近红外光谱法测定端羟基环氧乙烷-四氢呋喃共聚醚的羟值

提出了用近红外光谱测定端羟基环氧乙烷-四氢呋喃共聚醚(PET)的羟值,结合主成分回归和偏最小二乘法建立了PET羟值与其近红外光谱之间的关联模型。结果表明,近红外光谱法与化学分析法的测定结果一致;近红外光谱法测定PET羟值的相对误差在5%以内;利用遗传算法选择部分波长建立校正可以降低模型的预测误差。     

In‐Line Monitoring of Vinyl Chloride Suspension Polymerization with Near Infrared Spectroscopy, 2 ‐ Design of an Advanced Control Strategy

Near infrared spectroscopy (NIRS) may constitute a powerful tool for in‐line monitoring of morphological properties of PVC particles in suspension polymerizations. It is shown that dynamic trajectories of morphological properties, as predicted with NIR‐based calibration models, change smoothly along the batch; thus, these trajectories can be used as references for process monitoring and control. It is also shown that modification of operation variables during the batch leads to modification of the final morphological properties of the powder. This indicates that the morphology of PVC grains can be manipulated along the batch and that advanced NIR‐based control procedures can be implemented for control of the morphological properties of PVC resins, as illustrated through simulation.

     

近红外光谱法测定卷烟纸中钙和镁

应用傅里叶变换近红外(FT-NIR)光谱分析技术结合偏最小二乘法(PLS),建立了卷烟纸中钙和镁含量的数学预测模型。结果表明:钙和镁模型的相关系数分别为0.9870和0.9851,内部交叉验证均方差为0.462和0.0082,近红外光谱法预测值与原子吸收光谱法测定值的平均相对偏差各为3.1%和7.4%。该方法简便、快速、不破坏样品,可用于大批量卷烟纸样品中钙和镁的快速测定。     

废旧涤／棉混纺织物NIRS定性分析模型的建立与外部验证

利用近红外光谱技术对354个废旧涤/棉混纺织物进行研究,通过偏最小二乘法（partial least squares ,PLS ）和定性鉴别系数建立了不同光谱特征的涤/棉混纺织物近红外定性分析模型。染色涤/棉混纺织物N IR光谱主要有两大类,一类具有正常涤/棉光谱特征,另一类光谱由于样本中染料、颜料和消光剂等化学助剂的影响,使光谱谱线成斜线,失去其光谱特征。如以全部样本建模,模型识别率较低。故将样本分为两类：斜线光谱样本和正常光谱样本,分别建立NIR定性分析模型。NIR定性分析模型建立后,根据验证结果分别对建模的谱区、预处理方法和主因子数进行优化,以提高模型的稳健性和可靠性。结果表明,样本分别建模后,模型的识别率大大提高,用验证集样本进行内部验证,正常光谱和斜线光谱所建模型的识别率均达99％,其校正集相关系数 RC 均为0.991,验证集相关系数 RP 分别为0.983和0.984、校正标准差S EC分别为0．887和0.453、预测标准差SEP分别为1.131和0.573。用150个界外样本分别对正常光谱样本模型和斜线光谱样本模型进行外部预测检验,模型识别率分别达91.33％和88.00％,表明所建NIR定性分析模型能够较好地在回收现场进行涤/棉混纺织物的鉴别。     

稻米色氨酸含量近红外反射光谱全局和局部飞速定标技术研究

色氨酸是人类一种必需氨基酸,也是稻米中一种重要的限制性氨基酸。从4年份1256份材料中选择出272份有代表性的样品,采用碱水解-分光光度法测定了其色氨酸含量。比较不同定标方法的预测结果发现,运用改良的偏最小二乘法(modified partial least square,MPLS)的全局(Global)定标方法和局部(Lo-cal)飞速定标方法的预测效果较佳,基于精米粉光谱建立的方程的预测标准误差均为0.007%,外部验证决定系数分别为87.1%和87.4%,可用于定量分析;而基于糙米光谱建立的定标方程的预测效果略差,但仍具有良好的预测能力。研究结果表明,近红外光谱技术可作为水稻育种中间材料的快速筛选和食品工业中稻米原料的品质监控手段。     

应用近红外光谱技术重建南极湖泊初级生产力变化的一种新方法

为探求快速、廉价、无损、同步的光谱技术在南极古湖沼研究中的可能性,本文分析了南极中山站附近采集的一根湖泊沉积柱样晶的近红外反射光谱数据,通过主成分(PCA)统计分析方法,发现主成分因子载荷值与反映湖泊生产力变化的环境指标S2(有机质热解烃类化合物指标,指示湖藻类来源有机质)在深度剖面上具有一致的变化趋势,两者表现出显著...     

