Using near-infrared reflectance spectroscopy to predict physical parameters of beef

The objective of this study was to develop near-infrared reflectance spectroscopy models for predicting the physical parameters of beef from commercial cuts. Four hundred and forty-two minced beef samples from various commercial cuts of two cattle breeds were used for the modeling process and randomly divided into two subsets: a calibration set and an independent prediction set (75 vs. 25%). Reflectance spectra (1000–1800?nm) were collected from both subsets of samples, and calibration models were built using partial least square regression on the calibration set of samples. Different mathematical pretreatments were tested and mean centering or multiplicative scatter correction combined with first-derivative preprocessing gave the best calibration models on all the beef physical traits. Based on the selected calibration equations, the coefficients of determination in calibration and prediction for Warner-Bratzler shear force, pH, color L*, and a* were higher than 0.60, which means models in the calibration were acceptable. However, the ratio performance deviation for all parameters was less than 2.0, indicating that the prediction abilities on independent validation set were not adequate for routine analysis. Further studies are required to establish more robust models for practical application of using near-infrared reflectance spectroscopy to predict physical traits of beef.     

Rapid evaluation of the salt content of canned sardines in brine using near-infrared diffuse reflectance spectroscopy

ABSTRACT

In this study, the evaluation of the salt content of canned sardines in brine using near-infrared (NIR) spectroscopy with a Fourier transform NIR spectrometer in diffuse reflectance mode over a range of 12,500–4000?cm^?1 was investigated. The reference salt content of the samples was measured using an autotitrator. The optimum partial least squares regression model was developed using vector normalization spectra in the ranges of 9403.8–5446.3?cm^?1 and 4605.4–4242.9?cm^?1 with seven factors. The model provided a coefficient of determination for a prediction of 0.82, a root mean square error of prediction of 0.069%, a bias of ?0.019%, and a ratio of prediction deviation of 2.5. NIR spectroscopy has great potential as an alternative method for measuring the salt content of canned sardines in brine, and the calibration model is useful for the off-line quality control of canned sardines in brine processing. In addition, the oxygen–hydrogen bond stretch and deformation and the carbon–hydrogen bond stretch and deformation had obvious effects on the prediction of the salt content of canned sardines in brine.     

Dispersive liquid–liquid microextraction based on solidification of floating organic drop for separation and preconcentration of malachite green before its determination by flow injection spectrophotometry

ABSTRACT

A simple and fast dispersive liquid–liquid microextraction based on solidification of floating organic drop has been developed for the separation and preconcentration of malachite green in water samples prior to its determination by flow injection spectrophotometry. Sodium lauryl sulfate, an anionic surfactant, was used for the ion-pair formation with malachite green. The factors affecting the ion-pair formation and extraction were optimized. Under the optimized conditions (volume of 1-undecanol as the extraction solvent, 40 μL; the volume of ethanol as the disperser solvent, 100 μL; sodium lauryl sulfate concentration, 7.5 × 10^?7 mol L^?1, and the pH of the sample, ～3.0), the calibration graph was linear over the range of 0.8–25 µg L^?1 with the detection limit of 0.3 µg L^?1 and the preconcentration factor of 750. The relative standard deviation at 7 µg L^?1 (n = 6) was found to be 2.1%. The developed method was successfully applied to the determination of malachite green in river water and fish farming water samples.     

