Rapid Method For Quantitative Analysis Research Articles

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laser-induced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve (SC) and calibration-free laser-induced breakdown spectroscopy (CF-LIBS) technology to achieve synchronous, rapid, and accurate measurement of elements in a large number of samples, namely, SC-assisted CF-LIBS. Al alloy standard samples, divided into calibration and test samples, were applied to validate the proposed method. SC was built based on the characteristic line of Pb and Cr in the calibration sample, and the contents of Pb and Cr in the test sample were calculated with relative errors of 6% and 4%, respectively. SC built using Cr with multiple characteristic lines yielded better calculation results. The relative contents of ten elements in the test sample were calculated using CF-LIBS. Subsequently, the SC-assisted CF-LIBS was executed, with the majority of the calculation relative errors falling within the range of 2%–5%. Finally, the Al and Na contents of the Al alloy were predicted. The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples. Furthermore, this quantitative analysis method was successfully applied to soil and Astragalus samples, realizing an accurate calculation of the contents of multiple elements. Thus, it is important to advance the LIBS quantitative analysis and its related applications.

Rapid quantitative analysis of multiple rare earth elements in NdFeB alloys based on laser-induced breakdown spectroscopy (LIBS) and random forest (RF)

NdFeB material has excellent comprehensive magnetic properties, which plays a crucial role in the field of rare earth magnetic materials, and is one of the important basic materials to support modern high-tech industries. In the production of NdFeB alloys, the control of rare earth elements (REEs) is directly related to the quality and resource utilization efficiency of NdFeB materials. Therefore, the prediction of REEs content in NdFeB alloys is of great research significance and application value for the quality control of products, the enhancement of production efficiency and reduction of energy consumption by the rare earth material industry. In this study, a combination of laser-induced breakdown spectroscopy (LIBS) and random forest (RF) was used to investigate the quantitative analysis of four REEs (Nd, Pr, Tb and Dy) in NdFeB alloys. Firstly, the original LIBS spectra were screened by principal component analysis-mahalanobis distance (PCA-MD). Then, the effects of different data processing methods on the screened LIBS spectra were explored, and next, the feature variables were extracted from the preprocessed spectral data by the variable importance measurement (VIM). In order to further verify the prediction performance of the model, the prediction results of the RF models based on the different methods were compared. Finally, a PCA-VIM-RF calibration model was established on the basis of the optimized spectra, selected feature variables and parameters. Leave-one-out cross validation (LOOCV) was used to optimize the parameters of PCA-MD method, spectral preprocessing method and variable importance thresholds during the construction of the calibration model. The results show that the PCA-VIM-RF model has better prediction performance than the RF calibration model based on the raw spectra. For the PCA-VIM-RF calibration method of Nd, Pr, Tb and Dy elements, the values of R2CV are 0.9991, 0.9998, 0.9986, and 0.9984, respectively, the values of RMSECV are 0.06296%, 0.02788%, 0.04647% and 0.05252%, respectively. The values of R2P are 0.9508, 0.9975, 0.9691 and 0.9457, respectively, and the values of RMSEP are 0.6082%, 0.09205%, 0.5776% and 0.2631%, respectively.The above results indicate that LIBS combined with PCA-VIM-RF algorithm is a promising method for rapid quantitative analysis of REEs in NdFeB alloys without complicated sample preparation, which can provide some new ideas or strategies for the future research, development and quality control of rare earth materials.

Quality study of animal-derived traditional Chinese medicinal materials based on spectral technology: Calculus bovis as a case.

Calculus bovis (C. bovis) is a typical traditional Chinese medicine (TCM) derived from animals, which has a remarkable curative effect and high price. Rapid identification of C. bovis from different types was realized based on spectral technology, and a rapid quantitative analysis method for the main quality control indicator bilirubin was established. We conducted a supervised and unsupervised pattern recognition study on 44 batches of different types of C. bovis by five spectral pretreatment methods. Three variable selection methods were used to extract the essential information, and the partial least squares regression (PLSR) quantitative model of bilirubin by near-infrared (NIR) spectroscopy was constructed. The partial least squares discriminant analysis (PLS-DA) model could achieve 100% accuracy in identifying different types of C. bovis. The R2 of the NIR quantitative model was 0.979, which is close to 1, and the root mean square error of calibration (RMSEC) was 2.3515, indicating the good prediction ability of the model. The study was carried out to further improve the basic data of quality control of C. bovis and help the high-quality development of TCM derived from animals.

Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity

BackgroundThe clinical spectrum of acute SARS-CoV-2 infection ranges from an asymptomatic to life-threatening disease. Considering the broad spectrum of severity, reliable biomarkers are required for early risk stratification and prediction of clinical outcomes. Despite numerous efforts, no COVID-19-specific biomarker has been established to guide further diagnostic or even therapeutic approaches, most likely due to insufficient validation, methodical complexity, or economic factors. COVID-19-associated coagulopathy is a hallmark of the disease and is mainly attributed to dysregulated immunothrombosis. This process describes an intricate interplay of platelets, innate immune cells, the coagulation cascade, and the vascular endothelium leading to both micro- and macrothrombotic complications. In this context, increased levels of immunothrombotic components, including platelet and platelet-leukocyte aggregates, have been described and linked to COVID-19 severity.MethodsHere, we describe a label-free quantitative phase imaging approach, allowing the identification of cell-aggregates and their components at single-cell resolution within 30 min, which prospectively qualifies the method as point-of-care (POC) testing.ResultsWe find a significant association between the severity of COVID-19 and the amount of platelet and platelet-leukocyte aggregates. Additionally, we observe a linkage between severity, aggregate composition, and size distribution of platelets in aggregates.ConclusionsThis study presents a POC-compatible method for rapid quantitative analysis of blood cell aggregates in patients with COVID-19.

Rapid microRNA detection method based on DNA strand displacement for ovarian cancer cells.

The current cancer detection methods are heavily dependent on the component analysis of corresponding cancer antigens. There is a lack of effective and simple clinical methods of ovarian cancer screening, which hinders the early identification for ovarian cancer and its treatment. To develop a simple and rapid method for quantitative analysis of ovarian cancer, we developed a DNA strand displacement-based method and finished the rapid detection of miR-21 in ovarian cancer cells within 5 min by a one-step isothermal reaction. The fluorescence intensity trajectory had a good linear relationship with miR-21 concentrations in the range of 100 fM-100 nM, with a lower limit of 6.05 pM. This detection method is simple, faster, and accurate. Besides, it can be applied to detect the miRNA biomarkers of other cancers by changing the preset sequences of toehold.

Rapid quantitative analysis of rare earth elements Lu and Y in rare earth ores by laser induced breakdown spectroscopy combined with iPLS-VIP and partial least squares.

Rare earth ores are complex in composition and diverse in mineral composition, requiring high technical requirements for the selection of rare earth ores. It is of great significance to explore the on-site rapid detection and analysis methods of rare earth elements in rare earth ores. Laser induced breakdown spectroscopy (LIBS) is an important tool to detect rare earth ores, which can be used for in situ analyses without complicated sample preparation. In this study, a rapid quantitative analysis method for rare earth elements Lu and Y in rare earth ores was established by LIBS combined with an iPLS-VIP hybrid variable selection strategy and partial least squares (PLS) method. First, the LIBS spectra of 25 samples were studied using laser induced breakdown spectrometry. Second, taking the spectrum processed by wavelet transform (WT) as the input variables, PLS calibration models based on interval partial least squares (iPLS), variable importance projection (VIP) and iPLS-VIP hybrid variable selection were constructed to quantitatively analyze rare earth elements Lu and Y, respectively. The results show that the WT-iPLS-VIP-PLS calibration model has better prediction performance for rare earth elements Lu and Y, and the optimal coefficient of determination (R2) of Lu and Y were 0.9897 and 0.9833, the root mean square error (RMSE) were 0.8150 μg g-1 and 97.1047 μg g-1, and the mean relative error (MRE) were 0.0754 and 0.0766, respectively. It shows that LIBS technology combined with the iPLS-VIP and PLS calibration model provides a new method for in situ quantitative analysis of rare earth elements in rare earth ores.

