https://doi.org/10.4081/jae.2024.1611
Design and experiments of an integrated device for shrimp orientation and decapitation
Published: 16 October 2024
Abstract Views: 258
PDF: 133
HTML: 4
HTML: 4
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
To realize the automatic orientation and decapitation of shrimp, an integrated device for shrimp orientation and decapitation was designed based on the shape and size characteristics of shrimp, which was mainly composed of oriented rollers, shrimp pushing boards, adaptive clamping claw and knife for the decapitation of shrimp. Three kinds of shrimp of small, medium, and large size were selected. Taking the speed of the shrimp pushing boards, the horizontal speed of the adaptive clamping claw, the rotational speed of oriented rollers and the radius of the oriented rollers as the test factors, and the success rate of the shrimp decapitation as the index, the single factor test and the orthogonal test were carried out to study the effect of each factor on the shrimp decapitation, and then the main parameters of the device were optimized. The results showed that the optimal parameter combinations of the three sizes of shrimp were the speed of shrimp pushing plates of 60mm/s, the horizontal speed of adaptive clamping claw of 70mm/s, the rotational speed of oriented rollers of 60r/min, and the radius of oriented rollers of 20mm. Under the optimal combination of parameters, the device has the highest decapitation success rate and the success rate of shrimp decapitation was 91.5% for small shrimp, 94.6% for medium shrimp, and 92.8% for large shrimp, the decapitation speed was 36pcs/min for small shrimp, 38 pcs/min for medium shrimp, and 37 pcs/min for large shrimp. Therefore, the feasibility of the device design is verified.
Azarmdel, H., Mohtasebi, S.S., Jafari, A., Muñoz, A.R. 2019. Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision. Comput. Electron. Agr. 162:613-629.
DOI: https://doi.org/10.1016/j.compag.2019.05.005
Bibwe, B.R., Hiregoudar, S., Nidoni, U.R., Anantachar, M., Shrestha, B. 2013. Development of meat-bone separator for small scale fish processing. J. Food Sci. Technol. 50:763-769.
DOI: https://doi.org/10.1007/s13197-011-0381-5
Booman, A., Márquez, A., Parin, M.A., Zugarramurdi, A. 2010. Design and testing of a fish bone separator machine. J. Food Eng. 1003:474-479.
DOI: https://doi.org/10.1016/j.jfoodeng.2010.04.034
Chen, Q., Shen, J., Fu, R., Tan, J., Zhang, J. 2012. Research on the mechanical deheading method of typical small marine fish. Fish. Modern. 395:38-42.
Chen, Y., Jiao, M., Peng, X., Xu, C., Cai, L., Hu, Z., Ma, M. 2024. Study on positioning and detection of crayfish body parts based on machine vision. J. Food Meas. Charact. 18:4375-4387.
DOI: https://doi.org/10.1007/s11694-024-02500-2
Chen, Y., Mitra, A., Rahimnejad, S., Chi, S., Kumar, V., Tan, B., et al. 2024. Retrospect of fish meal substitution in Pacific white shrimp (Litopenaeus vannamei) feed: Alternatives, limitations and future prospects. Rev. Aquacult. 161:382-409.
DOI: https://doi.org/10.1111/raq.12843
Cheng, X., Li, M., Leng, X., Wen, H., Wu, F., Yu, L., et al. 2021. Creatine improves the flesh quality of Pacific white shrimp (Litopenaeus vannamei) reared in freshwater. Food Chem. 354:129498.
DOI: https://doi.org/10.1016/j.foodchem.2021.129498
Dang, T.T., Gringer, N., Jessen, F., Olsen, K., Bøknæs, N., Nielsen, P.L., Orlien, V. 2018. Emerging and potential technologies for facilitating shrimp peeling: A review. Innov. Food Sci. Emerg. 45:228-240.
DOI: https://doi.org/10.1016/j.ifset.2017.10.017
Dowgiallo, A. 2018. The Effect of cutting and fish-orientation systems on the deheading yield of carp. Int. J. Food Sci. Technol. 43:1688-1692.
DOI: https://doi.org/10.1111/j.1365-2621.2008.01750.x
Liu, J., Zhang, F., Wan, P., Tan, H. 2017. Freshwater fish pneumatic machinery to head-cutting method research. Food Machin. 331:87-92.
DOI: https://doi.org/10.1201/9781315375120-15
Liu, W., Lyu, J., Wu, D., Cao, Y., Ma, Q., Lu, Y., Zhang, X. 2022. Cutting techniques in the fish industry: a critical review. Foods 1120:3206.
DOI: https://doi.org/10.3390/foods11203206
Liu, Z., Liu, Q., Zhang, D., Wei, S., Sun, Q., Xia, Q., et al. 2021. Comparison of the proximate composition and nutritional profile of byproducts and edible parts of five species of shrimp. Foods 1011:2603.
DOI: https://doi.org/10.3390/foods10112603
Mesa, M.D., Gil, F., Olmedo, P., Gil, A. 2021. Nutritional importance of selected fresh fishes, shrimps and mollusks to meet compliance with nutritional guidelines of n-3 LC-PUFA intake in Spain. Nutrients 132:465.
DOI: https://doi.org/10.3390/nu13020465
N’Souvi, K., Sun, C., Che, B., Vodounon, A. 2024. Shrimp industry in China: overview of the trends in the production, imports and exports during the last two decades, challenges, and outlook. Front. Sustain. Food Syst. 7:1287034.
