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Copyright of Storage & Process is the property of Tianjin Academy of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Condiment is the property of China Condiment and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Dalian Polytechnic University is the property of Journal of Dalian Polytechnic University Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to increase yield,take the Bacillus subtilis Asr as the expreession strain, the fermentation process of Bacillus subtilis Asr was optimized by orthogonal test and response surface method. The results show that three main factors affecting bacterial yield are leaching yeast powder, MgSO4 and CaCl2. The best fermentation medium formulation is as following: sucrose 20 g/L, peptone 10 g/L, leaching yeast powder 8.65 g/L, K2HPO4 3.0 g/L, MgSO4 0.27 g/L and CaCl2 0.53 g/L. The optimal culture conditions are as following: 37 ℃, initial pH 7.0, inoculum of 10% and stirring speed of 250 r/min. After the optimization, the highest yield of Bacillus subtilis Asr reaches 7.30×108 cfu/mL, which is 3.95 times higher than that before optimization. The study provides a technical reference for the subsequent bacterial scale-up culture in fermentor and the optimization of fermentation medium from other Bacillus subtilis.

In order to investigate the fermentation process of Artemisia polysaccharides, this paper showcases an investigation into the effects of fermentation time, fermentation temperature, strain inoculum, Artemisia annua addition, and shaker speed on the polysaccharides production of Artemisia annua. The yield of Artemisia polysaccharides content was determined based on the optimization of single-factor test, and then a response surface test was conducted with temperature, inoculum, and time as response variables and the yield of Artemisia polysaccharides as response values. The fermentation process was then optimized and the antioxidant activity of Artemisia polysaccharides was monitored using DPPH, ABTS+, OH, and total reducing power. The optimum fermentation process was determined by the test to be 5% inoculum of Aspergillus niger, temperature 36°C, time 2 d, shaker speed 180 r/min, and 4% addition of Artemisia annua, and the extraction of Artemisia polysaccharides was up to 17.04% by this condition of fermentation. The polysaccharides from Artemisia annua fermented by Aspergillus Niger had scavenging effects on DPPH, ABTS, and OH free radicals.

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Yogurt is currently the most popular fermented milk product that is produced worldwide due to its multiple benefits for consumer health. Temperature on various technological phases is the determinant factor that influences the structure and texture of yogurt. Another important factor is the quality and dose of lactic bacteria used for starter cultures. By selecting lactic bacteria suitable for the substrate that ferments, at the optimal temperature for their metabolism, highly superior quality products can be obtained. The aim of this study is to highlight the combined effect of fermentation temperature and inoculum dose on finished yogurt under certain predetermined milk composition - raw material and starter culture quality. Yogurt samples were obtained at different fermentation temperatures (37 °C, 41 °C and 45 °C) using different amounts of inoculum (0.1 %, 0.2 % and 0.3 %). After 24 hours of storage at 4 °C the yogurt samples were analyzed for rheological and physico-chemical properties.

Abstract Pullulanase is an important starch-debranching enzyme mostly used in starch processing-related food industries. However, the levels of pullulanase produced from recombinant Bacillus subtilis, a Generally Recognized as Safe (GRAS) host, are generally limited. To enhance the activity of pullulanase, batch fermentation and fed-batch fermentation were systematically investigated. The overall purpose is to improve the fermentation yield by optimizing the feeding strategy in the fermentation process, thereby increasing the enzyme activity of pullulanase. Therefore, in this study, the feeding methods, the feeding ingredients, the feeding concentration, and pH values were studied in detail. The optimized fermentation conditions for pullulanase production from recombinant B. subtilis were determined as following: inoculum volume 7%, pH 6.5, the dissolved oxygen level 30%, and constant-rate feeding of 100 mL glucose solution (400 g L−1) in late logarithmic growth. The OD600 of recombinant B. subtilis and enzyme activity were 84.54 and 102.75 U mL−1, which were respectively 141% and 144% higher than that before optimization. These findings provided a prerequisite for further amplification of the fermentation system to obtain higher enzyme activity.

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Hebei University of Science & Technology is the property of Hebei University of Science & Technology, Journal of Hebei University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pullulanase is an important starch-debranching enzyme mostly used in starch processing-related food industries. However, the levels of pullulanase produced from recombinant Bacillus subtilis, a Generally Recognized as Safe (GRAS) host, are generally limited. To enhance the activity of pullulanase, batch fermentation and fed-batch fermentation were systematically investigated. The overall purpose is to improve the fermentation yield by optimizing the feeding strategy in the fermentation process, thereby increasing the enzyme activity of pullulanase. Therefore, in this study, the feeding methods, the feeding ingredients, the feeding concentration, and pH values were studied in detail. The optimized fermentation conditions for pullulanase production from recombinant B. subtilis were determined as following: inoculum volume 7%, pH 6.5, the dissolved oxygen level 30%, and constant-rate feeding of 100 mL glucose solution (400 g L−1) in late logarithmic growth. The OD600 of recombinant B. subtilis and enzyme activity were 84.54 and 102.75 U mL−1, which were respectively 141% and 144% higher than that before optimization. These findings provided a prerequisite for further amplification of the fermentation system to obtain higher enzyme activity. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The objective of this study was to increase the intracellular polysaccharide yield of Ganoderma lucidum. The accordingly optimized fermentation medium by central composite design method contains glucose 40 g L−1, yeast powder 12 g L−1, potassium dihydrogen phosphate 3 g L−1, initial pH 5.5, and inoculum size 10 mL 100 mL−1. Under this condition, the predicted value of intracellular polysaccharide yield was 2.03 g L−1. Shake flask experiments confirmed that the average intracellular polysaccharide yield was 1.98 g L−1 similar to the predicted value. The yields of intracellular polysaccharides in the 5-L and 50-L fermentors were 2.59 g L−1 and 2.65 g L−1, respectively. The molecular weight distribution of intracellular and extracellular polysaccharides obtained was determined by HPSEC-MALLS-RI. The results showed that the weight-average molecular weight of component 1 in the intracellular crude polysaccharide was 4.695 × 106 Da and the mass fraction was 58%. The weight-average molecular weight of component 2 in the extracellular polysaccharide was 5.554 × 104 Da. The mass fraction was 94.9%. The liquid submerged fermentation process of G. lucidum mycelium obtained from this study has effectively increased the yield of intracellular polysaccharides. Its intracellular and extracellular polysaccharides have good immunological activity. Conceivably, the optimized process can be applied for the large-scale production. [ABSTRACT FROM AUTHOR]

