tsae journal vol.21 - 1

Thai Society of Agricultural Engineering Journal Vol. 21 No. 1 (2015)

Journal of the Thai Society of Agricultural Engineering

21 1 2558 (Volume 21 No. 1 January June 2015) ISSN 1685-408X

:

: 5 5 10900 0 2940 6183 0 2940 6185 www.tsae.asia

. .

. . . . . . . . .

. . . . .

.

. . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . .

. . University of California, Davis Pictiaw Chen, Ph.D., Professor Emeritus David C. Slaughter, Ph.D., Professor University of Tsukuba Masayuki Koike, D.Agr., Professor Emeritus Tomohiro Takigawa, Ph.D., Professor Mie University Nobutaka Ito, D.Agr., Professor Emeritus Kansas State University Dirk E. Maier, Ph.D., Professor Purdue University Klein E. Ililiji, Ph.D., Associate Professor

.. 2556 2557

. . . . . . . . . .

Prof. Dr. Vilas M Salokhe Prof. Dr. Gajendra Singh Prof. Dr. Chin Chen Hsieh .

. . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . .

. . . . .

. .

1.

1.1

1.2 1)

2)

3)

4)

5)

6)

7)

1.3 3 (Research paper)

(Research note) (Review paper)

1.4 10 5 10

1.5 300

1.6

2 (Corresponding author)

2. * *

2.1 (Template)

(Template) (Manuscript example) (Styles) (www.tsae.asia)

2.2 A4 Mirror margins ()

2.0 cm, 1.5 cm 2.5 cm TH SarabunPSK

2.3

()

2.4 16 pt (Thai distributed)

14 pt

( Superscript)

12 pt ()

2.5

1 14 pt (Indentation) 1.0 cm ( 250 )

2.6 3-5 14 pt

2.7 2 8.25 cm 0.5 cm

1 ( 1.1 , 1.1.1 , ...) 0.5 cm 14 pt 0.5 cm Hanging

(Introduction)

(Materials and methods)

(List)

(Results and discussion)

(Conclusions)

(Acknowledgement)

(References) - (Name-year system) () (2545) ... (, 2550) (2555) ... () Mettam (1994) ... 3 (2551) et al. Perez-Mendoza et al. (1999)

, , a, b, c

2.8

, , . 2552. . 15(1), 2630.

Perez-Mendoza, J., Hagstrum, D.W., Dover, B.A., Hopkins, T.L., Baker, J.E. 1999 . Flight response, body weight, and lipid content of Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) as influenced by strain, season and phenotype. Journal of Stored Products Research 38, 183195.

(Edited book)

Mettam, G.R., Adams, L.B. 1994 . How to prepare an electronic version of your article. In: Jones, B.S., Smith, R.Z. (Eds.), Introduction to the Electronic Age (pp. 281304). New York: E-Publishing Inc.

, . 2550. . : . Strunk, W., Jr., White, E.B. 1979. The Elements of Style. (3rd ed.). Brooklyn, New York: Macmillan.

, , . 2553. . 11 2553 , 299304. : . 67 2553, , .

Winks, R.G., Hyne, E.A. 1994 . Measurement of resistance to grain fumigants with particular reference to phosphine. In: Highley, E., Wright, E.J., Banks, H.J., Champ, B.R. (Eds). Proceedings of the Sixth International Working Conference on Stored-product Protection, 244249. Oxford, UK: CAB International. 1723 April 1994, Canberra, Australia.

. 2546. . . : , .

Chayaprasert, W. 2007 . Development of CFD models and an automatic monitoring and decision support system for precision structural fumigation. PhD dissertation. West Lafayette, Indiana: Department of Agricultural and Biological Engineering, Purdue University.

. 2550. . : http://203.155.220.230/stat search-/frame.asp. 14 2550.

United Nations Environment Programme. 2000. The Montreal protocol on substances that deplete the ozone layer. Available at: http://ozone.unep.org/pdfs/Montreal-Protocol2000.pdf. Accessed on 7 August 2008.

2.9 International Systems (SI)

15 kg 15 15 . m s-1 m/s

2.10 Equation

editor (Nomenclature)

2.11

300 dpi - -

Figure 1 Relationship between Table 1 Results of TH SarabunPSK 14 pt ... Figure 1 Table 1 ...

2.12 (Line number) TH SarabunPSK 8 pt

1 mm 1 1

3.

online submission http://tsae.asia/journals/index.php/tsaej2014/ [email protected] (Hard copy) 3 3

. 1 6 . . . . 73140 ()

1 Comparing the Efficiency of Two Carrier Types on Drum Drying of Tamarind Juice Nartchanok Prangpru, Tawarat Treeamnuk, Kaittisak Jaito, Benjawan Vanmontree, Krawee Treeamnuk

7 , ,

15 ,

24 , ,

30 .. 2551 2555

37 Jaturong Langkapin, Sunan Parnsakhorn, Purin Akarakulthon

45 MIKE21 ,

21 1 (2558), 1-6

1

Thai Society of Agricultural Engineering Journal Research Paper Volume 21 No. 1 (2015) 1-6

ISSN 1685-408X Available online at www.tsae.asia

Comparing the Efficiency of Two Carrier Types on Drum Drying of Tamarind Juice Nartchanok Prangpru1*, Tawarat Treeamnuk1, Kaittisak Jaito1, Benjawan Vanmontree1, Krawee Treeamnuk2 1Department of Agricultural Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand, 30000 2Department of Mechanical Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand, 30000 *Corresponding author: Tel: +66-44-224-225, Fax: +66-44-224-610, E-mail: [email protected]

Abstract

The main purpose of this work was to study the effect of carrier agents on the drying capability and the qualities of tamarind powder produced by a drum dryer. Two popular carrier agents, namely maltodextrin and modified starch, were applied to tamarind juice at juice-to-carrier-agent ratios of 1:0.3, 1:0.4, 1:0.5, 1:0.6, 1:0.7 and 1:0.8 (w/w). A double drum dryer was employed in this work at a drying temperature of 140C, drum rotational speed of 0.50 rpm and gap between drums of 0.15 mm. The efficiency of carrier agent was evaluated by the capability of drying and product qualities such as product recovery, bulk density, total solid, moisture content and color difference. The results of the experiment indicated that the ratio of the carrier agent affected the drying capability. The tamarind powder were easily removed from the drums by doctor blades without sticking at the lowest ratios of moltodextrin and modified starch of 1:0.6 and 1:0.4, respectively. Furthermore, when considering the qualities of tamarind powder, as a carrier modified starch led to better tamarind powder qualities than maltodextrin

Keywords: Tamarind, Carrier agents, Drum drier

1 Introduction

Tamarind is one of the most important fruits of Thailand with the total production over 100,000 tons a year. Tamarind juice is an essential ingredient that provides the inimitable sour taste in many kinds of Thai food (Jittanit et al., 2011). However, the use of the fresh pulp still has many disadvantages due to its short shelf-life of about 6-8 months and, high cost of transportation. In addition, preparation for cooking is rather difficult. To overcome the aforementioned problems, a method of transforming tamarind paste into powder by a drum dryer is proposed.

A drum dryer consists of two hollow cylinders rotating in opposite directions. The drums are heated by high temperature of saturated steam inside. A thin film of solution is coated on the outside surface of a heated drum and subsequent removal of the film of dry solids by applying the doctor blade. Drum drying is commonly used in production of low moisture baby foods and fruit powder. It is a technique widely used in the food industry

to produce food powder particularly for heat sensitive products where short time high temperature drying is permissible (Nastaj, 2000). Additionally, Sunee (2008) stated that production of azuki bean powder using drum drying is advantageous because it can save time in product preparation, save storage space and convenie-nce to the users. Drum drying is a low cost and easy production process (Russamon, 1999).

Fruit juices are very difficult dried with a drum dryer because of the presence of low molecular weight sugars and acids, which have a low glass transition temperature, and high hygroscopicity (Jaya and Das, 2004). While under drum drying temperatures, they tend to stick to the surface of the drum and cannot be removed from the drums by doctor blades (Bhandari and Howes, 2005). Some possible consequences are related to impaired product stability, decreased yields (because of stickiness on the surface of the drum), and even operating problems to the dryer (Bhandari et al., 1997). Such problems can be alleviated by adding carrier agents,

Thai Society of Agricultural Engineering Journal Vol. 21 No. 1 (2015), 1-6

2

which are high molecular weight, such as maltodextrin (MD), which decrease powder hygroscopicity and increasing the glass transition temperature (Silva et al., 2006). Additionally, Carneiro et al. (2013) reported MD is a relatively low cost and low viscosity at high solids concentrations. However, the biggest problem of this carrier is its low emulsifying capacity. Therefore, it is common to use MD in combination with other carriers, such as gum arabic (Fernandes et al., 2008) or modied starch (Bule et al., 2010) in order to obtain an effective juice powder by drum drying. Oliveira et al. (2009) pointed out that gum arabic has a glass transition temperature higher than MD and is very efficient in flavour retention, which suggests that it is probably reducing powder hygroscopicity more effectively than MD, but gum arabic is expensive. So, this motivated researchers to look for materials to replace it. Modified starch (MS), a carbohydrate that changes the native starchs property in accordance with a certain application. Such as modified starch can be used to replace other substances, like emulsifiers. Non-polar modified starch can act as an emulsifier, offering stable emulsions.

The purpose of the present study was to evaluate the effects of MD and MS as carrier agents on the capability of drying and the quality of drum dried tamarind powder.

2 Materials and Methods

2.1 Materials Tamarind flesh (Tamarindus indica L.) was

purchased from a local market in Nakhon Ratchasima, Thailand. MD with dextrose equivalent of 10-12, pH of 4.5-6.5 and moisture content of 5.0-6.0% was purchased from Nutrition SC CO., LTD., Nakhonpathom, Thailand. MS with pH of 4.0-6.0 and moisture content of 4.0-8.0% was purchased from Questex CO., LTD., Sumutprakarn, Thailand. 2.2 Tamarind Juice Preparation

Tamarind flesh was deseeded and mixed with hot water at 80C at a ratio of 1:5 (w/w). The mixture was squeezed into tamarind paste. Then, the juice was screened with the two-layer of cheesecloth to discard the residues. The total soluble solid of juice was determined and adjusted to be 12oBrix. After that, either MD or MS was added as a carrier agent to the juice at

juice-to-carrier-agent ratios of 1:0.3, 1:0.4, 1:0.5, 1:0.6, 1:0.7 and 1:0.8 (w/w). The initial ratio of 1:0.3 was used by Kanniga (2006). Each the sample feed 500 ml. 2.3 Drum Dryer Setting

A double drum dryer with nip feed was employed in this work shown in Figure 1. The dryer, which consists of five main parts. The Control box was a box to control the drum outside surface temperature and drum speed of the rollers were 140C and 0.50 rpm, respectively. Cylindrical hollow rollers made of stainless steel had a diameter of 15 cm, a length of 20 cm and a gap between drums of 0.15 mm. Doctor blades made of stainless steel were used for scraping food through the process of drying out. An electric motor of 1 HP was used to drive the machine. Finally, the structure that supports the weight of the whole machine.

