Determination of the Limit of Detection of Multiple Pesticides Utilizing

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Determination of the Limit of Detection of Multiple Pesticides Utilizing Gold Nanoparticles and Surface-Enhanced Raman Spectroscopy A. M. Dowgiallo* and D. A. Guenther Ocean Optics, Incorporated, 8060 Bryan Dairy Road, Largo, Florida 33777, United States

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S Supporting Information *

ABSTRACT: Exposure to commonly used pesticides poses significant health risks to humans and wildlife. Hence, accurate and sensitive pesticide residue testing methods are imperative to minimize potential health hazards. In this study, we report a method to detect several pesticide residues at trace levels utilizing colloidal gold nanoparticles and surface-enhanced Raman spectroscopy (SERS). Gold nanoparticles suspended in water have been found to enhance Raman scattering from 21 pesticides, including fungicides and insecticides, such as neonicotinoids and organothiophosphates. Measured limits of detection ranged from 0.001 to 10 parts per million (ppm). Furthermore, simultaneous detection of two pesticides, phosmet and thiram, in both a mixture solution and on apple skin, was performed using the SERS method and principal component analysis. The results presented here indicate that SERS coupled with colloidal gold nanoparticles is a potential useful tool for identifying pesticides at trace levels for food safety applications. KEYWORDS: pesticides, gold nanoparticles, surface-enhanced Raman spectroscopy, SERS, food safety

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INTRODUCTION Pesticides are hazardous chemicals that have widespread distribution in the environment and can adversely impact the health of humans and wildlife.1−4 In humans, exposure to pesticides through eating foods or liquids containing pesticide residues, commercial or personal use, or even inhalation of pesticide-contaminated air has been linked with various diseases, including cancer, hormone disruption, asthma, and allergies.2−5 Continued improvements in the testing of pesticides in water and food are still required for early identification and to minimize potential health hazards. Most of the current testing methods, such as high-performance liquid chromatography (HPLC) and gas chromatography coupled with mass spectrometry (GC−MS), are extremely sensitive but are also costly, time-consuming, and require substantial sample manipulation and highly trained operators.6 Raman spectroscopy has been investigated as a potential tool to address these issues and offers certain advantages, such as reduced instrument size, fast measurement times, non-destructive sampling, and simple implementation.7−11 Raman scattering by molecules is an inelastic light scattering process as a result of molecular vibrations, which leads to a unique spectral output for each molecule.12 Hence, Raman spectroscopy is a powerful identification tool, but weak Raman scattering cross sections for most molecules severely limit its ability to detect very low concentration of samples, such as pesticide residues.7,8 Surface-enhanced Raman spectroscopy (SERS) has been found to overcome weak Raman signals by introducing electromagnetic amplification effects by localized surface plasmon excitation in metallic nanostructures.13 SERS often utilizes the unique optical properties of nanostructured gold or silver to enable Raman scattering of analyte molecules at greater than 106 times its normal intensity, where enhancement © XXXX American Chemical Society

factors lower or higher than this have been reported depending upon several experimental factors.10−14 SERS has been employed for trace-level detection of pesticides, where residue tolerances for food items are usually in the parts per million (ppm) to parts per billion (ppb) range.6,16−26 Most studies on SERS of pesticides, whether measured in a pure solution or on a food surface, report measurements of a few pesticides or less, where either (1) the SERS substrates were tailored to target certain pesticides, limiting their ability to detect a wide range of analytes and, thus, their versatility or (2) only pesticides that contain thiol or amine groups were examined as a result of their strong affinity for gold or silver surfaces.19,27−30 One exception to this was a study that examined 12 different pesticides with a gold nanostructured substrate using a portable cellphone SERS system.23 Additionally, SERS of pesticides on food surfaces often requires extraction of the pesticide, followed by the addition to the SERS substrate and waiting to dry, which increases the overall testing time.31 Hence, a SERS method that is versatile enough to detect multiple pesticides on a food surface at trace levels that does not require the extraction or drying steps may offer certain advantages. In this work, we measured the SERS spectra of 21 pesticides, including neonicotinoids, organothiophosphates, and fungicides, using colloidal gold nanoparticles and a benchtop Raman system. The ability to use a single SERS platform involving gold colloids with no additional modifications to Special Issue: 55th North American Chemical Residue Workshop Received: Revised: Accepted: Published: A

March 8, 2019 May 15, 2019 June 12, 2019 June 12, 2019 DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Journal of Agricultural and Food Chemistry

