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Optimization of liquid hot water pretreatment
for extraction of nanocellulose crystal from South
African waste corncobs
Oluwagbenga A. Olawuni, Olawumi O. Sadare & Kapil Moothi
To cite this article: Oluwagbenga A. Olawuni, Olawumi O. Sadare & Kapil Moothi (2024)
Optimization of liquid hot water pretreatment for extraction of nanocellulose crystal from
South African waste corncobs, Chemical Engineering Communications, 211:1, 26-39, DOI:
10.1080/00986445.2023.2218269
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Optimization of liquid hot water pretreatment for extraction of
nanocellulose crystal from South African waste corncobs
Oluwagbenga A. Olawuni, Olawumi O. Sadare, and Kapil Moothi
Department of Chemical Engineering, Faculty of Engineering and the Built Environment, University of Johannesburg, Doornfontein
Campus, Johannesburg, South Africa
ABSTRACT
This study extracted nanocellulose crystals from South African waste corncobs via liquid hot
water pretreatment and alkali treatment. The pretreatment process was designed and opti-
mized using Central Composite Design (CCD) and Response Surface Methodology (RSM),
respectively setting temperature (150–200 �C), time (10–60min), and solid loading rate (3–
10% w/w) as input variables. After pretreatment, the residue was treated with sodium
hydroxide (2%wt) at 90 �C for 90min. The extracted nanocellulose crystal was filtered,
washed with deionized water, and dried in an oven. The characterization of the nanocellu-
lose crystal was carried out based on standard procedures. The positive correlations
between the input variables were observed, whereby a rise in the pretreatment conditions
improved the nanocellulose crystal yield. Hence, the study obtained an optimum yield of
55.5% at 200 �C, 10% w/w, and 60min. The surface morphology showed a more porous and
rougher surface, and the crystallinity analysis indicated that run 7 had the most crystalline
nanocellulose crystal with a crystallinity index of 57.3%. The study revealed that nanocellu-
lose crystals could be extracted from corncobs via liquid hot water pretreatment and alkali
treatment.
KEYWORDS
Central composite design;
corncob; liquid hot water
pretreatment; nanocellulose
crystals; optimization;
response surface
methodology
Introduction
The continuous rise in global population growth
has led to high agricultural production and
amplified food demand, thus leading to an
increased generation of agricultural residue. The
waste generated has negatively impacted the
environment through improper disposal of waste
that builds up in landfills and sometimes gets
burned, polluting the environment and endanger-
ing human health (Wijaya et al. 2019; Magagula
et al. 2022). The challenges with waste manage-
ment include poor collection, improper manage-
ment, and corrupt behavior regarding waste
management by various industries. Therefore,
indiscriminate waste disposal can affect human
health and plants, injure animals, interrupt nat-
ural ecosystems, and discharge poisonous pollu-
tants into the atmosphere (Sadare et al. 2022).
The unprecedented increase in population rate
observed in South Africa lately has resulted in
overwhelming the country’s municipalities and
waste management capacities, thereby incapable
of providing adequate services (Simatele et al.
2017). The global waste generation rose to 2.43
billion metric tons as of 2021, and about 20% of
that was appropriately recycled (Tiseo 2022). In a
developing country like South Africa, approxi-
mately 54.2 million tons of waste were generated
in 2019, with almost 10% being recycled appro-
priately (Award 2019).
One of the significant sources of waste biomass
is agro-industrial waste, including wheat straw,
corncobs, rice husks, corn husks, stems of plants,
and so on. However, corn is among the world’s
most outstanding common crops, and corncob,
which is about 80% of the weight of the whole
corn ear, is the residue from corn processing
CONTACT Olawumi O. Sadare wumisadare@gmail.com Department of Chemical Engineering, Faculty of Engineering and the Built Environment,
University of Johannesburg, Doornfontein Campus, P.O. Box 17011, Johannesburg 2094, South Africa.
� 2023 The Author(s). Published with license by Taylor & Francis Group, LLC
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which
permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been
published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
CHEMICAL ENGINEERING COMMUNICATIONS
2024, VOL. 211, NO. 1, 26–39
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(Guo and L€u, 2021). Moreover, corncobs accu-
mulate to 9 million metric tons every year while
making up approximately 20% of all corn resi-
dues, and they are among the prevalent agricul-
tural residues generated in South Africa (Mohlala
et al. 2016). The target of reducing waste agrees
with Sustainable Development Goal (SDG) 6,
which focuses on decreasing pollution and indis-
criminate discarding of waste to achieve clean
water, zero waste, and sanitation (Leung 2019).
Moreso, this concern has stimulated substantial
interest in developing an environmentally sus-
tainable approach to transforming waste into
value-added products such as nanocellulose to
minimize waste biomass and its harmful effects
(Kargarzadeh et al. 2017).