Figure 1 A drawing of double drum dryer.

2.4 Drying Experiments The drying experiments were carried out using the

randomized complete block design of two carrier agent (MD and MS), and six ratios of tamarind juice and carrier agent (1:0.3, 1:0.4, 1:0.5, 1:0.6, 1:0.7 and 1:0.8 w/w). At the end of drying, the tamarind powder was collected, weighed and kept in the sealed container for determination of the qualities. The procedure for the raw material preparation until the drying of tamarind is shown in Figure 2.

21 1 (2558), 1-6

3

Figure 2 Schematic diagram of the experimental

procedure.

2.5 Quality Determination The qualities of tamarind samples, which included

tamarind juice, in terms of total solid, moisture content, total acidity and color, were measured. For the tamarind powder, product recovery, bulk density, total solid, moisture content and color were measured. Apart from that, for the reconstituted tamarind powder were subjected to the determination of solubility, total acidity and color. Then all of qualities will be measured in 3 replicates.

Product recovery was determined using the ratio in the weights of dry solid of tamarind juice and powder (Kanniga, 2006). The product recovery was calculated as:

100ab

MProduct recovery xM

(1)

where Ma and Mb are the weights (g) of dry solid of tamarind powder leaving the dryer and tamarind juice being fed into the dryer, respectively.

Bulk density of tamarind powder was determined using tamarind powder into the cylinder of known volume, then placing a cylinder with a tamarind powder and dropped by gravity at a distance of 0.1 m from the cylinder. After that, dropped tamarind powder until overflowing cylinder and then swept to the mouth of the cylinder smooth cylinder surface (Pao., 2005). The bulk density was calculated by using the equation as follows:

mBulk density

v (2)

where m is the mass of tamarind powder (kg) and v is the volume of the cylinder (m3).

Total acidity of the tamarind was determined using the tamarind 50 ml into a 250 ml erlenmeyer flask and add 200 ml of distilled water, then 3-5 drop of 1% phenolpthalein were added as an indicator. After that, the mixture was titrated with a standard solution 0.1 N of NaOH until at the endpoint. The solution was indicated by color change to light pink (Pao., 2005). The total acidity was calculated as:

1001000

wV x N x M xTotal acidityU

(3)

where V is the volume of NaOH which was used in the titration until at endpoint (ml), N is the normality of NaOH, Mw is the molecular weight of tartaric acid = 150, U is the weight of the sample used in the titration (g).

Total solid and moisture content of tamarind was determined using the convection oven method (AOAC, 1984). Samples were dried in an oven at 105C for 24 h. The total solid content and moisture content of tamarind in wet basis were calculated by using the equation as follows: Samples were dried in an oven at 105C for 24 h. The total solid content and moisture content of tamarind in wet basis were calculated by using the equation as follows:

2 3

2 1

1 100W W

Total solid xW W

(4)

2 3

2 1

100W W

Moisture content xW W

(5)

where W1 is the initial weight of moisture can (g), W2 is the weight of moisture can and tamarind before drying (g), and W3 is the weight of moisture can and tamarind after drying (g).

The color of the tamarind juice was determined using Hunter Lab colorimeter in terms of the total color change between the juice and the reconstituted powder. The color was expressed in terms of L (lightness), a (redness) and b (yellowness) (Shittu and Lawal, 2007). The change in the color was calculated by using the following equation:

2 2 20 0 0( ) ( ) ( )c p p pE L L a a b b (6)

where L0, a0 and b0 are the color values of the tamarind juice, and Lp, ap and bp are the color values of the reconstituted powder.

Solubility of tamarind powder was determined by using about 1 g of each sample which were suspended


4

in 10 ml of water at 30C in a centrifuge tube. The suspension was stirred intermittently for 30 min before it was centrifuged at 3,000 rpm for 10 min. After that, the supernatant was poured into a moisture can and dried in an oven at 105C for 24 h (Jaya and Das, 2004). The dry basis solubility of tamarind powder was calculated by using the following equation:

100sp

MSolubility xM

(7)

where Ms is the weight of dry solid of supernatant (g), and Mp is the weight of tamarind powder (g). 2.6 Statistical Analysis

Each tamarind powder quality parameter reflected the mean of three replicates. Statistical analyses were performed using SPSS. The statistical significance was determined by analysis of variance (ANOVA). The least significant difference of p

21 1 (2558), 1-6

5

was diluted by the carrier prior to drying. Apart from that, MD is a carrier with had lower of total acidity than MS.

Figure 5 The total acidity of reconstituted tamarind

powder.

The effect of the different carriers used to produce the tamarind powder on moisture content is shown in Figure 6. Moisture content is an important powder property, which is related to the drying efficiency. The moisture content of tamarind powder varied from 2.50% to 4.31%, which was close to the moisture content of spray dried blackberry (Ferrari et al., 2012). Increasing the ratio of the carrier resulted in a decrease in the moisture content due to high solid ratio. However, the moisture content of MD was more than MS. This behavior was probably due to the differences between the chemical structures of the carriers (Yousefi et al., 2011).

Figure 6 The moisture content of tamarind powder.

The total color change of reconstituted tamarind powder increased as the ratio of MD increased from 30% to 50%, then the total color change are not different (Figure 7). Similarly, the ratio of MS from 40% to 80%, because the dried product could be removed from the drums by doctor blades.

The effect of the different carriers used to produce the tamarind powder on solubility is shown in Figure 8. No significant differences was found in powder solubility

for MD and MS. All of the powder samples, except the one produced from MD at the 1:0.3 ratio, had a high degree of solubility, reaching values above 80% (Table 1).

Figure 7 The total color change of tamarind between

the fresh juice and the reconstituted powder.

Figure 8 The solubility of tamarind powder.

3.4 Statistical Analysis Base on the statistic analysis (Table 1), while all

other quality parameters of different samples were significantly different (p


6

4 Conclusions

The effect of the ratio of carriers on the drying behavior and quality were different for different parameters. The substance takes to make tamarind powder can be removed from the drums by doctor blades and has product recovery of more than 80%

when 60% MD and 40% MS was used as carrier. And it can be concluded that using MS as carrier leads to better quality of tamarind powder (such as bulk density, total acidity and moisture content) than using MD as the carrier. However, with the high cost of MS, using these carriers in combination would be preferred.

Table 1 Average standard deviation for the quality of tamarind powder. No. Carrier (%) PR (%) BD (kg/m3) TA (%) MC (%) cE SO (%)

1 MD = 30 71.980.24a 1024.499.79a 12.900.15a 4.310.22a 10.401.51a 79.251.36 2 MD = 40 78.120.09b 1057.2311.44b 11.800.08b 3.620.02b 12.310.64ab 82.310.38 3 MD = 50 77.200.23c 1062.9412.75b 11.450.08c 3.540.33b 14.101.22bc 81.415.06 4 MD = 60 85.000.22d 943.688.89c 10.900.08d 3.430.14b 13.380.52bc 84.150.93 5 MD = 70 90.590.02e 879.115.28d 9.900.15e 2.700.08cd 14.480.23c 82.562.08 6 MD = 80 92.280.37f 796.232.55e 9.200.08f 2.630.15cd 14.440.58c 81.952.37 7 MS = 30 73.290.40g 995.297.80f 16.800.15g 3.330.22b 22.941.05e 81.410.45 8 MS = 40 80.030.15h 832.6622.48g 15.100.08h 3.290.11b 14.801.74c 82.502.06 9 MS = 50 83.290.12i 694.279.91h 14.600.08i 2.910.07c 16.911.22d 81.642.43 10 MS = 60 89.740.43j 669.853.82i 14.050.08j 2.530.06cd 14.610.12c 82.641.12 11 MS = 70 87.550.16k 600.656.54j 12.550.08k 2.530.02cd 14.790.27c 82.922.64 12 MS = 80 88.200.16l 623.972.56k 11.500.08c 2.500.05d 15.451.13cd 81.370.45

PR=Product recovery, BD=Bulk density, TA=Total acidity, MC=Moisture content, =Total color change, SO=Solubility a-lDifferent letters in the same column indicate significant differences (p

21 1 (2558), 7-14

7

Thai Society of Agricultural Engineering Journal Research Paper Volume 21 No. 1 (2015) 7-14


Study on effecting parameters of fresh sweet corn shelling without cutting corn germ 1, 1, 1 Wutipan Tengpawadee1, Vicha Manthamkan1, Anupun Terdwongworakul1 1, , , , 73140 1Department of Agricultural Engineering, Faculty of Engineering at Kamphaengsaen, Kasetsart University - Kamphaengsaen Campus, Nakhon Pathom, 73140

- 10 2 2 1 2 cm 2 , 3 (36, 42 48) 3 (40, 50 60 rpm) 2 1 36 60 rpm 10.02%, 251.94 s/ears 14.03 W/ears

: , ,

Abstract

Fresh sweet corn shelling machine was designed and assembled to study the parameters effect on shelling of Hybrix 10 variety without cutting corn germ. The shelling process is divided into two parts; using grooving sets for gouging fresh sweet corn and shelling machine for kernels shelling. This machine can operate 1 corn each time and require 2 operators. The main part of the grooving set is open groove roller and the grooving knife. The operation begins as groove roller will cut open groove of kernels to help remove easier with the width of the slit about 2 cm whereas the grooving knife will slash the kernels out. Moreover, the main of shelling machine is the shelling set operated to move alternation and pushes the kernels out of the core. The parameters were studied follow by 1) type of shelling rubber; type I and type II, 2) angle of shelling; 36, 42 and 48 respectively, and 3) speed of shelling rubber revolution; 40, 50 and 60 rpm respectively. From this experiment showed that the shelling rubber type II gave the better shelling result than shelling rubber type I. The result from shelling rubber type II, angle 36 with speed at 60 rpm had an average of kernels damage at 10.02%. The time and power consumption were used for shelling had averages of 251.94 s/ears and 14.03 W/ears respectively.

Keywords: Sweet corn, Shelling, Corn germ


8

1

2551-2556 336, 428 365, 061 tonne 2556 5,400 ( , 2557) Kessler Harry (1998) (Wilson, 1991)

2

2.1

- 10 ( 68-70 ) 10

(A) (B) (C) (D) (E) (I) (J) 10 3 (F) (G) (H) Figure 1

Figure 1 Size measuring position of sweet corn.

2.2

1-2

2.3

2 Figure 2 1) (groove roller)

2 2 cm ( 2 )

21 1 (2558), 7-14

9

2) (groove cutter) 2 cm

PVC 10

Figure 2 Primary components of the groove.

