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Journal of Cereal Science 60 (2014) 584e588

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Journal of Cereal Science

journal homepage: www.elsevier .com/locate/ jcs

Hydration kinetics of soybeans: Transgenic and conventional cultivars

A.F. Fracasso a, C.A. Perussello a, *, C.W.I. Haminiuk b, L.M.M. Jorge c, R.M.M. Jorge a

a Graduate Program in Food Engineering, Department of Chemical Engineering, Federal University of Paran�a, Av. Francisco Hoffmann dos Santos, s.n., CEP81531-980, Curitiba, PR, Brazilb Graduate Program in Food Technology (PPGTA), Federal University of Technology e Paran�a, Via Rosalina Maria dos Santos, 1233, CEP 87301-899, CampoMour~ao, PR, Brazilc Technology Center, Department of Chemical Engineering, State University of Maring�a, Av. Colombo, 5790 e Bloco D90, Zona 787020-900, Maring�a, PR,Brazil

a r t i c l e i n f o

Article history:Received 16 December 2013Received in revised form23 July 2014Accepted 30 July 2014Available online 16 September 2014

Keywords:Soy cultivarsHydrationKineticsMass diffusion

* Corresponding author. Tel.: þ55 41 32663528.E-mail address: camila_ea@yahoo.com.br (C.A. Per

http://dx.doi.org/10.1016/j.jcs.2014.07.0110733-5210/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

Hydration processes of soybeans influence the physiological characteristics of the grain in order tofacilitate milling and extraction operations. Moreover, it can improve the soy digestibility and eliminateanti-nutritional factors. The knowledge about hydration kinetics is essential for the proper industrialequipment dimensioning. In the context of increasing production and use of genetically modified soy-beans, and the scarcity of physico-chemical and thermal studies regarding this product, the currentanalysis consists in studying the hydration process kinetics of conventional and transgenic varieties.Experimental tests were performed in five temperatures (25, 35, 45, 55 and 65 �C) using two cultivars oftransgenic soybeans (A7321 and CD231) and two conventional cultivars (CD206 and BRS232). Mathe-matical models presented in the literature (Peleg and concentrated parameters models) were fitted tothe experimental data. Both models adequately represented the hydration process. The process rateshowed a strong dependence on temperature, but no clear difference towards hydration rate or equi-librium moisture content was observed between conventional and transgenic cultivars.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Soy (Glycine max (L.) Merrill) is one of the most commonly graingrownworldwide. Soybeans arewidely used in the food industry asthey are rich in proteins, lipids and carbohydrates. The soybeanproduction is in continued and accelerated expansion. Brazil is thesecond largest producer, with an estimated production of 82.1million tons in 2012/2013, a volume that is 23.6 million tons higherthan the one produced in the 2011/2012 season (Embrapa, 2013).Transgenic soybeans are used in various food products around theworld as a result of interesting agricultural characteristics such asyield, cost of production and resistance to infestations (Dinon et al.,2010; Elsanhoty et al., 2013). In view of the increased planting ofgenetically modified soy, the knowledge about the properties ofconventional and transgenic cultivars is important. There areseveral types of transgenic soybeans currently being developed.The best known and commercially grown is a plant that received agene from another organism able to make it tolerant to the use of aherbicide commonly used for this culture, glyphosate. When

ussello).

inserted into the soybean genome, the plant becamemore resistantto the herbicide application and more productive (Embrapa, 2013).

The hydration process influences the physiological characteris-tics of cereals in order to facilitate milling and extraction of con-stituents of interest. Moreover, a cooking operation is often used inthe food industry to benefit other stages of the process, improvingthe digestibility and eliminating anti-nutritional factors of soy-beans (Coutinho et al., 2010; Maskan, 2002; Turhan et al., 2002).Due to the importance of grain hydration, the kinetic study iscrucial for the proper industrial equipment dimensioning. The ab-sorption of water by the soybeans during hydration dependsmainly on the binomial time-temperature. Models that representthe hydration process have been developed to predict the timerequired to obtain the desired moisture content at a given tem-perature. These models can be either empirical or phenomeno-logical (Coutinho et al., 2010). The empirical models are derivedfrom simple mathematical correlations of experimental data,therefore they are not based on physical laws or mass transfertheories (Gowen et al., 2007; Jideani andMpotokwana, 2009; Peleg,1988), while the phenomenological models mathematicallyrepresent the phenomenon of mass transfer by diffusion and/orconvection (Coutinho et al., 2010; Hsu, 1983). The latter can beclassified into concentrated or distributed parameters and usually

A.F. Fracasso et al. / Journal of Cereal Science 60 (2014) 584e588 585

represent the main trends of the process, even outside the range ofexperimental conditions in which they were validated, whichmakes their use very attractive .

