Production of biobutanol by clostridia is not straightforward process and 1-butanol is neither a typical primary metabolite, the formation of which is connected with cells growth, nor a typical secondary metabolite like antibiotics or pigments. The metabolic switch from acido — to solventogenesis, regulation of which is usually connected with sporulation initiation, does not need to happen necessarily during the fermentation. Actually, when cells are well nourished and their growth rate approaches its maximum then cells reproduce and form only acids; this state has been many times observed in continuous cultivations (Ezeji et al., 2005) but sometimes it can occur even in batch cultivation as so-called "acid crash" (Maddox et al., 2000; Rychtera et al., 2010) which was generally ascribed to fast acetic and butyric acids formation. The proposed acid crash prevention was careful pH control or metabolism slowdown by lowering cultivation temperature (Maddox et al., 2000). However, very recently the novel possible explanation of this phenomenon has been revealed in intracellular accumulation of formic acid by C. acetobutylicum DSM 1731 (Wang et al., 2011). If acid crash is the phenomenon that usually happens at random in the particular fermentation, so-called strain degeneration is a more serious problem when the production culture loses either transiently or permanently its ability to undergo the metabolic shift and to produce solvents. The reliable prevention of the degeneration is maintaining the culture in the form of spore suspension (Kashket & Cao, 1995). A cause of degeneration was investigated in many laboratories using various clostridial strains and therefore also with different results. The degeneration of C. acetobutylicum ATCC 824 is probably caused by loss of its mega plasmid containing genes for both sporulation and solvents production (Cornillot et al., 1997) but mechanism and reason of this degeneration were not offered by this study. Actually the authors (Cornillot et al., 1997) compared wild-type strain C. acetobutylicum ATCC 824 with isolated degenerated mutants. It is questionable how often or under which conditions the degeneration of C. acetobutylicum ATCC 824 happens because in the past, it was reported 218 passages of vegetative C. acetobutylicum ATCC 824 cells did not almost influence their solvents formation (Hartmanis et al., 1986). The cells of C. saccharoperbutylacetonicum N1-4 degenerated when quorum sensing mechanism in the

population was impaired (Kosaka et al., 2007). The very detailed study of C. beijerinckii NCIMB 8052 degeneration disclosed two different degeneration causes: involvement of global regulatory gene and defect in NADH generation (Kashket & Cao, 1995). It seems probable that degeneration has no single reason and if other strains were studied different reasons would be found.

ABE industrial fermentation was probably the first process that had to cope with bacteriophage infection of producing microorganism. The first severe bacteriophage attack was reported from Terre Haute plant in the U. S.A. in 1923 and the problems occurred at fermentation of corn by Clostridium acetobutylicum (the solvents yield was decreased by half for a year). From that time, Clostridium strains used for either starch or saccharose fermentations were attacked by various both lysogenic and lytic bacteriophages what was documented in the literature. The ABE plant in Germiston in South Africa faced to confirmed bacteriophage infection 4- times in its 46-year history (plus two unconfirmed cases). Till now, the best solution in battle against Clostridium bacteriophages seems to be the prevention i. e. good process hygiene, sterilization, decontamination and disinfection (Jones et al., 2000).

Lactic acid bacteria represent the most common type of contamination having very similar requests for cultivation conditions (temperature, pH, anaerobiosis, composition of cultivation media) as clostridia and grow faster. These bacteria can cause not only losses in solvents yield but also can hamper the metabolic switch of clostridia because formed lactic acid over-acidifies the medium and poisons the clostridia in higher concentration. Other contaminants like Bacillus bacteria or yeast are encountered only scarcely (Beesch, 1953).

In liquid culture, the growth rate of D. salina CCAP 19/18 was significantly retarded by a bleocin concentration of 0.25 mg L-1. In the presence of 0.5 and 1.0 mg bleocin L-1, however, growth was completely inhibited; yet, cells were able to survive for over a week. In accordance with this restricted cell division, these cells exhibited physical manifestations of stress including minimal chlorophyll pigmentation and reduced motility. Of most relevance to the current study, bleocin concentrations of 2.0 mg L-1 and higher proved to eventually eradicate the algal cultures, although some viable cells persisted for three to five days. Similar results were observed when D. salina was cultivated on solid medium containing comparable concentrations of bleocin; however, the rate of growth on agar plates was expectedly much slower. An appreciable number of D. salina colonies were able to survive on solid medium containing 2.0 mg bleocin L-1 for nearly one month, while concentrations of 4.0 mg bleocin L-1 and higher killed the cells within one week. Growth curves for liquid cultures that exhibited prolonged viability (0.25, 0.5, 1 mg L-1) are depicted in Figure 5. Based on these findings, the M. I.C. of bleocin for this microalgal strain were found to be 2.0 mg L-1 in liquid culture and 4.0 mg L-1 on solid medium. Both conditions of selection require at least one week of exposure to the respective M. I.C. of bleocin.

The commercial herbicide Basta®, which employs PPT as its active ingredient, proved to be the most potent and fastest-acting selective agent tested. PPT concentrations of 1 mg L-1 and higher were able to kill D. salina cells within a matter of hours. In the presence of 0.5 mg PPT L-1, the growth rate was essentially negligible and these cultures were not sustainable for more than three days. Lastly, although 0.25 mg PPT L-1 reduced the rate of cell division, cultures remained viable for over a week. This concentration of PPT also induced noticeable signs of toxicity such as inhibited motility and increased carotenoid pigmentation in the algae. On solid medium, D. salina was significantly more tolerant to PPT than in liquid culture. Cells survived on agar plates containing 0.25, 0.5 and 1.0 mg L-1 for over one month. Qualitatively, an inhibition of cell growth was reflected both in the relative number of surviving cells, which naturally was inversely proportional to PPT concentration, as well as the prolonged viability of these slower growing colonies due to their more gradual exhaustion of available nutrients. After one month, the cells were rich in |3-carotene and noticeably orange in color. Figure 6 shows a side-by-side comparison of D. salina spot tested on 1 M NaCl medium with no selective agent added (left) and 0.25 mg PPT L-1 (right). The threshold for complete cell death on solid medium was clearly crossed at a PPT concentration of 2.0 mg L-1 after one week.

