Study on Drying Process of Farmed Shrimp Meat in a Hot Air Convective Dryer and Variation of Some Related Parameters

ماشین های کشاورزی

Volume 14, Issue 3 - Serial Number 33, September 2024, Pages 253-269   

Document Type: Research Article

DOI: 10.22067/jam.2023.80905.1145

Authors

M. Almaei¹; S. M. Nassiri^{* 2}; M. A. Nematollahi¹; D. Zare¹; M. Khorram³

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

²Department of Biosystems Engineering and Seafood Processing Research Center, School of Agriculture, Shiraz University, Shiraz, Iran

³Department of Gas Engineering, School of Chemical, Petroleum and Gas Engineering, Shiraz University, Shiraz, Iran

Abstract

Introduction
Drying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers numerous advantages, including extended shelf life, enhanced microbial stability, convenient consumption, reduced transportation costs, increased value, and product diversity.
To accurately model these processes and thus obtain information on factors such as shelf life and energy consumption, it is necessary to determine the product’s initial and final temperatures, its geometry and dimensions, and its thermo-physical characteristics. Simulation of different drying processes requires accurate estimation of the effective moisture diffusion coefficient, which is highly dependent on temperature and humidity. Its dependence can be shown by an equation with an Arrhenius structure as an empirical function of humidity and temperature, or by considering the activation energy.
It is necessary to have sufficient knowledge about heat and mass transfer characteristics, such as diffusion or penetration coefficient and the heat transfer coefficient to estimate the final temperature and drying time. This study investigated the drying process of peeled farmed shrimp (Litopenaeus vannamei) using a convective hot air dryer. Various parameters such as shrinkage and the effective moisture diffusion coefficient were examined.
Materials and Methods
A drying device was built to conduct experimental studies on drying shrimp samples. The experiments were conducted on sliced shrimp meat samples at temperatures of 40, 50, and 60 degrees Celsius, with a constant air velocity of 1.5 m/s. The experimental drying models were based on diffusion theory. In these models, it is assumed that the resistance to moisture diffusion occurs from the outer layer of the food. In most cases, Fick's second law was used to describe the phenomenon of moisture penetration.
The study used the standard method of immersion in toluene to measure volume changes in the samples. During the drying process, the volume of the samples was measured at 45-minute intervals, and their volume changes were calculated. To measure the moisture content of the samples, each test started by recording the initial weight of the samples using a digital scale with an accuracy of ±0.001 g. During the drying process, the samples were weighed each time their volume was measured.
Shrinkage during the drying process is commonly modeled by finding a relationship between shrinkage and moisture, using linear and non-linear models. In most cases, effective permeability is defined as a function of humidity and temperature. For this purpose, curve-fitting methods were employed to analyze the data collected from experimental tests. The appropriate function was extracted by incorporating the Arrhenius equation, which is applicable to most food items.
Results and Discussion
Based on the results of statistical indices, the linear model was the best model for depicting the relationship between shrinkage changes versus moisture ratio changes among the various experimental models evaluated for shrinkage and drying kinetics. Similarly, the Weibull distribution demonstrated superior performance in expressing variations in moisture ratio over time. A moisture dependent experimental model was used to express the variations in the apparent density of shrimp, resulting in a computed range of 1017-1117 kg m^-3. Furthermore, an Arrhenius equation was derived to express the effect of moisture content and temperature on the effective diffusion coefficient of shrimp. According to the results, the effective diffusion coefficient of shrimp exhibited variations ranging from 0.08 ×10^-9 m² s^-1 to 7.39×10^-9 m² s^-1. When deriving the effective diffusion coefficient, the impact of the number of terms in Fick's second law on the variation of the moisture ratio was studied. The findings revealed that increasing the number of terms beyond 100 did not significantly affect the model’s outputs.
Conclusion
The linear model had the highest coefficient of determination (R²) among the evaluated shrinkage models, as well as the lowest root mean square error and sum of square error (SSE). This makes it the most optimal model for interpreting shrinkage at the tested temperature levels. The Weibull distribution experimental model proved to be the most suitable for expressing changes in the moisture ratio of shrimp meat slices over time within the evaluated temperature range. The Arrhenius model accurately predicts changes in the effective diffusion coefficient of shrimp slices with respect to temperature and moisture content within the tested temperature range.

