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Optimization of fluoride removal system using Ocimum sp. Leaves and ragi seed husk by applying bio-statistical tools

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R S Upendra at Reva University
R S Upendra
Pratima Khandelwal at New Horizon College of Engineering
Pratima Khandelwal
Zeynab raftani amiri at Sari Agricultural Sciences and Natural Resources University
Zeynab raftani amiri
Amulya Achar
Amulya Achar
Amulya Achar
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Fluoride is a naturally occurring element in water systems and enters food chain mostly through drinking water. The WHO permissible limit of fluoride in water is 1.0 mg/l. At < 1.0 mg/l, it inhibits dental caries, at > 1.0 mg/l causes molting of teeth, lesion of endocrine glands, thyroid, liver and other organs. At still higher concentration (3-6 mg/l), it causes skeletal fluorosis. Existing fluoride removal techniques haven’t been very effective as these remove fluoride only up to 2 mg/l. Therefore, an economically viable, eco-friendly and easy method for defluoridation of drinking water is highly desirable. In the present investigation, Ocimum sp. leaves along with ragi seed husk was used as natural fluoride adsorbents and the process parameters such as absorbent dosage (1-10 g/l), pH (3-12) and contact time (10-150 min) were optimized using Central Composite Design (CCD) of Response Surface Methodology (RSM). The fluoride content in the water was quantitatively determined by UV spectrophotometric analysis and the presence of fluoride in the treated Ocimum sp. leaves were identified with EDAX analysis. RSM design optimized conditions i.e - 5.5 g/l each of Ocimum sp. leaves and ragi seed husk, 6.0 pH and 50 min contact time gave the end values of 0.43 mg/l of fluoride. The optimized values of RSM with respect to the end fluoride content (0.43 mg/l) after treatment process were validated using feed forward model of Artificial Neural Network (ANN). ANN predicted value (0.4250 mg/l) was very close to the optimized experimental value of RSM design (0.43 mg/l) and the error was 0.049. In conclusion, an optimized process was developed for the removal of fluoride from the drinking water using Ocimum sp. leaves and Ragi seed husk as natural fluoride adsorbents. Final concentration of 0.43 mg/l of fluoride was achieved from initial concentration of 10mg/l. Key Words : Fluoride removal, Adsorption, Ocimum sp. leaves and Ragi seed husk, Response Surface Methodology (RSM), Artificial Neural Network (ANN), EDAX analysis
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J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1109
OPTIMIZATION OF FLUORIDE REMOVAL SYSTEM
USING Ocimum SP. LEAVES AND RAGI SEED HUSK
BY APPLYING BIO-STATISTICAL TOOLS
Upendra R.S.*, Pratima Khandelwal1, Amiri Z.R.2, Amulya Achar, Kumari B.G.,
Sowmaya M. and Tejaswini J.1
1. Department of Biotechnology, New Horizon College of Engineering, Marathahalli,
Bangalore, Karnataka (INDIA)
2. Department of Food Science & Technology, Sari Agricultural Sciences and Natural
Resources University, Sari (IRAN)
Received January 10, 2015 Accepted May 23, 2015
ABSTRACT
Fluoride is a naturally occurring element in water systems and enters food chain mostly through
drinking water. The WHO permissible limit of fluoride in water is 1.0 mg/l. At < 1.0 mg/l, it
inhibits dental caries, at > 1.0 mg/l causes molting of teeth, lesion of endocrine glands, thyroid,
liver and other organs. At still higher concentration (3-6 mg/l), it causes skeletal fluorosis.
Existing fluoride removal techniques haven’t been very effective as these remove fluoride only
up to 2 mg/l. Therefore, an economically viable, eco-friendly and easy method for defluoridation
of drinking water is highly desirable. In the present investigation, Ocimum sp. leaves along with
ragi seed husk was used as natural fluoride adsorbents and the process parameters such as
absorbent dosage (1-10 g/l), pH (3-12) and contact time (10-150 min) were optimized using
Central Composite Design (CCD) of Response Surface Methodology (RSM). The fluoride
content in the water was quantitatively determined by UV spectrophotometric analysis and the
presence of fluoride in the treated Ocimum sp. leaves were identified with EDAX analysis. RSM
design optimized conditions i.e - 5.5 g/l each of Ocimum sp. leaves and ragi seed husk, 6.0 pH
and 50 min contact time gave the end values of 0.43 mg/l of fluoride. The optimized values of
RSM with respect to the end fluoride content (0.43 mg/l) after treatment process were validated
using feed forward model of Artificial Neural Network (ANN). ANN predicted value (0.4250
mg/l) was very close to the optimized experimental value of RSM design (0.43 mg/l) and the
error was 0.049. In conclusion, an optimized process was developed for the removal of fluoride
from the drinking water using Ocimum sp. leaves and Ragi seed husk as natural fluoride
adsorbents. Final concentration of 0.43 mg/l of fluoride was achieved from initial concentration
of 10mg/l.
Key Words : Fluoride removal, Adsorption, Ocimum sp. leaves and Ragi seed husk,
Response Surface Methodology (RSM), Artificial Neural Network (ANN), EDAX analysis
INTRODUCTION
Fluoride is a naturally occurring element in
minerals, geochemical deposits and natural water
systems and enters food chains through either
drinking water or eating plants and cereals.
Fluoride is often called a two-edge sword – in
small dosages, it has remarkable influence on the
dental system by inhibiting dental carries, while
in higher dosages More than 1.5 mg/l causes
molting of teeth, lesion of endocrine glands,
thyroid, liver and other organs1. At still higher
concentration, 3-6 mg/l skeletal fluorosis occurs.
The disease affects the bone and
ligaments. According to WHO, the allowable
limit of fluoride in drinking water is 1 mg/l2.
