Category Archives: BIOMASS — DETECTION, PRODUCTION AND USAGE

Mixed forest management

A number of methods are practiced in the Nordic countries, most commonly the shelter method (Tham, 1988; Johansson and Lundh, 1991) and the "Kronoberg" method (Anon., 1985). The descriptions in the sections below are based on a mixed stand of birch and Norway spruce, since this is the most common situation, but the same techniques can be used for other broadleaved species with Norway spruce.

When managing this type of stand it is important that the density of the broadleaved stems is not too high once the spruces have been established. According to Braathe (1988), the competition is too strong for spruces if there are more than 1200 birches ha-1 and they are >3 m tall. In that case, he postulated a 30 % decrease in the height increment of the spruce.

Near-infrared spectroscopy on agricultural harvesters and spectral reflectance of plant canopy

The use of near-infrared spectroscopy on agricultural harvesters has the advantage of not being time and resources consuming. In contrast to conventional sample-based methods, near-infrared spectroscopy on agricultural harvesters secures a good distribution of measurements within plots and covers substantially larger amounts of plot material (Welle et al., 2003). Thus, this method reduces the sampling error and therefore, provides more representative measurements of the plot material.

Spectral reflectance of plant canopy is a non-invasive phenotyping technique that enables the monitoring with high temporal resolution of several dynamic complex traits, such as biomass accumulation (Montes et al., 2007). Investigations at the individual plant level under well controlled environmental conditions showed that spectral reflectance could be used to monitor plant photosynthetic pigment composition, assess the water status and detect abiotic or biotic plant stresses (Penuelas, and Filella, 1998; Chaerle, and Van Der Straeten, 2000).

Current methods for measuring biomass production in cereal plots involves destructive sampling which is not suitable for routine use by plant breeders where large numbers of samples are to be screened. The measurement of spectral reflectance using ground-based remote sensing techniques has the potential to provide a nondestructive estimate of plant biomass production. Quick assessment of genetic variations for biomass production may become a useful tool for breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production is of tremendous importance. The potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production would be helpful to achieve higher grain yield in crops.

Effects of environments on forest species

Rubber rootstocks (Hevea spp.) in greenhouses covered with transparent low density polyethylene (LDPE), in the field protected by 50% mesh plastic screen as windbreaks and in the unprotected field (control) in Campinas-SP/Brazil, showed no differences in growth in the field with and without protection (Table 10). However, the greenhouse, compared to the control showed increased diameter (60%), height (108%), leaf area (266%) and dry weight (286%), and was the only environment that showed 60% of rootstock with a minimum diameter of 8.0 mm, suitable for grafting (Pezzopane et al., 1995).

Control

Windbreaks

Greenhouse

Diameter (mm)

5.3 A *

5.5 A

8.4 B

Height (cm)

35 A

39 A

73 B

Leaf area (cm2)

624 A

621 A

2283 B

Dry weight (g)

— row system

1.4 A

2.2 A

5.4 B

— aerial portion

5.5 A

6.4

24.9 B

— total dry weight

6.9 A

8.6 A

30.3 B

* Means followed by same uppercase letters in the rows do not differ by the Tukey test at 5%;

Adapted from Pezzopane et al. (1995)

Table 10. Mean values and results of the statistical analysis for growth measured in diameter, height, leaf area, average distance between shoots and average weight of dry matter.

With the objective to obtain information on an angelim seedling production system (Andira fraxinifolia Benth) in Sao Cristovao-SE/Brazil, Carvalho Filho et al. (2004) studied two growth environment (50% shading and full sun), substrates and containers and concluded that the seedlings should be maintained in 50% shading and then be transferred to full sun.

Effects of greenhouse and full sun were studied using the parameters of emergence, mortality, stem diameter, plant height, leaf area and dry weight of araticum seedlings (Annona crassiflora Mart.) and it was verified that the stem diameter, plant height and leaf area were greater in the greenhouse and the other variables in full sun (Cavalcante et al., 2008).

