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为探讨优质鸡肉质合理评价模型,采用主成分和聚类分析方法对优质肉鸡7个新品系9个与肉质有密切联系的指标进行了分析。结果显示:9个原始指标依据主成分解释总变量和碎石图提取了4个主成分,反映原变量89.82%的信息。第一主成分主要综合了失水率、肌纤维面积、肌纤维密度和pH值信息,命名为质构因子;第二主成分主要综合了VB1、肌纤维密度、肌纤维面积和肌内脂肪(IMF)的信息,命名为作肉质因子;第三主成分综合了嫩度、肉色和肌内脂肪的信息即感官因子;第四主成分综合了肌苷酸、肌内脂肪含量和肉色的信息看作风味因子。聚类分析将9个肉质指标分为3类,聚类结果与主成分分析基本一致,综合利用主成分和聚类分析结果制定了优质鸡的肉质评价模型,为优质鸡选育和肉质评价提供了理论依据。
In order to explore the reasonable evaluation model of high-quality chicken meat quality, the principal components and cluster analysis were used to analyze the nine indicators of seven new-quality chicken meat quality closely related to meat quality. The results showed that the nine original indicators extracted four principal components based on the principal components explained total variables and the gravel map, reflecting 89.82% of the original variables. The first principal component integrates the information of water loss rate, muscle fiber area, muscle fiber density and pH value and is named as texture factor. The second principal component integrates the information of VB1, muscle fiber density, muscle fiber area and intramuscular fat (IMF) , Named as the fleshy factor; the third principal component combines tenderness, flesh color and intramuscular fat sensory information; the fourth principal component of inosinic acid, intramuscular fat content and flesh color information as flavor factor. The clustering analysis divided the nine meat quality indexes into three categories. The clustering results were basically the same as the principal component analysis. Based on the principal component analysis and clustering analysis, the meat quality evaluation models were established for the quality chicken selection and meat quality evaluation The theoretical basis.