Vol.4, No.9B, 63-69 (2013) Agricultural Sciences
http://dx.doi.org/10.4236/as.2013.49B011
Copyright © 2013 SciRes. OPEN ACCESS
Water sorption isotherms of globe artichoke leaves
Luis Mayor1, Alejandro Calvo1, Ramon Moreira2, Pedro Fito1, Esperanza Garcia-Castello1*
1Instituto Universitario de Ingeniería de Alimentos para el Desarrollo, Universitat Politécnica de València, Camino de Vera s/n,
46022 Valencia, Spain; *Corresponding Author: egarcia1@iqn.upv.es
2Departamento de Enxeñaría Química, Universidade de Santiago de Compostela, Rúa Lope Gómez de Marzoa s/n, E-15782 Santiago
de Compostela, Spain
Received August 2013
ABSTRACT
One third of the artichoke production is used in
industrial processes, where up to 70% - 85% of
the initial raw material is transformed into solid
wastes. For an adequate management of these
wastes, it is necessary to know their water
sorption properties, because physical, chemical
and biological changes which occur during their
storage depend on water-solid interactions. The
objectives of this work are to experimentally
determine equilibrium sorption (adsorption and
desorption) data of artichoke wastes at different
temperatures (25˚C - 55˚C), as well as correlate
and predict water sorption isotherms using bib-
liographic models. Equilibrium moisture content
ranged 0 - 0.6 kg water/kg dry solid (water activ-
ity 0.05 - 0.9). Water sorption isotherms were
classified between Types II and III. Hysteresis
phenomenon was not observed, neither w as the
dependence of the equilibrium data with tem-
perature. BET, GAB, Oswin and Peleg correla-
tion models were satisfactorily fitted to experi-
mental data. A predictive model based on com-
position and physical state of artichoke waste
components was also successfully used to re-
produce experimental data.
Keywords: Food Waste; Modeling; Moisture; Water
Activity
1. INTRODUCTION
Artichoke (Cynara scolymus L.) is an herbaceous plant
from the Astaraceae family originally from the Mediter-
ranean area, although currently is cultivated and con-
sumed worldwide. The edible part is its unripe inflores-
cence. The most appreciated parts are the soft internal
leaves and the fleshy parts of its centre, and both parts
together are called artichoke hearts.
One third of the artichoke production is used in indus-
trial processes, mainly for the production of canned or
frozen artichoke hearts [1]. In both processes, food wastes
make up to 70% - 85% of the initial raw material [2].
These wastes, made up of defective raw artichokes and
above all stems and external leaves, present management
problems. As high moisture organic materials are perfect
substrate for fermentations or for the development of
insects and rodents. By the other hand, the cost of their
transportation is expensive due to their high moisture
content. Currently these wastes are used for animal feed,
although other alternatives are also compost production
[2], methane [3] and bioalcohol production [4]. There are
also other less explored possibilities, i.e. the extraction of
functional compounds such as inulin and phenolics [5].
These compounds, extracted and purified, can be used as
raw material for other industrial processes.
For an adequate management and valorization of these
wastes, it is necessary to know their water sorption iso-
therms. These are plots of the equilibrium moisture con-
tent (X, kg water/kg dry solid (ds)) vs. water activity (aw)
at a certain temperature and pressure. Moisture content
and water activity data are important to evaluate the phys-
ical, chemical and biological changes which occur during
processing and storage of biomaterials [6] in processes
where water transfer exists, such as drying, packaging
and rehydration of dehydrated products [7]. In this con-
text, the knowledge of the water sorption isotherms of
artichoke wastes will provide very useful information to
select the best conditions of their storage. It will also be
useful in the design and optimization of valorization
processes where water removal is involved, such as dry-
ing.