While paromomycin is toxic to related microalgae, D. salina CCAP 19/18 was found to be remarkably insensitive to this antibiotic. In the presence of concentrations as high as 400 mg paromomycin L-1, the algal cells were able to proliferate vigorously. Consequently, paromomycin was deemed unsuitable as a selective agent for the genetic transformation of D. salina.

Generally, heating coils are used to heat the raw material in biodiesel production process. This treatment can be also done by microwave method. An alternative heating system "microwave irradiation" has been used in transesterification reactions in recent years. Microwaves are electromagnetic radiations which represent a nonionizing radiation that influences molecular motions such as ion migration or dipole rotations, but not altering the molecular structure (Fini & Breccia, 1999; Varma, 2001; Refaat et al., 2008). The frequencies of microwave range from 300 MHz to 30 GHz, generally frequency of 2.45 GHz is preferred in laboratory applications (Taylor et al., 2005). Microwave irradiation activates the smallest degree of variance of polar molecules and ions with the continuously changing magnetic field (Azcan& Danisman, 2007). The changing electrical field, which interacts with the molecular dipoles and charged ion, causes these molecules or ions to have a rapid rotation and heat is generated due to molecular friction (Azcan& Danisman, 2007; Saifuddin & Chua, 2004). The absorption of microwaves causes a very rapid increase of the temperature of reagents, solvents and products (Fini & Breccia, 1999).

Microwave process can be explained for the biodiesel production with transesterification reaction: the oil, methanol, and base catalyst contain both polar and ionic components. Microwaves activate the smallest degree of variance of polar molecules and ions, leading to molecular friction, and therefore the initiation of chemical reactions is possible (Nuechter et al., 2000). Because the energy interacts with the sample on a molecular level, very efficient and rapid heating can be obtained in microwave heating. Since the energy is interacting with the molecules at a very fast rate, the molecules do not have time to relax and the heat generated can be for short times and much greater than the overall recorded temperature of the bulk reaction mixture. There is instantaneous localized superheating in microwave heating and the bulk temperature may not be an accurate measure of the temperature at which the actual reaction is taking place (Barnard et al., 2007; Refaat et al., 2008).

When the reaction is carried out under microwaves, transesterification is efficiently accelerated in a short reaction time. As a result, a drastic reduction in the quantity of by­products and a short separation time are obtained (Saifuddin & Chua, 2004; Hernando et al., 2007) and high yields of highly pure products are reached within a short time (Nuechter et al., 2000). So, the cost of production also decreases and less by-products occurs by this method (Oner & Altun, 2009). Therefore, microwave heating compares very favorably over conventional methods, where heating can be relatively slow and inefficient because transferring energy into a sample depends upon convection currents and the thermal conductivity of the reaction mixture (Koopmans et al., 2006; Refaat et al., 2008). Microwave assisted transesterification process schematic diagram was presented in Figure 4.

There can be also a few drawbacks of microwave assisted biodiesel production, beside the great advantages. Microwave synthesis may not be easily scalable from laboratory small-scale synthesis to industrial production. The most significant limitation of the scale up of this technology is the penetration depth of microwave radiation into the absorbing materials, which is only a few centimeters, depending on their dielectric properties. The safety aspect is another drawback of microwave reactors in industry (Yoni & Aharon, 2008; Vyas et al., 2010). This survey of microwave assisted transformations is abstracted from the literature published from 2000 to 2011. And studies on microwave assisted method of transesterification reaction in the literature were summarized in Table 5. The biodiesel production have been studied by using microwave assisted method from different oils such as cottonseed oil (Azcan& Danisman, 2007), safflower seed oil ( Duz et al., 2011), rapeseed oil (Hernando et al., 2007; Geuens et al., 2008), soybean oil (Hernando et al., 2007; Hsiao et al., 2011; Terigar et al., 2010), corn oil (Majewski et al., 2009), macauba oil (Nogueira et al., 2010), waste frying palm oil (Lertsathapornsuk et al., 2008), micro algae oil (Patil et al., 2011), karanja oil (Venkatesh et al., 2011), jatropha oil (Shakinaz et al., 2010), yellow horn oil (Zhang et al., 2010), canola oil (Jin et al., 2011), camelina sativa oil (Patil et al., 2009), castor oil (Yuan et al., 2009), waste vegetable oils (Refaat et al., 2008), maize oil (Ozturk et al., 2010) and sunflower oil (Han et al., 2008; Kong et al., 2009).

The experimental lignocellulosic composition of agricultural straw can be determined using the modified NREL LAP method for "Determination of Structural Carbohydrates and Lignin in Biomass" (Table 1) (Adapa et al., 2011; Sluiter et al., 2008). This procedure uses a two-step acid hydrolysis to fractionate the biomass into forms that are more easily quantified. During this process, the lignin fractionates into acid insoluble material and acid soluble material, while the polymeric carbohydrates are hydrolyzed into the monomeric forms, which are soluble in the hydrolysis liquid and subsequently can be measured using HPLC. The Percentage cellulose in the samples can be measured using the percentage glucan content, while the percentage hemicelluloses can be measured by adding the percentage mannose, galactose, xylose and arabinose content in the biomass samples.

