Category Archives: BIOMASS NOW — SUSTAINABLE GROWTH AND USE

Affecting parameters

Within the anaerobic and aerobic environment, various important parameters affect the rates of the different steps of the process, i. e. pH and alkalinity, temperature, and hydraulic retention times.

Each group of microorganisms has a different optimum pH range. Methanogenic bacteria are extremely sensitive to pH with an optimum between 6.5 and 7.2 pH, alkalinity and volatile acids/alkalinity ratio. The fermentative microorganisms are somewhat less sensitive and can function in a wider range of pH between 4.0 and 8.5. at a low pH the main products are acetic and butyric acid, while at a pH of 8.0 mainly acetic and propionic acid are produced.

The temperature has an important effect on the physicochemical properties of the components found in the digestion substrate. It also influences the growth rate and metabolism of microorganisms and hence the population dynamics in the anaerobic reactor. Acetotrophic methanogens are one of the most sensitive groups to increasing temperatures. The degradation of propionate and butyrate is also sensitive to temperatures above 70 °C. The temperature has moreover a significant effect on the partial pressure of H2 in digesters, hence influencing the kinetics of the syntrophic metabolism. Thermodynamics show that endergonic reactions (under standard conditions), for instance the breakdown of propionate into acetate, CO2, H2, would become energetically more favourable at higher temperature, while reactions which are exergonic (e. g. hydrogenotrophic methanogenesis) are less favoured at higher temperatures.

The solids retention time (SRT) is the average time the solids spend in the digester, whereas the hydraulic retention time (HRT) is the average time the liquid sludge is held in the digester. The subsequent steps of the digestion process are directly related to the SRT. A decrease in the SRT decreases the extent of the reactions and viceversa. Each time sludge is withdrawn, a fraction of the bacterial population is removed thus implying that the cell growth must at least compensate the cell removal to ensure steady state and avoid process failure [28].

Artemia meal in broiler diets

In another experiment, different levels of protein from two kinds of artemia meal include artemia meal from Urmia lake and artemia meal from earth ponds beside Urmia lake with levels of 0, 25, 50, 75, 100 percent replaced to prue fish meal protein [12]. The experimental design was completely randomized with factorial method; include 10 treatments and 3 repetitions that in each repetition there were 10 one day-old male broilers from Ross 308 strain. This experiment was performed in 7 weeks and during and end of it, traits that related to broiler performance and carcass, was measured and analyzed. Results showed that effect of kind of artemia meal and effect of level of protein replacement weren’t significant for feed intake. But interaction between these two was significant for this trait (P<0.05). The highest feed intake belong to Urmia lake artemia meal treatment with 50% level of replacement and the lowest feed intake related to treatment of without artemia meal (contain 5% fish meal). For body weight gain and feed conversion ratio, effect of kind of artemia meal and effect of level of protein replacement and effect of interaction between these two weren’t significant. These effects weren’t significant for all carcass traits and gastro intestinal parts exception for femur percent that treatment of without artemia meal (contain 5% fish meal) had a lowest percent to comparison with other treatments for this trait.