Keywords

Drying; Effective moisture diffusion coefficient; Shrimp meat; Shrinkage

References

1. Achanta, S., Okos, M. R., Cushman, J. H., & Kessler, D. P. (1997). Moisture transport in shrinking gels during saturated drying. Association of International Chemical Engineers Journal, 43(8), 2112-2122. https://doi.org/10.1002/aic.690430818
2. Akonor, P. T., Ofori, H., Dziedzoave, N. T., & Kortei, N. K. (2016). Drying characteristics and physical and nutritional properties of shrimp meat as affected by different traditional drying techniques. International Journal of Food Science, 2016. 7879097. https://doi.org/10.1155/2016/7879097
3. Al-Hilphy, A., Al-Mtury, A., Al‐Iessa, S., Gavahian, M., Al‐Shatty, S., Jassim, M., & Mohusen, Z. (2022). The pilot-scale rotary infrared dryer of shrimp (Metapenaeus affinis): mathematical modeling and effect on the chemical, color components, and sensory attributes. Journal of Food Process Engineering, 45(6). https://doi.org/10.1111/jfpe.13945
4. Amankwah, E. A., Dzisi, K. A., Staten, G., & Boxtel, A. J. B. (2018). Moisture Dependent Diffusion and Shrinkage in Yam during Drying. International Journal of Food Engineering. https://doi.org/1515/ijfe-2017-0394
5. Anabel, F., Celia, R., Germán, M., & Rosa, R. (2018). Determination of effective moisture diffusivity and thermodynamic properties variation of regional wastes under different atmospheres. Case Studies in Thermal Engineering, 12(2018), 248-257. https://doi.org/10.1016/j.csite.2018.04.015
6. Aniesrani Delfiya, D. S., Murali, S., Alfiya, P. V., & Samuel, M. P. (2020). Drying characteristics of shrimp (Metapenaeus dobsoni) in electrical dryer. Pantnagar Journal of Research, 18(3), 281-285.
7. Anonymous. (2020). Iran Fisheries Organization statistical yearbook, 2014-2020. Iran Fisheries Organization Tehran. Iran. (in Persian).
8. Azimi, M. J. (2016). Cabinet Drying, Freeze Drying and Sun Drying methods of shrimp and study of its Physicochemical and Microbial. M.Sc. dissertation. University of Shiraz. (in Persian).
9. Azzouz, S., Guizani, A., Jomma, W., & Belghith, A. (2002). Moisture diffusivity and drying kinetic equation of convective drying of grapes. Journal of Food Engineering, 55(4), 323-330. https://doi.org/10.1016/S0260-8774(02)00109-7
10. Bai, J., Wang, J., Xiao, H., Ju, H., Liu, Y., & Gao, Z. (2013). Weibull distribution for modeling drying of grapes and its application. Transactions of the Chinese Society of Agricultural Engineering, 29(16), 278-285.
11. Blikra, M. , Skipnes, D., & Feyissa, A. H. (2019). Model for heat and mass transport during cooking of cod loin in a convection oven. Food Control, 102, 29-37. https://doi.org/10.1016/j.foodcont.2019.03.001
12. Buzrul, S. (2022). Reassessment of Thin-Layer Drying Models for Foods: A Critical Short Communication. Processes, 10(1), 118. https://doi.org/10.3390/pr10010118
13. Ceylan, İ. (2008). Determination of drying characteristics of timber by Using artificial neural networks and mathematical models. Drying Technology, 26(12), 1469-1476. https://doi.org/10.1080/07373930802412132
14. Clemente, G., Bon, J., Sanjuan, N., & Mulet, A. (2009). Determination of Shrinkage Function for Pork Meat Drying. Drying Technology, 27(1), 143-148. https://doi.org/10.1080/07373930802566051
15. Corzo, O., & Bracho, N. (2008). Application of Weibull distribution model to describe the vacuum pulse osmotic dehydration of sardine sheets. Lwt- Food Science and Technology, 41(6), 1108-1115. https://doi.org/10.1016/j.lwt.2007.06.018