(Table 1). Countries like India, China, Sri Lanka,
West Indies, Spain, Holland, Italy, Mexico,
North and South America are reported to have
high fluoride content in their ground water. In
India, high concentrations of fluoride in ground
water are common in some of the semi-arid areas
of Karnataka, Andhra Pradesh, Rajasthan,
Southern Punjab, Gujarat, Tamil Nadu, Madhya
Pradesh, and Southern Haryana states of India3.
Several areas of Karnataka have high
*Author for correspondence
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1110
concentrations of fluoride in ground water
exceeding 5 mg/l4. There are a number of cases of dental and skeletal fluorosis in these areas
(Table 2).
Table 1 : Permissible limit of fluoride in drinking water prescribed by various organizations
S/N Name of the organization
Desirable
limit (mg/l)
1 Bureau of Indian Standards (BIS)
0.6-1.2
2 Indian Council of Medical Research (ICMR) 1.0
3
The Committee on Public Health Engineering Manual and
Code of Practice, Government of India 1.0
4
World Health
Organization (International Standards for
Drinking Water) 1.0
Table 2 : Percentage of water source with different fluoride content in the stated districts
and percentage of villages with the cases of fluorosis5.
S/N District Taluk (samples)
having conc.
in mg/l
Villages
with
fluorosis
cases
<
1.5
mg/l
1.5
-
3.0
mg/l >3.0 mg/l
1
Kolar
Bangarpet (257)
85
15
00
15
Gudibanda (58)
81
19
00
35
2
Chitradurga
Hiriyur (173)
45
53
02
28
Hosadurga
73
22
05
22
3
Bijapur
Bagalkot(100)
63
32
05
20
Jamakhandi(73)
89
08
03
00
High profile of fluoride in shallow zone
ground water is due to the geochemical
disposition in the vicinity of the ground water
extraction structures. The toxicity of fluoride is
also influenced by high ambient temperature,
alkalinity, calcium and magnesium contents in
the drinking water. The most commonly used
methods for the defluoridation of water are
adsorption, ion exchange, precipitation,
Donnan dialysis and electrodialysis. Among
these methods, adsorption is the most widely
used method for the removal of fluoride from
water6. Several techniques have been
developed for removal of fluoride from
drinking water by adsorption and precipitation
processes. Though this technique has been
extensively used in India, but due to its high
cost, alkaline pH and large dosage, it was not
suitable for field application. It is also not
suitable for drinkable purpose as it removes
fluoride only up to 2 mg/l. Therefore, an
economically viable, eco friendly and easy
method for defluoridation of drinking water is
highly desirable. No research document was
found on using Ocimum sp. leaves as a natural
bio-adsorbent to remove fluoride.
In the present investigation, Ocimum sp. leaves
along with ragi seed husk was used as natural
fluoride bio-adsorbents and the process
parameters such as bio-absorbent dosage (1-10
g/l), pH (3-12) and contact time (10-150 min)
were optimized using Central Composite
Design (CCD) of Response Surface
Methodology (RSM). The fluoride content in
the water was quantitatively determined by UV
spectrophotometric analysis and the presence
of fluoride in the treated Ocimum sp. leaves
were identified with EDAX analysis. RSM
design optimized conditions i.e - 5.5 g/l each
of Ocimum sp. leaves and ragi seed husk, 6.0
pH and 50 min contact time had given the end
values of 0.43 mg/l of fluoride. The optimized
values of RSM with respect to the end fluoride
content (0.43 mg/l) after treatment process
were validated using feed forward model of
Artificial Neural Network (ANN). ANN
predicted value (0.4250 mg/l) was very close
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1111
to the optimized experimental value of RSM
design (0.43 mg/l) and the error was (0.049).
In conclusion, an optimized process was
developed for the removal of fluoride from the
drinking water using Ocimum sp. leaves and
Ragi seed husk as natural fluoride bio-
adsorbents. Final concentration of 0.43 mg/l of
fluoride was achieved.
AIMS AND OBJECTIVES
Removal of fluoride from portable drinking
water using Ocimum sp. leaves and ragi seed
husk as a natural bio-adsorbents. Optimization
of the fluoride removal process by applying
RSM and ANN design.
MATERIAL AND METHODS
All the chemicals and reagents used in this
study were of Analytical Grade (Merck and
Qualigens).
Collection of bio-adsorbent
Ocimum sp. plants were purchased from the
Lalbagh Botanical garden Bangalore, India.
Ragi seeds husk was purchased from local
market. These were kept at room temperature
for further bio-adsorption studies.
RSM experimental design and bio-
adsorption studies
A three factor Central Composite Design
(CCD) of RSM was generated with the design-
expert 9.0.0.7 software. The model applied
was CCD and a second order polynomial
response equation gives the final content
fluoride in treated water samples.
Y= bo +∑biXi + ∑bi2Xi2 + ∑bijXiXj
Where Y is lovastatin yield, bo is the intercept,
bi is the coefficient for linear direct effect, bij is
the coefficient for interaction effect. Bio-
absorbent dosage (1-10 g/l), pH (3-12) and
contact time (10-150 min) were the principle
input variables, the factor levels were coded as
−1 (low), 0 (central point) and 1 (high).
Adsorption studies were carried out as a batch
experiments (triplicate) based on RSM CCD as
shown in Table 1, with in the 250 ml conical
flask with the volume of 100 ml as a test
solution. The solution was then filtered and the
residual fluoride ion concentration was
estimated through UV spectrometric analysis7.
