Revista Mexicana de ngeniería uímica · un encogimiento severo. Para la muestras sin tratamiento...

Revista Mexicana de Ingeniería Química

CONTENIDO

Volumen 8, número 3, 2009 / Volume 8, number 3, 2009

213 Derivation and application of the Stefan-Maxwell equations

(Desarrollo y aplicación de las ecuaciones de Stefan-Maxwell)

Stephen Whitaker

Biotecnología / Biotechnology

245 Modelado de la biodegradación en biorreactores de lodos de hidrocarburos totales del petróleo

intemperizados en suelos y sedimentos

(Biodegradation modeling of sludge bioreactors of total petroleum hydrocarbons weathering in soil

and sediments)

S.A. Medina-Moreno, S. Huerta-Ochoa, C.A. Lucho-Constantino, L. Aguilera-Vázquez, A. Jiménez-

González y M. Gutiérrez-Rojas

259 Crecimiento, sobrevivencia y adaptación de Bifidobacterium infantis a condiciones ácidas

(Growth, survival and adaptation of Bifidobacterium infantis to acidic conditions)

L. Mayorga-Reyes, P. Bustamante-Camilo, A. Gutiérrez-Nava, E. Barranco-Florido y A. Azaola-

Espinosa

265 Statistical approach to optimization of ethanol fermentation by Saccharomyces cerevisiae in the

presence of Valfor® zeolite NaA

(Optimización estadística de la fermentación etanólica de Saccharomyces cerevisiae en presencia de

zeolita Valfor® zeolite NaA)

G. Inei-Shizukawa, H. A. Velasco-Bedrán, G. F. Gutiérrez-López and H. Hernández-Sánchez

Ingeniería de procesos / Process engineering

271 Localización de una planta industrial: Revisión crítica y adecuación de los criterios empleados en

esta decisión

(Plant site selection: Critical review and adequation criteria used in this decision)

J.R. Medina, R.L. Romero y G.A. Pérez

Vol. 13, No. 3 (2014) 865-885

EFFECT OF THE FLUIDIZED BED DRYING ON THE STRUCTURE ANDBIOSORPTION CAPABILITY OF Pb+2 OF AGAVE EPIDERMIS

EFECTO DEL SECADO POR LECHO FLUIDIZADO EN LA ESTRUCTURA YCAPACIDAD DE BIOSORCION DE Pb+2 DE EPIDERMIS DE AGAVEM.T. Hernandez-Botello1, J.J. Chanona-Perez1∗, J.A. Mendoza-Perez2, M. Trejo-Valdez3, G.

Calderon-Domınguez1, J.L. Barriada Pereira4, M.E. Sastre de Vicente4, M.J. Perea-Flores5, E. Terres-Rojas6

1Departamento de Ingenierıa Bioquımica, 2 Departamento de Ingenierıa en Sistemas Ambientales ENCB,3ESIQIE, IPN, Mexico, D.F.

4Departamento de Quımica Fısica e Enxenerıa Quımica I, Universidade da Coruna, Coruna, Spain.5Centro de Nanociencias y Micro y Nanotecnologıas, IPN, Mexico, D.F.

6Laboratorio de Microscopia Electronica de Ultra Alta Resolucion, IMP, Mexico D.F.

Received May 29, 2014; Accepted June 23, 2014

AbstractA fluidized bed drying study of agave epidermis obtained from wastes of the “pulque” manufacture was made. Dryingkinetics modeling and the influence of the operation conditions on the shrinkage, microstructure and biosorption capabilityof Pb+2 were studied. Drying kinetics was carried out at 50, 60, 70 and 80 °C. Six semi-empirical models were testedand diffusion approach model provided the best fits. Effective diffusivity varied from 3.73×10−9 to 6.99×10−9 m2s−1, foruntreated slabs (UT) and from 3.65×10−9 to 7.74×10−9 m2s−1 for treated samples (T) with hydrochloric acid. Activationenergy was found to be 21.22 and 23.89 kJ/mol for UT and T samples respectively. Shrinkage and the microstructurechanges of T slabs were larger than UT samples. T samples dried at 70 and 80 °C showed a reduction in their Pb+2

biosorption capability, caused by a large shrinkage and severe microstructural changes. For UT samples their biosorptioncapability was increased in relation with increase of the shrinkage and drying temperature. T samples dried at 50 and 60°C improved their biosorption capability of Pb+2, while UT samples dried at 70 and 80 °C showed a better biosorptioncapability. These results can be useful for preparation of biosorbents.

Keywords: Agave epidermis, fluidized bed drying, shrinkage, microstructure, biosorption.

ResumenSe realizo un estudio de secado en lecho fluidizado de epidermis de agave obtenida de desechos de la fabricacion del“pulque”. Se efectuo el modelado de las cineticas de secado y se estudio la influencia de las condiciones de operacionsobre el encogimiento, microestructura y capacidad de biosorcion de Pb+2. Las cineticas fueron hechas a 50, 60, 70 y 80°C. Seis modelos semi-empıricos fueron probados y el de aproximacion a la difusion proporciono los mejores ajustes. Ladifusividad efectiva cambio desde 3.73×10−9 a 6.99×10−9 m2s−1 para las placas sin tratar, y desde 3.65×10−9 a 7.74×10−9

m2s−1 para las muestras tratadas con acido clorhıdrico. La energıa de activacion fue de 21.22 kJ/mol para las muestras sintratar y 23.89 kJ/mol para las muestras tratadas. El encogimiento y los cambios microestructurales fueron mas drasticosen las placas tratadas en comparacion con las rebanadas sin tratamiento acido. El material tratado y secados a 70 y 80°C, mostro una reduccion en su capacidad de biosorcion de Pb+2, que fue causado por los cambios microestructurales yun encogimiento severo. Para la muestras sin tratamiento su capacidad de biosorcion se incremento con el encogimientoy la temperatura de secado. Las muestras tratadas y secadas a 50 y 60 °C, mejoraron su capacidad de biosorcion. Estosresultados pueden ser utiles para la preparacion de biosorbentes.

Palabras clave: epidermis de agave, secado por lecho fluidizado, encogimiento, microestructura, biosorcion.

∗Corresponding author. E-mail: jorge [email protected]

Publicado por la Academia Mexicana de Investigacion y Docencia en Ingenierıa Quımica A.C. 865

Hernandez-Botello et al./ Revista Mexicana de Ingenierıa Quımica Vol. 13, No. 3 (2014) 865-885

Fig.1. Parts of agave plant. a) Agave plant (Agave atrovirens Karw) , b) Cross section of agave leave: Epidermis(Ep), cuticle (Cu), parenchyma tissue (Pa) and c) Microphotograph of Agave epidermis tissue obtained byenvironmental scanning electron microscopy, shows epidermis cells (Ec).

