食品科学

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近红外光谱法对鸡肉品种的快速无损鉴别

龚 艳,汤晓艳*,王 敏,陶 瑞,毛雪飞   

  1. 中国农业科学院农业质量标准与检测技术研究所,农业部农产品质量安全重点实验室,北京 100081
  • 出版日期:2015-08-25 发布日期:2015-08-17
  • 通讯作者: 汤晓艳
  • 基金资助:

    国际科技合作专项(2012DFA31140);公益性行业(农业)科研专项(201303083);农业部“948”重点项目(2011-G5)

Rapid and Nondestructive Identification of Chicken Breeds by Near Infrared Spectroscopy

GONG Yan, TANG Xiaoyan*, WANG Min, TAO Rui, MAO Xuefei   

  1. Key Laboratory of Agri-food Safety and Quality, Ministry of Agriculture, Institute of Quality Standards and Testing Technology for
    Agro-products, Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Online:2015-08-25 Published:2015-08-17
  • Contact: TANG Xiaoyan

摘要:

选取爱拔益加肉鸡(又名AA肉鸡)、京海黄鸡和狼山鸡鸡胸肉各40 个肉样,应用便携式近红外光谱仪在1 000~2 500 nm波长条件下分别对鸡肉肉块和肉糜进行光谱扫描,并测定肉样的颜色、蛋白质、脂肪和水分含量。各选择90 个肉样作为建模集,采用偏最小二乘判别分析法分别建立了鸡肉肉块和肉糜的品种鉴别模型。所建的两个模型对校正集和验证集样本的鉴别准确率均分别为100%和97.7%,对剩余预测集的各30 个肉样进行鉴别分析的鉴别准确率均为90%。

关键词: 鸡肉品种, 近红外光谱, 快速无损鉴别

Abstract:

Totally 40 chicken breast muscle samples from AA broiler chicken, Jinghai yellow chicken and Langshan chicken
were subjected to near infrared (NIR) analysis. Chicken meat slice and meat emulsion were scanned with a portable
NIR spectrometer (1 000–2 500 nm), respectively and then analyzed for color, protein, fat and moisture. A total of 90
chicken samples were selected as modeling sets. Breeds identification models of chicken meat slice and meat emulsion
were established using partial least squares discriminant analysis (PLS-DA). The established models showed 100% and
97.7% accuracy for discriminating calibration set and validation set and 90% accuracy for the remaining 30 chicken
samples, respectively.

Key words: chicken breeds, near infrared spectroscopy, rapid and nondestructive identification

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