食品科学 ›› 2009, Vol. 30 ›› Issue (24): 347-350.doi: 10.7506/spkx1002-6630-200924077

• 分析检测 • 上一篇    下一篇

稻谷脂肪酸值近红外光谱快速测定技术研究

范维燕1,2,林家永1 ,*,邢 邯3,窦发德4,吴玉凯4   

  1. 1.国家粮食局科学研究院 2.南京农业大学食品科技学院 3.南京农业大学农学院 4.北京理工大学化工与环境学院
  • 收稿日期:2008-12-19 修回日期:2009-04-07 出版日期:2009-12-15 发布日期:2010-12-29
  • 通讯作者: 林家永 E-mail:linjy@chinagrain.org

Rapid Determination of Fatty Acid Content in Rice by Near-Infrared Spectroscopy

FAN Wei-yan1,2,LIN Jia-yong1,*,XING Han3,DOU Fa-de4,WU Yu-kai4   

  1. 1. Academy of State Administration of Grain, Beijing 100037, China;2. College of Food Science and Technology, Nanjing
    Agricultural University, Nanjing 210095, China;3. College of Agriculture, Nanjing Agricultural University, Nanjing 210095,
    China;4. College of Chemical Industry and Environment, Beijing Institute of Technology, Beijing 100081, China
  • Received:2008-12-19 Revised:2009-04-07 Online:2009-12-15 Published:2010-12-29
  • Contact: LIN Jia-yong1,*, E-mail:linjy@chinagrain.org

摘要:

采用近红外光谱(NIRS)分析技术和化学计量方法建立稻谷脂肪酸值的近红外分析模型,并对模型进行预测准确性评价;在建立定标模型的过程中,探讨光谱散射处理、数学(导数)处理等优化处理对定标模型的影响。结果表明:修正偏最小二乘法是建立稻谷脂肪酸值测定定标模型的最佳回归方法,所建立模型的定标相关系数(RSQ)为0.961,定标标准偏差(SEC)为1.9205;内部交互验证相关系数(1-VR)为0.9474,内部交互验证标准偏差(SECV)为2.2511。外部验证的相关系数(r)为0.951,外部验证标准偏差(SEP)为1.934。标准方法与NIRS 测定方法测定的稻谷脂肪酸值含量之间的t 检验值为1.403,显示两种方法测定结果无显著性差异(P < 0.1),预测值与实测值的平均绝对偏差为0.27,说明所建立的稻谷脂肪酸值的NIRS 数学模型预测准确性较好,可用于稻谷脂肪酸值的快速预测。

关键词: 稻谷, 脂肪酸值, 近红外光谱(NIRS), 定标模型

Abstract:

The mathematic models for the prediction of fatty acid content of rice was established with the technique of nearinfrared spectroscopy (NIRS). The result showed that the calibration models developed by the partial least square (PLS) regression were optimum. The statistical values of calibration equation were as follows: the coefficient of correlation (RSQ) of 0.961, the standard error of calibration (SEC) of 1.9205, the determination coefficient of cross-validation (1-VR) of 0.9474, the standard error of cross-validation (SECV) of 2.2511, Regression squared (r) of 0.951, square error of prediction (SEP) of 1.934. The t test value between the chemical standard methods and NIRS method was 1.403 (P<0.1), suggesting no significant difference between these two methods. The absolute average deviation was 0.27. This NIRS method could be applied to predict the fatty acid content in rice.

Key words: rice, fatty acid, near-infrared spectroscopy, calibration mode

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