Abstract
In an accompanying study, a predictive mathematical model was developed to simulate heat transfer in a tomato undergoing double sided infrared (IR) heating in a dry-peeling process. The aims of the present study were to validate the developed model using experimental data and to investigate different engineering parameters that most strongly influence the rate and uniformity of IR heating. The mode was verified by comparison of the predicted temperature profiles with experimental data for tomatoes with three dimensions. Uniformity of temperature distribution at tomato surface was quantified by surface-averaged temperatures and a derived temperature uniformity index. The predicted temperatures agreed well with experimental data (r 2 > 0.9). Simulation results illustrated that IR heating induced a dramatic temperature increase on the tomato surface, which extended to 0.6 mm beneath (>90 °C) during a 60-s heating period, whereas interior temperature at the tomato center remained low (<30 °C). Sensitivity analysis suggested that strategies to enhance IR heating rate and uniformity can be implemented through varying emissive power, adjusting the distance between emitters, and presorting tomatoes according to size. The validated model provides an effective design tool for better understanding the complex IR radiation heating in developing the innovative IR dry-peeling process.
Similar content being viewed by others
References
Das, D. J., & Barringer, S. A. (1999). Use of organic solvents for improving peelability of tomatoes. Journal of Food Processing and Preservation, 23(3), 193–202.
Garcia, E., & Barrett, D. M. (2006a). Evaluation of processing tomatoes from two consecutive growing seasons: Quality attributes, peelability and yield. Journal of Food Processing and Preservation, 30(1), 20–36.
Garcia, E., & Barrett, D. M. (2006b). Peelability and yield of processing tomatoes by steam or lye. Journal of Food Processing and Preservation, 30(1), 3–14.
Geedipalli, S., Rakesh, V., & Datta, A. (2007). Modeling the heating uniformity contributed by a rotating turntable in microwave ovens. Journal of Food Engineering, 82(3), 359–368.
Li, X (2012) A study of infrared heating technology for tomato peeling: process characterization and modeling. Ph.D. Dissertation, Department of Biological and Agricultural Engineering, University of California at Davis, Davis, California, USA.
Li, X., Pan, Z., Bingol, G., McHugh, T., & Atungulu, G (2009) Feasibility study of using infrared radiation heating as a sustainable tomato peeling method. In Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE) (Vol. 96074, pp. 1–14, Paper No. 095689), ASABE, Reno/St. Joseph.
Li, X., Pan, Z., Upadhyaya, S. K., Atungulu, G. G., & Delwiche, M. (2011). Three-dimensional geometric modeling of processing tomatoes. Transactions of the ASABE, 54(6), 2287–2296.
Pan, Z., Li, X., Bingol, G., McHugh, T., & Atungulu, G. (2009). Development of infrared radiation heating method for sustainable tomato peeling. Appl Eng Agric, 25(6), 935–941.
Schreiber, L., & Schönherr, J. (1990). Phase transitions and thermal expansion coefficients of plant cuticles. Planta, 182(2), 186–193.
Tanaka, F., Verboven, P., Scheerlinck, N., Morita, K., Iwasaki, K., & Nicola, B. (2007). Investigation of far infrared radiation heating as an alternative technique for surface decontamination of strawberry. Journal of Food Engineering, 79(2), 445–452.
Tiwari, G., Wang, S., Tang, J., & Birla, S. L. (2011a). Analysis of radio frequency (RF) power distribution in dry food materials. Journal of Food Engineering, 104(4), 548–556.
Tiwari, G., Wang, S., Tang, J., & Birla, S. (2011b). Computer simulation model development and validation for radio frequency (RF) heating of dry food materials. Journal of Food Engineering, 105(1), 48–55.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, X., Pan, Z. Dry Peeling of Tomato by Infrared Radiative Heating: Part II. Model Validation and Sensitivity Analysis. Food Bioprocess Technol 7, 2005–2013 (2014). https://doi.org/10.1007/s11947-013-1188-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11947-013-1188-3