Thermo-hygroscopic characterization of Arthrospira Platensis by DVS

Abstract

The objective of this work was to examine the thermo-hygroscopic behavior of Arthrospira (Spirulina) platensis using dynamic vapor sorption (DVS) system. This thermo-hygroscopic analysis focused on three parameters: desorption isotherms, the net isosteric heat of water desorption and moisture diffusivity. Desorption isotherms were performed at temperatures of 25°C, 40°C, 50°C, 60°C and 80°C across a relative humidity range of 10 to 80%. The desorption isotherm data were fitted to five semi-empirical models: GAB; Oswin; Smith; Henderson and Peleg. The results indicated that the GAB model provided the best fit for the desorption isotherm data. The net isosteric heat of desorption decreased from from 21.3 to 4.29 KJ/mol as the moisture content increased from 0.02 to 0.1 Kg/Kg (dry basis). Additionally, the moisture diffusivity of Arthrospira platensis moisture diffusivity ranged from 1.04 10 − 8 m ² /s to 1.46 10 − 7 m ² /s for average moisture contents varying from 0.003 Kg /Kg to 0.191 Kg /Kg (dry basis).

Full text

Page 1/22
Thermo-hygroscopic characterization of Arthrospira
Platensis by DVS
Thouraya GHNIMI
University of Gabes
Lamine HASSINI
University of Tunis el Manar. Tunis
Research Article
Keywords: Arthrospira platensis, desorption isotherms, DVS system. Modeling, net isosteric heat,
moisture diffusion
Posted Date: December 2nd, 2024
DOI: https://doi.org/10.21203/rs.3.rs-5437850/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License
Additional Declarations: No competing interests reported.

Page 2/22
Abstract
The objective of this work was to examine the thermo-hygroscopic behavior of
Arthrospira (Spirulina)
platensis using dynamic vapor sorption (DVS) system. This thermo-hygroscopic analysis focused on
three parameters: desorption isotherms, the net isosteric heat of water desorption and moisture
diffusivity. Desorption isotherms were performed at temperatures of 25°C, 40°C, 50°C, 60°C and 80°C
across a relative humidity range of 10 to 80%. The desorption isotherm data were tted to ve semi-
empirical models: GAB; Oswin; Smith; Henderson and Peleg. The results indicated that the GAB model
provided the best t for the desorption isotherm data. The net isosteric heat of desorption decreased
from from 21.3 to 4.29 KJ/mol as the moisture content increased from 0.02 to 0.1 Kg/Kg (dry basis).
Additionally, the moisture diffusivity of
Arthrospira platensis
moisture diffusivity ranged from 1.04 10− 8
m2/s to 1.46 10− 7 m2/s for average moisture contents varying from 0.003 Kg /Kg to 0.191 Kg /Kg (dry
basis).
Introduction
Arthrospira (Spirulina) platensis
is a microscopic and lamentous cyanobacterium that has existed for
over 3billion years. Its name is derived from its spiral shape and it belongs to the family of
cyanobacteria, commonly referred to as blue-green micro algae.
Spirulina platensis
is low in calories but
packed with nutrients in a very small volume [1]. Indeed.
Arthrospira
contains a very high rate of protein
which exceeds 60% of the dry mass and is therefore one of the most signicant sources of protein
among both protists and plants [2].
At the end of the cultivation phase, algal biomass has a very high moisture content, which poses
challenges for storage and recovery. Therefore, reducing the water content through dehydration is
necessary for preserving the quality of this biomass. This dehydration process accounts for nearly 30%
of the total processing cost of
Arthrospira platensis
[3]. Various dehydration techniques have been
employed to dry the
Spirulina platensis
biomass including convective air drying [4–5], solar drying [6],
freeze-drying [7], spray drying [8], drum drying [9] and hot air drying assisted by capillary draining [10].
Assessing the thermo-hygroscopic characteristics of
Spirulina
, such as desorption isotherms, net
esoteric heat and moisture diffusivity is crucial for its drying process. Understanding these properties
helps maintain biochemical stability and estimate desorption energy [11]. Desorption isotherms are
necessary for designing and optimizing drying equipment, particularly for calculating moisture changes
during the storage of dried products [12]. The net isosteric heat of desorption, often derived from
desorption isotherms using Clausius-Clapeyron relation, is essential for estimating the energy
requirements for desorption [13]. Furthermore, the diffusion coecient of
Spirulina platensis
during
desorption is a key parameter for simulating and optimizing the drying process [14].
Despite its signicance, literature on the desorption isotherms of
Arthrospira (Spirulina) platensis
is
limited. To our knowledge, only Desmorieux and Decaen have used the DVS method at two temperatures