Furthermore, it will be of interest to obtain, within the
studied temperature and water activity ranges, mathe-
matical models that relate water activity with moisture
content and temperature. For this purpose are usually
employed empirical or semi-empirical equations, being
the parameters of these equations obtained through the
fitting of experimental data. Examples of these correla-
tion models are the BET model [8], the GAB model [9]
and others [10-14]. Recently, some models have arisen
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
64
that allow predicting food water sorption isotherms from
the chemical composition. These models use the Ross
equation [15] and account for the multiphasic nature of
food systems [6,16].
The objectives of this work were to experimentally
determine sorption (adsorption and desorption) isotherms
of artichoke wastes (external leaves) at different temper-
atures, as well as obtain water sorption isotherms through
different models from the literature. For the last purpose,
correlation models as well as those based on the food
chemical composition were used.
2. MATERIALS AND METHODS
2.1. Sample Preparation
Artichokes (Cynara scolymus L, “Blanca de Tudela”
variety) were purchased in a local market, selecting those
with similar color, size and compactness. Then they were
stored in hermetic containers at 5˚C until use. Previously
to the experiments, artichokes were separated in their
different parts: stem, fleshy centre, internal and external
leaves. External leaves were used as solid waste since
they are 90% in weight of the total solid wastes.
2.2. Proximate Composition
2.2.1. Moisture Content
Moisture content, X, was calculated by determining
sample mass before and after dehydration in a vacuum
oven (Vaciotem-T, SELECTA) at 60˚C and less than 13
kPa till constant weight. Determinations were performed
in triplicate.
2.2.2. Reducing Sugars and Inulin
Dehydrated leaves were ground (GVX 242, KRUPS)
and 5 g of fine powder were extracted in 500 mL of wa-
ter during 100 min at 80˚C [17]. The filtered extract was
diluted and analyzed for reducing sugars (glucose, fruc-
tose and sucrose) content by ionic chromatography (Me-
trosep carb 1250/4.6 column, Ion Analysis cromatograph,
Methrom). Inulin was indirectly calculated by determin-
ing reducing sugars content in the filtered extract before
and after acidic hydrolysis [18]. Inulin content was given
by the following equation:
mg eq fructoseΔsucrose
Inulin0.9( fructose)
L extract2

 


(1)
where Δfructose (mg/L) is the increase of fructose and
Δsucrose (mg/L) is the decrease of sucrose after hydroli-
sis. 0.9 is a constant for the conversion of hydrated fruc-
tose to anhidrofructose [19].
2.2.3. Other Proximal Components from Food
Composition databases
Protein, fat, insoluble fiber and inorganic salts were
determined by consulting food composition databases
from the literature. The consulted food databases were:
National Nutrient Database for Standard Reference [20],
Danish Food Composition Databank [21] and Spanish
Food Composition Database [22].
2.3. Water Sorption Isotherms
Equilibrium moisture content of artichoke leaves at
different water activities and temperatures (25˚C, 35˚C,
45˚C and 55˚C) were determined by the static method
[23]. All determinations were performed in triplicate
using ca. 1.5 g of fresh leaves for the desorption iso-
therms and 0.5 of freeze-dried leaves (LyoAlfa 6/50,
Telstar) for the adsorption isotherms. Determinations were
performed in a range of water activity from 0.05 to 0.90
using different saturated saline solutions. Selected salts
were KOH, LiCl, MgCl2, K2CO3, Mg(NO3)2, NH4NO3,
NaCl, KCl and BaCl2. Each saturated solution was in-
troduced in a hermetic container, along with vials con-
taining the sample. For water activities above 0.65 a vial
with thymol was also introduced to avoid microbial growth.
Closed containers were introduced in an oven (Conterm
2000201, JP selecta) at the selected temperature. Equili-
brium between samples and their environment was at-
tained when weight variations measured each 7 days
were lower than that 0.1%. Moisture content of equili-
brated samples was determined as described in 2.2.1.