Near-infrared spectroscopy to assess typhaneoside and isorhamnetin-3-O-glucoside in different processed products of pollen typhae

With the ever increasing importance of testing drug quality, rapid analytical methods are needed for supervision of Chinese herbal medicines. Near-infrared spectroscopy is one of the most powerful tools in quality assessment of Chinese herbal medicines. In this work, near-infrared spectroscopy was applied to develop a rapid method for quantitative determination of typhaneoside and isorhamnetin-3-O-glucoside in different processed products of Pollen Typhae. A total of 71 batches of samples were collected from different regions in China. After acquisition of near-infrared spectra, different pre-processing methods were compared, and a competitive adaptive reweighted sampling algorithm was used to perform the variable selection. Then a partial least squares regression algorithm was applied to build the quantitative models. The root mean square error of calibration, root mean square error of cross validation, and root mean square error of prediction were 0.0190, 0.0364, and 0.0158%, respectively, for a quantitative model of typhaneoside. The root mean square error of calibration, root mean square error of cross validation, and root mean square error of prediction were 0.0190, 0.0377, and 0.0170%, respectively, for a quantitative model of isorhamnetin-3-O-glucoside. Moreover, the relative prediction deviation values of both quantitative models were larger than 3, indicating good performance of the partial least squares (PLS) models. The results demonstrated that high accuracy prediction of typhaneoside and isorhamnetin-3-O-glucoside could be obtained by near-infrared spectroscopy, to allow an alternative method for quality assessment of different processed products of Pollen Typhae.     

Nondestructive Quantification of Foliar Chlorophyll in an Apple Orchard by Visible/Near-Infrared Reflectance Spectroscopy and Partial Least Squares

Chlorophylls respond rapidly to the current physiological status of a tree and reflect nutrient availability. Visible/near-infrared spectroscopy was attempted to determine foliar chlorophyll content in an apple orchard. Backward interval partial least squares and genetic algorithms were sequentially applied to select an optimized spectral interval and an optimized combination of spectral regions selected from informative regions in model calibration. Backward interval partial least squares was used to remove the noninformative regions, which significantly reduced the number of variables. The subsequent application of genetic algorithms-partial least squares to this reduced domain could lead to an efficient and refined model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and the correlation coefficient (R _c ) in the calibration set, and was then tested by root mean square error of prediction (RMSEP) and the correlation coefficient (R _p ) in the prediction set. The optimal backward interval partial least squares-genetic algorithms model was obtained with 5 partial least squares factors with 3 spectral regions and 71 variables selected. The measurement results of the final model were achieved as follows: RMSEC = 0.26, R _c  = 0.91 in the calibration set; and RMSEP = 0.22, R _p  = 0.91 in the prediction set. This experiment showed that visible/near-infrared spectroscopy and backward interval partial least squares-genetic algorithms are useful tools for nondestructively assessing foliar chlorophyll content and may have potential application for field assessments in decision-making and operational fertilizer management programs for apple orchards.     

Evaluation of the Mooney Viscosity of Natural Rubber by Near‐Infrared Spectroscopy

Abstract

The direct near‐infrared spectroscopic reflectance measurements of prevulcanized natural rubber (brown crepe) was employed for determination of its Mooney viscosity. NIR reflectance spectra were obtained for a total of 100 samples whose Mooney viscosity (VM in the range 68–95 units) have been determined by the standard reference procedure using a commercial computerized Mooney viscometer. These samples were employed as the raw material or were treated to achieve better homogenization. A Fourier transform near infrared (FT‐NIR) spectrophotometer was employed, and the reflectance spectra were obtained with resolution of 4 cm^?1 in the range 4000–10,000 cm^?1 as an average of 75 scans. The samples were split in a calibration set containing 70 samples and in an external validation set consisting of the remaining 30 samples. The calibration and validation spectra sets were treated to correct for baseline shift, further transformed by first derivative and finally modeled by partial least squares (PLS) employing four latent variables. The model was evaluated with the external sample test set, and a RMSEP of 3.6 and 3.9 units of Mooney viscosity were obtained for homogenized and nonhomogenized samples, respectively. The NIR method is capable of determining the Mooney viscosity in few minutes in the non‐pretreated sample with an error that is satisfactory for quality control of natural rubber destined for automobile tire manufacturing.     