Page 3/22
(25 and 40°C) to establish the desorption isotherms of
Spirulina platensis
[3]. Additionally, we have not
found any studies focused on assessing the moisture diffusivity of
Arthrospira platensis
during
desorption as a function of moisture content and temperature using DVS technology.
Thus, this study aims to i) determine the desorption isotherms of
Arthrospira platensis
using the DVS
technique across temperatures ranging from 25 to 80°C and a relative humidity range of 10–80% ii)
identify the most suitable model for tting the desorption isotherm data iii) calculate the net isostatic
heat of desorption as a function of equilibrium moisture content based on Clausius-Clapeyron theory iv)
estimate the moisture diffusion coecient of
Spirulina platensis
during desorption using Fick’s second
law and v) correlate the moisture diffusion coecient with both equilibrium moisture content and
temperature across the studied ranges of humidity and temperature.
Materials and methods
2.1 Biomass cultivation and preparation
Arthrospira platensis
strains of type M2 (straight morphology) were sourced from the Pasteur Institute in
France and cultivated at the Bio Gatrana farm in Sidi Bouzid, Tunisia. The
Arthrospira
biomass culture
was fed with a modied Zarrouk medium [15], based on products from the supplier (Bio Gatrana. Tunisia)
[16]. The biomass was diluted in tap water and placed in culture jars. To ensure optimal culture
conditions, lamps were activated, and a magnetic stirrer was used to agitate the medium. The
temperature regulation system was set to maintain 35°C and a thermometer was placed in the culture
jars to monitor the temperature continuously. A lter with a pore size of 40µm was utilized to collect the
biomass for DVS tests, taking approximately 30 minutes to lter 2 liters of solution and yielding between
5 and 10 grams of wet biomass. After ltration, the
Arthrospira
biomass was rinsed with tap water
(distilled water was avoided to prevent osmotic shock to the
Spirulina
). The algae paste was stored in
the refrigerator at 4.0 ± 0.2°C. The initial moisture content of
Arthrospira platensis
which ranged from 80
to 85% (wet basis) was determined using the gravimetric method in a vacuum oven at (105°C ± 1) for 24
h [17].
2.2 DVS (Dynamic Vapor Sorption) apparatus and
experimental procedure
The DVS apparatus used for this study is available at the Laboratory of Automation, Process Engineering
and Pharmaceutical Engineering (LAGEPP), aliated with the University of Claude Bernard Lyon 1 as
illustrated in Fig.1. Dynamic vapor sorption [18], was conducted using a single 10 mg sample of
Spirulina
placed in a cupel. These measurements were performed at the “Surface Measurement
Systems” company in London. The device features an ultra-microbalance with a mass variation
sensitivity of 0.1µg. It operates at temperatures ranging from ambient to 85°C. The reference mass and
the
Arthrospira platensis
sample (ranging from 1 to 150 mg) were placed in quartz trays. A gas ow
composed of a mixture of a dry gas (nitrogen) and saturated vapor was directed over the upper side of

Page 4/22
the
Spirulina
sample in the desired proportion, regulated by a precision ow meter. Combined Rotronic
humidity and temperature probes positioned just below the sample, monitored the relative humidity and
temperature of the surrounding environment. Additionally, a constant dry gas ow swept the
microbalance head to prevent drift or instability in mass measurements caused by humidity
accumulation. The DVS device is fully automated and controlled by the DVS-WIN software package
provided with the instrument, offering a exible and user-friendly interface for setting up and conducting
moisture sorption/desorption experiments.
Figure 1. Photography of the DVS apparatus
2.3 Sorption isotherms
Dynamic vapor sorption isotherms are obtained by exposing a 10 mg sample of
Spirulina platensis
placed in a cupel, to a series of increasing (or decreasing) relative humidity levels in increments of 10%
at a specied temperature. Before conducting the sorption tests, the DVS parameters were optimized
through several preliminary experiments to establish equilibrium moisture between the air and the
product. The equilibrium state was determined when the drying rate (dm/dt) fell below 0.002% per
minute. The dry reference mass was recorded at the end of the (0.1%) relative humidity stage. The
equilibrium moisture content for each relative humidity enables the construction of sorption isotherms.
Figure2 shows an example of a typical water sorption result from a DVS measurement. The kinetic data
shows the change in mass and humidity as a function of time. From the kinetic results. the water
diffusion coecients can be determined
Figure 2. Example of a mass variation curve and the corresponding isotherm of a mineral. [19]
2.4 Modeling of the desorption isotherms
The desorption curves are inuenced by the nature and hygroscopic state of
Spirulina platensis
as well
as the process by which equilibrium is achieved. Numerous theoretical, semi-empirical and empirical
models are available in the literature to describe the experimental data of desorption isotherms [20–21].
The most recognized models are listed in Table1. Among these, the GAB model which has three
parameters, is widely considered to be a robust theoretical model for most agri-food products, across a
broad range of water activity levels [22].