Studies found in the literature regarding transgenic soybeansdeal with the detection of modified organisms in foods (Dinonet al., 2010; Elsanhoty et al., 2013; Kodama et al., 2009; Toyotaet al., 2006), the protein quality (Daleprane et al., 2009) and theimpact on consumer' health (Daleprane et al., 2009; Marrelli et al.,2013). However, there is no study with respect to the behavior oftransgenic soybeans during soaking. The aim of the current analysisis to evaluate the influence of temperature on the hydration processof conventional and transgenic soybeans by applying the models ofPeleg and concentrated parameters, and to evaluate the influenceof transgenesis on the water absorption.

2. Material and methods

2.1. Hydration tests

Samples of transgenic (A7321 and CD231) and conventional(CD206 and BRS232) soy cultivars were used in the hydration tests.The grains, harvested in 2009, were produced in Paran�a, Brazil, andwere donated by the Cooperative Coopagrícola Ponta Grossa. Theequipment used for hydration is a Dubnoff thermostatic bath withtemperature control (Q226M2 model, brand Quimis).

Samples of 200 g were placed in 400 mL beakers containing asolution of sodium benzoate in distilled water at a concentration of1 g/L. The beakers were placed in a thermostatic bath at constanttemperatures of 25, 35, 45, 55 and 65 �C. Sample portions ofapproximately 15 g were removed from the bath at the followingtimes: 0, 5, 10, 20, 30, 50, 70, 100, 120, 180, 270, 360 and 450 min.

After removal of the surface water, the grains were weighed andvolume and moisture content were analyzed. The volume wasdetermined by water displacement in a test tube according to themethodology described by Omoto et al. (2009). Moisture contentwas measured by oven drying at 105 �C for 24 h or until constantweight (AOAC, 1995) and was calculated by Equation (1):

Xbu ¼ 100�MUMS

(1)

where Xbu is the soybean moisture content w.b. [%] andMU [g] andMS [g] are the sample mass before and after drying, respectively.

The water mass concentration in the soybean (rA) was obtainedby Equation (2):

rA ¼ Xbs � rsoy (2)

where rA is the water mass concentration in the soybean [kg m�3],Xbs is the moisture content d.b. of the grain [kg kg�1] and rsoy is thesoybean density [kg m�3].

The hydration rate was calculated by:

W ¼ Xbsf � Xbs0Dt

(3)

whereW is the hydration rate [h�1], t is time [h] and Xbs0 [kg kg�1]and Xbsf [kg kg�1] are the moisture contents d.b. before and afterthe hydration process [kg kg�1], respectively.

2.2. Mathematical modeling

The moisture content of the soybeans in function of time waspredicted by the empirical model of Peleg (Peleg, 1988) and thephenomenological model proposed by Omoto et al. (2009).

The Peleg model is described by Equation (4):

XbsðtÞ ¼ Xbs0 þt

K þ K t(4)

1 2

where K1 and K2 are dimensionless constants and Xbs(t) [kg kg�1]and Xbs0 [kg kg�1] are the average moisture contents of soy d.b.in a process time t [s] and in the beginning of hydration,respectively.

The concentrated parameter model proposed by Omoto et al.(2009) was developed from a mass balance in transient state forthe water within the grain. Considering the average water contentinside the soybean, Equation (5) was obtained.

dðrAVÞdt

¼ �NAA (5)

where V is the soybean volume [m3], NA is the water mass flux[kg m�2 s�1] and A is the external area of the grain [m2].