The germination of the assacuzeiro (Hura crepitans L.) under 50% shading, greenhouse constructed of polypropylene and environment in full sun was studied by Effgen et al. (2005) in Alegre-ES/Brazil, who concluded that both 50% shade and the environment in full sun provided good conditions for germination.

In canafistula seedlings (Cassia grandis L.), subjected to full sun and 50% shading under the monofilament screen in Sao Cristovao-SE/Brazil, it was observed that plant height, leaf number, stem diameter and dry weight leaf were greater under 50% shading with fast initial growth (Carvalho Filho et al., 2002).

Effects of shading levels of 0%, 30% and 50% in Lavras-MG/Brazil on growth, biomass allocation and total chlorophyll content of young plants of Maclura tinctoria (L.) D. Don ex Steud. (moreira), Senna macranthera (Collad.) Irwin et Barn. (fedegoso), Hymenaea courbaril

L. var. stilbocarpa (Hayne) Lee et Lang. (jatoba) and Acacia mangium Willd. (acacia) revealed that the highest chlorophyll levels were observed in shaded conditions for all species; the chlorophyll a/b ratio in full sun and 50% shading showed no difference between species; in full sun, the fedegoso and moreira species showed greater growth; the diameter of the stem of moreira was smaller in full sun than 50% shading; the dry matter produced by moreira was greater than that of fedegoso, except in the shading level of 30% (Almeida et al., 2005).

Carvalho Filho et al. (2003) evaluated the effect of full sun and 50% shading environments on the production of jatoba seedlings (Hymenaea courbaril L.) in em Sao Cristovao-SE/Brazil, and found that the emergence percentage was higher in full sun, recommending the production of seedlings in this environment. They also observed that for the other features there was interaction between environments, containers and substrates.

Biomass Burning in South America: Transport Patterns and Impacts

Ana Graciela Ulke1, Karla Maria Longo2 and Saulo Ribeiro de Freitas3

1Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 2Divisao de Geofisica Espacial, Instituto Nacional de Pesquisas Espaciais,

Sao Jose dos Campos, Sao Paulo 3Centro de Previsao de Tempo e Estudos Climaticos, Instituto Nacional de Pesquisas

Espaciais, Cachoeira Paulista, Sao Paulo

1Argentina

2,3Brazil

1. Introduction

The Andes Mountains barrier and the interaction with the easterly trade winds, and the flow associated to the South Atlantic Subtropical High (SASH) are responsible of a key feature of the low-level atmospheric circulation and climate: the so called South American Low Level Jet (SALLJ). The SALLJ is a wind maximum immersed in a pole-ward and moist current with a cross stream mean dimension in the mesoscale, which has been identified as an efficient dynamical mechanism to transport heat and humidity from tropical to subtropical latitudes. The SALLJEX (South American Low Level Jet Experiment) field campaign provided a unique data set for the study and better understanding of the SALLJ (Vera et al., 2006). The SALLJ feeds and controls the life cycle of the mesoscale convective systems over an area that includes the Del Plata basin, and accounts for an important fraction of the precipitation in southern South America, thus influencing the water balance in the region (Nicolini et al., 2002; Saulo et al., 2000). The SALLJ has also being pointed as an important agent to transport and mix other biogeochemical components (Paegle, 1998).

The orographic control of the Andes favouring the poleward flow causes the persistency of the SALLJ all year round, being only episodically interrupted by mid-latitude transient systems arriving in the subtropical South America (SA) (James & Anderson, 1984; Nogues- Paegle et al., 1998). While during the summer this flow has a net poleward component, in the winter it has an eastward tendency up in the mid-latitudes, with an outflow toward the South Atlantic Ocean broadly ranging from 20° S to 40° S, strongly depending on the position of the SASH. Nogues-Paegle & Mo (1997) found an intraseasonal meridional seesaw of dry and wet conditions over tropical and subtropical South America during austral summer in which the South Atlantic Convergence Zone (SACZ) and the low-level stream intensify alternatively. Over the central and north bands of SA during the winter, the climate is strongly influenced by the northward motion of the Inter-tropical Convergence Zone (ITCZ) and the westward displacement of SASH, composing a scenario of a low levels high pressure system over the continent, with light winds and most of the convection being shifted to the northern part of the Amazon and very little precipitation.

