摘要
本文介绍了预处理方法在近红外光谱数据处理中的应用,并以牛奶为例探讨了具体的预处理参数．牛奶中脂肪和蛋白质含量的预测偏差为0．1g/dl～0．3g/dl,测量值与浓度参考值有良好的相关性．结果表明,数据预处理方法在模型优化中具有重要作用,对牛奶模型的建立有重要的参考价值。
In this paper, the application of preprocessing methods in near infrared spectral data processing is presented and the particular preproeessing parameters are discussed through the example of milk. The predicted errors of the fat and protein content in milk are 0.1g/dl - 0. 3g/dl. The measurements have a good eorrelativity with the reference values. The experiment results have shown that the preprocessing method can play an important role in the optimization of models and is of great reference value to the establishment of milk models.
出处
《红外》
CAS
2006年第11期27-30,共4页
Infrared
关键词
牛奶成分
近红外光谱
数据预处理
milk constituents
near-infrared spectroscopy
data preproeessing