2.4

Figure 3 2.3 cm 6 cm 45 2 Figure 4 5 1 1 2.3 cm 2 3 6.9 cm 4 cm 5 hp

10.16 cm 35.56 cm

Figure 3 Primary components of the sheller.

-

Figure 4 Rubber shelling (Type I).

Figure 5 Rubber shelling (Type II).


10

2.5 2X3X3

Factorial in CRD 3 2 1 3 3 36, 42 48 3 40, 50 60 rpm 3 3 54 ,

l

l f

mDamaged kernels (%) = 100

m m

(1)

ml (g) mf (g)

T N 736Power (W) =

716.2

(2)

1 Torque Transducer (TP-10KMCB) Indicator (SLW-220PC) Figure 6

Figure 6 Kernel characteristic for consideration.

2.6

(ANOVA) Duncans multiple range test (P

21 1 (2558), 7-14

11

Table 1 Physical properties data.

Data Dehusked ear

weight (g) Dehusked ear

length (mm),(A) Dehusked kernel range (mm),(B)

Dehusked ear diameter (mm)

Ear position Ear bottom (C) Ear middle (D) Ear top (E) Measurable value 331.9213.14 287.7516.05 191.3313.40 11.311.24 12.381.46 11.021.69

Data Kernel thick (mm), (J) Kernel width (mm) Ear position Ear bottom Ear middle Ear top Ear bottom

Kernel position Kernel top (F) Kernel middle (G) Kernel bottom (H) Measurable value 4.920.77 4.540.38 5.220.80 8.311.10 8.160.89 6.741.15

Data Kernel width (mm) Ear position Ear middle Ear top

Kernel position Kernel top (F) Kernel middle (G) Kernel bottom (H) Kernel to (F) Kernel middle (G) Kernel bottom (H) Measurable value 8.711.00 8.170.63 6.761.08 7.730.81 7.220.82 5.871.09

Table 2 The pushed force used for groove set each angle of groove cutter.

Data The pushed force for set each angle of groove cutter (kgf)

5 10 15 Measurable value 4.730.23 11.81.59 22.83.14

Table 3 The result of sweet corn Sheller.

Parameters Damaged kernels

total (%) Kernels grooving

damaged (%) Kernels shelling damaged (%)

Time total (s)

Kernels grooving time (s)

Kernels shelling time (s)

Power (W)

1, 36, 40 10.47 5.82 4.65 401.51 29.15 372.36 8.63 1, 36, 50 11.03 5.12 5.90 392.51 31.85 360.66 13.49 1, 36, 60 30.18 10.10 20.07 401.64 33.62 368.02 18.34 1, 42, 40 11.32 6.86 4.46 401.74 28.85 372.89 12.47 1, 42, 50 11.62 6.54 5.08 302.22 28.44 273.78 16.58 1, 42, 60 13.09 8.33 4.76 303.43 27.06 276.37 18.34 1, 48, 40 19.97 10.11 9.86 472.82 39.09 433.73 9.83 1, 48, 50 20.47 9.21 11.26 428.76 36.60 392.16 15.89 1, 48, 60 26.50 11.43 15.07 330.12 29.22 300.90 17.98 2, 36, 40 18.61 11.30 7.31 292.75 30.29 262.46 10.31 2, 36, 50 13.44 10.61 2.83 282.98 38.29 244.68 12.29 2, 36, 60 10.02 8.22 1.81 251.94 26.22 225.72 14.03 2, 42, 40 13.40 10.28 3.12 258.93 29.71 229.22 16.55 2, 42, 50 10.93 6.51 4.42 245.27 31.37 213.90 15.59 2, 42, 60 10.89 7.63 3.26 220.71 33.71 187.00 19.42 2, 48, 40 13.59 9.46 4.13 207.57 23.98 183.59 15.83 2, 48, 50 12.76 8.66 4.09 182.79 17.50 165.29 22.78 2, 48, 60 13.04 8.40 4.64 175.27 24.78 150.49 27.34

Note: Front numbers are type of rubber shelling (1=Type I, 2=Type II) Middle numbers are angle of shelling (36=36, 42=42 and 48=48) Behind numbers are speed of shelling (40=40 rpm, 50=50 rpm and 60=60 rpm


12

3

3.1

10 Table 1 (Kernel width) 2 cm, (Dehusked ear diameter) PVC 7.62 cm (Dehusked kernel range) 2.3 6.9 cm,

, Table 3 10.02-30.17% 5.12-11.43% 1.81-20.07% 175.27-472.82 s/ears 17.50-39.09 s/ears 150.49-433.73 s/ears 8.63-27.34 W/ears 11.8 kgf

10 Table 2

3.2 (ANOVA) -

0.05 , Table 4, 5 6

1 2 , 42 (Table 4), 40 rpm 1 60 rpm 2 (Table 5) 2 1 (Table 6)

1 2 , 42 1 48 2 (Table 4), 60 rpm (Table 5) 2 1 (Table 6) 1 2 , 36 (Table 4), 40 rpm (Table 5) 1 2 (Table 6)

,

21 1 (2558), 7-14

13

Table 4 The result of comparison between angles of rubber shelling type I and II.

Type rubber shelling

Angle of

shelling

Performance Parameters Damaged kernels

total (%)

Time total (s)

Power (w)

Type I 36 17.23ab 398.55ab 13.49a 42 12.01a 335.80a 15.80b 48 22.31b 410.56b 14.57a

Type II 36 14.02a 275.89c 12.21a 42 11.74a 241.63b 17.18b 48 13.13a 188.54a 21.98c

Table 5 The result of comparison between speeds revolution of rubber shelling type I and II.


Speed (rpm)

Performance Parameters Damaged kernels

total (%)

Time total (s)

Power (W)

Type I 40 13.92a 425.35b 10.31a 50 14.37a 374.50ab 15.32b 60 23.25a 345.06a 18.22c

Type II 40 15.20a 253.08b 14.23a 50 12.38a 237.01ab 16.89b 60 11.32a 215.97a 20.26c

Note: The different English alphabet in vertical column represent Duncans multiple range tests with 95% statistically significant.

Table 6 The result of comparison between rubber shelling type I and II.


Performance Parameters Damaged

kernels total (%)

Time total (s)

Power (W)

Type I 17.18a 381.64b 14.62a Type II 12.96a 235.36a 17.13b

Note: The different English alphabet in vertical column represent Duncans multiple range tests with 95% statistically significant.

3.3

PCA ( 2552)

PCA 3 3 SPSS Table 7

Table 7 The standard value for parameters analysis.

Parameters Damaged

kernels total (Z1)

Time total (Z2)

Power (Z3)

1, 36, 40 -0.7956 1.0358 -1.5675 1, 36, 50 -0.6988 0.9356 -0.5155 1, 36, 60 2.6106 1.0373 0.5343 1, 42, 40 -0.6487 1.0384 -0.7363 1, 42, 50 -0.5969 -0.0699 0.1533 1, 42, 60 -0.3428 -0.0564 0.5343 1, 48, 40 0.8461 1.8300 -1.3077 1, 48, 50 0.9325 1.3393 0.0040 1, 48, 60 1.9746 0.2408 0.4564 2, 36, 40 0.6111 -0.1754 -1.2038 2, 36, 50 -0.2824 -0.2842 -0.7753 2, 36, 60 -0.8734 -0.6299 -0.3986 2, 42, 40 -0.2893 -0.5520 0.1468 2, 42, 50 -0.7161 -0.7041 -0.0610 2, 42, 60 -0.7230 -0.9776 0.7680 2, 48, 40 -0.2564 -1.1240 -0.0090 2, 48, 50 -0.3999 -1.3999 1.4953 2, 48, 60 -0.3515 -1.4837 2.4823 PCA -

2 PC1 PC2 PC1 3 PC1 52.344% PC2 3 PC2 40.006%


14

PC1 = 0.135Z1-0.469Z2+0.654Z3 (3)

PC2 = 0.848Z1+0.281Z2+0.269Z3 (4)

PC1 PC2 1 2 Z1, Z2 Z3 , Table 8

Table 8 The result of parameters analysis. Performance Parameters PC1 PC2

Total variance (%)

Damaged kernels total 0.135 0.848 Time total -0.469 0.281

Power 0.654 0.269 Variance (%) 52.344 40.006 92.350

PC1 PC2

TPS = 52.344PC1+40.006PC2 ...(5)

Total Performance Score (TPS) - 2, 36 60 rpm -41.0623 Table 9

Table 9 Calculated result for each parameters. Parameters PC1 PC2 TPS

2, 36, 60 -0.0834 -1.0253 -41.0623 1, 36, 40 -1.6181 -0.8058 -33.0819 2, 42, 50 0.1936 -0.8219 -32.7778 2, 42, 60 0.8632 -0.6813 -26.8047 2, 36, 50 -0.4121 -0.5283 -21.3496 2, 48, 40 0.4862 -0.5361 -21.1911 1, 42, 50 0.0527 -0.4846 -19.3598 1, 36, 50 -0.8698 -0.4685 -19.1967 1, 42, 40 -1.0557 -0.4565 -18.8164 2, 42, 40 0.3157 -0.3611 -14.2790 2, 48, 50 1.5804 -0.3301 -12.3772 1, 42, 60 0.3298 -0.1627 -6.3374 2, 48, 60 2.2719 -0.0467 -0.6780 2, 36, 40 -0.6231 0.1447 5.4613 1, 48, 40 -1.5990 0.8800 34.3697 1, 48, 50 -0.4993 1.1687 46.4932 1, 48, 60 0.4518 1.8654 74.8653 1, 36, 60 0.2153 2.6498 106.1223

4

- 10 2 2 36 60 rpm 10.02% 251.94 s/ears 14.03 W/ears

5

6 [1] . 2552.

.: .

[2] . 2553. SPSS. : .

[3] . 2557. 2556. : http://www.-oae.go.th. 14 2557

[4] Kessler, Jr., Harry, T. 1998. Machine for cutting kernels from ears of corn. USA Patent 5830060.

[5] Krishna, D., Rama Mohan, S., Murthy, B.S.N. 2002. Performance evaluation of public research institutes using Principal Component Analysis. Journal of Scientific & Industrial Research 61, 940-947.

[6] Wilson, C.M. 1991. Proteins of the kernel. In Corn: Watson, S.A., Ramstad, P.E. (Eds), Chemis-try and Technology. St. Paul: American Associa-tion of Cereal Chemists Inc.