This is the climatological scenario of the SA dry season that eases the Tropical Forest and Cerrado biomes anthropogenic crackdown, followed by the biomass burning. In fact, the vegetation fire activity had been since remote times incorporated, as a supposedly acceptable practice, by the local culture to expand pasture and crop lands and even as a regular agricultural harvest tool for some types of produce, such as sugar cane. Every year during the dry season hundreds of thousands of fire spots and the produced thick regional smoke plume, which covers an area of about 4-5 millions of square kilometres, have been detected by satellite observation over SA.

As the SALLJ drives an important mass exchange from the tropical Amazon to the sub-tropics it is predictable that this low level flow could as well play an important role intercommunicating regional climate changes in the Amazonian basin to the southern South American basins. This paper examines the mass exchange between the Amazon basin and the subtropical SA patronized by the SALLJ during the dry/burning season, when the transport of heat and moist occurs associated with the transport of biomass burning smoke aerosol particles.

Possible further applications

The findings reported in this chapter have been obtained from a specific region in Japan. However, Fe is the third most abundant metal found in the soil (Spark, 1995), and Fe — oxidizing bacteria are not rare (Emerson et al., 1999; Emerson & Weiss, 2004; James & Ferris, 2004). Thus, this method can be applicable in many places, provided suitable aquatic conditions supporting the growth of Fe-oxidizing bacteria (low concentration of oxygen and circumneutral pH) are available. In addition, the immersed woody carrier can be applied directly to agricultural land in the form of a fertilizer, without P extraction procedures, which are commonly required for P recovery methods. Therefore, this method is a low-cost technique that should contribute to P resource recycling and the improvement of the aquatic environment, if adopted on a large scale.

4. Conclusions

A new method of P recovery from natural water bodies using Fe-oxidizing bacteria and woody biomass (Japanese cedar and Japanese cypress) was applied in an agricultural canal during irrigation and non-irrigation periods. The amounts of P adsorbed on the carrier during these periods were 0.332-0.350 and 0.172-0.187 g/kg, respectively, while the PO4-P concentrations of the water were 0.058 and 0.022 mg/L. Expressed these values in parts per million, the P adsorbed on the carrier was 5,700- to 8,500-fold more concentrated than the P dissolved in water. The P on the carrier was 8- to 17-fold higher than the required level for sufficient fertility to support rice production, and it was categorized in the range of high- fertility soil. Some traces of heavy metals adsorbed on the carrier were detected, but they were much lower than the regulation levels. In addition, the woody carrier can be applied directly to agricultural land without P extraction. Therefore, this method is a low-cost technique that should contribute to P resource recycling and the improvement of aquatic environment.

5. Acknowledgement

This study was partially supported by a grant from the Shimane University Priority Research Project and a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (#20380179).

Experimental work

Experimentally determining the relative impact of various significant bioprocess parameters on the daily kefir grain increase mass, during 24 h incubation in cow’s milk, based on Taguchi’s fractional factorial design approach, requires the performance of a series experiments. It was established (Harta et al., 2004; Schoevers and Britt, 2003) that culture medium temperature, 3, glucose mass concentration, yG, baker’s yeast mass concentration, y, and the rotational frequency of the stirrer, fm are the main influences bioprocess parameters. The bioprocess parameter in our case is a factor affecting daily kefir grain increase mass and its value is called the ‘level’. We examined the relative impact of the selected bioprocess parameters at four different levels, as shown in Table 1.