1 Introduction

The exploitation of the most important speciesof agave in Mexico (Agave tequilana Weber, A.americana and A. atrovirens Karw) generates anextensive quantity of agroindustrial wastes derivedmainly from production of “tequila”, “mezcal” and“pulque”. It is estimated that about 350 000 tonsper year of agroindustrial residues are generatedin the mezcal industry in Mexico. Agave wastescause complications for its final disposal due to itshigh humidity level (>80 % d.b.) causing a slowdecomposition and a great waste volume. Leavesand agave pulp (Figure 1a and 1b) are the remainingbiomass in the extraction of polysaccharides andsyrups; which are used in the production of alcoholicdrinks. The bagasse is mainly constituted byparenchymal, vascular tissue and epidermis of theplant. Bagasse is commonly used for the productionof traditional products such as textile weaving, paperpulps, glues, food for cattle and other craft usesand recently is considered as a potential source oflingocellulosic material for the manufacture of low-cost composites (Bessadok et al., 2009). About 54%of the agave total weight corresponds to the head thatis mainly used to produce tequila and other liquors.The leaves represent 32% and have been used for theproduction of sugar and fibers; whereas the remaining14% includes the epidermis and the cuticle (Figure

1b), that do not have any important use (Iniguez etal., 2001). The epidermis is the outermost layerof plant cells (Figure 1b); this layer is in directcontact with the environment and it is responsible ofimportant functions such as gases change, water vapor,water storage, photosynthesis, support and mechanicalprotection. The agave epidermis contains cellulose,hemicellulose, lignin, silica, oils, salts in crystallineform, resins and a cuticle with waxes monostratifiedand stomata on both sides of the leaf. Epidermal tissueis constituted by cortical parenchyma cells (Figure1c), abundant chloroplasts and mucilage cells withhigh content of polysaccharides that confer to theepidermis a large water absorption capability. Theepidermis cell wall has an anionic character due to thepresence of polar functional groups such as carboxyl,hydroxyl, phosphate and sulfide, which contributeto the formation of ionic interchange sites. Somereports had considered the potential of agave wastesas biosorbent to purify polluted effluents with heavymetals, polar compounds and dyes (Romero et al.,2005; Velazquez et al., 2013). For this reason,it is necessary to find an alternative use for thisagroindustrial waste. Often, biosorbents obtainedfrom agroindustrial waste are chemically activated byimmersion in acid solutions (HCl or HNO3) with thepurpose of increasing its biosorption capability. Afterthe chemical activation, they are dried in order toremove the water excess to facilitate its handling and

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storage (Qi and Aldrich 2008; Mata et al., 2009;Schiewer and Balaria, 2009; Feng et al., 2011).

Other important issue for preparation ofbiosorbents is the drying, this is one of the oldesttechniques used for the preservation of agriculturalproducts since this technology prevents microbialdeterioration and offers lighter weight and smallervolume for the transportation and storage. Drying ofbiomaterials involves physical and chemical changeswhich dramatically affect the products itself and itsfinal properties, as well as its functionality suchas adsorption capability of water and chemicalcompounds (Senadeera et al., 2003). Among thedrying technologies, the fluidized bed drying is widelyused to dry powders, grains and small pieces ofvegetable tissues due to its higher heat and masstransfer coefficients. Additionally, fluidized beddrying provides a more homogenous product thanconventional or solar drying (Doymaz, 2005; Demiret al., 2007; Arabhosseini et al., 2009; Akmel et al.,2009; Perea et al., 2012).

The drying kinetics studies are essential toevaluate drying rates and effective moisture diffusivity(Vagenas and Karathanos, 1993; Perea et al., 2012).These can be reproduced by using models (transfercoefficients and drying constants) that are directlyrelated to the drying conditions and describe thephenomenon in a simplified way. Such models arecommonly used in order to estimate drying times ofthe materials and also to generalize drying curves(Doymaz, 2005; Demir et al., 2007; Arabhosseini etal., 2009; Akmel et al., 2009). In order to studythe drying effect on the biomaterials, it is necessarya deep knowledge of the mass transfer parametersand drying kinetics modelling which are consideredimportant for the design, the selection of optimaldrying conditions, quality control of the biomaterials,simulation and optimization of the drying process(Guine and Fernandez, 2006). The mathematicalmodels have proved to be very useful in the newdesign and/or improvement of drying systems, andfor the analysis of mass transfer phenomena involvedduring drying. Thus, it is necessary to find accuratemodels, capable of predicting the water removalrates and describing the drying performance of eachbiomaterial under the common conditions used inthe industrial processes (Perea et al., 2012; Doymaz,2005). Nevertheless, there are few studies relatedwith the drying of agro-industrial wastes and themodeling of its drying kinetics, such as the epidermisof A. atrovirens (Doymaz, 2005; Demir et al., 2007;Arabhosseini et al., 2009; Akmel et al., 2009; Perea

et al., 2012). Considering this background and whichthere are not enough data available in the literatureabout the drying of agave epidermis and its effect onthe biosorption of heavy metals, the leading objectivesof this work can be summarized as follows:

To characterize the drying of agave epidermisuntreated (UT) and treated (T) with hydrochloric acidsolution through drying parameters such as effectivemoisture diffusivity coefficients, activation energy aswell as the mathematical modeling of drying kinetics.To study the relationships between drying conditions,shrinkage, microstructure and biosorption capabilityof Pb+2.

2 Material and methods

2.1 Sample preparation

Agave epidermis was obtained from waste of agaveleaves (A. atrovirens) remnant of handcraft elaborationof a local beverage (“pulque”). Agave leaves werecollected from 5-7 years old plants from a plantationestablished in Mexico City. Agave leaves were washedwith distilled water and the cuticle was removedmanually. Epidermis slabs of approximately 0.6 ×0.6 × 0.4 cm were obtained by manual cutting. Twotypes of samples were used, untreated slabs (UT)were soaked in distilled water and other slabs weretreated (T) with 0.1 M hydrochloric acid (1:250w/v) toprotonated the surface of the samples. This treatmentis usually applied in biological samples for active itssurface and improve the biosorption of heavy metals(Qi and Adrich, 2008; Schiewer and Balaria, 2009).Both samples were stirred in glass flasks at 250 rpmduring 30 min at 25 ºC. The samples were extensivelywashed with milli-Q water (Millipore Direct-Q 3,USA) until the pH of the suspension reached 5.0.Then, UT and T samples were pressed against a filterpaper in order to remove the remaining water (Bhainsaand D‘Souza, 2008). Initial moisture content of thesamples (UT and T) was determined according to theAssociation of Official Analytical Chemists (AOAC)32.1.03 method. All measurements were performed intriplicate. This moisture content was used as the initialmoisture content in the drying kinetics.

