Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm
Using Antarctic krill ( Euphausia superba ) as the research object, we optimized the process conditions for Antarctic krill sauce (AkS) by including three factors (salt addition, rock sugar addition, and the oil-to-material ratio) and sensory evaluation as response values. The data from the response...
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ftdoajarticles:oai:doaj.org/article:6378263b950441a297dfce470611719a 2024-09-30T14:26:54+00:00 Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm Hai Chi Zhiyu Fu Peng Wang Di Yu Lukai Zhao Long Li Yujun Liu Jie Zheng 2024-08-01T00:00:00Z https://doi.org/10.3390/app14167337 https://doaj.org/article/6378263b950441a297dfce470611719a EN eng MDPI AG https://www.mdpi.com/2076-3417/14/16/7337 https://doaj.org/toc/2076-3417 doi:10.3390/app14167337 2076-3417 https://doaj.org/article/6378263b950441a297dfce470611719a Applied Sciences, Vol 14, Iss 16, p 7337 (2024) Antarctic krill sauce optimized processing BP neural network genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 article 2024 ftdoajarticles https://doi.org/10.3390/app14167337 2024-09-02T15:34:38Z Using Antarctic krill ( Euphausia superba ) as the research object, we optimized the process conditions for Antarctic krill sauce (AkS) by including three factors (salt addition, rock sugar addition, and the oil-to-material ratio) and sensory evaluation as response values. The data from the response surface were fed into the back propagation (BP) neural network training, generating a model mapping the process conditions and sensory scores, which were subsequently combined with the genetic algorithm (GA) for global optimization to determine the optimal process for AkS preparation. The results revealed that the response surface model was well suited to the BP neural network training and prediction sets, with correlation values of 0.98 and 0.95, respectively. The fitting prediction effect was obvious for the sensory scoring results of the product. The parameters obtained from the GA’s global optimization search accord with the analytical results of the response surface. The findings demonstrated that combining a BP neural network with a GA can enhance the AkS preparation technique. Under optimal processing conditions, AkS has a high sensory score and protein and carbohydrate contents, moderate fat content, minimal fat oxidation, and non-detectable pathogens, indicating that the AkS in this study was nutritious and safe to consume. Article in Journal/Newspaper Antarc* Antarctic Antarctic Krill Euphausia superba Directory of Open Access Journals: DOAJ Articles Aks ENVELOPE(9.657,9.657,63.721,63.721) Antarctic Applied Sciences 14 16 7337 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Antarctic krill sauce optimized processing BP neural network genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
spellingShingle |
Antarctic krill sauce optimized processing BP neural network genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Hai Chi Zhiyu Fu Peng Wang Di Yu Lukai Zhao Long Li Yujun Liu Jie Zheng Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
topic_facet |
Antarctic krill sauce optimized processing BP neural network genetic algorithm Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
description |
Using Antarctic krill ( Euphausia superba ) as the research object, we optimized the process conditions for Antarctic krill sauce (AkS) by including three factors (salt addition, rock sugar addition, and the oil-to-material ratio) and sensory evaluation as response values. The data from the response surface were fed into the back propagation (BP) neural network training, generating a model mapping the process conditions and sensory scores, which were subsequently combined with the genetic algorithm (GA) for global optimization to determine the optimal process for AkS preparation. The results revealed that the response surface model was well suited to the BP neural network training and prediction sets, with correlation values of 0.98 and 0.95, respectively. The fitting prediction effect was obvious for the sensory scoring results of the product. The parameters obtained from the GA’s global optimization search accord with the analytical results of the response surface. The findings demonstrated that combining a BP neural network with a GA can enhance the AkS preparation technique. Under optimal processing conditions, AkS has a high sensory score and protein and carbohydrate contents, moderate fat content, minimal fat oxidation, and non-detectable pathogens, indicating that the AkS in this study was nutritious and safe to consume. |
format |
Article in Journal/Newspaper |
author |
Hai Chi Zhiyu Fu Peng Wang Di Yu Lukai Zhao Long Li Yujun Liu Jie Zheng |
author_facet |
Hai Chi Zhiyu Fu Peng Wang Di Yu Lukai Zhao Long Li Yujun Liu Jie Zheng |
author_sort |
Hai Chi |
title |
Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
title_short |
Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
title_full |
Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
title_fullStr |
Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
title_full_unstemmed |
Process Optimization for Antarctic Krill ( Euphausia superba ) Sauce Based on Back Propagation Neural Network Combined with Genetic Algorithm |
title_sort |
process optimization for antarctic krill ( euphausia superba ) sauce based on back propagation neural network combined with genetic algorithm |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/app14167337 https://doaj.org/article/6378263b950441a297dfce470611719a |
long_lat |
ENVELOPE(9.657,9.657,63.721,63.721) |
geographic |
Aks Antarctic |
geographic_facet |
Aks Antarctic |
genre |
Antarc* Antarctic Antarctic Krill Euphausia superba |
genre_facet |
Antarc* Antarctic Antarctic Krill Euphausia superba |
op_source |
Applied Sciences, Vol 14, Iss 16, p 7337 (2024) |
op_relation |
https://www.mdpi.com/2076-3417/14/16/7337 https://doaj.org/toc/2076-3417 doi:10.3390/app14167337 2076-3417 https://doaj.org/article/6378263b950441a297dfce470611719a |
op_doi |
https://doi.org/10.3390/app14167337 |
container_title |
Applied Sciences |
container_volume |
14 |
container_issue |
16 |
container_start_page |
7337 |
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1811633028976345088 |