原子吸收光谱检测法在检测重金属中检测原理的应用研究

原子吸收光谱检测法是21世纪50年代出现的一种新兴仪器分析办法,通过物质生成原子蒸气,对谱线吸收水平实行定量分析的一种办法。该方法被广泛运用在多个领域中,例如地质、机械、农业、生物医药、材料科学、食品等等。和传统的化学分析办法对比,原子吸收光谱检测法具有一定的优越性,其检测的结果更为可靠,有较高的灵敏度。本文将运用原子吸收光谱检测法,对中药材中重金属进行检测分析。

环境水样中锡的原子荧光光谱检测法

目的：建立一种快速检测饮用水中微量锡的方法。方法：应用原子荧光光谱检测法测定饮用水中微量锡。结果：在经过优化的条件下,锡的检出限为0.012μg/L;回收率在97.2%－101.4%之间,相对标准偏差小于1.0%。结论：方法操作更为简便、快速、准确、灵敏度高、仪器的性能稳定,便于推广使用。用此方法测定了大量的生活饮用水,结果令人满意,是一种较理想的分析方法。

山西老陈醋醋龄拉曼光谱快速检测方法的建立

该文建立了山西老陈醋醋龄拉曼光谱快速检测方法。首先确定川穹嗪的拉曼特征峰,其次,对山西老陈醋川芎嗪纳米增强拉曼光谱快速检测方法积分时间、积分次数、平滑系数、检测功率、样品量进行优化,从精密度、重复性、加标回收率3个方面进行方法学评价。最佳条件为:积分时间20s,积分次数10次,平滑系数10,功率300mW,样品量20μL。川穹嗪质量浓度在5~200mg/mL与峰强具有较好的线性关系(R^2=0.9251)。该方法精密度、重现性和准确度均较好,精密度在2.3%~3.6%,重复性在1.6%~3.2%,加标回收率在80.5%~87.2%。拉曼光谱快速检测方法能满足实验室及现场快速检测要求,实验结果可用于山西老陈醋醋龄的检测。

成像光谱技术在土地利用动态遥感监测中的应用研究

随着数字化调查技术的发展,国土资源管理对土地利用动态遥感监测提出了更高的要求,目前主要采用的多光谱数据由于受光谱分辨率限制以及“同谱异物,同物异谱”现象的影响,难以满足管理需要。成像光谱数据具有较高光谱分辨率,在类别细分方面具有一定的优势,在当前土地利用动态遥感监测中具有一定的应用潜质。该文针对成像光谱数据特点,探索了与成像光谱数据相适应的土地利用动态遥感监测方法,提出了异常光谱检测法,该方法在试验区应用中取得了良好效果。

铁矿石中全铁含量的检测技术研究

钢铁材料是人类社会发展依赖的重要基础物质,推动钢铁行业在促进国民经济发展方面有着重要作用。而全铁含量检测技术是铁矿石提炼中的重要技术应用,推动全铁含量检测技术发展对于钢铁行业的发展意义重大。基于此,本文将对铁矿石中全铁含量的检测技术进行了深入的分析探讨,旨在促进全铁检测准确性的提高,从而能够更好地推动我国钢铁行业更好发展。

有机磷类农药残留的检测技术

近年来,随着农业生产规模的扩大,各类农药使用量不断上升,在各类农药中,有机磷农药的适用范围较广、毒性较大,如果人类误食含有有机磷农药残留的食品就会发生中毒事件。基于此,本文先分析了有机磷类农药残留的危害,然后提出了有机磷类农药残留的检测技术,如快速检测法、光谱检测法、色谱检测法与高效液相色谱法等,以期为农药残留检测工作提供借鉴与参考。

水中有机污染物的化学检测技术探究

以净化水体环境为目标,针对水中有机污染物的检测进行分析。对于水中的污染物进行检测、处理,是非常重要的一个环节,需要在检测前,做好污染物来源的介绍,并详细说明其可能导致的问题。其次介绍化学检测技术中的综合检测法、直接鉴定法,在水中污染物检测中的应用,明确不同检测方法在实际应用中需要注意的要点。最后分别从提前准备检测样品、应用萃取技术两个方面提出优化建议,充分发挥化学检测技术的优势,提高水中有机污染物检测效率和准确性,了解水体环境中包含污染物的成分、结构等关键信息,提出针对性的污染物处理、解决办法,改善水体环境,为我国水资源净化、生态环境保护工作积累经验。

废水中重金属的检测方法分析

随着科技的发展,人们生活品质的提高,无论是生活废水还是工业废水都是越来越多,因此,废水的检测方法同样需要加强。本文通过对废水中的重金属检测方法进行分析,提出个人观点,希望为关注废水中重金属检测方法的人群带来帮助。

