Correction of the Effect of Humic Acids on the Fluorescence Detection of Polycyclic Aromatic Hydrocarbons by Combination Spectroscopy.

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in soil and water, but fluorescence spectroscopy for PAHs is often interfered with organic matter in the environment. The aim of this paper is to evaluate a correction method using combined spectral technology in an environment where humic acids and PAHs coexist. In the present work, humic acids and benzo[ghi]perylene were analyzed in various concentrations using fluorescence and near-infrared (NIR) spectroscopy from single and mixed samples. The NIR prediction model of humic acids in mixed samples was established based on synergy interval partial least squares, and the standard curve of fluorescence spectra for humic acids was established at 478 nm (characteristic wavelength of benzo[ghi]perylene). The fluorescence intensity of humic acids in the mixed sample was predicted from the content derived from the NIR spectra. The final correction was carried out by their exclusion from the fluorescence of the mixture at the same wavelength. The corrected fluorescence intensity was linearly correlated with the concentration of benzo[ghi]perylene with R2 = 0.8362, while R2 = 0.3538 before correction. These results give a new insight into the calibration modeling of the combined spectral method.

A strategy to reduce the effect of organic matter on fluorescence intensity for improving the detection accuracy of polycyclic aromatic hydrocarbons in soil.

Fluorescence spectroscopy has been used for rapid detection of PAHs in soil, but soil organic matter (SOM) produces strong interference to the fluorescence intensity of PAHs, which restricts the application of fluorescence spectroscopy for rapid detection of PAHs in soil. A correction method of reducing the interference of SOM on PAHs fluorescence intensity was proposed combining fluorescence and near-infrared (NIR) spectroscopy. Six soil samples with different concentrations of humic acid (HA) at a given phenanthrene concentration (5 mg/g) were prepared and scanned for obtaining the fluorescence and NIR diffuse reflectance spectra. The spectral data showed that the fluorescence intensity and NIR diffuse reflectance had an approximate trend with the change of HA concentration. It was found that the NIR diffuse reflection at 4672 cm-1 as a calibration factor could effectively reduce the interference of HA on the fluorescence intensity of phenanthrene. Subsequently, a standard curve for the quantitative analysis of phenanthrene in soil was established based on the fluorescence intensity before and after calibration. For the unknown samples, the predicted average relative errors of the standard curves before and after calibration were 27.46 % and 9.00 %, respectively. The results showed that the proposed correction method could reduce the interference of HA on the quantitative analysis of PAHs, and provide a reference for eliminating the interference constraint of fluorescence spectroscopy technique for rapid real-time detection of PAHs in soil.

Separation of the overlapped humic acid and BGP characteristic peaks using two-dimensional correlation fluorescence-UV-vis spectroscopy.

Fluorescence spectroscopy has been widely used to detect polycyclic aromatic hydrocarbons (PAHs) in the environment. However, the interference of coexisting humic acids (HA) in the environment poses a great challenge to the qualitative and quantitative detection of PAHs using fluorescence spectroscopy. In this study, the spectral properties of benzo [ghi] perylene (BGP) and HA were investigated based on fluorescence and UV-vis spectroscopy combined with two-dimensional (2D) correlation analysis. Under the external disturbance of HA concentration, the homo-2D (fluorescence, UV-visible) correlation and hetero-2D fluorescence-UV-visible correlation spectral characteristics of the mixed samples of HA and BGP were studied, and the effect of HA on the fluorescence of BGP was investigated. It can be inferred that the fluorescence peak at 478 nm come from BGP, and the fluorescence peaks at 442 nm and 533 nm, UV absorption peak at 233 nm come from HA. Meanwhile, asynchronous two-trace two-dimensional (2T2D) fluorescence correlation slice spectra at 533 nm were obtained. The slice spectral intensity at 478 nm was extracted to quantify the BGP concentration in mixture. The results showed that the slice spectral intensity and BGP concentration had a good linear relationship with the coefficient of determination R2 = 0.96. This research provides a way to further study the separation method of HA and PAHs or explore the correction method of the effect of HA on PAHs.

Identification of adulterated milk based on auto-correlation spectra.