Considering that the grain has a spherical geometry, with aradius ro, and constant volume, and that the mass flux can bedefined as NA ¼ KSðrAeq � rAÞ, one can obtain the concentratedparameter model, described by Equation (6):

dðrAÞdt

¼ �3KS�rAeq � rA

�T0

(6)

where KS is the apparent mass transfer coefficient [m s�1] and rAeqis the water mass concentration within the grain at equilibrium[kg m�3].

Integrating Equation (6), considering that rA and KS are constantfor a given hydration temperature, one can obtain Equation (7):

ln

rAeq � rA

rAeq � rA0

!¼ �3Ksxt

T0(7)

The parameters KS and rAeq can be obtained by fitting Equation(7) to the experimental data by linear regression.

3. Results and discussion

3.1. Hydration tests

During hydration, the variation ofmoisture content of transgenicand conventional soybeans in function of time was determinedexperimentally. Fig.1 shows the evolution ofmoisture on a dry basiswith time for three of the five temperatures studied. At all tem-peratures, the water absorption is higher in the initial stages ofhydration and decreases as the moisture content approaches satu-ration. In addition, the hydration curves showed an asymptoticbehavior, indicating the maximum moisture content attained, ac-cording to the findings of Hsu (1983) with respect to hydration ofbeans, whichmay be ascribed to the capillary transportmechanism.

The soybeans, with initial moisture of 0.14 ± 0.02 kg/kg, reachedequilibrium at an average moisture content of 1.47 ± 0.04 kg/kg,considering all cultivars and hydration temperatures. A significanttemperature effect (p < 0.05) on the hydration rate of all cultivarswas observed: the higher the temperature, the higher the processrate (Fig. 1). To render this figure clearer, only the results for thetemperatures of 25, 45 and 65 �C are presented. Several studieshave shown that increasing the temperature of the immersionmedium is an excellent way to accelerate the water absorption ofvarious seeds, shortening the immersion time (Abu-Ghannam andMcKenna, 1997; Hsu et al., 1983; Kon, 1979; Maskan, 2002; Quastand da Silva, 1977; Seyhan-Gürtas et al., 2001; Sopade andObekpa, 1990; Tang et al., 1994). According to Coutinho et al.(2010), the hydration rate of cereals at a given temperature isdirectly proportional to the difference between the concentration

Table 1Average values of hydration rate, initial moisture content and equilibrium moisturecontent of soybeans for all process temperatures.

Cultivar Equilibriummoisture content(kg kg�1)

Initial moisturecontent (kg kg�1)

Hydration rate (h�1)

CD 206 1.426 ± 0.215d 0.162 ± 0.066ª 0.169 ± 0.026c

BRS 232 1.512 ± 0.142a 0.138 ± 0.009c 0.183 ± 0.018ªCD 231 1.463 ± 0.111c 0.120 ± 0.005d 0.179 ± 0.015b

A 7321 1.487 ± 0.108b 0.143 ± 0.038b 0.179 ± 0.012b

aed Different characters within the same column indicate results that are statisticallydifferent (p < 0.05).

Table 2Parameters and determination coefficient (R2) of the Peleg model.

A7321(T) 25 �C 35 �C 45 �C 55 �C 65 �C Average

R2 0.998 0.996 0.998 0.992 0.995 0.996K1 102.500 69.714 41.185 16.996 18.469 49.773ªK2 0.658 0.596 0.648 0.716 0.675 0.659b

CD 231(T)

R2 0.998 0.999 0.993 0.998 0.993 0.996K1 80.121 57.711 42.955 30.885 20.473 46.429d

K2 0.694 0.640 0.666 0.584 0.645 0.646c

CD 206(C)

R2 0.995 0.996 0.996 0.998 0.995 0.996K1 88.588 59.795 45.568 30.393 22.046 49.278b

Fig. 1. Moisture content of soybeans in function of hydration time at different tem-peratures: (a) transgenic cultivars, and (b) conventional cultivars.

A.F. Fracasso et al. / Journal of Cereal Science 60 (2014) 584e588586

of water at equilibrium and at a certain instant of time. In fact, thisdifference is the driving force for the mass transfer.