Nanocellulose extraction from corncob has
been regarded as one of the sustainable
approaches to transforming corncob into value–
added products (Lavoine et al. 2012). The nano-
cellulose is divided into nanocellulose fibers,
nanocellulose crystals, and bacterial nanocellulose
(Mateo et al. 2021). They are generally extracted
from lignocellulosic waste biomass through acid
hydrolysis, accompanied by increased energy con-
sumption, high operating costs and generation of
hazardous by-products that can cause environ-
mental pollution. However, these challenges are
solved by using a green synthesis approach which
can be applied to substitute the conventional acid
hydrolysis techniques (Mood et al. 2013).
One of the leading green synthesis approachesis the liquid hot water technique, whereby no cat-
alysts or chemicals are required to extract nano-
cellulose crystals. The method is cost-effective
and environmentally friendly. The liquid hot
water (LHW) treatment of biomass occurs at
high temperatures (150–230 �C) to solubilize
hemicellulose, disrupt the lignocellulosic matrix,
and generate more reactive cellulose. The H
bonds start to break down, allowing water to
autoionize and form acid hydronium ions
(H3O
þ), which can serve as the precursor of
basic (OH�) or acidic (H3O
þ) catalysts. The
hemicellulose fraction of biomass experiences
depolymerization and cleavage of the acetyl
group because its heterocyclic ether linkages are
the most vulnerable. The reaction catalyzes
hydrolysis by combining water’s hydrolytic char-
acteristics with free organic acids’ activities
(Hakim et al. 2022; Troy et al. 2013). Moreover,
the concentration of H3O
þ and OH� in neutral
water is around 100 times higher than that of the
normal at high temperatures. In this manner, the
hot water will perform both acid and alkali
catalysis and disrupt the glycosidic bonds to solu-
bilize hemicellulose and slight delignification of
waste biomass (Suriyachai et al. 2020; Cui et al.
2021).
Various lignocellulosic biomass wastes have
been pretreated using the liquid hot water tech-
nique, such as corncob (Ara�ujo et al. 2019), pine
sawdust (Nitsos et al. 2016), sugarcane straw
(Sanchez-Herrera et al. 2018), green pepper waste
(Mart�ın-Lara et al. 2020), wheat straw and brew-
ers’ spent grains (Michelin and Teixeira 2016).
Similarly, Khongchamnan et al. (2022) investi-
gated the influence of the LHW pretreatment
process on the sugarcane bagasse’s solubilization.
The result showed that the LHW pretreatment
solubilized the hemicellulose and altered the sug-
arcane bagasse structure. In addition, Suriyachai
et al. (2020) studied the impact of acid-catalyzed
LHW pretreatment on corn stover. The study
discovered that the LHW modified the physico-
chemical properties and improved the enzymatic
susceptibility of the substrate. Additionally,
Antczak et al. (2022) assessed the performance of
steam explosion and LHW pretreatments on pop-
lar wood. It was observed that both pretreatments
disrupted the hemicellulose chemical content;
nevertheless, LHW pretreatment gave the highest
hemicellulose removal. Moreso, various research-
ers are making efforts to optimize, improve, and
simplify the LHW pretreatment techniques to
enhance nanocellulose yield without generating
hazardous by-products (Capolupo and Faraco
2016).
Furthermore, the liquid hot water pretreatment
process is optimized using Response Surface
Methodology (RSM), a set of statistical and math-
ematical methods for evaluating a process
whereby several variables influence one or more
response variables to optimize the response
(Aydar 2018). Thakur et al. (2020) assessed the
optimization of process parameters using RSM to
CHEMICAL ENGINEERING COMMUNICATIONS 27
extract nanocellulose crystals from rice husks
through acid hydrolysis. In addition, Wijaya et al.
(2019) examined the parametric optimization of
nanocellulose crystal extraction from bamboo
shoots through RSM. Furthermore, Garc�ıa-Garc�ı
et al. (2018) studied the optimization of hydroly-
sis parameters throughout the extraction of nano-
cellulose crystals from pinecones. The study
discovered that crystallinity, thermal stability, and
aspect ratio (diameter/length) influenced the
physicochemical properties of the extracted nano-
cellulose crystal. Similarly, Demewoz (2020)
investigated the optimization of process parame-
ters (acid concentration, time, and temperature)
for extracting nanocellulose crystals from corn-
cobs using RSM.
Although there are several studies on the
extraction of nanocellulose crystal from biomass
waste through acid hydrolysis, some of these
studies went further to optimize the extraction
process. However, there is limited study on the
green synthesis (liquid hot water) approach for
extracting nanocellulose crystal from waste corn-
cobs, significantly optimizing the liquid hot water
pretreatment process for improved nanocellulose
crystal yield. This study, therefore, aimed to opti-
mize the liquid hot water pretreatment of South
African waste corncob for the extraction of nano-
cellulose crystals. Central Composite Design
(CCD) was used to design the experiments and
to find the optimal temperature, time, and solid
loading rate using nanocellulose crystal yield as
the response variable. The CCD was selected in
this study for multiple analyses of nanocellulose
yield targeted at determining optimal conditions
resulting in maximum yield.
