近红外光谱检测蜂蜜中可溶性固形物含量和水分的应用研究

提出了一种利用近红外光谱技术定量分析蜂蜜中可溶性同形物含量(SSC)的新方法,同时对蜂蜜中的水分也进行了研究.在不同光谱范围内,通过对原始光谱的不同预处理,用偏最小二乘法分别建立了SSC和水分的近红外透反射光谱校正模型,所有模型都有高的的预测精度和水分的最优模型都为在全谱范围内,光谱预处理采用Norris平滑+一阶微分+多元信号校正,SSC模型的交互验证决定系数(RCV2)、交互验证误差均方根(RMSECV)、验证集决定系数(RP2)、验证误差均方根(RMSEP).SSC模型分别为0.998 6,0.190,0.998 5和0.127,水分模型分别为0.998 4,0.187.0.998 6和0.125.近红外光谱能实现蜂蜜中SSC和水分的准确测定.水分模型预测结果略好于相关文献的报道.

Prediction analysis of soluble solids content and moisture in honey by near infrared spectroscopy

A new method for the analysis of soluble solids content (SSC) in honey by near infrared spectroscopy (NIR) was developed, and moisture was also analyzed. The partial least square regression models of SSC and moisture were built for different pretreatments of the raw spectra in different spectral range. Good predictions were always obtained for all models. The best models of SSC and moisture were obtained by using Norris (3,2) smoothing + first derivative + multiplicative signal correction in total spectral range. The coefficient of determination (R(CV)2) and root mean square error of cross validation (RMSECV), the coefficient of determination (R(p)2) and root mean square error of validation sets (RMSEP) were 0.9986, 0.190, 0.9985 and 0.127 respectively for SSC, while for moisture they were 0.9984, 0.187, 0.9986 and 0.125 respectively. NIR could be used to analyze SSC and moisture in honey. The result of this article was better than that of related documents for moisture.