基于小波压缩的马铃薯全粉还原糖近红外光谱检测研究

为探讨小波压缩算法结合近红外光谱技术在马铃薯全粉还原糖含量检测中的可行性,采用傅里叶变换近红外光谱仪采集了250份马铃薯全粉样品的近红外光谱。分别优化了消失矩、小波系数和主成分因子数,优化结果为10,100和20。基于db小波函数将1 501个马铃薯全粉的近红外光谱变量压缩成100个小波系数。分别以1 501个光谱变量和100个小波系数为变量分别建立了偏最小二乘(PLS)校正模型。以62个未参与建模的样品作为预测集,考察模型的预测能力。经比较,小波压缩结合PLS的校正模型预测结果最优,模型预测相关系数为0.98,预测均方根误差为0.181%。实验结果表明小波压缩算法结合近红外光谱技术有效地保留了有效光谱信息,实现了光谱数据降维,简化了马铃薯全粉还原糖PLS校正模型,提高了模型的预测能力。     

Rapid and Direct Spectrofluorometric and Chemometrics Methods for the Simultaneous Determination of Two Dansyl Derivatives

ABSTRACT

In this study the simultaneous molecular spectrofluorometric determination of ultratrace amounts of two dansyl chloride derivatives, DMNPS (5-(dimethylamino)naphthalene-1-sulfonyl 4-phenylsemicarbazide) and DMNPH (2-(5-(dimethylamino)naphthalen-1-ylsulfonyl)-N-phenylhydrazinecarbothioamide), was accomplished using a genetic algorithm joint partial least squares (GA-PLS) technique that leads to very low detection limits (lower than 10^?6 mol/L) The linear dynamic ranges of the compounds were 1–6 µ mol L^?1 and 1–7 µ mol L^?1 for DMNPS and DMNPH, respectively. Quantification was performed using the emission wavelength range from 360 to 600 nm with an optimum calibration sample number of 25 and prediction sample number of 7. The technique was proved to be beneficial.     

A Novel Method for the Assessment of Cortisol Hormone in Different Body Fluids Using A New Photo Probe Thiazole Derivative

A low cost and accurate method for the detection and analytical determination of the cortisol in pharmaceutical preparation, blood serum and urine was developed. The method was based upon the enhancement of fluorescence intensity of the band at 424 nm of the photo probe by different cortisol concentrations in acetonitrile at (pH 5.7, λ_ex?=?320 nm). The influence of the different parameters, e.g. pH, solvent, cortisol concentration and foreign ions concentrations that control the enhancement process of fluorescence intensity of the band of photo probe was critically investigated. The remarkable enhancement of the fluorescence intensity at 424 nm in acetonitrile by various concentrations of cortisol was successfully used as a photo- probe for the assessment of cortisol concentration. The calibration plot was achieved over the concentration range 8.0?×?10^?6–5.5?×?10^?9 mol L^?1 cortisol with a correlation coefficient of 0.998 and a detection limit of 4.7?×?10^?9 mol L^?1. The developed method is simple and proceeds without practical artifacts compared to the other determination methods.     

Determination of dimethoate and phosmet pesticides with surface-enhanced Raman spectroscopy

ABSTRACT

Surface-enhanced Raman spectroscopy spectra of dimethoate and phosmet pesticides were recorded using a Klarite substrate. Significant enhancements were achieved with dimethoate over a concentration range of 0.5–10 µg mL^?1 and phosmet over a concentration range of 0.1–10 µg mL^?1. The best prediction model for dimethoate pesticide was achieved with a correlation coefficient of 0.940 and a root mean square error of prediction of 0.864 µg mL^?1, with the first derivative and standard normalized variate data preprocessing, and the best prediction model of phosmet pesticide was achieved with a correlation coefficient of 0.949 and a root mean square error of prediction of 0.741 µg mL^?1 with the first derivative data preprocessing. Our study shows that pesticides, including dimethoate and phosmet, could be quantitatively measured at as low as 0.5 µg mL^?1 level using surface-enhanced Raman technology coupled with a Klarite substrate and the results indicated that surface-enhanced Raman spectroscopy with a Klarite substrate has potential for the analysis of dimethoate and phosmet residues.     