Page 5/22
Table 1
Applied models to t desorption isotherms data.
Models Equation References
GAB (Von W.A Guggenheim, 1966)
Oswin (C.R. Oswin, 2007)
Smith (Sherman E. Smith, 1947)
Henderson (Henderson S.M, 1952)
Peleg (Micha Peleg, 1993)
Table1. Models used to t desorption isotherm data.
2.5 Statistical analysis
The chi-square test (R2) and the relative mean deviation χ 2 were employed to evaluate the t of the
drying models [27–28]. Their mathematical expressions are provided in Eq.(1) and Eq.(2):
(1)
(2)
where: XRi.exp is the i-th value of the experimental moisture content. XRi.pre is the i-th value of the
moisture content predicted by the selected model. XR is the average moisture content. N is the number
of observations and z is the number of constants.
2.6 Isosteric heat
Xw
=
X
0
CKaw
(1−
Kaw
)(1+(
C
−1)
Kaw
)
Xw
=
A
( )
b
aw
1−
aw
Xw
=
A
+
Bln
(1 −
aw
)
Xw
= (− )
(ln(1−
aw
)
A
1
B
Xw
=
AawB
+
CawD
R
2= 1 −
n
∑
1(
XRi
,exp −
XRi
,
pre
)2
n
∑
1(¯¯¯¯¯¯¯¯¯
XR
−
XRi
,
pre
)2
χ
2=
n
∑
1(
XRi
,exp −
XRi
,
pre
)2
N
−
z

Page 6/22
The net isosteric heat characterizes the binding energy of water to the substrate. It represents the
additional heat beyond the heat of vaporization of pure water, that must be supplied to the product for
dehydration [28]. The heat of desorption can be evaluated from the desorption isotherms [29], based on
the Clausius-Clapeyron equation as cited in Eqt (3):
(3)
To describe the relationship between the net isosteric heat of desorption Qst.n and the moisture content,
Tsami (1991) proposed the following empirical correlation [30]:
Qst.n= q0 exp (-Xeq/X0)
where Xeq is the equilibrium moisture content (Kg/Kg dry basis). q0 is the net isosteric heat of desorption
for the rst molecular layer of water (KJ/mol). (Qst.n →q0 as Xeq →0).
2.7 Estimation of moisture diffusion coecient
The water diffusion coecient is a crucial property for accurately designing and controlling drying
processes, as well as related operations such as storage. The effective diffusion coecient (Deff) is
calculated from water desorption kinetics using the complete solution of Fick's second law under the
assumptions that humidity is uniformly distributed within the product, the medium is isotropic and
homogeneous, the diffusion coecient (Deff) is constant and that product contraction is negligible [31].
Second law of Fick is expressed in Eq.(4) as follows:
(4)
where. X is the local dry basis moisture content. t is the time (s). r is the spatial variable and Deff is the
diffusion coecient
The general solution to Eq.(4) proposed by Crank takes the form of an innite series. [32] as expressed
in Eq.5
5
= −
∂ ln(
aw
)
∂( )
1
T
Qst
,
n
R
=
Deff
dX
dt
∂2
X
∂2
r
XR = =
∑
∞
n=0 exp(− )
X − Xeq
X0− Xeq
8
π
2
1
(2n + 1)2
(2n + 1)2
π
2Deff. t
4e2

