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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Bibliographic Details
Published in:Applied Sciences
Main Authors: Hai Chi, Zhiyu Fu, Peng Wang, Di Yu, Lukai Zhao, Long Li, Yujun Liu, Jie Zheng
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2024
Subjects:
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
Antarc*
Antarctic
Antarctic Krill
Euphausia superba
Online Access:https://doi.org/10.3390/app14167337
https://doaj.org/article/6378263b950441a297dfce470611719a
Description
Summary: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.

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