Cold Plasma: A Novel Pretreatment Method for Drying Canola Seeds: Kinetics Study and Superposition Modeling

ماشین های کشاورزی

Article 4, Volume 13, Issue 1 - Serial Number 27, March 2023, Pages 41-53   

Document Type: Research Article-en

DOI: 10.22067/jam.2022.75630.1096

Authors

F. Osloob¹; M. Moradi^{* 2}; M. Niakousari³

¹MSc graduated, Department of Biosystems Engineering, School of Agriculture, Shiraz University, Shiraz, Iran

²Department of Biosystems Engineering, School of Agriculture, Shiraz University, Shiraz, Iran

³Department of Food Science and Technology, School of Agriculture, Shiraz University, Shiraz, Iran

Abstract

Accurate investigation of kinetics and development of high-precision seed drying models will help better studying the drying process by identifying effective parameters. Present study investigates the application of cold plasma (CP), as a pretreatment process, in air drying of canola seeds. This may bring about some complication into the drying kinetics investigation. Canola seeds with an initial moisture content of 27.5±1% (dry basis) were exposed to CP for 0, 15, 30, and 60 s prior to fluidization by air at temperatures of 40, 50 and 60 °C in a pilot scale fluidized bed heated by a solar panel.  The results showed a decreasing trend in drying time from 40 to 60 ^oC. The shortest drying time corresponds to samples dried at 60 ^oC with no CP pretreatment. The longest period however occurred for samples dried at 40 ^oC with 60 s of CP pretreatment. The greatest effect of CP on reducing the drying time was observed at temperatures of 40 and 50 °C at the CP exposure time of 15 and 60 s, respectively.  A reasonably accurate study of drying kinetics was accomplished using the superposition method. Accordingly, using experimental data, curves correspond to different drying conditions were plotted and in two steps these were shifted to a reference curve to acquire a final drying curve. The curve then was fitted to a second-order equation, and was validated using the experimental data. The correlation coefficients, mean square error and mean absolute error were 0.99, 0.03, and 0.023, respectively.