Rapid nondestructive evaluation of duck meat pH and color using visible and near-infrared reflectance spectroscopy

In the present study, visible and near-infrared reflectance spectroscopy were applied to predict quality attributes of duck breast meat. The real color (expressed as lightness, redness, and yellowness) and pH of duck samples were recorded using traditional contact methods and then modeled with their corresponding spectral data by partial least square regression. Before the establishment of prediction models, three different spectral preprocessing methods including first derivative, standard normalized variate, and Savitzky–Golay smoothing were used. Compared to the models obtained from original spectral data set, the predictive capabilities of models based on the spectra after preprocessing were improved effectively. As a result, the determination coefficient of calibration set and prediction set of the best models for lightness, redness, yellowness, and pH parameters were 0.96 and 0.85, 0.94 and 0.94, 0.96 and 0.94, 0.81 and 0.76, respectively. Results demonstrated that visible and near-infrared spectroscopy can become a useful tool for rapid prediction of duck color and pH quality attributes.     

A sensitive amperometric detection of dopamine agonist drug pramipexole at functionalized multi-walled carbon nanotubes (f-MWCNTs) modified electrode

The electrochemical detection of dopaminergic agonist drug pramipexole dihydrochloride monohydrate (PPX) has been investigated by cyclic voltammetric (CV) and amperometric i–t techniques at functionalized multi-walled carbon nanotubes-modified glassy carbon electrode. For the first time, a sensitive and rapid electrochemical method was developed for the determination of PPX. The surface morphological characteristics of the proposed electrode have been studied by using transmission electron microscopy (TEM); further, electrochemical impedance spectroscopy (EIS) and Fourier transform infrared spectroscopy (FTIR) have been employed. PPX shows an irreversible anodic peak, which may be ascribed to the oxidation of the –NH groups of PPX. The proposed method was showing good sensitivity of 0.993 μA μM^?1 cm^?2 with a linear range of 5 to 340 μM by amperometric i–t and CV technique shows a linear range of 12.5 to 313 μM with a sensitivity of 1.92 μA μM^?1 cm^?2. The recovery of PPX from blood serum samples was found 100.6 and 98.9 %, respectively. Furthermore, the proposed method has been demonstrated for the determination of PPX in commercially available pharmaceutical samples and good agreement of results obtained.     

Electrochemical synthesis and performance of PANI electrode material for electrochemical capacitor

Polyaniline (PANI) electrode materials doped with sulfuric acid (H₂SO₄) were prepared by cyclic voltammetry (CV) method in different reaction conditions. The structure and morphology of PANI samples were characterized by Fourier transform infrared spectroscopy and scanning electron microscope. The electrochemical properties of PANI samples were studied by CV, galvanostatic charge/discharge, and electrochemical impedance spectroscopy tests. Additionally, the effects of reaction conditions including aniline concentration, voltammetry scan rate, and deposition time on the morphology and properties of PANI samples were investigated in detail. The results showed that the PANI synthesized under the optimal conditions of 0.2 mol?L^?1 aniline, scan rate 20 mV?s^?1, and deposition time 50 min is in the form of nanorods with a cross-linked network structure. It exhibits an outstanding capacitive performance with good cycle stability and high rate performance. Besides, the specific capacitance of PANI is as high as 757 F?g^?1.     

