文献类型：期刊文献

英文题名：Innovations in seafood freshness quality: Non-destructive detection of freshness in Litopenaeus vannamei using the YOLO-shrimp model

作者：Hou, Mingxin[1,2];Zhong, Xiaowen[3];Zheng, Ouyang[3];Sun, Qinxiu[3];Liu, Shucheng[3];Liu, Mingxin[2,4]

机构：[1]Guangdong Ocean Univ, Sch Mech Engn, Zhanjiang 524088, Guangdong, Peoples R China;[2]Guangdong Ocean Univ, Guangdong Prov Key Lab Intelligent Equipment South, Zhanjiang 524088, Peoples R China;[3]Guangdong Ocean Univ, Coll Food Sci & Technol, Zhanjiang 524088, Guangdong, Peoples R China;[4]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Guangdong, Peoples R China

年份：2025

卷号：463

外文期刊名：FOOD CHEMISTRY

收录：SCI-EXPANDED(收录号：WOS:001316000000001)、、EI(收录号：20243817045831)、Scopus(收录号：2-s2.0-85203635657)、WOS

基金：The authors would like to thank the reviewers and editors for their time to help improve this paper. This research was supported in part by the Natural Science Foundation of China (62171143) , the Special Fund for Scientific and Technological Innovation Strategy of Guangdong Province (2022A05036) , the Fund of Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching (2023B1212030003) , Guangdong Higher Education Association's "14th Five Year Plan" 2024 Higher Education Research Project (47) and Special Fund for Basic Research Business Expenses of the Chinese Academy of Tropical Agricultural Sciences (1630132024004) .

语种：英文

外文关键词：Litopenaeus vannamei; Freshness detection; YOLO shrimp model; Non-destructive detection; Food safety technology

外文摘要：The relationship between freshness changes and visual images of Litopenaeus vannamei was established based on Sensory Evaluation, Total Volatile Base Nitrogen (TVB-N), Total Viable Count (TVC), and Gray Value during storage at 4 degrees C. A non-destructive detection system using the advanced YOLO(You Only Look Once)-Shrimp model was developed to evaluate shrimp freshness. The results revealed a gradual increase in freshness indices over time, with the gray value showing strong positive correlations with TVB-N and TVC (0.88 and 0.81). The advanced YOLO-Shrimp model demonstrated notable performance enhancements over the YOLOv8 model, as evidenced by a precision increase of 5.07 %, a recall improvement of 1.58 %, a 3.25 % rise in the F1 score, and a 2.84 % elevation in mAP50. This innovative approach offers substantial potential for enhancing food safety and quality control in the seafood industry.