2.4. Sorption Isotherms Modeling
2.4.1. Correlation Models
Bibliographic models with different number of para-
meters were selected for the fitting sorption data. The
models are as follows:
- BET [8]


111
w
ww
aba
Xaba




(2)
- GAB [9]


1(11)
w
ww
abca
Xcab ca

  (3)
- Halsey [10]
1
ln
b
w
a
Xa
(4)
- Henderson [11]

1
ln 1b
w
a
Xa
(5)
- Oswin [12]
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
65
()
1
b
w
w
a
Xa a
(6)
- Peleg [13]
 
bd
ww
Xaaca (7)
- Smith [14]
ln(1 )
w
X
ab a  (8)
The fitting of these models to the experimental data
was performed through the nonlinear optimization tool
Solver of Excel 2007 (Microsoft, Redmond, WA, USA).
2.4.2. Predictive Model Based on Food
Composition
For simplification in the calculations only the proxim-
al composition of the artichoke leaves was used: soluble
sugars (glucose, fructose and sucrose), inulin, proteins,
insoluble fiber (as cellulose) and soluble inorganic salts
(as KCl). In this algorithm, previously described in detail
[6], water activity of the food material is determined as
the product of the water activity of each component, as-
suming that each component has an independent beha-
vior and considering their solubilities in water. Water
activity of soluble compounds was determined in the
case of non-electrolitic compounds (glucose, fructose and
sucrose) by the Norrish equation [24] and for electrolytic
compounds by the Pitzer equation [25]. Water activity of
non-soluble compounds (fiber, protein, inulin) and non-
solubilized fraction of solubles (sugars and KCl) was
determined through water sorption isotherms from the
literature [26,27]. To simplify the model it was consi-
dered that in the studied temperature range sugar sorp-
tion isotherms are constant. Solubility was calculated
through specific equations for each soluble component
[16].
The prediction algorithm consists in an iterative process
started with a supposed water activity value for insoluble
compounds and food equilibrium moisture content. Then
for this moisture content it is determined the fraction of
soluble compounds, and water activity of soluble and
insoluble compounds are calculated at each step accord-
ing to the following convergence criteria: a) aw of soluble
compounds aw of insoluble compounds; b) if aw of so-
luble compounds < initially supposed aw for insoluble
compounds, then it is necessary to add an amount of wa-
ter till both water activities are equal.
Finally, the results of the application of the algorithm
are pairs of data water activity and its corresponding
equilibrium moisture content. The algorithm has to be
repeated as times as pairs of data are required to build the
sorption isotherm. All calculations were performed through
the software Excel 2007.
2.5. Statistical Analysis
Experimental sorption data shown were the average
value of three experimental determinations. Goodness of
fit of the models was evaluated by the following para-
meters: mean relative deviation (E), median of the rela-
tive deviations, coefficient of determination (R2) and the
root mean square deviation (ERMS):
exp
exp
1
100 cal
Nii
ii
XX
ENX
(9)

12
2
exp
1
1N
RMS cal
i
EXX
N

(10)
Where cal
i
X
y exp
i
X
are the calculated and experi-
mental moisture content values, respectively, and N is the
number of experimental data. Calculations were per-
formed with the Excel 2007 software.
3. RESULTS AND DISCUSSION
3.1. Proximal Composition of Artichoke
External Leaves
Ta b l e 1 shows the proximal composition of artichoke
wastes (external leaves), obtained from moisture content,
sugars and inulin determinations, as well as information
of food composition databases.
Data from Tabl e 1 were obtained as follows: a) Mois-
ture content was determined experimentally; b) reducing
sugars and inulin were also experimentally determined; c)
protein, fat and inorganic salts are the average values of
the three consulted food composition databases. Since
potassium is by far the main inorganic cation, inorganic
salts are given in KCl equivalents. This simplification
makes easier the use of the model described in 2.4.2; d)
finally, cellulose as insoluble fiber was obtained through
a mass balance between total solids content and the other
proximal components calculated previously.
Table 1. Proximal composition of artichoke external leaves.