16. Corzo, O., Bracho, N., Pereira, A. & Vásquez, A. (2008). Weibull distribution for modeling air drying of coroba slices. Lwt- Food Science and Technology, 41(10), 2023-2028. https://doi.org/10.1016/j.lwt.2008.01.002
17. Costa, M. V., Silva, A. K. N., Rodrigues, P. R., Silva, L. H. M., & Cruz Rodrigues, A. M. (2018). Prediction of moisture transfer parameters for convective drying of shrimp at different pretreatments. Food Science and Technology, 38(4), 612-618. https://doi.org/10.1590/fst.31517
18. Dai, J. W., Wang, J., Ren, L., Liu, Y. W., & Zhang, L. H. (2018). Mathematical model of potato slices under process-based temperature and humidity integration control of tilted tray air impingement drying. In: Proceedings of 7^th International Conference on Energy and Environmental Protection (ICEEP 2018). 14-15 July. Shenzhen, China. pp. 50-56. https://doi.org/10.2991/iceep-18.2018.9
19. Doymaz, İ. (2008). Convective drying kinetics of strawberry. Chemical Engineering and Processing: Process Intensification, 47(5), 914-919. https://doi.org/10.1016/j.cep.2007.02.003
20. Erşan, A. C., & Tugrul, N. (2020). The drying kinetics and characteristics of Shrimp dried by conventional methods. Chemical Industry and Chemical Engineering Quarterly, 27(4), 319-328. https://doi.org/10.2298/ciceq201114050e
21. Falade, K. O., & Solademi, O. J. (2010). Modelling of air drying of fresh and blanched sweet potato slices. International Journal of Food Science & Technology, 45(2), 278-288. https://doi.org/10.1111/j.1365-2621.2009.02133.x
22. Farhang, A., Hosainpour, A., Darvishi, H., & Nargesi, F. (2011). Shrimp drying characterizes undergoing microwave treatment. Journal of Agricultural Science, 3(2), 157-164. https://doi.org/10.5539/jas.v3n2p157
23. Gaikwad, P. S., Sunil, C. K., Negi, A., & Pare, A. (2022). Effect of microwave assisted hot-air drying temperatures on drying kinetics of dried black gram papad (Indian snack food) Drying characteristics of black gram papad. Applied Food Research, 2(2022). https://doi.org/10.1016/j.afres.2022.100144
24. Gely, M. C., & Santalla, E. M. (2007). Moisture diffusivity in quinoa (Chenopodium quinoa) seeds: Effect of air temperature and initial moisture content of seeds. Journal of Food Engineering, 78(3), 1029-1033. https://doi.org/10.1016/j.jfoodeng.2005.12.015
25. Giovanelli, G., Zanoni, V., Lavelli, V., & Nani, R. (2002). Water sorption, drying and antioxidant properties of tomato products. Journal of Food Engineering, 52(2), 135-141. https://doi.org/10.1016/S0260-8774(01)00095-4
26. Guiné, R. d. P. F. (2006). Influence of drying method on density and porosity of pears. Food and Bioproducts Processing, 84(3), 179-185. https://doi.org/10.1205/fbp.05106
27. Hashemi, G., Mowla, D., & Kazemeini, M. (2009). Moisture diffusivity and shrinkage of broad beans during bulk drying in an inert medium fluidized bed dryer assisted by dielectric heating. Journal of Food Engineering, 92(3), 331-338. https://doi.org/10.1016/j.jfoodeng.2008.12.004
28. Hatamipour, M. S., & Mowla, D. (2002). Shrinkage of carrots during drying in an inert medium fluidized bed. Journal of Food Engineering, 55(3), 247-252. https://doi.org/10.1016/S0260-8774(02)00082-1
29. Kaminski, E., Szarycz, M., & Janowicz, L. (1996) The kinetics of drying sliced apples in the conditions of natural convection. In: Proceedings of 7^th Seminar on Properties of water in foods. Warsaw Agricultural University. Warsaw. Poland. pp. 24-34.
30. Kassama, L. S., & Ngadi, M. O. (2004). Pore development in chicken meat during deep-fat frying. LWT Food Science and Technology, 37(8), 841-847. https://doi.org/10.1016/j.lwt.2004.03.010