Raman experiments were performed using an Ocean Optics Raman system comprised of a QE Pro spectrometer, 785 nm laser, and Raman fiber optic probe. The laser power was 350 mW, and data were collected with 3−10 s integration time. The spot size of the focused laser was approximately 160 μm. After the raw spectra were collected, an algorithm known as “clean peaks” was applied to remove the baseline and any fluorescence. Absorption measurements on the colloidal gold nanoparticles, in both the isolated and aggregated state, were carried out with an Ocean Optics Flame spectrometer. Transmission electron microscopy (TEM) images were acquired with a Tecnai F20 TEM microscope. ImageJ software was used to measure the size of the gold nanoparticles, and at least 200 particles were analyzed. Mixtures of 10 ppm of phosmet and 10 ppm of thiram were prepared in the following ratios of phosmet/thiram: 1:3, 1:1, and 3:1. For example, in the 1:3 ratio, 20 μL of 10 ppm of phosmet was mixed with 60 μL of 10 ppm of thiram and was then added to the gold nanoparticles. These mixtures as well as the neat 10 ppm solutions were measured with the same experimental conditions described above. In addition, these pesticide mixtures were added to apple skin samples. Gala apples were purchased from a local grocery store, where the skin was peeled and cut into 1 × 1 cm squares. The flesh of the fruit was cut off to only leave the apple skin. The pesticide-contaminated apple skin samples were added to vials containing gold nanoparticles, vortexed for 30 s, and measured with the same parameters as the mixture solutions. PCA was performed on the acquired raw Raman spectra using AnalyzeIt. Data were arranged with rows devoted to each sample scan and columns devoted to each wavenumber pixel. The final column broadly categorized the trends by group, such that all scans from each analyte type were grouped appropriately. To generate a meaningful PCA plot, key wavenumbers of interest were selected for the software to differentiate activities between data sets. The peak values were determined from a peak finder using an 8-pixel width (8 forward, 8 back, and 17 total). The 10 most relevant wavenumbers were determined to be 499, 552, 605, 712, 780, 932, 1015, 1144, 1377, and 1512 cm−1 for the analysis.

Figure 1. (a) Absorption spectrum of isolated (solid) and aggregated (dotted) colloidal gold nanoparticles and (b) TEM image of gold colloids (scale bar is 200 nm).

detect all 21 pesticides demonstrates the versatility of the method. For some of these pesticides, this is also the first report of their detection using SERS. The limit of detection (LOD) using this technique was as low as 0.001 ppm for some pesticides, which approximates established pesticide residue tolerance levels.16 Additionally, a mixture of two pesticides at varying ratios was measured on apples using a unique sampling method, where the pesticide-contaminated apple skin pieces were added directly to the gold colloids, requiring no additional extraction or drying time. Principal component analysis (PCA) was used to differentiate the mixtures on apple skin. These results have the potential to improve the methodology and technology used to detect pesticide residues for enhanced food safety.

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MATERIALS AND METHODS

Gold(III) chloride hydrate (HAuCl4·H2O), sodium citrate tribasic dihydrate, TraceSELECT water, 2 M hydrochloric acid (HCl), acetone, ethanol, and methanol were purchased from Sigma-Aldrich. PESTANAL analytical standards for each pesticide were also purchased from Sigma-Aldrich: acetamiprid, carbofuran, carbophenothion, chlorpyrifos, clothianidin, coumaphos, N,N-diethyl-meta-toluamide, (DEET), diphenylamine, fludioxonil, imidacloprid, malathion, methomyl, permethrin, phosalone, phosmet, profenofos, thiabendazole, thiamethoxam, thiram, transfluthrin, and trichlorfon. Spherical gold nanoparticles were synthesized according to the method of Lee and Meisel.32 Briefly, 0.8 mL of 0.3 M HAuCl4 was added to 400 mL of TraceSELECT water and heated to a vigorous boil in a beaker. At this point, 120 mg of sodium citrate in 1 mL of water was added to the gold solution, where the solution changed from colorless to reddish purple within minutes, indicating the formation of gold nanoparticles. Stock solutions of each pesticide were prepared at 1000 ppm, and dilutions were prepared in the appropriate solvent. For each SERS measurement, 1 mL of gold nanoparticles was added to a vial, followed by the addition of 40 μL of pesticide solution. The first SERS measurement was performed on 10 ppm pesticide solutions, followed by 1, 0.1, 0.01, and 0.001 ppm to determine the LOD. In addition, a few microliters of HCl were added to each vial to induce nanoparticle aggregation, creating the necessary “hot-spot” locations for optimal SERS response.7,8 The solution was mixed by shaking the vial and allowed to sit for 1 min before collecting the SERS spectra. As a reference, 40 μL of the appropriate solvent (water, ethanol, acetone, or methanol) was added to 1 mL of gold nanoparticles with the same amount of HCl. For certain pesticides, lower LODs were achieved by adding greater volumes of pesticide to lower volumes of nanoparticles. For example, 0.8 mL of 0.001 ppm of pesticide was added to 0.2 mL of nanoparticles to increase the ratio of pesticide molecules to gold nanoparticles. The reference in this case involved 0.2 mL of the nanoparticles plus 0.8 mL of the solvent.