Although there are no studies in the literature about a com-parison of hydration rates between conventional and transgenicsoybeans, some authors have reported differences in the lipid andprotein profiles (Luna et al., 2013; Moldes et al., 2012) as well as inthe germination capacity (Garcia et al., 2009). As demonstrated byTorres et al. (2003), transgenic grains are more resistant to theherbicide glyphosate. Non-transgenic seeds suffered a negativelinear effect on germination due to the increased concentration ofglyphosate in the growth medium. GM crops, in turn, were notaffected until a glyphosate concentration of 200 mm. Based on theseresults, we considered the hypothesis that the transgenesis could insome way influence the hydration capacity of the grains.

Table 1 shows that the equilibrium moisture content is slightlyhigher for the conventional soybeans, however the hydration ratesassumed aleatory values, i.e., the results are different for each cultivar,regardless of being transgenic or conventional. The same randombehavior is observed for the initial moisture content of the soybeans.

K2 0.681 0.627 0.635 0.750 0.678 0.684a

BRS 232(C)

R2 0.995 0.999 0.994 0.968 0.994 0.990K1 97.802 63.201 42.618 21.754 20.919 49.258c

K2 0.676 0.640 0.666 0.614 0.602 0.640c

aed and aec Different characters within the same column indicate results that arestatistically different (p < 0.05). *Note: (T) ¼ transgenic; (C) ¼ conventional.

3.2. Mathematical modeling

3.2.1. Peleg modelAccording to Turhan et al. (2002), the Peleg model is able to

predict the hydration kinetics of grains until equilibrium based on

data of moisture content within the range of experimental condi-tions investigated. This model has been used satisfactorily byseveral authors to represent hydration kinetics (Abu-Ghannam andMcKenna, 1997; Gowen et al., 2007; Jideani and Mpotokwana,2009; Maskan, 2002; Pan and Tangratanavalee, 2003; Schmidtet al., 2009; Sopade and Obekpa, 1990; Sopade et al., 1992;Turhan et al., 2002). In this model, K2 is inversely related to theequilibrium moisture content and K1 is inversely related to thewater absorption initial rate (Gowen et al., 2007; Maskan, 2002;Sopade and Obekpa, 1990).

The Peleg model parameters, K1 and K2, were adjusted throughthe linearization of Equation (4) in a time interval from 0 to450 min. The rates found for K1 and K2 for all temperatures andcultivars are presented in Table 2. The determination coefficients(R2) indicate that a proper fit between experimental and predicteddata was achieved.

From the results presented in Table 2, one can verify that K1 isinversely proportional to the hydration temperature, which meansthat the higher the process temperature, higher is the water ab-sorption rate. Various authors related similar results on other seedsand grains (Cunningham et al., 2007; Gowen et al., 2007; Maskan,2002; Sopade and Obekpa, 1990; Turhan et al., 2002). It was alsoobserved that the rates found for K1 are statistically differentdepending on the cultivar. The following order of K1 was found forthe different cultivars: CD231(T) < BRS232(C) < CD206(C) < A7321(T).The highest average value for K1 was 49.773, for the transgeniccultivar A7321, and the lowest was 46.429, for the transgeniccultivar CD231, which represents a difference of 7.20% on the initialwater absorption rate between these two cultivars. However, therewas no statistically significant difference regarding the graintransgenesis, i.e., K1 and K2 presented aleatory values, regardless ofwhether soybeans are transgenic or conventional, according to theresults presented in Section 3.1.

A.F. Fracasso et al. / Journal of Cereal Science 60 (2014) 584e588 587

The values found for K2, which is related to the maximum ca-pacity of water absorption, did not change significantly (p > 0.05)with temperature, i.e., the equilibrium moisture content did notvary in function of temperature. The smaller K2, the higher themaximum water absorption by the product. The maximum wateruptake depends on the cell wall structure, compactness of cellswithin the seeds or grains and composition of the product (Khazaeiand Mohammadi, 2009; Turhan et al., 2002). Although there werestatistically significant differences for K2 among cultivars, thesedifferences cannot be ascribed to the transgenesis. Abu-Ghannamand McKenna (1997) reported that K2 was constant at all temper-atures during hydration of red beans. Similar results were reportedfor Maskan (2002) on hydration of flour. According to Abu-Ghannam and McKenna (1997) the values of K2 determine theequilibrium moisture content, therefore a variation of this param-eter as a function of temperature is not expected.

