Development of a comprehensive classification model for determining the storage day of frigate tuna (Auxis thazard) for freshness evaluation using a portable electronic nose

被引：2

作者：

Madhubhashini, M. Nerandi ^{[1
]}

Liyanage, Chamara P. ^{[1
]}

Alahakoon, Amali U. ^{[2
]}

Liyanage, Rumesh Prasanga ^{[2
]}

机构：

[1] Univ Sri Jayewardenepura, Fac Technol, Dept Informat & Commun Technol, Nugegoda 10250, Sri Lanka

[2] Univ Sri Jayewardenepura, Fac Technol, Dept Biosyst Technol, Nugegoda 10250, Sri Lanka

来源：

INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY | 2024年 / 59卷 / 07期

关键词：

Electronic nose; fish freshness; frigate tuna; random forest; sensors; support vector machine;

D O I：

10.1111/ijfs.17189

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

Ensuring the freshness of fish is essential to guaranteeing safer products for consumers. A classification model was developed using the PEN3 electronic nose to predict fish freshness with its storage day. Frigate tuna (Auxis thazard) was used for odour sampling along with the total volatile base nitrogen (TVB-N), at 4 degrees C for 14 days every other day. Random forest and support vector machine (SVM) were performed to develop freshness classification models based on PEN3 data and 100% and 99.8% accuracies were obtained, respectively, in distinguishing the eight storage day classes. The PEN3 sensors including W2S, W1S, W1W, W3S, and W6S were identified as key sensors for fish freshness. TVB-N analysis advances the freshness prediction of e-nose and three freshness levels were identified as 'Fresh', applicable from the 0th to the 6th day; 'Moderately fresh', lasting from the 7th to the 9th day; and 'Unsuitable for consumption', applicable from the 10th day onwards.

引用

页码：4672 / 4679

页数：8