Table 1. LOD of the Pesticides Using Colloidal Gold Nanoparticles and SERS pesticide neonicotinoid insecticides acetamiprid clothianidin imidacloprid thiamethoxam organothiophosphate insecticides carbophenothion chlorpyrifos coumaphos malathion phosalone phosmet profenofos fungicides diphenylamine fludioxonil thiabendazole thiram miscellaneous insecticides carbofuran methomyl permethrin transfluthrin trichlorfon insect repellent DEET B

LOD (ppm) 0.01 1 0.1 0.1 0.1 10 0.01 0.1 1 0.1 0.01 0.01 0.1 0.1 0.001 0.01 0.1 0.001 1 0.001 1 DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Figure 2. SERS spectra of the neonicotinoid insecticides examined in this study: (a) acetamiprid at 0.01 and 10 ppm, with acetone shown as the reference, (b) clothianidin at 1 and 10 ppm, with methanol shown as the reference, (c) imidacloprid at 0.1 and 10 ppm, with acetone shown as the reference, and (d) thiamethoxam at 0.1 and 10 ppm, with acetone shown as the reference.

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RESULTS AND DISCUSSION The gold nanoparticles used in this study exhibit the characteristic surface plasmon resonance (SPR) absorption peak at 533 nm (Figure 1a) and are mostly spherical with a diameter of 45 ± 10 nm based on TEM image analysis (Figure 1b). The {111} lattice spacing of 2.36 Å in the gold nanoparticles was determined from high-resolution TEM images (Figure S1 of the Supporting Information). The peak position of the SPR is crucial for the SERS technique to be effective, where there must be resonance between the excitation laser wavelength, the SPR of the nanoparticles, and the scattered Raman wavelengths of the targeted molecule.11,14,15 Here, 785 nm laser excitation is employed because upon aggregation of the nanoparticles in the presence of the pesticides and added HCl, the SPR of the nanoparticles shifts to longer wavelengths.11 To demonstrate this, HCl was added to the gold nanoparticles used in this study, where the SPR at 533 nm red shifts and a new SPR band forms at longer wavelengths as a result of aggregate formation (dotted trace in Figure 1a). In addition, Figure S2 of the Supporting Information shows the red-shifted absorption spectra for the pesticides examined in this work added to gold nanoparticles and HCl. The pesticides examined in this study can be grouped into different classes: neonicotinoid insecticides, organothiophosphate insecticides, fungicides, miscellaneous insecticides, and insect repellents. The spectrum of each pesticide at 10 ppm, a relatively higher concentration, was measured to reveal the characteristic peaks for that pesticide. The spectrum of each pesticide at the lowest concentration measurable or LOD is also shown. Finally, the spectrum of the solvent added to the nanoparticle suspension is plotted for comparison. The LOD is listed for each pesticide in Table 1. The characteristic peaks that are identified for each pesticide are highlighted in the SERS spectra with black arrows as a visual guide and are listed for each pesticide along with their vibrational mode assignments in Tables 2−5. Neonicotinoid Pesticides. Figure 2 displays the SERS spectra of the neonicotinoid insecticides: acetamiprid, clothianidin, imidacloprid, and thiamethoxam. The observed peak

