Chromatographia (2013) 76:849–855 DOI 10.1007/s10337-013-2487-6
ORIGINAL
Chemometric Resolution for Rapid Determination of Prometryn in Leek Samples Using GC–MS Xi Wu • Weiwei Yu • Xiangyu Luo Wensheng Cai • Xueguang Shao
•
Received: 25 November 2012 / Revised: 24 April 2013 / Accepted: 17 May 2013 / Published online: 31 May 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Much effort has been made to analyze the pesticides in foods or vegetables due to the interferences in the sample matrix. In this work, taking the determination of prometryn in leek samples as an example, a simple method is proposed for fast analysis of the components in real samples using GC–MS and chemometric resolution. The purification step in preparing the samples was simplified, and a short capillary column and fast temperature program were employed in GC–MS measurement. Although the measured signal is composed of overlapped peaks with the interferences and background, the signal of prometryn can be extracted by chemometric resolution. Six leek samples from different markets were analyzed within an elution time of 6 min. Compared with the results by the standard method, the results by the proposed method were found to be reliable. Keywords GC–MS Chemometrics Non-negative immune algorithm Prometryn Leek samples
Introduction GC–MS has been a commonly used and powerful technique for analyzing the complex samples [1, 2]. However, a sample preparation step is generally needed to separate the interested components from the complex matrix of the sample. For determination of pesticides in food or
X. Wu W. Yu X. Luo W. Cai X. Shao (&) State Key Laboratory of Medicinal Chemical Biology, Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, People’s Republic of China e-mail:
[email protected]
vegetables, various methods have been developed, such as liquid–liquid extraction (LLE) [3], solid-phase extraction (SPE) [4], solid-phase microextraction (SPME) [5], accelerated solvent extraction (ASE) [6], microwave-assisted extraction (MAE) [7] and matrix solid-phase dispersion (MSPD) [8], etc. All these methods have been employed in separating the pesticide residues from the real samples of food, fruit and vegetable. Sometimes, however, the selective separation is still needed because these methods can only isolate a class of compounds with similar property. On the other hand, the accuracy, reproducibility, and recovery of analysis may be affected by the separation step. Furthermore, the step is also an obstacle for rapid analysis. It is, therefore, still necessary to develop efficient approaches of fast analysis for GC–MS technique. Chemometrics has provided an alternative way for analyzing complex samples by resolving the overlapping signals. For example, a large number of methods have been developed based on chemical factor analysis (CFA) [9–11], such as evolving factor analysis (EFA) [12, 13], window factor analysis (WFA) [14, 15] and heuristic evolving latent projections (HELP) [16, 17]. These methods have been widely employed in resolving the signals of evolving processes such as chromatography or chemical reactions. Moreover, rank annihilation factor analysis (RAFA) [18] provided an efficient tool for quantitative analysis of gray systems, and target factor analysis (TFA) [19, 20] and iterative target transformation factor analysis (ITTFA) [21] can be used for both qualitative and quantitative purposes. On the other hand, alternative methods such as multivariate curve resolution-alternating least squares (MCR-ALS) [22– 24] and convolution methods like wavelet transform (WT) [25, 26] have been proposed. These methods have been proved to be powerful tools in analyzing the complex samples such as traditional Chinese herbal medicine [27]
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and foods [28, 29]. Although the principles are different, the methods can help us to extract useful information of the interested components from the overlapping signals. Therefore, chemometrics may provide approaches from different aspect for fast analysis avoiding the time-consuming step of sample preparation. Immune algorithm (IA) [30, 31] is a method based on curve fitting and extracts the contribution of each component to the total signal by projection and subtraction. Furthermore, because IA extracts the information of each component independently and simultaneously, it can avoid the influence of noise and background. Practicability of the method has been proved by the applications in the resolution of overlapping signals generated by a variety of analytical instruments [32–36]. For the aim of retrieving the contribution of a specific component from an overlapping signal, non-negative IA (NNIA) [37, 38] was proposed. With the method, the information of a compound of interest can be obtained from the measured data matrix of a multicomponent sample. Compared with most of the resolution methods, including the alternative methods, which resolve all the components simultaneously, NNIA can resolve the information of a specified component. Therefore, NNIA is more suitable in the cases where determination of a component in the samples with complex matrix is needed, although the method can be used for multi-component determination by resolving the components one by one. In this study, taking the determination of prometryn residue in leek samples as an example, a method for analysis of the components in real samples using GC–MS and chemometric resolution is proposed. In the method, the purification step in preparing the samples was simplified, and a short capillary column and fast temperature program are used for speeding up the separation. Then, NNIA is employed for resolving the signal of the compound of interest from the overlapping GC–MS data matrix. Therefore, the method may provide a simple and fast way for determination of a specified component in real samples using GC–MS analysis.
