Current Biochemical Engineering (Discontinued) - Volume 4, Issue 3, 2017

Background: The presence of lignin in rice straw, an abundant biomass acts as a barrier preventing the enzyme accessibility to cellulose and hemicellulose for hydrolysis and fermentation to ethanol. This makes biomass pretreatment an integral step which can broadly be classified into physical, chemical, and biological pretreatments. While physical and chemical pretreatments involve high cost inputs and produce fermentation inhibitors thus polluting environment, biological pretreatment is accomplished at low temperature and pressure without using expensive equipments and chemical agents. Biological pretreatment using ligninolytic white rot fungi involves a synergistic action of laccase (Lac), lignin peroxidase (LiP), manganese peroxidase (MnP) and versatile peroxidase (VP) and adjunct enzymes such as H2O2-producing oxidase. Method: The present review has been compiled by searching current physico-chemical and biological strategies for pretreatment of lignocellulosic biomass particularly rice straw across the scientific world. Results: The review summarizes the current status of physical and chemical processes such as autohydrolysis, irradiations, acids, alkali and oxidizing agents and highlights the biological pretreatment alone or in combination with other pretreatment processes. The specific topics discussed under the biological pretreatment process are: lignin degrading microorganisms (particularly fungi), major classes of rot-fungi and their modes of action, ligninolytic enzyme families, their detailed structure at the molecular levels, biochemical properties and their modes of function. Conclusion: The findings of the review highlight the advantages of biological pretreatment using white-rot fungi for the pretreatment of rice straw as an environment friendly and inexpensive approach over the currently practised physical and chemical processes of pretreatment.

Background: The oxygen transfer rate and volumetric oxygen transfer coefficient (KLa) are the most important parameters used for the design, operation, and scale-up of bioreactors. In aerobic fermentation processes, continuous supply of oxygen is required due to its low solubility in the growth medium. The gas–liquid mass transfer in a bioprocess is strongly influenced by the hydrodynamic conditions in the bioreactor which, in turn, are due to the type of microorganism be used, media composition and biocatalyst properties. Objectives: The main focus of the present review article is on the use of the oxygen vectors as a better and economical alternate for enhancing oxygen transfer rate during the production of industrially important biomolecules in aerobic bioreactors. The efficiency of oxygen transfer rate can be enhanced by adding oxygen-vectors in production broths without increasing the energy consumption for aeration. Results: The use of a variety of oxygen vectors with diverse microbial systems has been shown to result in the improvement of bioprocess performance. These organic liquids when used at an optimum concentration enhance the production of bio-molecules of commercial interest. These oxygen vectors only allow the increase in the OTR without interfering with the microbial metabolism due to their relatively inert and nontoxic nature. Conclusion: Much attention is required in the design and development of improved and efficient large-scale aerobic fermentation processes with the use of these oxygen carriers. The major factors which favour the economics and cost-effectiveness, include optimization of oxygen vector concentration, their compatibility with particular microorganism and suitable time for their addition. Moreover, the antifoaming action of oxygen vectors is the additional feature that makes them more suitable for use in aerobic fermentations.

Background: The dairy sector is responsible for 4% of global anthropogenic greenhouse gas (GHG) emissions. These emissions must be reduced. Anaerobic digestion [AD] converts volatile solids [VS] in cattle manure to methane, carbon dioxide and reactor effluent. AD has been proposed as a technology to reduce the emissions of methane from manure storage at the farms. There is a need to predict the methane yield for anaerobic digestion [AD] of dairy cattle manure in order to optimise the size of the AD reactors. Method: The model is in analogy of the decay of soil organic matter with a modified time dependent decay constant. The model has been tested with experiments on dairy cattle manure in batch and continuously stirred reactors. The model enables not only the prediction of the methane yield but also the calculation of the effect of AD on the effective organic mass [EOM] of the soil. The EOM is important for its fertility. A costs model has been developed for the reactor size. Results: The test results have been divided in four groups (Two for batch reactors, lab-scale reactors and farm scale reactors. The destruction of VS is in the reactors is ten times faster, than that in the soil. The model has a limitation as for each VS content in equation a decay constant can be fitted with the same root mean square [RMS]. A reduction of around 25 % in EOM has been calculated for a research farm using AD of the manure. Conclusion: The model presented can predict the methane yield of cattle manure with an accuracy of 10 - 15 %. It needs a minimum of input (manure production and retention time).The model enables the calculation of the effect of AD on the effective organic mass [EOM] in the soil. The methane production costs are nearly the same for a range of reactor sizes ( between 500 m3 and 1 500 m3) for a manure input of 7 500 m3/a.