Table 2. SERS Peak Positions and Assignments for the Neonicotinoid Insecticides at a Concentration of 10 ppm (ν, Stretching; ρ, Rocking; δ, Deformation; ω, Wagging; τ, Twisting; s, Symmetric; as, Antisymmetric; ip, In-Plane; and oop, Out-of-Plane) pesticide acetamiprid

clothianidin

SERS peak position (cm−1) 576 631 728 960 1110 1591 453 597 636 659 761 871 950

imidacloprid

thiamethoxam

C

1242 1403 427 832 998 1290 1462 597 640 679 778 832 1403

peak assignment ω(N−CN) ω(C−C−C) ω(C−H) δ(C−C−N) ν(N−C) ring breathing ω(CC−NC), ω(H−C−NC−S), ν(C−Cl), ω(C−N−H−C), and δ(N−N−O) ω(C−CC), ω(H−C−NC), ω(CC−NC), and ω(C−NC−Cl) δ(N−C−C−H), ωoop(N−H), νs(S−C−C), ν(H−N−N−O), and ν(N−C) ω(C−H), ω(C−N−N−N), ω(C−N−C−C), ρ(C−H), and νas(S−C−C) ω(N−NO2) ωoop(C−H) ρip(C−H), δip(N−H), ν(C−N), and δ(C−CC) τoop(C−H), δip(C−H), and δ(N−H) δ(C−H) and δ(N−H) N−C−C (C−C−C)ip benzene (C−H)oop benzene N−C−H (C−H)ip benzene C−Cl linkage hydrocarbons

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Figure 3. SERS spectra of the organothiophosphate insecticides examined in this study: (a) carbophenothion at 0.1 and 10 ppm, with acetone shown as the reference, (b) chlorpyrifos at 10 ppm, with acetone shown as the reference, (c) coumaphos at 0.01 and 10 ppm, with water shown as the reference, (d) malathion at 0.1 and 10 ppm, with water shown as the reference, (e) phosalone at 1 and 10 ppm with acetone shown as the reference, (f) phosmet at 0.1 and 10 ppm, with acetone shown as the reference, and (g) profenofos at 0.01 and 1 ppm, with ethanol shown as the reference.

peaks listed for the 10 ppm sample.38 In general, the peaks with strong intensity in the 10 ppm spectra also occurred in the spectra at lower concentrations for the neonicotinoids. The intermediate concentrations, meaning the concentrations measured in between 10 ppm and the LOD, for acetamiprid, imidacloprid, and thiamethoxam are shown in Figure S3 of the Supporting Information for comparison. Organothiophosphate Insecticides. Figure 3 displays the SERS spectra of the organothiophosphate insecticides: carbophenothion, chlorpyrifos, coumaphos, malathion, phosalone, phosmet, and profenofos. In Figure 3a, the SERS spectra of 10 and 0.1 ppm of carbophenothion exhibit similar peaks from 300 to 1600 cm−1 (Table 3).17 The SERS peaks observed for 10 ppm of chlorpyrifos (Figure 3b) are listed in Table 3 with their assignments.39 The LOD for chlorpyrifos in this study was 10 ppm, where the characteristic peaks were not observed when

positions as well as their assignments are listed in Table 2. The peaks that appear in the SERS spectrum of 10 ppm of acetamiprid (Figure 2a) are consistent with reports in the literature.11,33,34 The LOD for acetamiprid using the SERS technique is 0.01 ppm, as evidenced by peaks at 634 and 965 cm−1 corresponding to C−C−C wagging and C−C−N deformation. The observed peaks in the SERS spectrum of 10 ppm of clothianidin (Figure 2b) are also consistent with literature reports.35 The LOD for clothianidin is 1 ppm, as evidenced by the appearance of peaks at 636, 659, and 761 cm−1.35 In Figure 2c, the SERS spectrum for 10 ppm for imidacloprid is shown, where the LOD is 0.1 ppm, indicated by the peaks at 427, 832, and 998 cm−1.36,37 The remaining peaks observed resemble those in the solvent spectrum, which is acetone added to gold nanoparticles and HCl. Finally, the LOD for thiamethoxam is 0.1 ppm (Figure 2d) and exhibits the same D