Table 1 shows the lignocellulosic composition and higher heating values of non-treated and steam exploded barley, canola, oat and wheat straw samples. In general, the cellulose, hemicelluloses and lignin content of steam exploded straw was higher than non-treated straw. This may be due to other components (soluble lignin, loosely-bound sugars) being washed away during steam explosion, thereby leaving the proportion of insoluble lignin, cellulose and hemicellulose in the resulting dried sample higher than for the non-treated samples (i. e. higher percent of dry mass).

DM — Dry Matter; NT — Non-Treated; SE — Steam Exploded; a Average and standard deviation of 3 replicates at 95% confidence interval; b%Cellulose = %glucan; c%Hemicellulose = %(mannose + galactose + xylose + arabinose);

d%Total Lignin = %(soluble lignin + insoluble lignin); HHV — Higher Heating Values (measured using Parr 1281 Bomb Calorimeter); ф3 replicates; f 95% confidence interval

Table 1. Lignocellulosic composition and higher heating values of non-treated and steam exploded agricultural straw (Adapa et al., 2011)

The calorific (heating) value of biomass feedstocks are indicative of the energy they possess as potential fuels. The gross calorific value (higher heating value, HHV) and the net calorific value (lower heating value, LHV) at constant pressure measures the enthalpy change of combustion with and without water condensed, respectively (Demirba§, 2007). A bomb calorimeter can be used to determine the HHV of the non-treated and steam exploded straw in MJ/kg. In addition, the ASTM Standard D5865-03 (ASTM, 2003) test method for gross calorific value of coal and coke, can be used as a guideline for heating value testing (Table 1).

Cellulose, hemicelluloses and lignin are major components of a plant biomass. Therefore, a change in composition could potentially lead to change in HHV of the biomass (Adapa et al., 2010a). The Net combined percentage change of cellulose, hemicelluloses and lignin in steam exploded barley, canola, oat and wheat straw is 5%, 19%, 5% and 4% higher than non-treated straw, respectively. As a result, the average HHV of steam exploded barley, canola, oat and wheat straw was 6%, 10%, 9% and 5% higher than non-treated straw, respectively (Table 1).

Vibrational spectroscopy and microscopy techniques have been broadly used to analyze chemical and biological materials. The two main vibrational spectroscopic techniques, infrared spectroscopy and Raman spectroscopy, detect vibrations including both simple bond vibrations and group vibrations in molecules and thus identify these molecules by their spectral fingerprints originated from various vibrational modes. Infrared absorption typically involves photon absorption with the molecule excited to a higher vibrational energy level when the photon energy matches the energy difference between the two vibrational energy levels. This process depends on changes of dipole moments, and hence asymmetric vibrations cause the most intense infrared absorption. On the other hand, Raman scattering is the inelastic scattering of a photon that interacts with molecular vibrations, resulting in an energy shift of the exciting photon. This process depends on changes in polarizability of the electron cloud around the vibrating bonds or groups. Usually, symmetric vibrations cause the largest polarizability changes and thus render the greatest scattering. Therefore, these two techniques often provide complementary information about the molecules (Smith and Dent, 2005). All major cell wall biopolymers are both IR and Raman active. Nowadays both techniques are widely used in plant cell wall research (Dokken et al., 2005; Gierlinger and Schwanninger, 2007).

Unlike most of the current techniques for cell wall compositional analysis, such as wet chemistry assays, chromatography methods, mass spectrometry etc., which are destructive and involve breakdown of the cell wall components or extensive chemical treatment of the plant cell walls, IR and Raman spectroscopy can characterize cell wall components in their native form with minimal requirement for sample preparation. Moreover, a reliable measurement of a single sample can usually be completed from seconds to a few minutes. With the aid of a high throughput platform, such as 96-well plates, rapid screening of a large number of samples can be realized to meet the requirements of bioenergy feedstock development and biomass conversion process optimization for efficient biofuel production.

To acquire cellular level understanding of plant cell walls, various microscopic techniques have been employed, such as bright/dark field microscopy (D’Haeze et al., 2007), polarized light microscopy (Baskin et al., 2004), transmission electron microscopy (Fromm et al., 2003), scanning electron microscopy (Persson et al., 2007b), etc. However, to localize molecules of interest, histochemical and cytochemical staining and labeling methods have to be applied (Cavalier et al., 2008; Grunwald et al., 2002; Persson et al., 2007a). Although autofluorescence of lignin can be utilized to visualize distribution of lignin in the cell wall by fluorescence microscopy (Cavalier et al., 2008; De Micco and Aronne, 2007; Singh et al.,

2009) , chemical information of cellulose cannot be obtained without additional techniques and quantitative analysis is difficult. On the other hand, using IR and Raman microspectroscopy, chemical maps of specific cell wall components can be generated based on their spectroscopic fingerprints without any disruption of plant tissues and necessities of staining or any other extensive treatment of the cell walls. Localized and tissue/cell specific chemical information can be revealed, which enables acquisition of chemical information on the ultrastructure of plant cell walls. Thus, IR and Raman imaging can detect important compositional changes in cell walls by mutations not necessarily reflected in their average contents and spatial chemical changes during processing, which is very difficult to achieve by other chemical analysis and microscopic methods. Between these two vibrational spectroscopic techniques, IR spectroscopy has been established for decades as a useful tool for plant cell wall research. Integrated with attenuated total reflectance (ATR) technique, synchrotron sources, focal plane array (FPA) infrared detector, and chemometric analysis, IR technique has become increasingly powerful. However, this technique is limited by low sensitivity due to non-background-free detection, low spatial resolution associated with the long infrared wavelengths, and water absorption of the infrared light (Evans and Xie, 2008). The Raman technique, on the other hand, does not have these limitations. Recent advancement in laser technology, optics and detectors has led to a rapid growth in the applications of the Raman technique. Although auto-fluorescence from lignin may sometimes interfere with Raman measurement, the use of near infrared or UV excitation or a fluorescence quencher and effective baseline correction afterwards can alleviate this problem generally. In this section, the applications of IR and Raman techniques for cell wall analysis will be discussed.