Materials and methods
Materials
The raw corncobs used in this study were bought
from local sellers in Johannesburg, South Africa,
cleaned, and dried to remove impurities or dust.
The dried, clean corncobs were ground, sieved
with a 0.5mm sieve to obtain a fine powder, and
stored in a dry airtight container. The deionized
water used throughout this study was produced
in the laboratory, and sodium hydroxide (NaOH,
98%) was purchased from Protea Chemical Ltd
South Africa and was used without additional
purification. All methods were carried out
according to standard procedures.
Experimental design and optimization of
pretreatment parameters
The experiment was designed using Central
Composite Design (CCD) before the pretreat-
ment experiment based on three parameters,
which are time (10–60min), temperature (150–
200 �C), and solid loading rates (3–10% w/w).
After the experimental design with the pretreat-
ment parameters defined, eleven runs were gener-
ated, as shown in Table 1, and the information
obtained was further applied to optimize the pre-
treatment process. The study utilized Response
Surface Methodology (RSM) to statistically ana-
lyze the experimental data obtained after pre-
treatment to determine the optimum conditions
for the three parameters influencing the nanocel-
lulose crystal yield from corncobs. In addition,
the analysis of variance (ANOVA) and a signifi-
cance test were carried out to estimate the quality
of the generated model equation.
Pretreatment and extraction of nanocellulose
crystal from corncobs
The corncob powder was pretreated with liquid hot
water (LHW) at varying solid loading rates (3–
10%w/w) in a stainless steel cylindrical reactor at a
varying temperature between 150–200 �C, for a
reaction time between 10–60min, and continuous
stirred using a mechanical stirrer according to the
method by Mart�ın-Lara et al. (2020). The mixture
from the pretreatment was cooled, and the insoluble
Table 1. Design of experiment using Central Composite
Design (CCD).
Run Temp (�C) Time (min) Solid loading rate (% w/w)
1 150 10 10
2 175 35 6.5
3 175 35 10
4 200 60 3
5 175 60 6.5
6 200 10 10
7 150 60 10
8 150 10 3
9 150 60 3
10 200 10 3
11 200 60 10
28 O. A. OLAWUNI ET AL.
solid was obtained, then washed methodically using
deionized water and allowed to dry for 24h at
60 �C. Further treatment was done by soaking the
earlier liquid hot water pretreated nanoscale cellu-
lose in a sodium hydroxide (NaOH) solution (2wt
%) for 90min at 90 �C using a magnetic stirrer.
Similarly, the NaOH–treated residue was filtered
and thoroughly rinsed using deionized water until it
turned colorless and dried for 24 h at 60 �C. The
dried LHW–NaOH corncob residue was ground
and kept in a dry airtight bottle (Ara�ujo et al. 2019).
The nanocellulose crystal yield was estimated using
Equation (1):
Yield %ð Þ ¼ Final mass of nanocellulose after extraction
Initial mass of sample before extraction
� 100
(1)
Nanocellulose crystal characterization
The surface morphologies and elemental compo-
sitions of the nanocellulose crystals were checked
through Scanning Electron Microscopy (SEM)
coupled with Energy Dispersion X-ray (EDX).
The nanocellulose crystal was coated with 40%
Gold and 60% Palladium (Au/Pd) before the
SEM analysis using CARL ZEISS sigma field elec-
tronic scanning electron microscope (FESEM) at
diverseintensifications.
The functional group and surface chemistry of
the extracted nanocellulose crystal were checked
with a Bruker Tensor 27 by Fourier Transform
Infrared Spectroscopy (FTIR). Potassium bromide
(KBr) was used as a carrier for the nanocellulose by
mixing 2mg of nanocellulose crystal with 200mg of
KBr to permit infrared transmission. The mixture
of nanocellulose crystal and KBr was pelletized by
pressing it at 20MPa for 3min. The spectra were
obtained at the wavelength range of 500–4000 cm�1
(Sadare et al. 2022). The purity and crystallinity of
the nanocellulose crystal were checked by carrying
out an X-ray diffraction (XRD) analysis. A diffract-
ometer (XRD) was used to determine the X-ray dif-
fractograms patterns of nanocellulose crystal at
ambient conditions. It was utilized with radiation
from copper (Cu) at a wavelength of 0.154 nm,
40 kV voltage, 40mA power, and diffraction inten-
sities between the range of 2h (5� � 50�) at a scan-
ning rate of 0.05�/s (3� per minute). The empirical
approach established by Segal et al. (1959) was
applied to estimate the crystallinity index (CrI) as
stated in Equation (2):
CrI ¼ ðI200� IamÞ
Iam
x 100 (2)
I200 indicates the peak intensity for the (200)
lattice, and Iam is the minimum intensity between
the 200 and 110 peaks when 2h is nearly 18�.