Bioprocess parameter

Level

1

2

3

4

A

Culture medium temperature

£(°C)

20

22

24

26

B

Baker’s yeast mass concentration

У (g/L)

0

5

10

15

C

Glucose mass concentration

yG (g/L)

0

10

20

30

D

Rotational frequency of the stirrer

fm (1/ min)

0

50

70

90

Table 1. Proposed bioprocess parameters and their levels

Experiment

Bioprocess parameter[1]

A

B

C

D

E[2]

1

1

1

1

1

1

2

2

1

2

3

4

3

1

2

2

2

2

4

4

1

4

2

3

5

1

4

4

4

4

6

2

2

1

4

3

7

4

2

3

1

4

8

4

4

1

3

2

9

4

3

2

4

1

10

3

1

3

4

2

11

2

3

4

1

2

12

3

4

2

1

3

13

1

3

3

3

3

14

2

4

3

2

1

15

3

3

1

2

4

16

3

2

4

3

1

Table 2. Design of experiments — orthogonal array L16

During the first stage of the experimental work, it is necessary to prepare the design of experiments. The DoE envisages determining the number of experiments, their performance conditions, and their sequence. Based on the assumption that the daily kefir grain increase mass would be affected by four bioprocess parameters being considered at four levels, we chose the L16 array as the most adequate OA requiring the performance of 16 experiments (Ranjit, 1990). The OA L16 is usually intended for the investigation of five bioprocess parameters at four levels; however, it may also be used in our case (four parameters at four levels) by ignoring the bioprocess parameter E. The DoE is presented in Table 2. The first column presents the experimental serial number. Each experiment was defined by the bioprocess parameters (A, B, C, D and E) marked at specific levels by numbers from 1 to 4. During the second stage of the experimental work, we implemented the proposed DoE by performing the 24 h kefir grain biomass incubations in the RC1 system. The incubation procedure was the same for all experiments. Individual experiments were implemented by means of first charging the reactor by 1 L of fresh HTP whole fat cow’s milk and adding the mass of glucose previously defined by the DoE. This fermentation medium was heated up to working temperature under the defined rotational frequency of the stirrer. After establishing the temperature steady state and dissolved glucose, we inoculated the fermentation medium with the mass of the baker’s yeast also defined by DoE and with 40 g of active kefir grains, which corresponds to initial kefir grain mass concentration, yKG = 40 g/L. After the 24 h incubation was completed, the kefir grain increase mass was determined using the gravimetric method.

Membrane fouling control and cleaning

It is generally accepted that the optimal operation of an MBR depends on understanding membrane fouling (Judd, 2007). Abatement of fouling leads to elevated energy demands and has become the main contribution to OPEX (Verrech et al., 2008). In addition, uncertainty associated with this phenomenon has led to conservative plant designs where the supplied energy is so far to be optimised.

Traditional strategies for fouling mitigation such as air sparging, physical cleaning techniques (i. e backflushing and relaxation) and chemical maintenance cleaning have been incorporated in most MBR designs as a standard operating strategy to limit fouling. Air sparging, expressed as specific aeration demand SADm, takes a typical value for full-scale facilities between 0.30 Nm3/h m2 (FS configuration) to 0.57 Nm3/h m2 (HF configuration). Relaxation and backflushing (only for HF) are commonly applied for 30-130 seconds every 10-25 min of filtration (Judd, 2010). Frequent maintenance cleanings (every 2-7 d) are also applied to maintain membrane permeability. However, these pre-set fixed values of key parameters, based on general background or the recommendations of membrane suppliers, lead to under-optimised systems and results in loss of permeate and high energy demand. Recently, several authors have proposed a feedback control system for finding optimal operating conditions. For example, Smith et al. (2006) have successfully validated a control system for backflush initiation by permeability monitoring. This system automatically adjusts the backflushing frequency as a function of the membrane fouling, which results in a reduction of up to 40% in the backflushing water required. Ferrero et al. (2011) have used a control system at semi-industrial pilot scale trials based on monitoring membrane permeability, which achieved a energy saving between 7 to 21% with respect to minimun aeration recommended by membrane suppliers.