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Journal of Agricultural and Food Chemistry 1 ppm of chlorpyrifos was added to gold nanoparticles. Figure 3c shows the SERS spectrum of 10 ppm of coumaphos, where the LOD is 0.01 ppm, as exhibited by the appearance of the characteristic peaks at 636, 1349, and 1725 cm−1.21 The intensity of the 0.01 ppm SERS spectra is much higher than the 10 ppm spectra, and this is attributed to using a lower concentration of nanoparticles for this measurement; i.e., 0.2 mL of gold nanoparticles was added to 0.8 mL of 0.01 ppm of coumaphos (see the Materials and Methods). This method results in a higher ratio of pesticide molecules to nanoparticles, leading to nanoparticle aggregation. In addition, several other peaks appear in the 0.01 ppm of coumaphos spectrum, but they occur at similar positions to peaks observed in the SERS spectrum of water added to colloidal gold nanoparticles with HCl added. The SERS spectra of 10 ppm of malathion is shown in Figure 3d, where the LOD is 0.1 ppm, as evidenced by the peaks that appear at 503, 628, 829, 1236, and 1392 cm−1.11,39,40 In Figure 3e, the SERS spectrum for 10 ppm of phosalone exhibits several peaks that are distinctly different compared to the solvent reference but only one of the peaks can be assigned on the basis of literature findings: the peak at 656 cm−1 is assigned to the PS stretch in the (RO)2P(S−)S moiety (R = alkyl group).21 The LOD for phosalone is 1 ppm, which exhibits the same peak positions as the 10 ppm sample in the 300−1600 cm−1 range. For 10 ppm of phosmet (Figure 3f), the peaks observed from 500 to 1800 cm−1 are consistent with reports in the literature.11,28 The LOD for phosmet was 0.1 ppm and had similar peaks in its spectrum compared to the 10 ppm sample at 478, 501, 608, 778, 1194, 1409, and 1451 cm−1. A peak at 1273 cm−1 occurred in the 0.1 ppm phosmet spectrum but not the 10 ppm spectrum and is assigned to the C−N stretching vibration mode in S−CH2−N.10 For profenofos shown in Figure 3g, several peaks appear in both the 1 and 0.01 ppm spectra but the peaks at 656, 758, 1177, 1247, and 1576 cm−1 are consistent with a study on SERS of profenofos using silvercoated gold nanoparticles; however, there are no spectral assignments listed.18 For this pesticide, 1 ppm was shown instead of 10 ppm because the more concentrated sample had a SERS intensity that was significantly higher than the 0.01 ppm sample, making it difficult to plot both on one graph and compare. The intermediate concentrations for carbophenothion, coumaphos, malathion, and phosmet are shown in Figure S3 of the Supporting Information for comparison. Fungicides. Figure 4 displays the SERS spectra of the fungicides: diphenylamine, fludioxonil, thiabendazole, and thiram. The SERS peak positions of the 10 ppm sample for each fungicide are listed in Table 4, along with their vibrational mode assignments. The SERS peaks for 10 ppm of diphenylamine, a diphenyl fungicide, are presented in Figure 4a and resemble reported literature peak positions.22 The LOD of diphenylamine is 0.01 ppm, where the peaks listed above also appear in the 0.01 ppm spectrum, except for the peaks at 1219 and 1584 cm−1. Fludioxonil, a pyrrole fungicide, has several distinct peaks in both the 10 and 0.1 ppm spectra, shown in Figure 4b. Only two of the peaks appear in both spectra and occur at 1188 and 1321 cm−1, and no vibrational mode assignments are made here. A few of the peaks are consistent with a recent study performing SERS of fludioxonil and other pesticides using a smartphone-based approach, although more spectral detail is observed with the benchtop Raman system employed here.23 In Figure 4c, the LOD for thiabendazole, a benzimidazole fungicide, was 0.1 ppm, as evidenced by the

Table 3. SERS Peak Positions and Assignments for the Organothiophosphate Insecticides at a Concentration of 10 ppm (ν, Stretching; ρ, Rocking; δ, Deformation; ω, Wagging; τ, Twisting; s, Symmetric; as, Antisymmetric; ip, In-Plane; and oop, Out-of-Plane) pesticide carbophenothion

chlorpyrifos

coumaphos

malathion

phosalone phosmet

profenofos

SERS peak position (cm−1) 345 407 492 540 628 744 1069 1092 1177 1573 617 676 752 800 1100 1242 1457 1567 636 675 1195 1349 1556 1725 503 628 823 1013 1129 1154 1392 1457 656 501 608 668 778 1015 1194 1300 1380 1409 1772 656 758 1177 1247 1576

peak assignment

ν(C−C) and ring breathing

ν(C−C) and ring breathing ring deformation ring breathing ν(CC) ν(CC) ν(CC) ν(CC) ν(CC) ν(CC) ν(PS)

carbonyl ν(P−S) ν(PS) ν(C−O−C) ν(P−O−CH3) ν(C−C) ν(CH2) ν(CH3) δ(CH2) and δ(CH3) ν(PS) in (RO)2P(S−)S (R = alkyl group) ρ(CH2) and ρ(PO2) δ(CO) δ(PS) ν(P−O) and δ(CH3) ν(P−O−C) δ(C−N) ν(C−C) δ(CH3) δ(C−H) in S−CH2−N ν(CO)

appearance of the peaks at 634, 789, 1015, and 1276 cm−1.19 The SERS spectrum for 1 ppm of thiram, a dithiocarbamate fungicide, is displayed in Figure 4d, where the LOD is 0.001 ppm, as a result of the reoccurrence of the peaks at 557 and 1380 cm−1.11,41 Similar to profenofos (Figure 3g), the SERS spectrum of 1 ppm of thiram is shown instead of 10 ppm for ease of comparison to the E

