The color on the woody carrier changed from light yellow to dark brown. Observation using a microscope revealed that biogenic Fe oxides produced by Fe-oxidizing bacteria had accumulated on the woody carrier (Fig. 8(a)). In many cases, the woody carriers were not easily visible because they had been completely covered by a mass of Fe oxides (Fig. 8(b)). Figure 9 shows the Fe collected on the woody carrier and the D-Fe concentrations of the water at the site of the immersion test. The average accumulation of Fe on the Japanese cedar was 7.91 g/kg during the irrigation period and 6.74 g/kg during the non-irrigation period. The respective values for the Japanese cypress were 7.67 and 5.54 g/kg. There were no significant differences between the values during the irrigation and the non-irrigation period. The average D-Fe concentration during the irrigation period (0.952 mg/L) was much higher than that during the non-irrigation period (0.338 mg/L). There were no significant differences during the irrigation and non-irrigation period between the collected Fe for the Japanese cedar and the Japanese cypress (Fig. 10). When these values are expressed in parts per million (ppm), the Fe collected during the irrigation period was 7,910 ppm for the Japanese cedar and 7,670 ppm for the Japanese cypress, while the D-Fe concentration was 0.952 ppm. Therefore, the concentration of the Fe on the woody carrier was 8,000- to 8,300-fold greater than the Fe dissolved in the water. For the non-irrigation period, the degree of Fe concentration was 16,000- to 20,000-fold greater.

Figure 11 shows the P adsorbed on the woody carrier and the PO4-P concentration. The average P adsorbed on the Japanese cedar carrier was 0.350 g/kg during the irrigation

period and 0.187 g/kg during the non-irrigation period. The respective values for the Japanese cypress were 0.332 and 0.172 g/kg. The differences between the values during the irrigation and non-irrigation periods were significant (p < 0.05). The average PO4-P concentration of the water during the irrigation period (0.058 mg/L) was much higher than that during the non-irrigation period (0.022 mg/L). This is probably because the anaerobic conditions caused by flooded water on the paddy fields during the irrigation period lead to the reduction of ferric phosphate (FePO4) compounds and the release of Fe2+ and phosphate (PO43-) ions. There were no significant differences in the adsorbed P during the irrigation and the non-irrigation period between the Japanese cedar and the Japanese cypress (Fig. 12). When these values are expressed in ppm, the P adsorbed during the irrigation period was 350 ppm for the Japanese cedar and 332 ppm for the Japanese cypress, while the PO4-P concentration was 0.058 ppm. Therefore, the concentration of the P on the woody carrier was 5,700- to 6,000-fold greater than the P dissolved in the water, and for the non-irrigation period, it was 7,800- to 8,500-fold greater.

Fig. 9. Fe content after the immersion test. (a), (b): collected Fe after 4 weeks immersion; (c): D-Fe concentration of the water (means and standard errors, n=8)

12
12
^PIO
1O
ьо 8 0) s 6
8 0) 6
!=l О U
Japanese cedar	Japanese cedar
Japanese cypress	Japanese cypress

0.0

Irrigation period Non-irrigation period

0.5
0.5 0.4 bO 0.3 43 0.2 5-й о 0.1 <
“ 0.4 ‘b0
0.0	0.0
Japanese cedar	Japanese cedar
Japanese cypress	Japanese cypress

Fig. 12. Comparison of adsorbed P between Japanese cedar and Japanese cypress (n=8)

Figure 13 shows the P fertile position of the immersed carrier on the relationship between the Bray-2 P in arable soils and the rice yield index (adapted from Komoto, 1984). In low — fertility soil (Fig. 13(a)), the yield index increases with Bray-2 P, but does not increase over the fertile level of 0.025 g/kg of Bray-2 P. As shown in Fig. 13(b), soils containing greater than 0.1 g/kg are categorized as high-fertility soil. The P values from this study were between 8- and 17-fold higher than the required level (0.025 g/kg) and categorized in the range of high-fertility soil. Therefore, the immersed carrier had obtained sufficient P fertility.