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For effective monitoring and control of the fermentation process, an accurate real-time measurement of important variables is necessary. These variables are very hard to measure in real-time due to constraints such as the time-varying, nonlinearity, strong coupling, and complex mechanism of the fermentation process. Constructing soft sensors with outstanding performance and robustness has become a core issue in industrial procedures. In this paper, a comprehensive review of existing data pre-processing approaches, variable selection methods, data-driven (black-box) soft-sensing modeling methods and optimization techniques was carried out. The data-driven methods used for the soft-sensing modeling such as support vector machine, multiple least square support vector machine, neural network, deep learning, fuzzy logic, probabilistic latent variable models are reviewed in detail. The optimization techniques used for the estimation of model parameters such as particle swarm optimization algorithm, ant colony optimization, artificial bee colony, cuckoo search algorithm, and genetic algorithm, are also discussed. A comprehensive analysis of various soft-sensing models is presented in tabular form which highlights the important methods used in the field of fermentation. More than 70 research publications on soft-sensing modeling methods for the estimation of variables have been examined and listed for quick reference. This review paper may be regarded as a useful source as a reference point for researchers to explore the opportunities for further enhancement in the field of soft-sensing modeling.

Hyaluronic acid (HA) is a high molecular weight glycosaminoglycan consisting of alternating D-glucuronic acid and VV-acetylglucosamine and plays extremely important roles in many biological processes. In this study, we optimized fermentation process for the production of HA by Streptococcus zooepidemicus ATCC35246, including fermentation broth composition and various fermentation parameters. The experimental results showed that the optimal fermentation broth composition was : glucose 45 g/L, yeast extract 10 gL, tryptone 12 g/L, KH2P04 2 g/L, K2HPO4 · 3H2 0 2 gL, MgSO„ · 7H2 0 2 g/L, ad (NH4)2SO„ 0.4 g/L. The optimal parameters involved in fermentation was : liquid volume 20%, pH 6 .0, rotation speed 180 r/min, fermentation temperature 35 t, fermentation duration 18 h, CTAB concentration 25 mg/L. Under the optimized conditions, the yield of HA was 0. 305 g /L, which was dramatically improved by 43. 87% compared to that of 0.212 g/L before optimization. [ABSTRACT FROM AUTHOR]

Abstract: The determination of the optimal neural network topology is an important aspect when using neural models. Due to the lack of consistent rules, this is a difficult problem, which is solved in this paper using an evolutionary algorithm namely Differential Evolution. An improved, simple, and flexible self-adaptive variant of Differential Evolution algorithm is proposed and tested. The algorithm included two initialization strategies (normal distribution and normal distribution combined with the opposition based principle) and a modified mutation principle. Because the methodology contains new elements, a specific name has been assigned, SADE-NN-1. In order to determine the most influential inputs of the models, a sensitivity analysis was applied. The case study considered in this work refer to the oxygen mass transfer coefficient in stirred bioreactors in the presence of n-dodecane as oxygen vector. The oxygen transfer in the fermentation broths has a significant influence on the growth of cultivated microorganism, the accurate modeling of this process being an important problem that has to be solved in order to optimize the aerobic fermentation process. The neural networks predicted the mass transfer coefficients with high accuracy, which indicates that the proposed methodology had a good performance. The same methodology, with a few modifications, and with the best neural network models, was used for determining the optimal conditions for which the mass transfer coefficient is maximized. A short review of the differential evolution methodology is realized in the first part of this article, presenting the main characteristics and variants, with advantages and disadvantages, and fitting in the modifications proposed within the existing directions of research. [Copyright &y& Elsevier]

For effective monitoring and control of the fermentation process, an accurate real-time measurement of important variables is necessary. These variables are very hard to measure in real-time due to constraints such as the time-varying, nonlinearity, strong coupling, and complex mechanism of the fermentation process. Constructing soft sensors with outstanding performance and robustness has become a core issue in industrial procedures. In this paper, a comprehensive review of existing data pre-processing approaches, variable selection methods, data-driven (black-box) soft-sensing modeling methods and optimization techniques was carried out. The data-driven methods used for the soft-sensing modeling such as support vector machine, multiple least square support vector machine, neural network, deep learning, fuzzy logic, probabilistic latent variable models are reviewed in detail. The optimization techniques used for the estimation of model parameters such as particle swarm optimization algorithm, ant colony optimization, artificial bee colony, cuckoo search algorithm, and genetic algorithm, are also discussed. A comprehensive analysis of various soft-sensing models is presented in tabular form which highlights the important methods used in the field of fermentation. More than 70 research publications on soft-sensing modeling methods for the estimation of variables have been examined and listed for quick reference. This review paper may be regarded as a useful source as a reference point for researchers to explore the opportunities for further enhancement in the field of soft-sensing modeling. [ABSTRACT FROM AUTHOR]