ARCHIVES
Year 2026 · Volume 6 · Issue 5
Review Article
Artificial Neural Network (ANN) Model for the Prediction of Shrimp Shelf Life During Cold Storage
Sudhi S1
Krishnaja Mk2
1 Assistant Professor, Santhigiri College of Computer Sciences, Vazhithala, Thodupuzha, Kerala, India. 2 Hsst Computer Applications (Guest Faculty), GVHSS East marady, Muvattupuzha, Kerala, India.
Published Online: September-October 2026
Pages: 374-380
Cite this article
↗ https://www.doi.org/10.59256/ijrtmr.20260605040
References
1. Bishop, Christopher M. 2006. Pattern Recognition and Machine Learning. Springer.
2. Breiman, Leo. 2001. “Random Forests.” Machine Learning 45 (1): 5–32.
3. Erkmen, Osman, and T. Faruk Bozoglu. 2016. Food Microbiology: Principles into Practice. John Wiley & Sons.
4. FAO. 2022. The State of World Fisheries and Aquaculture 2022: Towards Blue Transformation. Food and Agriculture Organization of the United Nations.
5. Fellows, P. J. 2017. Food Processing Technology: Principles and Practice. 4th ed. Woodhead Publishing.
6. Goodfellow, I., Bengio, Y., and Courville, A. 2016. Deep Learning. MIT Press.
7. Gram, Lone, and Hans H. Huss. 1996. “Microbiological Spoilage of Fish and Fish Products.” International Journal of Food Microbiology 33 (1): 121–137.
8. Huss, Hans H. 1995. Quality and Quality Changes in Fresh Fish. Food and Agriculture Organization of the United Nations.
9. James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2021. An Introduction to Statistical Learning. 2nd ed. Springer.
10. Jay, James M., Martin J. Loessner, and David A. Golden. 2005. Modern Food Microbiology. 7th ed. Springer.
11. M/s. SAI Marine Exports Pvt. Ltd.–Unit II Institutional Review Board. 2026. “Ethical Approval Letter, Approval No. 1930.” Visakhapatnam, India.
12. Montgomery, Douglas C. 2019. Design and Analysis of Experiments. 10th ed. John Wiley & Sons.
13. Nielsen, Michael A. 2015. Neural Networks and Deep Learning. Determination Press.
14. Pedregosa, Fabian, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, et al. 2011. “Scikit-Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–2830.
15. Rumelhart, D. E., Hinton, E., and Williams, R. J. 1986. “Learning Representations by Back-Propagating Errors.” Nature 323 (6088): 533–536.
16. Simpson, B. K., L. M. L. Nollet, F. Toldrá, S. Benjakul, G. Paliyath, and Y. H. Hui, eds. 2012. Seafood Quality Analysis. Wiley-Blackwell.
17. Taoukis, P. S., T. P. Labuza, and I. S. Saguy. 1997. “Kinetics of Food Deterioration and Shelf-Life Prediction.” In Quality in Frozen Food, edited by M. D. Erickson and Y.-C. Hung, 359–403. Springer.
18. Tokusoglu, Ö., and B. G. Swanson. 2014. Improving Seafood Products for the Consumer. CRC Press.
19. Venugopal, V. 2006. Seafood Processing: Adding Value through Quick Freezing, Retortable Packaging, and Cook-Chilling. CRC Press.
20. Zhang, Guoqiang, B. Eddy Patuwo, and Michael Y. Hu. 1998. “Forecasting with Artificial Neural Networks: The State of the Art.” International Journal of Forecasting 14 (1): 35–62.
21. Zou, J., Y. Han, and S. S. So. 2008. “Overview of Artificial Neural Networks.” Methods in Molecular Biology 458: 15–23.
2. Breiman, Leo. 2001. “Random Forests.” Machine Learning 45 (1): 5–32.
3. Erkmen, Osman, and T. Faruk Bozoglu. 2016. Food Microbiology: Principles into Practice. John Wiley & Sons.
4. FAO. 2022. The State of World Fisheries and Aquaculture 2022: Towards Blue Transformation. Food and Agriculture Organization of the United Nations.
5. Fellows, P. J. 2017. Food Processing Technology: Principles and Practice. 4th ed. Woodhead Publishing.
6. Goodfellow, I., Bengio, Y., and Courville, A. 2016. Deep Learning. MIT Press.
7. Gram, Lone, and Hans H. Huss. 1996. “Microbiological Spoilage of Fish and Fish Products.” International Journal of Food Microbiology 33 (1): 121–137.
8. Huss, Hans H. 1995. Quality and Quality Changes in Fresh Fish. Food and Agriculture Organization of the United Nations.
9. James, Gareth, Daniela Witten, Trevor Hastie, and Robert Tibshirani. 2021. An Introduction to Statistical Learning. 2nd ed. Springer.
10. Jay, James M., Martin J. Loessner, and David A. Golden. 2005. Modern Food Microbiology. 7th ed. Springer.
11. M/s. SAI Marine Exports Pvt. Ltd.–Unit II Institutional Review Board. 2026. “Ethical Approval Letter, Approval No. 1930.” Visakhapatnam, India.
12. Montgomery, Douglas C. 2019. Design and Analysis of Experiments. 10th ed. John Wiley & Sons.
13. Nielsen, Michael A. 2015. Neural Networks and Deep Learning. Determination Press.
14. Pedregosa, Fabian, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, et al. 2011. “Scikit-Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–2830.
15. Rumelhart, D. E., Hinton, E., and Williams, R. J. 1986. “Learning Representations by Back-Propagating Errors.” Nature 323 (6088): 533–536.
16. Simpson, B. K., L. M. L. Nollet, F. Toldrá, S. Benjakul, G. Paliyath, and Y. H. Hui, eds. 2012. Seafood Quality Analysis. Wiley-Blackwell.
17. Taoukis, P. S., T. P. Labuza, and I. S. Saguy. 1997. “Kinetics of Food Deterioration and Shelf-Life Prediction.” In Quality in Frozen Food, edited by M. D. Erickson and Y.-C. Hung, 359–403. Springer.
18. Tokusoglu, Ö., and B. G. Swanson. 2014. Improving Seafood Products for the Consumer. CRC Press.
19. Venugopal, V. 2006. Seafood Processing: Adding Value through Quick Freezing, Retortable Packaging, and Cook-Chilling. CRC Press.
20. Zhang, Guoqiang, B. Eddy Patuwo, and Michael Y. Hu. 1998. “Forecasting with Artificial Neural Networks: The State of the Art.” International Journal of Forecasting 14 (1): 35–62.
21. Zou, J., Y. Han, and S. S. So. 2008. “Overview of Artificial Neural Networks.” Methods in Molecular Biology 458: 15–23.
Related Articles
2026
A Strategic Framework for Depth-Dependent Hydroelectric Conversion along the Indian Coastline
2026
Reimagining Development in India: A Critical Analysis of the Viksit Bharat Vision
2026
AI-Enabled Image Description: Bridging the Gap for the Visually Impaired
2026
Perceived Occupational Risks of Emergency Medical Services Personnel
2026
Origin, Growth and recent Development of Integrated Reporting (IR): A theoretical Review
2026
Smart Hostel Management System
Share Article
Or copy link
https://www.ijrtmr.com/archives/artificial-neural-network-ann-model-for-the-prediction-of-shrimp-shelf-life-during-cold-storage
*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.