When practicing direct seeding on forest land there are practical recommendations considering among others Norway spruce (Picea abies (L.) Karst.) , Scots pine (Pinus sylvestris

L. ), birch, beech (Fagus sylvatica L.) and oak in relation to the target species. There are, however, few recommendations available for seeding on farmland, although the factors associated with successful establishment are the same as for natural seeding (species, mineral soil, moisture, competition by grasses and herbs, and weather conditions).

The success of establishment of seedlings after direct seeding depends on the nature of the soil treatment and the date of seeding. The critical phase is the emergence of seedlings during the first days or weeks after seeding and the moisture conditions in the treated spots. Generally, precipitation is low in late spring and therefore seeding must be undertaken early in spring.

High quality seeds are expensive and therefore a natural seed source close to the planting site can allow collection from mature seed trees of the appropriate species. Birch and alder are suitable species for producing stands for bioenergy harvest, with subsequent vigorous sprouting or suckering. Depending on seeding method the amount of seeds is 0.5-1.0 kg ha-1.

In the semi-arid agricultural areas of the world, soil salinization is closely linked to the extensive use of artificial irrigation, which in combination with extended dry seasons, very quickly turns formerly productive areas practically into deserts. In the future, this effect will even increase due to the high demand of water from other non agriculture sectors (i. e. industry, overpopulated cities), whereas the possibilities to increase any crop’s productivity through irrigation will necessarily decrease. Apart from irrigated areas, salinity is a major management problem in many unirrigated rainfed areas.

Dryland salinity ranges from a slightly saline soil condition which reduces crop growth to extensive areas where cultivation is almost impossible. This constraint has been a threat to the land and water resources in several parts of the world including the SAT, although the seriousness of the problem well realized in recent years. All the crops are affected by salinity while they vary in their degree of response as some of them being tolerant while others are sensitive.

1.2.1 Cereals Pearl millet

Soil salinity is a major problem for pearl millet [Pennisetum glaucum (L.) R. Br.] production in the arid and semi-arid zones of south Asia and West-Africa (Blummel et al. 2003). Pearl millet also remains as a potential crop to grow in the rice fallows of saline areas in south Asia, where typical increases of salinity levels during post-rainy season prevent crop production. Compared to other crop species, Pearl millet and its wild relatives are rated to be fairly tolerant to salinity (Maas and Hoffman 1977; Shannon 1984; Krishnamurthy et al.

2007) and provide an option while selecting crops that can be more profitably grown in saline soils.

Lack of a single reproducible screening protocol and lack of knowledge on trait(s) that confer yield under salinity is a great limitation to breeding tolerant varieties. Field screening under salinity stress may not be effective because of the extent of variability in salinity experienced within a single field and among plots even at shorter distances (Richards and Dennet 1980). Pearl millet seems to be sensitive at germination stage in ECe of 16 dS m-1 and beyond but this sensitivity is to some extent compensated by the tillering capability (Dua 1989). However, it seems that salinity response estimated at germination stage does not correlate well with plant performance at later stages (Munns and James 2003; Krishnamurthy et al. 2007).

Na+ exclusion and grain K/Na ratios were suggested to be reliable traits for selection. However, their usefulness as selection criteria (Munns and James 2003; Poustini and Siosemardeh 2004) could not be emphasized when five cultivars in pearl millet used for this association study (Ashraf and McNeilly 1987) where as leaf Na+ contents or the K+/Na+ and the Ca++/Na+ ratios assessed with 100 ICRISAT breeding lines were found to explain the biomass productivity at flowering time (Krishnamurthy 2007). Therefore this relationship of Na-based ratios needs to be evaluated with a wider range of genotypes and in association with the grain yield. Overall, it seems that although various aspects have been related to tolerance, the variation in whole plant reaction to salinity has been suggested to provide the best means of initial isolation of salinity tolerant genotypes (Shannon 1984; Ashraf and McNeilly 1987).