2.2 Drying experiments

Drying experiments were carried out in a fluidizedbed dryer at laboratory scale (ArmfieldFT31, UK).The drying column (section test) was made of anacrylic cylinder (9.6 cm internal diameter, 35 cm

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height). Epidermis slabs were dried at different airtemperatures (50 ºC, 60 ºC, 70 ºC and 80 ºC) andair flow was kept constant (2.3±0.2 m s−1) for alldrying condition. Pressure drop measurements for thefluidized bed were obtained using U-tube manometerfilled with distillate water. Under this regime ofair flow a good fluidization was obtained and thebed material showed a perfect mixing. The pressuredrop in the packing bed material showed almost nofluctuations as the air flow was increased, whichwas a measurement for smooth fluidization withoutslug formation, which is an adequate fluidizationaccording to reported by Gazor and Mohsenimanesh(2010). A thermoanemometer (TSI Inc, 8330-M,USA, accuracy of ±0.1 m/s) was used for monitoringthe dry bulb temperature and air velocity. Wetbulb temperature was measured by means of type-K-thermocouple wrapped in a distillate water wet cottoncloth and connected to a digital thermometer (DakotaInstruments Inc, 1604, USA, accuracy of ±0.1 °C).Changes in the absolute humidity of air at the inlet ofthe column were determined from the psychometricchart using wet and dry bulb temperatures. Theabsolute humidity of the drying air oscillated from0.001 to 0.003 kg water/kg air dry at all studiedtemperatures. In the present work the influence ofair temperature was the only parameter studied asit is considered in several reports as the key factoraffecting drying kinetics. Furthermore, the selectedtemperature range (50-80 °C) used in this researchis typical for the study of biological materials dryingprocess (Sturm et al., 2014; Gumeta et al., 2011;Gazor and Mohsenimanesh et al., 2010; Doymaz,2005). Each drying run was carried out to a specifiedmass of agave epidermis slabs (42 ± 0.5 g) measuredwith a digital balance (Adam equipment, PGW 4502i,USA, accuracy±0.01 g) and L/D ratio of 0.5, whereL is the bed height (4.8±0.3 cm) and D is the beddiameter, as recommended by Santiago-Pineda et al.,(2007). The height of the static bed was measuredusing a Vernier caliper (Mitutoyo, Kawasaki 39652-20, Japan). During drying experiments, the weightloss of the slabs was measured with the digital balanceaforementioned, every 2 min until no further changesin their mass were observed (constant weight), takingless than 10 s to weigh the sample. Drying kineticswere calculated based on the initial and final mass,moisture content, weight loss, final moisture and thedried solid content of slabs, plotting the moisture ratio(MR, see equation 1) in function of drying time. The

equilibrium moisture content of slabs was obtained byusing the dynamic method described by Kashaninejadet al., (2007). The drying experiments were replicatedthree times and drying kinetics was reported as theaverage of the three replicates. An analysis ofvariance (ANOVA) and a Tukey test were applied inorder to statistically compare the results between thedrying kinetics replicates of both untreated and treatedsamples. The ANOVA also was used to compare theeffect of drying temperature on the shrinkage and ionremoval in both kind samples (UT and T); significantdifferences were considered when p ≤ 0.05.For theseanalysis Sigma Plot software version 12.0 (SYSTATInc., USA) was used.

2.3 Mathematical modeling of the dryingkinetics

To study the drying kinetics of agave epidermisslabs, it is important to select an accurately modelfor describe acceptably its drying behavior. Thus,in this work the experimental drying kinetics datafor each of experiment were fitted to six of themost frequently semi-theoretical models, which wereselected from recent researches focused in the dryingof similar agricultural products (Shen et al., 2011;Promvonge et al., 2011; Doymaz, 2005). The modelsselected were: exponential or Lewis, Hendersonand Pabis, Page, two-term exponential, logarithmicand diffusion approach or approximation of thediffusion. The mathematical expressions and relevantinformation about these models are shown in Table1. In these models, the dimensionless moisture ratio(MR) of agave epidermis slabs during fluidized beddrying experiments was calculated from the followingequation:

MR =Mt −Me

Mo −Me(1)

where Mo is the initial moisture content, Me is theequilibrium moisture content, and Mt is the moisturecontent at time t (Wang et al., 2007; Iguaz et al., 2003).

The drying rate (DR) expressed as g (water) g−1

(dry solids) min−1 is defined as:

DR =M1 −M2

t2 − t1(2)

where t1 and t2 are the drying times in minutes atdifferent times during fluidized bed drying; M1 and M2are the moisture contents (d.b.) of agave slabs at timet1 and t2, respectively.

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Table 1. Mathematical models selected to modelling of agave slabs drying kinetics

Models Model equation Model Relevant information Referencesconstants

Exponential orLewis

MR =Mt−MeMo−Me

=

exp(−kt)k This model assumes

negligible internalresistance, whichmeans that there isnot resistance in themoisture displacementbetween the interior ofmaterial towards thematerial surface

Doymaz, (2005);Kashaninejad et al.,(2007); Perea et al.(2012).

Henderson andPabis

MR =Mt−MeMo−Me

=

aexp(−kt)a,k This model controls the

liquid process diffusionand take place only inthe falling rate period

Doymaz, (2005); Vega-Galvez et al., (2010);Perea et al., (2012).

Page MR =Mt−MeMo−Me

=

exp(−ktn)k,n This model suggests the

used of two empiricalconstants, it has beenshown to produce goodfits to describe dryingof many agricultureproducts.

Iguaz et al., (2003);Rafiee et al., (2009);Perea et al., (2012).

Two termexponential

MR =Mt−MeMo−Me

=

a1 exp(−k1t) +

a2 exp(−k2t)

a1, a2, k1, k2 This model assumes thatdiffusivity is constantand solution appliesregardless of particlegeometry and boundaryconditions.

Iguaz et al., (2003);Rafiee et al., (2009);Vega-Galvez et al.,(2010); Shen et al.,(2011).

Logarithmic MR =Mt−MeMo−Me

=

aexp(−kt) + ca, k, c This model has been

successful used tofit drying kinetics atdifferent operationconditions.

Demir et al., (2007);Sacilik, (2007);Sirisomboon andKitchaiya, (2009);Vega-Galvez et al(2010).

Diffusionapproach orapproximation ofthe diffusion

MR =Mt−MeMo−Me

=

aexp(−kt) + (1 −

a)exp(−kbt)

a, k, b This model tends tounderestimated in thelatter stage while themodel tends to have agood fit in the initialstages for several dryingconditions.

Akgun and Doymaz,(2005); Rafiee et al.,(2009); Perea et al.,(2012).

∗t is the time for all equations

2.4 Statistical evaluation of themathematical models

The statistical validity of models was evaluatedand compared by means of different statisticalindicators and the non-linear regression analysis ofdrying kinetics was done using SigmaPlot software

version 12.0 (SYSTAT Inc. USA). The drying rateconstants and coefficients of all models were estimatedusing non-linear least squares regression analysis,performed using Marguardt-Levenberg algorithm. Inorder to select the best model to describe dryingbehavior accurately, the coefficient of determinationR2, was used as the main+41 00 selection criteria,

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but also the goodness of the fit was determinedadditionally using others statistical parameters suchas reduced chi-square (χ2), mean relative percentdeviation (EMD) and root mean square error (ERMS )values. For quality fit, R2 value should be higherand χ2, EMD and ERMS values should be lower(Promvonge et al., 2011;Doymaz, 2011; Vega et al.,2010; Wang et al., 2007; Kashaninejad et al., 2007).The parameters were calculated using the followingexpressions:

R2 =

N∑i=1

MR,pre,i − MR,ex,i

(MR,ex,i − MR,ex,i)2 (3)

EMD =100N

N∑i=1

|MR,ex,i −MR,pre,i|

MR,ex,i(4)

ERMS =

1N

N∑i=1

(MR,ex,i −MR,pre,i

)21/2

(5)

χ2 =

∑Ni=1

(MR,ex,i −MR,pre,i

)2

N − z(6)

where: MR,exp,I and MR,pre,I are experimental andpredicted dimensionless moisture ratios, respectively;N is the number of observations; and z is the numberof constants. EMD (%) indicates the deviation betweenthe experimental data and predicted data.

