Research Article of American Journal of Agricultural Research
Modelling of unsteady spatially distributed drying parameters assessed non-destructively in a small industrial food dryer
Waseem Amjada*, Anjum Munira, Liaqat Ali Shahidb, Barbara Sturmc
aDepartment of Energy Systems Engineering, University of Agriculture Faisalabad, Pakistan; bPakistan Agricultural Research Council (PARC) Islamabad, Pakistan; cDepartment of Agricultural & Biosystems Engineering, University of Kassel, Germany
Modelling of unsteady moisture diffusion in relation of product temperature become complex due to complexity involve in solving complex numerical equations. In this study, a simplified methodology (determination of drying parameters: lag factor and drying constant) used to model change in food quality with its temperature in an industrial dryer using potato slices (6mm thick, 60°C). A shiftable real time data acquisition box was developed. Linear and exponential models were developed to estimate product quality as a function of dimensionless moisture ratio, linked with change in product temperature. The experimental and models predicted color kinetics using variable values of lag factor and drying constant revealed good correlation coefficients (R2 = 0.88-0.99, P ˂ 0.0001). The change in spatially distributed quality parameter with product weight loss was successfully assessed and modelled unsteadily, providing a better way to optimize the design process as a function of food physiognomies in an industrial dryer.
Keywords: Unsteady modelling, Real time data acquisition, image analysis
How to cite this article:
Waseem Amjad, Anjum Munir, Liaqat Ali Shahid, Barbara Sturm.Modelling of unsteady spatially distributed drying parameters assessed non-destructively in a small industrial food dryer. American Journal of Agricultural Research, 2020,5:74.
1. Akpinar E, Midilli A, Bicer Y. Single layer drying behaviour of potato slices in a convective cyclone dryer and mathematical modelling. Energy Convers Manage 44: 1689–705 (2003).
2. Akpinar EK, Bicer Y. Mathematical modelling and experimental study on thin layer drying of strawberry. International Journal of Food Engineering, 2006; 2(1): article 5.
3. Amjad W, Munir A, Esper A, Hensel O. Spatial homogeneity of drying in a batch type food dryer with diagonal air ﬂow design. Journal of Food Engineering, 2015; 144: 148–155
4. Bamji SF, Corbitt C. Glyceollins: Soybean phytoalexins that exhibit a wide range of health-promoting effects. J. Funct. Foods, 2017; 34: 98–105
5. Bamji SF, Page RB, Patel D, Sanders A, Alvarez AR, Gambrell C, Naik K, Raghavan AM, Burow ME, Boue SM, Klinge CM, Ivanova M, Corbitt C. Soy glyceollins regulate transcript abundance in the female mouse brain. Funct. Integr. Genomics, 2015; 15: 549–561
6. Crank J. The mathematics of diffusion. Oxford University Press: (1975).
7. Dincer I, Dost SA. Modelling study for moisture diffusivities and moisture transfer coefﬁcients in drying of solid objects. International Journal of Energy Resources, 1996; 20: 531–9
8. Dincer I, Hussain MM. Development of a new Biot number and lag factor correlation for drying applications. International Journal of Heat Mass Transfer, 2004; 47: 653–8
9. Fernandez L, Castillero C, Aguilera JM. An application of image analysis to dehydration of apple discs. Journal of Food Engineering, 2005; 67: 185–193
10. Finlayson G, Darrodi MM, Mackiewicz M. The alternating least squares technique for nonuniform intensity colour correction. Colour Research & Application, 2015b; 40 (3): 232–242
11. Finlayson G, Mackiewicz M, Hurlbert A. Colour Correction using Root-Polynomial Regression. IEEE Transactions on Image Processing, 2015a; 24 (5): 1460 – 1470
12. León K, Mery D, Pedreschi F, León J. Colour measurement in Lab units from RGB digital images. Food Research International, 2006; 39: 1084-1091
13. Mujumdar AS, Law CL. Trends and applications in postharvest processing, Food and Bioprocess Technol. Drying technology, 2009; 3 (6): 843-852
14. Nazghelichi T, Aghbashlo M, Kianmehr MH, Omid M. Prediction of energy and exergy of carrot cubes in a fluidized bed dryer by artificial neural networks. Drying Technology, 2011; 29 (3): 295–307
15. Nunez Vega AM, Sturm B, Hofacker W. Simulation of the convective drying process with automatic control of surface temperature. Journal of Food Engineering, 2016; 170: 16-23
16. Pardsseshi IL, Arora S, Borker PA. Thin-layer drying of green peas and selection of a suitable thin-layer drying model. Drying Technology, 2009; 27: 288-295
17. Pathare PB, Opara UL, Al-Said FAJ. Colour Measurement and Analysis in Fresh and Processed Foods: A Review. Food Bioprocess Technol DOI 10.1007/s11947-012-0867-9 (2012).
18. Simal S, Garau C, Femenia A, Rossello C. Drying of red pepper (Capsicum annuum): water desorption and quality. International Journal of Food Engineering 1(4): article 1 (2005).
19. Sturm B, Anna-Maria NV, Hofacker WC. Influence of process control strategies on drying kinetics, colour and shrinkage of air dried apples. Applied Thermal Engineering, 2014; 62: 455-460
20. Sturm B, Einfluss der Führung des Trocknungsprozesses auf den Trocknungsverlauf und die Produkteigenschaften empfindlicher Biologischer Güter (Influence of Process Control on Drying Kinetics and Product Attributes of Sensitive Biological Products), Forschungsbericht Agrartechnik 491, VDI-MEG, Witzenhausen, Germany, ISSN 0931-6264 (2010).
21. Sturm B, Hofacker W, Hensel O. Optimizing the drying parameters for hot air dried apples. Drying Technology, 2012; 30 (14): 570-1582
22. Tripathy PP, Kumar S. Determination of temperature dependent drying parameters for potato cylinders and slices during solar drying. Energy Conversion and Management, 2008; 49: 2941–2948
23. Turhan M, Erdogdu F. Error associated with assuming a finite regular geometry as an infinite one for modelling of transient heat and mass transfer processes. Journal of Food Engineering, 2003; 59: 291–6