Classification of Guizhou Aspidistra Plants by Near-infrared Diffuse Reflectance Spectroscopy

[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis （PCA）. [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.

Rapid Identification for Drought Resistance of Wheat Using Near-infrared Diffuse Reflectance Spectroscopy

[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat （GB/T 21127-2007）. In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality （full spectrum analyzer） and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient （RSQ） and coeffi- cients of determination for cross validation （1-VR） in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.

Monitoring real time polymorphic transformation of sulfanilamide by diffuse reflectance visible spectroscopy

This study investigated the development of a novel approach to surface characterization of drug poly- morphism and the extension of the capabilities of this method to perform ＇real time＇ in situ measure- ments. This was achieved using diffuse reflectance visible （DRV） spectroscopy and dye deposition, using the pH sensitive dye, thymol blue （TB）. Two polymorphs, SFN-β and SFN-γ, of the drug substance sulfanilamide （SFN） were examined. The interaction of adsorbed dye with polymorphs showed different behavior, and thus reported different DRV spectra. Consideration of the acid/base properties of the morphological forms of the drug molecule provided a rationalization of the mechanism of differential coloration by indicator dyes. The kinetics of the polymorphic transformation of SFN polymorphs was monitored using treatment with TB dye and DRV spectroscopy. The thermally-induced transformation fitted a first-order solid-state kinetic model （R2=0.992）, giving a rate constant of 2.43 × 10^- 2 s 1.

RAPID DETERMINATION OF PROTEIN IN MILLET BY FOURIER TRANSFORM NEAR-INFRARED(FTNIR)DIFFUSE REFLECTANCE SPECTROSCOPY

In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.

Rapid, Non-Destructive, Textile Classification Using SIMCA on Diffuse Near-Infrared Reflectance Spectra

Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.

Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy

A method for quantitative determination of fish sperm deoxyribonucleic acid(fsDNA)was developed by using titanium dioxide(TiO2)as an adsorbent and near-infrared diffuse reflectance spectroscopy(NIRDRS).The selective enrichment of fsDNA was proved by comparing the adsorption efficiency of bovine serum albumin,tyrosine and tryptophan,and the low adsorption background of TiO2 was illustrated by comparing the spectra of four commonly-used inorganic adsorbents(alkaline aluminium oxide,neutral aluminium oxide,nano-hydroxyapatite and silica).The spectral feature of fsDNA can be clearly observed in the spectrum of the sample.Partial least squares(PLS)model was built for quantitative determination of fsDNA using 28 solutions,and 13 solutions with interferences were used for validation of the model.The results showed that the correlation coefficient(R)between the predicted and the reference concentration is 0.9727 and the recoveries of the validation samples are in the range of 98.2%-100.7%.

Determination of Cysteine Using Near-infrared Diffuse Reflectance Spectroscopy with Enrichment via Thiol-maleimide Click Reaction

Enrichment technique has been proved to be an efficient way to make the near-infrared diffuse reflectancespectroscopy（NIRDRS） suitable for micro analysis. However, low selectivity presented by conventional enrichmentmethods makes the quantitative analysis easy to be affected by the coexisting components. In this study, a specificenrichment method with chemical bonding via thiol-maleimide click reaction was used to achieve the reduction of theinterferences. Taking cysteine as the analyzing target, maleimide-functionalized SiO2 nanoparticles were prepared forthe enrichment of cysteine. Then determination of cysteine in aqueous solution and human serum was studied usingthe partial least squares model built from the NIRDRS spectra of the adsorbate. The results show that the concentra-tion that can be quantitatively detected is as low as 2.0 μg/mL, and the correlation coefficient（R） between thereference and predicted concentration is 0.9871 for the validation samples. The recoveries are in the range of89.5%-113.8% for human serum samples in the concentration range of 0--16.2 μg/mL.

Determination of triglycerides in human serum by near-infrared diffuse reflectance spectroscopy using silver mirror as a substrate

Near infrared diffuse reflectance spectroscopy(NIRDRS) has gained wide attention due to its convenience for rapid quantitative analysis of complex samples. A method for rapid analysis of triglycerides in human serum using NIRDRS with silver mirror as the substrate is developed. Due to the even and high reflectance of the silver mirror, the spectral response is enhanced and the background interference is reduced.Furthermore, both linear and nonlinear modeling strategies were investigated adopting the partial least squares(PLS) and least squares support vector regression(LS-SVR), continuous wavelet transform(CWT)was used for spectral preprocessing, and variable selection was tried using Monte Carlo uninformative variable elimination(MC-UVE), randomization test(RT) and competitive adaptive reweighted sampling(CARS) for optimization the models. The results show that the determination coefficient(R) between the predicted and reference concentration is 0.9624 and the root mean squared error of prediction(RMSEP) is 0.21. The maximum deviation of the prediction results is as low as 0.473 mmol/L. The proposed method may provide an alternative method for routine analysis of serum triglycerides in clinical applications.