Apparent digestibility True digestibility

Amino acids ———————————————————————————————

Excreta

Ileal

SEM1

P2

Excreta

Ileal

SEM

P

Methionine

0.92

0.94

0.004

NS

0.96

0.99

0.004

0.09

Lysine

0.88

0.92

0.007

NS

0.92

0.96

0.007

NS

Threonine

0.85

0.90

0.013

NS

0.93

0.98

0.011

NS

Tryptophan

0.88

0.94

0.014

NS

0.90

0.97

0.017

NS

Arginine

0.89

0.95

0.008

0.09

0.93

0.98

0.008

NS

Isoleucine

0.88

0.94

0.011

NS

0.92

0.98

0.011

NS

Leucine

0.89

0.95

0.009

0.06

0.94

0.98

0.009

NS

Valine

0.87

0.93

0.011

NS

0.93

0.98

0.010

NS

Histidine

0.89

0.93

0.007

NS

0.95

0.97

0.007

NS

Phenylalanine

0.87

0.94

0.009

0.09

0.92

0.97

0.009

NS

Glycine

0.81

0.88

0.015

NS

0.93

Serine

0.80

0.89

0.018

NS

0.91

0.97

0.017

NS

Alanine

0.85

0.91

0.014

NS

0.90

0.94

0.014

NS

Aspartic acid

0.86

0.91

0.010

NS

0.91

0.94

0.005

0.09

Glutamic acid

0.87

0.93

0.014

NS

0.93

0.95

0.013

NS

Total

0.85

0.92

0.010

0.09

0.94

0.96

0.011

NS

CP(№6.25)3

0.81

0.89

0.013

NS

0.89

0.94

0.012

NS

NS — Non Significant ; 1- Standard Error of Mean ; 2 — Probability ; CP — Crude Protein ;N — Nitrogen 3 — The values (protein digestibility) were not corrected for uric acid.

Table 2. Apparent and true digestibility (coefficients) of artemia meal determined by sampling either excreta or ileum contents

5. Conclusion

Results of this studies revealed that artemia meal can be used as a feedstuff in poultry and other farm animal’s diets because it has high level of protein and high protein digestibility. Compared with other animal proteins, artemia does not contain any feather, bone, hair or gastrointestinal tract components. In addition, in artemia production there is no requirement for high pressure and high temperature treatments which can influence protein quality. Artificial culture of artemia is easy and is possible everywhere.

Author details

A. Zarei[5]

Department of Animal Science, College of Agriculture and Natural Resources, Islamic Azad

University — Karaj Branch, Karaj, Iran

Results and discussions

1.1. Analysis of energy indices in varieties rice production under traditional and semi-mechanized system condition

In "Figure 4" (traditional system) and "Figure 5" (semi-mechanized system), seven groups of reserves of production of studied figures according to percentage of total energy of reserve is observed. Results showed that highest energy consumption in all varieties was related to chemical fertilizer. The amount of further use of fertilizer and also raising of equivalent amounts of energy in this reserve showed this subject. The energy of water reserve, fuel, poison, machines, seed and human labor are in next grades.

Rice plants require fertilizer during vegetative stage to promote growth and tillering, which in turn, determines potential number of panicles. Fertilizer contributes to spikelet production during early panicle formation stage, and contributes to sink size during the late panicle formation stage. Fertilizer also plays a role in grain filling, improving the photosynthetic capacity, and promoting carbohydrate accumulation in culms and leaf sheaths [1].

Results of "Tables 5 and 6" showed that breed varieties (Khazar, Hybrid and Gohar) because of suitable genetic specifications have higher operation in compared with local varieties (Hashemi and Alikazemi), highest paddy yield (9500 kg/ha), straw yield (12969 kg/ha), husk yield (2375 kg/ha) and biomass yield (24844 kg/ha) of semi-mechanized system and paddy yield (8360 Kg/ha), straw yield (11413 kg/ha), husk yield (2090 kg/ha) and biomass yield (21863 kg/ha) of traditional system observed in Gohar rice.

Breed varieties because of accepting higher fertilizer have further input energy than local varieties under two farming systems condition "Tables 5 and 6". Traditional system because of consumption higher fertilizer and seed has further input energy than semi-mechanized system "Tables 3 and 4".

image083

Figure 4. The share (%) production inputs for varieties rice under traditional system condition

image084

Figure 5. The share (%) production inputs for varieties rice under semi-mechanized system condition

Semi-mechanized system because of producing higher paddy yield, straw yield, husk yield and biomass yield than traditional system of has higher output energy "Tables 5 and 6". Breed varieties (Khazar, Hybrid and Gohar) because of suitable genetic specifications have

