傅里叶变换近红外光谱仪扫描条件对数学模型预测精度的影响

Influence of FT-NIR Spectrometer Scanning Requirements on the Math Model's Precision

以小麦粉状样品为例 ,研究了傅里叶变换近红外光谱仪在不同分辨率 ,不同的激光频率下扫描样品对近红外光谱用于分析小麦样品蛋白质含量的影响。结果表明 :以 4 ,8,16cm- 1 的分辨率扫描样品或当激光频率改变幅度在 1cm- 1 以内时对小麦蛋白模型的影响不显著 。

This study is based on the agriculture product near infrared spectra database, which is a foundation database. The database has very important effects on agriculture products quality analysis and agriculture breeding. What the NIR researchers and NIR users care about is how to utilize information of the foundation database fully. To share the NIR resource, unifying the scanning term to get high quality spectra is the first step. This article uses wheat powder as sample to study the influence of different resolution, different He-Ne frequency and sample granularity on the wheat powder protein model. The results show that scanning sample by 4, 8 or 16 cm -1 resolution has little influence on the wheat powder protein math model. The change in He-Ne frequency has influence to wavenumber accuracy, but when the change is within 1 cm -1, the influence is indistinctive. For FT-NIR instruments with He-Ne to have better stability, we needn't often adjust the He-Ne wavenumber. Sample granularity has more distinctive influence on the NIR math models.