近红外光谱技术在线测定白砂糖色值.docx

近红外光谱技术在线测定白砂糖色值黎庆涛，王远辉，卢家炯(广西大学轻工与食品工程学院，南宁 530004)摘要：采用国产近红外 近红外光谱技术在线测定白砂糖色值 黎庆涛，王远辉，卢家炯 (广西大学轻工与食品工程学院，南宁 530004) 摘要：采用国产近红外在线分析系统，对广西某糖厂的白砂糖色值进行了在线测定研究。采用 SupNIR-4000型近红外在线分析仪，直接对成品传送带上的白砂糖进行扫描获得光谱数据，测定 时间仅需90 s。光谱预处理方法“标准化+Savitzky-Golay一阶求导+正交信号校正”最佳，人工 神经网络(ANN)建模最佳。结果显示，ANN模型的校正集相关系数(Rc)和标准偏差(RMSEC)分别 为0.9215和5.1984，预测集相关系数(Rp)和标准偏差(RMSEP)分别为0.6771和9.3042，色值预测偏 差基本在±10，满足糖厂需要。此法在制糖行业具有广泛的应用推广前景。 关键词：近红外光谱；白砂糖；色值；在线测定 中图分类号：TS 247 文献标志码：A 文章编号：1005-9989(2011)01-0271-04 Online determination of white granulated sugar color by near infrared spectroscopy technique LI Qing-tao, WANG Yuan-hui, LU Jia-jiong (Institute of Light Industry and Food Engineering, Guangxi University, Nanning 530004) Abstract: Online determining white granulated sugar color of a sugar factory in Guangxi was carried out using a domestic online near infrared spectroscopic analysis system (SupNIR-4000 NIR analyzer). The spectral data were obtained by scanning the granulated sugar on the belt conveyer with NIR analyzer, the time measured only 90 s. The spectral preprocessing method “Standardization+Savitzky-Golay 1st derivative+orthogonal signal correction (OSC)” was the best and artificial neural network(ANN) modeling was the best. The results showed that ANN model calibration correlation coefficient(Rc) and standard deviation(RMSEC) were 0.9215 and 5.1984 respectively, the prediction correlation coefficient(Rp) and standard deviation(RMSEP) were 0.6771 and 9.3042 respectively. The prediction errors was ±10, to meet the sugar factory’s requirement. This method has a wide application prospect in the sugar industry Key words: near infrared spectrum(NIRS); white granulated sugar; color; online determination 处理简捷、无需化学试剂、低成本等优点[2]。近 红外光谱分析在粮食、果蔬、乳制品等行业的应 用广泛[3-6]，在制糖工业的应用在国外报道较多， 主要集中在美国、德国、澳大利亚和南非等国， 但多局限于实验室研究[7-10]，而国内鲜见报道。本 人所带领的科研团队在近红外技术应用甘蔗制糖 白砂糖质量分析中色值作为重要参数指导生 产管理，被企业重点关注，严格控制。传统的化 学分析方法时间长达1 h，对生产的指导严重滞 后，无法满足质量监控的需要，迫切需要一种准 确快速的分析方法替代传统方法[1]。近红外光谱 (Near infrared spectrum, NIRS)分析技术具有样品