Item

Unit

Hashemi

Alikazemi

Khazar

Hybrid

Gohar

Paddy

Yield

kg/ha

3520

4180

4840

6600

8360

Input energy

MJ/ha

32843

32843

36922

40523

40523

Output energy

MJ/ha

51744

61446

71148

97020

122892

Energy ratio

1.58

1.87

1.93

2.39

3.03

Energy intensity

MJ/kg

9.33

7.86

7.63

6.14

4.85

Energy productivity

kg/MJ

0.11

0.13

0.13

0.16

0.21

Net energy gain

MJ/ha

18901

28603

34226

56497

82369

Water and energy productivity

g/m3.MJ

0.011

0.012

0.013

0.016

0.020

Straw

Yield

kg/ha

4437

5706

6607

9010

11413

Input energy

MJ/ha

32843

32843

36922

40523

40523

Output energy

MJ/ha

55463

71325

82588

112625

142663

Energy ratio

1.69

2.17

2.24

2.78

3.52

Energy intensity

MJ/kg

7.40

5.76

5.59

4.50

3.55

Energy productivity

kg/MJ

0.14

0.17

0.18

0.22

0.28

Net energy gain

MJ/ha

22620

38482

45666

72102

102140

Water and energy productivity

g/m3.MJ

0.013

0.017

0.018

0.022

0.028

Husk

Yield

kg/ha

813

1045

1210

1650

2090

Input energy

MJ/ha

32843

32843

36922

40523

40523

Output energy

MJ/ha

11219

14421

16698

22770

28842

Energy ratio

0.34

0.44

0.45

0.56

0.71

Energy intensity

MJ/kg

40.40

31.43

30.51

24.56

19.39

Energy productivity

kg/MJ

0.02

0.03

0.03

0.04

0.05

Net energy gain

MJ/ha

-21624

-18422

-20224

-17753

-11681

Water and energy productivity

g/m3.MJ

0.002

0.003

0.003

0.004

0.005

Biomass

Yield

kg/ha

8770

10931

12657

17260

21863

Input energy

MJ/ha

32843

32843

36922

40523

40523

Output energy

MJ/ha

119857

149390

172979

235887

298794

Energy ratio

3.65

4.55

4.69

5.82

7.37

Energy intensity

MJ/kg

3.74

3.00

2.92

2.35

1.85

Energy productivity

kg/MJ

0.27

0.33

0.34

0.43

0.54

Net energy gain

MJ/ha

87013

116547

136057

195364

258271

Water and energy productivity

g/m3.MJ

0.027

0.033

0.034

0.043

0.054

higher output energy in compared with local varieties (Hashemi and Alikazemi). Highest output energy with averages 139650, 162113, 32775 and 339535 MJ/ha of semi-mechanized system and with averages 122892, 142663, 28842 and 298794 MJ/ha of traditional system observed in Gohar rice "Tables 5 and 6".

Energy ratio in two farming systems and five varieties showed that positive output of energy production and being further of energy output of semi-mechanized system than traditional system and breed varieties than local varieties (tables 5 and 6).

Results of energy intensity under two farming systems condition "Tables 5 and 6" showed that local varieties require of further input from production of paddy yield, straw yield, husk yield and biomass yield than breed varieties.

Results of energy productivity under two farming systems condition "Tables 5 and 6" were showed that in breed varieties lieu of imported energy consumption have higher energy productions than local varieties.

Net energy gain in two farming systems and five varieties showed that highest net energy gain of semi-mechanized system than traditional system and breed varieties than local varieties. Highest net energy gain with averages 97865, 120328, -9010 and 297750 MJ/ha of semi-mechanized system and with averages 82369, 102140, -11681 and 258271 MJ/ha of traditional system observed in Gohar rice "Tables 5 and 6"

Direct, indirect energy, renewable, non-renewable, % direct, % indirect energy, % renewable and % non-renewable in two farming systems and five varieties were showed "Tables 7". In two farming systems and five varieties were showed that direct energy and % direct energy as compared with indirect energy and % indirect energy; renewable energy and % renewable energy as compared with nonrenewable energy and % nonrenewable energy have lower amount "Tables 7". The amount of higher consumption of machinery and diesel fuel in semi-mechanized system lead to increasing indirect energy in this system in compared with traditional system. The amount of higher consumption of chemical fertilizer in breed varieties lead to increasing indirect energy in these varieties in compared with local varieties. Results showed that, lower amount of consumption of seed and human labor in semi-mechanized system in compared with traditional system leads to being lower of renewable energy in semi-mechanized system than traditional system "Tables 7". Lower amount of consumption of seed in breed varieties in compared with local varieties leads to being lower of renewable energy in breed varieties than local varieties. The amount of higher consumption of chemical fertilizer in breed varieties in compared with local varieties leads to increasing nonrenewable energy in these breed varieties than local varieties. The share of direct and indirect energy from total reserve of energy and share of renewable and nonrenewable energies from total reserve of energy "Tables 7" in studied farming systems and varieties were that the percentage of direct energy is lowest than percentage of indirect energy and percentage of renewable energy in producing rice is lowest than nonrenewable energies that this required to consider saving in energy consumption.