Content of Ca, Cu, Fe, K, Mg, Mn and Zn in wheat grain after BRs treatment (field experiment)

Values of metals content in wheat grain in individual years of cultivation are given in Table 6. The changes of the metals content in spring wheat grain were observed during the field experiments. Statistically significant differences in the total content of metals between years were found in the Ca, Mg, Mn and Fe contents. In potassium content, year 2007 differed from 2005 and 2006, while no difference was found between 2005 and 2006. Likewise, zinc content in 2005 differed from years 2006 and 2007. No statistically significant difference between 2005, 2006 and 2007 was found in copper content. In 2005, no differences in the selected metals content between untreated control plants and plants treated with BRs were determined. In 2006, potassium content increased in plants treated with 24-epiBL (by 22.2%), 4151 (by 31.2%) and KR1 (by 24.5%), while zinc content decreased in variants treated with 24-epiCS (by 14.5%) and KR1 (by 12.4%) as compared to the control variant. 2007, Mg, Mn and Fe contents decreased. In comparison with untreated control plants, there was lower magnesium content (by 11%) and manganese content (at least 7.5%) in variants treated with 24-epiCS, 4154 and with KR2-KR5. Different iron content was determined in variants treated with 24-epiBL, 24-epiCS and with KR1-KR5. Weather conditions were similar in all three years. Mean air temperature was higher as compared with the long-term normal value(Table 7) in whole three-year period. Mean precipitation in 2005 and 2006 was lower as

Variety

Year

Calcium

Magnesium

Potassium

Zinc

Copper

Manganese

Iron

untreated plants

2005

190.4

1337

3073

34.2

4.87

38.1

43.2

24-epiBL

187.3

1350

3089

36.6

4.93

37.9

44.0

24-epiCS

192.8

1353

3382

35.4

4.77

38.0

44.8

4154

190.8

1334

3330

37.8

4.77

36.9

44.6

KR1

191.5

1379

3097

37.4

4.82

37.5

45.8

KR2

188.4

1338

3062

34.9

4.80

38.2

46.0

KR3

186.7

1311

3146

35.2

4.77

36.8

44.3

KR4

189.6

1335

3445

35.7

4.90

38.4

46.4*

KR5

187.1

1351

3394

34.9

5.06

37.3

44.9

untreated plants

2006

304.5

1407

2591

37.3

4.76

44.6

46.1

24-epiBL

282.0

1439

3168*

33.4

4.77

46.4

44.8

24-epiCS

291.4

1428

3106

31.8*

4.91

46.2

47.2

4154

312.9

1456

3399*

33.5

4.92

45.2

47.2

KR1

287.7

1420

3226*

32.6*

4.75

43.5

46.1

KR2

301.3

1459

3174

35.2

4.82

44.2

47.8

KR3

294.3

1450

3111

35.2

4.70

42.4

48.4

KR4

315.1

1468

3117

33.2

4.84

46.7

47.7

KR5

306.7

1421

2898

34.4

4.78

45.7

48.1

untreated plants

2007

315.3

1262

3718

34.8

4.92

35.2

57.7

24-epiBL

313.9

1178

3533

34.4

4.83

34.0

49.4*

24-epiCS

320.5

1112*

3462

34.8

5.00

32.5*

49.6*

4154

327.7

1056*

3341

32.5*

4.77

32.3*

59.0

KR1

310.8

1145

3393

33.9

4.62

34.1

48.7*

KR2

314.7

976*

3314

33.1

4.80

29.3*

52.9*

KR3

318.2

1015*

3334

34.2

4.92

30.7*

65.7*

KR4

319.5

977*

3295

33.3

4.77

30.5*

48.6*

KR5

307.4

996*

3584

33.4

5.00

30.2*

48.5*

Table 6. Content of Ca, Cu, Fe, K, Mg, Mn and Zn (mg kg-1 DM) in spring wheat grain; *statistically significant difference (at the level of significance p < 0.05) between treated and untreated plants

compared with the long-term normal value, while close to long-term level in 2007. The results achieved in three-year period 2005-2007 indicate a possible effect of the year on metal content of grain affected probably by precipitation. In 2007, with usual precipitation level, contents of Fe, K, Mg and Mn were decreased. In 2005 and 2006 with below average precipitation, total content of metals were comparable or higher than content of metals in untreated control plants grain. Nevertheless, such hypothesis needs to be tested in further experiments.