Component % (wet basis) % (dry basis)
Water 83.74 -
Protein 3.16 19.41
Insoluble fiber (cellulose) 8.74 53.78
Inulin 1.93 11.86
Fat 0.18 1.13
Inorganic salts (KCl) 1.02 6.27
Glucose 0.23 1.41
Fructose 0.51 3.12
Sucrose 0.49 3.00
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
66
Protein, fat, inorganic salts and fiber are an approxi-
mation to the real values, since they have been obtained
from food databases. Furthermore, in these tables the
values are for the whole artichoke.
3.2. Sorption Isotherms
Figure 1 shows experimental sorption data of arti-
choke external leaves at different temperatures. Moisture
content for each water activity is the average of three
replicates.
It is observed a similar trend for all the isotherms;
moisture content increases with water activity progres-
sively, very smoothly at low moisture contents and asymp-
totically from water activity of 0.8. For this, isotherms
show a slightly sigmoid shape between types II and III
proposed by IUPAC [28]. Equilibrium moisture content
ranged 0 - 0.6 kg water/kg ds. Both shape of isotherms
and equilibrium moisture content ranges are similar to
other food products such as pumpkin [29], pepper [30]
and garlic [31].
It can be also observed that adsorption and desorption
isotherms are overlapped, indicating that hysteresis is not
produced. This phenomenon is observed as a displace-
ment between adsorption and desorption isotherms, be-
ing the last one above the first. The hysteresis is conse-
quence of irreversible phenomena of conformational and
structural rearrangements, which alter the accessibility of
energetically favorable polar sites and thus may hinder
the movement of moisture [32]. It is well known that
freeze-drying is a dehydration process where the struc-
tural collapse is minimized, leading to products with high
rehydration capability [33]; then the use of this drying
technique in the preparation of samples for the adsorp-
tion experiments may have influenced on the absence of
hysteresis.
An effect of temperature on the water sorption iso-
therms is not observed, indicating that the external arti-
choke leaves show similar hygroscopicities within the
studied temperature range (25˚C - 55˚C). The effect of
temperature is more evident at higher temperatures and
wider ranges. At moderate temperatures less physical and
chemical changes are promoted, and the attained energy
levels do not allow significant water mobility changes.
This behavior at moderate temperatures has been ob-
Figure 1. Water sorption isotherms for artichoke external leaves: (a) 25˚C; (b) 35˚C; (d) 45˚C; (e) 55˚C.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.2 0.4 0.6 0.81
Moisture, X (kg water/ kg ds)
W ater activity, a
w
desorption
adsorption
(a)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.2 0.4 0.6 0.81
Moisture, X (kg water/ kg ds)
Water act i vi t y, a
w
desorption
adsorption
(b)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.2 0.4 0.6 0.81
Moisture, X (kg water/ kg ds)
W ater activity , a
w
desorption
adsorption
(c)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.2 0.4 0.6 0.81
Moisture, X (kg water/ kg ds)
W ater activity, a
w
desorption
adsorption
(d)
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
67
served by other authors for pumpkin [29] and sweet po-
tato [34]. Since sorption properties are not temperature
dependent, external artichoke leaves can be stored in the
same atmosphere at any temperature within the studied
range. In addition, experimental data obtained at differ-
ent temperatures were used together for modeling pur-
poses.
3.3. Wa ter Sorption Isotherms Modeling
3.3.1. Correlation Models
Figure 2 shows water sorption (adsorption and de-
sorption) data at all the studied temperatures, as well as
the sorption isotherms obtained with the selected correla-
tion models. The fit of the models to experimental data is
adequate, although Halsey and Smith models show high-
er deviations at high water activities (0.8 - 0.9).
Table 2 shows the calculated parameters after fitting
and the goodness of fit of the models. Those with better
fits (lower E, median and ERMS values and higher R2) are
BET, GAB, Oswin and Peleg, all of them with similar
values for these parameters.
