Fig. 3. shows the results of SSF on wet oxidized rape straw with 80 g/L DM content using initial yeast concentrations from 2.0 to 8.2 g/L.

As expected, the rate of fermentation dependants on the concentration of yeast, as there is plenty of sugar monomers present in the medium, which are produced in the pre-hydrolysis step of the SSF. At some point the excess sugar from the prehydrolysis is depleted and the rate of fermentation becomes dependent on the amount of sugar released by hydrolysis

(rate of hydrolysis). Since the enzyme loading was the same in all the samples the fermentations produce ethanol at roughly the same rate once the excess sugar has been used.

In experiments with high dry matter content such as 170 g/L the difference between the yeast dependant and the enzyme dependant phase is more pronounced than with low DM content (Fig. 4). The viscosity of the sample changes drastically during SSF since hydrolysis changes insoluble cellulose to soluble glucose. This means that the rate of both the yeasts and the enzymes production increases over time, as the production rate of both the enzymes and the yeast is related to the viscosity of the medium. An explanation can be that a high concentration of dry matter gives higher inhibitor concentrations and a larger yeast concentration can make faster detoxification.

As shown in table 2, the high DM content result in low ECE% of 67% compared to 75% when using low DM content. This is an essential problem in ethanol production since industrial distillation works best with more than 50 g/L ethanol, which could potentially be achieved with 75% ECE and 220 g/L of rape straw. However, in reality this is a challenge since increased DM contents result in reduced ECE% due to increasing viscosity and difficulties in mixing and higher concentrations of inhibitors. No direct correspondence between the final ECE% and the initial amount of yeast is found in this study. This indicates that the drop in ECE% at high DM can be due to decreasing enzyme performance in high DM pre-hyrolysates of rape straw.

The rate of fermentation is calculated for the time period with the highest fermentation rate and the results are shown in Fig. 5. For 170 g/L DM content that is between 10 and 52 hours, and for 80 g/L DM content it is between 2 and 4 hours. This time period covers the phase

where the excess sugars from the hydrolysis is fermented and the positive feedback effect seen in high DM contents is also expressed. As shown in Fig. 5 generally the maximum rate of fermentation increases as a function of the yeast concentration. The slope coefficient of 80 g/L DM was found by linear regression to be 0.48 h-1 while it was found to be 0.20 h-1 at 170 g/L DM. The amount of yeast therefore contributes strongly to the positive feedback effect as explained in Fig. 4 and in this time period the dependency is also due to the fact that high yeast content can simply ferment the excess sugar from the hydrolysis faster than low contents of yeast.

In order to acquire competitive catalytic performance with noble metals, a series of optimization procedures need to be carried out over cobalt based catalysts. The significance of support was first explored by Haga et al. [59] indicating that Co/ Al2O3 shows more promising activity than SiO2, C, ZrO2, and MgO. A relatively systematic investigation of the effect of supports was performed by Llorca and his coworkers [65]. Among the supports of CeO2, Sm2O3, MgO, Al2O3, SiO2, TiO2, ZnO, La2O3, V2O5 reported in this study, ZnO was ranked the best.

Recently mixed metal oxides have been employed as the support to improve the behavior of single metal oxides by doping one or more additional components into the original support lattice. For instance, in the implementation of Ce1-xZrxO2, as the washcoat material in three­way catalysts, support combines the oxygen mobility of CeO2 and thermal tolerance of ZrO2 [66-69]. The introduction of Ca creates oxygen vacancies, which is beneficial for the enhancement of oxygen mobility [70, 71]. Besides, the perovskite-type oxides such as LaAlO3, SrTiO3, and BaTiO3 have been used as the support for BESR catalysts due to their highly labile lattice oxygen [72, 73].

The cobalt precursor was proved by several authors [60, 74, 75] to have prominent effect on catalytic performance, which was proposed to be related to the cobalt dispersion. From the comparison between several precursor candidates, the one complexed with organic functional groups gave higher dispersion, which could be attributed to its isolation effect on the nearby Co atoms from agglomeration. It has been accepted that the active site during bio-ethanol steam reforming is related to the metal cobalt [76], that is, the higher the percentage of the cobalt that is available, the better the catalytic performance for BESR. Therefore, the improvement of cobalt dispersion will benefit the enhancement of corresponding catalytic activity.

