The Effect of Processing Parameters on the Phytochemical Yield of Eurycoma Longifolia

Water Extract Yield

SAIFUL IRWAN ZUBAIRI PMIFT, Grad B.E.M. B. Eng. (Chemical-Bioprocess) (Hons.), UTMM. Eng. (Bioprocess), UTM

ROOM NO.: 2166, CHEMISTRY BUILDING,TEL. (OFF.): 03-89215828,FOOD SCIENCE PROGRAMME,CENTRE OF CHEMICAL SCIENCES AND FOOD TECHNOLOGY, UKM BANGI, SELANGOR

Outline

Introduction Tongkat Ali Background Tongkat Ali Extraction Experimental Design Results and Discussion Conclusion

Introduction

Global Market growing at 15-20% growth USD 70 Billion market for nutraceuticals USD 20 Billion market for phytomedicines

RM4.55 Billion Malaysian Market 80 % imported

Tongkat Ali, Eurycoma Longifolia Anti-Malarial, Aphrodisiac, Energy Boosting Malaysia-MIT Biotechnology Partnership Programme MAVCAP RM20 million invested

Standardisation

Fresh materials (roots, leaves, etc) (2)

Dried powder (10)

Non-standardized extract (25)

Standardized extract (100)

Phytomedicine

Freeze/spray dried extracts (40)

Valueadded

Fresh materials (roots, leaves, etc) (2)

Dried powder (10)

Non-standardized extract (25)

Standardized extract (100)

Phytomedicine

Freeze/spray dried extracts (40)

Valueadded

Source: Prof Dr. Zhari Ismail, USM

Engineering Questions

What are critical process parameters? How do we maximise yield? What are the economically optimal operating

conditions? How can we scale up the process? How do we ensure active ingredient is

present and in the correct amounts i.e. Standardisation

Processing Technology

Based on traditional method

Food Technology oriented

Need to overcome Limited concentration in raw material Solvent cost

More data needed for Optimisation Scale up

Objective and Scope

To develop a mathematical model for the mass transfer in Batch Solid Liquid Extraction of Tongkat Ali

Limited to Single stage water extracts Eurycomanone as marker Optimisation & Scale Up studies

Tongkat Ali background

Biology Chemistry Pharmacology Analysis

Biology and Phytochemistry

Biology

Part of Simaroubaceae family Slow growing plant, 6-7 years to maturity

Phytochemistry

Quassinoids Major Component is Eurycomanone

Alkaloids Highest concentration is 9-Methoxycanthin-6-one

Alkaloids and Quassinoids

Me

Me

OH

CH 2

OH

O

O

OH

O

HOOH

O

H

HH

R

R R

R

R

R

S

R

S

S

MeO

O

N

N

9-Methoxycanthin-6-one Eurycomanone

PharmacologyTraditionally

Used for anti-diarrhoea, postpartum tonic, for treating wounds, boils, and syphilis, anti-pyretic, anti-malarial, anti-ulcer, energy boosting, and aphrodisiac applications.

Root boiled and decoction drunk

Scientifically

Definite anti-malarial properties (Kardono et al, 1991) Increases Testosterone production (Farzaturradiah, 1994) Possibly improves sperm quality (Farzaturradiah, 1994) Confirmed aphrodisiac effect as Viagra (Pihie, 2003) Anti tumour properties (Itokawa, 1992)

Analysis

Large number of compounds >20 Difficulty in identification and quantification

Methods used include: Thin Layer Chromatography UV-Vis Spectrophotometer High Performance Liquid Chromatography Liquid Chromatography/Mass Spectrometry

Compounds

Major quassinoids

eurycomanone longilactone eurycomalactone 15-acetyl-14-

hydroxyklaineanone 6-hydroxy-

eurycomalactone 14,15-

dihydroxyklaineanone 1,12,15-

triacetyleurycomanone

Major alkaloids

9,10-dimethoxycanthin-6-one

10-hydroxy-9-methoxycanthin-6-one

11-hydroxy-10-methoxycanthin-6-one

5,9-dimethoxycanthin-6-one

9-methoxy-3-methylcanthin-5,6-dione

Thin Layer Chromatography

Solvent mixture based on Zhari et al (1999) Only detects Alkaloids at 365nm Does not detect quassinoids