21 1 (2558), 15-23

15

21 1 (2558) 15-23


Microwave drying kinetics of holy basil (Ocimum sanctum L.) leaves 1, 1* Praphun Jino1, Rittichai Assawarachan1* 1 , , 50290 1Faculty of Engineering and Agro-Industry, Maejo University, Chiang Mai, Thailand 50290 *Corresponding author: Tel: +66-8-5704-9146, Fax: +66-34-351-896, E-mail: [email protected], [email protected]

164-752 W 30 g 30-90 g 752 W 5.190.13 gwater gdry matter-1 0.060.02 gwater gdry matter-1 Newton, Henderson and Pabis, Page, Wang and Singh Logarithmic Page

(R2) (2) (RMSE) (MBE) (Deff) 4.15x10-11 - 2.76 x10-10 m2/s 19.85 W g-1

: , ,

Abstract This study aimed to determine the effects of power level and sample mass on moisture ratio of holy basil

leaves undergoing microwave drying process. Various microwave power levels ranging from to 164 to 752 W were used for drying of 30 g of holy basil leaves. To investigate the effect of sample mass on drying, the samples in the range of 30 to 90 g were dried at microwave power level of 752 W dried holy basil leaves to reduce the moisture content from 5.190. 13 gwater gdry matter-1 to 0.060.02 gwater gdry matter-1 . Mathematical models including the Newton, Henderson and Pabis, Page, Wang and Singh and Logarithmic models were evaluated for describing the drying kinetics under various microwave drying conditions, Pages model gave a better fit for all drying conditions used as

the highest coefficient of determination (R2), the least chi-square (2 ) , the lowest root mean square error (RMSE) and mean bias error (MBE). The effective diffusivity varied from 4.15x10-11 - 2.76 x10-10 m2/s and the activation energy for microwave drying of holy basil leaves was 19 . 8 5 W g-1 which was well explained by an exponential expression based on the Arrhenius models.

Keywords: holy basil leaves, microwave drying kinetics, mathematical model


16

1 (Ocimum sanctum L.) -

(Antioxidants) ( , 2550)

(Water activity) ( , 2555)

(, 2555)

7-10 (, 2554) (2555); Ozkan et al. (2007); Dadal et al. (2007); Assawa-rachan et al. (2011); zbek and Dadali (2007) Mas-kan (2001) (Spirogyra sp.) (Spinach) (Okra) (Paddy rice) (Mint leaves) (Kiwifruits)

(Deff) (Ea) (m/P)

2

2.1

3 (Wasino Model: CE03) (Haier Model: HP-921F) 40.5C 24 hr zbek and Dadali (2007) 1 g 3 oz (Memmert Model: 500/108I) 1052C

21 1 (2558), 15-23

17

24 hr (AOAC, 2005) 5.190.13 gwater gdry matter-1

2.2

(Mode stirring) 800 W (Panasonic Model: NN-S235WF) (Sartorius Model: CP3202S) 5 164, 231, 465, 605 752 W ( , 2555)

30 g 20x20 cm 164, 231, 465, 605, 752 W 30, 50, 70, 90 g 752 W 0.060.02 gwater gdry matter-1 3

2.3

(MR) Newton, Henderson and Pabis, Page, Wang and Singh Logarithmic (Table 1) Eq. (1) zbek and Dadali (2007) Evin (2012)

t e t

i e i

M M MMR

M M M ...(1)

MR Mt, Mi, Me ( , 2555; Evin, 2012; Assawarachan et al., 2013) (Semitheoretical model) (Ficks second law)

(2)

2

2

2 4exp

8

L

tDMR

eff

(2)

Deff (m2/s), L (m) t (s)

Deff (3) (3)

2

2 2

8ln( ) ln

4

effD tMR

L

...(3)

Deff ln(MR) (t)

(Ea) (Arrhenius equation) (k) Eq. (4)

0 exp

aE mk kP

...(4)

k0 (min-1), Ea (W g-1), m (g) P (W) (zbek and Dadali, 2007) (Heat of Vaporization)


18

(Deff) (k) (m) (P) (Ea) (4) , 2558; Evin, (2012), Assawarachan et al.,(2013), Ozkan (2007) zbek and Dadali (2007)

Table 1 Mathematical models given by various authors.

Model name Model equation Reference

Newton exp( )MR kt Assawarachan et al. (2011)

Henderson and Pabis

exp( )MR a kt Dadal et al.

(2007)

Page exp( )nMR kt Pongtong et al. (2011)

Wang and Singh

21MR at bt McMinn (2006)

Logarithmic exp( )MR a kt c Assawarachan et al. (2013)

k = drying constant (min-1), n = drying index, and a, b and c = model parameters (Coefficient of determi-

nation, R2) (Chi-square, 2) (Root mean square error, RMSE) (Mean bias error, MBE) (Maskan, 2001; Ozkan et al., 2007) R2 1.0

2 RMSE MBE R2

2, RMSE MBE

3

3.1

30 g 5.190.13 gwater gdry matter-1 0.060.02 gwater gdry matter-1 18.50, 14.00, 9.00, 4.00 2.75 min 164, 231, 465, 605 752 W (Figure 1) 752 W 164 W 6.73 752 605 W 1.86 1.38 gwater (gdry mattermin) -1 (Moisutr Ratio Curve) Figure 1 Maskan (2001) Dadal et al. (2007) (, 2554) (Constant rate period) (Falling rate period)

21 1 (2558), 15-23

19

Newton, Henderson and Pabis, Page, Wang and Singh Logarithmic Page R2 0.9980-0.9995

2 0.1138-0.1413 RMSE MBE 0.0095-0.0291 0.0001-0.0008 (Table 2) Newton, Henderson and Pabis, Wang and Singh Logarithmic Kingsly and Singh (2007) Dadal et al. (2007) Page Table 3 Page (k) (n) Page

Page Figure 1 Dadal et al. (2007) zbek and Dadali (2007) k n Page 752 W 164 W

Figure 1 Moisture ratios for holy basil leaves versus

time at various microwave power levels for sampl mass of 30 g, comparing experimental curve with most predicte semi-empirical Pages equation; 164 W, 231 W, 465 W, 605 W, 752 W, kinetic model.

Figure 2 Moisture ratios for holy basil leaves versus time

at various sample mass for microwave power level of 752 W, comparing experimental curve with most predicted semi-empirical Pages equation; 30 g, 50 g, 70 g, 90 g, kinetic model.

Figure 3 The effect of power level/sample mass on

drying constant of holy basil leaves.


20

Table 2 Statistical analysis of models at various microwave power levels. Models Power (W) R2 2 RMSE MBE

Newton

164 0.9676 0.1935 0.1111 0.0123

231 0.9692 0.1756 0.1019 0.0104 465 0.9760 0.1801 0.0920 0.0085

605 0.9485 0.2008 0.1466 0.0215

752 0.9612 0.2203 0.1341 0.0180

Henderson and Pabis

164 0.9749 0.1428 0.0879 0.0077

231 0.9762 0.1312 0.0800 0.0064 465 0.9819 0.1375 0.0702 0.0049

605 0.9559 0.1378 0.1240 0.0154

752 0.9661 0.1687 0.1163 0.0135

Page

164 0.9989 0.1219 0.0209 0.0004 231 0.9992 0.1200 0.0148 0.0002

465 0.9995 0.1310 0.0095 0.0001

605 0.9993 0.1138 0.0163 0.0003

752 0.9980 0.1413 0.0291 0.0008

Wang and Singh

164 0.9942 0.1575 0.0465 0.0022

231 0.9919 0.1502 0.0520 0.0027 465 0.9948 0.1609 0.0453 0.0021

605 0.9819 0.1663 0.0849 0.0072

752 0.9960 0.1728 0.0419 0.0018

Logarithmic

164 0.9957 0.1380 0.0366 0.0013 231 0.9932 0.1274 0.0428 0.0018

465 0.9949 0.1376 0.0371 0.0014

605 0.9846 0.1367 0.0732 0.0054 752 0.9965 0.1713 0.0376 0.0014

Table 3 Coefficients of Pages model estimated at various microwave power levels. Power (W) k (min-1) n

164 0.0134 1.9319

231 0.0347 1.8429 465 0.0903 1.7277

605 0.1637 2.5158

752 0.3051 2.2760

21 1 (2558), 15-23

21

3.2

30, 50, 70 90 g 752W 2.75, 5.00, 6.00 7.50 min (Figure 2) 5.190.13 gwater gdry matter-1 0.060.02 gwater gdry matter-1 30g 90g 2.73 Dadal et al. (2007) zbek and Dadali (2007)

(Non-linear regression) R2

2, RMSE, MBE -

R2 2, RMSE, MBE (Maskan, 2001; Dadal et al., 2007; zbek and Dadali; 2007; Assawarachan et al., 2011) Table 4 - Page R2

0.9990-0.9995 2 0.1311-0.1412 RMSE MBE 0.0068-0.0291 0.0001-0.0008 Dadal et al., 2007 Page

Table 5 Page (k) (n) Figure 2 752 W 30, 50, 70 90 g Page k n 30g 90g

3.3 (Deff)

(Deff) 164, 231, 465, 605, 752 W 30, 50, 70, 90 g (m/P) 0 . 0 3 9 , 0.046, 0.051, 0.062, 0.067, 0.093, 0.119, 0.182 0.130 g W -1 (Deff) 4.15x10-11, 5.92x10-11, 6.64x10-11, 7.02x10-11, 8.71x10-11, 1.07x10-10 1.34x10-10, 2.05x10-10 2.76 x10-10 m2/s (Surface diffusion) Deff (m/P)


22

(k) (m/P) (2557) zbek and Dadali (2007) Deff

(m/P)

Table 4 Statistical analysis of models at various samples mass. Models Weight (g) R2 2 RMSE MBE

Newton

30 0.9612 0.2203 0.1341 0.0180

50 0.9727 0.1866 0.1004 0.0101

70 0.9675 0.1960 0.1129 0.0127

90 0.9680 0.1995 0.1133 0.0128

Henderson and Pabis

30 0.9661 0.1687 0.1163 0.0135

50 0.9781 0.1434 0.0803 0.0065

70 0.9738 0.1461 0.0915 0.0084

90 0.9745 0.1478 0.0911 0.0083

Page

30 0.9980 0.1412 0.0291 0.0008

50 0.9999 0.1342 0.0068 0.0000

70 0.9992 0.1311 0.0172 0.0003

90 0.9990 0.1326 0.0193 0.0004

Wang and Singh

30 0.9960 0.1728 0.0419 0.0018 50 0.9191 0.1693 0.1545 0.0239

70 0.9939 0.1647 0.0491 0.0024

90 0.9947 0.1645 0.0460 0.0021

Logarithmic

30 0.9965 0.1715 0.0376 0.0014 50 0.9942 0.1458 0.0413 0.0017

70 0.9952 0.1449 0.0392 0.0015

90 0.9960 0.1455 0.0359 0.0013

Table 5 Coefficients of Pages model estimated at various sample mass. Sample (g) k (min-1) n

30 0.3051 2.2760

50 0.2092 1.8295

70 0.1119 1.9610

90 0.0682 1.9621

3.4

(Eq. (4)) Eq. (5)

0ln lnaE mk kP

...(5)

(k0) (Ea) ln(k) (m/P) k0 Ea 0.5773 min-1

21 1 (2558), 15-23

23

19.85Wg-1 Figure 3 Ea

4

Page (R2)

(2) (RMSE) (MBE) (Deff) 4.15x10-11 2.76 x10-10 m2/s (m/P) 0.039, 0.046, 0.051, 0.062, 0.067, 0.093, 0.119, 0.182 0.130 g W -1

5 [1]

. 2550. . : .