31. Kassama, L. S., & Ngadi, M. O. (2016). Shrinkage and density change of de-boned chicken breast during deep-fat frying. Food and Nutrition Sciences, 2016(7), 895-905. https://doi.org/10.4236/fns.2016.710089
32. Komolafe, C. A., Oluwaleye, I. O., Adejumo, A. O. D., Waheed, M. A., & Kuye, S. I. (2018). Determination of moisture diffusivity and activation energy in the convective drying of fish. International Journal of Heat and Technology, 36(4), 1262-1267. https://doi.org/10.18280/ijht.360414
33. Ling, J., Teng, Z., & Lin, H. (2018). Improved method for prediction of milled rice moisture content based on Weibull distribution. International Journal of Agricultural & Biological Engineering, 11(3), 159-165. https://doi.org/10.25165/j.ijabe.20181103.3429
34. Manjeet, S. C. (1984). Evaluation of selected mathematical models for describing Thin-Layer drying of In-Shell Pecans. Transactions of the ASAE, 27(2), 610-615. https://doi.org/10.13031/2013.32837
35. Mayor, L., & Sereno, A. M. (2004). Modelling shrinkage during convective drying of food materials: a review. Journal of Food Engineering, 61(3), 373-386. https://doi.org/10.1016/S0260-8774(03)00144-4
36. Mohebi, M., Akbarzadeh, M. R., Shahidi, F., & Porshahabi, M. R. (2007). Investigation of the possibility of using the visual machine and artificial neural network in predicting the moisture content of dried shrimp. In proceeding of 4^th Iranian Machine Vision and Image Processing Conference. 14-15 Feb. Ferdowsi university of Mashhad. Mashhad. Iran. (in Persian).
37. Moreira, R., Figueiredo, A., & Sereno, A. (2000). Shrinkage of apple disks during drying by warm air convection and freeze drying. Drying Technology, 18(1-2), 279-294. https://doi.org/10.1080/07373930008917704
38. Mulet, A., Garcia Reverter, J., Bon, J., & Berna, A. (2000). Effect of shape on potato and cauliflower shrinkage during drying. Drying Technology, 18(6), 1201-1219. https://doi.org/10.1080/07373930008917772
39. Murali, S., Aniesrani Delfiya, D. S., Sathish Kumar, K., Kumar, L. R. G., Ezhil Nilavan, S., Amulya, P. R., Krishnan, V. S., Alfiya P. V., & Samuel M. P. (2021) Mathematical modeling of drying kinetics and quality characteristics of shrimps dried under a Solar–LPG hybrid dryer. Journal of Aquatic Food Product Technology, 30(5), 561-578. https://doi.org/10.1080/10498850.2021.1901814
40. Nguyen, M. P., Ngo, T. T., & Le, T. D. (2019). Experimental and numerical investigation of transport phenomena and kinetics for convective shrimp drying. Case Studies in Thermal Engineering, 14(2019), 100465. https://doi.org/10.1016/j.csite.2019.100465
41. Niamnuy, C., Devahastin, S., Soponronnarit, S., & Raghavan, V. G. S. (2008). Modeling coupled transport phenomena and mechanical deformation of shrimp during drying in a jet spouted bed dryer. Chemical Engineering Science, 63(22), 5503-5512. https://doi.org/10.1016/j.ces.2008.07.031
42. Ochoa, M. R., Kesseler, A. G., Pirone, B. N., Marquez, C. A., & DeMichelis, A. (2002). Volume and area shrinkage of whole sour cherry fruits (Prunus Cerasus) during dehydration. Drying Technology, 20(1), 147-156. https://doi.org/10.1081/DRT-120001371
43. Pabis, S., Jayas, D., & Cenkowski, S. (1998). Grain drying: Theory and practice. New York, United States: John Wiley and Sons.
44. Park, K. J. (1998). Diffusional model with and without shrinkage during salted fish muscle drying. Drying Technology, 16(3-5), 889-905. https://doi.org/10.1080/07373939808917443