unit

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Temperature

°C

-2.1

-0.8

3.4

8.2

13.4

16.3

18.2

17.5

14.0

8.6

3.2

-0.5

Precipitation

mm

28

27

31

46

65

74

74

72

49

41

34

34

Table 7. Long-term normal of mean air temperature and mean precipitation of cultivation area (50°2’0"N, 14°36’54"E)

Variety

Year

Bulk density (mass per hectolitre)

Falling

number

Protein

Gluten

Sedimentation index (Zeleny test)

kg hL-1

sec

%

%

mL

untreated plants

2005

79.3

153.8

13.8

34.0

61.0

24-epiBL

79.4

138.8

13.9

34.4

58.3

24-epiCS

79.4

145.3

13.9

34.4

61.0

4154

79.6

146.7

13.8

34.2

58.8

KR1

79.3

156.3

13.9

34.4

61.8

KR2

79.4

151.3

14.0

34.6

58.3

KR3

79.5

160.8

13.7

33.9

57.3

KR4

79.4

153.5

13.5

33.2

58.0

KR5

79.4

152.5

13.6

33.5

55.5

untreated plants

2006

80.1

346.5

12.9

29.9

46.5

24-epiBL

79.9

335.8

12.2

28.1

42.8

24-epiCS

79.9

344.8

12.6

28.7

43.0

4154

80.1

346.8

12.9

29.4

45.5

KR1

80.2

350.3

12.6

28.7

42.5

KR2

80.2

348.8

12.8

29.1

45.8

KR3

79.9

353.8

12.8

29.5

46.3

KR4

79.9

344.0

12.5

28.7

43.8

KR5

80.0

332.5

12.9

30.6

46.3

untreated plants

2007

80.4

274.3

15.6

44.0

68.5

24-epiBL

80.6

290.5

15.5

44.1

70.5

24-epiCS

80.7

275.8

15.5

44.1

68.8

4154

80.5

273.0

15.4

43.4

68.8

KR1

80.6

282.8

15.3

44.4

69.0

KR2

80.3

274.3

15.3

43.7

68.8

KR3

80.5

286.0

15.3

43.5

68.8

KR4

80.6

269.0

15.4

43.6

69.3

KR5

80.6

269.0

15.3

43.8

68.3

Table 8. Quality parameters of grain after spring wheat treatment with brassinosteroids

Variety

Year

Yield (corrected on moisture 14 %)

1000 kernels weight

t ha-1

g

untreated plants

2005

6.54

53.24

24-epiBL

6.09*

56.99*

24-epiCS

6.19

55.77*

4154

6.36

56.61*

KR1

6.20

54.99*

KR2

6.12

54.77*

KR3

6.41

54.91*

KR4

6.37

55.59*

KR5

6.33

55.38*

untreated plants

2006

7.10

45.04

24-epiBL

6.66

45.10

24-epiCS

7.12

45.10

4154

7.19

44.46

KR1

7.04

45.22

KR2

7.12

44.62

KR3

7.13

44.17

KR4

6.86

44.62

KR5

7.09

44.38

untreated plants

2007

4.57

45.60

24-epiBL

4.32

44.71

24-epiCS

4.60

45.74

4154

4.53

45.44

KR1

4.53

45.05

KR2

4.52

45.10

KR3

4.45

45.33

KR4

4.48

46.00

KR5

4.65

45.87

Table 9. Yield of grain and 1000 kernels weight after spring wheat treatment with brassinosteroids; *statistically significant difference (at the level of significance p < 0.05) between treated and untreated plants

Arsenic

The element arsenic exists in three allotropes: grey arsenic, density 5.73 g/ mL; yellow arsenic, density 1.93 g/ mL; and non stable black amorphous arsenic, density 4.73 g/mL. Arsenic (atomic weight 74.92) shows metallic as well as non metallic properties. In its inorganic compound it presents different oxidation states: -3, 0, +3, +5. It is released into the air by volcanoes and is a natural contaminant of some deep-water wells. Arsenic is used to preserve wood, as a pesticide, to produce glass, in copper and other metal manufacturing, in the electronics industry and in medicine.