近红外光谱技术快速测定农药有效成分的研究

农药有效成分含量不足和农药有效成分滥用是农药质量不合格的最主要问题,但是缺乏农药的快速现场分析方法。采用傅里叶近红外光谱技术结合偏最小二乘法(PLS),定量分析了乳油中有效成分高盖的含量,模型的决定系数R2大于0.999 9,SEC小于0.019,SEP小于0.030;同时对影响模型的因素进行了研究,并用实际样品进行了验证。结果表明：近红外光谱技术可以准确地定量分析农药乳油中有效成分含量,仪器分辨率、助剂含量变化对模型的影响不显著。近红外光谱法测量商品农药制剂中有效成分的含量,方便快速,特别适合现场、在线分析,对生产企业的连续在线检测、监督部门进行农药质量控制和农产品安全具有重要意义。     

Hydrodynamic Sequential Injection Spectrophotometric System for Determination of Manganese in Soil

ABSTRACT

A novel hydrodynamic sequential injection (HSI) spectrophotometric system for determination of manganese was developed. It is based on the complexation of Mn(II) with formaldoxime in basic solution (pH ≥ 10) to produce product that could be monitored spectrophotometrically at 450 nm. Based on the HSI concept, both sample and reagents were aspirated through solenoid valves to fill a defined volumes conduit between 3-way connectors connected in series, forming stacked zones of solutions similar to those in normal SI. The concept was successfully demonstrated for manganese determination. A linear calibration graph over a range of 0.5 to 30 mg L^?1 Mn(II) with a detection limit of 0.2 mg L^?1 was obtained. Relative standard deviations for 11 replicated injections of 5 and 20 mg Mn L^?1 were 5.6% and 2.4%, respectively. A sample throughput of 45 h^?1 was achieved. The results from investigation of exchangeable manganese in soil samples by the developed method were found to be in good agreement with the results obtained by a batch spectrophotometric method, despite the proposed system employed simpler and more cost-effective devices/instruments, had higher degrees of automation with full microcontroller control of the operation, and consumed smaller amounts of chemicals (250 µL each of hydroxylamine, sample, and formaldoxime solutions and 2.5 mL of buffer carrier solution per operation cycle).     

Determination of Cr in water solution by laser-induced breakdown spectroscopy with different univariate calibration models

In order to prove the feasibility of laser-induced breakdown spectroscopy (LIBS) in measuring toxic metals Cr in water solution, a series of potassium bichromate standard solutions were prepared in the lab. The characteristic line intensity of Cromium (Cr) element at 357.87, 359.35, 360.53, 425.43, 427.48, and 428.97 nm was taken to build up the correlation with concentration. The indexes of relative standard deviation, intercept, slope, R ² (coefficient of determination), and root mean square error of calibration were selected to verify the precision and accuracy of models. The comprehensive results showed that the 425.43 nm line had better superiority than other lines. And the detection limit of 6 ug/ml and repeatability of 3 % are reported. To improve the model accuracy further, the intensity ratio of single 425.43 nm line to the whole spectrum was extracted. And a linear relationship between the intensity ratio and the element Cr concentration was constructed. The results demonstrated the intensity ratio calibration had better accuracy than single line calibration, especially after smoothing. To verify the accuracy of prediction, the 100 ug/ml concentration sample was used as prediction sample. The relative error values are 13.2, 11.7, and 10.8 % for single line calibration, intensity ratio calibration with raw data, and by use of smooth processing data, respectively. The results further indicated that the intensity ratio calibration improved the accuracy of measurement than single line calibration. It is worth mentioning that the application of LIBS aiming the direct analysis of heavy metals in water is a great challenge that still needs efforts for its development and validation.     

A calix[4]arene derivative-doped perchlorate-selective membrane electrodes with/without multi-walled carbon nanotubes