Quantification of fluoride by UV
spectrometric analysis
Treated and prepared water sample were
analyzed qualitatively by measuring the
absorbance for the presence of fluoride at
wavelength 520 nm in three replicates using
pure fluoride (Merck) as a standard in
UV/Visible spectrophotometer. (Shimadzu,
Model no UV-2450 and Software UV-probe
2.21). A calibration curve was prepared from
the plot of absorbance against concentration of
standard solutions. The concentrations of the
sample solutions were determined from the
plot8.
Characterization of bio-adsorbent by SEM
and EDAX analysis
After the adsorption process the Ocimum sp.
leaves used as bio-adsorbent in the study was
examined by SEM experiments using Philips
Scanning Electron Microscope. The presence
of elemental silver in bio-adsorbent was
analyzed using energy dispersive spectroscopy
attached to SEM9.
Artificial Neural Network (ANN)
In this study, Neural Network MATLAB R
2011a mathematical software was used for
simulation.10 The same experimental data of
RSM design was employed in designing the
artificial neural network. The input variables
were bio-absorbent dosage (1-10 g/l), pH (3-
12) and contact time (10-150 min). The
optimum adsorption capacity was used as a
target. The data were randomly divided into
three groups, 70% in the training set, 15% in
the validation set and 15% in the test set.
Trainlm is a training function selected and it is
a network training function that updates weight
and bias values according to the Levenberg-
Marquardt algorithm. All variables and
response were normalized between 0 and 1 for
the reduction of network error and higher
homogeneous results.11-16
The normalization equation applied was as
follows : Ya-Ymin
Yn=
Ymax-Ymin
Yn, Ya, Ymin and Ymax were normalized value,
actual value, minimum value, and maximum
value, respectively.17-21
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1112
RESULTS AND DISCUSSION
Response surface methodology
Based on the experimental results of CCD in
Table 3, a quadratic polynomial was established
to identify the relationship between adsorption
capacity and process variables. Final Equation in
terms of coded factors represents the end fluoride
content End fluoride content = +0.72-0.84* A -
0.84* B+2.09* C+0.59* D-0.61* AB-0.56* AC -
0.12* AD-0.050* BC-0.90* BD+0.84* CD+0.84
* A^2+0.65* B^2+2.07* C^2+2.54* D^2.
(Table 3) The experimental results and
the predicted values obtained from the model
equation were compared. The Model F-value
of 14.49 implies the model is significant.
There is only a 0.01% chance that an F-value
this large could occur due to noise. Values of
"Prob> F" less than 0.0500 indicate model
terms are significant. In this case A, B, C,
AB, BD, A^2, B^2, C^2, D^2 are significant
model terms (Table 3). The predicted values
matched the experimental values reasonably
well with R-Squared = 0.9311. This implies
that 93.11% of the variations for adsorption
capacity are explained by the independent
variables, and this also means that the model
does not explain only about 6.89% of
variation. In addition, the value of adjusted
determination coefficient (Adj R-Squared
=0.8669) was also high, showing a
significance of the model.
Table 3 : ANOVA for response surface quadratic model fluoride content
ANOVA for Response Surface Quadratic model
Analysis of variance table [Partial sum of squares - Type III]
Source Sum of
squares df Mean
square F
value p-value
Prob> F
Model
116.44 14 8.32 14.49 < 0.0001
significant
A
-
Ocimum
sp.
leaves 9.70 1 9.70 16.89 0.0009
B
-
Ragi seed husk
9.74 1 9.74 16.97 0.0009
C
-
PH
20.70 1 20.70 36.05 < 0.0001
D
-
Contact time
1.66 1 1.66 2.89 0.1098
AB
5.93 1 5.93 10.33 0.0058
AC
2.21 1 2.21 3.85 0.0687
AD
0.11 1 0.11 0.18 0.6742
BC
0.017 1 0.017 0.030 0.8638
BD
5.65 1 5.65 9.84 0.0068
CD
2.21 1 2.21 3.85 0.0685
A^2
19.32 1 19.32 33.65 < 0.0001
B^2
11.48 1 11.48 19.99 0.0004
C^2
23.24 1 23.24 40.48 < 0.0001
D^2
34.67 1 34.67 60.39 < 0.0001
Residual
8.61 15 0.57
Lack of
f
it
8.61 10 0.86
Pure
e
rror
0.000 5 0.000
Cor
t
otal
125.05 29
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1113
Quantification of fluoride by UV spectro
metric analysis
Treated and prepared water sample were
analyzed quantitatively by measuring the
absorbance for the presence of fluoride at
wavelength 520 nm in three replicates using pure
fluoride (Merck) as a standard in UV/Visible
spectrophotometer. (Shimadzu, Model no UV-
2450 and Software UV-probe 2.21) the end
fluoride content of each run was mentioned in
the Table 4.
Characterization of bio-adsorbent by SEM
and EDAX analysis
Scanning electron microscope is one of the
powerful tools to identify the adsorbed content
of fluoride on the bio-adsorbents. Further,
elemental analysis is carried out to confirm the
presence of fluoride in the bio-adsorbents used.
EDAX analysis of Ocimum sp. leaves bio-
adsorbent shows an intense signal at 1 keV
indicating the presence of elemental fluoride in
the Ocimum sp. leaves bio-adsorbent. (Fig. 1)
Fig. 1 : EDAX analysis of Ocimum sp. leaves representing the fluoride element
Artificial Neural Network
The optimal architecture of ANN model in this
case is shown in Fig. 2. It has three-layer
ANN, with tangent sigmoid transfer function
(tansig) at hidden layer with 11 neurons and
linear transfer function (purelin) at output
layer. The MSE value was found to be 0.0003.