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Figure 4. SERS spectra of the fungicides examined in this study: (a) diphenylamine at 0.01 and 10 ppm, with water shown as the reference, (b) fludioxonil at 0.1 and 10 ppm, with water shown as the reference, (c) thiabendazole at 0.1 and 10 ppm, with methanol shown as the reference, and (d) thiram at 0.001 and 1 ppm, with acetone shown as the reference.

SERS spectrum of 0.001 ppm. The intermediate concentrations for diphenylamine, fludioxonil, thiabendazole, and thiram are shown in Figure S3 of the Supporting Information for comparison. Miscellaneous Insecticides and DEET. Figure 5 exhibits the SERS spectra of miscellaneous insecticides: carbofuran, methomyl, permethrin, transfluthrin, and trichlorfon. In addition, the SERS spectrum of DEET, an insect repellent, is displayed in Figure 5f. The SERS peak positions as well as the vibrational mode assignments are listed in Table 5. Carbofuran is a benzofuranyl methylcarbamate insecticide and displays several peaks in the 300−1600 cm−1 range, as seen in Figure 5a, for the 10 ppm spectrum that are consistent with literature findings, although no specific vibrational mode assignments are listed.42 The LOD of carbofuran using the SERS technique described here is 0.01 ppm, where peaks at 625 and 1392 cm−1 are observed in the 0.01 and 10 ppm spectra and not the reference water spectrum. In Figure 5b, the oxime carbamate insecticide, methomyl, has a LOD of 0.1 ppm, as evidenced by the peaks at 529, 997, and 1021 cm−1.43 Figure 5c shows the SERS spectra of permethrin, a pyrethroid ester insecticide, at 10 and 0.001 ppm, where they both exhibit peaks that are consistent with the literature.25 The LOD of permethrin is 0.001 ppm, where the 501, 998, and 1598 cm−1 peaks can be seen, albeit weak in intensity. Transfluthrin (Figure 5d) is also a pyrethroid ester insecticide, where the LOD is 1 ppm based on the appearance of the peaks at 529, 996, 1168, 1525, and 1578 cm−1.43 For trichlorfon, the LOD is 0.001 ppm (Figure 5e), as evidenced by the occurrence of peaks at 571, 600, 657, 721, 1013, 1132, 1177, and 1273 cm−1.20 Figure 5f shows the SERS spectrum of 1 and 10 ppm of DEET as well as the background spectrum of ethanol. The peaks at 520, 684, and 996 cm−1 appear in both the 1 and 10 ppm samples.24 The intermediate concentrations for carbofuran, methomyl, and trichlorfon are shown in Figure S3 of the Supporting Information for comparison. To demonstrate the reproducibility of the technique, SERS spectra of one pesticide from each group was selected and measured in triplicate (Figure S4 of the Supporting Information). The SERS spectra of acetamiprid, coumaphos,

Table 4. SERS Peak Positions and Assignments for the Fungicides at a Concentration of 10 ppm (ν, Stretching; ρ, Rocking; δ, Deformation; ω, Wagging; τ, Twisting; s, Symmetric; as, Antisymmetric; ip, In-Plane; and oop, Out-of-Plane) pesticide diphenylamine

fludioxonil thiabendazole

thiram

F

SERS peak position (cm−1) 320 410 518 566 639 880 993 1018 1196 1219 1584 1188 1321 634 789 1015 1117 1151 1276 1400 1462 1499 1570 1592 1626 356 440 554 931 1148 1380 1524

peak assignment δip(C−NHC6H5) (C−C)oop ring torsion (C−C)oop ring torsion δip(C−C−C) δip(C−C−C) ωoop(C−H) ring breathing ωip(C−H) δip(C−H) δip(N−H) νip(C−C)

