Non-Destructive Detection of Chicken Freshness Based on Electronic Nose Technology and Transfer Learning

• Published in: Agriculture (Basel) Vol. 13; no. 2; p. 496
• Main Authors: Xiong, Yunwei, Li, Yuhua, Wang, Chenyang, Shi, Hanqing, Wang, Sunyuan, Yong, Cheng, Gong, Yan, Zhang, Wentian, Zou, Xiuguo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2023
• Subjects: agriculture; Artificial neural networks; breasts; chicken freshness detection; Chickens; Classification; Conversion; convolutional neural network; Data processing; Deep learning; electronic nose; Electronic noses; Feature extraction; Freshness; Gases; Learning algorithms; Machine learning; Meat; Methods; Neural networks; Nondestructive testing; Nose; Odor; Odors; Poultry; Sensors; Support vector machines; Three dimensional printing; time series analysis; Transfer learning; VOCs; Volatile organic compounds

As a non-destructive detection method, an electronic nose can be used to assess the freshness of meats by collecting and analyzing their odor information. Deep learning can automatically extract features and uncover potential patterns in data, minimizing the influence of subjective factors such as s...