Optimization of rice wine fermentation process based on the simultaneous saccharification and fermentation kinetic model

Chinese rice wine making is a typical simultaneous saccharification and fermentation （SSF） process. During the fermentation process, temperature is one of the key parameters which decide the quality of Chinese rice wine. To optimize the SSF process for Chinese rice wine brewing, the effects of temperature on the kinetic parameters of yeast growth and ethanol production at various temperatures were determined in batch cultures using a mathematical model. The kinetic parameters as a function of temperature were evaluated using the software Origin8.0. Combing these functions with the mathematical model, an appropriate form of the model equations for the SSF considering the effects of temperature were developed. The kinetic parameters were found to fit the experimental data satisfactorily with the developed temperature-dependent model. The temperature profile for maximizing the ethanol production for rice wine fermentation was determined by genetic algorithm. The optimum temperature profile began at a low temperature of 26℃ up to 30 h. The operating temperature increased rapidly to 31.9 ℃, and then decreased slowly to 18℃ at 65 h. Thereafter, the temperature was maintained at 18 ℃ until the end of fermentation. A maximum ethanol production of 89.3 g.L 1 was attained. Conceivably, our model would facilitate the improvement of Chinese rice wine production at the industrial scale.

Learning control of fermentation process with an improved DHP algorithm

Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.

Stabilization of jiuyao quality for huangjiu brewing by fortifying functional strains based on core microbial community analysis

Jiuyao as a generally small saccharifying and spontaneously fermenting starter is indispensable for huangjiu brewing.However,jiuyao currently in use is facing a major challenge of standardized manufacturing because of its open operating environment and rather primitive operations.This study provided a stead manufacturing procedure for jiuyao by controlling the processing parameters.Saccharomycopsis fibuligera and Rhizopus microsporus were revealed as the core functional species related to starch-degrading enzyme activities with single-molecule real-time(SMRT)sequencing.Two strains with high starch-degrading abilities were successfully isolated and identified as Saccharomycopsis fibuligera CY2111 and Rhizopus microsporus SM4.Meanwhile,the environmental fermentation parameters of jiuyao were optimized to enhance enzyme activities.The glucoamylase andα-amylase activities of fortified jiuyao with strain CY2111 and SM4 were 3.07 and 3.15 times that of traditional jiuyao,respectively.Moreover,the alcohol content increased by approximately 7.5%when fortified jiuyao was used for huangjiu brewing.The flavor profiles determined by gas chromatography-mass spectrometry indicated there was no significant difference in the key aromas between the huangjiu fermented with fortified jiuyao and that of traditional jiuyao.Further,fortified jiuyao produced more pleasant esters in huangjiu such as ethyl isovalerate,isoamyl acetate,and ethyl caprylate.Combined with the sensory evaluation,huangjiu fermented with fortified jiuyao presented stronger fruity aroma.These results demonstrated that careful fermentation settings combined with biofortification technology were feasible to improve jiuyao quality,thus promoting huangjiu flavor.Taken together,it provided scientific guidance to improve traditional handcrafting and scale up the production of jiuyao under controllable fermentation.