δ(C−C−C) and δ(S−C−N) δ(C−H) outer surface δ(C−H) inner surface δ(C−H) inner surface δ(C−H) inner surface ring stretching ν(CC) ν(CN) ν(CC) ν(CN) ν(CN) ν(CN) δ(SC−S) and δ(C−S−S) δ(CH3−N−C) and ν(CS) ν(S−S) ν(CH3−N) and ν(CS) ρ(CH3) and ν(C−N) δ(CH3) and ν(C−N) ρ(CH3) and ν(C−N) DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Figure 5. SERS spectra of (a) carbofuran at 10 and 0.01 ppm, with water shown as the reference, (b) 0.1 and 10 ppm of methomyl, with methanol shown as the reference, (c) permethrin at 0.001 and 10 ppm, with acetone shown as the reference, (d) transfluthrin at 1 and 10 ppm, with ethanol shown as the reference, (e) trichlorfon at 10 and 0.001 ppm, with ethanol shown as the reference, and (f) DEET at 1 and 10 ppm, with ethanol shown as the reference.

diphenylamine, and trichlorfon are shown in Figure S4 of the Supporting Information as representative samples. Table S1 of the Supporting Information lists two of the main Raman peaks for each pesticide, along with the average SERS intensity and relative standard deviation (% RSD) at these peak positions. The average % RSD values for acetamiprid, coumaphos, diphenylamine, and trichlorfon were 6.6, 4.1, 15.1, and 6.3, respectively. The % RSD was higher for diphenylamine, where the intensity of the SERS spectra in the 700−1600 cm−1 range varied significantly more than the other pesticides. Also, concentration curves for acetamiprid, diphenylamine, and trichlorfon are plotted in Figure S5 of the Supporting Information, where a linear trend is observed for all samples when examining the SERS intensity as a function of the concentration at designated SERS peak positions. Pesticide Mixtures. Finally, the simultaneous detection of two pesticides, phosmet and thiram, both in a mixture solution

and on apple skin samples, was performed. These pesticides were chosen based on their distinct and strong Raman signatures with the SERS technique used above. Mixtures of 10 ppm of phosmet and 10 ppm of thiram were prepared with the following volume ratios: 1:3, 1:1, and 3:1 phosmet/thiram. The SERS spectra of the pure pesticide samples and their mixtures are presented in Figure 6a. These spectra have been baselinecorrected by subtracting the intensity of the absolute minimum of the spectra to yield the most coherent and expected peak intensity trends for this detection system. The SERS spectrum for phosmet exhibits peaks at 499, 605, 712, 780, 1015, and 1377 cm−1 that are distinctly different from the SERS spectrum of thiram, where the main peaks occur at 552, 932, 1144, 1374, and 1512 cm−1. These peak positions are indicated in Figure 6a with arrows. The expected concentration trends within the data are shown in Figure S6 of the Supporting Information, where the G

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Journal of Agricultural and Food Chemistry intensities at 605 cm−1 for phosmet and 1512 cm−1 for thiram as a function of the mixture concentration ratios are plotted as a representative comparison. The intensity at 605 cm−1 (phosmet peak) increases with an increasing phosmet concentration, while the peak at 1512 cm−1 (thiram peak) decreases in intensity with a decreasing thiram concentration. One notable feature of the mixture spectra is that the thiram peaks tend to dominate the spectra over the phosmet peaks, in terms of Raman signal intensity. This is likely due to increased binding affinity of thiram to the gold nanoparticle surface compared to phosmet, where thiram has a disulfide bond that spontaneously breaks upon exposure to gold nanoparticles and binds through the Au−S bond.41 Phosmet also has the potential to form this gold− thiolate bond but only has two sulfur atoms available for binding, whereas thiram has four sulfur atoms. To distinguish the 1:3, 1:1, and 3:1 mixtures of phosmet and thiram, we used PCA. The PCA scatter plot is shown in Figure 6b. The PCA plot was calculated without performing a baseline correction and found solid statistical correlation between data sets using the peaks listed above for phosmet and thiram, with 99% of the data explained by the first two components. The PCA scatter plot shows natural groupings within the data sets for each sample while also showing the distinct separation between the different mixture samples. Next, pesticide mixtures at the same volume ratios of 1:3, 1:1, and 3:1 phosmet/thiram were added to pieces of apple skin. The SERS spectra of the pesticide-contaminated apple skin samples mixed with gold nanoparticles are displayed in Figure 6c, where they are baseline-corrected and offset for clarity. There are some differences in the SERS intensity compared to the method using the pesticide mixtures in solution, which may be due to variability in the apple skin method. For example, it is possible that there is a reduced transfer of pesticides from the apple skin to the nanoparticles compared to directly adding the pesticides to the nanoparticles. Again, the peak positions for thiram and phosmet are indicated in Figure 6c with arrows. The concentration trends within the data are shown in Figure S6 of the Supporting Information, where the intensities at 605 cm−1 for phosmet and 1512 cm−1 for thiram as a function of the mixture concentration ratios on apple skin are plotted as a representative comparison. Similar to the direct addition method, the intensity at 605 cm−1 increases with an increasing phosmet concentration, while the peak at 1512 cm−1 decreases in intensity with a decreasing thiram concentration. The corresponding PCA plot is shown in Figure 6d, where the natural groupings within the data sets for each sample and the distinct separation between samples can be observed. Hence, PCA successfully discriminates the different pesticide sample mixtures and shows potential for the SERS technique described above coupled with PCA to be an option for detecting multiple pesticides at parts per million concentrations. This method for testing real world samples is simple to implement, where the pesticide-containing apple skin pieces are added directly to the gold nanoparticle solutions and measured in the liquid phase, requiring no extraction or drying for faster measurement times. The LOD was determined for several pesticides utilizing SERS and colloidal gold nanoparticles. For certain pesticides, the LOD was as low as 1 ppb using this technique. This method was rapid, sensitive, and versatile, where a significant number and variety of pesticides were detected, which could potentially lead to the development of a pesticide library. In addition, the LODs achieved with this method approximate typical residue