Determination of Cabernet Sauvignon wine quality parameters in Chile by Absorbance-Transmission and fluorescence Excitation Emission Matrix (A-TEEM) spectroscopy

A-TEEM spectroscopy is presented as a novel rapid quantitative analysis method for 44 individual phenolic and basic wine chemistry compounds. To date no practical and combined analysis method for these recognized quality parameters important to the wine industry exists. The method was implemented in a Lambert-Beer linear concentration range to facilitate traceable absorbance and fluorescence spectral signatures. Both components were comparatively analyzed as single- and combined multi-block variable sets, and regressed against HPLC–DAD, UV–vis spectroscopy and other analytical reference data, using the Extreme Gradient Boost Regression (XGBR) and Partial Least Squares Regression (PLSR) algorithms. The approach was applied on 126 wines, and subsequently validated by a random split of 13% of the set and an additional independent set of 16 wines. XGBR with multi-block data organization systematically yielded the highest prediction accuracy and precision with respective overall valid fits indicated by mean R2 and relative bias of 0.94 ± 0.04 and 4.1 ± 1.8%.

A comprehensive strategy for quality evaluation of Wushe Zhiyang Pills by integrating UPLC-DAD fingerprint and multi-ingredients rapid quantitation with UPLC-MS/MS technology

Wushe Zhiyang Pills (WZP), a classical traditional Chinese medicine (TCM) formula, has been extensively used for the treatment of chronic urticaria and other relevant dermatologic diseases. In this study, a holistic method combining ultra-performance liquid chromatography coupled with diode array detector (UPLC-DAD) fingerprint and multi-components quantitative analysis was developed and validated for quality evaluation of WZP. As a result, a total of 34 characteristic peaks were screened to assess the chemical similarities of 16 batches of WZP samples. By coupling with a hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer, 163 compounds were identified or tentatively identified in WZP. Furthermore, a rapid quantitative analysis method based on ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) technique was optimized and validated for simultaneously determination of 16 chemical markers within 13 min in WZP. The developed UPLC-MS/MS approach was successfully employed for analysis of 16 batches of WZP samples. The proposed comprehensive method combining holistic chemical profile with notable target compounds has proved to be suitable for the systematical quality evaluation of WZP, which provides a feasible and efficient strategy to monitor the overall quality consistency of TCM formulae.

Analysis of Molar Substitution of Hydroxybutyl Group by Zeisel Reaction in Starch Ethers

A new etherified starch, δ-hydroxybutyl starch (δ-HBS), was prepared by utilising 4-chlorobutan-1-ol as the etherifying reagent. The method of Zeisel gas chromatography for the determination of the molar substitution was described. This technique offers a simple and rapid method for quantitative analysis with reproducible results. Meanwhile, the mechanism of the Zeisel reaction was also investigated.

Development and validation of UPLC method for quantitative determination of major bovine milk oligosaccharides and their heat stability

Bovine milk oligosaccharides (BMOs) and human milk oligosaccharides (HMOs) have similar functions. In this investigation, a simple and rapid quantitative analysis method of UPLC for BMOs concentration was proposed, and the heat stability of BMOs was also revealed. BMOs were separated on an Acquity UPLC® Glycan BEH amide column (2.1 mm × 150 mm, 1.7 μm) using 100 mm ammonium formate (pH 4.5) and 100% acetonitrile as mobile phase for gradient elution at a flow rate of 0.45 mL min−1. The potential in quantification of BMOs were satisfactorily validated in terms of linearity (R2 ≥ 0.9992), repeatability and intermediate precision (RSD ≤ 4.46%), and spike recovery (≥90.27%). For all investigated oligosaccharides, LOD ranged from 1.97 to 9.38 μg L−1 and LOQ values ranged between 6.84 and 31.25 μg L−1. In addition, BMOs did not degrade after heating at 45–100 °C for 10–120 min.