Results and discussion
Extraction of nanocellulose crystal from corncob
The intact hemicellulose structure of the corncob
was disrupted or weakened by dissolving it in
liquid hot water to make cellulose more accessible.
Consequently, after the pretreatment of the corn-
cob with liquid hot water (LHW), the hemicellu-
lose structure was perfectly disrupted to produce a
residue rich in lignin and cellulose (Liu et al.
2016). The liquid hot water pretreatment was inef-
fective at solubilizing most of the lignin content in
the corncob. After the liquid hot water pretreat-
ment, lignin content was present, similar to the
observation by Li et al. (2017) in their study. The
residue from the liquid hot water pretreatment was
further treated with sodium hydroxide solution
(NaOH) to decrease the lignin content available in
the residue from the liquid hot water pretreatment
and extract nanocellulose crystal. The LHW pre-
treatment was done by varying the solid loading
rate (3–10% w/w) and increasing temperature
from 150 �C to 200 �C for a time range between 10
to 60min. The nanocellulose crystal yield obtained
after the liquid hot water pretreatment and NaOH
treatment was determined using Equation 1, and
the results are shown in Table 2. The physical
appearance of the extracted nanocellulose crystal
Table 2. Nanocellulose crystal extraction from waste
corncobs.
Run Temp (�C) Time (min)
Solid loading
rate (% w/w)
Actual
yield (%)
1 150 10 10 49
2 175 35 6.5 47.23
3 175 35 10 51
4 200 60 3 41.67
5 175 60 6.5 52.92
6 200 10 10 51.10
7 150 60 10 51
8 150 10 3 36
9 150 60 3 44.67
10 200 10 3 47.67
11 200 60 10 55.5
CHEMICAL ENGINEERING COMMUNICATIONS 29
was smooth and soft, with the maximum nanocel-
lulose crystal yield of 55.5% at 10% w/w, 200 �C
and 60min, while the minimum yield of 36% at
3% w/w, 150 �C and 10min.
Optimization of pretreatment parameters for
nanocellulose crystal yield using response surface
methodology (RSM)
The experiment was designed using a Central
Composite Design (CCD) before extracting nano-
cellulose crystal from South African waste corn-
cobs via the liquid hot water pretreatment and
NaOH treatment approach. The experimental
(actual) and predicted yields, along with the
residual values, are presented in Table 3, and the
Table reveals all the experimental runs with their
corresponding pretreatment parameters. Design
Expert 11.0.5.0 software was employed for statis-
tical analysis and to evaluate the coefficients of the
model equation with their statistical significance.
The study presents the outcome of the analysis of
variance (ANOVA) and the test of significance for
each coefficient of regression in Table 4.
Furthermore, the model’s goodness of fit was eval-
uated using the coefficient of determination (R2)
with a value of 0.7497, indicating that model per-
fection is required. In addition, the F-value of the
model is 6.99, and it shows the significance of the
model. Also, the high value of F means that there
is only a probability of 1.64% that such a value
could result from noise. Similarly, the terms of the
model are significant when the p-values less than
0.0500; thus, the significant model term in this
study is solid loading rate (C).
The adequate precision, which measured the sig-
nal-to-noise ratio of 8.025, was used to evaluate the
model’s suitability for predicting nanocellulose yield
from the liquid hot water pretreatment of the corn-
cob. The signal-to-noise ratio suggested a sufficient
signal that might be utilized to explore the design
space. Equation 3 shows a single regression model
for the relationship between the nanocellulose yield
and all the pretreatment conditions (in coded form)
used in the modeling investigation. To further verify
the model, the plot of predicted versus the actual
responses for the nanocellulose crystal yield was
done and shown in Figure 1. The plotted data
points may be uniformly spaced along the model
line, indicating a low deviation between the actual
and predicted response data points. Although only
a few predictions deviated from the actual values,
some outliers were observed. The outliers’ proxim-
ity to the model line shows that the model assump-
tions are accurate, with minor errors.
Yield %ð Þ ¼ 47:43 þ 1:91 A þ 1:62 B
þ 4:46 C (3)
Where A represents temperature (�C), B for
time (min), and C for solid loading rate (%w/w)
Interactive effect of time and temperature on nano-
cellulose crystal yield
The interactive effect of reaction time and tem-
perature on the nanocellulose crystal yield is
shown in Figure 2. As the figure shows, an
Table 3. Design of experiment for nanocellulose crystal extraction from waste corncobs.
Run Temp (�C) Time (min) Solid loading rate (% w/w) Actual yield (%) Predicted yield (%) Residual
1 150 10 10 49 48.36 0.6389
2 175 35 6.5 47.23 47.43 �0.1954
3 175 35 10 51 51.89 �0.8881
4 200 60 3 41.67 46.49 �4.82
5 175 60 6.5 52.92 49.04 3.88
6 200 10 10 51.10 52.18 �1.08
7 150 60 10 51 51.60 �0.5976
8 150 10 3 36 39.44 �3.44
9 150 60 3 44.67 42.67 2.00
10 200 10 3 47.67 43.25 4.42
11 200 60 10 55.5 55.42 0.0849
Table 4. Analysis of variance (ANOVA) and test of significance
for model equation.