It is expectable that cobalt loading has direct impact on the cobalt dispersion in the final catalyst. From the studies performed over Ni-based catalysts [53, 77], there exists an optimal loading, which can obtain the highest metal dispersion, through increasing the metal loading while avoiding metal sintering occurring at high loading due to the agglomeration of nearby metal atoms during thermal treatment. To the best of our knowledge, there is no systematic research of the effect of cobalt loading on its catalytic performance during BESR. Therefore, executing such a study can provide us better control of the catalyst optimization.

The impregnation medium is expected to have influence on the diffusion of cobalt precursor during impregnation and redistribution of cobalt atoms during the subsequent thermal treatment, which is shown by the experimental observations over Co/SiO2 [78]. The smaller Co3O4 crystallite size obtained for samples using ethanol rather than water as impregnation solvent is attributed to the formation of ethoxyl groups on silica and/or Co3O4 surface during impregnation which hindered the sintering of Co3O4 by physically interfering during the thermal decomposition of nitrates. As a result, a higher percentage dispersion of cobalt metal was achieved from reduction of smaller crystallites of Co3O4. In addition, further sintering of cobalt metal during reduction might be hindered by ethoxyl groups as well. Since the cobalt dispersion is closely correlated to the activity during BESR as described above, this effect needs to be further investigated.

It was reported by Enache et al. [79] and Ruckenstein [80] in their studies of cobalt-based catalysts for Fischer-Tropsch reaction that the parameters used in the sample heat treatment before being charged for reaction play a significant role on the cobalt dispersion and in turn catalytic activity. Thus the synthesis parameters during calcination and reduction need to be explored to optimize the catalytic performance.

The promotion effect of alkali metal addition has been observed separately by Llorca et al., and Galetti et al. [63, 64, 81]. The hydrogen yield enhancement and carbon deposition inhibition showed the improvement of catalytic performance even when a small amount of Na and K (~0.7 wt. %) was introduced. As an inexpensive additive, this promising modification should be further explored.

Similar to Ni catalysts, promotion effect has also been evidenced over the samples with the formation of metallic alloy. According to the results published so far, the second active metal in addition to Co can be generally categorized as noble metals (e. g., Rh [82] and Ru [83-85]) and non-noble metals (e. g., Ni, Cu [63, 86], Fe, and Mn [87]). The integration of each metal specialized in different functions might be responsible for the synergetic interaction on the improvement of catalytic performance. The non-noble metal additives also merit further investigation.

Not only the modifications to the formulation of catalyst system, but also the preparation methods can impact the catalytic performance. Versatile synthesis strategies have been developed for obtaining catalysts with high performance during BESR. Incipient wetness impregnation (IWI) [88-91], wet impregnation [84, 92, 93], sol-gel (SG) [94, 95], and co­precipitation (CP) [63, 64, 86, 87] are the most commonly utilized methods, each of which has its own advantages and disadvantages. Impregnation is the most convenient method to be scaled up, for manufacturing. However, nonhomogeneous distribution of the metal precursor is the biggest issue associated with the impregnation method, leading to metal agglomeration, one of the reasons which contribute to catalyst deactivation. On the contrary, it is easier for SG and CP to achieve homogeneous dispersion of active metal. However, the synthesis procedure of SG and CP is more complicated compared with that of impregnation, leading to poor reproducibility between various batches. Also, since most of the active metal atoms are embedded in the matrix of support, resulting in less exposure of active metal on the sample surface, SG and CP prepared samples are more stable but less active than those prepared by impregnation. In addition, several novel preparation protocols such as hydrothermal [96], solvothermal [97], and microemulsion [98] have been developed to control the sample particle size and morphology which have been shown to be highly relevant to catalytic activity. On the other hand, most of the newly developed methods mentioned involve the employment of organic solvents, which could be harmful to the surroundings. Although all the preparation techniques documented up to now supply abundant resources to start with, the establishment of an appropriate method balancing low cost, easy operation, and environmental benignancy is important to be researched.