手持式马铃薯干物质含量无损检测装置设计与试验

面向马铃薯品质抽检的需求,研发了手持式马铃薯干物质无损检测装置。装置硬件部分包括光谱采集模块、电路控制模块、控制与显示模块、外壳模块,装置设计为枪形,尺寸为180 mm×85 mm×210 mm。利用装置采集可见近红外漫反射光谱,比较Savitzky-Golay卷积平滑(SM)、一阶导数(first-order derivative,FD)、多元散射校正(multiple scattering correction,MSC)和标准正态变量变换(standard normal variate transformation,SNV)的预处理方式,SM结果较优。采用竞争性自适应重加权采样(competitive adapative reweighted sampling,CARS)筛选27个特征波长,建立马铃薯干物质含量的支持向量回归(support vector regression,SVR)预测模型,结果显示,验证集决定系数和均方根误差分别为0.802和0.98%。基于QT开发工具编写装置软件,包括黑白校正与测量模块、电量显示模块、光谱数据显示模块、保存数据模块、光谱数据刷新模块、检测结果显示模块。开展装置验证,预测均方根误差为1.01%,单次测量平均耗时为0.62 s。结果表明,手持式马铃薯干物质无损检测装置可快速、准确检测干物质含量,具有在马铃薯生产源头与加工现场应用的潜力。

紫外可见光谱结合化学计量学对当归及其掺伪品的可视化鉴别

该文考察了紫外可见漫反射光谱结合化学计量学对当归及其掺伪品进行鉴别的可行性,并对40个当归纯品和75个掺伪品进行鉴别。首先采用Kennard-Stone(KS)分组法将数据集分成86个样品的训练集和29个样品的预测集。考察了训练集原始光谱以及连续小波变换及其结合SG平滑、数据标准化方法预处理后的光谱及主成分分析得分图,确定最佳预处理方法,最后采用偏最小二乘-判别分析建立鉴别模型。结果表明,对原始紫外可见光谱进行主成分分析,无法将当归和掺伪品分开。而经连续小波变换-SG平滑-数据标准化预处理后,不仅可区分当归纯品和其掺伪品,还可区分不同含量的掺伪品。经最佳预处理后仅使用一个因子建立偏最小二乘-判别分析模型,对预测集中当归及其掺伪品的鉴别正确率可达100%。因此,紫外可见光谱结合连续小波变换-SG平滑-数据标准化-偏最小二乘-判别分析模型,可以实现当归及其掺伪品的快速准确鉴别。

丙酮盐酸混合液提取土壤腐殖质组分的光谱学特征

采用丙酮盐酸混合液提取土壤胡敏酸(HA)和胡敏素(HU)组分,利用元素分析、紫外-可见漫反射光谱和红外光谱进行结构表征。元素分析表明,HA中C、H、N和S含量均高于HU,O含量低于HU。原子比分析表明HA的缩合度相对较高,分子结构相对复杂,HU的缩合度相对较低,分子结构相对简单。紫外-可见漫反射光谱分析表明,由于腐殖质(HS)的组成复杂,多种官能团互相干扰,HA和HU紫外-可见漫反射光谱无明显特征峰,吸光度值随着波长的增加呈下降趋势,且HA包含的吸光有机成分较多,化学组成较复杂。HA和HU紫外特征参数SUV254和E4/E6比较分析表明,与HU相比,HA芳香性较大,腐殖化程度较高。红外光谱分析表明,HA和HU具有相似的红外光谱,各研究对象特征吸收峰的吸收强度不同,其中开垦黑土20~40 cm和未开垦灰土18~37 cm土层HA的振动幅度较大,说明其包含的酚类化合物、含羟基化合物、脂肪族化合物和羧酸,以及含羰基的醛、酮、醚等化合物的含量较多。开垦黑土10~20 cm土层和未开垦灰土18~37 cm土层HU在各特征吸收峰振动幅度较大,说明其包含的酚类化合物、羧酸、脂肪烃和糖类化合物含量较多。红外光谱各吸收峰强度比较分析表明,开垦后黑土HA和HU酚类化合物、羟基官能团和脂肪族化合物等含量增加,而开垦后灰土HA和HU酚类化合物、羧酸和脂肪族化合物含量下降,表明开垦对黑土土壤有机质影响相对较小,并且在一定程度上增加了土壤有机质含量,而促进了灰土土壤有机质的分解。综上所述,丙酮盐酸混合液提取法为HS生物化学和生理活性的研究提供了新的技术手段,为合理利用土壤资源提供理论依据。