Occupational exposure to arsenic is common in the smelting industry (in which arsenic is a by-product) and in the microelectronics industry. Low-level arsenic exposure takes place in the general population through the use of inorganic arsenic compounds in common products such as wood preservatives, pesticides, herbicides, fungicides, and paints; through the consumption of foods treated with arsenic-containing pesticides; and through the burning of fossil fuels in which arsenic is a contaminant. The toxicity depends on its valence oxidation state and on its form inorganic or organic. In general, inorganic arsenic is more toxic than organic arsenic, and trivalent arsenite is more toxic than pentavalent and zero- valent arsenic. Arsenic, particularly in its trivalent form, inhibits critical sulphydryl — containing enzymes. In the pentavalent form, the competitive substitution of arsenic for phosphate can lead to rapid hydrolysis of the high-energy bonds in compounds such as ATP. The normal intake of arsenic by adults primarily occurs through ingestion and averages around 50 gg/ d. After absorption, inorganic arsenic accumulates in the liver, spleen, kidneys, lungs, and gastrointestinal tract. It is then rapidly cleared from these sites but leaves a residue in keratin-rich tissues such as skin, hair, and nails.

Guide line value for drinking water is 0.01 mg/L. It is a provisional value, as there is evidence of a hazard, but the available information on heath effects is limited (WHO, 2008).

By-products of sorghum processing

The by-product of sorghum ethanol production is distillers’ grains. Table 9 presents the available nutritional information for wet and dry sorghum distillers’ grains, and dry grains plus solubles. Distiller’s dried grains with solubles contain all fermentation residues, including yeast, remaining after ethanol is removed by distillation (Shurson, 2009).

Wet

distillers’

Dry

distillers’

Dry distillers’ + solubles

DM. °o1

23.5-35.3

91.4

91.4

(% DM basis)

Crude Protein

31.2-31.6

32.9

31.4

Ash

2.5

Total fat

11.3-13.3

13.0

11.8

ADF 2

28.5

28.4

NDF 3

41.3-15.4

45.8

51.1

NSC4

9.2

3.3

Starch

10.2

7.4

1 Dry matter; 2 Acid detergent fibre ; 3 Neutral detergent fibre ; 4Non-structural carbohydrate Table 9. Nutrient composition of sorghum distillers’ grains (Quotation from OECD, 2010).

2. Conclusion

It is clear that biomass production for biofuel from sweet sorghum is the best choice to be implement under hot and dry climatic conditions regarding both economic and environmental considerations. Because, sweet sorghum has higher tolerance to drought (Tesso et al., 2005), water logging, and salt (Almodares et al., 2008a, 2008b), alkali, and aluminum soils; It may be harvested 3-4 month after planting and planted 1-2 times a year (in tropical areas); Its energy output/fossil energy input is higher than sugarcane, sugar beet, corn, wheat and etc… specially in temperate areas; It is more water use efficient (1/3 of water used by sugarcane at equal sugar production); Its production can be completely mechanized and Its bagasse has higher nutritional value than the bagasse from sugarcane, when used for animal feeding. Also, by implementing agricultural practices such as adequate water and fertilizers, suitable cultivars or hybrids, crop rotation, pest management and etc. can increase productivity with focus on biofuel production from its biomass (Reddy et al., 2005). In addition, sweet sorghum has high amount of sucrose (Almodares and Sepahi, 1996) and invert sugar (Almodares et al., 2008c) which are easily converted to ethanol (Prasad et al., 2007). Therefore, it seems that sweet sorghum biomass is the most suitable raw material for biofuel production in arid regions of the world. This awareness should push government of the countries with such climatic conditions to promote the development of projects for fuel ethanol production from sweet sorghum biomass.