A regression analysis between ANN outputs
and the experimental data was carried out. This
ANN model indicated a precise and effective
prediction of the experimental data with a
correlation coefficient of 0.999, 0.999, 0.995
and 0.999 for training, validation, testing and
all data, respectively. (Fig. 3) The simulated
value of end fluoride content as predicted by
Feed forward model (0.4250 mg/l) of ANN
was in close agreement with the experimental
values (0.43 mg/l) and accurately matching
with the predicted value of central composite
design of RSM (Table 4).
Table 4 : Central composite design matrix of three variables and the experimentally
determined, RSM model predicted and ANN model predicted adsorption capacity
Run Ocimum
Leaves g/l
Ragi seed
husk g/l pH Contac
t time
Min
Concentration of Fluoride
mg/l Error
Experi
mental
value
RSM
predicted
ANN
predicted
1
1.00
1.00
3.00
10.00
5.375
5.141508
5.335174
0.039
2
1.00
10.00
3.00
10.00
5.22
5.256838
5.181653
0.0383
3
10.00
1.00
3.00
10.00
5.67
5.254838
5.634824
0.0351
4
-
3.50
5.50
6.00
50.00
4.86
5.049988
4.856290
0.0037
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1114
5
1.00
1.00
3.00
100.00
2.96
2.723321
2.954555
0.0054
6
10.00
10.00
9.00
100.00
0.5
7
0.535175
0.5
59591
0.0104
7
10.00
1.00
9.00
10.00
4.11
4.336508
4.079444
0.0305
8
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.0049
9
5.50
5.50
6.00
150.00
3.12
2.271654
3.071939
0.0480
10
5.50
5.50
12.00
50.00
4.55
3.867488
4.651360
0.101
11
1.00
10.00
3.00
100.00
2.84
2.745175
2.834253
0.00574
12
10.00
10.00
3.00
100.00
0.051
0.269004
0.387760
0.0122
13
1.00
1.00
9.00
10.00
5.52
5.514614
5.519273
0.00072
14
1.00
10.00
9.00
10.00
6.85
6.358008
6.664666
0.1853
15
14.50
5.50
6.00
50.00
1.93
1.395671
1.974661
0.044
16
5.50
14.50
6.00
50.00
2.27
2.007171
2.251866
0.0181
17
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.0049
18
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.0049
19
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.0049
20
5.50
5.50
0.00
50.00
2.89
3.228171
2.843741
0.0462
21
10.00
1.00
9.00
100.00
0.35
0.525821
0.354684
0.00468
22
5.50
-
3.50
6.00
50.00
1.954
1.877488
1.942772
0.01122
23
1.00
10.00
9.00
100.00
3.675
4.303821
3.670765
0.004235
24
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.0049
25
10.00
1.00
3.00
100.00
0.364
0.987675
0.349230
0.014797
26
10.00
10.00
9.00
10.00
3.99
4.439338
3.692805
0.297195
27
10.00
10.00
3.00
10.00
4.86
4.629642
4.817561
0.42439
28
1.00
1.00
9.00
100.00
3.1909
3.552942
3.439222
-
0.24832
29
5.50
5.50
6.00
-
50.00
8
.09
8
.594004
8.168846
-
0.07885
30
5.50
5.50
6.00
50.00
0.43
0.43
0.425098
0.004902
Fig 2 : Topology of Feed Forward Model of ANN with input layer, hidden layer and output layer
J. Environ. Res. Develop.
Journal of Environmental Research And Development Vol. 9 No. 04, April-June 2015
1115
Fig. 3 : ANN regression plots showing training, validation, target and all regression values
CONCLUSION
Ocimum sp. leaves along with ragi seed husk
was used as natural fluoride adsorbents and the
process parameters such as absorbent dosage
(1-10 g/l), pH (3-12) and contact time (10-150
min) were optimized using Central Composite
Design (CCD) of Response Surface
Methodology (RSM). The optimized values of
RSM with respect to the end fluoride content
(0.43 mg/l) after treatment process were
validated using feed forward model of
Artificial Neural Network (ANN). ANN
predicted value (0.4250 mg/l) was very close
to the optimized experimental value of RSM
design (0.43 mg/l) and the error was 0.049. In
conclusion, an optimized process was
developed for the removal of fluoride from the
drinking water using Ocimum sp. leaves in
combination with ragi seed husk as natural
fluoride adsorbents. Final concentration of
0.43 mg/l of fluoride was achieved.
ACKNOWLEDGEMENT
We wish to express our sincere gratitude to
The Chairman and the Principal, New Horizon
College of Engineering, Bangalore, India for
providing all facilities to undertake research
work. We extend our sincere thanks to VGST,
Bangalore, India for their funding under TRIP
programme.
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... The biggest challenge in the bioprocess was providing optimal fermentation conditions for the economically feasible bioprocesses (Upendra et al., 2013). Response surface methodology (RSM) is an effective and convenient method for designing experiments, building models, and screening key factors of process conditions (Kar et al., 2009;Upendra and Khandelwal, 2021;Upendra et al., 2015b). RSM employed with the hybrid artificial neural network-genetic algorithm (ANN-GA) will be able to address the nonlinear relationship between the actual and coded factors (Upendra et al., 2014a). ...
... RSM is a pool of mathematical and modeling tools applied in building an experimental model design to analyze the response impact of multivariable process parameters on the overall process yield (Kar et al., 2009;Upendra et al., 2014bUpendra et al., , 2015b. Type of carbon source, type of nitrogen source, pH, temperatures, and agitation of the fermentation process were the most important process parameters influencing the bacteriocin yield (Gautam and Sharma, 2009;. ...