Large genotypic variation was reported to exist in pearl millet for salinity response in terms of whole plant response (Ashraf and McNeilly 1987; 1992; Dua 1989). Moreover, availability of high levels of tolerance in other species of Pennisetum (Ashraf and McNeilly 1987; 1992; Muscolo et al. 2003) and within the P. glaucum (Dua 1989) offers a scope for understanding the traits related to tolerance and to integrate these tolerant crop species/genotypes into appropriate management programs to improve the productivity of the saline soils. A total shoot biomass productivity ranging from 9 to 12 t ha-1 and a grain yield from 3.1 to 4.9 t ha-1 recorded in normal Alfisol fields at Patancheru, India (van Oostrom et al. 2002) got reduced to an average of 3.3 t shoot biomass and 1.1 t ha-1 grain yield of 15 germplasm accessions when grown in a 10 dS m-1 saline vertisols at Gangavathi, Karnataka, India (Kulkarni et al.

2006) .

Sorghum

Sorghum is characterized to be moderately tolerant to salinity (Maas, 1985; Igartua et al., 1995) with a large genotypic variation reported. It is considered relatively more salt tolerant than maize, the cereal crop ranking first in productivity globally (Maas, 1985). Therefore, sorghum has a good potential for salt affected areas (Ayers & Westcott, 1985; Igartua et al.,

1994) .

There are limited successes in enhancing crop yields under salinity stress as available knowledge of the mechanisms of salt tolerance has not been converted into useful selection criteria to evaluate a wide range of genotypes within and across species. Attempts have been made to evaluate salt tolerance at germination and emergence stages in grain sorghum (Igartua et al., 1994; Krishnamurthy et al. 2007), and large genotypic differences were reported, but this early evaluation appears to have little relation with overall performance under saline conditions (Munns et al., 2002; Krishnamurthy et al. 2007). Though Na+ exclusion and grain K+/Na+ ratios have been suggested to be reliable traits for selecting salt tolerant crops (Munns & James, 2003; Munns et al., 2002; Poustini & Siosemardeh, 2004; Netondo et al., 2004; Krishnamurthy et al. 2007), the value of that trait has not been used in a large scale. Therefore, there is a need to identify traits associated with salinity tolerance, and simple, high throughput, repeatable screening methods to evaluate large number of genotypes. In fact, the variation in whole-plant biomass responses to salinity was considered to provide the best means of initial selection of salinity tolerant genotypes (Shannon, 1984; Ashraf & McNeilly, 1987), prior to the evaluation on the basis of specific traits.

Some of the known salt tolerant genotypes (n=29) of sorghum have been reported to yield in the range of 1.5 to 4.2 t ha-1 in naturally occurring saline soils with an average ECe of 10 dS m-1 at the Agricultural Research Station, Gangavathi, Karnataka, India (Reddy et al. 2010). However the grain yield range was much superior (4.7 to 6.0 t ha-1) for the hybrids that were tested along the germplasm lines under similar saline field conditions.

1.2.2 Legumes

Chickpea

Chickpea (Cicer arietinum L. ) is sensitive to salinity (Flowers et al. 2010). The decline in the area sown to chickpea in traditional chickpea-growing areas of northern India and the Indo — Gangetic Plain (Gowda et al. 2009) is partly due to increased soil salinity and increased use of brackish water for irrigation. If this decline is to be reversed, then resistance of existing chickpea varieties to salinity needs to be improved. Since management options are often too expensive for small-holder farmers to adopt, breeding and selection of salinity-resistant varieties remains a more practical and immediate option.

Until recently, little genetic variation for salinity resistance had been observed in chickpea (Saxena 1984; Dua 1992; Johansen et al. 1990). However, recently a large range of variation (Vadez et al. 2007; Krishnamurthy et al. 2011) was found to exist in seed yield of 265 chickpea genotypes grown in artificially-salinized soils watered to field capacity with 80 mM sodium chloride. Further, it was found that the seed yield under salinity in chickpea was closely associated with time to flowering and to the seed yield under non-saline conditions.