1.2.1 Cassava chip

Similar to bioethanol production of corn grains, there are two processes for preparing cassava chips which are "Dry Milling" and "Wet Milling". In Dry Milling process (Figure 2), chips are transferred to the hopper and a metal and stone detector. The chips are then milled and sieved to obtain fine powders. Coarse powders are remilled. The fine powder having all components including fibers is slurried with water and proceeds to cooking and enzyme hydrolysis. The heat to cook slurry for liquefaction process is usually from direct steam instead of a jet cooker due to the difficulties of handling particles and contaminants in slurry. Owing to contamination of sand, conveyor system and grinding system require special treatment. Furthermore, after passing through syrup making process, an extra separation unit or hydrocyclone is required to remove sand and other impurities. The dry milling process is suitable for batch fermentation. Most of existing factories in China and some factories being installed in Thailand apply this dry milling process as it uses less equipment and investment (Sriroth & Piyachomkwan, 2010b).

As corn grains are composed of many valuable components including protein, lipid and starch, wet milling process has been developed as a separation technique in order to fractionate starch and other high-valued products including corn gluten meal with high protein content, corn gluten feed and corn germ for oil extraction. The grains are initially

cleaned and soaked in steeping water containing some chemicals such as sulfur dioxide, the most typically used one, and lactic acid to soften the grains. The soften kernels are milled to be suitable for degermination process and separated germ is used for oil extraction. Degermed ground kernels are then passed through fine mills so that the fiber can be readily separated. The protein is further fractionated from the defibered starch slurry by centrifugal separators. After fractionation of each component, starch slurry is further processed to cooking and enzyme hydrolysis for ethanol production. In wet milling process of cassava chips (Figure 3), the starch slurry is prepared from dried chips by modifying typical cassava starch production process. Unlike wet milling of corn grains with water, the chips are milled to fine powder before slurried with water. The process is sometimes named as "Starch milk" process of which the starch is then extracted from chips by a series of extractors. After depulping, the starch slurry is then concentrated by a separator and subjected to a jet cooker for liquefaction. Currently, only a few plants are using this process, because this process requires a high investment. Factories have modified the process by reducing the extractor and stipping tank unit. Wet milling generates high starch losses in the solid waste. However, the process is more controllable and can be practically applied to high solid loading and continuous fermentation process (Sriroth & Piyachomkwan, 2010b).

In contrast to wet milling process, dry-milling process does not fractionate each component, yielding a by-product of mixed components. Although more valuable products are co­produced by wet milling process, this process is capital and energy intensive and results in a lower yield of ethanol as compared to dry-milling process; one ton of corn yields 373 and 388 liters of ethanol when processed by wet — and dry — milling, respectively (FO Licht, 2006).

both germ and fiber prior to fermentation (Singh and Eckhoff, 1997; Wahjudi et al., 2000; Huang et al., 2008). This combined process improves cost reduction as compared to wet­milling process while increases value addition to dry-milling process. Although, cassava chips are corn analog and can be processed either by wet-milling or dry-milling process, the chips do not contain other valuable components. Dry-milling process is therefore generally applied for bioethanol production.

Other proposed alternative to process sorghum before dry-milling is steam-flaking. This technology, widely used in feedlots, disrupts the endosperm structure with the injection of live steam in a period of 15 to 30 min, followed by flaking through grooved rolls. Before flaking, moisture of sorghum is increased to at least 21% and a conditioning or surfactant agent as lecithin is added in order to obtain whole flakes and reduce processing losses (Serna-Saldivar, 2010). After drying and cooling, sorghum flakes can be milled using traditional processes. The pregelatinized starch associated to the ground and steamed flaked sorghum had higher susceptibility during liquefaction and produced more ethanol during fermentation. Compared to the whole sorghum counterpart the steam-flaked sorghum yielded approximately 40% more ethanol (Chuck-Hernandez et al., 2009). Currently, the cost of steam flaking one ton of sorghum is approximately $7.5 US dollars.

Thanks to the latest breakthroughs in the research for improving the enzymes, nowadays most enzymes are produced for a commercially acceptable price. Nonetheless, the industrial

utilization of cellulases could be even more convenient by improving their stability in long­term operations and by developing methods/processes for the downstream recovery and reuse. These objectives can be achieved by the immobilization of the enzymes (Cao, 2005). The main advantages of the enzyme immobilization are:

1. more convenient handling of enzymes

2. easy separation from the product

3. minimal or no protein contamination of the product

4. possible recovery and reuse of enzymes

5. enhanced stability under storage and operational conditions (e. g. towards denaturation by heat or organic solvents or by autolysis) (Sheldon, 2007).