Bacteriocin production optimization applying RSM and hybrid (ANN-GA) method for the indigenous culture of Pediococcus pentosaceus Sanna 14
Article
Full-text available
  • Jan 2021
The present study optimized the submerged fermentation conditions of Pediococcus pentosaceus Sanna 14 culture to improve bacteriocin yield by applying response surface methodology (RSM) and hybrid artificial neural networkgenetic algorithm (ANN-GA). A full factorial central composite design (CCD) of RSM was applied to assess the effect of four principle variables, i.e., pH (4.0–8.0), agitation (120–220 rpm), sucrose (20–40 g/l), and peptone (5–20 g/l), on the yield of bacteriocin. The RSM optimized the experimental results of pH (7.0), agitation (200), sucrose (40 g/l), and peptone (20 g/l), and supported a higher yield (2.4 g/l) of bacteriocin and was validated applying ANN-GA methodology. The RSM bacteriocin yield (2.4 mg/l) was found to match with the ANN-predicted yield (2.4 mg/l). GA results confirmed the genetic fitness of the culture of P. pentosaceus Sanna 14 during fermentation. The present study registered a sixfold increase in bacteriocin yield (2.4 mg/l) compared to the yield (0.4 mg/l) of the unoptimized process conditions.
... (Nagaraj et al., 2020) Biopolymer such as raw chitosan also exhibits a low defluoridation capacity and further modifications of these biopolymer materials with metal impregnation or through composite formation have demonstrated to be effective methodologies for improving the defluoridation performance (Prabhu and Meenakshi, 2015;Ma et al., 2014;Chaudhary et al., 2019). Several natural materials like agricultural wastes Bibi et al., 2017), sawdust Singh et al., 2019), microbial biomass Annadurai et al., 2019), aquatic plants (Karmakar et al., 2018;Upendra et al., 2015) have been utilized for the removal of fluoride removal. However, their practical implementations for the removal of highly contaminated water remain unsuitable. ...
... Though the results were unsatisfactory for on-field operations, such natural sorbents open up the scope for defluoridation using the widely available natural aquatic plants. In another work, the leaves of Ocimum sp. were studied together with finger millet (ragi seed) husk for defluoridation (Upendra et al., 2015). A fluoride concentration of 10 mg/L was treated with 5.5 g/L quantity of each adsorbent (Ocimum leaves and ragi seed husk) for a contact time of 50 min. ...
Techno-economical assessment of defluoridation of water
Chapter
Full-text available
  • Jan 2021
Fluoride while beneficial for human health at low concentration shows harmful impacts on skeletal fragility, kidney, nerve damage, etc., if consumed in excess. Several techniques were applied for the removal of excess fluoride from water such as adsorption, membrane separation, ion exchange, precipitation, etc. The selection of a particular technique depends on its specific advantages and disadvantages. These techniques were initially developed at a lab scale and further evolved as pilot plants. Successful pilot plant studies were subsequently developed into community-based applications for fluoride removal. Some of these processes not only removed fluoride but also other unwanted species, namely, phosphate, arsenic, bicarbonates. These plants are extremely popular in various Asian and African countries as they are useful for providing safe drinking water to underprivileged people. In such studies, adsorption was one of the popular methods that employed various adsorbents and the overall cost was about 20 USD/m³. Similarly, precipitation methods like Nalgonda technique were also successfully applied at the cost around 15 USD/m³. Electrocoagulation using aluminium electrode is also a popular method having an operational cost of about 1 USD/m³, whereas equipment cost is substantially high. On the other hand, membrane separation has the highest installation cost of about 800k USD and operational cost of about 0.2 USD/m³. This chapter is specifically discussing about the economics, cost analysis of water defluoridation, and possible applicability.
... MATLAB R2011a software is widely applied by many biotech researchers for process optimization experiments. MATLAB is a versatile programming language that supports a multi-paradigm computing environment [15]. Already, huge potential of the work in isolation, characterization of lovastatin producing fungi and optimization of the SmF processes were available in the literature. ...
Biosimulation studies-based optimization of fungal derived Lovastatin
Article
  • Jan 2021
he preset study aimed to optimize downstream process (DSP) conditions of fungal derived secondary metabolite named lovastatin for the submerged state fermentation (SmF) cultures of strain Aspergillus terreus-11045. A five factorial central composite design methodology (CCD) of Response Surface design Methodology (RSM) employed to enhance impactful factors of fungal derived lovastatin biosynthesis, i.e Ethyl acetate (200–1000 mL) pH (2.0–10.0), Temperature (30–38oC), Agitation (120–200 rpm), Incubation Time (0.5–2.5 h). The optimized trail of RSM design was validated with artificial neural network (ANN). RSM trail of 750 mL of ethyl acetate, pH 2.0, temperature 38 oC, agitation speed-160 rpm and incubation time-2 h, has conferred higher yield (3.453 mg/g dry matter). ANN validated yield (3.447 mg/g dry mass) was in congruence with the experimental values (3.453 mg/g dry mass) and more than the predicted value-CCD-RSM (3.406 mg/g dry mass). The standardized conditions of the present study reported the lovastatin yield (3.453 mg/g dry mass) approximately by 3.5 times compared to that of (952.7?mg/L) lovastatin reported earlier, similarly the lovastatin yield is 3.5 times higher than the lovastatin yield (0.997 mg/g dry matter) of suboptimal SmF DSP of Aspergillus terreus MTCC-11045. Keyword: Aspergillus terreus; Lovastatin; Downstream process; Response Surface Methodology; Artificial Neural Network.
... Data analysis was carried out by the standard procedure of Plackett-Burman experimental design along with the design expert software (8.0.7.1) 25, 26 . Optimization studies were carried out as a batch experiments based on CCD of RSM as shown in Table 2 within the 250 ml conical flask with the volume of 100 ml as a production media 27,28 . Downstream processing of terreic acid: At the end of fermentation process, pH of the final fermentation broth was measured and adjusted to 2.0 using dilute HCl (1N). ...