Materials and Methods Chemicals and Materials The standard solution of prometryn (100 ppm) was purchased from Agro-Environmental Protection Institute, Ministry of Agriculture of China (Tianjin, China). The standard substance of phenanthrene (98.9 %) was used as internal standard and purchased from Accustandard (New Haven, USA). Solutions containing different concentrations of phenanthrene were prepared with acetic acid/acetonitrile (0.1/100, v/v) as the solvent. Acetonitrile, acetone and acetic acid (HPLC grade)
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were obtained from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Anhydrous magnesium sulfate and anhydrous sodium acetate (analytical reagent grade) were supplied by Guangfu Chemical Reagent (Tianjin, China). Primary secondary amine (PSA) and octadecylsilane chemically bonded silica (C18) were purchased from Varian Technologies China Co., Ltd. (Beijing, China). Stock solution was obtained by dilution of the prometryn standard solution with acetic acid/acetonitrile (0.1/100, v/v). All stock solutions were stored at 4 °C in refrigerator. Sample Collection and Preparation Leek samples were purchased from different markets. Edible part of leek samples was washed by gently rubbing, homogenized in a food processor, and then stored in a polyethylene bottle. For preparing the samples for GC–MS analysis, the standard method suggested by Ministry of Agriculture of China (NY/T 1380–2007) was used. The method includes two steps, i.e., extraction and purification. In the extraction step, 7.5 g of homogenized samples was weighed in a 100-mL centrifuge tube. Then 5.0 g anhydrous magnesium sulfate (MgSO4), 1.5 g anhydrous sodium acetate (NaAc) and 15 mL acetic acid/acetonitrile (0.1/100, v/v) were added into the samples and mechanically shaken for 10 min. After that, the mixtures were centrifuged for 10 min at 5,000 rpm, and then 2 mL of the supernatant was transferred into another centrifuge tube. For purification of the supernatant, 0.3 g MgSO4, 0.1 g PSA and 0.1 g C18 were added to the tube, the mixture was shaken for 5 min, centrifuged for 5 min at 5,000 rpm, and the supernatant was filtered with microfiltration membrane. Then, 1 mL of supernatant was pipetted into a 1-mL volumetric flask and evaporated to about 0.8 mL under a gentle stream of nitrogen. Finally, 100 lL internal standard solution of phenanthrene (10 ppm) was added and the solution was diluted with acetic acid/acetonitrile to 1 mL. The extracts were stored at 4 °C in refrigerator before GC–MS analysis. To simplify the sample preparation, only the extraction step in the standard method was used in this study. Avoiding the purification step may make the sample more complex and the GC–MS signal more complicated. Chemometric resolution, therefore, was used to obtain the information of the prometryn from the overlapping signal. GC–MS Measurements A GCMS-QP2010 Ultra system (Shimadzu, Kyoto, Japan) which consisted of a GC-2010 Plus gas chromatograph and a twin line MS system with an electron impact ionization (EI) source was employed. For the standard method, a 30-m capillary column (0.25 mm i.d. and 0.25 lm film
Determination of Prometryn GC–MS
thickness, Restek, Bellefonte, PA, USA) was used, and the oven temperature was set to 60 °C for the first 2 min, increased to 250 °C with a rate of 50 °C min-1, and then held for 5 min. Helium was used as carrier gas with a flow rate of 1.0 mL min-1. Splitless injection was used and the temperature of the GC injector was controlled at 250 °C. The mass spectrometer was operated with a transfer line temperature of 250 °C and ion source temperature of 200 °C. The electron impact ionization was tuned at 70 eV, and the mass range for the MS detector was from 50 to 650 amu and scan event time 0.20 s. For the proposed method, however, to speed up the separation, a 10-m capillary column (0.1 mm i.d. and 0.1 lm film thickness, Restek, Bellefonte, PA, USA) and a fast temperature program were employed, i.e., the over temperature was set to 60 °C for the first 2 min, increased to 250 °C with a rate of 100 °C min-1 and held for 5 min. Calculations NNIA was used for extracting the information of prometryn from the measured GC–MS matrix. The method has been used for resolution of overlapping GC–MS signal in our previous studies [37, 38]. The basic idea of IA is to iteratively subtract the signals of each component from an overlapping signal [32–36]. Taking the measured signal of a mixture and the standard signals of the components as the input, the method iteratively subtracts the signal of each component from the total signal, and the iteration of the subtraction stops when no signal of the components can be extracted. In NNIA, a negative correction operation was used and, therefore, the information of a compound of interest can be obtained only with the standard signal of the component. For GC–MS, the signal can be described as an m 9 n data matrix, where m is the number of retention time and n is m/z channels. Thus, each column is a chromatogram for an m/z channel, while each row is a mass spectrum at a retention time. In an overlapping chromatographic peak, the spectrum is a linear combination of the spectra of the overlapped components. Therefore, the chromatogram of the components can be obtained by NNIA. In this work, taking the measured signal around the retention time of prometryn and the mass spectrum of prometryn as the input, the chromatogram of prometryn was calculated directly from the measured GC–MS signal using NNIA.