Page 7/22
Where, XR is the reduced moisture content, X0 is the initial moisture content, X is the average moisture
content at time t, Xeq is the average equilibrium moisture content and L is the sample thickness.
When the diffusion time is suciently long, all terms in the series become negligible compared to the
rst term [24], resulting in Eq.6:
6
The effect of temperature on the diffusion coecient generally follows an Arrhenius-type law [25] as
expressed in Eq.7:
7
Where D0 is the pre-exponential factor, Ea is the activation energy, R is the ideal gas constant. and T is
the product temperature.
Equation (7) can be rearranged as:
Results and discussions
4.1 Desorption isotherms
The desorption isotherms for
Spirulina Platensis
at temperatures of 25°C, 40°C, 50°C, 60°C and 80°C,
and over a water activity range of 10 to 80%, are shown in Fig.3. The curves represent the averages of
two repetitions for each experiment, reecting the high reproducibility of the tests (p < 5%) and the
lengthy duration of each manipulation, which exceeds three days.
Figure 3.
Arthrospira platensis
desorption isotherms.
According to the BET classication. the desorption isotherms of
Spirulina Platensis
take the sigmoid
form of type II as reported by Desmorieux. Oliveira and Pâmella de Carvalho Melo [8. 33–34]. one can
note also that temperature had a signicant effect on desorption isotherms in all studied RH ranges for
Spirulina platensis
. Indeed. at a constant RH. the
X
eq values decreased as T increased.
4.2 Fitting of
Spirulina platensis
desorption isotherms
lnXR = ln
( )
−
8
π
2
π
2Deff. t
4e2
Deff
=
D
0exp(− )
Ea
RT
lnDeff
= ln
D
0− .
( )
Ea
R
1
T

Page 8/22
To determine the predictive correlation of the experimental desorption isotherms, ve models cited in
Table1 were tested. For each operating condition, the parameters of the models, along with the selection
criteria are summarized in Table2.

Page 9/22
Table 2
Values of the tested models parameters for the different temperatures
models Temperature (°C) Models parameters R2X2
GAB 25 X0 = 1.1951E-01 0.9997 0.0032
C = 1.0209E + 00
K = 9.7118E-01
40 X0 = 1.1255E-01 0.9977 0.0059
C = 1.1534E + 00
K = 8.2559E-01
50 X0 = 2.1841E-01 0.9973 0.0053
C = 5.3129E-001
K = 6.8439E-001
60 X0 = 1.5200E-01 0.9984 0.0029
C = 1.0408E + 00
K = 5.7888E-01
80 X0 = 2.8390E-02 0.9990 0.0014
C=-6.8972E-10
K = 9.0795E-001
OSWIN 25 A = 1.1426E-01 0.9997 0.0032
B = 9.3817E-01
40 A = 8.4770E-02 0.9965 0.0067
B = 7.3242E-01
50 A = 7.7419E-02 0.9950 0.0063
B = 6.3353E-01
60 A = 6.0731E-02 0.9921 0.0060
B = 6.0130E-01
80 A = 5.2106E-02 0.9946 0.0036
B = 4.9837E-01
SMITH 25 A=-2.9860E-02 0.9787 0.0299

Page 10/22
models Temperature (°C) Models parameters R2X2
B = 2.4904E-01
40 A=-5.1462E-03 0.9944 0.0085
B = 1.4057E-01
50 A = 2.8146E-03 0.9959 0.0057
B = 1.1115E-01
60 A = 2.9237E-03 0.9965 0.0040
B = 8.4321E-02
80 A = 8.3095E-03 0.9898 0.0050
B = 6.0828E-02
HENDERSON 25 A = 2.8839E + 00 0.9982 0.0086
B = 6.5723E-01
40 A = 5.8353E + 00 0.9971 0.0061
B = 8.7274E-01
50 A = 9.3970E + 00 0.9956 0.0059
B = 1.0333E + 00
60 A = 1.4246E + 01 0.9974 0.0034
B = 1.0940E + 00
80 A = 3.6053E + 01 0.9993 0.0012
B = 1.3561E + 00
PELEG 25 A = 1.3354E + 00 0.9915 0.0224
B = 2.7232E + 00
C = 5.9939E-01
D = 2.7205E + 0
40 A = 1.1723E + 00 0.9899 0. 0138
B = 1.9747E + 00
C = 8.3130E-01
D = 1.9891E + 0
50 A = 1.1235E + 00 0.9890 0.0111