高精度光纤光栅振动解调系统研究与应用

为实现工程系统中对振动信号的检测,提出了一种基于衍射光栅的光纤布拉格光栅(FBG)振动解调系统。解调系统通过色散成像原理获取传感器反射光谱,由所设计的嵌入式单元进行信号处理,并通过专用的上位机解调软件完成数据处理与分析。将系统封装为解调仪器,能实际应用于振动信号的探测。所设计的系统波长解调范围为1525~1570 nm,波长重复性可达±1 pm,分辨率为0.5 pm,可实现8通道复用测量,最高光谱解调速度可达10 kHz。实验结果表明,该FBG振动解调系统能够高精度测量不同频率与幅度的振动信号,最小可探测应变约为0.319με/Hz^(1/2),在结构安全监测等领域具有重要的应用前景。

Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry

AIM： To detect the new serum biomarkers for colorectal cancer （CRC） by serum protein profiling with surfaceenhanced laser desorption ionisation - time of flight mass spectrometry （SELDI-TOF MS）. METHODS： Two independent serum sample sets were analysed separately with the ProteinChip technology （set A： 40 CRC ＋ 49 healthy controls; set B： 37 CRC ＋ 31 healthy controls）, using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. RESULTS： Mass-to-charge ratios （m/z） 3.1×10^3, 3.3× 10^3, 4.5×10^3, 6.6×10^3 and 28×10^3 were used as classitiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%.Host of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3× 10^3, main classifier in most trees, was a doubly charged form of the 6.6× 10^3-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1×10^3 was identified as an N-terminal fragment of albumin, and m/z 28× 10^3 as apolipoprotein A-I. CONCLUSION： SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Analysis of volatile chemical components of Radix Paeoniae Rubra by gas chromatography-mass spectrometry and chemometric resolution

The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results show that 38 volatile chemical components of RPR are determined, accounting for 95.21% of total contents of volatile chemical components of RPR. The main volatile chemical components of RPR are (Z, Z)-9,12-octadecadienoic acid, n-hexadecanoic acid, 2-hydroxy- benzaldehyde, 1-(2-hydroxy-4-methoxyphenyl)-ethanone, 6,6-dimethyl-bicyclo[3.1.1] heptane-2-methanol, 4,7-dimethyl-benzofuran, 4-(1-methylethenyl)-1-cyclohexene-1-carboxaldehyde, and cyclohexadecane.

Analysis of variabilities of serum proteomic spectra in patients with gastric cancer before and after operation

AIM： To study the variabilities of serum proteomic spectra in patients with gastric cancer before and after operation in order to detect the specific protein markers that can be used for quick diagnosis of gastric cancer. METHODS： Proteomic spectra of 46 serum samples from patients with gastric cancer before and after operation and 40 from normal individuals were generated by IMAC-Cu protein chip and surface-enhanced laser desorption/ionization time of flight mass spectrometry. RESULTS： Fourteen differentially expressed proteins in serum were screened by analysis of proteomic spectra of preoperative patients and normal individuals. We obtained 4 proteins （heat shock protein 27, glucoseregulated protein, prohibitin, protein disulfide isomerase A3） making up marker pattern which was able to class the patient-team and normal-team. These marker patterns yielded 95.7% sensitivity and 92.5% specificity, respectively. The proteins over-expressed in serum of preoperative patients were obviously down-regulated. CONCLUSION： Specific protein markers of gastric cancer can be used for the quick diagnosis of gastric cancer and judgment of prognosis. SELDI-TOF-MS is a useful tool for the detection and identification of new protein markers in serum.

Determination of fluorinated quinolone antibacterials by ion chromatography with fluorescence detection

For preparing fluorinated quinolone antibiotic medicine locally used in stomatology, simultaneous determination of norfloxacin, ciprofloxacin, and enoxacin was carried out by multiphase ion chromatography with fluorescence detection. Quinolone antibiotics were separated by Dionex OmniPac PAX-500 column with an eluent of 15 mmol/L H2SO4 and 35% methanol （v/v） at a flow-rate of 1.0 ml/min and detected with fluorescence with excitation and emission wave lengths of 347 ran and 420 ran respectively. The detection limits （S/N=3） of norfloxacin, ciprofloxacin and enoxacin were 50, 105 and 80 ng/ml respectively. The relative standard deviations of retention time, peak area and peak height were less than 1.1% and good linear relationship resulted. The developed method was applied to pharmaceutical formulations and biological fluids.

Comparison Between MIR and NIR Spectroscopic Techniques for the Determination of Fat and Protein Contents in Milk

To compare mid-infrared(MIR)and near-infrared(NIR)spectroscopies for the determination of the fat and protein contents in milk,the same sample sets with varying concentrations of fat and protein were measured in the MIR range of 3 200-700 cm-1 and NIR range of 9 000-4 000 cm-1.The spectral features in the two regions were analyzed.The MIR spectra of milk were characteristic due to the MIR inherent molecular specificity,whereas the NIR spectra were relatively characterless due to the NIR low selectivity.Partial least squares(PLS)regression models for fat and protein were developed by using both MIR and NIR spectra.MIR data with no pretreatment gave better results than NIR data.The square correlation coefficient(R2)and the root mean square error of prediction(RMSEP)were 0.98 and 0.10 g/dL for fat and 0.97 and 0.11 g/dL for protein.With NIR techniques,satisfactory results were not obtained with raw data.However,NIR data after pretreatment gave similarly good results to the ones using MIR method.This paper indicates that either of the MIR and NIR spectral methods is reliable for the determination of the fat and protein contents.