苹果可溶性固形物和糖酸比可见/近红外漫反射与漫透射在线检测对比研究

可溶性固形物和糖酸比是苹果内部品质主要评价指标之一。为此进行苹果糖酸比和可溶性固形物可见/近红外漫反射和漫透射对比检测研究。180个冰糖心和红富士样品被分成建模集和预测集(136∶44),分别用于建立偏最小二乘模型和验证模型的预测能力。在运动速度5个/秒时,采集了冰糖心和红富士两种样品的可见近红外光谱。漫反射和漫透射可见近红外光谱经多元散射校正、标准正态变量变换、基线校正等预处理后,建立了偏最小二乘回归模型。未参与建模的44个样品用于评价模型的预测能力,经比较,漫透射检测方式优于漫反射检测方式,主要因为漫透射检测方式能更有效地克服杂散光。可溶性固形物模型预测相关系数达到0.936,预测均方根误差为0.476°Brix;糖酸比模型预测相关系数达到0.785,预测均方根误差为10.94。研究结果表明:应用可见/近红外漫透射光谱技术,可实现苹果可溶性固形物和糖酸比在线检测。为大宗水果内部品质分选提供了技术支持和参考依据。

基于可见-近红外漫反射光谱技术的葡萄贮藏期间可溶性固形物定量预测

利用可见-近红外漫反射光谱技术,建立不同品种葡萄贮藏期间可溶性固形物含量定量预测的通用模型。以10℃贮藏的玫瑰香葡萄、马奶葡萄、红提葡萄的混合光谱为定标材料,探讨不同化学计量学建模方法、不同光谱预处理方法、间隔点、平滑数以及不同特征波长区间选择对建模效果的影响及模型的品种适用性。结果显示,采用改进偏最小二乘法,16点平滑,间隔点数16点,结合二阶导数、去散射的处理方法,在波长范围408～1 092.8 nm内建立的模型效果最优,其交互验证误差和交互验证判定系数R2CV分别为0.308 7、0.980 2。由3种葡萄混合组成的预测集对模型进行评价,预测标准差0.354、预测判定系数Rp2为0.980 8、验证相对分析误差为6.22、预测残差平方和为7.993。模型对单一品种预测Rp2均达到0.94以上。因此,葡萄果实可溶性固形物含量的近红外预测模型具有可行性,可同时适用于多种葡萄品种。

基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究

联合使用连续小波变换(continuous wavelet transform,CWT)和广义回归神经网络(generalized regression neural networks,GRNN)建立用于测定樱桃中糖含量的CWT-GRNN预测校正模型。利用CWT提取樱桃样本数据中反映含糖量的关键光谱特征,在CWT域中选择3个具有代表性的尺度,并在每个尺度下根据樱桃样本的可见-近红外光谱的特征将其划分为4个特征区间,从而构造12个特征输入到GRNN,GRNN的光滑因子取为0.0001。CWT-GRNN模型对20个预测样本集中的樱桃含糖量的预测相对误差在2%以内。结果表明,可见-近红外光谱技术可以快速、准确和无损地测定樱桃中的含糖量,本研究提出的方法可以用于果蔬产业的品质管理与控制。

可见/近红外漫反射光谱无损检测磨盘柿果实硬度的研究

建立可见/近红外光谱与磨盘柿果实硬度之间的数学模型,评价可见/近红外光谱技术无损检测磨盘柿硬度的应用价值。在可见/近红外光谱区域(570～1848nm),实验对比分析了不同数学建模算法、不同导数处理方法和不同散射及标准化处理的磨盘柿果实硬度定标模型。结果表明,应用偏最小二乘回归算法、一阶导处理和标准正常化和散射处理所建柿果实硬度定标模型的预测性能较优,模型的相关系数(Rc2)为0.7992,均方根误差(RMSEC)为2.0642;用该模型对40个预测样本进行预测,其相关系数(Rp2)为0.8267,预测均方根误差(RMSEP)为2.0223。研究表明,可见/近红外漫反射技术对磨盘柿果实硬度的快速无损检测具有可行性。