Rf=0.25Light Florescent Green

Rf=0.86Light Florescent Yellow- Green

Rf=0.69Light Florescent Blue

Rf=1.0Light Florescent Blue

UV Vis Spectrophotometer

Can be calibrated at 238 nm for extract concentration

y = 20.053x

R2 = 0.9943

0

5

10

15

20

25

30

35

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6ABS

Con

cen

trat

ion

, C (

g/m

L)

x10-

5

High Performance Liquid Chromatography

Based on Chan et al (1998) First Peak is Eurycomanone, as confirmed by LC/MS

High Performance Liquid Chromatography

Eurycomanone Calibration

y = 3.1087x

R2 = 0.9997

0

10

20

30

40

50

60

0 2 4 6 8 10 12 14 16 18

Area (x1E6)

pp

m

Tongkat Ali Extraction

Process Modelling Optimisation Scale Up

Process

Deionized Water

Extract+ fibre

Slurry

Water Extract

FILTER

EXTRACTOR

SPRAY DRYER

Hot Air

Dehydrated water extract(final product)

HOLDINGTANK

Tongkat Ali

Deionized Water

Extract+ fibre

Slurry

Water Extract

FILTER

EXTRACTOR

SPRAY DRYER

Hot Air

Dehydrated water extract(final product)

HOLDINGTANK

Tongkat Ali

ModellingIn solid liquid extraction 4 phenomena occur:

1. The solvent diffuses into the herb particle 2. The solute is dissolved by the solvent3. The solute diffuses to the surface of the herb particle 4. The solute is dissolved into the bulk solution

The extraction usually is dominated by 3 or 4

1

2

3

4

Cs C*

Cf

Factors affecting extraction

1. Solvent or solvent mixture utilised

2. Solvent to Raw Material Ratio

3. Raw Material Particle size

4. Temperature of Extraction

5. Duration of Extraction

6. Extraction vessel agitation speed

7. Extraction vessel volume

Mass Transfer Model

Yield/Concentration = f (Ratio, Particle Size, Temperature, Duration, Agitation, Volume)

Can be done through:-

Theoretical model Response Surface Methodology Artificial Neural Networks

Theoretical Model

Liquid Mass Transfer Coefficient, kL

Need to determine relationship between all factors

Mass Balance on vessel

Can be rewritten in a exponential form

Agitation increases Mass Transfer Coefficient, kL, to a maximum value

Diffusion of marker, DAB, in liquid is a critical factor as well

)( *fL

f CCAkdt

dCV

tV

kA

fof

ff eCC

CC

Theoretical Model

Solid Diffusion, Ds

If Solid Diffusion, Ds, is the controlling factor, the mass transfer coefficient, kL, is determined by it

Based on work by Schwartzberg and Chao (1982) and Spiro and Selwood (1984)

Estimates of Solid Diffusion for plant material is around 10-10-10-12 m2/s (Doulia et al, 2000)

Theoretical Model

Other factors

Based on Spiro and Selwood (1984) Partition Coefficient, K

Can estimate C*

Weight Fraction of marker/extract, x0

Response Surface Methodology

Statistical-mathematical method Design of Experiment Quantitative Data Builds model Optimises

Good for selecting data No prior knowledge required of process May not be able to extrapolate well Model limited to system studied

Artificial Neural Networks

Model data with unknown structure Good for complex models (de Villiers & Barnard,

1992) Can get good results with proper data selection and

treatment (Baratti et al, 1998) Limited in extrapolation

Optimisation

Method of choosing best operating point to maximise desired output i.e. yield or concentration or profit

Based on the function obtained from the Mass Transfer Modelling, it is likely that we will use One dimensional constrained optimisation, or Multivariable constrained optimisation

Scale Up

Produce an identical process result at a larger production rate i.e. larger extraction vessel

Need defined relationship i.e.