[2] , , , . 2555. . 7 2555. : . 6-8 2555, , .

[3] , , , . 2555. . 18, 1-8.

[4] . 2554. . 1, 31-42.

[5] . 2554. . 17, 41-52.

[6] . 2555. . : .

[7] AOAC. 2005. Official Methods of Analysis. (18th

ed.). Association of Official Analytical Chemists, Washington, D.C.: USA.

[8] Assawarachan, R., Sripinyowanich, J., Theppa-dungporn, K., Noomhorm, A. 2011. Drying paddy by microwave vibrofluidized drying using single mode applicator. Journal of Food, Agriculture & Environment 9, 50-54.

[9] Assawarachan, R., Nookong, M., Chailungka, N., Amornlerdpison, D. 2013. Effect of microwave power on the drying characteristics, color and phenolic content of spirogyra sp. Journal of Food, Agriculture & Environment 11, 15-18.

[10] Dadal, G., Apar, D.K., zbek, B. 2007. Microwave drying kinetics of okra. Drying Technology 25, 917-924.

[11] Evin, D. 2012. Thin layer drying kinetics of Gundelia tournefortii L. Food and Bioproducts Processing 90, 323-332.

[12] Kingsly, A.R.P., Singh, D.B. 2007. Drying kinetics of pomegranate arils. Journal of Food Engineering 79, 741-744.

[13] Maskan, M. 2001. Microwave/air and microwave finish drying of banana. Journal of Food Engineering 44, 71-78.

[14] McMinn, W.A.M. 2006. Thin-layer modeling of the convective, microwave, microwaveconvec-tive and microwave vacuum drying of lactose powder. Journal of Food Engineering 72, 113-123.

[15] zbek, B., Dadali, G. 2007. Thin-layer drying characteristics and modelling of mint leaves undergoing microwave treatment. Journal of Food Engineering 83, 541-549.

[16] Ozkan, I.A., Akbudak, B., Akbudak, N. 2007. Microwave drying characteristics of spinach. Journal of Food Engineering 78, 577-583.

[17] Pongtong, K., Assawarachan, R., Noomhorm, A. 2011. Mathematical models for vacuum drying characteristics of pomegranate aril. Journal of Food Science and Engineering 1, 11-19.


24

21 1 (2558) 24-29


Study of Potential of Erianthus sp. for Biogas Production 1*, 2, 2 Pinit Jirukkakul1*, Taksina Sansayawichai2, Preecha Kapetch2 1 , , , 40000 1Khon Kaen Agricultural Engineering Research Center, Department of Agriculture, Muang, Khon Kaen, Thailand 4000

2 , , , 40000 2Khon Kaen Field Crops Research Center, Department of Agriculture, Muang, Khon Kaen, Thailand 4000 *Corresponding author: Tel: +6682-3055-175, Fax: +6643-255-038, E-mail: [email protected]

(ThE98-242) 6 C, H, N, S O 45.232, 6.333, 0.678, 0.201 47.557 165.46 l kg-1 (195.81 l kgTS-1) 90 54.5 1,636.40 m3.Rai-1

1,963.68 kW-h.Rai-1 CH4 CO2 53.5 46.50 7 () 0.5, 0.75 1.0 m 4.95, 3.45 2.9 Ton.Rai-1

: , ,

Abstract

Due to the energy crisis, renewable energy production has been promoted in Thailand such as gasification and biogas production for electric power. Recently, the Department of Alternative Energy Development and Efficiency, Ministry of Energy has put emphases on the development of renewable energy from crops such as Napier, rice straw etc. The production of alternative energy plants suitable for growing area would be the way to increase productivity. Therefore, the production of Erianthus sp. (ThE98-242) on a commercial scale was studied. The chemical composition of 6-month old Erianthus sp. showed C, H, N, S and O contents of 45.232, 6.333, 0.678, 0.201 and 47.557%, respectively. This sample could yeild biogas production of approximately 165.46 l.kg-1 along with degradable organic matter of 90% at moisture content of 54.5%, which in total could provide biogas production of 1,636.40 m3.Rai-1 or electricity generation of 1,963.68 kw-h.Rai-1. The CH4 and CO2 contents in the biogas were 53.5 and 46.50%, respectively. The Erianthus sp. plated for 7 months with different plant spaces of 0.5, 0.75 and 1.0 m yielded dried matter of 4.95, 3.45 and 2.9 Ton.Rai-1, respectively.

Keywords: Erianthus sp., Biogas, Renewable crop.

21 1 (2558), 24-29

25

1

1-2 MW ( , 2556) (Alternative Energy Development Plan, AEDP) 25552564 3,000 MW

6-10 15 -30 Ton.Hectare-1.year-1 (silage) 500-600 m3 500 hectare 10 MW (FACT, 2013)

3 1) () 2) () (Saccharum spontan-eum) 3) (Erianthus arundinaceus

section Ripidium Henrard) 50-70 Erianthus sp.

2

2.1

RANDOMIZED COMPLETE BLOCK DESIGN (RCBD) 4 TPJ04-768 ThE03-07 ThE 03-242 3 (KK3) 5 8 m 3 1.5 m 1 m 22 Rai 3 2555 11 2556

2.2

2 x 3 factorial in RCBD 4 2

1

2 3 1.5x0.5 m 1.5x0.75 m 1.5x1 m

2 kg 80oC 48 h . 2555- 2558


26

2.4

(CHN Analyzer) LECO 628 6 (Proximate Value) (Moisture Content) (Volatile Matter) (Ash Content) ASTM D1762-84

(Brix Refractometer) Brix

2.5

Buswell and Mueller (1962) CaHbOcNd (1) 1 MW

a b c d 2

4a b 2c 3dC H O N H O

4

(1)

3

ThE98-242 10.70 9.89 Ton.Rai-1 3 5.68 Ton.Rai-1 ThE98-242 5.40 4.50 Ton.Rai-1 3 1.87 Ton.Rai-1 ThE03-07 52.9% ThE98-242 TPJ04-768 3 46.0, 45.3, 40.2 33.0% 3 26.2% 24.0% Table 1

Figure 1 Erianthus sp. at 6 months.

Table 1 The mass and total soluble solid of renewable crop. Crops Wet wt. (Ton.Rai-1) Dry wt. (Ton.Rai-1) Brix (%) Dry wt. (%)

Napier 11.70 a 5.40 a 14.4 f 46.0 a KK3 5.68 bcd 1.87 cd 26.2 a 33.0 b

ThE98-242 9.89 a 4.50 a 15.6 ef 45.3 a ThE03-07 5.72 bcd 3.11 b 18.2 cd 52.9 a TPJ04-768 3.98 cd 1.59 cd 24.0 b 40.2 ab

Note: Different superscripts in the same column indicate statistical difference (p0.05) by Ducan Multiple range test(DMRT).

4 2 3

4a b 2c 3d 4a b c 3dCH CO dNH

8 8

21 1 (2558), 24-29

27

Table 2 Planting spaces, high, width shape and survival rate of biomass. Crops Planting space

(cm) High (cm)

Width shape (cm)

Survival rate (%)

ThE03-07 1.5x0.5 47.68 139.63 84.00 1.5x0.75 45.55 145.95 86.50 1.5x01.0 45.58 137.25 82.50

Average 46.27b 140.94b 84.33b ThE98-242 1.5x0.5 74.53 146.27 97.25

1.5x0.75 70.83 144.23 96.50 1.5x01.0 71.05 153.68 98.50

Average 72.13 a 148.06 a 97.42 a Note: Different superscripts in the same column indicate statistical difference (p0.05) by Least Significant Difference (LSD)

ThE98-242 ThE03-07 97.42 84.33% Table 2 21 2556 7 Table 3 Table 4 ThE98-242 3.77 Ton.Rai-1 ThE03-07 3.16 Ton.Rai-1 348, 317 cm 19.93, 13.42 cm ThE98-242 ThE98-242 8,272

Ton.Rai-1 ThE03-07 12,237 Ton.Rai-1

ThE98-242 6 C, H, N O 45.232, 6.333, 0.678 47.557% Table 4 S 0.201% H2S Table 5

Table 3 The production of ThE03-07 and ThE98-242 varieties at the different plants space.

Varieties Plants space (m) Wet production (Ton.Rai-1) Dry production (Ton.Rai-1)

ThE03-07 1.5 X 0.5. 3.53b 1.73ab

1.5 X 0.75 3.43b 1.69ab

1.5 X 1.0 2.53c 1.27b

Avg. 3.16 1.56 ThE98-242 1.5 X 0.5 4.95a 2.28a

1.5 X 0.75 3.45b 1.41b

1.5 X 1.0 2.9bc 1.29b

Avg. 3.77 1.66 Note: Different superscripts in the same column indicate statistical difference (p0.01).


28

Table 4 The ultimate analysis of ThE98-242 at 6 months. Part C(%) H(%) N(%) S(%) O(%)

Dry leaf 45.342 6.311 0.474 0.220 47.653 Fresh leaf 45.365 6.157 0.742 0.197 47.539

Stem 44.888 6.838 0.480 0.191 47.603 Top 45.334 6.024 1.016 0.194 47.432 Avg. 45.232 6.333 0.678 0.201 47.557

Table 5 The mass of TPJ04-452 at 6 months (2 times) and 12 months harvested period on 3 periods at Khon Kean Field Crops Research Center.

Period Harvested period (month) Dry wt. (Ton.Rai-1)

1. 25 April 2012 6 (2 times) 4.4303 a 12 3.9632 a

2. 23 May 2012 6 (2 times) 1.7697 c 12 2.8837 b

3. 25 June 2012 6 (2 times) 2.8912 b 12 3.1991 b

Note: Different superscripts in the same column indicate statistical difference (p0.05).

Table 6 Ultimate analysis of renewable crop at 6 months. Crop C(%) H(%) N(%) S(%) O(%)

Napier 43.10 6.97 0.25 0.10 49.58 KK3 42.9 7.2 0.25 0.21 49.44

THE98-242 45.23 6.33 0.67 0.2 47.57 TPJ03-452 43.4 7.11 0.14 0.09 49.26 TPJ04-768 43.9 7.05 0.1 0.08 48.87

Table 6

C:N 20:1 C:N

90% (Proximate Value) 14.4%wb, Total Solid 845 g.kg-1, Volatile Solid 393.3 g.kg-1 1.28%

Table 7 Biogas calculation from ultimate analysis. Crop CaHbOcN Biogas (l.kg-1) % CH4 % CO2

1.Napier C23H45.3O19.4N 159.93 55.8 44.16 2.KK3 C23H47O19.5N 78.40 56.8 43.19

3.THE98-242 C23H39.2O17.9N 165.46 53.5 46.50 4.TPJ04-768 C23H45O18.68N 124.74 56.3 43.73

Note: the performance of degradable organic matter 90%.

