A Quality Evaluation Model for Salt-Baked Chicken Based on Principal Component Analysis
CHEN Chao, HAN Jiajing, LI Mingyu, YAO Jing, WANG Zhenyu, ZHANG Dequan, ZHANG Chunjiang
1. Integrated Laboratory of Processing Technology for Chinese Meat Dishes, Ministry of Agriculture and Rural Affairs, Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China; 2. Department of Food and Environmental Engineering, Heilongjiang Oriental University, Harbin 150066, China; 3. Chengdu National Agricultural Science & Technology Center, Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu 610213, China
Abstract：This study aimed at developing a comprehensive quality evaluation model for six typical types of salt-baked chicken in Guangdong. A total of 11 key flavor compounds were identified by headspace solid phase microextraction-gas chromatography-mass spectrometry based on odor activity values (OAVs). These flavor compounds and 12 physicochemical indicators such as protein, water, and fat contents were taken as independent variables to develop a comprehensive quality evaluation model for salt-baked chicken using principal component analysis (PCA). The results showed that the first four PCs cumulatively explained 80.38% of the total variation, indicating that these PCs could well represent the original information of the quality indexes of salt-baked chicken. The model results were significantly correlated with the sensory evaluation results. The grading results of the proposed model for the six types of salt-baked chicken were essentially consistent with those of sensory evaluation. The model could provide a more intuitive and objective classification basis, which made the quality evaluation of salt-baked chicken more objective and accurate.
陈 超，韩佳晶，李明宇，姚 晶，王振宇，张德权，张春江. 基于主成分分析的盐焗鸡综合品质评价模型构建[J]. 肉类研究, 2025, 39(7): 20-25.
CHEN Chao, HAN Jiajing, LI Mingyu, YAO Jing, WANG Zhenyu, ZHANG Dequan, ZHANG Chunjiang. A Quality Evaluation Model for Salt-Baked Chicken Based on Principal Component Analysis. Meat Research, 2025, 39(7): 20-25.
2025, Vol. 39 