Page 11/22
models Temperature (°C) Models parameters R2X2
B = 1.5453E + 00
C = 8.7717E-01
D = 1.5416E + 0
60 A = 1.0912E + 00 0.9958 0.0051
B = 1.5079E + 00
C = 9.0925E-01
D = 1.5163E + 01
80 A = 1.06214E + 00 0.9975 0.0029
B = 1.1165E + 00
C = 9.3786E-01
D = 1.1155E + 00
Table2. Values of the tested model parameters for different temperatures
the GAB equation proved to be the most suitable for representing the experimental data within the
studied ranges of water activities and temperature. The monolayer moisture content
X
m value is
particularly important for the stability of solid substrates, as it indicates the moisture content at which
the rates of lipid oxidation, non-enzymatic browning and enzyme activity are minimized [35–36]. The
(
X
m) values for
Spirulina
alga at 25 and 40°C were found to be 0. 119 and 0.112 Kg/Kg (dry basis) for
desorption data. Cheng et al (2023) reported
Xm
values for chlorella powders at 20 and 40°C of 0.0526.
and 0.0456 Kg/kg (dry basis), and for
Spirulina
powders, they found values of 0.0581. and 0.0420 Kg/Kg
(dry basis) for adsorption data, respectively [37].
4.3 Calculation of net isosteric heat of desorption
The net isosteric heat of desorption was graphically determined from the sorption isosteres which
represent the relationship between temperature and water activity for constant moisture content as
described by Eq.(3). In a logarithmic diagram. the lines were plotted with -ln (aw) in ordinates and 1 / T
on the abscissa as shown in Fig.4.
Figure 4. Desorption isosteres of
Arthrospira platensis
for different moisture contents.
Desorption isosteres are generally described by Clausius Clapeyron equation [37]. The slope of the
isosteres curves allows for the determination of the corresponding net isosteric heat of desorption for
each moisture content as illustrated in Fig.5.
Figure 5. Variation of net isosteric heat of desorption as a function of moisture content.

Page 12/22
Analysis of the curve showing the net isosteric heat of desorption as a function of equilibrium moisture
content indicates its signicance for low moisture levels in
Spirulina
. Specically, the net isosteric heat
Qst for
Spirulina Platensis
decreased from 21.3 to 4.29 KJ/mol as the equilibrium moisture content
increased from 0.02 to 0.1 Kg/Kg (dry basis). This decrease is attributed to the strong binding of water
molecules to the solid matrix, which necessitates considerable additional heat beyond the latent heat of
vaporization to effectively dehydrate the product.
A study by Moreira et al. (2017) found that the
Q
st values for
Fucus vesiculosus
seaweed decreased
from 21.24 to 0.01 KJ/mol as the
X
e increased from 0.07 to 0.34 Kg /Kg (dry basis). suggesting that the
interaction energy between water and seaweed samples in the high moisture region was similar to that
between pure water molecules [38]. Yu et al. (2019) reported a decrease in the
Q
st value for the probiotic-
fermented sea tangle powder. from 15.02 to 0.49 KJ/mol as the
X
e increased from 0.02 to 1.29 Kg/Kg
(dry basis) at temperatures ranging from 4°C to 37°C which aligns with our ndings [39]. Fitting the
evolution curve of the isosteric heat with respect to the equilibrium moisture content using the Tsami
equation [30]. yields the following expression (Eqt(8)):
Q = 35.49*exp (-xeq/0.037) (8)
4.4 Determination of moisture diffusion coecient
Starting from Eq.(6), we plotted the curves of -Ln(aw) as a function of time. The diffusion coecient
values were extracted for each relative humidity from the desorption kinetics. Figure6 illustrates the
water diffusivity values for various moisture contents, ranging from 0.003 Kg/Kg to 0.2 Kg/Kg (dry basis),
across a temperature range of 40°C to 80°C. The indicated moisture content represents the average for
the corresponding relative humidity level.
Figure 6. Variation of the diffusion coecient as a function of the equilibrium moisture content.
The data show that effective diffusivity increases with rising moisture content for
Spirulina platensis
at
the studied temperatures. During the desorption process, the diffusion coecient values ranged from
2.75 × 10− 8 to 2.881 × 10− 7 m2s− 1 for temperature between 40°C and 80°C. Goneli (2008) explained that
as temperature increases, the vibration of water molecules intensies, resulting in decreased product
viscosity [40]. Notably, the effective diffusion coecients for
S. platensis
at the studied temperatures
were higher than those for many agri-food products reported in the literature. This can be attributed to
the chemical composition of
S. platensis
which has weak water interactions with nutrients, allowing for
greater molecule vibration and reduced viscosity.
Numerous empirical parametric equations expressing diffusivity as a function of moisture content can
be found in the literature with a compilation by Zogzas et al. 1996. [41]. The inuence of temperature can
be effectively described by an Arrhenius-type relationship [25]. However, the impact of moisture content
has not yet been framed within a widely accepted general model. The diffusion coecient can be
expressed by the following Eq.(9):