A qualitative analysis of melamine-adulterated milk was proposed based on two-trace two-dimensional (2T2D) auto-correlation spectra. The concentration of melamine was used as external perturbation, and 40 adulterated samples of each brand with different concentrations of melamine (0.01 g/L to 1 g/L) were configured. Four brands of milk were used to configure experimental samples, including Guangming brand, Mengniu brand, Sanyuan brand and Wandashan brand. Spectroscopic data of pure milk and melamine-adulterated milk were measured by infrared (IR) (80-4000 cm-1) spectrophotometer. 2T2D auto-correlation spectral technology combined with least squares support vector machine (LS-SVM) method was used for qualitative analysis. The two strongest auto-correlation peaks in the auto-correlation spectra were selected for modeling. For Guangming brand, the intensities of auto-correlation at two wave numbers 2898 cm-1 and 2972 cm-1 were selected as independent variables. For Mengniu brand, the intensities of auto-correlation at two wave numbers 2852 cm-1 and 2920 cm-1 were selected. For Sanyuan brand, the intensities of auto-correlation at two wave numbers 2900 cm-1 and 2974 cm-1 were selected. For Wandashan brand, the intensities of auto-correlation at two wave numbers 2900 cm-1 and 2974 cm-1 were selected. For four brands fused together, the intensities of auto-correlation at two wave numbers 2900 cm-1 and 2974 cm-1 were selected. For each brand, the accuracy of qualitative analysis was 100 %. For four brands fused together, the accuracy of qualitative analysis was 99.05 %. In this way, it greatly reduced the amount of data to be processed. This study showed that 2T2D auto-correlation spectral technology combined with LS-SVM method was perfect for the discrimination of melamine-adulterated milk.

Slice spectra approach to synchronous Two-dimensional correlation spectroscopy analysis for milk adulteration discriminate.

The discrimination approach of adulterated milk was proposed combined synchronous two-trace two-dimensional (2T2D) correlation slice spectra at the characteristic wavebands of adulterant in milk with multivariate method. Two common adulterants, melamine and urea, were analyzed to demonstrate useful by the method. 2T2D (near infrared) NIR slice spectra at characteristic wavebands of adulterant were extracted from the synchronous 2T2D correlation spectra, and were input to construct the N-way partial least squares discriminant analysis (NPLS-DA) models. One-dimensional (1D) spectroscopy featuring all the present components in the samples combined with partial least squares discriminant analysis (PLS-DA) was also evaluated for comparison. The results indicated that for one kind of adulterant in model, prediction accuracies of slice spectral models were both 100% for melamine-adulterated and urea-adulterated samples discrimination. Moreover, for two kinds of adulterants in model, prediction accuracies of slice spectral models were 90.57% and 100% for melamine-adulterated and urea-adulterated discrimination, respectively, which was better than those of 1D whole models based on PLS-DA (only 81.13% and 98.15%, respectively). The comparison informs that the 2T2D slice spectra extracted at the characteristic wavebands of adulterant highlighted the adulterant spectral features and was obviously advantage to improve the discrimination accuracy. Meanwhile, the complexity of slice spectra is significantly reduced compared with the whole matrix of synchronous 2T2D correlation spectra.

Influence of brands on a discrimination model for adulterated milk based on asynchronous two-dimensional correlation spectroscopy slice spectra.

To improve the robustness of near infrared (NIR) identification models for the milk adulteration, a novel approach was explored based on asynchronous two-dimensional correlation spectroscopy (2D-COS) slice spectra obtained at characteristic wavebands for pure milk and adulterant combined with an N-way partial least squares discriminant analysis (NPLS-DA). NIR diffuse reflectance spectra from four different brands, Guangming (GM), Mengniu (MN), Sanyuan (SY), and Wandashan (WDS), were collected in range of 11,000 to 4000 cm-1. Influence of brands on discrimination models for adulterated milk was analyzed. The asynchronous 2D-COS slice spectra at 10 characteristics wavebands, including 4 wavebands for pure milk and 6 wavebands for urea, were input into NPLS-DA to construct discriminant models. External validations using five independent calibration sets from intrabrand or interbrand were established. The same prediction set of 26 SY samples was used to assess the prediction ability of different calibration sets and compared with traditional one-dimensional (1D) NIR spectra based on a partial least squares discriminant analysis (PLS-DA). It showed that for intrabrand model, the correct rates for the calibration and predication sets were 100% and 96.15%, respectively. For the interbrand model, the correct rates by the NPLS-DA for the calibration set of GM, MN, and WDS milk were both 100%. The corresponding rates for the prediction set were 73%, 88.46% and 69.23%, respectively, which were much higher than those of PLS-DA (only 50%, 53.83% and 50%, respectively). It was proven that model robustness was sensitive to changes in the milk brands. The proposed method can effectively reduce the influence of brands on the discrimination models.