Rapid quantitative analysis of six flavonoids in licorice by ultra-performance convergence chromatography

Abstract Objective This study was to establish a rapid quantitative method for determination of six characteristic flavonoids, including licochalcone A (1), liquiritigenin (2), glabridin (3), isoliquiritigenin (4), liquiritoside (5), and isoliquiritoside (6) in licorice by a ultra-performance convergence chromatography (UPC2) apparatus equipped with a photodiode-array detector (PDA). Methods: The flavonoids studied were separated on an ACQUITY UPC2 TM Torus 2-PIC column (2.1 × 100 mm, 1.7 μm) using gradient elution (85:15–70:30) with a mobile phase consisting of CO2 and methanol: formic acid (99.8:0.2, v/v), back pressure of 2,000 psi, flow rate of 0.8 mL/min, and detection at 254 nm. This method was further applied for the analysis of the flavonoids present in 10 batches of licorice roots samples. Results: Good linearity (R2 = 0.9990–0.9998) was achieved and limits of detection (LOD) and quantification (LOQ) ranging from 0.12 to 0.49 µg/mL and 0.46 to 1.61 µg/mL, respectively. The relative standard deviations (RSD) for repeatability and reproducibility were 2.30–2.80% and 2.30–2.98%, respectively. The flavonoids distributed differently in Glycyrrhiza uralensis , Glycyrrhiza glabra, and Glycyrrhiza inflate . Conclusion: The established rapid quantitative analysis method was environment friendly and suitable to the quality control of species licorice.

A simple and rapid HPLC method for the quantitative determination of sodium oleate in flotation study

Sodium oleate (NaOL) is an important surfactant chemical used in the separation of oxide minerals by the froth flotation process. The adsorption capacity and the adsorption mechanism of NaOL on the mineral surface are important for understanding flotation behaviour. In this study, a simple, nontoxic and rapid quantitative analysis method of High Performance Liquid Chromatography (HPLC) for residual sodium oleate concentration was proposed and verified. The NaOL was identified in chromatogram by comparison with standard oleic acid. A linear range from 10 to 100 mg/l was observed, and the precision, accuracy, LOD and LOQ were evaluated.

Effects of pressure and composition on Raman spectra of CO-H2-CO2-CH4 mixtures.

There is great interest in the development of renewable and environmentally friendly fuel sources such as biogas and syngas for generation of heat and electricity. Raman spectroscopy is a promising method for rapid quantitative analysis of the composition of such gases. To improve the accuracy of the method, information is needed on changes in the spectra of the main components as a function of pressure and gas composition. In this work the spectral characteristics of the most intense peaks of methane, carbon monoxide, carbon dioxide and hydrogen in the range of 200-3800 cm-1 were investigated in the range of 1-25 bar for pure gases and binary mixtures. It has been revealed that, under these conditions, the change in the characteristics of pure rotational hydrogen lines is negligible, while the Q-branches of the main vibrational bands of methane, carbon monoxide and carbon dioxide shift to a few tenths of cm-1. The values of errors that can occur in the case of ignoring such changes in the spectra are estimated.

Simultaneous quantitative analysis of protein, carbohydrate and fat in nutritionally complete formulas of medical foods by near-infrared spectroscopy

A rapid, efficient, nondestructive and cost-effective method for simultaneous quantitative analysis of protein, carbohydrate and fat in nutritionally complete formulas of medical foods by Fourier transform near-infrared (FT-NIR) spectroscopy was developed. NIR spectra in the range of 3846–7692 cm−1 of 80 emulsion samples with different concentrations of three components were measured. The optimized spectral region was 4167–4878/5405–6452 cm−1. To enhance spectral features, NIR spectra were processed using a first derivative and smoothing method. Partial least squares regression (PLSR) was used to establish NIR models for protein, carbohydrate, fat and energy. The performances of the four models were evaluated by factors such as the values of correlation coefficient (r), root mean square error of prediction (RMSEV), root mean square error of calibration (RMSEC) and residual predictive deviation (RPD). The RMSEC of protein, carbohydrate, fat and energy was 0.29% (w/v), 0.71% (w/v), 0.30% (w/v) and 0.06 kcal/mL, respectively. The RMSEV was 0.29% (w/v), 0.50% (w/v), 0.24% (w/v) and 0.02 kcal/mL, respectively. The r value was 0.995, 0.968, 0.976 and 0.951, respectively. The RPD was 9.12, 4.44, 5.44 and 8.73, respectively. Furthermore, the four models were verified by cross and external validation. These results demonstrated that FT-NIR spectroscopy was a precise and rapid method for quantitative analysis of protein, carbohydrate and fat, and could be successfully applied to the determination of them in commercial medical foods.