Results and Discussion Comparison of the Sample Preparation Methods To compare the difference between the standard method and the simplified method, the extracts obtained by the
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Fig. 1 Total ion chromatogram (TIC) of the extracts from a leek sample prepared with standard method (a) and simplified method (b) obtained with long column (30 m) and regular temperature program. The dashed and dotted lines in the enlarged figure represent the curves (a) and (b), respectively
two methods were analyzed by GC–MS with the same conditions. The total ion chromatograms (TICs) of a sample are shown in Fig. 1 with two curves labeled as (a) and (b). Clearly, the two TICs are similar to each other. All the components are eluted within 16 min, the peak of prometryn is around 11.56 min, and the peak of the target component is well separated from the coexisting components. Compared with Fig. 1a, however, more than 10 new peaks appeared in Fig. 1b, such as the peaks around 4.49, 6.06, 7.06, 7.27 and 13.3 min. The difference apparently shows the function of the purification step. Impurities were removed by PSA and C18. However, there are also peaks, e.g., around 8.42, 9.71 and 11.30 min in Fig. 1a, that do not appear in Fig. 1b, indicating that the purification may introduce new impurities to the sample. For a detailed comparison of the two TICs, an enlarged figure in the retention time range of 11.0–11.6 min was shown in Fig. 1, in which the peaks of the internal standard and the target component are included. In the enlarged figure, the dashed and dotted lines represent the curves (a) and (b), respectively. It can be seen that the peak of the internal standard in curve (a) is slightly smaller than that in curve (b). This may be caused by the variation of sample injection in the experiment. The peak of the target component in curve (a), however, decreased obviously compared with that in curve (b). Therefore, the purification may cause the loss of the target component. Less operation time in preparing the samples may be a better choice to simplify the experiment, introduce less impurity, and avoid the loss of the target component.
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Rapid Analysis and Extracting the Information of Target Component To achieve a rapid analysis, the extract obtained with simplified extraction was measured with the fast temperature program. Figure 2 shows the TIC of a sample. Clearly, due to the fast program and the short column, all the components are eluted within 6 min, but the TIC is composed of overlapping peaks. With standard sample of prometryn, the peak of the target component can be detected around 4.90 min, being hidden in an overlapping peak, as labeled in the figure. For extracting the information of prometryn from the overlapping peak, NNIA was employed. The curve (a) in the bottom plot of Fig. 3 shows the experimental signal in the retention time region of 4.87–4.94 min, in which the peak of the target component is hidden. Taking the mass spectrum of prometryn in the top left of Fig. 3 as standard signal, the concentration of the component at each retention time can be obtained using NNIA. Then by connecting the values of the calculated concentration, the resolved chromatographic profile of the target component can be obtained as the curve (b) in Fig. 3. The peak seems reasonable because the maximum is located at retention time 4.90 min and the symmetry is acceptable, although a small tail exists. For further analyzing the overlapping peak, the residual after extracting the information of prometryn, the curve (c) in Fig. 3, was investigated. The component was identified as phytol by matching the mass spectrum, as shown in the top right of Fig. 3. Phytol is obviously a component of the sample, because it is a part of chlorophyll [39]. Taking the mass
Fig. 3 Reference mass spectra of prometryn (top left) and phytol (top right), and the resolved results (bottom) by NNIA. a Experimental TIC, b resolved TIC of prometryn, c residual after extracting the TIC of prometryn, d resolved TIC of phytol, e residual after extracting the TIC of prometryn and phytol
spectrum of phytol as the standard signal, the curve (d) in Fig. 3 was obtained using NNIA, and the curve (e) in the figure represents the residual TIC after extracting the information of prometryn and phytol. The rationality of the curves (d) and (e) may be a further proof of the correct resolution. It is worth noting that there are selective ions for prometryn in this case. The problem can also be overcome using these selective ions. The aim of this study, however, was to develop a common method for fast determination of the components in complex samples. Furthermore, from Fig. 3 it can be indicated that the effect of noise and background can be eliminated by the usage of multivariate signals in chemometric resolutions. Quantitative Analysis