2.5 Estimation the effective moisturediffusivity (De f f ) and activation energy(Ea)

The effective moisture diffusivity of agave epidermisslabs was studied using the mathematical Fick’ssecond diffusion model. The solution to this equation,developed by Crank (1975), could be used for variousregularly shaped bodies such as slabs, cylindrical andspherical products. In this work the usage of theform of Eq. (7) could be applicable for samples withslab geometry by assuming uniform initial moisturedistribution (Shen et al., 2011; Crank, 1975).

MR =8π2

∞∑n=0

1(2n + 1)2 −

(2n + 1)2π2De f f t

4L2

(7)

where MR is the moisture ratio, De f f is the effectivediffusivity (m2s−1) and L is the half thickness ofslab (m) and t is the time (s). Slab thicknesswas calculated using an image analysis methodologysimilar to reported by Perea et al., (2011) and it isdescribe in detail in the following section. For long

drying time, Eq. (7) could be further simplified toretain only the first term and the logarithmic formis showed in the Eq. (8). The effective moisturediffusivity could be typically determined by plottingexperimental drying data in tERMS of ln(MR) versusdrying time (Doymaz, 2011; Shen et al., 2011; Wanget al., 2007) and De f f was calculated from slope of theplot.

ln MR = ln8π2 −

π2De f f t

4b2

(8)

The De f f can be related to temperature of fluidizedbed drying by Arrhenius equation (Promvonge et al.,2011; Wang et al., 2007; Iguaz et al., 2003) as show inthe Eq. (9)

De f f = Do exp(−

Ea

RT

)(9)

where Do is the pre-exponential factor equivalent tothe diffusivity at infinitely high temperature (m2s−1),Ea is the activation energy (kJmol−1), R is theuniversal gas constant (8.314 J mol−1K−1), and T isthe absolute temperature (K). Both kinetic parameters(Ea and Do) could be determined by plotting ln(De f f )versus T−1 after linearization for Eq. (9) (Shen et al.,2011;Vega et al., 2010).

2.6 Shrinkage of agave slabs

Top and lateral views of samples were consideredto evaluate the shrinkage of agave slabs. For thetop view, the acquisition of images was carried outwith a color digital camera (CCD) model power shotSX110 IS (Canon, NY, USA) with nine megapixelsand positioned vertically over the sample at a distanceof 15.5 cm from the floor of the computer visionsystem to the lens as previously reported (Arzate etal., 2012). The images were taken using the followingcamera settings: manual mode with lens aperture atf = 2.8 and speed 1/15 s, no zoom and no flash.A matte white background was used to improve thecontrasts during the capture of this view. Due tosmall thickness of agave slabs and to avoid shadows,the lateral view images were obtained by using astereomicroscope (Nikon SMZ 1500, Japan) and thesamples were positioned laterally by using white play-dough to set up a vertical position and improve thecontrast. The image capture procedure was similarto that reported by Perea et al. (2012). All imageswere captured as RGB and stored in BMP format toa size of 1600×1200 pixels. A reference bar in mmwas positioned very close to the slabs in both capturedscenes, thus the resolution of images was estimate in0.0082 mm/px.

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Fig. 2. Binary image gallery of agave epidermisslabs, top view and lateral view, as function of dryingtemperature, untreated and treated samples.

For both views around 600 images of agave slabswere used to evaluate the shrinkage by using projectedarea and thickness of slabs. Image processingincluded: cropping, conversion of the color image togrey-scale values, application of a threshold tool atgrey level in a limited range from 0 to 85-110 unitsin the intensity histogram of pixels and backgroundsubtraction to obtaining the binary image from thegrey-scale images. Subsequently, projected area andthickness of the images were obtained as number ofpixels within the boundary (Figure 2). According withMcLaughlin, and Magee, (1998) the shrinkage couldbe evaluated, assuming that this process is isotropic,and that the sample geometry corresponds to arectangular parallelepiped. Under these assumptions,the slabs volume was estimate from project area oftop view multiplied by the average slabs thickness oflateral view. The thickness was measured in differentzones of the lateral views and at least 3 measurementswere taken, one at the center and two at the slabtips. The shrinkage was expressed as a percentage ofchange or relative to the original geometry of the slabs.Thus, the relative shrinkage was estimated by using thefollowing expression (Sansiribhan et al., 2012):

Shrinkage(%) =Vi −V f

Vi× 100 (10)

where Vi is the initial volume obtained from imagesof fresh slabs and V f is the final volume. Theimage analysis was selected as a methodology forevaluation of the shrinkage, because it has been usedas successful method to estimate the shrinkage inthe drying of biological materials (Fernandez et al.,2005; Gumeta et al., 2011).Around 300 images wereused in the measurements for each view at initial andfinal drying time. ImageJ software v.1.48i (NationalInstitutes of Health, Bethesda, MD, USA) was used inall steps of image analysis methodology.

2.7 Environmental scanning electronmicroscopy (ESEM)

To examine the microstructural changes caused bythe drying process on the agave epidermis surface,the samples (fresh, dry, untreated and treated) weremounted on aluminum stubs with double-sided carbonadhesive tape and directly observed under a XL-30 Environmental Scanning Electron Microscope(Philips, USA) at 25 kV accelerating voltage. ESEMwas coupled to a GSE (gaseous secondary electrondetector).

2.8 Biosorption capability of Pb+2

Biosorption experiments were carried out with freshand dry UT and T agave slabs samples. In allcases, 0.7 g of material were mixed (175 rpm)at room temperature (25°C) with 20 mL of 100ppm Pb+2 solution (pH 5, adjusted with dilutedHNO3 and NaOH) for 30 min. Pb+2 concentrationwas selected due to at this level, the precipitationof Pb+2at the pH used was avoided, besides, thisconcentration conditions was in the suitable rangeused in the biosorption experiments reported byother authors (Qi and Aldrich, 2008; Schiewer andBalaria, 2009; Mata et al., 2009). After mixing, thesamples were filtered (Whatman 40 filter paper), andthe Pb+2 concentration of the filtrate was analyzedusing the Polarographic (Metrohm polarographicanalyzer, model 707, Switzerland) coupled to apersonal computer. A typical three electrode systemequipped with a dropping mercury working electrode,a platinum counter electrode and Ag/AgCl/3 M KClas a reference electrode. Nitrogen was used as aninert gas to purge the analyze solution and to operatethe mercury electrode. The optimum nitrogen gaspressure of 0.5 kg cm−2 was used throughout in thisstudy (Comte, et al., 2008, 2006; Mohammadi etal., 2004). Relative biosorption capability of agave

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slabs was expressed as ion removal (%) according toreported by Lopez-Garcia et al., (2012) and it wasobtained by means of following equation:

ion removal(%) =ci − c f

ci× 100 (11)

where ci is the initial concentration in the solution andc f is the final concentration in the solution, estimatedfrom a calibration curve of Pb+2 concentration (C)in ppm against current intensity (CI) in amperes(CI=0.224C+2.737, R2=0.99, range of 0-200 ppm ofPb+2). All experiments were replicated at least threetimes.