Applications of IR microspectroscopy in plant cell wall research: The most prevalent type of IR spectrometer is a Fourier Transform Infrared Spectrometer (FTIR) by recording the raw data as an interferogram and then using Fourier transform to turn this raw data into a spectrum. Attenuated total reflection (ATR) objectives containing an internal reflection element usually made of ZnSe, Ge, or diamond are often used with IR spectroscopy to study plant materials due to faster sampling, improved reproducibility and less impedance by water absorption. IR spectra are most commonly obtained from 4000 to 400 cm-1, the mid­infrared region, where the peaks in the spectra can be associated with fundamental vibrations and the peak intensities are proportional to concentrations. Chemical compositions of various lignocellulosic biomass have been studied by mid-IR spectroscopy, such as wood samples, grasses and herbaceous plants (Dokken et al., 2005). Peak assignments for major cell wall components of representative biomass were summarized by Adapa et al. (2009). Compositional changes by biochemical and chemical treatments of cell walls were also investigated by FTIR. For example, behaviors of cell wall components of oak wood and barley straw treated with cellulase, acidic sodium chlorite, acid and base were studied (Stewart et al., 1995). Dilute acid pretreatment and ionic liquid pretreatment were compared using switchgrass as a model bioenergy feedstock (Li et al., 2010). Moreover, with the aid of chemometric techniques, FTIR can be used as a rapid method for cell wall mutant screening (Chen et al., 1998; Mouille et al., 2003). In addition, using polarizers with FTIR, the orientation of particular functional groups or cell wall components can be determined (McCann et al., 1993; Wilson et al., 2000).

The chemical imaging capability has made IR microscopy a powerful tool to reveal spatial distribution of cell wall components by collecting spectra at each spatial position in the defined area for imaging. FTIR microscopy was also demonstrated by Gierlinger et al. (2008a) to monitor in situ the enzymatic degradation of poplar wood and fast and selective degradation of the gelatinous layer in tension wood was observed. This method could be used for enzyme screening and working condition optimization for enzymes. The source intensity from conventional IR thermal sources can only provide a spatial resolution of tens of micrometers, which is limited by both signal-to-noise (S/N) ratio and diffraction, thus restricting plant analysis to the tissue level. Coupling a synchrotron IR source with a small effective source size to IR microscopy can overcome this difficulty due to the high source brightness that allows smaller regions to be probed with acceptable S/N, and thus only diffraction controls spatial resolution in this case (Carr, 1999). Using the synchrotron radiation-based FTIR microspectroscopy (SR-FTIR), imaging structures of plant tissue at cellular level with high S/N at ultraspatial resolutions (3-10 pm) was achieved (Dokken and Davis, 2007; Yu et al., 2003). The main drawbacks of SR-FTIR are the expense and limited access to synchrotrons and slow imaging acquisition by the point-by-point process. A more recent technique known as focal plane array (FPA) based FTIR imaging becomes available and promises many advantages. The FPA-FTIR imaging technique is laboratory based and employs two-dimensional detector arrays to collect spectra at marked positions simultaneously. Thus, FPA-FTIR imaging can acquire the chemical map in a fraction of time required by SR-FTIR imaging. Heraud et al. (2007) compared results produced by FPA — FTIR imaging and SR-FTIR imaging using Eucalyptus botryoides leaves as a model sample. They found that the two methods produced similar infrared images allowing differentiation of all tissue types in the leaves. While SR-FTIR imaging provided superior S/N ratio and better spatial resolution, it only took approximate 2 min for FPA-FTIR to map a 350 pm2 of tissue area, which took approximate 8 h for the SR-FTIR imaging to complete.

In addition to mid-IR spectroscopy, near infrared (NIR) spectroscopy has also been used as a useful tool for compositional analysis of lignocellulosic materials. Absorption spectra in the NIR region, i. e. 14000 — 4000 cm-1, are derived from the overtone or harmonic vibrations. Krongtaew et al. (2010a) has summarized the NIR peak assignments for major cell wall components. Nevertheless, multivariate methods are often implemented for NIR data analysis and both qualitative and quantitative information can be derived. For example, a partial least-squares regression (PLSR) model was developed based on the NIR spectra to assess lignin composition (p-hydroxyphenyl to guaiacyl ratio) in maritime pine wood (Alves et al., 2006). Key properties influencing the enzymatic hydrolysis yield and rates, such as lignin content, hemicellulose content, and cellulose crystallinity, influenced by different pretreatment methods were resolved in FT-NIR spectra and successfully evaluated by principal component analysis (Krongtaew et al., 2010a). Total residual lignin content, enzymatically released reducing sugars, total solids, volatile solids, and biogas yield can be assessed quantitatively by FT-NIR spectroscopy combined with partial least-squares regression models (Krongtaew et al., 2010b).