Correction for the effect of soil types on the fluorescence intensity of polycyclic aromatic hydrocarbons.

A correction method was proposed and established to reduce the effect of soil types on the PAHs fluorescence intensity based on near-infrared (NIR) diffuse reflectance spectroscopy. The benzo [ghi] pyrene in soil was as the research object. Five types of soil samples with concentration of 1 mg/g benzo [ghi] pyrene were prepared respectively. The fluorescence spectra and NIR diffuse reflectance spectra of all samples were collected. The effects of soil types on the fluorescence spectra and NIR diffuse reflectance spectra were studied. It was found that the effect of soil types on PAHs fluorescence intensities was reduced by dividing the fluorescence intensity by the transformed diffuse reflectance at 4688 cm-1. In order to verify its effectiveness, the established correction method was used to quantitatively analyze the benzo [ghi] pyrene concentration in soil. The correlation coefficients R2 of linear fitting between the fluorescence intensities and concentrations of benzo [ghi] perylene are 0.90 and 0.95 before and after correction, respectively. The average relative prediction error decreased from 35.7% before the correction to 8.71% after the correction. The results show that the established correction method can effectively reduce the effect of soil type on PAHs fluorescence intensity based on NIR diffuse reflectance spectrum. The research can provide theoretical basis and technical support for the accurate and rapid detection of PAHs in soil by fluorescence spectroscopy.

Development of weaning food with prebiotic effects based on roasted or extruded quinoa and millet flour.

Weaning is the gradual process of introducing solids or semisolid foods into an infant's diet, in order to ensure their healthy growth. This study developed two kinds of formula weaning food based on roasted or extruded quinoa and millet flour, and evaluated their quality. A fructo-oligosaccharide (FOS)/galacto-oligosaccharide (GOS) mix was added to provide the prebiotic potential. The protein contents of the roasted quinoa-millet complementary food (RQMCF) and extruded quinoa-millet complementary food (EQMCF) were 16.7% and 17.74% higher, respectively, than that of commercial millet complementary food (CMCF). Both RQMCF and EQMCF provided sufficient levels of energy and minerals. Extrusion provided the foods with a lower viscosity, and higher solubility and water absorption ability than roasting. In vitro digestion results showed that EQMCF exhibited the highest starch and protein digestibility (89.76% and 88.72%, respectively) followed by RQMCF (87.75% and 86.63%) and CMCF (83.35% and 81.54%). The digestas of RQMCF and EQMCF after in vitro digestion exhibited prebiotic effects by promoting the growth of the probiotics (Lactobacillus plantarum and Lactobacillus delbrueckii). These results will contribute to developing complementary weaning foods for infants. PRACTICAL APPLICATION: This study has shown that extrusion is an efficient and stable processing method for producing infant complementary foods with low density, balanced nutrition, and high levels of starch and protein digestibility. Extruded quinoa-millet prebiotic complementary food can also promote the proliferation of probiotics. This will provide a new direction for developing novel infant formula weaning foods.

Correction method of effect of soil moisture on the fluorescence intensity of polycyclic aromatic hydrocarbons based on near-infrared diffuse reflection spectroscopy.

Soil moisture has a strong impact on the fluorescence intensity of PAHs, which is undoubtedly posing a challenge for the development of rapid real-time fluorescence detection technology of PAHs in soil. In this work, NIR diffuse reflectance spectroscopy was used to correct the fluorescence spectra of PAHs in order to reduce the effect of the soil moisture. To establish the correction method, eight soil samples with different moisture contents and a given phenanthrene concentration (8 mg/g) were prepared. The fluorescence and NIR diffuse reflectance spectra were collected for of all samples. It was found that the fluorescence spectra of the soil samples that vary with the moisture content together with the NIR diffuse reflectance spectra were considered for the correction of the fluorescence intensity of phenanthrene related to the moisture content. The results showed that the ratio of the fluorescence intensity at 384 nm to the NIR diffuse reflectance spectrum absorbance at 5184 cm-1 can be used as a correction factor to reduce the effect of the soil moisture on the fluorescence intensity of phenanthrene in the soil. The validity of the correction method was verified by the quantitative analysis of PAHs with different concentrations and soil moisture contents. The results showed better linearity between the fluorescence intensity and the concentration of PAHs after the correction (with a correlation coefficient R of 0.99) than before the correction (with R of 0.86). The relative prediction errors for three unknown samples decreased from 19%, 51% and 40% before the correction to 5%, 13% and 0.44% after the correction, respectively, indicating the feasibility of the detection of PAHs in the soil by the combination of fluorescence and NIR diffuse reflectance spectroscopy.