3 Results and discussion

3.1 Drying curves analysis

Initial moisture content of untreated (UT) and treated(T) agave slabs was in both cases of 86.6 ±0.5% (d.b.).The changes in MR as function of drying time of agaveslabs at different air drying temperatures (50-80ºC)are presented in Figures 3a and 3b. The drying timerequired to reduce the moisture from initial moisture

for UT agave slabs to final moisture content was 34,28, 18 and 14 min at air drying temperatures of 50, 60,70 and 80ºC, respectively. The final moisture contentsreached for each time were 2.97 ±0.19, 1.16±0.24,1.75±0.22 and 2.47± 0.19% d.b. respectively. In thecase of T agave slabs, the drying time was 34, 28, 20and 16 min at air drying temperatures of 50, 60, 70and 80ºC, respectively. The final moisture contents(equilibrium moisture) reached for each time was 2.97±0.19, 2.85±0.19, 2.79 ±0.19 and 2.61±0.18% d.b.respectively. As expected the moisture ratio wasreduced exponentially with drying time in both kindsof samples; this behavior is typical for the drying ofsome biological materials (Doymaz, 2005; Calzettaet al., 2004; Shen et al., 2011; Wang et al., 2007).The drying kinetics behavior suggests that the dryingprocess occurs mainly during the falling rate period,and as consequence the drying rate is controlledby internal diffusion phenomenon, thereby moleculardiffusion migration of the moisture contained in thesamples could be the predominant mechanism fordrying, as has been reported for several agriculturalproducts (Doymaz, 2011; Gazor and Mohsenimanesh,2010; Gumeta et al., 2011; Kashaminejad et al., 2007;Vega et al., 2010; Zielinska and Markowski, 2007).

Fig. 3. Experimental and predicted moisture ratio (MR) by diffusion approach model in function drying time atdifferent drying temperatures for agave slabs, a) untreated and b) treated. Experimental drying rate (DR) curves atdifferent drying temperatures for agave slabs, c) untreated and d) treated.

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The statistical analysis (ANOVA) of the dryingkinetics revealed that there is no significant difference(p < 0.05) among untreated and treated slabs, whenthe drying is carried out at the same temperature.Nevertheless, for both kind of samples the moistureratio was increased with the increment of the dryingair temperature and showed significant differences(p < 0.05) between the different drying temperaturesapplied. This effect is in agreement with other reportsof drying for different vegetable tissues (Abalone etal., 2006; Arabhosseini et al., 2009; Barrozo et al.,2006; Chua et al., 2000; Doymaz, 2005; Kerdpiboonet al., 2007; Ruiz et al., 2008; Sacilik et al., 2006;Shivhare et al., 2000).

Additionally to the drying kinetic analysis, theamount of water removed from samples as functionof time was represented as drying rate (DR). Thesecurves, at the different tested drying temperatures (50,60, 70 and 80ºC), are shown in Figure3c and 3dfor UT and T agave slabs, respectively. The DRdecreases continuously with drying time, and thisbehavior confirm that the drying process occurredmainly during the falling rate period. Also, whenthe air temperature was increased, the DR parameterincreased too. Similar results related to behaviorof DR curves have also been reported in severaldrying studies of biological materials (Doymaz, 2005;Calzetta et al., 2004; Shen et al., 2011; Wang et al.,2007).

3.2 Mathematical modeling of the dryingkinetics

In the Tables 2 and 3, the details of the statisticalanalysis results for the six models applied to dryingkinetics of UT and T agave slabs are shown.The values of R2, EMD, ERMS and χ2 changedbetween 0.9997-0.9964, 0.189-1.053, 0.0016-0.0280and 0.000082-0.00148 respectively. R2 values greaterthan 0.99 were found for the six models tested. Itwas observed that the diffusion approach and thelogarithmic model showed higher R2 values than theothers models tested (Table 2 and 3), presenting theformer a better performance (R2) to fit curves thanthe logarithmic model. In contrast, the Lewis andHenderson and the Pabis models showed a minorfit to experimental drying data in comparison withlogarithmic and diffusion approach models. Eventhough Lewis model is easier to implement thanthe others, because it uses only one fitting constant,the results indicated that Lewis and Henderson andPabis models yielded lower values of R2 and higher

EMD (%) than diffusion approach and logarithmicmodels. These results could be due to that Lewismodel is a special case of the Henderson and Pabismodel, but both models tended to overestimate in theearly stages and underestimate in the later stages ofthe drying (Akgun and Doymaz, 2005). However,for all mathematical models EMD (%) values werelower than 10%, and this level of bias is acceptedas adequate. These results indicated that all modelshad low deviation in relation to experimental dataand it is not surprising that the diffusion approachmodel showed the lowest values of EMD (%) in almostall cases, except for agave slabs untreated at 70 and80 °C, where the logarithmic model presented thelowest EMD (%) values (Table 2). The analysis ofERMS showed that the diffusion approach model give asuperior fit to experimental data (Table 2 and 3). Also,diffusion approach model provided lower χ2 values incomparison with the others models; when χ2 valuesapproach to zero, the closest is the prediction (Robertset al., 2008; Gazor and Mohsenimanesh, 2010), whichindicated good predictions to drying kinetics of UTand T agave slabs. Similar results have been reportedfor several agricultural products such as medicinalplants (Gundelia tournefortii, Evin, 2012), aromaticplants (tarragon, Artemisa dracunculus, Arabhosseiniet al., 2009), apple (Wang et al., 2007), greenbeans (Doymaz, 2005) and coconut (Niamnuy andDevahastin, 2005).

In Figures 3a and 3b the experimental MR datafitted to the diffusion approach model is shown. It canbe observed from this figure that there is a suitablefit between experimental and predicted MR data.Based on this statistical information, it is possible toselect the diffusion approach model as the best fordescribing the behavior of fluidized bed drying of UTand T agave slabs. Diffusion approach model hasalso been reported by other authors as an adequatemodel to fit drying kinetics of several food materialssuch as okra (Doymaz, 2011), canola seeds (Gazorand Mohsenimanesh, 2010), rough rice (Cihan et al.,2007) and plum (Sacilik et al., 2006).