Analysis of Sucrose Esters with Long Acyl Chain by Coupling of HPLC-ELSD with ESI-MS System

The analysis of sucrose esters with long acyl chain by improved high performance liquid chromatographic method with evaporative light scattering detection （HPLC-ELSD） and electrospray ionization mass spectrum （ESI-MS） is investigated. The improved HPLC-ELSD method for the separation and quantitation of commercial and synthesized sucrose esters is described. Samples are analyzed by means of a reversed-phase （RP） HPLC using a Hypersil C8 column （250 mm× 4.6 mm, 5 μm particle size） with methanol-tetrahydrofuran （vo）ume ratio of 90 ： 10） and water under gradientcondition as the mobile phase, in which the flow rate is 1.0 ml·min^-1 and the column temperature is set at 40℃. This procedure provides a complete separation and determination ot monoester, diester, triester and higher esters with different acyl chain lengths in each fraction by a single run, in combination with the ESI-MS technology. With this method, it is possible to determine the approximate compositions of monoto polyesters in one analysis and quantitate pure positional isomers precisely using an external standard method. It is found that the method of ESI-MS coupling with HPLC system for the analysis of sucrose esters is straight forward, rapid and inexpensive, and can be readily applied in synthesis, purification and structure studies.

Quantitative Surface Chirality Detection with Sum Frequency Generation Vibrational Spectroscopy： Twin Polarization Angle Approach

Here we report a novel twin polarization angle （TPA） approach in the quantitative chirality detection with the surface sum-frequency generation vibrational spectroscopy （SFG-VS）. Generally, the achiral contribution dominates the surface SFG-VS signal, and the pure chiral signal is usually two or three orders of magnitude smaller. Therefore, it has been difficult to make quantitative detection and analysis of the chiral contributions to the surface SFG- VS signal. In the TPA method, by varying together the polarization angles of the incoming visible light and the sum frequency signal at fixed s or p polarization of the incoming infrared beam, the polarization dependent SFG signal can give not only direct signature of the chiral contribution in the total SFG-VS signal, but also the accurate measurement of the chiral and achiral components in the surface SFG signal. The general description of the TPA method is presented and the experiment test of the TPA approach is also presented for the SFG-VS from the S- and R-limonene chiral liquid surfaces. The most accurate degree of chiral excess values thus obtained for the 2878 cm^-1 spectral peak of the S- and R-limonene liquid surfaces are （23.7±0.4）% and （-25.4±1.3）%, respectively.

Automatic segmentation of Colon Cancer Cells Based on Active Contour Method： A New Approach

Automatic interpretation of the images of colon cell biopsies requires automatic segmentation of these cells in the image obtained. The active contour method for image segmentation is a well known method for automatic detection of the cell contour. However, the application of this method on colon cell images was not effective. In this paper, the authors have proposed a new technique to reduce the analysis time needed to detect cells in a given image. This technique is based on the active contour method but now using a progressive division of the dimensions of the image to achieve convergence. The model proposed succeeded in detecting cells whose boundaries are not necessarily defined by a gradient. The initial curve can be anywhere in the image, and interior contours can be automatically detected. The developed algorithm was successfully applied on textured multispectral images of three types of cells, including benign hyperplasia （BH）, intraepithelial neoplasia （IN）, and carcinoma （Ca） cells.

Highly Effective Detection of Amitraz in Honey by Using Surface-Enhanced Raman Scattering Spectroscopy Coupled with Chemometric Methods

As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive, rapid, and environmentally friendly surface-enhanced Raman spectroscopy method (SERS) was developed for the determination of trace amount of amitraz in honey with the use of silver nanorod (AgNR) array substrate. The AgNR array substrate fabricated by an oblique angle deposition technique exhibited an excellent SERS activity with an enhancement factor of -10^7. Density function theory was employed to assign the characteristic peak of amitraz. The detection of amitraz was further explored and amitraz in honey at concentrations as low as 0.08 mg/kg can be identified. Specifically, partial least square regression analysis was employed to correlate the SERS spectra in full-wavelength with Camitraz to afford a multiple-quantitative amitraz predicting model. Preliminary results show that the predicted concentrations of amitraz in honey samples are in good agreement with their real concentrations. Compared with the conventional univariate quantitative model based on single peak’s intensity, the proposed multiple-quantitative predicting model integrates all the characteristic peaks of amitraz, thus offering an improved detecting accuracy and anti-interference ability.