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Validation of the Component Model for Prediction of Moisture Sorption Isotherms of Two Herbs and other Products

Sorption isotherm is an essential property for the processing of biological materials. In this study, a component model for the prediction of the sorption isotherm was evaluated. In order to validate this component model, the moisture sorption isotherms for Chrysanthemum morifolium flowers and the o...

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Detalles Bibliográficos
Autor principal: Chen, Chiachung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616909/
https://www.ncbi.nlm.nih.gov/pubmed/31159457
http://dx.doi.org/10.3390/foods8060191
Descripción
Sumario:Sorption isotherm is an essential property for the processing of biological materials. In this study, a component model for the prediction of the sorption isotherm was evaluated. In order to validate this component model, the moisture sorption isotherms for Chrysanthemum morifolium flowers and the orchid Anoectochilus formosanus Hayata were determined. The sorption isotherm was measured by using the equilibrium relative humidity technique for five temperatures. Seven sorption isotherm models were selected with four quantitative criteria and residual plots to evaluate fitting ability and prediction performance for these products. The results indicated that the sorption temperature did not significantly affect the adsorption isotherm. The Caurie and Henderson equations could be used for C. morifolium flowers and A. formosanus Hayata. The isotherm data of raw bamboo, elecampe and three varieties of corn kernels from the literature were adopted to validate the component model. Comparing with the predicted values of component values and actual isotherm moisture, the component model has good predictive ability at the a(w) range smaller than 0.7. Considering the practical application, the a(w) range below 0.7 is the main range for the processing of agricultural products, and the predictive values of this component model could be helpful for food engineering and for the food industry.