{"title":"基于人工神经网络模型的海产品中假单胞菌生长速率预测","authors":"I. Y. Genç","doi":"10.1080/10498850.2023.2219675","DOIUrl":null,"url":null,"abstract":"ABSTRACT The aim of this study is to predict the growth rate (µmax) of Pseudomonas sp. in seafood under different temperature -2 - 25°C and modified atmosphere packaging (MAP) conditions. At total 52 µmax were compiled from the literature to develop and 68 different µmax values to validate the ANN model. For the development of ANN model different transfer functions were applied and based on the bias (Bf) (0.91) and accuracy factors (Af) (1.60) 3 layers 10 neurons with purelin transfer function was assumed to be best topology to predict the µmax of Pseudomonas sp. in seafood.","PeriodicalId":15091,"journal":{"name":"Journal of Aquatic Food Product Technology","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prediction of the Growth Rates of Pseudomonas sp. in Seafood Based on Artificial Neural Network (ANN) Model\",\"authors\":\"I. Y. Genç\",\"doi\":\"10.1080/10498850.2023.2219675\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The aim of this study is to predict the growth rate (µmax) of Pseudomonas sp. in seafood under different temperature -2 - 25°C and modified atmosphere packaging (MAP) conditions. At total 52 µmax were compiled from the literature to develop and 68 different µmax values to validate the ANN model. For the development of ANN model different transfer functions were applied and based on the bias (Bf) (0.91) and accuracy factors (Af) (1.60) 3 layers 10 neurons with purelin transfer function was assumed to be best topology to predict the µmax of Pseudomonas sp. in seafood.\",\"PeriodicalId\":15091,\"journal\":{\"name\":\"Journal of Aquatic Food Product Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Aquatic Food Product Technology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1080/10498850.2023.2219675\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Aquatic Food Product Technology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/10498850.2023.2219675","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Prediction of the Growth Rates of Pseudomonas sp. in Seafood Based on Artificial Neural Network (ANN) Model
ABSTRACT The aim of this study is to predict the growth rate (µmax) of Pseudomonas sp. in seafood under different temperature -2 - 25°C and modified atmosphere packaging (MAP) conditions. At total 52 µmax were compiled from the literature to develop and 68 different µmax values to validate the ANN model. For the development of ANN model different transfer functions were applied and based on the bias (Bf) (0.91) and accuracy factors (Af) (1.60) 3 layers 10 neurons with purelin transfer function was assumed to be best topology to predict the µmax of Pseudomonas sp. in seafood.
期刊介绍:
The Journal of Aquatic Food Product Technology publishes research papers, short communications, and review articles concerning the application of science and technology and biotechnology to all aspects of research, innovation, production, and distribution of food products originating from the marine and freshwater bodies of the world. The journal features articles on various aspects of basic and applied science in topics related to:
-harvesting and handling practices-
processing with traditional and new technologies-
refrigeration and freezing-
packaging and storage-
safety and traceability-
byproduct utilization-
consumer attitudes toward aquatic food.
The Journal also covers basic studies of aquatic products as related to food chemistry, microbiology, and engineering, such as all flora and fauna from aquatic environs, including seaweeds and underutilized species used directly for human consumption or alternative uses. Special features in the journal include guest editorials by specialists in their fields and book reviews covering a wide range of topics.