Screening Inorganic Arsenic in Rice by Visible and Near-Infrared Spectroscopy

The potential of near-infrared spectroscopy (NIRS) for screening the inorganic arsenic (i-As) content in commercial rice was assessed. Forty samples of rice were freeze-dried and scanned by NIRS. The i-As contents of the samples were obtained by acid digestion-solvent extraction followed by hydride generation atomic absorption spectrometry, and were regressed against different spectral transformations by modified partial least square (MPLS) regression. The second derivative transformation equation of the raw optical data, previously standardized by applying standard normal variate (SNV) and De-trending (DT) algorithms, resulted in a coefficient of determination in the cross-validation (1-VR) of 0.65, indicative of equations useful for correct separation of the samples in low, medium and high groups. The standard deviation (SD) to standard error of cross-validation (SECV) ratio, expressed in the second derivative equation, was similar to those obtained for other trace metal calibrations reported in NIRS reflectance. Spectral information relating to starch, lipids and fiber in the rice grain, and also pigments in the caryopsis, were the main components used by MPLS for modeling the selected prediction equation. This pioneering use of NIRS to predict the i-As content in rice represents an important reduction in labor input and cost of analysis.     

烟草近红外光谱分析网络化及其应用进展

该文回顾了近红外光谱(NIRS)分析技术的应用历程以及"近红外光谱分析+互联网"模式在烟草领域中的应用研究与实践,探讨了在近红外光谱分析网络化环境中,近红外光谱仪器设备存在的硬件差异以及常规化学计量学方法(算法)在建模、数据处理存在的不足对近红外光谱的深度应用产生的影响,并提出了近红外光谱分析云计算应用的解决思路。最后,对大数据时代近红外光谱分析网络化模式的应用前景进行了展望。     

菊苣体外干物质消化率近红外分析模型的建立

菊苣(Cichorium intybus L.)是一种新型的高产优质饲用牧草,具有极大的推广利用价值。体外干物质消化率(in vitro dry matter digestibility,IVDMD)是评价饲草营养价值的重要指标之一。建立菊苣体外干物质消化率的NIRS定量分析模型的研究,采集了72个品种、不同基因型、不同生长发育时期的204个菊苣地上部分为样品,应用傅里叶变换近红外漫反射光谱技术,通过采用不同的回归算法,比较不同的光谱范围和光谱预处理方法,建立了8个菊苣体外干物质消化率(IVDMD)的近红外漫反射光谱校正模型,从中选出最佳参数的校正模型。其校正决定系数(R2cal)和外部验证决定系数(R2val)分别为0.953 17和0.904 55,校正标准差(RMSEC)和预测标准差(RMSEP)分别为1.977 99%和2.008 82%,预测值与化学值间的相关系数(r)达0.951 08。结果表明,利用近红外漫反射光谱法来测定菊苣体外干物质消化率(IVDMD)是可行的,可为菊苣体外干物质消化率(IVDMD)的测定提供快速的分析测定方法。     

Determination of inorganic elements in animal feeds by NIRS technology and a fibre-optic probe

In the present work we study the use of near infra-red spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for the analysis of the mineral composition of animal feeds. The method allows immediate control of the feeds without prior sample treatment or destruction through direct application of the fibre-optic probe on the sample.The regression method employed was modified partial least squares (MPLS). The calibration results obtained using forty samples of animal feeds allowed the determination of Fe, Mn, Ca, Na, K, P, Zn and Cu, with a standard error of prediction (SEP(C)) and a correlation coefficient (RSQ) of 0.129 and 0.859 for Fe; 0.175 and 0.816 for Mn; 5.470 and 0.927 for Ca; 2.717 and 0.862 for Na; 4.397 and 0.891 for K; 2.226 and 0.881 for P; 0.153 and 0.764 for Zn, and 0.095 and 0.918 for Cu, respectively.The robustness of the method was checked by applying it to 10 animal feeds samples of unknown mineral composition in the external validation.