Two key methods

Basis Choose logical basis i.e. P/V Scale up based on chosen basis

Dimensional analysis (pi matrix/Buckingham method) Maintain geometrical similarity and identical relevant dimensionless

numbers i.e. Sherwood and Schmidt for Mass Transfer Reynolds for fluid flow

pilotplant DNDNV

P 2323

Dimensionless Numbers

Reynolds Number

Sherwood Number

Schmidt Number

AB

L

D

DkSh

NDDv aRe

ABDSc

Experimental DesignPreliminary Experiments (1 litre and 5 litre Glassware)

1. Analytical Method development2. Determination of relevant parameters3. Fix value for particle size and agitation rate

Benchscale Experiments (5 litre Pressure vessel)

1. Perform Experiments as per Experimental Design i.e. General Factorial with 1 replicate 2. Determine optimal point3. Central Composite Design around Optimal point4. Calculate Ds, k, NRe and NSc for all experiments5. Build mass transfer model

Scale Up Experiments (300 litre media tank)

1. Base case on optimal point in Benchscale experiments2. Scale up agitation to match P/V3. Test scale up requirement for dimensionless number similarity i.e. NRe and NSc

4. Build Scale up model if necessary

Preliminary Experiments

Based on UV-Vis calibration to total extract weight

Ratio: 20:1, 30:1, 40:1, 50:1, 60:1 w/w

Duration: 30: 60: 90: 120: 150: 180: 210: 240: 270: 300 min

Particle size: Smooth (0.5 – 1.0 mm) and Rough (1 – 3.5 mm)

Volume: 1 dm3 (Small Scale) and 5 dm3(Large Scale)

Sample: 10g (Small Scale) and 50g (Large Scale)

Total of 10 experiments for each scale with multiple samplings

Preliminary Experiments

Hydrodistillation apparatus 5 litre small scale

Soxhlet extraction apparatus 1 litre small scale

Preliminary Experiments ResultsEffect of extraction duration on yield

Yield (%) versus time for same ratio (60:1g/g) at different scale and particle size

5

5.5

6

6.5

7

7.5

8

8.5

9

9.5

0 30 60 90 120 150 180 210 240 270 300

Time,t (min)

Yie

ld (

% g

/g)

Lab-Smooth Large-Smooth

Lab- Rough Large-Rough

Preliminary Experiments ResultsEffect of extraction duration on yield

Percent of extraction accomplished with time (large-scale sample with ratio of 20:1g/g for smooth particles)

0

10

20

30

40

50

60

70

80

90

100

0 30 60 90 120 150 180 210 240

Time, t (min)

Ex

tra

ctio

n A

cco

mp

lish

ed (

%)

Preliminary Experiments ResultsEffect of solvent ratio on yield

Yield versus ratio for 1hr sample at different scales and particle sizes

4

4.5

5

5.5

6

6.5

7

7.5

8

8.5

20 30 40 50 60

Ratio (g/g)

Yie

ld (

%)

1hr-Smooth (Lab) 1hr-Rough (Lab)1hr-Smooth (Large) 1hr-Rough (Large)

Preliminary Experiments ResultsExtraction yield model

Yield versus time for samples with the water to Tongkat Ali ratio of 60:1g/g

y = 1.0864Ln(x) + 2.9712R2 = 0.9741

y = 0.958Ln(x) + 3.6718R2 = 0.9829

y = 1.0674Ln(x) + 1.926R2 = 0.9886

y = 1.061Ln(x) + 1.7311R2 = 0.9896

4

5

6

7

8

9

10

0 30 60 90 120 150 180 210 240 270 300 330 360 390 420

Time,t (min)

Yie

ld (%

g/g

)