OPTIMIZATION OF SUBMERGED STATE FERMENTATION PROCESS FOR TERREIC ACID PRODUCTION APPLYING BIOSTATISTICAL TOOLS
Article
Full-text available
  • Mar 2016
A quinine epoxide called terreic acid a secondary metabolite produced by the fungus Aspergillus terreus, is considered to be the “next generation antibiotic” due to its broad range antibiotic specificity. The antibiotic property of terreic acid was recognized more than 60 years ago. Previously many researchers were attempted different techniques and conditions for obtaining terreic acid. Very scanty research has been carried out on the optimization of SmF process for the production of terreic acid. Mathematical designs and biostatistical tools were never been used in the process optimization studies. In the present investigation, the focus is on optimization of various nutrients factors of Aspergillus terreus MTCC-11395; SmF cultures, namely Dextrose, Sucrose, Starch, Mannitol, Yeast extract, Dried yeast, L-tyrosine, Acetic acid, Malt extract, Sodium nitrate and process parameters such as pH, Agitation (Rpm), Temperature, Inoculum volume, Fermentation time considering, Agar (dummy1), Agarose (dummy2), Mineral oil (dummy3) and Water (dummy4) as a four dummy variables, for enhanced production of terreic acid applying Plackett-Burman design (PBD) and Response Surface Methodology (RSM). The terreic acid in the fermented broth was confirmed by bioassay and estimated through UV spectrophotometry (214nm). PBD identified Sucrose, L-tyrosine, Agitation (rpm) and Inoculum volume were the principal factor influencing the production of terreic acid (0.463 mg/ml). Further, PBD identified principle factors were optimized applying Central Composite Design (CCD) of Response Surface Methodology (RSM). An optimized medium containing 65 g/L of sucrose, 1 g/L of L-tyrosine, Agitation 180 RPM and 15% of inoculum volume was found to support high yield (0.620 mg/L) of terreic acid under SmF process. Keywords: Aspergillus terreus, terreic acid, Submerged fermentation process, Plackett-Burmann design, Response Surface Methodology, Bioassay
Sustainable green approaches in sorption-based defluoridation: Recent progress
Chapter
  • Jan 2021
One of the adverse environmental impacts of anthropogenic activities is the occurrence of toxic pollutants in freshwater sources. Fluoride is one such persistent pollutant causing serious hazards to living organisms, humans in particular. Ingestion of fluoride in higher concentrations over prolonged durations is said to cause possibilities of dental and skeletal fluorosis and can also lead to lesions of the organs. Unfortunately, above 200 million people worldwide are at the risk of consuming fluoride-contaminated water above the acceptable and tolerable levels. To mitigate such precarious impacts, several physical, chemical, and biological defluoridation techniques have been explored and implemented around the globe. Adsorption is one of the most steadfast techniques employed as it is simple in operation, reliable, and cost-effective. Further, this technique provides a wider choice of material sources known as adsorbents which can be rationally designed to suit the application. To this degree, nature provides a greener choice of several adsorbents which are readily available and do not require high-end synthetic requirements. These green sorbents are inclusive of natural materials, biomaterials, or biosorbents, carbonaceous materials from wastes, agricultural, and industrial by-products. These materials are cheap, eco-friendly, and do not pose secondary toxicity concerns compared to many other synthetic adsorbents. Additionally, these adsorbents can be modified with physical and chemical treatments to enhance their defluoridation performance. This chapter intends to highlight the recent progress made toward the use of naturally available green adsorbents for the adsorption of fluoride ions in an eco-friendly manner.
Comprehensive and critical appraisal of plant-based defluoridation from environmental matrices
Article
Fluoride is recognized as one of the global environmental threats because of its non-biodegradable nature and long-term persistence in the environment. This has created the dire need to explore various defluoridation techniques (membrane process, adsorption, precipitation, reverse osmosis, ion exchange, and electrocoagulation). Owing to their cost ineffectiveness and high operational costs, these technologies failed to find any practical utility in fluoride remediation. Comparatively, defluoridation techniques involving the use of low-cost plant-derived adsorbents and fluoride phytoremediators are considered better alternatives. Through this review, an attempt has been made to critically synthesize information about various plant-based bioadsorbents and hyperaccumulators from existing literature. Moreover, mechanisms underlying the fluoride adsorption and accumulation by plants have been thoroughly discussed that will invigorate the researchers to develop novel ideas about process/product modifications to further enhance the removal potential of the adsorbents and plants. Literature survey unravels that various low-cost plant-derived adsorbents have shown their efficacy in defluoridation, yet there is an urgent need to explore their pragmatic application on a commercial scale.
Bio-inspired materials for defluoridation of water: A review
Article
The polluted water sources pose a serious issue concerning the various health hazards they bring along. Due to various uncontrolled anthropogenic and industrial activities, a great number of pollutants have gained entry into the water systems. Among all the emerging contaminants, anionic species such as fluoride cause a major role in polluting the water bodies because of its high reactivity with other elements. The need for water remediation has led the research community to come up with several physicochemical and electrochemical methods to remove fluoride contamination. Among the existing methods, biosorption using bio and modified biomaterials has been extensively studied for defluoridation, as they are cheap, easily available and effectively recyclable when compared to other methods for defluoridation. Adding on, these materials are non-toxic and are safe to use compared to many other synthetic materials that are toxic and require high-cost design requirements. This review focuses on the recent developments made in the defluoridation techniques by biosorption using bio and modified biomaterials and defines the current perspectives of fluoride removal specifically using biomaterials.