45. Porciuncula, B. D. A., Zotarelli, M. F., Carciofi, B. A. M., & Laurindo, J. B. (2013). Determining the effective diffusion coefficient of water in banana (Prata variety) during osmotic dehydration and its use in predictive models. Journal of Food Engineering, 119(3), 490-496. https://doi.org/10.1016/j.jfoodeng.2013.06.011
46. Queiroz, M. R., & Nebra, S. A. (2001). Theoretical and experimental analysis of the drying kinetics of bananas. Journal of Food Engineering, 47(2), 127-132. https://doi.org/10.1016/S0260-8774(00)00108-4
47. Radhakrishnan, S. (1997). Measurement of thermal properties of seafood. Sc. dissertation. Virginia Polytechnic Institute and State University. Blacksburg, Virginia.
48. Reyes, A., Alvarez, P. I., & Marquardt, F. H. (2002). Drying of carrots in a fluidized bed. I. Effects of drying conditions and modelling. Drying Technology, 20(7), 1463-1483. https://doi.org/10.1081/DRT-120005862
49. Ruiz-López, I. I., & García-Alvarado, M. A. (2007). Analytical solution for food-drying kinetics considering shrinkage and variable diffusivity. Journal of Food Engineering, 79(1), 208-216. https://doi.org/10.1016/j.jfoodeng.2006.01.051
50. Shafiur Rahman, M., & Driscoll, R. H. (1994). Density of fresh and frozen seafood. Journal of Food Process Engineering, 17(2), 121-140. https://doi.org/10.1111/j.1745-4530.1994.tb00331.x
51. Sharaf-Elden, Y. I., Blaisdell, J. L., & Hamdy, M. Y. (1984). A model for ear corn drying. Transactions of the ASAE, 23(5), 1261-1265. https://doi.org/10.13031/2013.34757
52. Suvarnakuta, P., Devahastin, S., & Mujumdar, A. S. (2007). A mathematical model for low-pressure superheated steam drying of a biomaterial. Chemical Engineering and Processing: Process Intensification, 46(7), 675-683. https://doi.org/10.1016/j.cep.2006.09.002
53. Tirawanichakul, S., Na Phatthalung, W., & Tirawanichakul, Y. (2011). Drying Strategy of Shrimp using Hot Air Convection and Hybrid Infrared Radiation/Hot Air Convection. Walailak Journal of Science and Technology (WJST), 5(1), 77-100.
54. Toğrul, İ. T., & Pehlivan, D. (2002). Mathematical modelling of solar drying of apricots in thin layers. Journal of Food Engineering, 55(3), 209-216. https://doi.org/10.1016/S0260-8774(02)00065-1
55. Trujillo, F. J., Wiangkaew, C., & Tuan Pham, Q. (2007). Drying modeling and water diffusivity in beef meat. Journal of Food Engineering, 78, 74-85. https://doi.org/10.1016/j.jfoodeng.2005.09.010
56. Vazquez, G., Chenlo, F., Moreira, R., & Costoyas, A. (1999). The dehydration of garlic. 1. Desorption isotherms and modelling of drying kinetics. Drying Technology, 17(6), 1095-1108. https://doi.org/10.1080/07373939908917596
57. Wang, J., Tang, J., Rasco, B., Sablani, S. S., Ovissipour, M., & Qu, Z. (2018). Kinetics of Quality Changes of Shrimp (Litopenaeus setiferus) During Pasteurization. Food and Bioprocess Technolgy, 11, 1027-1038. https://doi.org/10.1007/s11947-018-2073-x
58. Wisaiprom, N., Kasayapanand, N., Pratinthong, N., Songprakorp, R., Thepa, S., & Deeto, S. (2018). The study of shrimp drying by greenhouse drying combined with low humidity air. International Journal of Smart Grid and Clean Energy, 7(4), 303-313. https://doi.org/10.12720/sgce.7.4.303-313
59. Yi, X. K., Wu, W. F., Zhang, Y. Q., Li, J. X., & Luo, H. P. (2012). Thin-Layer drying characteristics and modeling of Chinese Jujubes. Mathematical Problems in Engineering, 2012, 386214. https://doi.org/10.1155/2012/386214
60. Zielinska, M., & Markowski, M. (2007). Drying behavior of carrots dried in a spout–fluidized bed dryer. Drying Technology, 25(1), 261-270. https://doi.org/10.1080/07373930601161138