Lab scale- Smooth Large scale- Smooth

Lab scale- Rough Large scale- Rough

Preliminary Experiments Results Physical Parameters

Density of Tongkat Ali Root Dry: 0.2g/ml Wet: 0.6 g/ml

UV Absorbance Max: approximately 220-240 nm

Extract mass fraction of Tongkat Ali Root 8-10 % w/w

Fraction of Eurycomanone 0.5% of extract w/w

Preliminary Experiments Results Extraction Parameters

K, partition coefficient 0.9-1.3 (preliminary)

kL, mass transfer coefficient Small Scale, Smooth particle 2 x10-6m/s Small Scale, Rough particle 6 x10-6m/s Large Scale, Smooth particle 2 x10-6m/s Large Scale, Rough particle 6 x10-6m/s

Ds, Solid diffusion (Schwartzberg & Chao, 1984) Small Scale, Smooth particle 9 x 10-12 m2/s Small Scale, Rough particle 80 x 10-12 m2/s Large Scale, Smooth particle 9 x 10-12 m2/s Large Scale, Rough particle 80 x 10-12 m2/s

Preliminary Experiments Discussion

Longer duration leads to higher yield max at 4 to 5 hours 85 % extracted within 30 min and 90% in 1 hr

40:1 ratio best for Smooth and 50:1 ratio best for Rough particles Higher concentration gradient for mass transfer

Similar yield for Small Scale and Large Scale extractions

Higher yield for smaller particle More mass transfer area Lower solid diffusion factor

kL and DS, affected by particle size more than ratio Need to revise calculation on new data

Preliminary Experiments in Progress

Other preliminary work in progress

1. Fine tuning analysis method and apparatus2. Calibration of Standard3. Effect of agitation4. Effect of particle size5. Effect of Temperature6. Temperature effect of marker degradation

Optimal values of agitation and particle size will be used for benchscale experiments

Various particle sizes of Tongkat Ali raw material

Benchscale Experiments Pressurised 5/20 litre heated vessel with agitator

Temperature: 80 C, 90 C, 100 C, 110 C, 120 C Ratio: 20:1, 30:1, 40:1, 50:1, 60:1 w/w Duration: 30, 60, 90, 120, 150, 180, 210, 240,

270,300 min

Total of 25 randomised experiments with multiple samplings 2 replicates and repeated analysis of samples Mass Transfer Model to be built and optimal parameters

determined Central Composite design around optimal point to confirm

model validity

Expected Benchscale Results

Mass Transfer Model Surface Response Model Optimal Operating Point

Properties Mass transfer coefficient, kL

Solid Diffusion, DS

Reynolds number, Re Sherwood number, Sh Schmidt number, Sc

Scale Up Experiments

500 litre Media Tank Based on Optimal Operating point in

Benchscale experiment Experiment repeated at larger scale with

central composite design around optimal point

500 litre Media Tank for Scale up studies

Expected Scale up Results

No significant difference in yield

Differences in duration due to heating process and mixing difference

Scale up relationship to be formed should there be a significance difference

ConclusionFuture Work

1. HPLC Calibration based on analysis from Universiti Sains Malaysia/FRIM

2. Determination of optimal particle size and agitation rate

3. Determination of the effects of temperature on extract degradation

4. The benchscale extraction studies

5. The scale up studies

ConclusionRecommendations

1. To acquire chemical standards or independent calibrations as soon as possible rather than to develop their own standards

2. To develop a theoretical or empirical model of the process as soon as possible as well as to take into account variations caused by organic material

3. To investigate the effects of multiple stage extraction processes to reduce utility usage

4. To perform economic optimisations to determine optimal economic process parameters

5. To simulate the process on a batch simulator such as SuperPro Designer to perform economic evaluation of various design options

Work PlanPhase\Month 2004 1 2 3 4 5 6 7 8 9 10 11 12

Preliminary X X X

Benchscale X X X X X X

Scale up X X X

Phase\Month 2005 1 2 3 4 5 6 7 8 9 10 11 12

Analysis of Data X X X

Experiments X X

Writing X X X X X X

Defence and Publications X X X

THANK YOU FOR YOUR KIND ATTENTION

QUESTION AND ANSWER SESSION

Contribution

Application of Engineering Methodology Physical and chemical parameters Optimal Extraction parameters General Optimization and Scale up method

for Malaysian Herbs