Item

Unit

Hashemi

Alikazemi

Khazar

Hybrid

Gohar

Paddy

Yield

kg/ha

4000

4750

5500

7500

9500

Input energy

MJ/ha

33935

33935

38014

41785

41785

Output energy

MJ/ha

58800

69825

80850

110250

139650

Energy ratio

1.73

2.06

2.13

2.64

3.34

Energy intensity

MJ/kg

8.48

7.14

6.91

5.57

4.40

Energy productivity

kg/MJ

0.12

0.14

0.14

0.18

0.23

Net energy gain

MJ/ha

24865

35890

42836

68465

97865

Water and energy productivity

g/m3.MJ

0.012

0.014

0.014

0.018

0.022

Straw

Yield

kg/ha

5461

6485

7508

10239

12969

Input energy

MJ/ha

33935

33935

38014

41785

41785

Output energy

MJ/ha

68263

81063

93850

127988

162113

Energy ratio

2.01

2.39

2.47

3.06

3.88

Energy intensity

MJ/kg

6.21

5.23

5.06

4.08

3.22

Energy productivity

kg/MJ

0.16

0.19

0.20

0.25

0.31

Net energy gain

MJ/ha

34327

47127

55836

86203

120328

Water and energy productivity

g/m3.MJ

0.016

0.019

0.019

0.024

0.030

Husk

Yield

kg/ha

1000

1188

1375

1875

2375

Input energy

MJ/ha

33935

33935

38014

41785

41785

Output energy

MJ/ha

13800

16394

18975

25875

32775

Energy ratio

0.41

0.48

0.50

0.62

0.78

Energy intensity

MJ/kg

33.94

28.56

27.65

22.29

17.59

Energy productivity

kg/MJ

0.03

0.04

0.04

0.04

0.06

Net energy gain

MJ/ha

-20135

-17541

-19039

-15910

-9010

Water and energy productivity

g/m3.MJ

0.003

0.003

0.004

0.004

0.006

Biomass

Yield

kg/ha

10461

12423

14383

19614

24844

Input energy

MJ/ha

33935

33935

38014

41785

41785

Output energy

MJ/ha

142967

169781

196568

268058

339535

Energy ratio

4.21

5.00

5.17

6.42

8.13

Energy intensity

MJ/kg

3.24

2.73

2.64

2.13

1.68

Energy productivity

kg/MJ

0.31

0.37

0.38

0.47

0.59

Net energy gain

MJ/ha

109032

135846

158554

226273

297750

Water and energy productivity

g/m3.MJ

0.031

0.037

0.038

0.047

0.059

Item

Hashemi

Alikazemi

Khazar

Hybrid

Gohar

Traditional system

Direct energy (MJ/ha)

17547

17547

17547

17547

17547

Direct energy (%)

53.43

53.43

47.53

43.30

43.30

Indirect energy (MJ/ha)

15296

15296

19375

22976

22976

Indirect energy (%)

46.57

46.57

52.47

56.70

56.70

Renewable energy (MJ/ha)

11915

11915

11575

10895

10895

Renewable energy (%)

36.28

36.28

31.35

26.89

26.89

Nonrenewable energy (MJ/ha)

20928

20928

25347

29628

29628

Nonrenewable energy (%)

63.72

63.72

68.65

73.11

73.11

Semi-mechanized system

Direct energy (MJ/ha)

18346

18346

18346

18346

18346

Direct energy (%)

54.06

54.06

48.26

43.91

43.91

Indirect energy (MJ/ha)

15589

15589

19667

23439

23439

Indirect energy (%)

45.94

45.94

51.74

56.09

56.09

Renewable energy (MJ/ha)

11534

11534

11194

10684

10684

Renewable energy (%)

33.99

33.99

29.45

25.57

25.57

Nonrenewable energy (MJ/ha)

22401

22401

26819

31100

31100

Nonrenewable energy (%)

66.01

66.01

70.55

74.43

74.43

Table 7. Division of the energy for varieties rice under traditional and semi-mechanized system condition