Several reports have shown that the resistance to salinity in chickpea is related to the resistance of reproduction (Mamo et al., 1996; Katerji et al., 2001). Salinity resistance indeed had been shown to be associated with the capacity to maintain a large number of filled pods, rather than to the capacity to grow under salt stress (Vadez et al., 2007), indicating that salt stress may have a deleterious effect on flower/pod production and retention. Yet, reproductive success may have been conditioned by the late-sown conditions in which the previous work was carried out (Vadez et al., 2007) and needs to be validated with sowing at the normal sowing time.

As salinity is likely to be an increasing problem in a warming and drying world, especially for relatively sensitive crops such as chickpea, it is important to make sources of resistance available to the breeding community by systematically screening a representative set of germplasm. To date, only the mini-core collection of chickpea germplasm has been evaluated for salinity resistance (Vadez et al., 2007). This mini-core collection is based on morphological and agronomic traits (Upadhyaya and Ortiz 2001) and not a systematic screening for diversity of molecular markers. More recently, a reference collection of chickpea has been assembled using marker data from 50 SSR markers screened in over 3,000 genotypes (Upadhyaya et al., 2006). Although the reference collection includes all the germplasm in the mini-core collection, 89 additional entries of cultivated chickpea with additional molecular variability have been identified (Upadhyaya et al. 2008).

Groundnut

spite of the importance of the constraint as well as the crop very little has been published with groundnut being affected by soil salinity. In a salinity tolerance screening saturating soil once with with 80 mM NaCl solution and testing 288 groundnut genotypes/ germplasm accessions it has been found that the shoot biomass productivity was the least affected (0­30%) while the pod yield was affected by 50 to 100%. However there were genotypes that could produce pod yields >half of the control but these were very few (Srivastava 2006).

Pigeonpea

Pigeonpea is one of the major legume crops grown in the semi arid tropics, particularly in India. Its high sensitivity to salinity coupled with the dry growing environment pose a major constraint to crop production in certain areas. Salinity affects plant growth, development and yield of pigeonpea. However the quantum of work that had been carried out with pigeonpea under salinity is scarce. A study involving a tolerant (ICPL227) and a sensitive (HY3C) cultivated pigeon pea genotypes and some tolerant (Atylosia albicans, A. platycarpa and A. sericea) and sensitive (Rynchosia albiflora, Dunbaria ferruginea, A. goensis and A. acutifolia) wild relatives tested over a range of salinity levels (0, 4, 6, 8 and 10 dS/m) have shown that transpiration rate decreased with increasing salinity in tolerant and sensitive pigeon pea genotypes alike, while key difference was the greater salinity tolerance of A. albicans, A. platycarpa and A. sericea was associated with efficient sodium and chloride regulation in the plant system (Subbarao et al. 1990).

Shoot sodium concentrations of the tolerant wild species were found to be 5 to 10 times less than those of the sensitive species, while root sodium concentrations in the tolerant species were 2 to 3 times higher than in the sensitive species. Thus the efficiency of regulation of ion transport to shoots seemed to explain the differences in salinity response among pigeon pea genotypes and related wild species. Srivastava et al. (2007) assessed the morphological and physiological variation in pigeonpea for salinity tolerance in 300 genotypes, including the mini core collection of ICRISAT, wild accession and landraces from putatively salinity — prone areas worldwide. A large range of variation in salinity susceptibility index and the percent relative reduction (RR %) in both cultivated and wild accessions were shown to exist. Also less Na+ accumulation in shoot was indicative tolerance and this relationship was limited to the cultivated material. Some of the wild species reported tolerant are C. platycarpus, C. scarabaeoides and C. sericea whereas C. acutifolius, C. cajanifolius and C. lineata were more sensitive. In another study, six pigeonpea genotypes were tested under five different NaCl concentrations (0, 50, 100, 125, 150 mM) under controlled conditions. Salt concentration of 75 mM was identified to be the critical one as it reduced the biomass production by an average 50%. For pigeonpea, as SCMR was positively associated with higher biomass under salinity, SCMR was suggested to be an early indicator for salinity tolerance. The Na+ accumulation did not help to be of any indication of tolerance in pigeonpea.