The quadratic deviations of the moisture contents predicted bythe Peleg model in comparison to the experimental data were:0.01811, 0.01881, 0.01981 and 0.02214 for the cultivars A7321,CD231, CD206 and BRS232, respectively. Therefore, the globalaverage quadratic deviation, including all cultivars and tempera-tures, was 0.019718 ± 0.001759.

3.2.2. Concentrated parameter modelThe fitting of the concentrated parameter model to the experi-

mental data was performed by linear regression, and the parame-ters KS (m s1) and rAeq (kg m�3) were obtained for differenttemperatures and soybean cultivars (Table 3), however lowervalues of R2 were obtained in comparison to the Peleg model. Adependencewas found for the apparent mass transfer coefficient KS

in function of temperature, that is, the hydration rate increasedwith temperature, which agrees with data reported in literature.According to Coutinho et al. (2010), the mass transfer coefficientincreases with temperature and decreases with an increasingconcentration of water inside the bean. As reported by Omoto et al.(2009), in addition to the process temperature, the type of grain hasa significant influence on KS inasmuch as the diffusion coefficient isa characteristic of each material through which water diffuses.Different cultivars showed statistically different results for KS (m s1)and rAeq, however these differences could not be ascribed to thegrain transgenesis, since the results did not show a tendency toeither transgenic or conventional soy cultivars.

The quadratic deviations of the moisture contents predicted bythe concentrated parameter model in comparison to the

Table 3Parameters and determination coefficient (R2) of the concentrated parametersmodel.

A7321(T) 25 �C 35 �C 45 �C 55 �C 65 �C Average

R2 0.913 0.858 0.882 0.693 0.940 0.882Ks (m s�1) 0.00128 0.00234 0.00334 0.00432 0.00668 0.00334ªrAeq (kg m�3) 0.653 0.664 0.662 0.657 0.647 0.657b

CD 231(T)

R2 0.925 0.909 0.816 0.836 0.826 0.836Ks (m s�1) 0.00218 0.00259 0.00277 0.00470 0.00493 0.00277c

rAeq (kg m�3) 0.637 0.655 0.693 0.675 0.652 0.655b

CD 206(C)

R2 0.977 0.939 0.983 0.958 0.938 0.958Ks (m s�1) 0.00041 0.00050 0.00382 0.00096 0.00599 0.00096d

rAeq (kg m�3) 0.653 0.680 0.655 0.673 0.658 0.658b

BRS 232(C)

R2 0.719 0.917 0.866 0.890 0.716 0.866Ks (m s�1) 0.00218 0.00249 0.00260 0.00489 0.00545 0.00260b

rAeq (kg m�3) 0.659 0.651 0.669 0.673 0.676 0.669a

aed and aec Different characters within the same column indicate results that arestatistically different (p < 0.05). *Note: (T) ¼ transgenic; (C) ¼ conventional.

experimental data were 0.01406, 0.02072, 0.00229 and 0.00725 forthe cultivars A7321, CD231, CD206 and BRS232, respectively,resulting in an average value of 0.01108 ± 0.00804.

Fig. 2 shows the comparison between experimental data andthose predicted by the mathematical models. Both models repre-sented satisfactorily the phenomenon of hydration of soybeans,although higher values of R2 were obtained for the Peleg model.The higher deviations of the concentrated parameter model may beascribed to the assumptions made, such as spherical geometry andconstant volume of the soybean during the process. For illustrationpurposes, only the results for the temperatures of 25 and 65 �C arepresented.

Although the empirical model of Peleg consists of a mathe-matical fitting to the experimental data of moisture concentrationagainst hydration time, the coefficients K1 and K2 have a physicalmeaning and reveal important aspects of the process. K1 isinversely related to the initial rate of water absorption and K2 isinversely related to the equilibrium moisture content. It wasobserved that the temperature had an influence on the parameterK1, i.e., the hydration rate increases with temperature. On the otherhand, the parameter K2 did not vary significantly depending onprocess temperature, that is, the final moisture of the grain is sta-tistically the same in all conditions tested. In addition, K1 and K2

Fig. 2. Experimental and predicted moisture content versus time during hydration ofsoybeans of the cultivar: (a) A7321, (b) CD 231, (c) CD 206 and (d) BRS 232.