Moradi and Azarpour [23] with study of energy indices for native and breed rice varieties production in Iran were recorded the highest grain yield, input energy, output energy, energy ratio, energy productivity and Net energy gain obtained from breed varieties as compared with local varieties. Eskandari Cherati et al. [11] with study energy survey of mechanized and traditional rice production system in Mazandaran province of Iran showed that the total energy used for semi-mechanized and traditional rice production system was 67217.95 and 67356.28 MJ/ha, respectively. Based on the results, irrigation and fertilizer in both systems with 50232 and 7610.32 MJ/ha was the most input energy. Total energy output of the traditional method was 127.5 GJ/ha and that of the semi-mechanized was 132.26 GJ/ha. Parallel to the mechanization level of operations that increased, consumption of fuel and machinery energy increased similarly, but the human labor and seed energy consumption dropped. The renewable energy in the traditional and semi-mechanized systems was 3168.3 (4.70% total energy) and 2312.1 MJ/ha (3.44%), respectively. Energy ratio and energy productivity in traditional and semi-mechanized systems was 3 and 3.08, and 0.111 and 0.116 kg/MJ 116.0, respectively. Nonetheless, net energy gain and specific energy showed that energy efficiency of semi-mechanized systems was more than the traditional system. Khan et al. [16] with energy requirement and economic analysis of rice production in western part of Pakistan Energy requirement and economic analysis of rice production in western part of Pakistan revealed that energy consumption and rice yield were 5,756 kWh and 3.23 tons per hectare on Bullock Operated Farms (BOF) and 11,162 kWh and 4.12 tons per hectare on Tractor Operated Farms (TOF). Consumption of animate energy on BOF was more than TOF due to heavy use of animate energy in land preparation operation. Result also showed that energy efficiency i. e. output-input ratio on BOF (6.32) was higher than TOF (4.16). Cost of production remained lower on BOF than TOF, however, the yield and consequently crop values and net return were higher on TOF than BOF.

Khan et al. [17] with study energy requirements and economic analysis of wheat, rice and barley production in Australia revealed that chemical fertilizer consumed 47, 43 and 29 % of the total energy inputs on wheat, rice and barley growing farms, respectively. Wheat consumed 3028, rice 6699 and barley consumed 2175 kWhha-1. Similarly, wheat utilized 2852, rice 17754 and barley 856 m3ha-1. Average energy output of wheat was 27874, rice 44885, and barley obtained 17865 kWhha-1. Wheat was most energy efficient crop compared to rice and barley, whereas barley achieved the highest water productivity.

Second Generation Ethanol from Residual Biomass: Research and Perspectives in Ecuador

Enrique Javier Carvajal Barriga, Cristina Guaman-Burneo, Patricia Portero Barahona, Edgar Salas, Carolina Tufino, Bernardo Bastidas

Additional information is available at the end of the chapter http://dx. doi. org/10.5772/51951

1. Introduction

Ecuador is located between 1°N and 5°S on the west coast of South America. Although relatively small in size, mainland Ecuador can be subdivided nevertheless into three different and quite distinctive climatic regions: the Pacific coastal plain, the Andean highlands and the Amazon basin. In addition, Ecuador possesses a fourth region, namely the Galapagos Islands.

Climatically, the Pacific coastal plain is hot all year, with a rainy season between December and May. In the Andean highlands, the climate is markedly cooler, varying according to altitude. In contrast, the Amazon basin is hot, humid and wet all year round, while the Galapagos Islands are dry, with an annual average temperature of 25° C (77° F).

These characteristics provide Ecuador with a huge potential to develop second generation ethanol from industrial biomass, to replace a portion of the gasoline needed and, thus, the reduction of CO2 emissions. The climatic conditions as well as the photoperiods and rainfall along the year make this country an excellent candidate to develop second generation biofuels technology from biomass.

Tropical cultures such as bananas, oil palm, sugar cane, and others that are produced mainly in the coastal region of the country generates each year enough cellulose to produce almost all the ethanol the country needs. The current situation in terms of the use of these lignocellulosic materials is still in its very beginning and much work is to be developed to establish a market for the lignocellulosic residues.

Additionally, microbial biodiversity and its research is becoming one important issue in terms of the development of innovative technologies based on biotechnology, pointing out

© 2013 Barriga et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

the search for novel genes and metabolic abilities especially in wild yeasts studied in natural environments all around the country. Local researchers are devoted to the metabolic engineering of yeasts to improve the fermentation yields.