Applications of Raman microspectroscopy in plant cell wall research: Classical dispersive Raman spectrometers are usually composed of laser with wavelength in the visible range for excitation, a dispersive spectrometer and a charge coupled device detector (CCD) for detection. This system is often coupled to a confocal microscope equipped with objectives with high numerical apertures to achieve high spatial resolution (Gierlinger and Schwanninger, 2007; Smith and Dent, 2005). For example, a Raman spectrometer with a 514.5 nm laser was used to study the concentration of lignocellulosics in the cell corner middle lamella of both birch and spruce (Tirumalai et al., 1996). However, for plant cell wall research, the strong autofluorescence from lignocellulosic materials may mask the Raman spectra. Therefore, near infrared Fourier Transform Raman spectrometers (NIR-FT Raman) with laser radiation at 1064 nm coupled with interferometers is often utilized for cell wall analysis, because fluorescence is much less in this region. FT-Raman was used to characterize cell wall components of milled black spruce wood (Agarwal and Ralph, 1997) and in various anatomical parts of flax (Himmelsbach and Akin, 1998). Alternatively, the excitation laser can be shifted to the UV region (below 300 nm) where fluorescence is nearly absence. The utilization of UV excitation also leads to the resonance enhancement of aromatic structures and thus is very sensitive for lignin analysis. Nuopponen et al. (2004) has used UV resonance Raman (UVRR) spectroscopy to analyze the extractable compounds and solid wood samples of Scots pine. Saariaho et al. (2003) has characterized Raman peaks for p-hydroxyphenyl, guaiacyl and syringyl structures of lignin using UVRR. Raman peak assignments for major cell wall components were summarized by Agarwal and Ralph (1997) and Adapa et al. (2009). In addition to compositional analysis, a Raman spectroscopy-based method was also developed to obtain mechanical properties of plant cell walls (Ryden et al., 2003), which may serve as an indicator for the ease of cell wall deconstruction during pretreatment or enzymatic saccharification.

Like IR microspectroscopy, one of the major advantages of Raman technique exists in its chemical mapping capabilities. With a much higher lateral spatial resolution than IR (~ 1 pm), ultrastructure of plant cell walls with the corresponding compositional information can be revealed. Using confocal Raman imaging, the distribution of lignin and cellulose in black spruce wood was investigated (Agarwal, 2006) and changes of molecular composition in secondary plant cell wall tissues of poplar wood were illustrated (Gierlinger and Schwanninger, 2006). Raman imaging of Arabidopsis thaliana, one of the most important model plants, was recently demonstrated (Schmidt et al., 2009). Principal component analysis (PCA) and partial least square (PLS) modeling can be incorporated in image analysis to provide a more detailed comparison of cell wall compositions at different mapped regions (Gierlinger et al., 2008b). Raman imaging technique was also used to compare lignification in wild type and lignin-reduced 4-coumarate-CoA ligase (4CL) transgenic Populus trichocarpa stem wood (Schmidt et al., 2009). Raman imaging was further implemented to provide a more complete picture of the effects of alkaline treatment on Miscanthus x giganteus, a potential energy crop and a model lignocellulosic material. Longitudinal and transversal-section images of the parenchyma cells were generated, which revealed that lignin is removed preferentially from the inner surface of the cell wall and that cellulose is largely undisturbed (Chu et al., 2010).

Very recently our laboratory has developed a Raman imaging method to provide complete tissue/cell type specific compositional information for the first time (Sun et al., 2011). The method was demonstrated on stem sections of corn stover ranging from the epidermis to the pith area by both one-dimensional and two-dimensional chemical mapping. Lignin and cellulose abundance was determined in various cell types in the following order: sclerenchyma cells and tracheids (~5 times) > epidermal cells (~3 times) > bundle sheath cells > parenchyma cells. Unlike other Raman imaging work only showing the total lignin content, a Raman characterization study was performed to assign peaks for lignin compositions in terms of p-hydroxyphenyl, guaiacyl and syringyl units. Our imaging results have shown that significant amount of p-hydroxyphenyl units are present in the tracheids of corn stover stem, but not in the tracheids of the Eucalyptus globulus stem, which was corroborated by literature data (Galletti et al., 1996; Pinto et al., 2005).

Polarized Raman is another very useful tool for plant cell wall research by including polarizers in the optical path. Cao et al. (2006) has demonstrated a Raman study on the net orientation of biomacromolecules in the outer epidermal walls of mature wheat stems by comparing spectra collected with Raman light polarized perpendicular or parallel to the longitudinal axis of the cell. By changing the laser polarization direction in 3° steps, Gierlinger et al. (2010) investigated the dependency between cellulose and laser orientation direction and determined cellulose microfibril angle in S1 and S2 layers of wood samples, which was validated by X-ray diffraction measurement.

A separate category of nonlinear Raman techniques represented by coherent anti-Stokes Raman scattering (CARS) microscopy and stimulated Raman scattering (SRS) microscopy have emerged in recent years for plant cell wall research. CARS is orders of magnitude more sensitive, much faster in image acquisition and less affected by fluorescence compared with spontaneous Raman microscopy, and has the intrinsic capability of three-dimensional sectioning due to the nonlinear nature. CARS imaging of lignin in cell walls was demonstrated using corn stover (Evans and Xie, 2008). However, a CARS spectrum is different from its corresponding spontaneous Raman spectrum due to a nonresonant background, which causes difficulties in image interpretation. The major advantages SRS offers include an identical response to spontaneous Raman scattering, a linear dependence on the analyte concentration and fast image acquisition. Saar et al. (2010) has realized real­time monitoring of delignification reaction in corn stover using the acid chlorite method by SRS with high spatiotemporal resolution. However, some major problems associated with nonlinear Raman techniques are the cost and limited access to the instruments that are not commercially available and system optimization requirement for daily usage, which allows only very experienced people to operate the instruments.