Keywords

Canola seeds; Mean comparison; Shifted factor; Superposition

References

1. Amini, M., & Ghoranneviss, M. (2016). Effects of cold plasma treatment on antioxidants activity, phenolic contents and shelf life of fresh and dried walnut (Juglans regia) cultivars during storage. LWT- Food Science and Technology, 73, 178-184.‏ https://doi.org/10.1016/j.lwt.2016.06.014
2. Bao, T., Hao, X., Shishir, M. R. I., Karim, N., & Chen, W. (2021). Cold plasma: An emerging pretreatment technology for the drying of jujube slices. Food Chemistry, 337, 127783. https://doi.org/10.1016/j.foodchem.2020.127783
3. Benseddik, A., Azzi, A., Zidoune, M. N., & Allaf, K. (2018). Mathematical empirical models of thin-layer airflow drying kinetics of pumpkin slice. Engineering in Agriculture, Environment and Food, 11(4), 220-231.‏ https://doi.org/10.1016/j.eaef.2018.07.003
4. Cheung, B., Terekhov, A., Chen, Y., Agrawal, P., & Olshausen, B. (2019). Superposition of many models into one. arXiv preprint arXiv, 1902.05522.‏
5. Ghasemi, J., Moradi, M., Karparvarfard, S. H., Golmakani, M. T., & Khaneghah, A. M. (2021). Thin layer drying kinetics of lemon verbena leaves: a quality assessment and mathematical modeling. Quality Assurance and Safety of Crops & Foods, 13(1), 59-72.‏ https://doi.org/10.15586/qas.v13i1.835
6. Kek, S. P., Chin, N. L., & Yusof, Y. A. (2014). Simultaneous time-temperature-thickness superposition theoretical and statistical modeling of convective drying of guava. Journal of Food Science and Technology, 51(12), 3609-3622.‏ https://doi.org/10.1007/s13197-013-0923-0
7. Khanali, M., Rafiee, Sh., Jafari A., Hashemabadi, S. H., & Banisharif, A. (2012). Mathematical modeling of fluidized bed drying of rough rice (Oryza sativa) grain. Journal of Agricultural Technology, 8(3), 795-810.‏
8. Khazaei, J., Chegini, G. R., & Bakhshiani, M. (2008). A novel alternative method for modeling the effects of air temperature and slice thickness on quality and drying kinetics of tomato slices: Superposition technique. Drying Technology, 26, 759-775. https://doi.org/10.1080/07373930802046427
9. Li, S., Chen, S., Han, F., Xv, Y., Sun, H., Ma, Z., ... & Wu, W. (2019). Development and Optimization of Cold Plasma Pretreatment for Drying on Corn Kernels. Journal of Food Science, 84(8), 2181-2189. https://doi.org/10.1111/1750-3841.14708
10. McVetty, P. B. E., & Duncan, R. W. (2016). Canola/Rapeseed: Genetics and Breeding. In Reference Module in Food Science; Elsevier: Amsterdam, the Netherlands.
11. Moradi, M., Niakousari, M., & Mousavi Khaneghah, A. (2019). Kinetics and mathematical modeling of thin layer drying of osmo‐treated Aloe vera (Aloe barbadensis) gel slices. Journal of Food Process Engineering, 42(6), e13180.‏ https://doi.org/10.1111/jfpe.13180
12. Moradi, M., Azizi, S., Niakousari, M., Kamgar, S., & Khaneghah, A. M. (2020). Drying of green bell pepper slices using an IR-assisted Spouted Bed Dryer: An assessment of drying kinetics and energy consumption. Innovative Food Science & Emerging Technologies, 60, 102280.‏ https://doi.org/10.1016/j.ifset.2019.102280
13. Nishime, T. M. C., Borges, A. C., Koga-Ito, C. Y., Machida, M., Hein, L. R. O., & Kostov, K. G. (2017). Non-thermal atmospheric pressure plasma jet applied to inactivation of different microorganisms. Surface and Coatings Technology, 312, 19-24. https://doi.org/10.1016/j.surfcoat.2016.07.076
14. Pankaj, S. K., Bueno-Ferrer, C., Misra, N. N., O'Neill, L., Tiwari, B. K., Bourke, P., & Cullen, P. J. (2015). Dielectric barrier discharge atmospheric air plasma treatment of high amylose corn starch films. LWT-Food Science and Technology, 63(2), 1076-1082.‏ https://doi.org/10.1016/j.lwt.2015.04.027
15. Pankaj, S. K., & Keener, K. M. (2018). Cold plasma processing of fruit juices. In Fruit juices (pp. 529-537). Academic Press.‏ https://doi.org/10.1016/B978-0-12-802230-6.00026-6
16. Sarangapani, C., Devi, Y., Thirundas, R., Annapure, U. S., & Deshmukh, R. R. (2015). Effect of low-pressure plasma on physico-chemical properties of parboiled rice. LWT- Food Science and Technology, 63, 452-460. https://doi.org/10.1016/j.lwt.2015.03.026
17. Simha, P., Mathew, M., & Ganesapillai, M. (2016). Empirical modeling of drying kinetics and microwave assisted extraction of bioactive compounds from Adathoda vasica and Cymbopogon citratus. Alexandria Engineering Journal, 55(1), 141-150.‏ https://doi.org/10.1016/j.aej.2015.12.020
18. Saengrayap, R., Tansakul, A., & Mittal, G. (2015). Effect of far-infrared radiation assisted microwave-vacuum drying on drying characteristics and quality of red chili. Journal of Food Science and Technology, 52(5), 2610-2621. https://doi.org/10.1007/s13197-014-1352-4
19. Yousefi, A., Niakousari, M., & Moradi, M. (2013). Microwave assisted hot air drying of papaya (Carica papaya) pretreated in osmotic solution. African Journal of Agricultural Research, 8(25), 3229-3235.‏ https://doi.org/10.5897/AJAR12.180
20. Wang, H., Yi, S., & Sharma, M. M. (2018). A computationally efficient approach to modeling contact problems and fracture closure using superposition method. Theoretical and Applied Fracture Mechanics, 93, 276-287.‏ https://doi.org/10.1016/j.tafmec.2017.09.009
21. Wang, Y., Guo, P., Dai, F., Li, X., Zhao, Y., & Liu, Y. (2018). Behavior and modeling of fiber-reinforced clay under triaxial compression by combining the superposition method with the energy-based homogenization technique. International Journal of Geomechanics, 18(12), 04018172.‏
22. Zhang, X. L., Zhong, C. S., Mujumdar, A. S., Yang, X. H., Deng, L. Z., Wang, J., & Xiao, H. W. (2019). Cold plasma pretreatment enhances drying kinetics and quality attributes of chili pepper (Capsicum annuum). Journal of Food Engineering, 241, 51-57. https://doi.org/10.1016/j.jfoodeng.2018.08.002
23. Zhou, Y. H., Vidyarthi, S. K., Zhong, C. S., Zheng, Z. A., An, Y., Wang, J., ... & Xiao, H. W. (2020). Cold plasma enhances drying and color, rehydration ratio and polyphenols of wolfberry via microstructure and ultrastructure alteration. LWT- Food Science and Technology, 134, 110173.‏ https://doi.org/10.1016/j.lwt.2020.110173