Detection of pesticide in water using two-dimensional fluorescence correlation spectroscopy and N-way partial least squares.

To determine the concentration of carbaryl and chlorothalonil in water, the potential of two-dimensional (2D) fluorescence correlation spectra with N-way partial least squares (N-PLS) was investigated. A total of 40 mixture solutions of carbaryl and chlorothalonil were prepared and 27 of them were used to form a calibration set. The excitation-emission matrix (EEM) fluorescence spectra of all samples were measured. Under the excitation perturbation, 2D fluorescence correlation spectra of all samples were calculated and formed a 2D correlation spectral matrix. And N-PLS models for determination of carbaryl and chlorothalonil in water were built based on 2D correlation fluorescence spectral matrix and traditional EEM spectral matrix, respectively. Finally, the performances of N-PLS models using both methods were compared. For chlorothalonil, the root mean square error of calibration (RMSEC) were 3.43 × 10-6 g L-1 and 5.08 × 10-6 g L-1, the root mean square errors of prediction (RMSEP) were 5.86 × 10-6 g L-1 and 8.99 × 10-6 g L-1 for 2D correlation spectra and EEM spectra, respectively. For carbaryl, the RMSEC were 5.24 × 10-7 g L-1 and 6.18 × 10-7, the RMSEP were 9.20 × 10-7 g L-1 and 9.63 × 10-7 g L-1 for 2D correlation spectra and EEM spectra, respectively. From the results of this study, it may conclude that 2D fluorescence correlation spectra is superior over the traditional EEM fluorescence spectra in terms of predictability and can be used as an alternative method for detection of organic pollutants in environment.

Feasibility of the simultaneous determination of polycyclic aromatic hydrocarbons based on two-dimensional fluorescence correlation spectroscopy.

A new approach for quantitative determination of polycyclic aromatic hydrocarbons (PAHs) in environment was proposed based on two-dimensional (2D) fluorescence correlation spectroscopy in conjunction with multivariate method. 40 mixture solutions of anthracene and pyrene were prepared in the laboratory. Excitation-emission matrix (EEM) fluorescence spectra of all samples were collected. And 2D fluorescence correlation spectra were calculated under the excitation perturbation. The N-way partial least squares (N-PLS) models were developed based on 2D fluorescence correlation spectra, showing a root mean square error of calibration (RMSEC) of 3.50µgL-1 and root mean square error of prediction (RMSEP) of 4.42µgL-1 for anthracene and of 3.61µgL-1 and 4.29µgL-1 for pyrene, respectively. Also, the N-PLS models were developed for quantitative analysis of anthracene and pyrene using EEM fluorescence spectra. The RMSEC and RMSEP were 3.97µgL-1 and 4.63µgL-1 for anthracene, 4.46µgL-1 and 4.52µgL-1 for pyrene, respectively. It was found that the N-PLS model using 2D fluorescence correlation spectra could provide better results comparing with EEM fluorescence spectra because of its low RMSEC and RMSEP. The methodology proposed has the potential to be an alternative method for detection of PAHs in environment.

[Analysis of Three Polycyclic Aromatic Hydrocarbons in Solution Based on Two-Dimensional Fluorescence Correlation Spectroscopy].

Polycyclic aromatic hydrocarbons (PAHs) are listed as the priority pollutants. It is difficult to resolve effectively the peaks of PAHs by conventional one-dimensional fluorescence spectroscopy due to its low content and the overlapping fluorescence three mixed ystems and a total of 27 samples, are to be prepared with different concentrations of three PAHs. Concentrations of three PAHS are monotonically increasing or decreasing in each mixed system. Then the 2D fluorescence correlation spectrum of each mixed systems will be calculated under the perturbation of the concentration of anthracene, phenanthrene and pyrene in solution. There are seven strong autopeaks at 425, 402, 381, 373, 365, 393 and 347 nm in synchronous 2D correlation spectrum. The fluorescence peak of phenanthrene at 347 nm is uncovered in three mixed systems, so the band at 347 nm is to be used as clues for further assignment. According to positive or negative cross peaks at 347 nm in synchronous 2D correlation spectrum, we can know that the peaks at 402, 381, 425 and 452 nm are assigned to anthracene, the peaks at 373 and 393 nm are assigned to pyrene, and the peaks at 365, 356 and 347 nm are assigned to phenanthrene. The fluorescence peak of phenanthrene at 385 nm is shown in asynchronous 2D correlation spectrum; it means the spectral resolution of asynchronous spectrum is better than the synchronous spectrum. The results are that it is feasible to analyze serious overlapping multi-component PAHs using two-dimensional fluorescence correlation spectroscopy, which can be extended to the detection of other pollutants in the air.