E values are relatively high, mainly due to the high
deviations at low moisture contents (X < 0.1). Medians
of the deviations and determination coefficients show
that the fits of the models are adequate, above all consi-
dering that fits have been performed with adsorption and
desorption data at different temperatures together (wide
application range of the models).
BET and GAB models can be selected for modeling
purposes because the physical meaning of their parame-
ters [29], as well as Oswin model because of its simplic-
ity. Specifically for the GAB model the “a” parameter is
0.075 kg water/kg ds, and corresponds to the monolayer
moisture content, an important value for the selection of
the storage conditions of the artichoke leaves.
3.3.2. Predictive Model Based on Food
Composition
The application of the predictive model (Figure 3) at
different temperatures corroborates the no significant
temperature effect on the sorption isotherms in the stu-
died temperature range, as observed experimentally.
It is also observed that the predictive model evaluated
at 40˚C (average temperature) gives acceptable results
regarding the shape of the water sorption isotherm. Nev-
ertheless, predicted equilibrium moisture content is sys-
tematically higher than experimental data. This result can
be explained based on the use of bibliographic composi-
tion data (protein, fat, salts and fiber) for whole artichoke
instead of data for artichoke leaves, since the last were
not available.
In spite of this, statistical data E = 47.9%, median of
deviations = 30.7%, ERMS = 0.060 and R2= 0.96 are
within the range given by the correlation models.
Figure 2. Experimental sorption data (dots) and sorption iso-
therms (lines) obtained with the selected correlation models.
Figure 3. Experimental sorption data (dots) and sorption iso-
therms (lines) obtained with the prediction model.
Table 2. Correlation models: calculated constants after model fitting and goodness of fit statistics.
Model Fitting constants Statistics
a b c d E (%) Median of dev. (%) R2 E
R
MS
BET 0.059 1.103 - - 21.52 14.74 0.97 0.026
GAB 0.075 0.995 0.947 - 20.96 10.75 0.98 0.025
Halsey 0.080 0.713 - - 33.62 26.13 0.93 0.057
Hendersopn 4.819 0.748 - - 21.87 13.63 0.96 0.035
Oswin 0.063 0.975 - - 21.50 14.14 0.97 0.026
Peleg 0.622 6.958 0.161 1.375 19.88 13.26 0.97 0.023
Smith 0.005 0.120 - - 27.66 20.13 0.88 0.066
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.20.40.60.81
Moisture, X (kg water/kg ds)
Water act ivit y, a
w
25 ºC35 ºC
45 ºC55 ºC
BET GAB
Halsey Henders on
Oswin Peleg
Smith
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
00.2 0.4 0.6 0.81
Moisture, X (kg water/kg ds)
W ater activity, a
w
Experimental dat a
Pre dictive model, 25 ºC
Pre dictive model, 35 ºC
Pre dictive model, 40 ºC
Pre dictive model, 45 ºC
Pre dictive model, 55 ºC
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
68
4. CONCLUSIONS
The shape of the sorption isotherms of artichoke leaves
was between types II and III (slight sigmoidal curve).
Within the studied temperature range, hysteresis phe-
nomenon was not observed, neither was the equilibrium
data dependence on temperature.
BET, GAB, Oswin and Peleg correlation models were
satisfactorily fitted to experimental data. The predictive
model based on composition and physical state of arti-
choke waste components was also successfully used to
reproduce experimental values. An advantage of this last
model is its independence of experimental water sorption
values to obtain predicted data and experimental time
saving.
5. ACKNOWLEDGEMENTS
Author Luis Mayor acknowledges JCI2009-04923 grant to MINECO
(Spain).
REFERENCES
[1] Arthey, D. and Dennis, C. (1992) Procesado de hortalizas.
Editorial Acribia, Zaragoza.
[2] Rodriguez Lopez, J.N. (2009) Aprovechamiento de Resi-
duos de alcachofa. http://hdl.handle.net/10201/6303
[3] Mata, J. (1998) Plantas de biometanización para la
fracción orgánica de los RSU: II Tecnologías. Residuos,
42, 72-75.
