Mathematical modelling of solar drying of apricots in thin layers

By I. T. Toğrul, D. Pehlivan. 2002

536 citations recorded by the source corpus.

Subfields: Food Science, Mechanical Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/e2d8a677e00c32ac3f5909d7352ee0fe3dac1f8f

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Citations in the corpus

Mathematical modelling of drying of bay leaves (2005, methodology): “Some products studied are as follows: Sultana grape [6], banana [7], apricot [8], seedless grape, fig, green pea, tomato and onion [9], pistachio [10], potato slice [11], pumpkin slice [12] and eggplant [13].”
Mathematical Modeling of Drying Characteristics of Indian Mackerel (Rastrilliger kangurta) in Solar-Biomass Hybrid Cabinet Dryer (2008, methodology): “The drying curves obtained from different drying methods were fitted with moisture ratio equations However, the moisture ratio (MR) was simplified to M=M0 instead of (M Me)=(M0 Me) because relative humidity of the drying air continuously fluctuated in the drying chamber.([14]) The best drying model ”
Mathematical modeling of convective thin layer drying of basil leaves (2011, background): “In addition to coefficient of determination, the goodness of fit was determined by various statistical parameters such as reduced chi-square (χ2), mean bias error (MBE), and root mean square error (RMSE).”
Mathematical modeling of drying kinetics of milky mushroom in a fluidized bed dryer (2009, background): “should be lower (Demir et al., 2004; Erenturk et al., 2004; Pangavhane et al., 1999; Sarsavadia et al., 1999; Togrul and Pehlivan, 2002 ).”
Mathematical Modeling of Withering Characteristics of Tea Leaves (2006, methodology): “where MRexp,i is the ith experimental moisture ratio, MRpre,i is the ith predicted moisture ratio, N is the number of observations, n is the number of constants in drying model, and MRexpmean is the mean value of experimental moisture ratio.([1,2])”