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TITLE OF THE POSTER – ALL CAPITAL LETTERS – 30 TO 36 PUNTO Ihsan Burak CAM1,2, Emrah EROGLU2, Ayhan TOPUZ2* 1Akdeniz University Food Safety and Agricultural Research Center, Antalya, Turkey 2Akdeniz University Faculty of Engineering Food Engineering Department, Antalya, Turkey ABSTRACT Abstact should be around 200 words punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto punto. Abstact should be around 300 words punto. RESULTS Table 2. Calculated kinetic parameters for different drying conditions Drying Condition Model RMSE X 2 EF CC-MAD 5% O2 Midilli (MR = a exp(-ktn) + bt) 0,02672 0,00103 -0,0107 k=0, n=2, a=0, b=0 CC-MAD 10% O2 0,02303 0,0008 -0,0059 k=0, n=2, a=0, b=0 Hot Air 21% O2 Wang Sing (MR = 1 + at + bt2) 0,010166 0,000121 -0,001344 a=-0, b=-0, MATERIAL & METHOD Banana was peeled and cut into circle of 5mm in thickness using laser slicing knife. Sliced banana fruits were subjected to three different drying treatments as CC-MAD at 60˚C with 3 m/s air velocity in 5% oxygen medium, 10% oxygen medium and 21% oxygen (air) medium. Thirteen different drying models used for modelling drying kinetics of banana slices [2]. SAMPLE POSTER TEMPLATE Figure 1. Moisture ratio changes during drying for banana slices under different drying conditions CONCLUSION Experimental moisture content data on dry weight basis were used for modeling of drying experiments. During the drying process performed under different drying air oxygen level conditions, these moisture content data obtained at various times were converted into moisture ratio values and fitted against the drying time. The 13 thin layer drying models were compared in terms of the statistical parameters RMSE, MBE, χ2, R2 and EF. Midilli (MR = a exp(-ktn) + bt) model was found best fitting model for CC-MAD in both 5% and 10% drying medium. On the other hand, Wang Sing (MR = 1 + at + bt2) model was the best fitting model for hot air drying kinetics of banana slices. ACKNOWLEDGE This project was financially supported by the Scientific and Technological Research Council of Turkey (TUBITAK), project number: 213 O 065 *CC-MAD is patent pending application on food drying. REFERENCES Cam, I.B., Basunal-Gulmez, H., Eroglu, E., Topuz, A. Strawberry Drying: Development of a Closed-cycle Modified Atmosphere Drying System for Food Products and the Performance Evaluation of a Case Study, Drying Technology (DOI: / ) Menges, H.O. and Ertekin, C. Thin layer drying model for treated and untreated Stanley plums. Energy Conversion and Management, 47, 2337–2348 (2006)Farkas I.: Use of artificial intelligence for modelling of drying process, Drying Technology, Vol. 31, No. 7, 2013, pp
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