DOI: https://doi.org/10.3389/fsufs.2023.1287034
Nirmal, N.P., Santivarangkna, C., Rajput, M.S., Benjakul, S. 2020. Trends in shrimp processing waste utilization: An industrial prospective. Trends Food Sci. Technol. 103:20-35.
DOI: https://doi.org/10.1016/j.tifs.2020.07.001
Okpala, C.O.R., Bono, G. 2016. Investigating the biometric and physicochemical characteristics of freshly harvested Pacific white shrimp (Litopenaeus vannamei): a comparative approach. J. Sci. Food Agr. 964:1231-1240.
DOI: https://doi.org/10.1002/jsfa.7211
Omar, F.K., De Silva, C.W. 2000. Optimal portion control of natural objects with application in automated cannery processing of fish. J. Food Eng. 461:31-41.
DOI: https://doi.org/10.1016/S0260-8774(00)00068-6
Wang, Q., Tian, Y., Wang, J., Li, J.Y., He, W., Craig, N.J. 2023. Assessing pathways of heavy metal accumulation in aquaculture shrimp and their introductions into the pond environment based on a dynamic model and mass balance principle. Sci. Total Environ. 881:163164.
DOI: https://doi.org/10.1016/j.scitotenv.2023.163164
Wang, Y., Zhang, M., Mujumdar, A. S. 2011. Trends in processing technologies for dried aquatic products. Drying Technol. 294:382-394.
DOI: https://doi.org/10.1080/07373937.2011.551624
Zhang, D., Lillywhite, K.D., Lee, D.J., Tippetts, B.J. 2014. Automatic shrimp shape grading using evolution constructed features. Comput. Electron. Agr. 100:116-122.
DOI: https://doi.org/10.1016/j.compag.2013.11.009
Zhang, X., Wang, L., Yi, J., Wang, Z., Wang, J. 2017. Design and experiment of shrimp backside cutting machine formed by belt clamping and conveying. Trans. Chin. Soc. Agr. Eng. 3320:284-291.
Zhao, Z. 2005. Mechanized processing of dace. Fish. Modern. 337:36–37.
How to Cite
Ruan, P. (2024) “Design and experiments of an integrated device for shrimp orientation and decapitation”, Journal of Agricultural Engineering, 55(4). doi: 10.4081/jae.2024.1611.
Copyright (c) 2024 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Gabriele Mattachini, Elisabetta Riva, Francesca Perazzolo, Ezio Naldi, Giorgio Provolo, Monitoring feeding behaviour of dairy cows using accelerometers , Journal of Agricultural Engineering: Vol. 47 No. 1 (2016)
- Wenjun Wang, Sihao Zhang, Jingyu Li, Pengfei Zhang, Yulong Chen, Effects of the twin-row planter with subsoiling on soybean growth and yield in northern China , Journal of Agricultural Engineering: Vol. 53 No. 3 (2022)
- Ossama M. M. Abdelwahab, Ronald L. Bingner, Fabio Milillo, Francesco Gentile, Effectiveness of alternative management scenarios on the sediment load in a Mediterranean agricultural watershed , Journal of Agricultural Engineering: Vol. 45 No. 3 (2014)
- Alessandro Parenti, Piernicola Masella, Lorenzo Guerrini, Antonio Guiso, Paolo Spugnoli, Energetic and economic viability of olive stone recovery as a renewable energy source: a Southern Italy case study , Journal of Agricultural Engineering: Vol. 45 No. 2 (2014)
- Simone Pascuzzi, Giovanni Russo, Giacomo Scarascia-Mugnozza, Giuseppe Verdiani, Sanitary risk analysis for farm workers exposed to environmental pollutants , Journal of Agricultural Engineering: Vol. 43 No. 4 (2012)
- Vincenzo Bagarello, Andrea De Santis, Giuseppe Giordano, Massimo Iovino, Source shape and data analysis procedure effects on hydraulic conductivity of a sandy-loam soil determined by ponding infiltration runs , Journal of Agricultural Engineering: Vol. 48 No. 2 (2017)
- Antonio Guiso, Alessandro Parenti, Piernicola Masella, Lorenzo Guerrini, Fabio Baldi, Paolo Spugnoli, Environmental impact assessment of three packages for high-quality extra-virgin olive oil , Journal of Agricultural Engineering: Vol. 47 No. 4 (2016)
- Alvaro Marucci, Danilo Monarca, Andrea Colantoni, Enio Campiglia, Andrea Cappuccini, Analysis of the internal shading in a photovoltaic greenhouse tunnel , Journal of Agricultural Engineering: Vol. 48 No. 3 (2017)
- Ren Hiraoka, Yuya Aoyagi, Kazuki Kobayashi, Automatic travelling of agricultural support robot for a fruit farm. Verification of effectiveness of real-time kinematic-global navigation satellite system and developed a simulator for specification design , Journal of Agricultural Engineering: Vol. 54 No. 1 (2023)
- Eliseo Roma, Pietro Catania, Mariangela Vallone, Santo Orlando, Unmanned aerial vehicle and proximal sensing of vegetation indices in olive tree (Olea europaea) , Journal of Agricultural Engineering: Vol. 54 No. 3 (2023)
<< < 15 16 17 18 19 20 21 22 23 24 > >>
You may also start an advanced similarity search for this article.
