C. Portillo - One of the best experts on this subject based on the ideXlab platform.
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Saccharomyces and non-Saccharomyces Competition during Microvinification under Different Sugar and Nitrogen Conditions
Frontiers in Microbiology, 2016Co-Authors: Jessica Lleixà, Albert Mas, Maria Manzano, Maria C. PortilloAbstract:The inoculation of wines with autochthonous yeast allows obtaining complex wines with a peculiar microbial footprint characteristic from a wine region. Mixed inoculation of non-Saccharomyces yeasts and S. cerevisiae is of interest for the wine industry for technological and sensory reasons. However, the interactions between these yeasts are not well understood, especially those regarding the availability of nutrients. The aim of the present study was to analyze the effect of nitrogen and sugar concentration on the evolution of mixed yeast populations on controlled laboratory-scale Fermentations monitored by density, plate culturing, PCR-DGGE and sugar and nitrogen consumption. Furthermore, the effect of the time of inoculation of Saccharomyces cerevisiae respect the initial co-inoculation of three non-Saccharomyces yeasts was evaluated over the evolution of Fermentation. Our results have shown that S. cerevisiae inoculation during the first 48h conferred a stabilizing effect over the Fermentations with non-Saccharomyces strains tested and, generally, reduced yeast diversity at the end of the Fermentation. On the other hand, nitrogen limitation increased the time of Fermentation and also the proportion of non-Saccharomyces yeasts at mid and Final Fermentation. High sugar concentration resulted in different proportions of the inoculated yeast depending on the time of S. cerevisiae inoculation. This work emphasizes the importance of the concentration of nutrients on the evolution of mixed Fermentations and points to the optimal conditions for a stable Fermentation in which the inoculated yeasts survived until the end.
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Analysis of microbial diversity and dynamics during wine Fermentation of Grenache grape variety by high-throughput barcoding sequencing
LWT - Food Science and Technology, 2016Co-Authors: Maria C. Portillo, Albert MasAbstract:Abstract Understanding the diversity and evolution of microorganisms during wine Fermentation is essential for controlling its production. Previous studies have been primarily based on culture-dependent methods but recent incorporation of culture-independent molecular methods is showing a quite different view of microbial composition and diversity during the wine making process. Herein we applied barcoded pyrosequencing technology to monitor bacterial and yeast dynamics during laboratory scale spontaneous wine Fermentation from Grenache variety. Members of the lactic acid bacteria (LAB) and acetic acid bacteria (AAB) were the most abundant, representing the orders Lactobacillales and Rhodospirillales more than 70% of the bacterial population. Other bacterial genera, not previously detected at the end of Fermentation, were present in low proportion and their possible role remains unknown. Within the yeast community, the genera Hanseniaspora and Candida were dominant during the initial and mid Fermentation while the Final Fermentation was mainly dominated by Candida and Saccharomyces . This study contributes to the knowledge of the microbial dynamics across spontaneous wine Fermentation and presents high-throughput sequencing as a useful tool to monitor and evaluate bacterial and yeast diversity and dynamics during wine Fermentation.
Catherine Béal - One of the best experts on this subject based on the ideXlab platform.
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Combined Effects of Culture Conditions and Storage Time on Acidification and Viscosity of Stirred Yogurt
Journal of Dairy Science, 1999Co-Authors: Catherine Béal, Eric Latrille, J. Skokanova, Nathalie Martin, Georges CorrieuAbstract:This work aims to study the effects of culture conditions and storage time on stirred yogurt acidity and texture and to determine relationships in order to better control product viscosity. A four-factor experimental design was carried out to display the simple and combined effects of the ratio of two Streptococcus thermophilus strains, incubation temperature, Final Fermentation pH, and storage time on bacterial concentrations, acidification activity (determined by the time corresponding to the maximum acidification rate), texture (determined by the flowing time coefficient measured with a modified Posthumus funnel), and postacidification. The development of viscosity was influenced by all four factors studied and by some two-factor interactions. The acidification activity was affected by temperature and strain association. Greater viscosity was correlated to lower acidification activity, thus indicating that Fermentation time affects the development of texture. As a consequence, linear relationships between the flowing time coefficient and Final Fermentation time were established. Finally, the most viscous yogurt was obtained by low temperature and Fermentation at a low Final pH with a texturing strain of S. thermophilus, which required the longest Fermentation time.