[4] Lázaro, L. and Arauzo, J. (1994) Aprovechamiento de
residuos de la industria de conservas vegetales. Hidrólisis
enzimática, 12, 227-240.
[5] Lattanzio, V., Kroon, P.A., Linsalata, V. and Cardinali, A.
(2009) Globe artichoke: A functional food and source of
nutraceutical ingredients. Journal of Functional Foods, 1,
131-144. http://dx.doi.org/10.1016/j.jff.2009.01.002
[6] Moreira, R., Chenlo, F. and Torres, M.D. (2009) Simpli-
fied algorithm for the prediction of water sorption iso-
therms of fruits, vegetables and legumes based upon che-
mical composition. Journal of Food Engineering, 94,
334-343.
http://dx.doi.org/10.1016/j.jfoodeng.2009.03.026
[7] Singh, R.P. and Heldman, D.R. (1993) Introduction to
food engineering. 2nd Edition, Academic Ress. Inc., San
Diego.
[8] Brunauer, S., Emmett, P.H. and Teller, E. (1938) Adsorp-
tion of gases in multimolecular layers. Journal of the
American Chemical Society, 60, 309-319.
http://dx.doi.org/10.1021/ja01269a023
[9] Van der Berg, C. and Bruin, S. (1981) Water activity and
its estimation in food systems. In: Rockland, L.B. and
Stewarts, G.F., Eds., Theorical Aspects in Water Activity:
Influence on Food Quality, Academic Press, New York,
12-45.
[10] Halsey, G. (1948) Physical adsorption on non-uniform
surfaces. Journal of Chemical Physics, 16, 931-937.
http://dx.doi.org/10.1063/1.1746689
[11] Henderson, S.M. (1952) A basic concept of equilibrium
moisture. Agricultural Engineering, 33, 29-32.
[12] Oswin, G.R. (1946) The kinetics of package life. Interna-
tional Chemical Industry, 65, 419-421.
http://dx.doi.org/10.1002/jctb.5000651216
[13] Peleg, M. (1993) Assessment of a semi-empirical four
parameter general model for sigmoid moisture sorption
isotherms. Journal of Food Process Engineering, 16, 21-
37. http://dx.doi.org/10.1111/j.1745-4530.1993.tb00160.x
[14] Smith, S. E. (1947) The sorption of water vapour by high
polymers. Journal of the American Chemical Society, 69,
646-651. http://dx.doi.org/10.1021/ja01195a053
[15] Ross, K. D. (1975) Estimation of water activity in inter-
mediate moisture foods. Food Technology, 3, 26-34.
[16] Roman, A.D., Herman-y-Lara, E., Salgado-Cervantes, M.
A. and García-Alvarado, M.A. (2004) Food sorption iso-
therms prediction using the Ross equation. Drying Tech-
nology, 22, 1829-1843.
http://dx.doi.org/10.1081/DRT-200032802
[17] Dubois, M., Gilles, K.A., Hamilton, J.K., Rebers, P.A.
and Smith, F. (1956) Colorimetric method for determina-
tion of sugars and related substances. Analytical Chemi-
stry, 28, 350-356. http://dx.doi.org/10.1021/ac60111a017
[18] Saengkanuk, A., Nuchadomrong, S., Jogloy, S., Patano-
thai, A. and Srijaranai, S. (2011) A simplified spectro-
photometric method for the determination of inulin in Je-
rusalem artichoke (Helianthus tuberosus L.) tubers. Eu-
ropean Food Research & Technology, 233, 609-616.
http://dx.doi.org/10.1007/s00217-011-1552-3
[19] McCleary, B.V., Murphy, A. and Mugford, D.C. (2000)
Measurement of total fructan in foods by enzymatic/
spectrophotometric method: Collaborative study. Journal
of AOAC International, 83, 356-364.
