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Changes of Volatile Flavor Compounds in Chicken Soup during Stewing Process of Yellow-feathered Chicken Using Multiple Technologies Combined with PCA-BP Neural Network
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Hongxia LÜ1, Yongrui WANG2, *
Science and Technology of Food Industry | 2026, 47(18) : 306 - 315
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Science and Technology of Food Industry | 2026, 47(18): 306-315
• Modern Analysis and Intelligent Detection •
Changes of Volatile Flavor Compounds in Chicken Soup during Stewing Process of Yellow-feathered Chicken Using Multiple Technologies Combined with PCA-BP Neural Network
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Hongxia LÜ1, Yongrui WANG2, *
Affiliations
  • 1Medical College, Xi'an International University, Xi'an 710077, China
  • 2College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
Published: 2026-09-15 doi: 10.13386/j.issn1002-0306.2025070092
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To investigate the changes in volatile flavor compounds in chicken soup during the stewing process of yellow-feathered chicken, headspace solid phase microextraction (HS-SPME)-gas chromatography-mass spectrometry (GC-MS), electronic nose, and electronic tongue combined with PCA-BP neural network were used to study chicken soup samples at different cooking times (0.5, 1.0, 1.5, 2.0 and 2.5 h). The results showed that as the stewing time increased, the color of the chicken soup became darker. A total of 35 volatile compounds were identified through GC-MS, primarily consisting of aldehydes and alcohols. The total content of volatile flavor compounds increased first and then decreased, and reached a peak after stewing for 2.0 h. GC-MS combined with OAVs value method identified 13 key volatile compounds, including 1-hexanol, 1-octene-3-ol, (E,E)-2,4-decadiena,l (E,E)-2,4-nonadienal, (Z)-2-heptenal, (E)-2-nonenal, (E)-2-octenal, (E)-2-decenal, 2-pentylfuran, heptanal, hexanal, nonanal and octanal. Based on VIP values, 19 characteristic volatile compounds were screened, which could be used to distinguish 5 chicken soup samples. Significant differences in the electronic nose and electronic tongue of chicken soup samples with different stewing times, and these samples could be effectively distinguished by PCA and cluster analysis. The electronic tongue PCA-BP neural network model could accurately predict the stewing time of chicken soup samples and the linear relationship between the true value and the predicted value was good (R2=0.9998). The chicken soup stewed for 2.0 h showed significantly high scores for flavor, color, appearance, and overall acceptability. In conclusion, the optimal stewing time for chicken soup was 2.0 h. The results can be used as the basis for the flavor of the original chicken soup and pave the way for subsequent high-quality Chinese herbal chicken soup research.

chicken soup  /  stewing process  /  GC-MS  /  E-tongue  /  E-nose  /  PCA-BP neural network  /  volatile flavor compounds  /  sensory analysis
吕虹霞, 王永瑞. 多技术结合PCA-BP神经网络研究黄羽鸡炖煮过程中鸡汤挥发性风味物质变化. 食品工业科技, 2026 , 47 (18) : 306 -315 . DOI: 10.13386/j.issn1002-0306.2025070092
Hongxia LÜ, Yongrui WANG. Changes of Volatile Flavor Compounds in Chicken Soup during Stewing Process of Yellow-feathered Chicken Using Multiple Technologies Combined with PCA-BP Neural Network[J]. Science and Technology of Food Industry, 2026 , 47 (18) : 306 -315 . DOI: 10.13386/j.issn1002-0306.2025070092
Year 2026 volume 47 Issue 18
135
56
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doi: 10.13386/j.issn1002-0306.2025070092
  • Receive Date:2025-07-08
  • Online Date:2026-10-24
  • Published:2026-09-15
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  • Received:2025-07-08
Affiliations
    1Medical College, Xi'an International University, Xi'an 710077, China
    2College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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