应用近红外透射光谱法测定稻米淀粉消减值的研究

以183份稻米为样品,利用近红外透射光谱分析仪,对样品进行光谱扫描,并用快速黏度分析仪测定黏滞特性值消减值.采用多种计量数学处理方法和不同的回归统计方法进行定标曲线的开发和比较,得到了稻米消减值测定的近红外分析数学模型,数学模型的定标标准偏差(SEC)、交叉检验标准误差(SECV)和定标决定系数(RSQ)分别为:18.69,19.08和O.949 7.相关性达极显著水平,内部交叉验证和外部验证结果表明近红外定量分析消减值有很高的准确度.该研究利用近红外透射光谱技术为快速准确无损测定黏滞特性指标提供了一条新途径.     

近红外光谱技术在川麦冬原位检测中的应用研究

原药材检测费时费力一直是川麦冬质量分析中亟待解决的问题。该文将近红外光谱分析技术应用于川麦冬原药材的质量分析，以漫反射模式对麦冬颗粒进行无损原位检测后，采用光谱预处理方法减少因粒径造成的干扰，通过变量筛选方法提取有效信息，最终建立了快速定量分析模型。结果表明，水分、浸出物和总皂苷含量模型的验证均方根误差（RMSEP）分别为0.165 5%、0.401 9%、0.078 4%，验证集决定系数（Rv2al）分别为0.965 1、0.696 5、0.803 6，相对分析误差（RPD）分别为4.50、2.68、2.22,3个质量指标的RPD均大于2，说明模型性能较好，能够满足川麦冬质量分析的要求。该法通过近红外光谱技术采集川麦冬颗粒的原位光谱，避免了粉碎，真正意义上实现了川麦冬无损、绿色、快速的含量分析，为川麦冬的质量分析提供了参考。     

近红外光谱法快速检测烟草中部分香气物的应用研究

应用傅立叶变换近红外漫反射光谱仪,从500个样品中按高、中、低含量挑选出具代表性的150～172个烟草样品建立了近红外光谱与烟草中的苹果酸、柠檬酸和石油醚提取物成分含量间的数学模型,用建立的模型对36个样品进行预测,结果表明,各成分近红外预测值与实测值之间的平均偏差:苹果酸为0.090,柠檬酸为0.040,石油醚提取物为0.124;且近红外预测值与化学法不存在显著性差异,近红外光谱分析技术可初步用于烟草部分香气成分的快速定量分析.     

近红外光谱用于注射用曲克芦丁质量控制研究

运用近红外光谱(NIRS)分析技术建立注射用曲克芦丁的定量分析预测模型,并进行相关验证。近红外积分球漫反射光谱法对73个批次样品进行采集得到NIRS图,根据高效液相色谱法(HPLC)测定样品的有效成分含量并测得样品pH值,使用TQ Analyst光谱分析软件运用偏最小二乘法(PLS)建立定量分析方法模型。模型结果显示,含量预测模型的线性相关系数(R)为0.99239,校正标准偏差(RMSEC)和预测标准偏差(RMSEP)分别为0.1790和0.5460,pH值预测模型R为0.81575,RMSEC和RMSEP分别为0.0749和0.0704。验证结果显示,含量与pH值预测模型外部验证结果的平均误差率分别为0.46%和1.57%,且t检验无显著性差异(P>0.05)。NIRS分析技术可快速稳定的对产品含量和pH值进行预测,对产品质量控制提供了新的方法依据。     

傅立叶变换近红外光谱法测定腐乳中总酸、蛋白质和水分

应用傅立叶变换近红外光谱技术,建立了腐乳中总酸、蛋白质和水分的分析模型。测定32份腐乳的近红外光谱数据,得到原始光谱信息,通过光谱预处理方法消除原始光谱噪声,最后采用偏最小二乘法建立回归方程。最终得到总酸、蛋白质和水分近红外光谱分析模型的决定系数(R2)依次为99.37%、99.70%、99.73%,交叉验证均方根差(RMSECV)依次为0.00871、0.11、0.0714。用该模型对11个未知腐乳样品进行外部验证,其总酸、蛋白质和水分外部验证的决定系数(R2)依次为98.74%、99.38%、99.48%,预测标准偏差(RMSEP)依次为0.00862、0.113、0.0683。内部交叉验证和外部验证均证明,近红外定量分析有较高的准确度,能满足腐乳生产中总酸、蛋白质和水分的检测精度要求。     