Additionally to the selection of an accurate modelto describe the agave samples drying kinetics, adirect link between k coefficients and the air dryingtemperatures was established, observing a similartendency to that showed in MR and DR curves; thiscan be noticed in Tables 2 and 3. The values of k canbe related to the effective moisture diffusivity whenthe drying process is controlled by internal diffusionphenomena. Thereby, k values can be associatedwith the facility of moisture to be removed from thematerial.

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Table 2.Statistical results obtained from the six selected drying models and estimate parameters for slabsagave slabs untreated

Temperature (°C) Models Model constants R2 EMD (%) ERMS χ2

50 Henderson a:1.0147, k:0.1565 0.9976 0.3180 0.0135 0.00020and PabisLewis k:0.1544 0.9974 0.3290 0.0010 0.00021Page k:0.1286, n:1.0862 0.9989 0.2150 0.0093 0.00009Two term a1:0.5115, k1:0.1565, 0.9976 0.3180 0.0135 0.00023exponential a2:0.5032,k2:0.1565Logarithmic a:1.0255, k:0.1473, 0.9990 0.2020 0.0086 0.00008

c:-0.0193Diffusion a:-121.8259, k:0.2182, 0.9991 0.1890 0.0082 0.00008approach b:0.9968

60 Henderson a:1.0201, k:0.1867 0.9955 0.5620 0.0199 0.00045and PabisLewis k:0.1834 0.9951 0.5704 0.0207 0.00046Page k:0.1401, n:1.1380 0.9983 0.3040 0.0121 0.00017Two term a1:0.5176, k1:0.1867, 0.9955 0.5620 0.0199 0.00054exponential a2:0.5024, k2:0.1867Logarithmic a:1.0366, k:0.1727, 0.9978 0.3920 0.0138 0.00024


70 Henderson a:1.0215, k:0.2252 0.9934 0.9071 0.0261 0.00085and PabisLewis k:0.2211 0.9929 0.9004 0.0272 0.00082Page k:0.1621, n:1.1766 0.9980 0.4800 0.0146 0.00026Two term a1:0.5205, k1:0.2252, 0.9070 0.0261 0.00114exponential a2:0.5011, k2:0.2252 0.9934Logarithmic a:1.0614, k:0.1948, 0.9983 0.4430 0.0133 0.00025




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Table 3. Statistical results obtained from the six selected drying models and estimate parameters for agaveslabs treated

Temperature (°C) Models Model constants R2 EMD (%) ERMS χ2




c:-0.0.0238Diffusion a:-135.3750, k:0.2736, 0.9989 0.2598 0.0099 0.00010approach b:0.9967





The model selected (Diffusion approach) proved tobe adequate to describe the drying behavior of agaveslabs. Thus, the knowledge of drying kinetics and theirmodeling could be important to design, simulate and

optimize drying process and the information obtainedfrom drying models can be apply to estimate optimumdrying conditions.

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3.3 Effective moisture diffusivity (De f f ) andactivation energy (Ea)

As the results showed that the drying of UT andT agave slabs occurs in the falling rate period andthe moisture transfer during drying is controlled byinternal diffusion, the experimental required data forthe determination of diffusivity coefficients can bedetermined by means of the Fick’s diffusion equation.The linear regressions of ln (MR) against dryingtime are presented in Figure 4a and 4b. The slopederived from linear regression allows obtaining thevalues of the effective moisture diffusivity (De f f ).Generally, the De f f is used as a consequence ofscarce information on the mechanism of moisturetransfer during drying and complexity of the process(Kashaninejad et al., 2007). The average values ofeffective moisture diffusivity (De f f ) at different dryingtemperature for UT and T agave slabs can be observedin Table 4, where the De f f varied from 3.73×10−9

m2s−1to 6.99×10−9, for the case of UT agave slabsand from 3.65×10−9 m2s−1to 7.74×10−9for T agaveslabs. As expected, the values of De f f increasedwith increasing temperature and were in the suitablegeneral range of 10−9 to 10−8 m2s−1for drying ofthe biological materials; this effect has been reportedfor heterogeneous systems, included vegetable tissues(Chen et al., 2012; Shen et al., 2011; Ruiz et al.,2008; Sacilik et al., 2007; Doymaz, 2005; Doulia etal., 2000). It can be seen, that the drying at 50, 60 and70 °C for UT agave slabs promoted a slightly increaseon the values of the effective diffusivity coefficientsin comparison with T samples. Frequently, for thedrying of biological materials, it has been reportedthat the pretreatment by dipping with several chemicalcompounds such as alkali solutions, oils, fatty acidethyl esters, organic acids, inorganic salts, combinedwith thermal treatment as the blanching, can increasethe effective moisture diffusivity reducing the dryingtime by relaxing tissue structure, removal of filmwax or polymeric compounds on the vegetal tissue(Walde et al., 2006; Doymaz, 2006, 2010; Tarhan,2007; Vasquez-Parra et al., 2013). However, thepretreatment with hydrochloric acid did not increasethe values of effective moisture diffusivity, when thesamples were dried at 50, 60 and 70 °C, probably dueto that acid treatment could promote a decrease on thepermeability of agave tissue structure. A proposal toexplain this effect is that under acid conditions andwithout blanching, a partial solubilization of somestructural components, as the cellulose, hemicelluloseand lignin, could have occurred during the chemical

Fig. 4. a) Experimental logarithmic moisture ratio(MR) in function drying time at different dryingtemperatures for agave slabs untreated and b) treated.c) Arrhenius-type relationship between the logarithmof effective moisture diffusivity (De f f ) and the inverseof absolute temperature for agave slabs untreated andtreated.

pretreatment (Kohlerand Spatz, 2002; Bessadok etal., 2009). Subsequently, when the drying proceeds,the temperature and internal stresses in the sampleare increased, at the same time, the fast drying leads

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Table 4. Drying parameters values of agave slabs untreated and treated at different dryingconditions.

Treatment Temperature De f f (m2/s) Do (m2/s) Ea (kJ/mol)

Agave slabs untreated 50°C 3.73×10−9 (R2=0.99) 1.03×10−5 21.2260°C 4.76×10−9 (R2=0.99)70°C 6.72×10−9 (R2=0.95)80°C 6.99×10−9 (R2=0.95)

Agave slabs treated 50°C 3.65×10−9 (R2=0.98) 2.64×10−5 23.8960°C 4.67×10−9 (R2=0.98)70°C 6.09×10−9 (R2=0.99)80°C 7.74×10−9 (R2=0.96)

to a mechanical stabilization of the surface, and athin crust or shell in the external surface of slabscan be formed, promoting a diminishing on the waterdiffusion rate (Sturm et al., 2014; Mayor and Sereno,2004). In contrast, for the drying at 80 °C thewater diffusion rate was increased for T samples incomparison with UT slabs. This could be due to a highdrying temperature avoiding the formation of crust orits disruption by an effect of melting or plasticizationof the compounds structural and polymeric of agavetissue. Consequently, the water transport can befacilitated under high drying temperature, maybedue to the drying temperature is close to boilingtemperature of water and in consequence the waterdiffusion that could be carried out in vapor phase.