Components Analysis of Biochar Based on Near Infrared Spectroscopy Technology

Abstract This study aims to establish a rapid quantitative analysis method for biochar based on near infrared spectroscopy (NIRS) technology. Near infrared spectra of 163 samples in the 10000–3800 cm–1 (1000–2632 nm) range were collected, and the contents of fixed carbon (FC), volatile matter (VM) and ash of samples were also analyzed. A partial least square (PLS) model for FC, VM and Ash was established after the model spectral ranges were optimized, the optimal factors were determined, and the raw spectra were pretreated by multiple scatter correction and second derivative (MSC + SD) method. Finally, the prediction performance of predictive model was evaluated. The results showed that the PLS model had a good prediction ability, and the predicted coefficient R2p of actual values vs prediction values for FC, VM and ash were 0.9423, 0.9517 and 0.9265, respectively. Root mean square error of prediction (RMSEP) was 0.1074, 0.1201 and 0.1243, and ratios of prediction to deviation (RPD) were 3.51, 4.28 and 2.03, respectively. The PLS model had good accuracy and precision for both of FC and VM, and could be used as a quantitative method for FC and VM contents analysis. Nevertheless, PLS model need to improve the precision for Ash analysis according to RPD value. This method provides a fast and effective technical means for the quantitative analysis of biochar components.

Geographical origin discrimination and polysaccharides quantitative analysis of Radix codonopsis with micro near-infrared spectrometer engine

At present, Tradition Chinese Medicine (TCM) industry in China is in the stage from the empirical development to industrial production. Near infrared (NIR) spectroscopy has been widely used in the quality control of TCM’s modernization with its characteristics including rapidness, nondestruction, simplicity, economy, and so on. In this study, as one type of a portable micro NIR spectrometer, Micro NIR 1700 was used to establish the qualitative models for identification of geographical region and authenticity of Radix codonopsis based on discriminant analysis (DA) method. Both of the DA models had better predictive ability with 100% accuracy. In addition, a method for rapid quantitative analysis of polysaccharide in Radix codonopsis was also developed based on Micro NIR 1700 spectrometer with partial least-squares (PLS) algorithm. In the PLS calibration model, the NIR spectra of samples were pretreated with different preprocessing methods and the spectral region was selected with different variable selection methods as well. The performance of the final PLS model was evaluated according to correlation coefficient of calibration ([Formula: see text]), correlation coefficient of prediction ([Formula: see text]), root mean squared error of cross validation (RMSECV), and root mean squared of prediction (RMSEP). The values of [Formula: see text], [Formula: see text], RMSECV, and RMSEP were 0.9775, 0.9602, 2.496, and 2.734[Formula: see text]g/mL, respectively. This work demonstrated that micro infrared spectrometer could be more convenient and rapid for quality control of Radix codonopsis, and the presented models would be a useful reference for quality control of other similar raw materials of TCM.

Paper‐based microfluidic aptasensor for food safety

AbstractFood analysis is requiring rapid, accurate, sensitive, and cost‐effective methods to monitor and guarantee the safety and quality to fulfill the strict food legislation and consumer demands. In this study, a nano‐materials enhanced multipurpose paper‐based microfluidic aptasensor was developed as a sensing tool for accurate detection of food allergens and food toxins. graphene oxide (GO) and specific aptamer‐functionalized quantum dots (QDs) were employed as probes, the fluorescence quenching, and recovering of the QDs caused by the interaction among GO, aptamer‐functionalized QDs, and the target protein were investigated to quantitatively analyze the target concentration. The homogenous assay was performed on the paper‐based microfluidic chip, which significantly decreased the sample and reagent consumption and reduced the assay time. Egg white lysozyme, ß‐conglutin lupine and food toxins, okadaic acid and brevetoxin standard solutions, and spiked food samples were successfully assayed by the presented aptasensor. Dual‐target assay was completed within 5 min, and superior sensitivities were achieved when testing the samples with commercial enzyme linked immunosorbent assay kits side by side.Practical applicationsThe present aptasensor provides a simple, accurate method for rapid quantitative analysis of allergens or toxins in food. This method is able to achieved rapid on‐site detection of potential allergen/toxin contaminations, which is a critical necessity for individuals with food allergies and other types of food sensitivities. In addition, the present method can be easily implemented into routine analysis to help food producers and regulations secure the safety and compliance of food products.