一种可见光响应纳米TiO_2粉体的光响应特性表征

利用有机溶剂水热法制备了一种新型的可见光响应纳米TiO2粉体光催化剂。对其进行光响应特性表征,研究发现:固相粉末漫反射吸收谱反映了该TiO2粉体具有类似改性TiO2的可见光响应的特征;而在纳米颗粒稀悬浮液的特定条件下,紫外-可见吸收谱给出了该纳米TiO2粉体的类似本征TiO2的光响应特征,观测不到其可见光响应特征;分析表明,该现象可能与在稀悬浮液的条件下,声子参与的光致电子跃迁过程的退化有关．

可见/近红外漫反射光谱无损检测南丰蜜桔维生素C的研究

应用可见/近红外漫反射光谱对南丰蜜桔维生素C含量进行了无损检测研究。在谱区350～1800nm,应用主成分分析和偏最小二乘法对经过预处理光谱进行数学建模,主成分数和光谱区间选择分别由完全交互验证和回归系数法确定。定标模型对10个未知样品的预测结果是:预测相关系数为0.813,预测均方差为2.112mg(100g)-1,预测偏差为-0.810mg(100g)-1。文章表明利用可见/近红外漫反射光谱技术无损检测南丰蜜桔维生素C具有可行性。

涩柿可溶性单宁的可见/近红外漫反射光谱无损检测研究

旨在建立可见/近红外漫反射光谱与涩柿内部可溶性单宁之间的关系,以评价可见/近红外漫反射光谱在测量涩柿内部指标可溶性单宁的应用价值。在可见/近红外光谱区域（570~1 848 nm）,实验对比分析了不同数学建模算法、不同导数处理方法和不同散射及标准化处理的涩柿可溶性单宁定标模型。结果表明,应用改进偏最小二乘回归算法、一阶导处理和去散射处理所建涩柿可溶性单宁定标模型的预测性能较优,其定标交互验证相关系数（RCV）和预测相关系数（R2p）分别为0.722 7和0.678 5,定标交互验证均方根误差（RMSECV）和预测均方根误差（RMSEP）分别为0.148 4和0.176 3。研究表明,可见/近红外漫反射光谱对涩柿可溶性单宁的快速无损检测具有一定的可行性,但模型精度有待提高。

可见/近红外漫反射光谱无损检测甜柿果实硬度

该研究的目的是建立可见/近红外漫反射光谱无损检测甜柿果实硬度的数学模型,评价可见/近红外漫反射光谱无损检测甜柿果实硬度的应用价值。果实硬度采用果皮脆性、果皮强度和果肉平均硬度作为评价指标。在可见/近红外光谱区域(400～2 500 nm),采用改进偏最小二乘法,对比分析了不同导数处理、不同散射及标准化处理的甜柿果实硬度定标模型。结果表明,对于果皮强度和果皮脆性,采用最小偏二乘法、一阶导数处理和标准多元离散校正处理建立的定标模型预测效果较好,RP2分别为0.858和0.862,SEP分别为0.094和0.157,RPD分别为2.47和2.63。对于果肉平均硬度,采用改进偏最小二乘法、一阶导数处理和标准正常化和去散射处理建立的定标模型预测效果较好,RP2为0.82,SEP为0.063,RPD为2.35。因此,可见/近红外漫反射光谱无损检测技术可用于甜柿果实硬度的无损检测。

红提葡萄V_C含量的可见/近红外检测模型

为了建立红提葡萄VC含量的可见/近红外漫反射光谱检测模型,并评价其应用价值,应用不同的化学计量学建模方法和光谱预处理方法,在不同特征波长区间内建立定标模型,讨论建模效果,并通过预测集样品验证最优模型的精度。结果显示:在全光谱范围内,应用改进偏最小二乘法(MPLS)结合一阶导数、5点平滑、加权多元离散校正(WMSC)处理得到的定标模型效果最优,交互验证标准差SECV为0.054 3,定标决定系数R2cv为0.920 2,预测决定系数R2p为0.931 8,预测标准差SEP为0.050 0,残差平方和PRESS为0.188 0,预测相对分析误差RPD为3.640 0。故应用可见/近红外漫反射技术对红提葡萄果实VC含量进行快速无损检测是可行的,模型稳定且精度较高。