Artificial Neural Network: A novel method for optimization of Bioproducts and Bioprocesses: A critical review
Article
Full-text available
  • Jan 2014
Artificial Neural Network (ANN) is a computerized program designed to simulate the process in which the Central Nervous System (CNS) functions. In a recent time ANN being increasingly used in biotechnology and pharmaceutical research to predict the non-linear relationship between casual factors and response variables. ANN has a remarkable ability to derive meaningful information from complicated data. Medium formulation and optimization is essential for the success of an industrial fermentation as it directly affects the time and cost of bio-products and most of the optimization methods like conventional, Plackett burmann and Response surface methodologies finds a multiobjective simultaneous optimization problem which can be solved through ANN. The potential application of ANN methodology in the Biotechnology and pharmaceutical science, range from interpretation of analytical data, optimization of drug production and drug dosage, optimization of bioremediation process of polluted, waste water treatment, and also from design through bio-pharmacy to clinical pharmacy. Present review focuses on introduction to ANN, ANN types, ANN working model, various software tools used and some real time applications of ANN in optimization of bioproducts and bioprocess.
QUANTITATIVE MICROBIAL RISK ASSESSMENT IN THE MANAGEMENT OF Escherichia coli STRAINS VIA DRINKING WATER
Article
Full-text available
  • Jul 2013
Quantitative Microbial Risk Assessment (QMRA) is a process, analogous to chemical risk assessment of estimating human health risks due to exposures to microbial pathogens. Now -a - days Escherichia coli strains have emerged as water borne pathogens. It has been involved many water borne outbreaks across the world. The predominant outbreaks caused by the strain Escherichia coli O157:H7.It belongs to the member of the Enterohemorrhagic Escherichia coli. In order to manage Escherichia coli strains and to devise approaches to reduce the public health risk posed, many national and international groups have applied QMRA techniques to model the risk posed by Escherichia coli O157:H7 on drinking water. While multiple sources and routes of transmission of this pathogen are now recognized, contaminated drinking water serves as one of the important vehicle of the pathogen and continue to be linked to outbreaks across both developed and developing countries. This paper reviews these quantitative microbial risk assessments and their application in managing the risk posed by Escherichia coli O157: H7 on drinking water.
AN EPIDEMIOLOGICAL STUDY OF SKELETAL FLUOR-OSIS IN SOME VILLAGES OF CHANDRAPUR DISTRICT, MAHARASHTRA, INDIA
Article
Full-text available
  • Mar 2013
Fluorosis is an important public health problem in certain parts of India. Chandrapur is one of the fluorosis endemic district of Maharashtra. An investigation was undertaken in three villages of study area to assess the clinical symptoms of skeletal fluorosis and in turn to find out the severity of the disease. A door to door approach with face to face interviews of the study population was carried out and classified into three age groups i.e. 30-45 yrs (529), 46-60 yrs (387) and 61 yrs to above (262) for different grades of clinical symptoms and collected information was entered in a precoded questionnaire. Fluorosis was diagnosed clinically and as well as the drinking water samples were tested for fluoride level. The concentration of fluoride in drinking water varies from 0.66 to 5 mg/l. Among the 1178 subjects (572 males and 606 females) surveyed 367 (31.15%) patients exhibited the symptoms of different grades of skeletal fluorosis. The skeletal symptoms including tingling and numbing of extremities, joint pain in both upper and lower limbs, unable to bend, unable to bend neck, back pain, shoulder pain and knock-knee. Prevalence of skeletal fluorosis was found to be 20.22% (30-45 yrs), 34.62% (46-60 yrs) and 48.09% (61 yrs to above). A direct association existed between age and severity of skeletal fluorosis. A higher prevalence was recorded in the older one (61 yrs to above). With advancing age, the prevalence of skeletal fluorosis increased and it was more prevalent among males (36.18%) than the females (26.40%).
PREVALENCE AND SEVERITY OF DENTAL FLUOROSIS AMONG SCHOOL STUDENTS IN DONGARGAON OF CHANDRAPUR DISTRICT, MAHARASHTRA, INDIA
Article
Full-text available
  • Oct 2013
The purpose of this study was to assess the exposure of fluoride in drinking water and evaluate the prevalence and severity of dental fluorosis among the school students in Dongergaon village of Warora Tehsil, Chandrapur district, Maharashtra, India. Total 178 (93 boys and 85 girls) students of 6-14 year aged were clinically examined using Dean's Index. Water samples from dugwell, borewell and groundwater stream were analyzed for fluoride ion concentration by ion selective electrode. The fluoride concentration was found to be 0.53-5 ppm which was more than permissible limit. Overall 78% of students showed some grades of dental fluorosis with Community Fluorosis Index (CFI) 1.847. Gender wise percentage of dental fluorosis was more in girls (78.8%) as compared to boys (77.4%). 21.9% of students were normal, 5% questionable, 10.6% very mild, 25.8% mild, 29.8% moderate and 6.7% had severe fluorosis. The severity of fluorosis was found more in girls (66.6%) than in boys (33.3%). The prevalence and severity increased with the age. There was high prevalence of mild to severe fluorosis in school students of Dongargaon village.
Adsorption Isotherms on Fluoride Removal: Batch Techniques
Article
Full-text available
  • Jan 2010
The ability of cynodon dactylon based thermally activated carbon to remove fluoride from aqueous solution has been investigated. The batch adsorption studies were carried out at neutral pH as the functions of contact time, adsorbent dose, adsorbate concentration, temperature and effect of co-anions, which are commonly present in water. The rate of adsorption was rapid during initial 105 minutes and attained equilibrium. Adsorption isotherms have been modeled by Langmuir, Freundlich, Temkin and Redlich–Peterson isotherms. The data indicate that prepared adsorbent surface sites are heterogeneous in nature and that fits into a heterogeneous site binding model. The present system followed the Redlich–Peterson isotherm as well as Langmuir adsorption isotherm model. The enthalpy change (∆H°) and entropy change (∆S°) for the adsorption reaction are calculated as +8.725 kJ/mol and +0.033 J/mol K respectively. The adsorption is endothermic in nature. Instrumental analysis XRD, FT-IR and SEM gives the conformation about the fluoride binding ability of adsorbent. Field studies were carried out with the fluoride containing water sample collected from a fluoride-endemic area in order to test the suitability of the sorbent at field conditions and obtained good success rate.