21 1 (2558), 24-29

29

Table 8 Renewable crop production for biogas power plant 1 MW. Crop Biogas/area/year (m3.Rai-1) Electric/area (kW.Rai-1) Area (Rai.MW-1)

1.Napier 1871.18 2245.42 3527.184 2.kk3 445.31 534.37 14821.07

3.THE98-242 1636.40 1963.68 4033.26 4.TPJ04-768 496.47 595.76 13293.98

Note: work rate 330 days 24 h, Biogas 1 m3 equal 1.2 kW-h at CH4 53.5%.

Table 1 Table 7 1 MW

Table 8 1 MW 4,033 Rai

4

7 () 1.5 m 0.5, 0.75 1.0 m 4.95, 3.45 2.9 Ton.Rai-1 1.5 m 0.5 m 97.42 84.33 13.4% 2 ( 6 )

6 C, H, N, S O 45.232, 6.333, 0.678, 0.201 47.557%

165.46 l.kg-1 90% 54.5%wb CH4 54.29% CO2 45.70% ThE98-242 1636.40 m3.Rai-1 1963.68 kw-h.Rai-1 1 MW 4033 Rai 2

5

2556

6 [1] . 2556.

Adder Feed-in tariff . : http://www.eppo.go.th-/FIT/part1.pdf. 7 2556.

[2] Buswell, A.M., Mueller, H.F. 1962. Mechanisms of methane fermentations. Industrial Enginee-ring Chemistry 44, 550.

[3] FACT. 2013. Bioenergy Technology. Available at: http://www.fact-foundation.com. Accessed on 7 December 2013.


30

21 1 (2558) 30-36


.. 2551 2555 Different Curriculums Related to the Field of Agricultural Engineering in Thailand during 2008 to 2012 1* Tanya Niyamapa1* 1, , , , 73140 1Department of Agricultural Engineering, Faculty of Engineering at Kamphaengsaen, Kasetsart University - Kamphaengsaen Campus, Nakhon Pathom, 73140

*Corresponding author: Tel: +-6634-351-896, Fax: +-6634-351-896, E-mail: [email protected]

3

Agricultural Engineering Biological and Agricultural Engineering Agricultural Engineering Biological Engineering

: , , Biological engineering

Abstract

This paper is written concerning the curriculums of Agricultural Engineering in Thailand. The Agricultural Engineering curriculums of Kasetsart University, King Mongkut's Institue of Technology Ladkrabang and Khon Kaen University are described. The status of the graduates with the bachelor's degree in Agricultural Engineering from Kasetsart University are reported. The curriculum of Agricultural Engineering of China Agricultural University is also mentioned. The interesting aspect of the China Agricultural University curriculum is that the curriculum does not only focus on principles and theories, but also the engineering practices and experiments simultaneously. However, the pioneers of Biological and Agricultural Engineering curriculums would be Canada and the United States of America. It should be noted that the name, Agricultural Engineering, is considered part of the name, Biological Engineering.

Keywords: Curriculum, Agricultural engineering, Biological engineering

1

ASEAN Economics Community (AEC) 2015

18 .. 2555 AEC 2015 ,

21 1 (2558), 30-36

31

Dr. Abdel Ghaly Biological and Environmental Engineering Process Engineering Dalhousie University .. 2551 2555 Biological and Agricultural Engineering University of California, Davis, U.S.A.

Department of Biological and Agricultural Engineering, Department of Biosystems Engineering, Department of Bioresources Engineering, Department of Biological Systems Engineering Department of Bioproduction and Machinery Division of Environmental Science and Technology Department of Agricultural System Engineering Division of Bioproduction Engineering Department of Biosystems and Biomaterials Science and Engineering Department of Biological and Agricultural Engineering Department of Agricultural Engineering, Department of Agricultural and Food Engineering, Farm Machinery and Power Department Department of Agricultural Engineering Department of Agricultural Engineering - (Department of Agricultural Engineering) Department of Agricultural Engineering Department of Agricultural Engineering Biosystems Engineering Department of Biosystems

Engineering Department of Agricul-tural Engineering

(Agricultural Engineering) Agricultural Engineering Bio Department of Biological and Agricultural Engineering, College of Engineering, University of California, Davis, U.S.A.

2 .. 2551 2555

12 3

2.1 .. 2551

2.1.1

1)

2)


32

3)

2.1.2

1) 146 2) - 30

10 12 3 3 2

- 110 24 80 6

- 6 - 240 ( , 2551)

2.2 .. 2552

3

2.2.1

1) 145 2) - 30

6 6 12 6

- 109 21 9 67 6 6

- 6 ( , 2552)

2.3 .. 2550

2.3.1

1)

2)

2.3.2

2 1 Table 1

21 1 (2558), 30-36

33

3

.. 2543

(Basic Sciences) (Basic Engineering) 18 6 (Specific Engineering) 12 4

1) 9

2) 6 3) 3

4 (, 2555)

468

94

1) 2) 3) (

)

4)

( ) ( ) .


34

Table 1 .. 2550 .

1 2 1. 30 30 30 - - -

12 6 12

12 6 12

12 6 12

2. 116 116 117 117 136 - 31 31 31 31 31 - 46 46 47 47 44 - 30 27 30 27 52 - 9 3 9 3 9 - 0 9 0 9 0 3. 6 6 6

152 153 172 ( , 2550)

5 Agricultural Engineering

Department of Agricultural Engineering College of Engineering, China Agricultural University 4 168 () 168 Mechanical CAD/CAM Experiment, Robotic Creation Experiment (1), Robotic Creation Experiment (2 ) , Robotic Creation Experiment (3) , Technological Innova-tion Practice, Metals Technology Practive (A), Agricul-tural Machinery of Equipment Manufacturing Practice

6 Bio

Dr. Abdel Ghaly ASEAN Economics Community (AEC) 2015 Agricultural Engineering

Biological Engineering (Depart-ment of Agricultural Engineering) Iowa Agricultural College, Iowa State University .. 1908 Faculty of Agricultural Science, University of Mani-toba .. 1906 .. 1908 .. 1912 Biological Engineering .. 1965 4 Mississippi State University (USA), North Carolina State University (USA), University of Guelph (Canada) Technical University of Nova Scotia (Canada) Agricultural Engineering Biological Engineering .. 1980 American Society of Agricultural Engineers (ASAE) Canadian Society of Agricultural Engineers (CSAE) .. 1987

21 1 (2558), 30-36

35

Agricultural Engineering .. 1989 Agricultural Engineering Biological Engineering Agricultural Engineering Biological Engineering .. 2000 Biological Engineering, Bioresources Engineering, Biosystems Engineering Biological Systems Engineering .. 2004 CSAE CSBE .. 2005 ASAE ASABE Figure 1 Biological Engineering

Figure 1 Biological

Engineering (Ghaly, 2012).

Bio

6.1 Department of Biological and Agricultural Engineering, College of Engineering, University of California, Davis, U.S.A.

6.1.1 (Mission): Department of Biological and Agricultural

Engineering (biological systems) (principles) (application)

6.1.2 (Objectives):

(biological system) ( analysis) (synthesis) (engineering practice) (graduate education)

6.1.3 Biological Systems Engineering Biological Systems Engineering

(biology) (biotechnology) (bioenergy) (bioprocessing) (biotechnology) (food processing) (aquaculture) (agriculture)

1 2 Biological Systems Engineering (engineering science) Biological Systems Engineering


36

Units Mathematics 16 Mathematics 6 Physics 15 Chemistry 10 Biological Sciences 14 Biological Systems Engineering 4 Engineering 11 Biological Systems Engineering 4 University Writing Program 4 Communication 4 General Education electives 8 Minimum Lower Division 96

3 4 Biological Systems Engineering (Upper Division Require-ments) 8

Agricultural Engineering Aquaculture Engineering Bioenergy Engineering Biomechanics/Premedicine/Preveterinary Medicine Biotechnical Engineering Ecological Systems Engineering Food Engineering Forest Engineering

6.1.4 (Agricultural Engineering)

7 ASEAN Economics Community (AEC) 2015

1)

2)

3) Bio 4)

5) Department of

Biological and Agricultural Engineering Biological Engineering 2015

6) 15-20 (Ghaly, 2012)

8 [1]

. 2551. .. 2551.

[2] . 2552. .. 2552.

[3] . 2550. .. 2550.

[4] . 2555. . .. 2555.

[5] Ghaly, A. 2012. Personal communication.

21 1 (2558), 37-44

37

21 1 (2558) 37-44


Development of a Dry Lotus Seed Sheller 1*, 1, 2 Jaturong Langkapin1*, Sunan Parnsakhorn1, Purin Akarakulthon2 1, , , , , 12110 1Department of Agricultural Engineering, Faculty of Engineering, Rajamangala University of Technology Thanyaburi, Thanyaburi, Pathumthani, 12110

2, , , , , 12110 2Department of Post Harvesting Tecnology, Faculty of Agricultural Tecnology, Rajamangala University of Technology Thanyaburi, Thanyaburi, Pathumthani, 12110

*Corresponding author: Tel: +-662-549-3328, Fax: +-662-549-3581, E-mail: [email protected]; [email protected]

2 10.5 11.5 mm 2 hp 13.3 mm s-1 1.30.1 kg hr-1 75.76.4 18.20.7% 73.34.0 20.21.8% 0.52 kW-hr 1 1,200 hr 24 Baht kg-1 3 month 40 hr year-1

: , ,

Abstract A dry lotus seed sheller was designed and fabricated to reduce shelling time and number of labor for the dry

lotus seed shell removing. The prototype consisted of main frame, feeding unit, 2 sizes of shelling unit; the 10.5 and 11.5 mm cylinder cutting balde were installed in first and second shelling unit, respectively, the power transmission unit, and 2 hp electric motor was used as a prime mover. The dry lotus seeds were fed manually into feeding chute at the top of the machine, then were conveyed to shelling unit by seed feeder, and left through in front of the machine after shelling. Testing results indicated that the best shelling quality was obtained when operated at 13.3 mm s-1 piercing rod speed. Working capacity was found to be 1.30.1 kg hr-1, the percentage of shelling and seeds damaged of the first shelling unit were 75.76.4 and 18.20.7%, the percentage of shelling and seeds damaged of the second shelling unit were 73.34 .0% and 20.21.8%, and consumed 0 .52 kW-hr of energy. Based on the engineering economical analysis, indicated that the operating cost was 24 Bath kg-1, payback period 3 months and the break-even point of the machine was 40 hr year-1 at the annual use of 1,200 hr year-1.