The main methods of enzyme immobilization can be classified into four classes: support binding (carrier), entrapment, encapsulation and cross-linking.

Support binding is based on fixing the enzyme to the external or internal surface of a substrate, by physical (adsorption), ionic or covalent bonding. Adsorption is a simple and inexpensive method of immobilization, and does not modify the enzyme chemical structure. However, it does not produce strong bonds between enzyme and substrate and this could cause a progressive lost of the enzyme from the support. Ionic-binding determines a strong bond between enzyme and support. The supports may be functionalized with a variety of chemical groups to achieve the ionic interaction, including quaternary ammonium, diethylaminoethyl and carboxymethyl derivates (Brady & Joordan, 2009). Covalent binding is the most widely used method of immobilization. Here the amino group of lysine is typically used as point of covalent attachment (Brady & Joordan, 2009). Lysine is a very common amino-acid in proteins, often localized on the surface of proteins. It has a good reactivity and provides acceptable bonds stability (Krenkova & Forest, 2004). Supports containing epoxy groups are widely used in the immobilization by covalent binding. These can react with lysine and with many other nucleophilic groups on the protein surface (e. g. Cys, Hys, and Tyr). Epoxy groups also react, in a slower way, with carboxylic groups (Mateo et al., 2007). The support used in this immobilization method is typically a prefabricated carrier, such as synthetic resins, biopolymers, inorganic polymers such as silica or zeolites.

Entrapment is based on inclusion of the enzyme in a polymer network (i. e. organic polymer, silica sol-gel). Unlike the previous methods, entrapment requires the synthesis of the polymeric network in the presence of the enzyme (Sheldon, 2007). This method has the advantage of protecting the enzyme from direct contact with the environment, reducing the effects of mechanical sheer and hydrophobic solvents. However, low amount of enzymes can be immobilized (Lalonde & Margolin, 2002).

Encapsulation is a method similar to entrapment, but, in this case, the enzyme is enclosed in a membrane that acts as a physical barrier around it (Cao L., 2005). The disadvantage is that entrapping or encapsulating matrix offer a certain resistance to the substrates diffusion.

Cross-linking results in the formation of enzyme aggregates by using bifunctional reagent, like glutaraldehyde, able to bind enzymes to each other without resorting to any support. In 1996, cross-linked enzyme crystals (CLEC; St. Clair and Navia 1992) were commercialized by Altus Biologics (Margolin, 1996). However the CLEC formation requires laborious and expensive processes of protein purification and it is applicable only to crystallisable enzymes. In addition, only one kind of enzyme can be used in the CLEC formation (Brady & Joordan, 2009). In 2001 a less-expensive method, known as CLEA (cross linked enzyme aggregates) was developed in Sheldon’s Laboratory and commercialized by CLEA Technologies (Netherlands), (Sheldon et al., 2005). Recently a new method has been developed, especially suitable for lipase immobilization. It is defined Spherezymes and it is based on the formation of a water-in-oil emulsion, in which lipases and surfactant are dissolved. Following the addition of a bifunctional cross-linker, permanent spherical particles of enzyme are generated (Brady & Joordan, 2009).

The most interesting immobilization procedures are in the area of covalent binding. Supports containing epoxy groups are widely used in the immobilization by covalent binding because these generate intense multipoint covalent attachment with different nucleophiles present on the surface of the enzyme molecules (Mateo et al., 2007). One limitation of the epoxy supports is the slow reaction of immobilization. To overcome this problem, Mateo and coworkers have designed epoxy supports able to ensure a mild physical adsorption of the enzymes followed by a very fast intramolecular covalent binding with the material epoxy groups. These supports were used to immobilize and stabilize enzymes such as glutaryl acylase (Mateo et al., 2001), |3- galactosidase from Thermus sp. (Pessela et al., 2003), and peroxidase (Abad et al., 2002). Epoxy supports, known as Sepabeads® are marketed by Resindion s. r.l. and quickly have begun to supersede another commercial support, known as Eupergit. This last is a microporous, epoxy­activated acrylic beads with a diameter of 100-250p, used for a wide variety of different enzymes (Boller et al., 2002).