近红外光谱用于过氧化氢含量的定量分析研究

用长波近红外光谱仪（傅里叶变换,InGaAs检测器）和短波近红外光谱仪（光栅分光,CCD检测器）对比研究了25％～30％过氧化氢水溶液中过氧化氢含量的定量分析方法。结果表明,应用短波近红外光谱结合长光程样品池对25％-30％过氧化氢水溶液样品中过氧化氢含量进行定量分析,可以显著减少过氧化氢分解对定量分析的干扰,使定量分析的准确度和重复性显著提高。短波近红外光谱定量分析模型RMSECV和RMSEP分别为0．06和0．05;长波近红外光谱定量分析模型RMSECV和RMSEP分别为0．10和0．09。     

扑热息痛片剂药品的近红外光谱法非破坏定量分析

现代近红外光谱分析技术将近红外光谱 (NIR)法同计算机科学和化学计量学结合 ,实现了对样品进行无损非破坏性定量分析 .该法具有速度快、操作简单及所需样品少等特点 ,能够实现样品分析的时间同步、地点同步及无损非破坏分析 .为实现生产过程中即时、在线的质量控制提供了新的手段[1 ] .本文应用人工神经网络 [2 ]与近红外漫反射光谱相结合对扑热息痛片剂药品进行了非破坏快速定量分析 .用扑热息痛片剂药品的近红外漫反射光谱数据、一阶导数光谱数据及二阶导数光谱数据分别建立了 ANN模型 ,预测未知样品 ,讨论了影响网络的因素 ,使用了新…     

近红外光谱法无损检测平谷产大桃品质方法研究

利用近红外（Near infrared, NIR）漫反射光谱法结合化学计量学定量分析技术开展了平谷产大桃品质的无损检测研究。使用手持式近红外光谱仪采集7个不同品种平谷产大桃的近红外漫反射光谱，采用系统抽样法将其划分为验证集和验证集，结合Savitzky-Golay卷积平滑法（Savitzky-Golay Smoothing, S-G）、标准正态变换法（Standard normal variation, SNV）和多元散射校正法（Multivariate scattering correction, MSC）3种预处理方法以及偏最小二乘回归（Partial least square regression, PLSR）与随机森林（Random forest, RF）两种建模算法，分别建立了大桃中的糖度（Soluble solids content, SSC）、酸度、硬度和水分定量模型。结果表明，非线性RF模型优于线性PLSR模型，对于SSC，一阶导数光谱结合MSC预处理建立的RF模型效果最佳，验证集决定系数（Coefficient of determination,R2）和预测均方根误差...     

基于XRF和Vis-NIR光谱数据融合的土壤镉含量定量分析法

根据鄱阳湖南矶山区域土壤的X荧光光谱和可见近红外光谱特征,建立了3种数据融合(等权融合、累加融合、外积融合)的最小二乘向量机定量分析模型。结果表明,等权融合和外积融合模型精度和稳定性均优于单一光谱定量分析模型。其中外积融合模型性能最佳,其决定系数(R2)为0.85,校正均方根误差(RMSEC)为009,预测均方根误差(RMSEP)为006,相对分析误差(RPD)为2.41,满足实际土壤中Cd的检测需求。该方法准确可靠,可为我国土壤重金属分类分级方法研究提供参考。     

鱼粉近红外光谱模型传递应用研究

为探讨光栅型与傅里叶变换型近红外分析仪之间模型传递的应用效果,选取国产鱼粉为近红外光谱样本,DS2500F型近红外分析仪为源仪器,MPA型近红外分析仪为目标仪器,采用分段直接校正(PDS)方法实现近红外光谱传递。分别建立水分、粗蛋白质、粗脂肪、蛋氨酸和赖氨酸等组分的预测模型,通过交互验证决定系数(R2cv)、交互验证标准误差(RMSECV)、马氏距离(MD)、系统偏差(Bias)、预测均方根误差(RMSEP)和相对分析误差(RPD)等参数,多维度评估光谱传递后所建预测模型的效果。结果表明,DS2500F仪器的近红外光谱传递到MPA型仪器时,所建国产鱼粉的水分、粗蛋白质、粗脂肪、蛋氨酸、赖氨酸的预测模型与MPA型仪器原始预测模型各参数对比无显著差异,预测效果基本一致,说明国产鱼粉在DS2500F仪器上的近红外光谱通过传递可以替代MPA型仪器的原始光谱,间接实现了模型传递,且具有良好的适用性和共享性,可提高近红外预测模型的应用效率。     

阴离子交换树脂结合近红外漫反射光谱测定碳酸饮料中日落黄

采用强碱性阴离子交换树脂富集饮料中的合成食用色素日落黄,用近红外漫反射光谱技术直接测定富集有色素的树脂.将34个模拟样品建模,日落黄浓度范围为0.05～1.2g/L.以柠檬黄和亮丽春红5R为干扰,经偏最小二乘回归建模,得到决定系数为0.9883,标准偏差为0.0187的稳健模型.定量预测3种不同市售饮料中的日落黄,回收...     

