Modular Feed Forward Networks to Predict Sugar Diffusivity from Date Pulp Part I. Model Validation

REFERENCES

• Rhouma , A. 1994 . Le palmier dattier en Tunisie. I: le patrimoine génétique , 127 Tunis, Tunisie : ARABESQUE .
   Google Scholar
• Centre Régional du Développement Agricole de la Tunisie . 2006 . Rapport annuaire , Tunis, Tunisie : Centre Régional du Développement Agricole de la Tunisie .
   Google Scholar
• Vagenas , G.K. and Karathanos , V.T. 1991 . Prediction of Moisture Diffusivity in Granular Materials with Special Applications to Foods . Biotechnology Progress , 7 : 419 – 426 .
   Web of Science ®Google Scholar
• Veraverbeke , A. , Verboven , P. , Oostveldt , P.V. and Nicolaï , B.M. 2003 . Prediction of moisture loss across the cuticle of apple (Malus sylvestris subsp. mitis (Wallr.)) during storage, Part 1: Model development and determination of diffusion coefficients . Postharvest Biology and Technology , 30 : 75 – 88 .
   Web of Science ®Google Scholar
• Nguyen , T.A. , Verboven , P. , Scheerlinck , N. , Vandewalle , S. and Nicolaï , B.M. 2006 . Estimation of effective diffusivity of pear tissue and cuticle by means of a numerical water diffusion model . Journal of Food Engineering , 72 : 63 – 72 .
   Web of Science ®Google Scholar
• Ochoa-Martinez , C.I. and Ayala-Aponte , A.A. 2006 . Prediction of mass transfer kinetics during osmotic dehydration of apples using neural networks . Lebensmittel-Wissenschaft und -Technologie , 40 ( 4 ) : 638 – 645 .
   Google Scholar
• Raymond , K. B. and Paterson , A. 2002 . An artificial neural network model for predicting flavour intensity in blackcurrant concentrates . Food Quality and Preference , 13 : 117 – 128 .
   Google Scholar
• Rai , P. , Majumdar , G.C. , DasGupta , S. and De , S. 2005 . Prediction of the viscosity of clarified fruit juice using artificial neural network: a combined effect of concentration and temperature . Journal of Food Engineering , 68 : 527 – 533 .
   Web of Science ®Google Scholar
• Hernàndez-Pérez , J.A. , Garcia-Alvarado , M.A. , Trystrama , G. and Heyda , B. 2004 . Neural networks for the heat and mass transfer prediction during drying of cassava and mango . Innovative Food Science and Emerging Technologies , 5 : 57 – 64 .
   Google Scholar
• Mattar , H.L. , Minim , L.A. , Coimbra , J.S.R. , Minim , V.P.R. , Saraiva , S.H. and Telis-Romero , J. 2004 . Modeling Thermal Conductivity, Specific Heat, and Density of Milk: A Neural Network Approach . International Journal of Food Properties , 7 ( 3 ) : 531 – 539 .
   Web of Science ®Google Scholar
• Therdthai , N and Zhou , W. 2002 . Hybrid Neural Modeling of the Electrical Conductivity Property of Recombined Milk . International Journal of Food Properties , 5 ( 1 ) : 49 – 61 .
   Web of Science ®Google Scholar
• Neurosolutions . 2006 . “ The neural network simulation environment ” . In Getting started manual v. 5.0 , 82 – 165 . Gainesville, FL : NeuroDimension Inc .
   Google Scholar
• Neurosolutions Software v.5.0. NeuroDimension Inc., FL, USA. 2006.
   Google Scholar
• Geankoplis , C.J. 1983 . Transport processes and unit operations , 415 – 475 . Boston, MA : Allyn and Bacon Inc .
   Google Scholar
• Bird , R.B. , Stewart , W.E. and Lightfoot , E.N. 1960 . Transport Phenomena , 780 New York : John Wiley & Sons .
   Google Scholar
• Philibert , J. 1985 . Transfert de Masse, Diffusion et Transport , 472 Diffusion et transport de matière dans les solides .
   Google Scholar
• Bouabidi , H. , Reyens , M. and Roussi , M.B. 1996 . Critères de caractérisation de fruits de quelques cultivars de palmier dattier (Phoenix dactylifera L.) du sud tunisien . Ann de l'INRAT , : 69 – 78 .
   Google Scholar
• 2002 . “ Table Curve 2D Software v.5.01 ” . In SYSTAT Software Inc Chicago, IL
   Google Scholar
• 2002 . “ Table Curve 2D. Getting started manual v. 5.01 ” . In SYSTAT Software Inc Illinois, Chicago, , USA
   Google Scholar