Costa & Leal (2009) observed that in hydroponic production of lettuce, variety Vera, in three greenhouses, one without evaporative cooling and CO2 injection, another with injection of CO2 and without evaporative cooling and a third, with CO2 injection and evaporative cooling (acclimatized), the environment with evaporative cooling and CO2 injection promoted the best development of plants with larger leaves.

In acclimatized environment with evaporative cooling, Costa & Leal (2008) found greater accumulation of leaf biomass and greater leaf area of strawberry plants than in non — acclimatized environments, regardless of the season (Table 1).

For five cultivars of lettuce (Veronica, Vera, Cinderella, Isabela, Veneranda) under four different environmental conditions (Black screens with 30%, 40%, 50% shading and without the screen) in the region of Caceres-MT/Brazil, Queiroz et al. (2009) found that the Veronica cultivar was the most productive during the winter of 2008 and shading of 40% was best for most cultivars.

RDM (g)

Table 3. Root dry mass (RDM) of cucumber seedlings at 23 days after sowing for the various hybrids (H) in environments (A) and substrate (S) studied.

In tomato production in greenhouses with and without aluminized screen, Gent (2007) verified that the use of the screen with 50% shading increased commercial fruit production by 9% compared to the environment without the screen, verifying the beneficial use of this screen type in protected environments. Comparisons between the mobile aluminized screens with 40, 50 and 60% shading and the environment with polyethylene plastic film painted with lime, were evaluated by Fernandez-Rodriguez et al. (2001) in tomato production and it was found that the screens minimize energy consumption during periods of low temperatures.

With the objective of evaluating cucumber seedlings in function of environmental conditions, polystyrene trays with 72 and 128 cells and substrates with percentages of organic compound in Aquidauana-MS/Brazil, Costa et al. (2009c) conducted an experiment in six environmental conditions: plastic greenhouse with a height of 2.5 m; nursery with a black monofilament screen with 50% of shading and height of 2.5 m; nursery with an aluminized screen with 50% of shading and height of 2.5 m; nursery covered with native coconut palms with height of 1.8 m; plastic greenhouse with height of 4.0 m, zenithal opening and thermo-reflective screen over the black monofilament screen with 50% of shading and height of 3.5 m. The authors concluded that the greenhouses promoted better results for cucumber seedlings.

In previous text main groups of biotechnologically important metabolites used for enrichment of red yeast biomass were described. Mainly carotenoids, ergosterol, lipids and metal accumulation in red yeast cells makes them attractive for industrial applications.