Two-dimensional hetero-spectral mid-infrared and near-infrared correlation spectroscopy for discrimination adulterated milk.

A new approach for discriminant analysis of adulterated milk is proposed based on two-dimensional (2D) hetero-spectral near-infrared (NIR) and mid-infrared (IR) correlation spectroscopy along with multi-way partial least squares discriminant analysis (NPLS-DA). NIR transmittance spectra and IR attenuated total reflection spectra of pure milk and adulterated milk with level of melamine varying from 0.03 to 3 g·L(-1) were collected at room temperature. The synchronous 2D hetero-spectral IR/NIR correlation spectra of all samples were calculated to build a discriminant model to classify adulterated milk and pure milk. Also, the NPLS-DA models were built based on synchronous 2D homo-spectral NIR/NIR and IR/IR correlation spectra, respectively. Comparison results showed that the NPLS-DA model could provide better results using 2D hetero-spectral IR/NIR correlation spectra than using 2D homo-spectral NIR/NIR and 2D IR/IR correlation spectra.

[Progress in Application of Two-Dimensional Correlation Spectroscopy for Detection of Food Quality].

In recent years, the food safety and quality has always been a serious issue. Therefore, it is urgent to develop a rapid and widely available method to determine the quality of food. Due to high spectral resolution, good spectral selectivity and good ability of spectrogram analysis, the technology of two-dimensional (2D) correlation spectroscopy is an effective method for solving three major problems encountered by the conventional one-dimensional (1D) spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. Therefore, 2D correlation spectroscopy, which is suited to distinguish similar samples hardly distinguished by the conventional 1D spectroscopy, has been successfully applied in many complex biological systems. The developmental process, the experimental way to obtain spectrum, the fundamental mathematical principle and the properties of 2D correlation spectroscopy were introduced in this paper. At the same time, it is pointed out that the origin of weak characteristic bands of substance can be verified in terms of the positive or negative corss peaks in synchronous 2D correlation spectrum combined with the existence or inexistence of corss peaks in asynchronous 2D correlation spectrum. The application of 2D near-infrared, mid-infrared, fluorescence, and raman correlation spectroscopy in the detection of food quality and adulteration, concentrated specifically on diary product, wine, oil, meat, honey, and rice were reviewed. Finally, the limitations and future development prospects were pointed out.

[Discrimination of adulterated milk based on Euclidian distances between two-dimensional infrared correlation spectra].

Based on Euclidian distances between synchronous two-dimensional infrared correlation spectra, in terms of the average Euclidian distances between unknown samples and "extreme samples", and average intra- and inter-Euclidian distances of samples in the calibration set, a new method for the discrimination of adulterated milk was proposed. Sixteen pure milk samples were collected and 16 adulterated milk samples with urea (0.01-0.3 g x L(-1)), and 16 adulterated milk samples with melamine (0.01-0.3 g x L(-1)) samples were prepared, respectively. The IR absorption spectra of all samples were measured at room temperature. The synchronous two-dimensional correlation spectra were generated from concentration-dependent spectral variation of adulterant in milk. The Euclidian distances were calculated between synchronous two-dimensional infrared correlation spectra of all samples. Then, the classification models were built respectively for adulterated milk with urea, and adiulterated milk with melamine. The "extreme samples", average intra- and inter-Euclidian distances were determined. Finally, the unknown samples in prediction set were predicted using constructed models in terms of classification rules of adulterated milk. The classification accuracy rates for pure milk and adulterated milk were 100%. The effectiveness of the proposed method was verified. The results obtained in this study revealed that synchronous two-dimensional infrared correlation spectra in combination with Euclidian distance has a feasible potential to discriminate adulterated milk and pure milk.