Source df Sum of squares Mean square p-value F–value
A 1 29.15 29.15 0.1461 2.67
B 1 23.33 23.33 0.1869 2.14
C 1 177.42 177.42 0.0050 16.27
Model 3 228.60 76.20 0.0164 6.99
Residual 7 76.32 10.90
R2 0.7497
Adjusted R2 0.6424
Adequate Precision 8.0252
A¼ Temperature, B¼ Time, C¼ Solid loading rate.
30 O. A. OLAWUNI ET AL.
increase in temperature and time is directly pro-
portional to a rise in the nanocellulose crystal
yield at a constant solid loading rate of 10% w/w.
When the temperature increased from 150 �C to
175 �C and time increased from 10min and
35min, the nanocellulose yield increased from
49% to 51%, respectively. The low increase in the
nanocellulose yield showed that the lignocellulo-
sic matrix of the corncob was not wholly dis-
rupted at this condition by autoionization of hot
water; hence higher temperature and long pre-
treatment time are necessary. The nanocellulose
crystal yield further increased from 51% to 55.5%
when the temperature increased from 175 �C to
200 �C and time from 35 to 60min, respectively.
This observation implied that higher temperature
and extended reaction time substantially solubi-
lized the hemicellulose and enhanced the nano-
cellulose crystal yield using LHW pretreatment
(Hakim et al. 2022).
The effect of time on the nanocellulose crystal
yield was evaluated when temperature and solid
loading rate remained constant at 150 �C and 3%
w/w, respectively. The yield improved from 36%
to 44.67% when the time rose from 10min to
60min, respectively. Similarly, the same trendFigure 1. Predicted vs. actual (experimental) nanocellulose crystal yield.
Figure 2. Interactive effect of time and temperature on nanocellulose crystal yield.
CHEMICAL ENGINEERING COMMUNICATIONS 31
was observed when temperature and solid loading
rate were kept constant at 150 �C and 10% w/w,
respectively. The nanocellulose crystal yield
improved from 49% to 51% as the pretreatment
time rose from 10min to 60min, respectively.
This behavior is similar to the study by
Syarifuddin et al. (2020) as they observed that
before equilibrium was achieved, thus extending
the pretreatment duration increased the reaction
rate, thereby improving the product selectivity.
Additionally, extended reaction time allowed the
corncob powder to interact more with liquid hot
water during the pretreatment process, which
caused high hemicellulose dissolution and the
break-down of the cell structure (Hakim et al.
2022; Ara�ujo et al. 2019), hence enhancing the
access to cellulose and improved the nanocellu-
lose crystal yield. In addition, an increase in
nanocellulose crystal yield was observed at con-
stant pretreatment time and solid loading rate as
the temperature rose from 150 �C to 200 �C.
Interactive effect of temperature and solid loading
rate on nanocellulose yield
Figure 3 shows the interactive effect of tempera-
ture and solid loading rate on the yield of nano-
cellulose crystals. The plot revealed that at a
constant time of 60min, when the pretreatment
temperature rose to 175 �C from 150 �C, and the
solid loading rate increased to 6.5% w/w from 3%
w/w, the nanocellulose crystal yield improved to
52.92% from 44.67%, respectively. Likewise, when
the temperature was further raised to 200 �C
from 175 �C, and the solid loading rate increased
to 10% w/w from 6.5% w/w, the nanocellulose
crystal yield rose to 55.5% from 52.92% respect-
ively. Therefore, there is a directly proportional
relationship between the solid loading rate and
temperature to influence the nanocellulose crystal
yield. Furthermore, the study investigated the
influence of solid loading rate at constant time
and temperature on the nanocellulose crystal
yield and observed that at a constant time and
temperature of 35min and 175 �C respectively,
the yield for run 2 improved from 47.23% to
51% for run 3.
Moreover, a lower nanocellulose crystal yield
was observed at a solid loading rate of 3% w/w.
However, the yield continued to improve until the
highest yield was obtained at 10% w/w as the solid
loading rate increased. This trend is similar to the
study by Pereira and Arantes (2020), whereby the
cellulose conversion rate increased as the loading
rate increased using bleached sugarcane pulp. In
addition, Luterbacher et al. (2010) achieved high
glucose extraction from different biomasses (corn
stover, switchgrass, and wood) at a high solid con-
tent of 40wt% as related to 20wt%. Also, the con-
nection between temperature and nanocellulose
crystal yield is seen in Figure 3, whereby the yield
was detected to rise directly proportional to tem-
perature. Luterbacher et al. (2010) reported in their
study that further improvements like operating the
pretreatment process at high temperatures could
promote the glucose yields and reduce the gener-
ation of furfural; hence in the current research,
increased temperature promoted nanocellulose
Figure 3. Interactive effect of temperature and solid loading rate on nanocellulose crystal yield.