The characteristics of the BT process are similar to the indirect gasification process with a pyrolyzer. This gasifier has three reactors for the preheating process, the reforming process and the pyrolysis process. The gasifier has the following characteristics; 1) pyrolysis reactions take place in the pyrolyzer, 2) pyrolysis gases are reformed by H2O (steam), 3) heat required for their reactions is supplied by combustion of off-gas, Tar and Char. Additional heat through a chip boiler might be required in order to accelerate the reactions well. With regard to the gasification performance, the gaseous yield and concentration are dependent upon the kinds of materials, the operating temperature, and the inner pressure (Muhlen et al., 1999, Mayer et al., 2004). Here, in order to evaluate the reliability of each fuel production, we fabricated an apparatus, which included the concept of the BT process (a pyrolyzer and a reformer), and we executed the basic chemical experiments using the biomass samples with the size of 2-3 mm. In the experiments, we measured the syngas components and estimated the equilibrium constants, adjusting the temperature condition and/or steam-carbon ratio (S/ C). Also, we ensured the reliability of our simulator which was available for some analyses on the energy cost and/or CO2 intensity etc. comparing our calculation to the demo-plant data. Assuming that the materials chopped at the size of 20-30 mm are fed into the reactor, H2 of 54.4 vol.% and CO of 24.4 vol.% were generated at 950°C and Steam/ Carbon=1.0 due to our simulator (Dowaki et al., 2007). On the other hand, we executed the studies in order to confirm the absolute proof of the chemical equilibrium reactions, and/or the heat balance in use of the experimental apparatus and/or the demo — plant (1t/d scale) at Izumo, shimane prefecture in Japan. Likewise, the studies on the handling of equipment (the plant operation) have been done at Izumo. In the previous studies, we made the simulator of BT process in order to estimate the operational performance. This simulation program used the parameters estimated by the experimental results of a room condition. Also, the estimation accuracy due to the simulator was analysed. For instance, Kameyama et al. compared the operational result of the demo-plant to that of the simulator. Accordingly, we made sure that the simulated data were corresponding with the practice data to some extent (Kameyama et al., 2010).

Here, we describe the system outline and the performance characteristics of this process which was evaluated through the demonstrated operation with 1t/d plant (see Fig. 2) of the Blue Tower gasification process.

Various microorganisms are capable of hydrolyzing starch, though a preliminary process called gelatinization is needed to ensure an efficient hydrolysis. During this preliminary process, the starch granules swell, particularly rupturing the hydrogen bonds in the crystalline regions. The long glucose chains comprising the starch must be converted into fermentable sugars by means of a process called the "hydrolysis technique", during which the starch reacts with the water normally used to break down the starch into its fermentable sugars. There are numerous microorganisms capable of hydrolyzing starch, but those involved in the starch degradation process are generally amylase, a-amylase, P-amylase and isoamylase. The most important for the purposes of the SSF process are certainly the first two. a-amylase is an endo-amylase that randomly attacks the a-1,4 bonds, rapidly reducing the starch molecule’s dimensions and consequently also its viscosity, i. e. it liquefies the starch. a-amylase can be obtained by means of heat-resistant bacteria such as Bacillus licheniformis, or by means of new strains of Escherichia coli or Bacillus subtilis, used on the starch suspensions during the first hydrolysis stage. For amylase to succeed in attacking these suspensions, they must be brought up to high temperatures (90-110°C) to rupture the starch cell nuclei. The products of this preliminary hydrolysis phase, called liquefaction, is a solution containing dextrins and a small amount of glucose.

At this point, the liquefied starch undergoes saccharification at low temperatures (60-70°C), induced by the action of glycoamylase generally obtained from Aspergillus or Rhizopus species. This enzyme is an exo-amylase capable of producing units of glucose from amylose and amylopectin chains.

The factors that influence starch hydrolysis include the substrate, enzyme activity and the reaction conditions (temperature, pH and other parameters) (Prasad et al., 2007). The microorganisms take effect more easily on gelatinized starch, but this process demands large amounts of energy so on an industrial level there has been a tendency to focus on using microorganisms capable of growing on ungelatinized starch. Various studies on this issue have considered certain species of fungi for producing enzymes capable of degrading starch in its natural state (Soccol et al., 1994). Liquefaction is followed by a saccharification stage under the effect of glycoamylase.

1.11.1 Milling

The milling phase enables the starch to be extracted from the biomass and it is very important for the purposes of analyzing the bioethanol production process as a whole because it strongly influences not only the subsequent stages but also the co-products obtained at the end of intermediate stages, which also vary according to the specific raw material entering the process (wheat, barley, corn, oats). The two main options are wet milling and dry milling.

Wet milling is the standard procedure generally used in the starch-based foodstuffs industry. Though this procedure demands more energy and more economic resources, and it delivers a smaller quantity of ethanol, it is still preferred at industrial level because its capacity to separate the grain into its components enables a purer form of starch to be obtained, along with more valuable byproducts. Wet milling can be used to obtain not only ethanol, but also products such as corn oil, gluten-based foods and flour, and corn steep liquor (CSL).

Dry milling means there is no need to pre-treat the raw material, which simply has to be ground before going through the other processing stages (hydrolysis, fermentation, distillation), which are identical to those following the wet milling process. Because dry milling does not break down the cereals into their various components, the unfermentable residue leaving the process that extracts the ethanol from the fermentation broth is rich in proteins, fibers, fats and sugars.