Comprehensive in silico analysis is carried out to establish rational guidelines for further genetic modification of recombinant yeast. The basic strategy is to identify the effective target mode for the genetic change. To this end, we examine the effect of overexpressing enzymes (catalyzing the throughput flux of EMs) on the ethanol productivity (Peth) which is computed as follows:

PETH — [xETH (t f ) “ xETH (0)] / tf (6)

where xETH is the (molar or mass) concentration of ethanol, and tf is the batch fermentation time.

For realistic simulations, incorporation of metabolic burden is critical. Metabolic burden is ascribed to the lower availability of internal resources for host cells because the same resources are competitively used by plasmids for their replication and more importantly, the synthesis of exogenous proteins. While several empirical correlations are available to consider the change of growth rate with the plasmid content (e. g., Lee et al., 1985; Satyagal & Agrawal, 1989), cybernetic models are able to directly take into account of the reduction of internal resources (b), for example, as follows:

b0

1 + ф

where ф is the parameter depending on the overexpressed level of heterologous proteins as well as the plasmid copy number, and b0 denotes the fraction of internal resources when no genetic modification is made (i. e., ф = 0). We simulate enzyme overexpression by increasing the constitutive enzyme synthesis rate (aMj rs) in Eq. (3) and relate ф to the ratio of "the total incremental of aM, j’s due to plasmids" to "the summation of inducible enzyme synthesis rates."

As the number of fungal genome sequenced increase, the number of proteomics studies increase the same way. The studies are driven for various reasons, but some of them are devoted to the identification of proteins produced (and most frequently secreted) by fungi

Fig. 3. Expression of the genome of Fusarium graminearum when grown on different carbon sources. Microarrays were analyzed and the number of genes overexpressed (p<0.02, fold change >2) comparatively that after growth on glucose where determined (Table). The graph represents the repartition of the CWDE (cellulases in yellow, hemicellulases in pink and pectinases in green) as a function of the substrate used for growth.

in response to plant material. This fact fits well with the purpose of this chapter and is perfectly summarized by the title of a recent paper: "Plant-pathogen interactions: what is proteomics telling us" (Mehta et al., 2008). In this paper, is shown that when pathogens are in the presence of plants, their metabolism is changed to secrete proteins, including CWDE, potentially involved in plant cell wall degradation. These findings are in perfect accordance with the conclusion of the transcriptomics studies (see previous section).

We performed a proteomics study with the plant pathogen Fusarium graminearum grown either on glucose or on a preparation of plant cell wall as the sole carbon source (Phalip et al., 2005). When it is grown on glucose (Fig. 4.), the fungus secretes a few proteins in small quantities. When the more complex and diverse plant cell wall is used, the fungus reacts by secreting a much higher amount of more diverse proteins. Approximately half (45%) of these are putative CWDE. Furthermore, CWDE identified are able to take in charge the three cell wall layers: cellulose (11 proteins are putative cellulases), hemicellulose (25) and pectin (19). These results are also perfectly correlated with transcriptome studies. The fungus clearly responds to cell wall diversity by enzyme diversity. It could be a good point to keep in mind when looking for an enzyme cocktail for biomass valorization.

Fig. 4. Proteomics studies of Fusarium graminearum grown on glucose (A) and plant cell wall (B). Culture supernatants were concentrated and the equivalent of the same volume of supernatant was loaded on SDS-PAGE (C). The corresponding proteins were by identified by Mass Spectrometry and classified thanks to their homologies with protein in databases (D). The CWDE were further considered as a function of the cell wall layer they degrade (E).

Traditionally, production of ethanol from starch comprises of three general separate processes namely; liquefaction using я-amylase enzyme, which reduces the viscosity of the starch and fragments the starch into regularly sized chains, followed by saccharification whereby the starch is converted into sugar using glucoamylase enzyme. Each of the process operated at different temperature and pH optima with respect to the maximum enzyme reaction rate. The final process involved the fermentation of sugar into ethanol using yeast. The simplified flow of the process can be summarized as in Figure 1.

One of the most promising research priorities in agricultural production is the genetic improvement of crops with high economic relevance. In the case of sorghum for fuels there are important advances in the development of biomass, sweet and high yielding grain varieties and hybrids, but is yet one of the most important and critical research topics. The new cultivars should be adapted to marginal lands and also they must be resistant to pests, other phytopathogens and stable facing water stress.