32 O. A. OLAWUNI ET AL.
yield. Likewise, Lu et al. (2021) stated that solubi-
lizing the hemicellulose was faster when operated
at an elevated temperature because the reaction
rate increased. Also, Hongdan et al. (2013) noticed
similar behavior in their study, whereby the sac-
charification of sugarcane bagasse improved as the
temperature rose.
Interactive effect of time and solid loading rate on
nanocellulose crystal yield
The interactive effect of solid loading rate and
time on the nanocellulose crystal yield at a con-
stant temperature of 200 �C is illustrated in a 3D
plot, as shown in Figure 4. The nanocellulose
yield increased from 47.67% to 55.5% when the
time was raised to 60min from 10min, and the
solid loading rate improved to 10% w/w from 3%
w/w, respectively. Also, a continuous rise in the
nanocellulose yield was observed as time
increased from 10min to 60min, which means
that the liquid hot water penetrated the cell
matrix of the corncob powder and disrupted the
amorphous domains of the hemicellulose, making
the cellulose more accessible (Dube 2022).
Nevertheless, a very high pretreatment time led
to extreme decomposition and breaking of the
cellulose amorphous domain, causing minimal
yields (Sadare et al. 2022). Furthermore, as the
solid loading rate increased from 3% w/w to 10%
w/w at constant time and temperature, a steady
rise in the nanocellulose yield was observed.
Optimization of pretreatment parameters
The plots of optimized pretreatment parameters
and the interaction effects of the combined three
parameters on the extraction of nanocellulose
crystal were illustrated by the response surface
graphs presented in Figure 5. The yield of nano-
cellulose crystal was set at the optimum while the
pretreatment parameters were adjusted to the
highest values. The optimum yield of nanocellu-
lose crystal was 55.42% when corncob powder
was pretreated at a solid loading rate of 10%
w/w, 200 �C temperature for 60min using liquid
hot water. The desirability value for optimizing
the pretreatment parameters is a value that lies
between 0 and 1, with the desirability value of 1
showing the optimum factor of performance
while 0 indicating that the factor provides an
undesirable response, hence signifying the desir-
able response (Amdoun et al. 2018). Nevertheless,
in this study, the desirability value of 0.996 was
obtained for the pretreatment conditions opti-
mization, indicating that the pretreatment param-
eters (time, temperature, and solid loading rate)
gave a desirable yield of nanocellulose crystal,
thus achieving the objective of increasing and
maximizing the nanocellulose crystal yield.
Characterization of nanocellulose crystal
Surface morphology of nanocellulose crystal
Scanning Electron Microscopy (SEM) was applied
to check the surface and morphological
Figure 4. Interactive effect of time and solid loading rate on nanocellulose crystal yield.
CHEMICAL ENGINEERING COMMUNICATIONS 33
Figure 5. Optimization of pretreatment parameters.
Figure 6. Surface morphology analysis for (a) Run 5 (b) Run 6 (c) Run 7 (d) Run 11.
34 O. A. OLAWUNI ET AL.
characteristics of the extracted nanocellulose crys-
tal, as shown in Figure 6(a–d). Runs 5, 6, 7, and
11 were selected for characterization because they
produced higher yields of nanocellulose crystals
than other experimental runs. After the pretreat-
ment process, the structure of the pretreated
corncob lost the protective layer, thus revealing
the primary fibers and structure. The morpho-
logical images show that the pretreatment tech-
nique enhanced the cellulose surface area,
reducing the external recalcitrance and making it
more accessible (Suriyachai et al. 2020). The cell
wall of the corncob partially collapsed due to the
loss of hemicellulose during the defibrillation
procedure, which enhanced the accessible poros-
ity and surface area (Imman et al. 2018). In add-
ition, treatment with sodium hydroxide (NaOH)
further dissolved the lignin content, resulting in
the disintegration and disruption of the corncob
fibers. The combination of liquid hot water and
sodium hydroxide treatment resulted in a distin-
guished porous texture of the macrofibril shape
and more uniform crystal dispersion (Ara�ujo
et al. 2019). Figure 6(c) shows the surface charac-
teristics of nanocellulose extracted for run 7 at
150 �C, 10% w/w, and 60min with pores on the
surface. However, some large compact fibers were
seen on the image, meaning a small surface area
and the cellulose was partially accessible.
Moreover, the nanoscale cellulose pretreated at
the optimum conditions wasmore porous, as
shown in Figure 6(d), with a smaller and thinner
size of fibers observed on the surface, which illus-
trated increased surface area and more accessible
cellulose. Boonsombuti et al. (2013) also reported
that both time and temperature affect the mor-
phological characteristics of the nanocellulose
crystal, whereby prolonged time, high tempera-
ture, and sodium hydroxide concentration
improved the cellulose surface area with a more
porous material. An irregular shape and rough
micro-sized fibers were observed for the nanocel-
lulose extracted at the optimum conditions, and
this showed that most of the hemicellulose and
part of the lignin contents were successfully
removed by the liquid hot water pretreatment
and alkali treatment processes (Suriyachai et al.