Piper nigrum Leaf and Stem Assisted Green Synthesis of Silver Nanoparticles and Evaluation of Its Antibacterial Activity Against Agricultural Plant Pathogens
Article
Full-text available
Utilization of biological materials in synthesis of nanoparticles is one of the hottest topics in modern nanoscience and nanotechnology. In the present investigation, the silver nanoparticles were synthesized by using the leaf and stem extract of Piper nigrum. The synthesized nanoparticle was characterized by UV-vis spectroscopy, X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), energy dispersive X-ray analysis (EDAX), and Fourier Transform Infrared Spectroscopy (FTIR). The observation of the peak at 460 nm in the UV-vis spectra for leaf- and stem-synthesized silver nanoparticles reveals the reduction of silver metal ions into silver nanoparticles. Further, XRD analysis has been carried out to confirm the crystalline nature of the synthesized silver nanoparticles. The TEM images show that the leaf- and stem-synthesized silver nanoparticles were within the size of about 7-50 nm and 9-30 nm, respectively. The FTIR analysis was performed to identify the possible functional groups involved in the synthesis of silver nanoparticles. Further, the antibacterial activity of the green-synthesized silver nanoparticles was examined against agricultural plant pathogens. The antibacterial property of silver nanoparticles is a beneficial application in the field of agricultural nanotechnology.
Comparative Study of Artificial Neural Network and Response Surface Methodology for Modelling and Optimization the Adsorption Capacity of Fluoride onto Apatitic Tricalcium Phosphate
Article
  • Jan 2014
In this study, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to develop an approach for the evaluation of fluoride adsorption process. A batch adsorption process was performed using apatitic tricalcium phosphate an adsorbent, to remove fluoride ions from aqueous solutions. The effects of process variables which are pH, adsorbent mass, initial concentration, and temperature, on the adsorption capacity (qe (mg/g)) of fluoride were investigated through three-levels, four-factors Box-Behnken (BBD) designs. Same design was also utilized to obtain a training set for ANN. The results of two methodologies were compared for their predictive capabilities in terms of the coefficient of determination(R2), root mean square error (RMSE), and the absolute average deviation (AAD) based on the experimental data set. The results showed that the ANN model is much more accurate in prediction as compared to BBD.
Health security in ethnic communities through nutraceutical leafy vegetables
Article
  • Jan 2013
Spectrometric Determination of Fluoride in Water, Soil and Vegetables from the Precinct of River Basawa, Zaria, Nigeria
Article
Fluoride levels of water, soil and vegetables from four irrigation farms at the bank of Basawa River, Zaria, Nigeria were estimated using Alizarin red spectrometric method. The soil samples from the four farms had a mean soil leachable fluoride in the range of 0.091 mg Kg -1 to 0.135 mg Kg -1 , while the river water had mean fluoride levels in the range 0.081 to 0.191 mg Kg -1 . The mean concentration of soil leachable fluorides for soils from the farms, at 95% confidence limit, were 0.110 ± 0.011, 0.108 ± 0.001, 0.114 ± 0.012 and 0.108 ± 0.001 mg Kg -1 for farms A, B, C and D respectively. At the same confidence limit, the mean fluoride concentration for the river water Upstream, Midstream and Downstream were 0.148 ± 0.027, 0.152 ± 0.036 and 0.137 ± 0.013 mg Kg -1 , respectively. T-test was used to evaluate and compare mean values of fluoride in the different vegetables. At 95% confidence interval (p = 0.05) and 18 degrees of freedom, with critical value of 2.26, the │t exp │ were 0.600, 1.986, 2.649, 1.924, 2.858 and 0.772 for Cabbage and Garden Egg, Cabbage and Onion, Cabbage and Tomato, Garden Egg and Onion, Garden Egg and Tomato and Onion and Tomato respectively. The only significant difference was observed for the fluoride levels of Cabbage and Tomato, and Garden Egg and Tomato where t exp > Critical value. The fluoride values obtained were all below the toxic limit of 2.57 to 16.44 mg Kg -1 for soil and maximum contaminant level of 4.0 mg Kg -1 for water, food and vegetables as stipulated by the joint EPA, FAO, and WHO Standard limit for fluoride. The implications of the results are discussed.
Comparative Study of Artificial Neural Network and Response Surface Methodology for Modelling and Optimization the Adsorption Capacity of Fluoride onto Apatitic Tricalcium Phosphate
Article
  • Jan 2014
In this study, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were employed to develop an approach for the evaluation of fluoride adsorption process. A batch adsorption process was performed using apatitic tricalcium phosphate an adsorbent, to remove fluoride ions from aqueous solutions. The effects of process variables which are pH, adsorbent mass, initial concentration, and temperature, on the adsorption capacity (qe (mg/g)) of fluoride were investigated through three-levels, four-factors Box-Behnken (BBD) designs. Same design was also utilized to obtain a training set for ANN. The results of two methodologies were compared for their predictive capabilities in terms of the coefficient of determination(R2), root mean square error (RMSE), and the absolute average deviation (AAD) based on the experimental data set. The results showed that the ANN model is much more accurate in prediction as compared to BBD.