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INFLUENCE OF Fermentation AND STORAGE CONDITIONS ON THE SENSORY PROPERTIES OF PLAIN LOW FAT STIRRED YOGURTS
Journal of Sensory Studies, 1999Co-Authors: Nathalie Martin, Eric Latrille, Catherine Béal, J. Skokanova, Georges CorrieuAbstract:Influence of strain association, temperature, pH and storage on the sensory properties of low fat stirred yogurt was studied through a factorial design including three associations of thermophilic lactic acid bacteria (one Lactobacillus delbrueckii subsp. bulgaricus, one ropy and one nonropy Streptococcus thermophilus strains), three incubation temperatures (39C, 42C and 45C), two Final Fermentation pH (4.4 and 4.8) and two storage times (7 and 21 days). The 36 formulated yogurts were assessed by Quantitative Descriptive Analysis and by instrumental measurements: apparent viscosity (modified funnel of Posthumus), lactate and pH. Texture perceptions and acid taste, rather than other flavor properties, gave the best discrimination between samples according to strain association, temperature and Final pH. Significant two-factor interaction displayed the concomitant influence of strain association and temperature on the sample texture properties. Instrumental parameters correlated best with thickness and acid taste (pH and lactate) and mouthcoating (apparent viscosity).
Nathalie Martin - One of the best experts on this subject based on the ideXlab platform.
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Combined Effects of Culture Conditions and Storage Time on Acidification and Viscosity of Stirred Yogurt
Journal of Dairy Science, 1999Co-Authors: Catherine Béal, Eric Latrille, J. Skokanova, Nathalie Martin, Georges CorrieuAbstract:This work aims to study the effects of culture conditions and storage time on stirred yogurt acidity and texture and to determine relationships in order to better control product viscosity. A four-factor experimental design was carried out to display the simple and combined effects of the ratio of two Streptococcus thermophilus strains, incubation temperature, Final Fermentation pH, and storage time on bacterial concentrations, acidification activity (determined by the time corresponding to the maximum acidification rate), texture (determined by the flowing time coefficient measured with a modified Posthumus funnel), and postacidification. The development of viscosity was influenced by all four factors studied and by some two-factor interactions. The acidification activity was affected by temperature and strain association. Greater viscosity was correlated to lower acidification activity, thus indicating that Fermentation time affects the development of texture. As a consequence, linear relationships between the flowing time coefficient and Final Fermentation time were established. Finally, the most viscous yogurt was obtained by low temperature and Fermentation at a low Final pH with a texturing strain of S. thermophilus, which required the longest Fermentation time.
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INFLUENCE OF Fermentation AND STORAGE CONDITIONS ON THE SENSORY PROPERTIES OF PLAIN LOW FAT STIRRED YOGURTS
Journal of Sensory Studies, 1999Co-Authors: Nathalie Martin, Eric Latrille, Catherine Béal, J. Skokanova, Georges CorrieuAbstract:Influence of strain association, temperature, pH and storage on the sensory properties of low fat stirred yogurt was studied through a factorial design including three associations of thermophilic lactic acid bacteria (one Lactobacillus delbrueckii subsp. bulgaricus, one ropy and one nonropy Streptococcus thermophilus strains), three incubation temperatures (39C, 42C and 45C), two Final Fermentation pH (4.4 and 4.8) and two storage times (7 and 21 days). The 36 formulated yogurts were assessed by Quantitative Descriptive Analysis and by instrumental measurements: apparent viscosity (modified funnel of Posthumus), lactate and pH. Texture perceptions and acid taste, rather than other flavor properties, gave the best discrimination between samples according to strain association, temperature and Final pH. Significant two-factor interaction displayed the concomitant influence of strain association and temperature on the sample texture properties. Instrumental parameters correlated best with thickness and acid taste (pH and lactate) and mouthcoating (apparent viscosity).