2020, Hakim et al. 2022). Although, the study
achieved the extraction of nanocellulose from
corncob due to the fragmentation of the fiber
into individual cells because of the alkali treat-
ment to remove the lignin content. However, in
the study by Ara�ujo et al. (2019), more porous
nanocellulose was obtained compared to the
structure shown in Figure 6(d).
Elemental composition analysis
The elemental composition of the nanocellulose
crystal samples was checked using Energy
Dispersion X-ray (EDX) analysis. After the inves-
tigation, different elements with their correspond-
ing atomic percentages are shown in Table 5.
The Table reveals Cu, Mg, and Al buildup over
the surface of run 6 and 7, respectively. All the
runs show the presence of O and Na elemental
compositions in higher quantities than other ele-
ments. However, run 7 had higher oxygen com-
position than other runs, probably due to the
adsorption of water molecules to the nanocellu-
lose crystal. In addition, the analysis result
showed that additional elements such as Fe, Ca,
and Si are present, which could be ascribed to
the availability of the mineral content in corncob.
In addition, S was present in minimal amounts
in the nanoscale cellulose, similar to the study by
Mohlala et al. (2016), which could be attributed
to impurities.
Fourier transform infrared spectroscopy (FTIR)
analysis
The surface chemistry and chemical functionality
of the nanocellulose crystals extracted via the
liquid hot water pretreatment technique and fur-
ther treated with sodium hydroxide were checked
using FTIR for runs 5, 6, 7, and 11, as shown in
Figure 7, and the spectra are also listed in Table 6.
Table 5. Result of elemental compositions for extracted nano-
cellulose crystal.
Atomic %
Element Run 5 Run 6 Run 7 Run 11
Na 43.85 42.20 21.33 50.35
Si 5.23 5.34 9.42 3.39
S 2.23 1.86 2.76 1.87
Ca 2.51 3.59 3.08 1.82
Fe 2.61 1.49 3.64 1.70
Co 0.31 0.14 – 0.11
O 43.88 43.98 52.88 40.98
Cu – 1.41 – –
Mg – – 3.90 –
Al – – 2.99 –
CHEMICAL ENGINEERING COMMUNICATIONS 35
The peak absorption at 3460 cm�1, 3460 cm�1,
3465 cm�1, and 3475 cm�1 were observed for runs
5, 6, 7, and 11, respectively. These peaks could be
attributed to hemicellulose and O–H cellulose
stretching, which revealed the tendency of the fiber
to dissolve, mix, or contains water (Rhim et al.
2015; Ma et al. 2015). Likewise, the absorption
peaks at 1645.94 cm�1, 1644.47 cm�1,
1644.70 cm�1, and 1644.89 cm�1 were noticed for
runs 5, 6, 7, and 11, respectively. These peaks cor-
responded to the O–H bending of absorbed water
molecules according to the studies by Ara�ujo et al.
(2019) and Sadare et al. (2022). Furthermore, C–H
asymmetric deformation in cellulose was observed
at the absorption peaks of 1384.36 cm�1,
1384.27 cm�1, 1384.27 cm�1, and 1384.43 cm�1 for
runs 5, 6, 7, and 11, respectively (Ara�ujo et al.
2019; Sadare et al. 2022). In addition, the peaks for
runs 5, 6, and 11 showing asymmetric C–O–C
vibration of hemicellulose and cellulose were seen
at 1164.16 cm�1, 1164.04 cm�1, and 1163.96 cm�1,
respectively. Nevertheless, there was no band
observed in the sample for run 7. Also, the
observed peaks at 1114.00 cm�1, 1113.49 cm�1,
1114.30 cm�1, and 1113.67 cm�1 indicated C–OH
skeletal vibration in cellulose for runs 5, 6, 7, and
11, respectively. However, cellulose’s C–O–C
stretching was only seen at 1035.54 cm�1 for the
run 6 sample. In addition, the bands at
896.46 cm�1 and 896.24 cm�1 for runs 6 and 7 cor-
responded to the C–H deformation vibration of
cellulose and indicated in the glucose monomers
connected by the b-glycosidic between them (Ma
et al. 2015; Wang et al. 2017), but there were no
visible absorption bands for run 5 and 11.
X-ray diffraction (XRD) analysis of nanocellulose
crystal
The nanocellulose samples were analyzed using
X-ray diffraction (XRD) analysis to determine
their crystallinity, and the results of the analysis
are shown in Figure 8 for runs 5, 6, 7, and 11.
