Bed moisture estimation by monitoring of air stream temperature rise in packed-bed solid-state fermentation

Humidity Control Strategies for Solid-State Fermentation: Capillary Water Supply by Water-Retention Materials and Negative-Pressure Auto-controlled Irrigation

Solid-state fermentation (SSF) has regained interest owing to its advantages in solid waste treatment and fermentation industries. However, heterogeneous heat and mass transfer are often caused by the absence of free water and noticeable water loss from microbial utilization and moisture evaporation in SSF. It is necessary to explore more effective ways to solve issues of water loss and water supplement in SSF based on online capillary water monitoring, because capillary water is the dominant form of water that is present and lost in substrate. Two novel capillary-water supply strategies were proposed, established and evaluated using three selected reference strains, including water-retention materials and negative-pressure auto-controlled irrigation (NPACI). This study employed superabsorbent polymer, a kind of water-retention material to enhance enzyme productivity with the most significant increase of 2.47 times. Moreover, the combination of NPACI and 0.1% superabsorbent polymers increased productivity by 2.80-fold, together with lowered gradients of temperature, moisture and products. Furthermore, a modified liquid-supply SSF was constructed through successful capillary water control by proposed humidity control strategies. This modified SSF system could address the shortcomings of inhomogeneous culture of traditional SSF.

Construction of industrial Saccharomyces cerevisiae strains for the efficient consolidated bioprocessing of raw starch

BACKGROUND

Consolidated bioprocessing (CBP) combines enzyme production, saccharification and fermentation into a one-step process. This strategy represents a promising alternative for economic ethanol production from starchy biomass with the use of amylolytic industrial yeast strains.

RESULTS

Recombinant Saccharomyces cerevisiae Y294 laboratory strains simultaneously expressing an α-amylase and glucoamylase gene were screened to identify the best enzyme combination for raw starch hydrolysis. The codon optimised Talaromyces emersonii glucoamylase encoding gene (temG_Opt) and the native T. emersonii α-amylase encoding gene (temA) were selected for expression in two industrial S. cerevisiae yeast strains, namely Ethanol Red™ (hereafter referred to as the ER) and M2n. Two δ-integration gene cassettes were constructed to allow for the simultaneous multiple integrations of the temG_Opt and temA genes into the yeasts' genomes. During the fermentation of 200 g l^-1 raw corn starch, the amylolytic industrial strains were able to ferment raw corn starch to ethanol in a single step with high ethanol yields. After 192 h at 30 °C, the S. cerevisiae ER T12 and M2n T1 strains (containing integrated temA and temG_Opt gene cassettes) produced 89.35 and 98.13 g l^-1 ethanol, respectively, corresponding to estimated carbon conversions of 87 and 94%, respectively. The addition of a commercial granular starch enzyme cocktail in combination with the amylolytic yeast allowed for a 90% reduction in exogenous enzyme dosage, compared to the conventional simultaneous saccharification and fermentation (SSF) control experiment with the parental industrial host strains.

CONCLUSIONS

A novel amylolytic enzyme combination has been produced by two industrial S. cerevisiae strains. These recombinant strains represent potential drop-in CBP yeast substitutes for the existing conventional and raw starch fermentation processes.

Bioreactors in solid state fermentation technology: Design, applications and engineering aspects

In recent years, substantial credibility in employing Solid-State Fermentation (SSF) technique has been witnessed owing to its numerous advantages over submerged fermentation (SmF). In spite of enormous advantages, true potential of SSF technology has not been fully realized at industrial scale. The lack of rational and scalable bioreactor designs backed by mathematical models and automated control system that could successfully address heterogeneity with respect to heat and mass, and also operate aseptically, remains the prime reason for it. As a result, there still exists vast scope in SSF bioreactor research and development to facilitate broad spectrum of biotechnological applications. The present article reviews state-of-the-art in SSF technology with focus on bioreactors that have been employed for bioprocess applications, in particular, enzyme production. Based on the mode of operation, bioreactors are divided into four categories with emphasis on design features, effect of operating conditions on productivity, applications and limitations. Selected modeling studies developed over the years, have been revised and presented in problem specific manner in order to address the limitations. Some interesting designs including few recent ones that have been proposed and/or employed at pilot and industrial levels are discussed in more detail.

Using millet as substrate for efficient production of monacolin K by solid-state fermentation of Monascus ruber

In this study, various grains such as rice, millet, corn, barley and wheat were used as raw materials for monacolin K production by solid-state fermentation of Monascus ruber. Among these substrates, millet was found to be the best one for monacolin K production, by which the yield reached 7.12 mg/g. For enhanced monacolin K production, the effects of fermentation time, charge amount, initial moisture content and inoculum volume were systematically investigated in the solid-state fermentation of M. ruber. Moreover, complementary carbon source and nitrogen source were added for further improving the production of monacolin K. Results showed that the maximum production of monacolin K (19.81 mg/g) could be obtained at the optimal conditions. Compared with the traditional red mold rice, using millet as substrate is promising for high production of monacolin K in the solid-state fermentation of M. ruber.

Operating conditions of a 200l staged vertical reactor for bioconversion of wheat straw by Phanerochaete chrysosporium

Bioconversion of wheat straw using Phanerochaete chrysosporium was carried out in a 200l staged vertical reactor. The bioconversion process was characterized by measuring the percentage degradation of lignin and cellulose, and increment in crude protein content. The effect of airflow rate, inoculum amount and wheat straw loading on bioconversion was investigated using a statistical experimental design. An analysis of variance was performed to determine response surfaces. The quality of bioconversion indicated by an optimization index called the desirability coefficient had the highest value of 0.75 for the fifth day of cultivation. This corresponded to an operating condition of 1.5kg wheat straw per stage using an inoculum amount of 0.38g (100g dry wheat straw)(-1) and an airflow rate of 15lmin(-1). The lignin and cellulose degradation achieved at this operating condition was 27% and 29%, respectively. A ratio of 3 for the weight of wheat straw to inoculum amount gave the highest crude protein of 5.9% on dry weight basis. Among the variables investigated, the airflow rate exhibited a significant effect on the quality of bioconversion. Our results indicate that the quality of bioconversion may be controlled by implementing a predetermined airflow rate schedule.

Predictive controller evaluation including non-stationary high frequency noise and outliers for batch solid substrate fermentation bioreactors

Optimum operation and automatic control of large-scale solid substrate fermentation (SSF) bioreactors is difficult. Though advanced control algorithms can handle most challenges encountered properly, for real-time SSF processes such controllers are expensive and time consuming to design and tune. With these considerations, advanced control algorithm tests using realistic simulations appear more appropriate. We used a phenomenological process model of an SSF pilot bioreactor, coupled with a realistic noise model, to test linear model predictive controllers. We focused on the effect noise has on the performance of the control algorithms, and how to enhance performance using a combination of low-pass (Butterworth) and outlier shaving (Hampel) filters. In simulations undertaken directly with the phenomenological model it was relatively straightforward to achieve good control performance. Nevertheless, control degraded sharply when the output of the phenomenological model was contaminated with noise using our realistic noise model, even with proper signal filtering.