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Moisture sorption characteristics and dynamic mechanical thermal analysis of dried petiole and rhizome of red water lily (Nymphaea x rubra)


This research aimed to experimentally determine moisture sorption characteristics and mechanical thermal properties of different parts of red water lily (Nymphaea x rubra). The data obtained from dynamic vapor sorption (DVS) were modeled with six sorption isotherm models. The shape of sorption isotherms of dried petiole and rhizome was classified as Type III and II, respectively. Peleg model was the best fit with the experimental data. GAB and BET models were used to estimate monolayer moisture content (M0) of the samples and M0 of petiole ranged between 7.17 to 8.291% d.b. and 10.455 to 10.588% d.b. for GAB and BET models, respectively and M0 of rhizome ranged between 6.208 to 7.741% d.b. and 3.566 to 3.669% d.b. for GAB and BET models, respectively. Blahovec-Yanniotis model was used to describe the amount of bounded water and solution water in material and the contribution of solution water played an important role in both adsorption and desorption processes of dried petiole and rhizome. Dried red water lilies were equilibrated at different relative humidity levels. Dynamic mechanical thermal analysis (DMTA) was used to estimate the glass transition of the samples at different water activities. Increasing the solicitation frequency shifted the temperature of the relaxation to a higher temperature and Arrhenius equation described well the frequency dependency of the transition temperature. The apparent activation energies (Ea) of dried petiole and rhizome were in the range from 217.98 to 248.49 kJ/mol and 187.34 to 230.30 kJ/mol, respectively.

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Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.


A, B, C, a, a1, a2, b, b1, b2 c, d:

Model constants


Association of Official Analytical Chemists

aw :

Water activity

\({B}_{x}\) :

Bias limit in a predicted parameter


Dry basis

\(df\) :

Degree of freedom


Differential scanning calorimetry


Dynamic vapor sorption


Dynamic mechanical thermal analysis

Ea :

Apparent activation energy (kJ/mol)


Storage modulus (Pa)


Loss modulus (Pa)

\(f\) :

Frequency (Hz)

\({k}_{0}\) :

Rate of moisture changing for zero order equation (% d.b. /min)

\({k}_{1}\) :

Rate of moisture changing for first order equation (% d.b. /min)

\({k}_{2}\) :

Kinetic parameters of moisture sorption process

\({k}_{3}\) :

Kinetic parameters of diffusion process

Me :

Equilibrium moisture content (% d.b.)

Mo :

Monolayer moisture content (% d.b.)

\(m\) :

Moisture content at any time (% d.b.)

\({m}_{0}\) :

Moisture content of sample at time zero (% d.b.)

\(N\) :

Number of data

\(n\) :

Number of model parameter

\({P}_{x}\) :

Precision limit for a sample


Universal gas constant (8.314 J/mol K)

\({R}^{2}\) :

Co-efficient of determination


Relative humidity (%)

RHe :

Equilibrium relative humidity (%)


Root mean square error


Standard error of estimate

\({S}_{x}\) :

Precision index


Temperature of tan δ maximum (K)

tan δ:

E″/ E′

Tg :

Glass transition temperature (ºC)

t :

Process time (min)


Wet basis

\({w}_{x}\) :

Overall uncertainty in a predicted parameter

\(\overline{x }\) :

Mean of sample population

x 1 , x 2 , , x n :

Independent parameters

χ2 :


\(Y\) :

Experimental data

\(\overline Y\) :

Mean of sample population

\(Y'\) :

Predicted data


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The authors would like to thank the junior research fellowships program of The French Embassy in Bangkok for the financial support, in cooperation between L’Institut Agro Dijon and Suranaree University of Technology.


This research was supported by the junior research fellowships program of The French Embassy in Bangkok in cooperation between L’Institut Agro Dijon and Suranaree University of Technology.

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Phahom, T., Roudaut, G. Moisture sorption characteristics and dynamic mechanical thermal analysis of dried petiole and rhizome of red water lily (Nymphaea x rubra). Heat Mass Transfer 59, 309–328 (2023).

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  • Dynamic mechanical thermal analysis
  • Dynamic vapor sorption
  • Glass transition temperature
  • Sorption isotherms
  • Sorption kinetics