Additionally, the effective moisture diffusivitycan be associated with drying temperature by usingArrhenius-type relationship to obtain the activationenergy (Ea). The Ea is the energy barrier that mustbe overcome in order to activate moisture diffusionand the diffusivity constant equivalent (Do) to thediffusivity at infinitely high temperature (Arabhosseiniet al., 2009; Wang et al., 2007). Thus, the logarithmof De f f as a function of the reciprocal of the absolutetemperature (Figure 4c) for UT and T agave slabsresults in a linear relationship with a R2 of 0.94 and0.99 respectively. The diffusivity constant (Do) andactivation energy (Ea), values are shown in Table 4.From the slope of the curve, the values of activationenergy obtained were: 21.22 and 23.89 kJ/mol for UTand T agave slabs respectively. The Ea values foundfor agave slabs were in reasonable agreement with thedata reported by several authors for different biologicalmaterials (Gazor and Mohsenimanesh, 2010; Vega etal., 2010; Guıne and Fernandez, 2006; Senadeera etal., 2003). High values of the activation energy are

associated with materials where the water is boundmore strongly or samples having a dense structure.Thereby, for treated agave slabs the activation energywas slightly larger than untreated agave slabs, maybedue to the formation of the crust caused by acidtreatment when the slabs are dried at 50, 60 and70 °C. The equations 11 and 12 show the effect oftemperature on the De f f of untreated and treated agaveslabs respectively, as they are useful for the design andscale of equipment in the temperature range studied.

De f f =1.03× 10−5 exp(−

2553.27T

)(12)

De f f =2.64× 10−5 exp(−

2873.81T

)(13)

3.4 Microstructure and shrinkage

The microstructure of agave slabs observed underESEM is shown in the Figure 5. Fresh tissue ofUT samples displayed intact cells with a regularand isodiametric shape, with typical structure ofparenchymatic tissue and also an opaque aspect;cell walls with thick borders, turgid cells andfilled with intracellular material could be perceived.However, the acid treatment caused changes in themicrostructure of agave tissue and although the cellsof treated fresh samples conserved its regular andisodiametric shape, the cellular walls showed thinborders, tissue with a translucent aspect and cellsempty without intracellular material. In the caseof the dried samples, the T agave slabs showed amore structural damage than UT samples, mainly inthe T samples at 70°C, where it can be observed ahigh loss of cellular shape, severe structural damagewith great number of cells melted and breached.

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Fig. 5. Environmental scanning electron microscopymicrographs of agave epidermis slabs, fresh anddrying at different temperatures, untreated and treatedsamples.

In this way, microstructural changes caused bypretreatment promoted a large collapsing anddeformation of the cells on the slabs surface thatprobably can explain the low rate of drying observedin the T samples dried at 50-70 °C. When drying at 80°C, the collapsing, damaging and crumpling of cellswere more noticeable for T samples in comparisonwith UT samples, although some isodiametric shapeof cells can be still observed; maybe due to that at thistemperature the drying was fast and water diffusioncould take place in vapor phase. Additionally, asdrying at 80 °C for T samples was carried out at higher

rate, a less cellular damage could observed in contrastwith T samples drying at 70 °C, in this temperaturecellular damage was the more drastic in comparisonwith the others drying conditions. The dryingtemperature effect on the microstructure of biologicalmaterials has been previously documented and the ourresults are in agreement with those reported for SEMimages of apple slices, carrot cubes, Aloe vera gelslabs and agave slabs, dried at a temperature rangeof 40-80 °C (Vega-Galvez et al., 2012; Sansiribhanet al., 2012; Gumeta et al., 2011; Miranda et al.,2010).The effect of pretreatments by dipping in boilingwater, vacuum impregnation, freezing/thawing, anduni-axial compression on the apple microstructure hasbeen reported to damage the tissue structure, yieldinglarger cell cavities and caused higher drying rates anddiffusivity coefficients (Ramırez et al., 2011). While,Maldonado et al., (2010) has reported a great cellulardamage, absence of middle lamella and plasmolysis inmango osmodehydrated and pretreated with sucroseand glucose. However, there are not reports aboutthe effect of pretreatment with hydrochloric acid andconvective drying on the microstructure of Agaveepidermis.

In overall, the relative shrinkage was higher forUT samples than for T samples and in both casesthe percentage of shrinkage increased in relation todrying temperature (Figure 5a). Multiple comparisontest showed that the shrinkage (%) of UT samplesat 50 °C had significant difference in relation withthe other drying temperatures, while the samples at60 °C and 80 °C, also showed statistical differencebetween them. In the case of T samples dried at50 °C and 60 °C, the shrinkage (%) had significantdifferences with the samples at 70 and 80 °C. While,in the comparison the shrinkage between the UTand T samples, only the samples dried at 60 °Cand 80 °C have statistical different. As it has beenaforementioned, the acid treatment could promote adecrease on the permeability of agave surface bymeans of a partial solubilization of the structuralcomponents such as cellulose, hemicellulose andlignin (Kohler and Spatz, 2002; Bessadok et al., 2009),forming a small crust in the surface of T samples, andhigher damage in cellular structure as was observedunder ESEM. This could explain the less shrinkageobserved in the agave samples treated with acid.In relation to the dependence of the shrinkage withdrying temperature, the effect the drying temperatureon the shrinkage is mainly due to higher dryingrate when the temperature is increased. This effecthas been reported for biological materials such as

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apples, carrots and potatoes (Vega-Galvez et al., 2012;Sansiribhan et al., 2012; Sturm et al., 2014; Mayorand Sereno, 2004).

3.5 Biosorption capability of Pb+2

In this work, the combine effect of an acidpretreatment and fluidized bed drying temperatureson the biosorption capability of Pb+2 of agaveepidermis slabs was studied. Frequently, the biologicalsamples used in biosorption experiments are initiallypreconditioned by means of acid treatment by dippingthe materials into HCl or HNO3, and then dryingover a wide range of temperature conditions (40-110 °C ) (Mata et al., 2009; Qi and Aldrich, 2008;Schiewer and Balaria 2009; Njikam and Schiewer,2012). These drying temperatures are typically usedin the standard methods for the determinations of themoisture contain and preparation biosorbent materials.However, the combined effect of the acid pretreatmentand the drying temperature have been scarcely studied.For instance, the effectiveness of biosorbents dependson a large extent on their biochemical composition,particularly their functional groups, where carboxylgroups play an important role in metal biosorptionof several biomaterials, such as pectin, cellulose,hemicellulose and lignin, besides the ability of some ofthem, to bind divalent cations (Schiewer and Balaria,2009); Nevertheless, these components could belixiviated or modified by the acid treatments or dryingprocess. Moreover, during drying, the biomaterialmicrostructure is drastically affected. This promoteschanges in their superficial area and permeability,which have been related to heavy metal biosorptioncapability. One non exploited waste biomaterial,that could be used in biosorption of heavy metals,due to its structural components is agave. Figure 5bshows that the Pb+2 biosorption capability of fresh UTsamples was higher than fresh T samples (p < 0.05).Similar behavior was observed between the samplesUT and T dried at 80 °C. While for UT and T samplesdried at 70 °C there was not significant differences.This behavior could be due to two phenomena, inthe case fresh samples the acid treatment couldhave lixiviated some structural components and thismodified the content of the carboxyl groups involvedin the biosorption. In the case of dry samples,the high drying temperatures applied (80 °C) couldpromote changes in the superficial area, microstructureand shrinkage, that caused a reduction on thebiosorption capability of Pb+2 on the biomaterial.These modifications on the sample surface could