[20] United States Department of Agriculture (2013) National
nutrient database for standard reference.
http://ndb.nal.usda.gov
[21] Danish National Food Institution (2013) Danish food
composition databank. http://www.foodcomp.dk
[22] Spanish Agency of Food Safety and Nutrition (2013)
Spanish database of food composition.
http://www.bedca.net
[23] Wolf, W., Spiess, W.E.L. and Jung, G. (1985) Standardi-
zation of isotherm measurements (Cost project 90 and 90
bis). In Simatos, D. and Multon, J.L., Eds., Properties of
Water in Foods, Martinus Nijhoff, Dordrecht, 661-679.
http://dx.doi.org/10.1007/978-94-009-5103-7_40
[24] Norrish, R.S. (1966) An equation for the activity coeffi-
cients and equilibrium relative humidities of water in
confectionary syrups. Journal of Food Technology, 1, 25-
39. http://dx.doi.org/10.1111/j.1365-2621.1966.tb01027.x
[25] Pitzer, K.S. (1973) Electron repulsion integrals and sym-
metry adapted charge distributions. Journal of Chemical
Physics, 59, 3308-3312.
http://dx.doi.org/10.1063/1.1680474
[26] Salgado, M.A., Garcia, M.A. and Waliszewski, K.N. (1994)
Modeling of water activity and enthalpy of water sorption
L. Mayor et al. / Agricultural Sciences 4 (2013) 63-69
Copyright © 2013 SciRes. OPEN ACCESS
69
in cassava chips. Drying Technology, 12, 1743-1752.
http://dx.doi.org/10.1080/07373939408962197
[27] Makower, B. and Dye, W.B. (1956) Equilibrium moisture
content and crystallisation of amorphous sucrose and
glucose. Journal of Agriculture and Food Chemistry, 4,
72-77. http://dx.doi.org/10.1021/jf60059a010
[28] Sing, K.S.W., Everett, D.H., Haul, R.A.W., Moscou, L.,
Pierotti, R.A., Rouquerol, J. and Siemienievwska, T. (1985)
Reporting physisorption data for gas/solid systems. Pure
Applied Chemistry, 57, 603-619.
http://dx.doi.org/10.1351/pac198557040603
[29] Mayor, L., Moreira, R., Chenlo, F. and Sereno, A.M.
(2005) Water sorption isotherms of fresh and partially
osmotic dehydrated pumpkin parenchyma and seeds at
several temperatures. European Food Research and Te-
chnology, 220, 163-167.
http://dx.doi.org/10.1007/s00217-004-1065-4
[30] Chenlo, F., Moreira, R., Chaguri, L. and Santos, F. (2005)
Desorption isotherms of Padron peppers (Capsicum an-
nuum L. Var Longum). Ciencia y Tecnología Alimentari a,
5, 18-24.
[31] Vázquez, G., Chenlo, F., Moreira, R. and Costoyas, A.
(1999) The dehydration of garlic. 1. Desorption isotherms
and modelling of drying kinetics. Drying Technology, 17,
1095-1108.
http://dx.doi.org/10.1080/07373939908917596
[32] Rizvi, S. S. (2005) Thermodynamic properties of foods in
dehydration. In: Rao, M.A., Rizvi, S.S.H. and Datta A.K.
Eds., Engineering properties of foods, 3rd Edition, Taylor
& Francis, Boca Ratón, 259-346.
http://dx.doi.org/10.1201/9781420028805.ch7
[33] Lin, T.M., Durance, T.D. and Scaman, C.H. (1998) Cha-
racterization of vacuum microwave, air and freeze dried
carrot slices. Food Research International, 31, 111-117.
http://dx.doi.org/10.1016/S0963-9969(98)00070-2
[34] Chen, C. (2002) Sorption isotherms of sweet potato slices.
Biosystems Engineering, 83, 85-95.
http://dx.doi.org/10.1006/bioe.2002.0093