Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness.
Food Chem
; 447: 138931, 2024 Jul 30.
Article
en En
| MEDLINE
| ID: mdl-38484548
ABSTRACT
Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fisetin, puerarin, daidzein) with a flexible film, forming a fluorescent sensor array. The fluorescent sensor array was used as a freshness indication label for packaged meat. Then, the images of the indication labels on the packaged meat under different freshness levels were collected by smartphones. A deep convolutional neural network (DCNN) model was built using the collected indicator label images and freshness labels as the dataset. Finally, the model was used to detect the freshness of meat samples, and the overall accuracy of the prediction model was as high as 97.1%. Unlike the TVB-N measurement, this method provides a nondestructive, real-time measurement of meat freshness.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Flavonoides
/
Aprendizaje Profundo
Idioma:
En
Revista:
Food Chem
Año:
2024
Tipo del documento:
Article