Fig. 6. a) Effect of treatment conditions on the% shrinkage, b) effect treatment conditions on the% ion removal (Pb+2) and c) relationship between% shrinkage and % ion removal. UT: Untreatedsamples and T: Treated samples. Same letters in theeach plot indicate significant difference (p ≤ 0.05). ’indicate comparison between T samples. ” Indicatecomparison between UT and T samples at sametemperature or treatment.

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be due to reactions between the functional groupsof biopolymeric compounds associated with thebiosorption, that could be catalyzed by the protonationof biomaterial and a partial hydrolysis of somestructural components of the agave tissue, and thiscould have blocked some active carboxyl groupsuseful for the biosorption.

When only the effect of drying temperature onthe biosorption capability of Pb+2 was compared,significant variations between UT and T samples driedat different temperatures (Figure 5b) were found.Differences (p < 0.05) between UT samples, fresh anddried at 50 °C and 60 °C in comparison with the drymaterial at 70 °C and 80 °C were observed. In the caseof T samples, the behavior was similar, and significantdifferences were detected for fresh and dry materials at50 °C in comparison with the dry samples at 60 °C, 70°C and 80 °C, and 60 °C and 70 °C respectively. ForUT and T samples, the increase of temperature and ahigher drying rate caused an slight improvement onthe biosorption capability of Pb+2; this can be linkedto an increase in the superficial area, a higher damageon the microstructure and a large shrinkage in thebiomaterial.

Finally, the relationship between the biosorptioncapability of Pb+2 and the shrinkage is shown inthe Figure 6c, where for UT samples there is aclear tendency to increase the heavy metal biosorptioncapability with relation to increase of shrinkage degreeand drying temperature. While, for T samples thebiosorption capability did not show a clear tendencyto increasing with relation the shrinkage. At lowtemperatures (50 °C and 60 °C) biosorption capabilitywas greater than UT dry samples processed at the sametemperatures, but at high temperatures (70 °C and 80°C) the biosorption decrease in comparison with UTsamples. As has been explained above this reductionof the biosorption capability can be associated tothe lixiviation of biopolymers and the blocked offunctional groups available for the biosorption. Thus,the UT samples drying at 70 °C and 80 °C werethe better conditions for the biosorption of Pb+2,suggesting that the acid pretreatment for activation ofthe biomaterial surface could not be favorable, whenthe shrinkage is drastic.

ConclusionsOn the basis of obtained results it can be concludedthat:

1. Drying air temperature had significant effect on

the moisture ratio of the samples, internal waterdiffusion controlled the fluidized bed drying ofUT and T agave and Diffusion approach modelshowed the best fitting for drying kinetics.

2. The effective diffusivity varied from 3.73×10−9

to 6.99×10−9 m2s−1, for UT agave slabs andfrom 3.65×10−9 to 7.74×10−9 m2s−1 for Tagave slabs. The activation energy was found tobe 21.22 and 23.89 kJ/mol for UT and T samplesrespectively.

3. ESEM studies indicated that the acidpretreatment modified the microstructure ofagave tissue. As a result, the T agave slabsshowed a more microstructural damage than theUT samples, mainly for the T samples dried at70°C, where the largest cellular damage and agreat number of melted and ruptured cells wereobserved. Shrinkage was higher for the UTsamples than the T samples, and in both casesthe shrinkage (%) was increased in relation todrying temperature. Acid pretreatment causedsolubilization and lixiviation of some structuralcomponents on the slabs surface that promotedthe formation of a crust that could explainthe lower shrinkage and great microstructuraldamage observed.

4. Treated and dried samples at 70 and 80 °Cshowed a reduction in their Pb+2 biosorptioncapability caused by a large shrinkage andsevere microstructural changes, that couldhave blocked the carboxyl groups associatedwith the biosorption phenomenon. Whilefor UT samples their biosorption capabilitywas increased in relation with the increase ofthe shrinkage and drying temperature. As arecommendation for biosorbents preparation,the treated and dried samples at lowtemperatures (50 and 60 °C) can improve theirbiosorption capability, while for UT samples theapplication of higher drying temperatures (70and 80 °C) improve the biosorption capability.

5. The results found in this work could beuseful to design, simulate, and scale dryingequipment and also to provide criteria for theselection of pretreatment conditions and dryingfor preparation of biosorbents for Pb+2 fromagave wastes.

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AcknowledgmentsMayuric Teresa Hernandez Botello wishes to thankCONACyT for the scholarship provided for her studiesand international stay. This research was fundedthrough projects 20110627 and 20121001, 20120789,20130333 and 20140387 at the Instituto PolitecnicoNacional (SIP-IPN Mexico) and133102 of CONACyT

Nomenclaturea fit coefficient, -a1 fit coefficient, -a2 fit coefficient, -B fit coefficient, -C model constant, -C concentration, ppmCI current intensity, ampersCi initial concentration of Pb+2, ppmC f final concentration of Pb+2, ppmCu cuticled.b. dry basisDe f f effective diffusivity, m2s−1

Do pre-exponential factor m2s−1

DR drying rate, g (water) g−1(dry solids)min−1

Ea energy activation, kJmol−1

Ec epidermis cellsEMD relative percent deviation, -Ep epidermis of agaveERMS root mean square error, -ESEM environmental scanning electron

microscopyGSE gaseous detector of secondary

electronsk model constant (s−1)k1 model constant (s−1)k2 model constant (s−1)L half of thickness of slab, mM1 moisture content at time t1, g (water)

g−1(dry solids)M2 moisture content at time t2, g (water)

g−1(dry solids)Me equilibrium moisture content, g

(water) g−1(dry solids)Mo initial moisture content, g (water)

g−1(dry solids)MR moisture ratioMR,exp,I experimental dimensionless moisture

ratioMR,pre,I predicted dimensionless moisture

ratio

Mt moisture content at time t, g (water)g−1(dry solids)

N model constant -N number of observationsPa parenchyma tissueR universal gas constant, 8.314 J

mol−1K−1

R2 coefficient of determinationT treated agave epidermist time, sT absolute temperature, Kt1 drying time at time 1, mint2 drying time at time 2, minUT untreated agave epidermisVi initial volume, m3

V f final volume, m3

z number of constants

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Revista Mexicana de ngeniería uímica · un encogimiento severo. Para la muestras sin tratamiento...

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