In this chapter we report some results from the or Sustainable Resources for Ethanol (RESETA) project, from the quantification and characterization of the most important cultures in Ecuador, its residues and characteristics, to the development of genetic engineered yeasts and the design and construction of a biorefinery at pilot scale.

The above mentioned project involves one of the most important researches the Ecuadorian Government has founded since 2008. The advances and results of this project can be taken as models for other tropical countries in the world.

Finally, we present the economic viability analysis of second generation ethanol projects in large scale in Ecuador, looking forward the industrial production of ethanol, biogas, biofertilizers and renewable chemicals in biorefineries in Ecuador.

Dry matters and organic matters

DM concentration is an important parameter to design the biogas reactor size and calculate capacity of a biogas plant such as an electrical power installation [2]. Too diluted animal slurry reduces economic viability but too high DM, for example higher than 15% DM, may cause a pumping problem. It is generally said that 10% DM is optimal.

The slurries included in this study had a wide range of DM contents (Table 2). It ranged between 34.1 (mink) to 238.6 kg-1 (calf). The highest DM was found in calf manure, since the majority was composed of straw bedding materials, but currently calf slurry is not used for biogas production in Denmark. DM concentration of all the tested samples was 9.7% of the mean value, close to the optimal DM concentration. However excluding the calf manure that is not used for biogas production, the mean DM concentration is much lower. Indeed, the DM concentration of the biogas reactor to which most of the manures tested were fed was 5.8%. As can be seen in Table 2, particularly piglet and mink manure have very low content of DM, which approximately amounts to 3-5% DM of total mass.

Slurry type

PH

DM

VS

(g kg-1)

(g kg-1)

% of DM

Piglet (n=4)

7.20(0.3)

54.3(31.0)

42.8(25.5)

77.4

Sow and piglet(n=3)

6.90(0.2)

66.5(18.9)

53.7(13.4)

81.7

Fattening pig (n=2)

7.53(0.3)

64.5(77.9)

52.9(67.5)

69.7

Sow (n=3)

7.74(0.5)

79.2(42.7)

64.2(36.8)

80.2

Dairy cow (n=3)

7.10(0.2)

94.1(12.1)

80.9(11.1)

85.9

Cattle (n=2)

7.42(0.2)

144.6(41.0)

95.6(1.8)

68.7

Calf (n=2)

NA

238.6(118.8)

218.8(108.1)

91.8

Mink (n=1)

7.28

34.1

27.0

79.2

Mean

7.31(0.3)

97.0(48.9)

79.47(37.5)

79.3

Table 2. The concentration of dry matters (DM) and organic materials (VS) of the slurry tested; given as mean values, standard errors in parentheses. n = number of samples included

Figure 3. Comparison of dry matters (DM) depending on manure type; error bars show standard deviation; S. P: sow and piglet; F. P: fattening pig.

Compared to the large variation of DM concentration within and between manure groups (See Figure 3), the VS concentration (as a percentage of DM) varies much less. Table 2 shows that VS concentration varies between 70 to 90% of DM. The VS concentration is crucial to determine organic loading rate, and determines the methane yield. The variation of VS as a percentage of fresh weight is large, since VS is the organic fraction of DM.

Combination with ammonia and carbon dioxide solution

The aim of combination is to enhance alkaline or acidic intensity of liquid hot water by ammonia or carbon dioxide for lignocelluloses fractionation.

Ammonia is an extremely important widely used bulk chemical. The polarity of Ammonia molecules and their ability to form hydrogen bonds explains to some extent the high solubility of ammonia in water. In aqueous solution, ammonia acts as a base, acquiring hydrogen ions from H2O to yield ammonium and hydroxide ions.

NH3(aq) + H2O(l) = NH4+(aq) + OH-(aq)

The production of hydroxide ions when ammonia dissolved in water gives aqueous solutions of ammonia the characteristics of alkaline properties.

Carbon dioxide can be considered as an ideal solvent for the treatment of natural products, because of the relatively low critical pressure (73.8 atm) and critical temperature (31.1 °C), it. In contrast with organic solvent, Super-critical carbon dioxide is non-toxic, non-flammable, non corrosive, cheap and readily available in large quantities with high purity [171].