In this study, poly (vinyl chloride)(PVC) membrane electrodes with/without multi-walled carbon nanotubes (MWCNTs) based on a calix[4]arene derivative for perchlorate ion were described. The influence of membrane composition, pH, conditioning solution on the potentiometric response of the electrodes was investigated. Perchlorate-selective PVC membrane electrode exhibited a slope of 47.8 ± 0.6 mV/pClO₄ in the range of 1.0 × 10^?7–1.0 × 10^?1 mol L^?1at pH 4.0 while the coated Pt electrodes with MWCNT-OH, MWCNT-COOH and MWCNT displayed slopes of 46.1 ± 0.7 mV/pClO₄ (5.0 × 10^?6–1.0 × 10^?1 mol L^?1), 50.4 ± 1.9 mV/pClO₄ (1.0 × 10^?6–1.0 × 10^?1 mol L^?1) and 44.4 ± 0.3 mV/pClO₄ (1.0 × 10^?5–1.0 × 10^?1 mol L^?1), respectively. Other response characteristics of these electrodes such as response time, lifetime and detection limit were identified, and the selectivity coefficients towards various anions were calculated by separate solution method. Moreover, the perchlorate-selective electrodes described here were successfully used as an indicator electrode for the determination of perchlorate in real samples such as tap water, river water and human urine by direct calibration method.     

近红外光谱法测定不同产地黄芪中毛蕊异黄酮葡萄糖苷和黄芪甲苷含量

采用近红外漫反射光谱法对黄芪中毛蕊异黄酮葡萄糖苷和黄芪甲苷的含量进行快速无损检测。以液相色谱质谱联用分析值为参比,采用偏最小二乘法建立黄芪中毛蕊异黄酮葡萄糖苷和黄芪甲苷的定量分析模型。结果显示,毛蕊异黄酮葡萄糖苷近红外光谱经多元散射校正(MSC)+一阶导数+Savitzky-Golay卷积平滑预处理后模型最优,模型参数R2为0.826 6,RMSEP值为0.022 7,校正集R2为0.863 5,RMSEC值为0.019 0;黄芪甲苷近红外光谱经二阶导数+Savitzky-Golay卷积平滑预处理后模型最优,模型参数R2为0.854 8,RMSEP值为0.006 41,校正集R2为0.796 3,RMSEC值为0.007 99。近红外光谱技术结合偏最小二乘法可快速、准确的对黄芪中毛蕊异黄酮葡萄糖苷和黄芪甲苷的含量进行检测。此外,通过主成分分析,发现甘肃产黄芪与其他产地黄芪差异不大,排除甘肃产黄芪后,山西、四川和吉林的样本区分度较高。     

应用近红外光谱法建立伤疖膏制备过程中黄芩苷含量模型

建立一种伤疖膏制备过程提取液中黄芩苷动态含量快速测定的近红外光谱分析方法,近红外透射光谱法扫描得到65组伤疖膏制备过程中提取液的近红外光谱图,以提取液中黄芩苷的HPLC测量值作为对照值,采用偏最小二乘回归算法(PLSR)建立NIR光谱与对照值的校正模型。校正模型主成分数为8,交叉验证均方根差(RMSECV)为0.006 8,相关系数(r)为0.999 1。应用校正模型对预测集的30组样品进行黄芩苷含量预测,所得预测均方根差(RMSEP)为0.009 2,r为0.998 7。结果表明,该方法快速、准确,为复方膏剂制备过程中化学成分快速定量和质量控制提供了方法和依据。     

Online Copper Removal for Selenium Determination by Hydride Generation–Inductively Coupled Plasma Optical Emission Spectrometry

Abstract

Selenium determination in samples with a high copper content by hydride generation–inductively coupled plasma optical emission spectrometry (HG‐ICP‐OES) after online copper removal and selenium (VI) reduction is described. An activated carbon minicolumn was used for the retention of copper and its subsequent separation of Se. Se(VI) was then online reduced by heating into a PTFE coiled reactor with 12 M HCl. The analyte was introduced into a water stream containing sodium tetrahydroborate (NaBH₄) in order to generate selenium hydride (H₂Se). The detection limit (DL) obtained was 0.8 µg L^?1, and the precision, expressed by the relative standard deviation (RSD), was 2.5% (n=10; 10 µg L^?1 selenium level). The current method was applied to the Se determination in two copper reference materials, MBH‐39DK 3601 (with a Se content of 90 mg kg^?1) and MBH‐39 DK 3604 (with a Se content of 15 mg kg^?1).