离子排斥色谱法测定环境样品中挥发性有机酸及乳酸

提出了同时测定环境样品中挥发性有机酸及乳酸的离子排斥色谱法（IEC法）。考察了流动相浓度、流速对有机酸分离的影响。实验结果表明,乳酸、甲酸、乙酸、丙酸、正丁酸和正戊酸可达到完全分离,被测组分的浓度与其峰高在一定的范围呈良好的线性关系,检出限均低于0.10 mg/L。测定了糖蜜酒精废水和消化污泥中有机酸的含量,结果满足检...     

Fungal Pretreatment by Phanerochaete chrysosporium for Enhancement of Biogas Production from Corn Stover Silage

Corn stover silage (CSS) was pretreated by Phanerochaete chrysosporium in solid-state fermentation (SSF), to enhance methane production via subsequent anaerobic digestion (AD). Effects of washing of corn stover silage (WCSS) on the lignocellulosic biodegradability in the fungal pretreatment step and on methane production in the AD step were investigated with comparison to the CSS. It was found that P. chrysosporium had the degradation of cellulose, hemicellulose, and lignin of CSS up to 19.9, 32.4, and 22.6 %, respectively. Consequently, CSS pretreated by 25 days achieved the highest methane yield of 265.1 mL/g volatile solid (VS), which was 23.0 % higher than the untreated CSS. However, the degradation of cellulose, hemicellulose, and lignin in WCSS after 30 days of SSF increased to 45.9, 48.4, and 39.0 %, respectively. Surface morphology and Fourier-transform infrared spectroscopy analyses also demonstrated that the WCSS improved degradation of cell wall components during SSF. Correspondingly, the pretreatment of WCSS improved methane production by 19.6 to 32.6 %, as compared with untreated CSS. Hence, washing and reducing organic acids (such as lactic acid, acetic acid, propionic acid, and butyric acid) present in CSS has been proven to further improve biodegradability in SSF and methane production in the AD step.     

油田水中短链有机酸的等速电泳法研究

本文采用水相蒸发除去大量的氯离子,用等速电泳法对油田水中短链有机酸进行了定性定量分析。结果表明,油田地层水中有机酸成分主要有甲酸、乙酸、丙酸、丁酸、苯甲酸和乳酸等,本法回收率和相对标准偏差分别在96％～105％和2.4％～7.6％之间。     

利用和频振动光谱研究空气/短链脂肪酸界面的分子取向

利用和频振动光谱(SFG-VS)方法检测了5种短链脂肪酸分子(乙酸、丙酸、正丁酸、正戊酸及正己酸)在空气/纯液体界面的结构, 得到了3种偏振组合(ssp, ppp, sps)下的和频振动光谱. 通过偏振选择定则对各个谱峰进行了指认和分析, 同时计算出空气/纯脂肪酸液体界面上脂肪酸分子的甲基取向角. 对比发现, 从丙酸到己酸, 分子甲基基团的界面取向角随碳链的增长略有增大. 并对其机理进行了分析.     

Application of gas chromatography coupled to chemical ionisation mass spectrometry following headspace solid-phase microextraction for the determination of free volatile fatty acids in aqueous samples

Gas chromatography coupled to positive and negative ion chemical ionisation mass spectrometry was evaluated for the determination of free volatile fatty acids (VFAs) from aqueous samples by headspace solid-phase microextraction. Negative ion chemical ionisation in the selected ion monitoring mode using ammonia as reagent gas provided acceptable sensitivity and the highest selectivity for the determination of C2-C7 fatty acids using a polydimethylsiloxane-Carboxen fibre. Detection limits in the range of 150 microg l(-1) for acetic acid and from 2 to 6 microg l(-1) for the remaining carboxylic acids were achieved. The reproducibility of the method was between 9 and 16%. The developed analytical procedure was applied to the analysis of VFAs in raw sewage. The absence of interfering peaks provided a more accurate determination of acetic, propionic, butyric and isovaleric acids than a similar analytical scheme but using a flame ionisation detector.     

