Browsing by Author "Zare, Zahra"
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- Modelling of mass transfer kinetic in osmotic dehydration of kiwifruitPublication . Jabrayili, Sharokh; Farzaneh, Vahid; Zare, Zahra; Bakhshabadi, Hamid; Babazadeh, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel Saraiva deOsmotic dehydration characteristics of kiwifruit were predicted by different activation functions of an artificial neural network. Osmotic solution concentration (y(1)), osmotic solution temperature (y(2)), and immersion time (y(3)) were considered as the input parameters and solid gain value (x(1)) and water loss value (x(2)) were selected as the outlet parameters of the network. The result showed that logarithm sigmoid activation function has greater performance than tangent hyperbolic activation function for the prediction of osmotic dehydration parameters of kiwifruit. The minimum mean relative error for the solid gain and water loss parameters with one hidden layer and 19 nods were 0.00574 and 0.0062% for logarithm sigmoid activation function, respectively, which introduced logarithm sigmoid function as a more appropriate tool in the prediction of the osmotic dehydration of kiwifruit slices. As a result, it is concluded that this network is capable in the prediction of solid gain and water loss parameters (responses) with the correlation coefficient values of 0.986 and 0.989, respectively.
- Screening of the aerodynamic and biophysical properties of barley maltPublication . Ghodsvali, Alireza; Farzaneh, Vahid; Bakhshabadi, Hamid; Zare, Zahra; Karami, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel Saraiva deAn understanding of the aerodynamic and biophysical properties of barley malt is necessary for the appropriate design of equipment for the handling, shipping, dehydration, grading, sorting and warehousing of this strategic crop. Malting is a complex biotechnological process that includes steeping; ger-mination and finally, the dehydration of cereal grains under controlled temperature and humidity conditions. In this investigation, the biophysical properties of barley malt were predicted using two models of artificial neural networks as well as response surface methodology. Stepping time and germination time were selected as the independent variables and 1 000 kernel weight, kernel density and terminal velocity were selected as the depen-dent variables (responses). The obtained outcomes showed that the artificial neural network model, with a logarithmic sigmoid activation function, presents more precise results than the response surface model in the prediction of the aerodynamic and biophysical properties of produced barley malt. This model presented the best result with 8 nodes in the hidden layer and significant correlation coefficient values of 0.783, 0.767 and 0.991 were obtained for responses one thousand kernel weight, kernel density, and terminal velocity, respectively. The outcomes indicated that this novel technique could be successfully applied in quantitative and qualitative monitoring within the malting process.
- The impact of germination time on the some selected parameters through malting processPublication . Farzaneh, Vahid; Ghodsvali, Alireza; Bakhshabadi, Hamid; Zare, Zahra; Carvalho, Isabel S.In the present study, the impacts of germination time on the enzymes activity attributed in malting and some polysaccharides contents of the malt prepared from the Joseph barley variety have been screened using a completely random design with three levels of germination time(3, 5 and 7 days). The archived outcomes revealed that the highest quantity of starch has been observed in the malt resulted from 3 days germination, and an enhancement in the germination period from 3 to 7 days decreased the quantity of available starch. An enhancement in the germination period presented a reduction in the beta-glucan quantity in the malting seeds. The malt produced 7 days after germination had the highest enzymatic activity(253 U. kg(-1)). The comparison of data average using Duncan test showed that the minimum and maximum value of alpha-Amylase enzyme activity and diastatic power were recorded in the malts produced 3 and 7 days after germination, respectively. Increasing in the germination time led to a reduction in malting efficiency, however the efficiency of the hot water extraction showed enhancement. The outcomes of the correlation between the studied parameters showed that the beta-glucan and starch quantities are negatively affected by the activities of beta-Glucanase and alpha-Amylase. (C) 2016 Elsevier B.V. All rights reserved.