A.F. Fracasso et al. / Journal of Cereal Science 60 (2014) 584e588588

were not dependent on the type of cultivar, indicating that thehydration rate and equilibrium moisture content are nearly thesame for both conventional and transgenic grains.

Regarding the theoretical model of concentrated parameters,the coefficients Ks and E also correspond to the process physics. Theapparent mass transfer coefficient, Ks, increased with temperaturedue to the diffusive characteristic of the hydration process. Theanalysis of the hydration kinetics by this model confirmed thestrong dependence of Ks in relation to temperature, as expected.Therefore, the use of higher hydration temperatures, with theappropriate precautions with regard to possible thermal damage(browning, protein denaturation, alteration of taste, among others),can be an interesting alternative to reduce process time.

4. Conclusions

Themain purpose of this researchwas to evaluate the differencein the hydration behavior of transgenic and conventional soybeans.The mathematical models of Peleg and concentrated parameterswere both able to represent the major trends of the process,revealing that temperature influenced only the hydration rate.Comparing conventional and transgenic cultivars, however, nosignificant difference was observed for the hydration rate and theequilibrium moisture content, which suggest that the trangenesiswould not affect operations subsequent to hydration, such asmilling and extraction.

Acknowledgments

The authors would like to thank Coopagrícola, from PontaGrossa (Brazil), for donating the soybeans.

References

Abu-Ghannam, N., McKenna, B., 1997. Hydration kinetics of red kidney beans.J. Food Sci. 62 (3), 520e523.

AOAC Association of Official Analytical Chemists, 1995. Official Methods of Analysisof AOAC 16 ed. Arlington 2.

Coutinho, M.R., Omoto, E.S., Conceiç~ao, W.A.S., Andrade, C.M.G., Jorge, L.M.M., 2010.Evaluation of two mathematical models applied to soybean hydration. Int. J.Food Eng. 6 (6) article 7.

Cunningham, S.E., McMinn, W.A.M., Magee, T.R.A., Richardson, P.S., 2007. Modelingwater absorption of pasta during soaking. J. Food Eng. 82, 600e607.

Daleprane, J.B., Feij�o, T.S., Boaventura, G.T., 2009. Organic and genetically modifiedsoybean diets: consequences in growth and in hematological indicators of agedrats. Plant Foods Hum. Nutr. 64 (1), 1e5.

Dinon, A.Z., Treml, D., Mello, C.S., de, Arisi, A.C.M., 2010. Monitoring of GMO inBrazilian processed meat and soy-based products from 2007 to 2008. J. FoodCompos. Anal. 23 (3), 226e229.

Elsanhoty, R.M., Al-Turki, A.I., Ramadan, M.F., 2013. Prevalence of geneticallymodified rice, maize and soy in Saudi-food products. Appl. Biochem. Biotechnol.171 (4), 883e899.

Embrapa e Brazilian Company of Agricultural Research. Available in: <http://www.cnpso.embrapa.br>. (accessed 17.03.13.) (in portuguese).

Garcia, M.C., Garcia, B., Garcia-Ruiz, C., G�omez, A., Cifuentes, A., Marina, M.L., 2009.Rapid characterisation of (glyphosate tolerant) transgenic and non-transgenicsoybeans using chromatographic protein profiles. Food Chem. 113 (4),1212e1217.

Gowen, A., Abu-Ghannam, N., Frias, J., Oliveira, J., 2007. Influence of preblanching onthe water absorption kinetics of soybeans. J. Food Eng. 78, 965e971.

Hsu, K.H., 1983. A diffusion model with a concentration-dependent diffusion co-efficient for describing water movement in legumes during soaking. J. Food Sci.48, 618e622.

Jideani, V.A., Mpotokwana, S.M., 2009. Modeling of water absorption of Botswanabambara varieties using Peleg's equation. J. Food Eng. 92, 182e188.

Khazaei, J., Mohammadi, N., 2009. Effect of temperature on hydration kinetics ofsesame seeds (Sesamum indicum L.). J. Food Eng. 91, 542e552.