Ergosterol is provitamin D, part of was followed partly as the additional parameter of biomass quality and also to monitor the competition of two specialized branches of isoprenoid pathway, which is used for the biosynthesis of both carotenoids and sterols. The production of ergosterol was very similar to the production of P-carotene, even if these metabolites were formed in competitive branches of isoprenoid metabolic pathway (Marova et al., 2010). Practically simultaneous oscillation in carotenoid and ergosterol production under optimal conditions could be caused by the role of both metabolites in R. glutinis stress response. Carotenoids act as antioxidants and may prevent cells or cell membranes against negative effects of increased oxidative stress. Ergosterol is an integral component of yeast cell membranes, which are very sensitive to external stress. Recently it has been found that the major changes in intact cells of red yeast Rhodotorula minuta irradiated by UV-B were interpreted as combination of changes observed in the cell wall and membrane, the changes observed in the membrane preparations were attributed to ergosterol (Tan et al., 2003). Ergosterol is a precursor of Vitamin D2 and it is also used for the production of cortisone (Metzler 2003). Now ergosterol as single product is commercially produced by yeast fermentation using Saccharomyces cerevisiae strains. The popular means to improve the ergosterol fermentation are optimization of the culture medium, screening of the high ergosterol producing strains. Different carbon sources, nitrogen sources and other nutrient materials had different influences on cell growth and accumulation of ergosterol in yeast biomass. A new yeast strain, obtained by way of protoplast fusion, increased the biomass to 2.45 g/100 ml (dry cell weight) and the ergosterol content to 3.07% (Frengova a Beshkova, 2009). It was reported that the synthesis of ergosterol was not determined by cell growth but by the oxygen consumption rate. Ethanol was formed in yeast fermentation and it had an obvious influence on the growth of yeast. In yeast culture process, glucose is preferred and when the glucose concentration reaches a low value, the cell growth is confined. Then after a short period of adaption, cells continue to grow by consuming the ethanol produced in the first phase as the carbon source. The whole process appeared to be a two-phase process. The ergosterol content increased when the specific growth rate decreased. The environmental and physiological parameters such as the dissolved oxygen, oxygen uptake rate of yeast cells culture had direct or indirect influences on the accumulation of ergosterol and the growth of yeast cells. The interaction relation might help to optimize the ergosterol fermentation. But until now little work has been reported on this relation (Tan et al., 2003). Carotenoids are important natural pigments that play an essential role as accessory light­harvesting pigments and, especially, in protection against damage by photosensitized oxidation. Several yeast genera—Rhodotorula, Sporobolomyces, Rhodosporidium, and

Cryptococcus — produce also coenzyme Q10 (CoQ10; Dimitrova et al., 2010). CoQ10 has a similar isoprenoid chain in its structure. It is also an interesting product for biotechnology. CoQ10 is present in all cells and membranes, and in addition to being a member of the mitochondrial respiratory chain, it also has several other functions of great importance for the cellular metabolism, such as participation in the extra-mitochondrial electron transport (plasma membranes and lysosomes), regulation of the mitochondrial permeability of transition pores, and regulation of the physicochemical properties of membranes. CoQ10, especially, is widely used as an essential component of ATP generation in the oxidative phosphorylation process and as an antioxidant preventing lipid peroxidation and scavenging superoxide. It has been proved that yeast CoQ10 is much better absorbed by the skin than the synthetic CoQ10. Peroxide reduction in the stratus corneum is considerably more pronounced after yeast CoQ10 application. Therefore, research efforts on the production of CoQ10 by microorganisms focus on the development of potent strains by conventional mutagenesis and metabolic engineering, analysis and modification of the key metabolic pathways, and optimization of fermentation strategies. Various microorganisms, including bacteria (e. g., Agrobacterium, Rhodobacter) and yeasts (e. g., Candida, Rhodotorula, and Saitoella), are reported as CoQ10 producers in patented laid-open applications purposely applied in pharmaceutical and cosmetic industry (Dimitrova et al., 2010, Yurkov et al., 2008).

Strains of basidiomycetous yeasts isolated from different sources were studied in order to determine the content of carotenoid pigments and ubiquinone Q10 for subsequent selection work to obtain producers of these substances. The high specific productivity of carotenoids (600-700 mg/ g) was revealed in the representatives of the following species: Cystofilobasidium capitatum, Rhodosporidium diobovatum, R. sphaerocarpum, Rhodotorula glutinis, Rhodotorula minuta, and Sporobolomyces roseus. The ratio of the major pigments (torulene, torularhodine and P-carotene) in the representatives of different species was studied. Certain specific features of pigment formation in relation to the taxonomic position of the yeasts were determined. Eurybiont species with substantial ecological lability are the most active producers of carotenoids and ubiquinone Q10 among the epiphytes. It is the first time a comparative analysis of the coenzyme Q10 content in different taxa has been performed using several strains of the same species. The maximal coenzyme Q10 production (1.84 mg/g of dry biomass) was found in the yeast species R. sphaerocarpum (Yurkov et al., 2008).