Fig. 2 Total ion chromatogram (TIC) of the extracts from a leek sample prepared with simplified method and separated with short column (10 m) and fast temperature program
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For quantitative determination of the target component in leek samples, various methods could be used, such as internal standard and matrix-matched calibrations. However, standard addition method was used in this study to avoid the matrix effect. Furthermore, in standard addition method, the extracted chromatograms and the linearity of
Determination of Prometryn GC–MS
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Fig. 4 Total ion chromatograms (TICs) of the samples after standard addition (a) and the resolved peaks of the target component (b)
Fig. 5 Relationship between the peak areas and added concentrations of prometryn
their peak areas can be used for validating the correctness of the resolution. Figure 4a shows the enlarged part of the TICs in the retention time range of 4.87–4.94 min for the extract of a sample after adding 0.0, 0.5, 1.0, 1.5, 2.0 ppm of prometryn, respectively. It is clear that the peak of the target component is overlapped with the interferences and there is obvious background. Figure 4b displays the resolved TIC of the target component using NNIA. Both the shape and the intensity of the peaks seem to be reasonable. To further
validate the resolved peaks of the target component, the relationship between the peak areas and the added concentrations was investigated as shown in Fig. 5. The three lines for each sample were obtained with three parallel experiments. The correlation coefficients (R) for all the lines are higher than 0.99, indicating a good linearity. From Fig. 5, the concentrations of prometryn can be obtained by measuring the cross points of the lines and concentration axis. On the other hand, both the resolved chromatograms and the linearity of their peak areas may be a proof of the reliability of the method. Table 1 summarizes the quantitative results of six leek samples from different markets obtained by standard method, simplified method and simplified method with chemometric resolution, denoted as A, B and C, respectively. In method A, the standard sample preparation method, including an extraction and a purification step, was used and the measurement was achieved by a long (30 m) column. In method B, simplified sample preparation method and long column were used, while in method C, simplified sample preparation method and short column were used. Furthermore, the quantitative results of method A and B were obtained with internal standard method, but chemometric resolution and standard addition method were used in method C. It is clear that, for both the samples, similar results were obtained, i.e., the measured concentration of prometryn by method B is significantly higher than that by method A and slightly higher than that by method C. The significant difference between method A and B indicates that the purification step in the standard
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Table 1 Quantitative results (ppm) of the six samples by different methods Sample
Method Aa
Method B
Method C
1
0.52 (0.012)b
0.61 (0.010)
0.58 (0.032)
2
0.69 (0.016)
0.77 (0.016)
0.75 (0.029)
3
0.39 (0.012)
0.48 (0.018)
0.44 (0.030)
4
0.69 (0.011)
0.79 (0.038)
0.76 (0.031)
5
0.99 (0.035)
1.20 (0.053)
1.16 (0.027)
6
0.51 (0.022)
0.69 (0.010)
0.66 (0.020)
a
Method A, B and C represent the standard method, simplified pretreatment with long column and simplified pretreatment with short column, respectively
b
The number in the parentheses is the standard deviation obtained from the three parallel measurements
sample preparation method may cause a loss of prometryn, and the slight difference between method B and C may be caused by interferences of small contents of coexisting components or even the background in the chromatogram. On the other hand, such results may further demonstrate the benefit of method C, in which pure information of the target component is obtained by the chemometric resolution.
Conclusions A rapid determination of prometryn residues in leek samples was performed. A simplified pretreatment, a short capillary column and a fast temperature program were employed for speeding up the analysis. Although the signal of prometryn is overlapped with the coexisting components, the use of NNIA can offer a solution to the problem. Comparing the results obtained with different sample preparation and separation methods, it was shown that the proposed method can achieve a fast preparation, rapid separation and precise determination. Therefore, the method may provide a new way for fast determination of pesticide residues in vegetable samples. Acknowledgments This study is supported by National Natural Science Foundation of China (No. 21175074).
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