Kodama, T., Kuribara, H., Minegishi, Y., Futo, S., Watai, M., Sawada, C., Watanabe, T.,Akiyama, H., Maitani, T., Teshima, R., Furui, S., Hino, A., Kitta, K., 2009. Evalu-ation of modified PCR quantitation of genetically modified maize and soybeanusing reference molecules: Interlaboratory study. J. AOAC Int. 92 (1), 223e233.

Kon, S., 1979. Effect of soaking temperature on cooking and nutritional quality ofbeans. J. Food Sci. 44, 1329e1335.

Luna, A.S., Silva, A.P., da, Pinho, J.S.A., Ferr�e, J., Boqu�e, R., 2013. Rapid characteriza-tion of transgenic and non-transgenic soybean oils by chemometric methodsusing NIR spectroscopy. Spectrochim. Acta A Mol. Biomol. Spectrosc. 100 (1),115e119.

Marrelli, M., Tudisco, R., Mastellone, V., Conforti, F.A., 2013. Comparative study ofphytochemical composition of genetically and non-genetically modified soy-bean (Glycine max L.) and evaluation of antitumor activity. Nat. Prod. Res. 27 (6),574e578.

Maskan, M., 2002. Effect of processing on hydration kinetics of three wheat prod-ucts of the same variety. J. Food Eng. 52, 337e341.

Moldes, C.A., Cami~naa, J.M., Medici, L.O., Tsai, S.M., Azevedo, R.A., 2012. Physiolog-ical effects of glyphosate over amino acid profile in conventional and transgenicsoybean (Glycine max). Pesticide Biochem. Physiol. 102, 134e141.

Omoto, E.S., Andrade, C.M.G., Jorge, R.M.M., Coutinho, M.R., Paraíso, P.R.,Jorge, L.M.M., 2009. Mathematical modeling and analysis of hydration of peagrains. Ciencia Tecnol. Aliment. 29, 12e18 (in portuguese).

Pan, Z., Tangratanavalee, W., 2003. Characteristics of soybean as affected by soakingconditions. Lebensm. Wiss. Und Technologie LWT 36, 143e151.

Peleg, M., 1988. An empirical model for the description of moisture sorption curves.J. Food Sci. 53 (4), 1216e1219.

Quast, D.G., E Da Silva, S.D., 1977. Temperature dependence of hydration rate andeffect of hydration on the cooking rate of dry legumes. J. Food Sci. 42,1299e1303.

Schmidt, F.C., Carciofi, B.A.M., Laurindo, J.B., 2009. Application of diffusive andempirical models to hydration, dehydration and salt gain during osmotictreatment of chicken breast cuts. J. Food Eng. 91, 553e559.

Seyhan-Gurtas, F., Ak, M.M., Evranuz, E.O., 2001. Water diffusion coefficients ofselected legumes grown in turkey as affected by temperature and variety.Turkish J. Agric. For. 25, 297e304.

Sopade, P.A., Obekpa, J.A., 1990. Modelling water absorption in soybean, cowpea andpeanuts at three temperatures using Peleg's equation. J. Food Sci. 55 (4),1085e1087.

Sopade, P.A., Ajisegiri, E.S., Badau, M.H., 1992. The use of Peleg's equation to modelwater absorption in some cereal grains during soaking. J. Food Eng. 15,269e283.

Tang, J., Sokhansanj, S., Sosulski, F.W., 1994. Moisture-absorption characteristics ofLaird lentils and hard shell seeds. Cereal Chem. 71, 423e428.

Toyota, A., Akiyama, H., Sugimura, M., Watanabe, T., Kikuchi, H., Kanamori, H.,Hino, A., Esaka, M., Maitani, T., 2006. Quantification of genetically modifiedsoybeans using a combination of a capillary-type real-time PCR system and aplasmid reference standard. Biosci. Biotechnol. Biochem. 70 (4), 821e827.

Torres, A.C., Nascimento, W.M., Paiva, S.A.V., Arag~ao, F.A.S., 2003. Bioassay fordetection of transgenic soybean seeds tolerant to glyphosate. Pesqui. Agro-pecu�aria Bras. 38 (9), 1053e1057.

Turhan, M., Sayar, S., Gunasekaran, S., 2002. Application of Peleg model to studywater absorption in chickpea during soaking. J. Food Eng. 53, 153e159.