Page 13/22
9
Here, A generally follows the Arrhenius law and can be expressed as:
9a
By plotting Ln(A) against (1/T), we can determine the activation energy. Similarly, we can analyze how B
varies with temperature. The values of A and B are obtained by tting the curves describing D = f(Xeq)
using an exponential function of the form a*exp(b*x). Thus. it can be concluded that for moisture
contents ranging from 0.003 to 0.2 Kg / Kg (dry basis) and temperatures from 40°C to 80°C. the liquid
water diffusivity of
Spirulina platensis
can be expressed by the following empirical Eq.(9b):
The activation energy represents a barrier that must be overcome for the diffusion process to occur [41–
42]. For liquid diffusion in
S.platensis
, the activation energy (Ea) was found to be 33.71 KJ.mol− 1, wich
alligns with the ndings of Zogzas et al. (1996) where activation energies for agri-food products ranged
from 12.7 to 110 KJ mol− 1. [41].
Table3 shows the effect of temperature and air relative humidity on the diffusion coecient. The
indicated moisture content is that of the product at the beginning of the considered humidity stage:
Table 3
The effect of temperature and air relative humidity on moisture diffusion coecient
Effect of temperature at HR = 60% Effect of relative humidity at T = 50°C
T (°C) D (m2/s) HR(%), X0(Kg/Kg dry basis) (%) D (m2/s)
40 2,75E-08 10, X0 = 2,98 1,60E-08
50 4,05E-08 30, X0 = 5,53 3,14E-08
60 7,16E-08 50, X0 = 8,71 4,01E-08
80 15,7E-08 70, X0 = 15,24 5,76E-08
Table3. The effect of temperature and air relative humidity on the moisture diffusion coecient
D
=
A
×
exp
( )
−
B
T
A
=
a
×
exp
( )
−
Ea
RT
D
(
X
.
T
) = 13.709 × 10−08 exp
( )
×
exp
[(−0.1566
T
+ 59.284)
X
]
−33704
RT

Page 14/22
The diffusion coecient increases with the relative humidity of the air. Furthermore, temperature has a
clear inuence on moisture content, with higher temperature generally leading to an increase in the
diffusion coecient increases.
Conclusion
The purpose of this study was to determine the desorption isotherms of
Spirulina Platensis
using the
dynamic vapor sorption technique and to establish predictive correlations for its thermo-hygroscopic
properties based on experimental methods and physical laws. Our results lead to the following
conclusions:
-The desorption isotherms of
Spirulina Platensis
, obtained within the temperature range of 25°C to 80°C
exhibited type II behavior, which is characteristic of many agri-food products.
-Among the empirical and semi-empirical sorption models tested, the GAB model is recommended for
predicting the desorption isotherms within the studied range of temperatures and water activities.
-The net isosteric heat of desorption for
Spirulina Platensis
decreased from 21.3 to 4.29 Kj/mol as the
equilibrium moisture content increased from 0.02 to 0.1 Kg/Kg (dry basis).
- The diffusion coecient increased from 2.75 × 10− 8 to 15.7 × 10− 8 m2 s− 1 over the temperature range
of 40°C to 80°C indicating an activation energy for liquid diffusion in
S. platensis
of 33.7 KJ.mol− 1.
Declarations
Acknowledgments.The authors acknowledge the scientic support provided by LAGEPP members and
want to thank Mr. Lazheri Nouri from Bio Gatrana Farm for providing
Spirulina
platensis
biomass and Mr.
Abderrazek Zaaraoui for technical support.
Competing interestsThe authors have no competing interests to declare that are relevant to the content
of this article.
FundingThis research did not receive any specic grant from funding agencies in the public.
commercial. or not-for-prot sectors.
Availability of Data and MaterialsThe authors conrm that the data supporting the ndings of this study
are available within the article. Raw data that support the ndings of this study are available from the
corresponding author. upon reasonable request.
References
1. R. A. Soni. K. Sudhakar. R. S. Rana. Spirulina: From growth to nutritional product: A review. Trends in
Food Science & Technology. (2017) 69. 157–171