Keyword: Lotus, Dry Lotus seed, Sheller


38

1

(, 2554) 5,000 ( , 2554) ( , 2550) 1.2 (, 2552)

2 () ( ) ( , 2557) (Figure 1)

0.23 kg hr -1 SME ( , 2552)

Figure 1 Traditional dry lotus seed shelling method.

2

2.1 2.1.1

1)

2) 100 Baht kg-1 3)

0.3 kg hr-1

4) 50%

5)

21 1 (2558), 37-44

39

2.1.2

(Figure 2) (a) (b) (c) ASAE (Anon, 1983) 200 11.2-12.6 mm 11.90.3 mm 15.0-18.1 mm 16.30.5 mm 1.0-1.6 mm 1.20.1 mm 7.4% w.b.

11.5 mm 11.5-12.0 mm 12.0 mm 11, 65 24% 11.5 mm 89% 11.5 mm

Figure 2 Dimensions of dry lotus seed.

2.1.3

(Figure 3)

Figure 3 Equipment - used in laboratory testing.

2.2

(Shigley and Mischke, 1989) (Krutz et al., 1994) (, 2555) (Main frame) (Feeding unit) (Shelling unit) (Power transmission unit) 2 hp (Figure 4a)

465x490x500 mm (xx) 40x40 mm 4 mm

(Figure 4b) 1 kg 130 mm 12 mm 1 14 mm


40

(Figure 4c) Slider crank (Myszka, 2012) 2 10.5 mm 11.5-12.0 mm 11.5 mm 12.0 mm

1 1 1

(a) The dry lotus seed sheller design by using CAD.

(b) The feeding unit.

(c) The shelling unit.

(d) Prototype of dry lotus seed sheller.

Figure 4 Schematic of dry lotus seed sheller prototype.

2.3

) (Percentage of shelling, %)

Number of shelled seeds%Shelling= x100

Total number of seeds ...(1)

Number of shelled seeds Total number of seeds

) (Percentage of damage, %)

Number of damaged seeds%Damage = x100

Total number of seeds ...(2)

Number of damaged seeds ( Figure 6c)

) (Working capacity, kg hr-1)

21 1 (2558), 37-44

41

Number of shelled seedsWorking capacity =

Total working time ...(3)

Total working time ) (Power consumption,

kW-hr)

Power consumption = IVt

1000 (4)

I (A), V (V) t (hr)

11.5-12.0 mm 12.0 mm 10.5 ( 1) 11.5 mm ( 2) 7.2% w.b.

40 rpm 20, 30 40 rpm ( 8.8, 13.3 17.7 mm s-1 ) 3 100

2.4 2.4.1

(Fixed cost) (Variable cost) ( 5 ) ( 10%) (Hunt, 2001)

2.4.2 (Pay-back period)

(Hunt, 2001)

2.4.3 (Break-even point)

3

3.1

(Figure 5) 20, 30 40 rpm 72.32.5, 75.76.4 71.10.6% 67.32.5%, 73.34.0 59.313.0%

0.05 (Figure 5a) 10.5 mm 11.5 mm (Figure 5b)

30 rpm ( 13.3 mm s-1)

(a) Percentage of shelling at different cam speeds: (In

each cutting blade size, followed by a common letter are not significantly different at 5% by DMRT).


42

(b) Shelling percentages at different cam speeds.

Figure 5 Shelling percentages at different cutting blade size and cam speeds.

3.2 Figure 6 (a)

(b) (c) 20, 30 40 rpm 19.20.3, 18.20.7 21.21.0% 22.30.8% , 20.21.8 30.21.3% (Figure 7)

0.05 (Figure 7a) 40 rpm 17.7 mm s-1 20 30 rpm 30 rpm

Figure 6 Dry lotus seed (a), Dry lotus seed after shelling

(b) and Seed damaged (c).

(a) Seed damaged at different cam speeds: (means in

each cutting blade size, followed by a common letter are not significantly different at 5% by DMRT).

(b) Seed damaged at different cam speeds.

Figure 7 Seed damaged at different cutting blade size and cam speeds.

21 1 (2558), 37-44

43

3.3

20 , 30 40 rpm 1.10.0, 1.30.1 1.10.1 kg hr-1 (Figure 8) 30 rpm

Figure 8 Machine capacity at different cam speeds.

3.4

0.51-0.53 kW-hr (Figure 9) 30 rpm 0.52 kW-hr

Figure 9 Power consumption at different cam speeds.

3.5

19,000 Baht (Table 1) 5 year 10% 1 1.30.1 kg hr-1 0.52 kW-hr 1,200 hr year-1 24 Baht kg-1 3 month 40 hr

year-1 1 0.3 kg hr-1 100 Baht kg-1

Table 1 Cost of dry lotus seed sheller prototype. Item Amount (Baht)

1. Electric motor and Gear box 6,500 2. Materials cost 2.1 Main frame 2.2 Feeding unit 2.3 Shelling unit 2.4 Power transmission unit

2,000 1,500 2,500 3,000

3. Skilled labor cost for fabrication 3,500 Total 19,000

4

30 rpm 1.30.1 kg hr -1 4 75.76.4 18.20.7% 73.34.0% 20.21.8 0.52 kW-hr 1 1,200 hr 24 Baht kg-1 3 month 40 hr year-1

5 (.)


44

6 [1] . 2554. .

: http://www.doae.go.th/LIBRARY/-html/detail/sacreslotus/0 1 . htm. : 24 2555.

[2] . 2554. -. : .

[3] . 2552. . : http://bverd.-net/project_detail.php?project_id=89 : 24 2554.

[4] , , . 2557. . . 20(1): 9-15

[5] . 2555. SolidWorks (). : .

[6] . 2550. . . .

[7] . 2552. -. . : http://-www.matichon.co.th/matichon/view_news. : 24 2555.

[8] Anon, 1983. Moisture Measurement (pp. 329-330). ASAE Standard S 410 , Agricultural Engin-eers Handbook.

[9] Hunt, D. 2001. Farm Power and Machinery. (10th Edition). Ames, Iowa, USA: Iowa State University Press.

[10] Krutz, G., Thomson, L., Claar, P. 1994. Design of Agricultural Machinery. New York, USA: John Wiley and Sons Inc.

[11] Myszka, D.H. 2012. Machines and Mechanisms: Applied Kinematic Analysis, (4th edition). Upper Saddle River, New Jersey: Pearson Education.

[12] Shigley, J.E., Mischke, C.R. 1989 . Mechanical Engineering Design. (5th Edition). New York, USA: McGraw-Hill Book Company.

21 1 (2558), 45-55

45

21 1 (2558) 45-55


MIKE21 A Study of Sediment Transport in Pasak River Using MIKE21 Model 1, 1* Autthaporn Puangpiw1, Wisuwat Taesombat1* 1, , , , 73140 1Department of Irrigation Engineering, Faculty of Engineering at Kamphaengsaen, Kasetsart University - Kamphaengsaen Campus, Nakhon Pathom, 73140

*Corresponding author: Tel: + 66-8 6-383-3289, E-mail: [email protected]

6 MIKE21-HD/ST .. 2556-2557 MIKE21-HD Manningn 0.0286 R2 RMSE 0.85 0.17 m MIKE21-ST MIKE21-HD 100 750 m3 s-1 4 0.12 mm 2,650 kg m-3 0.4 0.0109 m s-1 0.66 0.95 m yr-1 MIKE21-HD/ST .. 2550-2555 2 1) 2) 1 0.76 m yr-1 2 0.22 m yr-1 29

: , , , MIKE21

Abstract

The purpose of this study is to simulate the hydrodynamic and sediment transport conditions in Pasak river between a downstream portion of Rama XI dam and a confluence of Chao Phraya river by an application of MIKE21-HD/ST model. First, observed data of river cross section, discharge, water level, and sediment in Pasak river were collected during year 2013-2014. The result of calibration and verification of MIKE21-HD along Pasak river found that the Manningn roughness coefficient for the whole river is equal to 0.0286, which gave the calculated water level close to the observed values at Nakhon Luang station. It provides statistical index of R2 and RMSE


46

equal to 0.85 and 0.17 m, respectively. The MIKE21-ST in conjugate with MIKE21-HD models were calibrated using steady state condition in the range of discharge between 1 0 0 to 7 5 0 m3 s-1 and measured soil sediment in four places along the river. It found that the average grain size was around 0.12 mm, unit weight of sediment equal to 2,650 kg m-3 , average porosity equal to 0.4 , and settling velocity equal to 0.0109 m s-1 . The calibration results showed that the rate of bed level change has a sedimentation rate in the range of 0.66 to 0.95 m yr-1 and the sedimentation rate is directly proportional to the flow rate which corresponds to the results analyzed by the physical model. Finally, MIKE2 1 - HD/ST model was applied to analyze the annual sedimentation rate during year 2007 - 2012 by dividing into two case studies namely 1 ) steady flow boundary condition and 2 ) unsteady flow boundary condition. The result showed that case 1 the average annual sedimentation rate is around 0.76 m yr-1 while case 2 the average rate is around 0 . 22 m yr-1 . It will be seen that the sedimentation rate of steady flow is more than unsteady flow conditions on average approximately 29%. Since unsteady flow model simulation is more similar to the real flow condition in Pasak river. However, sedimentation rate obtained from mathematical models are significantly higher than the actual because of sediment load input to the model was an average throughout the river. In the fact that sediment load varies unequal both in each month and section of the river.

Keywords: Sediment Transport, Hydrodynamic, Pasak River, MIKE21 Model

1

2

Duc et al. (2004) depth-average finite-volume boundary-fitted grids unsteady hydrodynamic

(2552) 2 CCHE2D

21 1 (2558), 45-55

47

Poulsen et al. (2013) 2D (flood plain model) (floodplain)

Gharibreza et al. (2014) Zohreh MIKE 21 (RS) MIKE21 80% 20% RS 0.07 m 2.45 m

Bourgoin et al. (2007) (Amazon) .. 2000-2003 5 558 828 103 t yr-1 130 km 41%-53% 517 t km-1 yr-1 0.0016 m yr-1 ( 23%)

2 MIKE21 6 51.65 km Figure 1

Figure 1 Study area at Pasak River.