Carbon dioxide dissolves in water becomes acidic due to the formation and dissociation of carbonic acid:

CO2 + H2O = H2CO3 = H+ + HCO3-

Over the temperature range 25-70 °C and pressure range 70-200 atm, the pH of solution ranged between 2.80 and 2.95, and increases with increasing temperature and decreases with increasing pressure [172]. It was shown that in the presence of water, supercritical CO2 can efficiently improve the enzymatic digestibility of lignocellulosic materials [32].

Cutback

There is much evidence that most newly-established willow plantations profit immensely from being cut back at the end of the first growing season (Figure 3).

Figure 3. After cutback willows sprout vigorously from the stumps

Not only does cutback encourage established cuttings to produce vigorous multiple shoots the following spring, it also helps reduce competition by weeds, thereby reducing the need for continued chemical weed control [38]. Furthermore, cutback facilitates entering the field at the beginning of the second growing season to fertilize and till soil between rows. Cutback is normally performed in the fall by cutting all newly-formed shoots at ground
level using conventional agricultural equipment, such as reciprocating mowers for large surfaces or a trimmer/brush-cutter for small plots.

Polyurethane

Inert materials such as polyurethane, impregnated with a suitable culture medium provided a homogeneous aerobic condition in the fermenter and impurities do not contribute to the final product. An additional advantage of using inert supports is the easy recovery of the product of interest, ease of performing balances because all nutrient concentrations in the middle of production are known, so one can study the effect of a given component of medium [60].

Recent studies have shown the superiority of polyurethane and polysulfone as immobilization support in comparison to polyacrylamide and alginate matrices. It has been reported a novel polyurathane gel bead fabrication technique for immobilizing Pseudomonas aeruginosa CSU. Preliminary studies conducted by them revealed that the P. aeruginosa CSU biomass immobilized within the polyurethane gel beads were effective in the removal of hexavalent uranium from low concentration acidic waters. Other authors have been immobilized phormidium laminosum on polysulfone and epoxy resins. They were successful in reusing the polysulfone immobilized biomass for ten consecutive biosorption/desorption cycles without apparent loss of efficiency after reconditioning it with 0.1 M NaOH. Immobilization of Citrobacter biomass in polysulfone matrix increased its metal loading capacity for lead, cadmium and zinc metals [57].

Charophytes biomass

The vast majority of papers published on charophytes worldwide, deals with their taxonomy and systematics. Comparatively, very few papers were published dealing with their biology, including citology, genetics, ecology and physiology.

Measure of biomass is one possibility to estimate the macrophyte’s capacity to photo synthetize (Wetzel 1964) and the most used. Other possibilities include population density and biovolume. According to Wetzel (2001), the submersed macrophytes biomass is low if compared to that of other plants. The importance of the charophytes living at the littoral zone of lakes is directly related to the amount of submersed biomass, spatial structure and these plants association with other submersed and emerged macrophytes.

Literature regarding charophytes biomass is not rare neither profuse worldwide and dates mostly from 1980 on, when eutrophication was recognized to be one of the most important events of the century. While not profuse, literature available consents a pretty good overview on the subject.

Continuous fermentation

Exponential growth in batch fermentation may be prolonged by adding of fresh medium to the vessel. In the continuous fermentation process, the added medium displaced an equal volume of culture from the vessel. Thus, the process of continuous fermentation non-stop and the exponential growth will proceed until the substrate is exhausted. By using proper technique, the desired products are obtained from the removed medium [13].

If medium is fed continuously to such a culture at a suitable rate, a steady state is eventually achieved i. e., the formation of new biomass by the culture is balanced by the loss of cells from the vessel. The flow medium into the vessel is related to the volume of the vessel by the term dilution rate, D, defined as:

d = f/v

Where F is the flow rate (volume units/time) and V is the volume (volume units).

The net change in cell concentration over a time period may be expressed as:

^x/dt = growth — output

dx/dt = gx-Dx

Under steady state conditions the cell concentration remains constant, thus = 0 and:

g = D

Thus, under steady state conditions, the specific growth rate is controlled by the dilution rate, which is an experimental variable. It is recalled that under batch culture conditions, an organism will grow at its maximum specific growth rate and, therefore, continuous culture may be operated only at dilution rates below the maximum specific growth rate.