Improved liquid chromatography/mass spectrometric analysis of low molecular weight carboxylic acids by ion exclusion separation with electrospray ionization

An improved, simple and sensitive analytical method for low molecular weight organic acids has been developed. A mixture of acetic, propionic, butyric, glycolic, lactic, 2-hydroxybutyric, malonic, succinic, glutaric, tartaric and citric acids was separated on a semi-rigid styrene-divinylbenzene copolymer-based H-type cation-exchange resin (ULTRON PS-80H) based on an ion exclusion chromatographic (IEC) mechanism, with detection using electrospray ionization mass spectrometry (ESI-MS). Formic or acetic acid was used as a mobile phase to separate the carboxylic acids within 15 min. For liquid chromatography/mass spectrometry (LC/MS), the ESI interface was used in both positive and negative ionization mode. ESI produced reasonable signals from positive ions, [M+NH(4)](+), of acetic, propionic and butyric acids and from negative ions, [M-H](-), of glycolic, lactic, 2-hydroxybutyric, malonic, succinic, glutaric, tartaric and citric acids. The effects of ionization parameters, source temperature, capillary voltage and cone voltage, on sensitivity and linearity were examined. Linear plots of peak area versus concentration were obtained over the range 0.1-20 ppm for MS detection. The detection limits of the target carboxylic acids calculated at signal-to-noise (S/N) ratio of 3 ranged from 9 to 59 ppb. The reproducibility of retention times and peak areas were 0.55-1.25 and 0.85-2.45%, respectively.     

Comparison and joint use of near infrared spectroscopy and Fourier transform mid infrared spectroscopy for the determination of wine parameters

A study of the statistic characteristics of the multidetermination of several enological parameters - namely, alcoholic degree, volumic mass, total acidity, glycerol, total polyphenol index, lactic acid and total sulphur dioxide - depending on the spectroscopic zone employed, was carried out. The two techniques used were near infrared spectroscopy (NIRS) and Fourier transform mid infrared spectroscopy (FT-MIRS). The combination of these two regions (sum of their spectra) was also studied. NIRS yielded better results, but the use of both zones improved the determination of glycerol and total sulphur dioxide. The training and validation sets used for developing general equations were built with samples from different apellation d’origine, different wine types, etc. Partial least squares regression was used for multivariate calibration, using systematic cross validation in the calibration stage and external validation in the testing stage. Sample preparation was not required.     

土壤速效磷近红外迁移学习预测方法研究

可见-近红外光谱技术是对土壤速效磷含量定量估测的有效手段,但某一地区土壤采集的光谱数据建立的模型在给其它地区使用时会出现预测精度低、模型失效等问题。该文以皖南土壤样本为源域,皖北土壤样本为目标域,通过迁移学习方法建立了预测模型,以提高土壤速效磷预测模型的准确性,并比较了迁移前后预测模型的精度。结果显示,皖南地区模型不能直接用于皖北地区,会出现模型失效问题,该模型的决定系数(R~2)和相对分析误差(RPD)分别为-0.19和0.92,预测均方根误差(RMSEP)为1.04;样本量不大的皖北地区建立模型的预测精度不高,R~2和RPD分别为0.61和1.60,RMSEP为0.60;而基于迁移成分分析(TCA)并加入部分皖北样本建立模型,可显著提高对皖北样本的预测精度,模型的R~2和RPD分别提升至0.79和2.18,RMSEP降低至0.44。表明基于TCA的方法能将皖南土壤速效磷预测模型应用于皖北,可提高皖北土壤速效磷预测模型准确性并降低成本,为土壤速效磷预测模型的广泛应用提供了新思路。     

Fermentation metabolism and kinetics in the production of organic acids byPropionibacterium acidipropionici

The genusPropionibacterium acidipropionici was grown under pH-controlled batch fermentation conditions for the production of acetic and propionic acids using 19.1 g/L glucose as a carbon source. The optimum pH range was found to be between 5.5 and 6.5. Bacterial metabolism and fermentation pathways were altered at pH values outside this range. Lactic acid was produced as a key intermediate, with the final acetic and propionic acid production entirely dependent on the cell's ability to metabolize the lactic acid. Most of the glucose in the medium was consumed in less than 20 h of fermentation and converted to lactic acid. Batch fermentation at pH 6 showed that lactic acid was completely utilized to produce 8.5 g/L propionic acid and 5.7 g/L acetic acid. However, the bacteria were unable to metabolize lactic acid at pH 7, resulting in 0.7 g/L propionic acid and 7.0 g/L acetic acid in the fermenter. A kinetic study of batch fermentation at pH 6 showed two distinct growth phases during the fermentation. Most of the cell growth was achieved in the exponential growth stage when glucose was consumed as a main substrate. A nonexponential growth stage was observed when lactic acid was utilized as a carbon source, producing propionic and acetic acids as secondary metabolites.