2

2.1

MIKE21 DHI Water Environment and Health 2 2

2.1.1 (MIKE21-HD, Hydrodynamic Module)

1)

2 NavieStokes Equation (Incompressible Fluid) x y FiniteVolume (1) (2) (3)


48

:

p q d

t x y t

(1)

x:

2 2 2

2 2

p p pq gp p qgh

t x h y h x C h

1

xx xy xw

h h q fVVx y

0aw

hp

x

(2)

y:

2 2 2

2 2

q q pq gq p qgh

t y h x h y C h

1yy xy y

w

h h q fVVy x

0aw

hp

xy

(3)

( , , )h x y t = ( d , m) ( , , )d x y t = (m) ( , , )x y t = (m) ( , , )p x y t =

x (m3 s-1 m-1) ( , , )q x y t =

y (m3 s-1 m-1) ( , )C x y = Chezy (m1/2 s-1) g =

(m s-2)

f V = , , , ,x yV V V x y t =

x, y (m s-1)

( , )x y = (s-1) ( , , )ap x y t = (kg m-1 s-2)

w = (kg m-3) ,x y = (m)

t = (s) , ,xx xy yy = x

y (N m-2)

2) (Bathymetry)

MIKE21 Bathymetry 4 Single Grid, Multiple Grids, Curvilinear Grid Flexible Mesh Figure 2 Flexible Mesh Triangles Quadrilateral Element ( resolution) Bathymetry

(A) Single Grid (B) Multiple Grids

(C) Curvilinear Grid D) Flexible Mesh

Figure 2 Type of Bathymetry in MIKE21 model.

2.1.2 (MIKE21-ST, Sand Transport Module)

1) sW

50118s

s gdW

for 50 0.1d mm (4)

21 1 (2558), 45-55

49

3502

50

1100 10s

s gdW

d

for 500.1 1d mm (5)

50

1.1 1sW s gd for 50 1d mm (6)

50d = (mm) s = (kg m-3) g = (m s-2) = , 110-6 (m2 s-1) 2) Van-Rijn (1984)

Van Rijn 2

1: blS

2.1

3500.3

*

0.053 1blT

S s g dD

(7)

T = , h = (m)

*D = ,

2: slS

sl aS f c V h (8)

*

4 sf

wu

D for * 10D (9)

4f su w for * 10D (10)

f =

ac = (kg m-3) V = (m s-1)

2.2

Root mean square error (RMSE) (11)

2

1

n

i

x yRMSE

n

(11)

Goodness-of-fit (Coefficient of

determination, R2) (12)

2

2 1

2 2

1 1

n

i ii

n n

i ii i

x x y yR

x x y y

(12)

x = y = x = y = i = n =

RMSE ( 0) Coefficient of

determination (R2) 1 0.6

2.3

Figure 3


50

Figure 3 Research methodology.

2.3.1

1) (river cross section) 2556 2557 50m 51.65km 1,033 .. (m.MSL)

2) / S.5 (.2+400) S.26 (.45+850) (. 16+650) 2556 2557 Figure 1

3) 6 4 1) (. 51+650) 2) (.38+400) 3) (.30+400) 4) - (.2+100) 2556 Figure 1

2.3.2 MIKE21-HD

1) Bathymetry Flexible Mesh

MIKE21-HD (Node) (Element) Bathymetry

2) MIKE21-HD

1-31 2556 S.26 S.5 (sideflow) S.26 S.5

(Manningn Coefficient) (NK) 2 R2 RMSE

2.3.3 MIKE21-ST

1) 4

(d50)

(s) (porosity) (Ws) (5)

2) MIKE21-ST MIKE21-ST

MIKE21-HD HD/ST (steady flow) (Percentile) 25%, 50%, 75%

21 1 (2558), 45-55

51

95% S.5

3)

( , 2557) .20+700 22+050 .40+300 40+900

Model ratio = 1:100 all axis Velocity ratio = 1:10 Gravity ratio = 1:1 yr () = 1:100 2

100 500 m3 s-1 0.02 mm 4.8 hr 48 hr Figure 4

Figure 4 Flow Chart of Pasak Physical Model.

2.3.4 MIKE21-HD MIKE21-ST

MIKE21-HD MIKE21-ST 2

1) (Steady flow)

(Percentile) 25%, 50%, 75% 95% S.5 6 .. 2550-2555 S.5

2) (Unsteady flow)

MIKE21-HD S.26 S.5 .. 2550-2555 MIKE21-ST 4.1

3 3 1)

MIKE21-HD 2) 3) MIKE21-HD MIKE21-ST

3.1 MIKE21-HD MIKE21-HD

(Bathymetry) Flexible Mesh MIK-E21-HD Figure 5

13.2

Electric Pump

Constant Head Tank

Receiving Tank and by-part tank

Geometric Model

Steady-stage, uniform Flow

Steady-stage, Non-uniform Flow


52

Figure 5 Bathymetry of Pasak River.

(Node) (Element) Bathymetry 11,584 Figure 6 19,252 Figure 7 Element 600 m2

Figure 6 Example Node of Pasak River Bathymetry.

Figure 7 Example Element of Pasak River Bathymetry.

ManningM 35 Manningn 0.0286 (NK) Figure 8 r2 0.85 RMSE 0.17 m MIKE21-HD

Figure 8 Result of MIKE21-HD Model Calibration and Verification at Nakhon Luang station.

3.2

3.2.1. MIKE21-ST

6 50d 0.12 mm

6 50d 1.25 mm

s 2,650 kg m-3 0.4

sW (5) 0.0109 m s-1 MIKE21

3.2.2. MIKE21-HD Steady flow

MIKE 21-HD (Percentile) 25%, 50%, 75% 95% 100, 240, 500 750 m3 s-1 Table 1

Table 1 Computed current velocity for each percentile at S.5 station.

(%)

(m s-1)

25% (100 m3 s-1) 0.76 50% (240 m3 s-1) 1.13 75% (500 m3 s-1) 1.41 95% (750 m3 s-1) 1.50

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1/12/2013

0:00

5/12/2013

0:00

9/12/2013

0:00

13/12/2013

0:00

17/12/2013

0:00

21/12/2013

0:00

25/12/2013

0:00

29/12/2013

0:00

(

.

.)

21 1 (2558), 45-55

53

3.2.3.

MIKE21-HD/ST (Parameter)

Parameter Value

Fluid density, w 1,000 kg m-3 Longitudinal dispersion coefficient, xD 10 m2 s-1 Transversal dispersion coefficient, yD 10 m2 s-1

Erosion coefficient, E 0.4 kg m-2 s-1 Critical shear stress for erosion, e 0.1 N m-2

Settling velocity, sW 0.0109 m s-1 ( ) Critical shear stress for deposition, d 0.1 N m-2

Boundary suspended-sediment concentration, oc 0.0 kg m-3 Bulk density of bottom sediment, s 2650 kg m-3 ( )

2 (deposition area) (erosion area) () () 100, 240, 500 750 m3 s-1 Table 2 100 500 m3 s-1 Table 2

Table 2 Rate of sedimentation in the Pasak River at each flow analyzed by MIKE21 and physical models.

(m yr-1)

100 (m3 s-1) 240 (m3 s-1) 500 (m3 s-1) 750 (m3 s-1)

0.66 0.73 0.82 0.95 0.70 - 0.79 -

3.3 MIKE21-HD MIKE21-ST

6 .. 2550-2555 2 1) Steady flow 2) Unsteady flow Table 3 Steady

flow 0.69 1.01 m yr-1 0.76 m yr-1 Unsteady flow 0.18 0.33 m yr-1 0.22 m yr-1


54

Steady Unsteady 29 Unsteady 1.80 MHz 8.00 GB 26 1

Zohreh 0.0016 0.07 m yr-1

Table 3 Annual sedimentation rate in the Pasak River analyzed by MIKE21 model during year 2007-2012.

(m yr-1)

.. 2550 .. 2551 .. 2552 .. 2553 .. 2554 .. 2555

0.71 0.73 0.66 0.77 1.01 0.69 0.76 0.19 0.21 0.17 0.23 0.33 0.18 0.22

4 MIKE21-HD/ST

MIKE21-HD Manningn 0.0286 6 4

50d 0.12 mm

s 2,650 kg m-3 0.4

sW 0.0109 m s-1 MIKE21-HD MIKE21-ST 100 750 m3 s-1 0.66 0.95 m yr-1 MIKE21-HD/ST .. 2550-2555 2 1) Steady flow 2) Unsteady flow Steady flow

6 S.5 0.76 m yr-1 Unsteady flow 0.22 m yr-1 Steady Unsteady 29

5

21 1 (2558), 45-55

55

..

6 [1] . 2546.

; (). , .

[2] . 2553. , (12). , .

[3] () . 2557. . ,

[4] . 2550. . , .

[5] . 2555. . 17 . 9 - 11 2555.

[6] , , , . 2552. .. 14 . 13 -15 2552.

[7] . 2553. Nash-Sutcliffe Efficiency R2. . 4 2553.

[8] . 2552. 2 MIKE21 HDFM . 14 . 13 - 15 2552.

[9] . 2556. . , .

[10] . 2554. . . : http://www.haii.or.th. 2 2554.

[11] Bourgoin, L.M., Bonnet, M.P., Martinez, J.M., Ko-suth, P., Cochonneau, G., Moreira-Turcq, P., Guyot, J.L., Vauchel, P., Filizola, N., Seyler, P. 2007. Temporal dynamics of water and sediment exchanges between the Curua flood-plain and the Amazon River, Brazil. Journal of Hydrology 335, 140 156.

[12] Duc, B.M., Wenka, T., Rodi, W. 2004. Numerical Modeling of Bed Deformation in Laboratory Channels. Journal of Hydraulic Engineering 130; 894-904.

[13] DHI Water Environment and Health. 2007 a. MIKE 21 & MIKE 3 FLOW MODEL FM, Sand Transport Module, Scientific Documentation. Denmark.

[14] DHI Water Environment and Health. 2007 b. MIKE 2 1 & MIKE 3 Flow Model FM, Hydrodynamic Module, Step-by-Step training guide. Denmark.

[15] DHI Water Environment and Health. 2007 c. MIKE 21 & MIKE 3 Flow Model FM, Hydrodynamic and Transport Module, Scientific Documentation. Denmark.

[16] DHI Water Environment and Health. 2007 d. MIKE 21 ST Non-Cohesive Sediment Transport Module, User Guide. Denmark.

[17] Gharibreza, M., Habibi, A., Imamjomeh, S.R., Ashraf, M.A. 2014. Coastal processes and sedimentary facies in the Zohreh River Delta (Northern Persian Gulf). Catena 122, 150158.

[18] Hardy, R.J., Bates, P.D, Anderson, M.G. 2000. Modelling suspended sediment deposition on a fluvial floodplain using a two-dimensional dynamic finite element model. Journal of Hydrology 229, 202-218.

[19] Poulsen, J.B., Hansen, F., Ovesen, N.B., Larsen, S.E., Kronvang, B. 2013. Linking floodplain hydraulics and sedimentation patterns along a restored river channel: River Odense, Denmark. The Journal of Ecological Engineering 66; 120-128.

[20] van Rijn, L.C. 1984. Sediment Transport, Part I: Bed Load Transport. Journal of Hydraulic Engineering 110, 14311456.

[21] Wu, W., M.ASCE. 2004. Depth-Averaged Two-Dimensional Numerical Modeling of Unsteady Flow and Nonuniform Sediment Transport in Open Channels. Journal of Hydraulic Engineering 130; 1013-1024

Blank PageBlank PageBlank Page

tsae journal vol.21 - 1

Documents