Page 15/22
2. L. Vernes. P. Granvillain. F. Chemat. M. Vian. Phycocyanin from Arthrospira platensis. Production.
extraction and analysis. Current Biotechnology (2015) 4. 481–491.
3. H. Desmorieux. N. Decaen. Convective Drying of Spirulina in Thin Layer. Journal of Food Engenering
(2005) 66. 497-503.
4. C. Chen. J. Chang. D. Lee. Dewatering and drying methods for microalgae. Drying Technology.
(2015) 33. 443–454.
5. E. G. Oliveira. J. H. Duarte. K. Moraes. V. T. Crexi.L. A. A. Pinto . Optimization of Spirulina platensis
convective drying: Evaluation on phycocyanin loss and lipid oxidation. International Journal of Food
Science and Technology. (2010) 45. 1572–1578.
. K. Show. D. Le. J. Tay. T. Lee. J. Chang. Microalgal drying and cell disruption: Recent advances.
Bioresource Technology. (2014)184. 258–266.
7. D. Mariana. J. O. de Moraes. M. C. Ferrari. F. D. Neves. Production of Spirulina (Arthrospira platensis)
powder by innovative and traditional drying techniques. Journal of Food Process Engineering.
(2021) 45(1).
. H. Desmorieux. F. Hernandez. Biochemical and Physical Criteria of Spirulina after Different Drying
Processes. Proceedings of the 14th International Drying Symposium (IDS 2004). Sào Paulo. 22-25.
(2004) 900-907.
9. N. C. Silva. M. V. C. Machado. R. J. Brandão. C. R. Duarte. M. A.S. Barrozo. Dehydration of
microalgae Spirulina platensis in a rotary drum with inert bed. Powder Technology. (2019) 351. 178–
185.
10. T. Ghnimi. L. Hassini. M. Bagane. Convective and infrared drying assisted by capillary drainage of
spirulina: a real possibility to reduce the energy consumption. Heat and Mass Transfer. (2019) 55(5).
11. T. Ghnimi. L. Hassini. M. Bagane. Experimental study of water desorption isotherms and thin-layer
convective drying kinetics of bay laurel leaves. Heat and Mass Transfer (2016) 52(12).
12. L. Hassini. E. Bettaieb. H. Desmorieux. S. S. Torres. A.Touil.Desorption isotherms and
thermodynamic properties of prickly pear seeds. Industrial Crops and Products. Volume 67 (2015)
457-465.
13. Q. shu. L. C. F.liao. B.Q. xu. W.Q. zou. Recovery of rare earth element ytterbium(III) by dried
powdered biomass of spirulina: Adsorption isotherm. kinetic and thermodynamic study.
Transactions of Nonferrous Metals Society of China. (2021) 31(4):1127-1139.
14. M. Pedrosa. R.S. Ribeiro. S. G. Rodríguez. J. R. Chueca. E.Rodríguez. A.M.T. Silva. M. Ðolic. A. R. L.
Ribeiro. Spirulina-based carbon bio-sorbent for the ecient removal of metoprolol. diclofenac and
other micropollutants from wastewater. Environmental Nanotechnology. Monitoring and
Management.(2022)Volume 18. 100720.
15. C. Zarrouk. Contribution à l’étude d’une cyanophycée : Inuence de divers facteurs physiques et
chimiques sur la croissance et la photosynthèse de Spirulina maxima. Ph.D. Thesis. Université de
Paris. Paris (1966).

