2021-05-14T05:35:40Z
https://digital.csic.es/dspace-oai/request
oai:digital.csic.es:10261/96390
2018-11-28T11:55:09Z
com_10261_42343
com_10261_2
col_10261_42344
Guignon, Bérengère
Torrecilla, J. S.
Otero, Laura
Ramos, A. M.
Molina García, Antonio D.
Sanz Martínez, Pedro D.
2014-05-08T13:29:19Z
2014-05-08T13:29:19Z
2008
Critical Reviews in Food Science and Nutrition 48: 328- 340 (2008)
http://hdl.handle.net/10261/96390
http://dx.doi.org/10.1080/10408390701347736
The Pure water (P,T)-phase diagram is known in the form of empirical equations or tables from nearly a century as a result of Bridgman's work. However, few data are available on other aqueous systems probably due to the difficulty of high-pressure measurements. As an alternative, six approaches are presented here to obtain the food phase diagrams in the range of pressure 0.1-210 MPa. Both empirical and theoretical methods are described including the use of an artificial neural network (ANN). Experimental freezing points obtained at the laboratory of the authors and from literature are statistically compared to the calculated ones. About 400 independent freezing data points of aqueous solutions, gels, and foods are analysed. A polynomial equation is the most accurate and simple method to describe the entire melting curve. The ANN is the most versatile model, as only one model allows the calculation of the initial freezing point of all the aqueous systems considered. Robinson and Stokes' equation is successfully extended to the high pressures domain with an average prediction error of 0.4°C. The choice of one approach over the others depends mainly on the availability of experimental data, the accuracy required and the intended use for the calculated data. Copyright © Taylor and Francis Group, LLC.
eng
closedAccess
Hydrostatic pressure
High pressure freezing/thawing processes
Artiﬁcial neural network
PT phase diagram
modelling
Freezing/melting point
The initial freezing temperature of foods at high pressure
artículo