Environmental pollution, strictly interconnected to industrial spread, started in the most advanced countries. It is now diffused all over the world with a significant predominance in the emerging industrialized states. Varying factors contribute to the location of a large number of "potential polluting" industries in these countries due to the quite recent industrialization: source of raw materials (mines, forests, . ), water availability, ready availability of manpower and its lower incidence on cost, laws not yet as restrictive as in advanced industrial countries. Actually, most raw matter is treated locally, not only for their natural resources, but also because of the lower cost of preliminary treatments. These treatments are the most hazardous, the heaviest and above all the most polluting.

In order to have a clear picture of the main anthropogenic sources of metal, or better said toxic element in general, pollution and their health effects, the sources, uses, correlated health disorders, and suggested concentration limits are reported in the following sections for each main polluting toxic element.

1.3.2 Bioethanol production from sweet sorghum

Sweet sorghum is a crop for producing energy which not only produce food, but also energy, feed and fiber (Almodares & Hadi, 2009). The chief sugars present in sorghum are monosaccharides: glucose and fructose, and disaccharides: sucrose. Fermentable

carbohydrates in sweet sorghum stalks comprise approximately 80% soluble sugars and 20% starch. To optimize production of ethanol from sweet sorghum grain requires both liquefying and saccharifying enzymes (Rooney and Waniska, 2000). Therefore, it seems that using carbohydrates in the stalk (sucrose and invert sugar) is suitable for ethanol production for biofuel production because these carbohydrates are easily converted to ethanol (Fig 2). Although, ethanol can be produced from sweet sorghum grain (Fig. 2) but it needs more process for converting it’s starch to glucose that later will be converted to ethanol (Jacques et al., 1999). In addition, the produced baggase after juice extraction can be used for ethanol production (Jacques et al., 1999) or animal feed. However, presently it is not economically feasible to produce ethanol from sweet sorghum baggase (Drapcho et al., 2008).

Biomass

Fig. 2. Proposed layout for ethanol production and by-product from sweet sorghum (Almodares & Hadi, 2009).

3.2.2 The important of ethanol in biofuel

One method to reduce air pollution is to oxygenated fuel for vehicles. MTBE (Methyl tert — butyl ether) is a member of a group of chemicals commonly known as fuel oxygenates (Fischer et al., 2005). It is a fuel additive to raise the octane number. But it is very soluble in water and it is a possible human carcinogenic (Belpoggi et al., 1995). Thereby, it should be substituted for other oxygenated substances to increase the octane number of the fuel. Presently, ethanol as an oxygenated biomass fuel is considered as a predominant alternative to MTBE for its biodegradable, low toxicity, persistence and regenerative characteristic (Cassada et al., 2000). In most countries, gasoline supply is an ethanol blend, and the importance of ethanol use is expected to increase as more health issues are related to air quality. Ethanol may be produced from many high energy crops such as sweet sorghum, corn, wheat, barely, sugar cane, sugar beet, cassava, sweet potato and etc (Drapcho et al.,

2008) . Like most biofuel crops, sweet sorghum has the potential to reduce carbon emissions. Therefore, it seems that sweet sorghum is the most suitable plant for biofuel production than other crops under hot and dry climatic conditions. In addition, possible use of bagasse as a by-product of sweet sorghum include: burning to provide heat energy, paper or fiber board manufacturing, silage for animal feed or fiber for ethanol production. However, since
sweet sorghum is at a relatively early stage of its development, continued research was needed to obtain better genetic material and match local agro-economic conditions. The challenge is to harvest the crop, separate it into juice and fiber, and utilize each constituent for year-round production of ethanol.

Sweet sorghum juice is assumed to be converted to ethanol at 85% theoretical, or 54.4 liter ethanol per 100 kg fresh stalk yield. Potential ethanol yield from the fiber is more difficult to predict (Rains et al., 1993). The emerging enzymatic hydrolysis technology has not been proven on a commercial scale (Taherzadeh and Karimi, 2008). One ton of corn grain produces 387 L of 182 proof alcohol while the same amount of sorghum grain produces 372 L (Smith and Frederiksen, 2000). Sorghum is used extensively for alcohol production (Gnansounou et al., 2005), where it is significantly lower in price than corn or wheat (Smith and Frederiksen, 2000). The commercial technology required to ferment sweet sorghum biomass into alcohol has been reported in china (Gnansounou et al., 2005). One ton of sweet sorghum stalks has the potential to yield 74 L of 200- proof alcohol (Smith and Frederiksen, 2000). Therefore, it seems that because ethanol can be produced from both stalk and grain of sweet sorghum (Fig. 2), so it is the most suitable crop for ethanol production using for biofuel comparing to other crops such as corn or sugarcane.