Research on modeling method to analyze Lonicerae Japonicae Flos extraction process with online MEMS-NIR based on two types of error detection theory

To establish a rapid quantitative analysis method for online monitoring of chlorogenic acid in aqueous solution of Lonicera Japonica Flos extraction by using micro-electromechanical near infrared spectroscopy (MEMS-NIR). High performance liquid chromatography(HPLC) was used as reference method．Kennard-Stone (K-S) algorithm was used to divide sample sets, and partial least square(PLS) regression was adopted to establish the multivariate analysis model between the HPLC analysis contents and NIR spectra. The synergy interval partial least squares (SiPLS) was used to selected modeling waveband to establish PLS models. RPD was used to evaluate the prediction performance of the models. MDLs was calculated based on two types of error detection theory, on-line analytical modeling approach of Lonicera Japonica Flos extraction process was expressed scientifically by MDL. The result shows that the model established by multiplicative scatter correction(MSC) was the best, with the root mean square with cross validation(RMSECV), root mean square error of correction(RMSEC) and root mean square error of prediction(RMSEP) of chlorogenic acid as 1.707, 1.489, 2.362, respectively, the determination coefficient of the calibration model was 0.998 5, and the determination coefficient of the prediction was 0.988 1．The value of RPD is 9.468.The MDL (0.042 15 g•L⁻¹) selected by SiPLS is less than the original,which demonstrated that SiPLS was beneficial to improve the prediction performance of the model. In this study, a more accurate expression of the prediction performance of the model from the two types of error detection theory, to further illustrate MEMS-NIR spectroscopy can be used for on-line monitoring of Lonicera Japonica Flos extraction process.

Quantitative Analysis of Salidroside and p-Tyrosol in the Traditional Tibetan Medicine Rhodiola crenulata by Fourier Transform Near-Infrared Spectroscopy.

A nondestructive, efficient, and rapid method for quantitative analysis of two bioactive components (salidroside and p-tyrosol) in Rhodiola crenulata, a traditional Tibetan medicine, by Fourier transform near-infrared (FT-NIR) spectroscopy was developed. Near-infrared diffuse reflectance spectra in the range of 4000 to 10000 cm(-1) of 50 samples of Rhodiola crenulata with different sources were measured. To get a satisfying result, partial least squares regression (PLSR) was used to establish NIR models for salidroside and p-tyrosol content determination. Different preprocessing methods, including smoothing, taking a second derivative, standard normal variate (SNV) transformation, and multiplicative scatter correction (MSC), were investigated to improve the model accuracy of PLSR. The performance of the two final models (salidroside model and p-tyrosol model) was evaluated by factors such as the values of correlation coefficient (R(2)), root mean square error of prediction (RMSEP), and root mean square error of calibration (RMSEC). The optimal results of the PLSR model of salidroside showed that R(2), RMSEP and RMSEC were 0.99572, 0.0294 and 0.0309, respectively. Meanwhile, in the optimization model of p-tyrosol, the R(2), RMSEP and RMSEC were 0.99714, 0.0154 and 0.0168, respectively. These results demonstrate that FT-NIR spectroscopy not only provides a precise, rapid method for quantitative analysis of major effective constituents in Rhodiola crenulata, but can also be applied to the quality control of Rhodiola crenulata.

Detection of total protein in milk using phosphomolybdic acid-mediated surface-enhanced Raman spectroscopy

Although many surface-enhanced Raman scattering (SERS)-based methods for detecting specific proteins have been studied, simple and direct detection of total protein in liquid using a SERS-based method remains difficult. In this study, a distinguishable effect on the SERS spectra from pre-mixture of phosphomolybdic acid (PMA) with protein was found, indicating that PMA could be used as a SERS reporter for total protein detection in a liquid sample. Further experiments confirmed a good linear relationship between a premixed concentration of protein (casein, whey protein or bovine serum albumin) and the SERS intensity of PMA in our SERS system. Using casein as a reference, a PMA-mediated SERS method was proposed that can quantitatively analyze protein at 2.5–25 µg/ml with a limit of detection of 1.5 µg/ml. Our PMA-mediated SERS method is a simple and rapid method for quantitative analysis of total protein in milk. Copyright © 2015 John Wiley & Sons, Ltd.