Hitoshi Nakagawa et al.*

Biomass Research and Development Center National Agriculture and Food Research Organization (NARO)

Japan

1. Introduction

About 12 billion tons of fossil fuels (oil equivalent) are consumed in the world in 2007 (OECD 2010) and these fuels influence the production of acid rain, photochemical smog, and the increase of atmospheric carbon dioxide (CO2). Researchers warn that the rise in the earth’s temperature resulting from increasing atmospheric concentrations of CO2 is likely to be at least 1°C and perhaps as much as 4°C if the CO2 concentration doubles from pre­industrial levels during the 21st century (Brown et al. 2000). A second global problem is the likely depletion of fossil fuels in several decades even though new oil resources are being discovered. To address these issues, we need to identify alternative fuel resources.

Stabilizing the earth’s climate depends on reducing carbon emissions by shifting from fossil fuels to the direct or indirect use of solar energy. Among the latter, utilization of biofuel is most beneficial because; 1) the solar energy that produces biomass is the final sustainable energy resource; 2) it reduces atmospheric CO2 through photosynthesis and carbon sequestration; 3) even though combustion produces CO2, it does not increase total global CO2; 4) liquid fuels, especially bioethanol and biomethanol, provide petroleum fuel alternatives for various engines and machines; 5) it can be managed to eliminate output of soot and SOx; and 6) in terms of storage, it ranks second to petroleum and is far easier to store than batteries, natural gas and hydrogen.

Utilization of biomass to date has been very limited and has primarily included burning wood and the production of bioethanol from sugarcane in Brazil or maize in the USA. The necessary raw materials for bioethanol production by fermentation are obtained from crop plants with high sugar or high starch content. Since these crops are primary sources of human nutrition, we cannot use them indiscriminately for biofuel production when the

demand for food keeps increasing as global population increases. Although fermentation of lignocellulosic materials, such as wood of poplar (Populus spp.) (Wyman et al. 2009), switchgrass (Panicum virgatum) (Keshwani and Cheng 2009) and Miscanthus (Miscanthus spp.) (Sorensen et al. 2008), straw of rice (Oryza sativa) (Binod 2010), old trunks of oil palm (Elaeis guineensis) (Kosugi et al. 2010) are being attempted by improving pre-treatment of the materials, yeast and enzymes, establishment of the technology with low cost and high ethanol yield will be required. Recently, a new method of gasification by partial oxidation and production of biomethanol from carbohydrate resources has been developed (Sakai 2001). This process enables any source of biomass to be used as a raw material for biomethanol production. We report on the estimated gas mixture and methanol yield using this new technology for biofuel production from gasification of diverse biomass resources, such as wood, forages, and crop residues etc. Data obtained from test plant operation is also provided.

In the world economic context, the optimization of industrial processes is a tool that has been applied frequently in order to reduce the consumption of raw materials, with the main objective of reducing production costs. Response surface methodology (RSM) is a powerful tool for the optimization of chemical reactions and/or industrial processes. The main advantages of this method include: (1) an understanding of how the test variables (process variables) affect the selected process response; (2) the determination of any possible interrelationship among the test variables; and (3) the characterization of the combined effect that all test variables may have on the process response (Myers & Montgomery, 1995). There are only few examples in the literature involving optimization of transesterification of vegetable oils to produce biodiesel, even knowing that the costs of biofuel production are high (Domingos et al., 2008).

Pinzi et al. (2011) evaluated together with the process variables, how raw material fatty acid composition affects the biodiesel production. The authors applied a factorial design to determine how the operation conditions affected the transesterification process (reaction temperature, initial catalyst concentration by oil mass and methanol concentration), while the reaction yield was considered as the response variable. The vegetable oils studied were maize (MME), sunflower (SFME), olive (OOME), coconut (CME), linseed (LME) and palm (PME). A different range of temperature (from 40 oC to 60 oC) was selected for coconut oil and palm oil, since these oils are rich in unsaturated fatty acids. Molar ratio methanol:oil ranged from 4.2:1 to 5.4:1 and catalyst concentration from 0.8 to 2.1% Optimized conditions for each of the raw materials are shown in Table 1.

A complementary study aimed to define the optimum time of reaction based on a study of reaction kinetics. During the transesterification reaction carried out at the optimized condition, samples were taken at 30s, 1, 2, 5, 10, 35, 60, 90 and 120 min. Kinetic curves showed that every transesterification reaction presents similar performance curve, with the exception of coconut that exhibits the lowest yield of fatty acid methyl esters (FAME). After 20-min reaction oils with longer fatty-acid chains (olive, corn, linseed and sunflower) achieve the optimal yield of FAME, but on the other hand palm oil and coconut oil show the best performance after 40-min reaction. The authors observed that the effect of catalyst concentration was influenced by fatty-acid composition. Vegetable oils composed by unsaturated fatty acids show a directly proportional dependence between the concentration of catalyst and yield, up to a maximum. Whereas, considering vegetable oils with (mono) saturated fatty acids, amounts of catalyst greater than the optimal value lead to soap production. Fatty acids chain length also seems to influence biodiesel conversion. Oils with longer fatty-acid chains need half of the reaction time requested by oils comprising shorter fatty-acid chains to achieve maximum yield.