Background: Chicken manure is a difficult substrate for anaerobic digestion, due to its high content of nitrogen and sulphur. Nitrogen (Ammonia) and Sulphur (H2S) inhibit the digestion process. In this paper an analysis is made of the methods to mitigate the effect of nitrogen and sulphur on the anaerobic digestion of chicken manure. Methods: A literature study was made on additives, that reduce the negative effects of nitrogen and sulphur. The data of a biogas plant in Thüringen (Germany) using chicken manure together with swine manure, cattle manure and maize silage are analysed. This installation operates with a total solids concentration [TS] of the substrate of 190 kg/m3 and a total nitrogen concentration [TKN] of the effluent of 9.3 kg/m3. number of additives, which reduce these negative effects, are discussed. Results: The plant in Thüringen could use more chicken manure and could have higher TS loading, when the pumps between primary and secondary reactors are replaced. Capacity of the plant can be increased by 15 %. The data of the plant in Thuringen (Germany) are compared with design data of a plant in the Dnepropetrovsk oblast (Ukraine). There is an option for this latter plant to recycle part of the effluent, when a nitrogen mitigating additive is used. Capacity could be increased by 25 %, when the total solids loading of the Thuringen plant is adopted. Conclusion: Chicken manure is economically digested in together with swine manure, cattle manure and maize silage. The contribution of the chicken manure to the biogas yield can be increased by 15 %, when pumps be- tween primary and secondary reactors are exchanged. Power of the plant in the Dnepropetrovsk oblast can be increased by 25 % or more of the liquid fraction of the effluent can be recycled, when iron containing compounds are used.

Background: Only one manganese peroxidase from Musa paradisiaca leaf has been purified and characterized but from other plant sources are still to be reported with efficient manganese peroxidase activity. Objective: To assay enzyme activity and to study the enzymatic properties like Km, pH optima and temperature optima of the manganese peroxidase present in Luffa acutangula fruit juice. To study the nature of inhibition by different inhibitors on manganese peroxidase. Method: Fresh L. acutangula fruit was cut, crushed, squeezed and centrifuged to get the clear juice extract. Manganese peroxidase activity was assayed and the steady state enzyme kinetics of the MnP catalysed reaction was studied spectrophotometrically at λ=270nm. The pH optima and the temperature optima of the enzyme was determined by measuring the steady state velocity of enzyme catalysed reaction in reaction solutions of varying pH and at varying temperature. The steady state velocity of enzyme catalyzed reaction was monitored at different concentrations of inhibitors. Results: The Michaelis Menten constants for the enzyme for Mn(II) and H2O2 were 22μM and 20μM. The pH and temperature optima of the enzyme were 4 and 22 °C. Sodium azide showed uncompetitive type whereas ethylenediamine and ethylenediamine tetra acetic acid showed competitive type of inhibition. Conclusion: It is the second manganese peroxidase reported from a plant source. The enzymatic properties are similar to manganese peroxidase from Musa paradisiaca stem juice and other reported fungal manganese peroxidases.

Background: Pleurotus ostreatus, an Oyster mushroom, is the most prevalent edible mushrooms. It served as a nutritional diet due to the presence of essential minerals and vitamins. It has offered pleiotropic clinical applications. The production of mushroom is influenced significantly by the process parameters. Hence, this paper is aimed to find the optimal conditions to maximize the production of mushroom biomass using both response surface methodology and Artificial neural networks (ANNs). Method: The central composite experimental design was chosen to find the optimum values of the process parameters, viz., humidity, inoculum size, quantity of rice straw, and cooking time, to maximize the production of oyster mushroom in a batch solid-state fermentation process. ANNs were trained and validated using the experimental design and its response. Results: The optimum values of humidity, inoculum size, rice straw, and cooking time were found to be 78.4%, 8.64 g, 64.56 g, and 58.15 min, respectively. The production of Pleurotus ostreatus under the optimized condition was 98.56 mg, which are two folds higher compared to the unoptimized production conditions. Conclusion: The output of ANN model was compared with the finding of the response surface methodology that showed a good agreement in the finding of the maximum production of mushroom biomass.