The XRD analysis for the run 5 sample revealed
obvious peaks at 2h¼ 18.5�, 2h¼ 22.8� and
2h¼ 38.1�. Similarly, run 6 contained visible
peaks at 2h¼ 18.64�, 2h¼ 22.5� and 2h¼ 34.8�,
while visible peaks were observed in run 7 at
2h¼ 18.64�, 2h¼ 22.54� and 2h¼ 38.06�. Finally,
run 11 showed peaks at 2h¼ 18.62�, 2h¼ 22.4�
and 2h¼ 38.08� on the XRD graph. The peak
intensity showed the atoms’ position within the
lattice structure, while the peak width provided
information about the size of the lattice strain
and crystallite. Sadare et al. (2022) and Das et al.
(2018) stated that the three main peaks were
observed in their studies. Furthermore, Zhang
Figure 7. Plots of FTIR analysis for runs 5, 6, 7, and 11.
Table 6. FTIR spectra with the corresponding functional groups in the nanocellulose crystals.
Wavelength (cm�1) Functional group Run 5 Run 6 Run 7 Run 11
3460–3475 O–H stretching of cellulose and hemicellulose Y Y Y Y
1645 O–H bending vibration of absorbed water molecules Y Y Y Y
1384 C–H asymmetric deformation in cellulose Y Y Y Y
1164 C–O–C vibration of cellulose and hemicellulose Y Y — Y
1114 C–OH skeletal vibration in cellulose Y Y Y Y
1035 C–O–C stretch vibrations in cellulose — Y — —
896 C–H deformation vibration of cellulose — Y Y —
Y means the functional group is present.
36 O. A. OLAWUNI ET AL.
et al. (2019) reported that XRD peaks inclined to
be mobile due to the non-cellulosic component
removal during the extraction of the nanocellu-
lose crystal. Nevertheless, the movement of peaks
was not observed in this study, which means lig-
nin and hemicellulose did not influence the initial
structure of cellulose in the corncob. The result
illustrated that the cellulose is stable since no poly-
morphic transformation was observed. The crystal-
linity indexes (CrI) estimated using Equation (2)
were 47%, 56.7%, 57.3%, and 53% for runs 5, 6, 7,
and 11, respectively. Run 7, with a higher crystal-
linity index, implied that after the liquid hot water
pretreatment and sodium hydroxide treatment
part of the amorphous cellulose, most of the hemi-
cellulose was removed from the corncob powder.
Additionally, the increase in the crystallinity
showed that the fraction of crystalline cellulose
structure increased, thereby enhancing the accessi-
bility of the cellulose surface (Suriyachai et al.
2020). It can be deduced from the crystallinity
indexes obtained in this study that some hemicel-
lulose and lignin contents were present in the
extracted nanocellulose.
Conclusions
This study was conducted to extract nanocellulose
crystals from waste corncob by applying the liquid
hot water (LWH) pretreatment technique and
sodium hydroxide treatment. The scanning elec-
tron microscopy images of the extracted nanocel-
lulose crystal revealed how the liquid hot water
pretreatment changed the morphological features
of the raw corncob, and the extracted nanocellu-
lose crystal can be differentiated from the
untreated corncob. Furthermore, the Fourier
transform infrared spectra of the nanocellulose
crystals revealed the availability of functional
groups, and the X-ray diffraction analysis showed
an improved crystallinity. In addition, the liquid
hot water pretreatment process was designed and
optimized using the central composite design and
response surfacemethodology, respectively. After
the experimental design, the model equation was
developed, and a rise in the pretreatment parame-
ters (temperature, time, and solid loading rate) led
to an increase in the yield of nanocellulose crystal
with the optimum yield of 55.5% obtained at a
solid loading rate of 10% w/w, 200 �C temperature
and 60min pretreatment time. Hence, the study
concluded that the nanocellulose crystal yield
improved with rising pretreatment conditions.
Disclosure statement
The authors report there are no competing interests to
declare.
Funding
This work was supported by the SASOL–National Research
Foundation of South Africa [Grant Number 138620]
awarded to Oluwagbenga A. Olawuni for his PhD degree
program.
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CHEMICAL ENGINEERING COMMUNICATIONS 39
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	Abstract
	Introduction
	Materials and methods
	Materials
	Experimental design and optimization of pretreatment parameters
	Pretreatment and extraction of nanocellulose crystal from corncobs
	Nanocellulose crystal characterization
	Results and discussion
	Extraction of nanocellulose crystal from corncob
	Optimization of pretreatment parameters for nanocellulose crystal yield using response surface methodology (RSM)
	Interactive effect of time and temperature on nanocellulose crystal yield
	Interactive effect of temperature and solid loading rate on nanocellulose yield
	Interactive effect of time and solid loading rate on nanocellulose crystal yield
	Optimization of pretreatment parameters
	Characterization of nanocellulose crystal
	Surface morphology of nanocellulose crystal
	Elemental composition analysis
	Fourier transform infrared spectroscopy (FTIR) analysis
	X-ray diffraction (XRD) analysis of nanocellulose crystal
	Conclusions
	Disclosure statement
	Funding
	References