Daily kefir grain increase mass was studied using fresh HTP whole fat cow’s milk (Ljubljanske mlekarne d. d.) as a culture medium. Its chemical composition is 3.2 % proteins, 4.6 % carbohydrates, 3.5 % fat and 0.13 % calcium. 3D-(+) Glucose anhydrous (Fluka) was obtained from commercial sources. Kefir grains, used as inocolum in this study, originate from Caucasian Mountain and were acquired from an internationally recognized local dairy (Kele & Kele d. o.o.). Their detailed microbial composition was not analyzed. Importantly, the microbial population (bacteria and yeasts) of kefir grains depends on many different factors (age, storage conditions and fermentation medium) and varies with the season. It is almost impossible to assure equal microbial composition during long term period, therefore for sets of experiments within one research, kefir grains with the same viability should be used.

1.2 Kefir grain biomass activation

Kefir grain biomass activation was performed in a glass lab beaker. The collected inactive kefir grains (^kG = 40 g/L) were inoculated in 1 L of fresh HTP whole fat cow’s milk. After
incubation at room temperature ($ = (22 + 2) °C) for 24 h, the grains were separated from the kefir beverages using a household sieve. After washing, they were reinoculated into the fresh milk. The same procedure was repeated over six subsequent days. After this procedure the kefir grains were considered active.

As was previously mentioned, the iMBR represents the most widely used configuration in large scale applications. This section gives some design and operation considerations including:

i. Pre-treatment,

ii. Design flux, hybrid systems and equalization tanks,

iii. Membrane fouling control and cleaning,

iv. Sludge retention time and biomass concentration, and

v. Membrane life

2.3.1 Pre-treatment

Membranes are very sensitive to damage with coarse solids such as plastics, leaves, rags and fine particles like hair from wastewater. In fact, a lack of good pre-treatment/screening has been recognised as a key technical problem of MBR operation (Santos and Judd, 2010a). For this reason fine screening is always required for protecting the membranes. Typically, screens with openings range between 1 mm (HF modules) to 3 mm (FS modules) are common in most facilities. However, data reported by Frechen et al. (2007) for 19 MBR European plants show a more conservative plant design by reducing the screen openings to 0.5-1.0 mm for both HF and FS. Regarding primary sedimentation, it was not economically viable for small-medium sized MBR plants (< 50.000 m3/d), except for cases of retrofitting or upgrading of an existing CAS. However, for larger plants, given its advantages (smaller bioreactor volumes, reduced inert solids in the bioreactor, increased energy recovery, etc.), primary clarification can be considered. Its selection should be a compromise between energy and land cost.

Protein (N x 5.70) content was determined by Kjeldahl method by automatic nitrogen analyzer (methodology ISO 1871:1975). Falling number was determined according to ISO 3093:2004. Gluten content was determined by Glutomatic according to ISO 7495:1990. Sedimentation index of wheat flour (Zeleny sedimentation test) was determined according ISO 5529:1992. Determination of bulk density, called "mass per hectoliter" was performed according to ISO 7971-2:1995.

1.1.4 Replicates and statistical analysis

All variants were cultivated and treated in four replicates. Statistical evaluation was performed with ANOVA. Post-hoc analyses were performed by Tukey’s HSD (Honestly Significant Difference) test (p < 0.05) for metals content and by Fisher’s LSD (Least Significant Difference) test (p < 0.05) for grain quality parameters, thousand-grain weight and yield of grain.