The creation of new varieties for ethanol production is not an easy task because the relevant traits, such as plant height, total soluble solids, juice production and lignin : cellulose : hemicellulose ratio are "non additive" (Reddy et al., 2005). On the other hand and according to Turhollow et al. (2010), the genetic mapping combined with its relatively fast hybridation and field tests, can facilitate the design and development of dedicated bioenergy cultivars.

It is also of upmost importance to develop machinery to harvest sweet and biomass sorghums because the use of existing sugarcane equipments reduce yields and efficiencies. Furthermore, it is also imperative to development new agronomical and technological packages that include "just in time" harvesting.

The use of biomass sorghum represents one of the most relevant topics in research even when there are not economic and energy efficient technologies. However, there have been important advances in terms of fiber degradation to yield extracts rich in C5 and C6 fermentable sugars. The development of new and more environmental-friendly pretreatments that include the use of fiber degrading enzymes and hot water and new strains of yeast and bacteria are critical points for the economics of biomass transformation.

The new microorganisms must be designed or genetically engineered to be more efficient in terms of enhanced capacity to fully ferment C5 and C6 sugars at high temperatures (Canizo, 2009). The development of new strains of Saccharomyces cerevisiae designed for pentose utilization, with high tolerance to inhibitors, and with a better genomic stability has not been yet fully addressed despite the recent advances in genetic engineering. Unfortunately, there are only few industrial and commercial strains in the market.

Process wise, biorefineries should focus on designing new bioreactors, flow-patterns, new cocktails of enzymes to optimize hydrolysis, the utilization of immobilized microorganisms and the development of new distillation and ethanol dehydration technologies that favors the total energy balance.

Heike Kahr, Alexander Jager and Christof Lanzerstorfer

University of Applied Sciences Upper Austria

Austria

1. Introduction

1.1 Motivation and environmental aspects

The combustion of fossil fuels is responsible for 73% of carbon dioxide emissions into the atmosphere and therefore contributes significantly to global warming. Interest in the development of methods to reduce greenhouse gases has increased enormously. In order to control such emissions, many advanced technologies have been developed, which help in reducing energy consumption, increasing the efficiency of energy conversion or utilization, switching to lower carbon-content fuels, enhancing natural sinks for carbon dioxide, capture and storage of carbon dioxide, reducing the use of fossil fuels in order to decrease the amount of carbon dioxide and minimizing the levels of pollutants. In the last few years, research on renewable energy sources that reduce carbon dioxide emissions has become very important. Since the 1980s, bioethanol has been recognized as a potential alternative to petroleum-derived transport fuels in many countries. Today, bioethanol accounts for more than 94% of global biofuel production, with North America (mainly the US) and Brazil as the overall leading producers in the world (about 88% of the world bioethanol production in 2009).

Generally, biofuel production can be classified into three main types, depending on the converted feedstocks used: biofuel production of first, second and third generation. Bioethanol production of the first generation is either from starchy feedstocks, e. g. seeds or grains such as wheat, barley and corn (North America, Europe) or from sucrose-containing feedstocks (mainly Brazil). The feedstocks used for bioethanol production of the second generation are lignocellulose-containing raw materials like straw or wood as a carbon source. Biofuel production of the third generation is understood as the production of lipolytic compounds mainly from algae.

The feedstocks of bioethanol production of the first generation could also enter the animal or human food chain. Therefore, bioethanol production of the first generation is regarded critically by the global population, worrying about food shortages and price rises. Other reasons which lead to research and developments in bioethanol production of the second generation are: a shortage of world oil reserves, increasing fuel prices and reduction of the greenhouse effect. In addition to this, the renewable energy directive (EC 2009/28 RED) demands a reduction for Europe of 6% in the greenhouse gases for the production and use of fuels. This reduction is only possible if biofuels are added to diesel fuel or gasoline by the year 2020. It also seems that the target for greenhouse gas reduction for Europe can only be

achieved if the biofuels are mainly from biothanol of the second generation. Outside Europe (Brasil, USA) the targets can be achieved using first generation biofuels. Hence, research and development on the production of bioethanol of the second generation needs to be intensively promoted, particularly in the European countries.