Silva et al. (2011) discussed in their paper the production process optimization for biodiesel by transesterification of soybean oil with ethanol, where several parameters, including catalyst, alcohol/vegetal oil molar ratio, and temperature would influence the transesterification. The authors’ main objective was to study how the process variables (ethanol-to-oil ratio, catalyst concentration, reaction time and temperature) affecting the yield of biodiesel and then optimize this process. The levels of process variables studied were: ethanol/oil ratio (i. e., 3:1, 6:1, 9:1, 12:1 and 15:1), catalyst concentration (0.1%, 0.5%, 0.9%, 1.3% and 1.7% w/v of NaOH), reaction time (40, 60, 80, 100, and 120 min) and temperature (40, 50, 60, 70 and, 80 °C). Optimum values of the process parameter for maximum efficiency (95% of ethyl esters) were molar ratio ethanol: soybean oil 9:1, catalyst concentration 1.3% w/v, temperature 40 oC and reaction time 80 minutes. The analysis of the effects of process variables on yield in ethyl esters showed that the molar ratio, catalyst concentration and reaction time had a positive effect while the temperature had a negative effect. A positive effect means that the larger the values of process variables, the greater the yield of biodiesel.

Another optimization study used Raphanus sativus (L. Var) crude oil in ethanolysis with sodium hydroxide as catalyst. Three process variables were used to develop the experimental design: the ethanol:oil molar ratio (MR of 6:1 and 12:1), the catalyst concentration in relation to oil mass (C of 0.4 and 0.8 wt% NaOH) and the alcoholysis temperature (T of 45 and 65 oC). This yield was expressed in relation to the oil mass used for ethanolysis, reason why some values were greater than 100%. Reaction temperature had no statistical significance over biodiesel yield. The highest biodiesel yield was 101.7% obtained at 65 oC with a MR of 12:1 and 0.4 wt% of C. Nevertheless, when the alcoholysis temperature was decreased to 45 oC, phase separation improved and lower levels of soap accumulation were obtained in the ethyl ester phase. The authors recommend the following procedure for the ethanolysis of Raphanus sativus crude oil: MR of 11.7:1, NaOH concentration of 0.4 wt%, 45 oC and vigorous agitation for 60 min as the first reaction stage, followed by a second stage in which MR and NaOH concentration can be reduced to 6:1 and 0.03 wt%, respectively (Domingos et al., 2008).

Heterogeneous catalysis optimization was studied by Marchetti & Errazu (2011). The reaction temperature’s effects (30, 45 and 55 oC), the initial amount of free fatty acid (2.8%, 9.9% and 19.5% w/w), the molar ratio of alcohol/oil (4.2:1, 5.01:1 and 6.1:1) and the type of catalyst (homogeneous — sulfuric acid or heterogeneous — Dowex monosphere 550A) over the main reaction are analyzed and their effects compared. Temperature and molar ratio had a positive effect over biodiesel production: when the temperature and molar ratio increase the final conversion increases as well. When the initial amount of free fatty acid was varied, experimental results show that the final conversion increases as the initial amount of free fatty acid increases. Therefore, this effect could also be seen on the total FAEE production since the final amount of biofuel will be produced from the triglycerides as well as from the fatty acids present in the reaction mixture. The last part of this paper, a comparative study was made between the production of esters using sulfuric acid and a base solid resin with ethanol anhydrous under similar operational conditions, such as T=55 oC, initial amount of FFA=9.9% w/w, 2.2% w/w of each catalyst, and a molar ratio of alcohol/mixture of 6.1:1. Sulfuric acid reaches its final conversion in about 3 days time, while base solid resin reaches almost 100% in 70 hours.

As can be seen by the results showed earlier, biodiesel production is influenced by several process variables. The ideal combination of these variables will result in a higher yield in esters as well as a final product of higher quality. In addition, production costs could be reduced, including the industrial level. It was observed that depending on the feedstock, the type of alcohol and catalyst, the optimum conditions change. Another relevant point is related to the diversification of oil sources, which also help to reduce costs and to produce a quantity of fuel that meets global demand. In this scenario come acid oils, such as waste frying, and the heterogeneous catalysts, which are being actively researched.

The vapour pressure of biobutanol and bioethanol is very low compared to gasoline. A disadvantage of the bioethanol use is a formation of volatile azeotropic mixtures of ethanol and hydrocarbons present in the gasoline which causes the increase in the vapour pressure of gasoline in the range of 6 — 8 kPa (Muzikova et al., 2009). The formation of azeotropes occurs in the concentration up to 10% v/ v of biobutanol in gasoline but the highest increase in the vapour pressure is as low as 0.5 kPa at 5% v/ v of biobutanol in gasoline. At higher biobutanol concentrations, another volatile and/or oxygen compound has to be added to compensate vapour pressure decrease and to keep good engine startability. The formation of azeotropes is also associated with decrease of the boiling points of the blends. While the addition of bioethanol influences negatively the distillation curve profile, biobutanol has minor effect on the distillation curve.

Because of the use of different gasolines in several European Union countries, the mixing of different oxygen compounds in the vehicle tank can occur, causing the simultaneous presence of ethers like MTBE and ETBE and other alcohols, especially ethanol, in combination with biobutanol in the gasoline. Ethers do not cause problems since their properties are close to hydrocarbons. They influence the vapour pressure of the butanol — gasoline blend proportionally according to the initial vapour pressure of pure components. On the contrary, bioethanol forms azeotropes, which can unpredictably change the vapour pressure of the mixture. The increase of vapour pressure depends on the final ethanol concentration in the mixture.

Biobutanol has significantly higher heat of vaporization than gasoline, which reduces the temperature of the air/fuel mixture and results in higher engine volumetric efficiency. At the same time it leads to lower compression temperature and longer ignition delay, which in turn may decrease the engine performance. The low vapour pressure and higher heat of vaporization is experienced to have a negative effect on the startability and cold start engine performance because of difficult fuel vaporization at low ambient temperatures (Xiaolong et al., 2009).