【摘要】：為探討優(yōu)質(zhì)雞肉質(zhì)合理評(píng)價(jià)模型,采用主成分和聚類(lèi)分析方法對(duì)優(yōu)質(zhì)肉雞7個(gè)新品系9個(gè)與肉質(zhì)有密切聯(lián)系的指標(biāo)進(jìn)行了分析。結(jié)果顯示:9個(gè)原始指標(biāo)依據(jù)主成分解釋總變量和碎石圖提取了4個(gè)主成分,反映原變量89.82%的信息。第一主成分主要綜合了失水率、肌纖維面積、肌纖維密度和pH值信息,命名為質(zhì)構(gòu)因子;第二主成分主要綜合了VB1、肌纖維密度、肌纖維面積和肌內(nèi)脂肪(IMF)的信息,命名為作肉質(zhì)因子;第三主成分綜合了嫩度、肉色和肌內(nèi)脂肪的信息即感官因子;第四主成分綜合了肌苷酸、肌內(nèi)脂肪含量和肉色的信息看作風(fēng)味因子。聚類(lèi)分析將9個(gè)肉質(zhì)指標(biāo)分為3類(lèi),聚類(lèi)結(jié)果與主成分分析基本一致,綜合利用主成分和聚類(lèi)分析結(jié)果制定了優(yōu)質(zhì)雞的肉質(zhì)評(píng)價(jià)模型,為優(yōu)質(zhì)雞選育和肉質(zhì)評(píng)價(jià)提供了理論依據(jù)。
[Abstract]:In order to study the reasonable evaluation model of high quality chicken quality, the main component and cluster analysis methods were used to analyze the indexes of 7 new lines of high quality broiler chicken which were closely related to meat quality. The results showed that four principal components were extracted from 9 original indexes according to principal component interpretation of total variables and lithotripsy, which reflected 89.82% information of original variables. The first principal component mainly synthesizes the information of water loss rate, muscle fiber area, muscle fiber density and pH value, which is named as the texture factor, and the second principal component mainly synthesizes the information of VB1, muscle fiber density, muscle fiber area and intramuscular fat (IMF), the second principal component mainly synthesizes the information of VB1, muscle fiber density, muscle fiber area and intramuscular fat (IMF). The third principal component synthesizes the information of tenderness, meat color and intramuscular fat, that is sensory factor, and the fourth principal component combines inosine acid, the information of intramuscular fat content and meat color as flavor factor. The nine meat quality indexes were divided into 3 groups by cluster analysis. The results of cluster analysis were consistent with that of principal component analysis (PCA). The evaluation model of meat quality of high quality chickens was established by using the results of principal component analysis and cluster analysis. It provides theoretical basis for high quality chicken breeding and meat quality evaluation.
【作者單位】： 中國(guó)農(nóng)業(yè)科學(xué)院家禽研究所;
【基金】：江蘇省科技支撐項(xiàng)目(BE2013386,BE2014364) 現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系建設(shè)專(zhuān)項(xiàng)基金資助項(xiàng)目(CARS-42-Z06)
【分類(lèi)號(hào)】：S831

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