Page 16/22
1. T. Ghnimi. L. Hassini. M. Bagane. Intensication of the convective drying process of Arthrospira
(Spirulina) platensis by capillary draining: effect of the draining support. Journal of applied
phycology. (2019) Volume 31. pages 2921-2931.
17. AOAC (1995) Ocial Methods of Analysis. 14th Edition. Association of Ocial Analytical Chemists.
Washington DC.
1. Y. Y. J. Heng. D. Williams. Vapour Sorption and Surface Analysis. In Solid state characterization of
pharmaceuticals. A. Richard. IY.S.Storey. Eds. Chichester. UK: John Wiley & Sons. Ltd. 2011. pp 268-
276.
19. A. Leonard. Multi-scale Characterization of Porous Media. Université de Liège. Chemical
Engineering. CARPOR ULiège. http://www.carpor.uliege.be
20. S. Brunauer. P.H. Emmett. E.Teller. Adsorption of Gases in Multimolecular Layers. Journal of the
American Chemical Society. (1938) 60. 309-319.
21. S.M. Henderson. A basic concept of equilibrium moisture. Agricultural Engineering. (1952) 33. 29-
32.
22. S. Yanniotis. J. Blahovec. Model analysis of sorption isotherms. LWT - Food Science and
Technology. Volume 42. Issue 10. (2009)1688-1695.
23. V. W. A. Guggenheim. Applications of Statistical Mechanics. Clarendon Press/Clarendon University
Press. London (1966). 1. Au.. 211 S.. zahlr. Abb.. Gl 55s.
24. C. R. Oswin. The kinetics of package life. III. The isotherm. J. Soc. Chem. Ind. (1946) 65(12). 419–
421.
25. S. E. Smith. The sorption of water vapor by high polymers. J. Am. Chem. Soc.. (1947) 69(3). 646–
651.
2. M. Peleg. Assessment of a semi-empirical four parameter general model for sigmoid moisture
sorption isotherms. J. Food Process Engineering. (1993) 21-37.
27. A. Midilli. H. Kucuk and Z. Yapar. A New Model for Single Layer Drying of Some Vegetables. Drying
Technology: An International Journal. Vol. 20. No. 7. (2002)1503-1513.
2. A. Midilli. H. Kucuk. Mathematical modeling of thin layer drying of pistachio by using solar energy.
Energy Conversion and Management. (2003) 44(7):1111-1122.
29. K.Wan. H. Qiongqiong. M. Zhenyong. L.Xuejing. H. Shaomeng.Water desorption isotherms and net
isosteric heat of desorption on lignite. Fuel. Volume 171 (2016)101-107
30. E.Tsami. Net isosteric heat of sorption in dried Fruits. J. Food Eng. 14 (1991)327–335
31. M. Zielinska. M. Markowski. Air drying characteristics and moisture diffusivity of carrots. Chemical
Engineering and Processing: Process Intensication. 49 (2). (2010) 212-218.
32. H. Toğrul. N. Arslan. Moisture Sorption Behaviour and Thermodynamic Characteristics of Rice
stored in a Chamber under Controlled Humidity. Biosystems Engineering. 95(2) (2006) 181-195.
33. E.G. Oliveira. G.S. Rosa. M.A. Moraes. L.A.A. Pinto. Characterization of thin layer drying of Spirulina
platensis utilizing perpendicular air ow. Bioresource Technology. 100(3). (2009)1297-1303.

Page 17/22
34. D. C. M. Pamella . A. D. Ivano. C.F.Lisboa. H. T. D.Pedro. Kinetics drying of Spirulina platensis. African
Journal of Agricultural Research (2016) 11(45):4683-4691.
35. A. Vega-Gálvez. M. Miranda. J. Vergara. E. Uribe. L. Puente. E. A. Martínez. Nutrition facts and
functional potential of quinoa (Chenopodium quinoa willd.). an ancient Andean grain: a review.
Journal of the science of food and agriculture. 90(15). (2010) 2541-2547.
3. A. L. D. Goneli. P. C. Corrêa. G. H. H. De Oliveira. C. F. Gomes. F. M. Botelho. Water sorption
isotherms and thermodynamic properties of pearl millet grain. International Journal of Food
Science+ Technology. 45(4) (2010) 828-838.
37. K. Mounir. N. Kechaou. M. Fliyou. Experimental study of sorption isotherms and drying kinetics of
Moroccan Eucalyptus Globulus. Drying Technology. 10(10) (2002) 2027-2039.
3. F. Moreira. J. Chenlo. S. Sineiro. S. A. Sexto. Drying temperature effect on powder physical
properties and aqueous extract characteristics of Fucus vesiculosus. Journal of Applied Phycology.
28 (2016) 2485-2494.
39. D. Yu. K. Moojoong. Y.M. Kim. G. Kwon. Moisture sorption characteristics of probiotic‐fermented sea
tangle powder and its thermodynamic properties. Journal of Food Processing and Preservation.
(2019) 43(7): e13991.
40. I. Doymaz. M. Pala. The Thin-Layer Drying Characteristics of Corn. Journal of Food Engineering.
(2003) 60. 125-130.
41. N. Zogzas. Z. Maroulis. D. Marinos-Kouris. Moisture Diffusivity Data Compilation in Foodstuffs.
Drying Technology (1996).
42. X. Cheng. P. Ling. M. S. Iqbal. F. Liu. J. Xu. X. Wang. Water adsorption properties of microalgae
powders: Thermodynamic analysis and structural characteristics. Journal of Stored Products
Research. (2023) Vol 101.102093.
Figures

Page 18/22
Figure 1
Photography of the DVS apparatus
Figure 2
Example of a mass variation curve and the corresponding isotherm of a mineral.

Page 19/22
Figure 3
Arthrospira platensis
desorption isotherms.

Page 20/22
Figure 4
Arthrospira platensis
desorption isosteres for different moisture content.

Page 21/22
Figure 5
Variation of net isosteric heat of desorption as a function of moisture content

Page 22/22
Figure 6
Variation of the diffusion coecient as a function of the equilibrium moisture content.