Table 5. SERS Peak Positions and Assignments for the Miscellaneous Insecticides and DEET at a Concentration of 10 ppm (ν, Stretching; ρ, Rocking; δ, Deformation; ω, Wagging; τ, Twisting; s, Symmetric; as, Antisymmetric; ip, In-Plane; and oop, Out-of-Plane) pesticide carbofuran methomyl

permethrin

transfluthrin

trichlorfon

DEET

SERS peak position (cm−1) 625 1392 529 775 891 942 997 1021 1089 1115 1231 1346 501 631 998, 1146 1165 1213 1242 1375 1598 529 800 996 1168 1525 1587 436 453 571 600 657 721 1013 1132 1177 1273 1396 520 684 996

peak assignment

ν(C−S)

ring breathing

δoop(C−Cl) ν(C−Cl) symmetric stretching benzene ring breathing δip(C−H) in the benzene ring ν(C−O) ν(C−O) νas(C−O−C) δip(CH2) ν(CC) in the benzene ring ν(C−Cl) ν(C−Cl) hydrocarbons hydrocarbons hydrocarbons hydrocarbons ν(C−Cl) and δ(PO−C) δ(O−PO) and ν(C−Cl) δ(C−P) ν(C−Cl) ν(P−C) ν(PO) ν(C−C) τ(CH3) and ν(PO) δ(O−H) δ(C−H) δ(C−H) + δ(O−H) (C−H) (C−H) aromatic hydrocarbons

tolerance levels for food items that occur in the ppb to ppm range. A mixture of two pesticides was also examined on apple skin, where PCA distinguished the different types of mixtures based on the concentration ratio of the two pesticides. The simultaneous detection of multiple pesticides on apple skin may have potential to be a tool for real-world pesticide testing. Future studies may include determining the LOD in the mixture samples, investigating other pesticides, more complex mixtures containing three or more pesticides, and measuring pesticides on other food items. The development of hand-held Raman systems could be implemented with the SERS method to make this method portable for field use. The results presented here have the potential to impact technologies aimed at detecting low concentrations of pesticides that need to be sensitive, efficient, H

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Journal of Agricultural and Food Chemistry

Figure 6. (a) SERS spectra and (b) PCA plot of 10 ppm of phosmet, 10 ppm of thiram, and the pesticide mixtures at ratios of 1:3, 1:1, and 3:1 phosmet/thiram prepared by the direct addition method. (c) SERS spectra and (d) PCA plot of 10 ppm of phosmet, 10 ppm of thiram, and the pesticide mixtures at ratios of 1:3, 1:1, and 3:1 phosmet/thiram added to apple skin samples and mixed with gold nanoparticles. The black arrows in panels a and c indicate the peak positions examined for PCA, which occur at 499, 605, 712, 780, 1015, and 1377 cm−1 for phosmet and 552, 932, 1144, 1377, and 1512 cm−1 for thiram.

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ABBREVIATIONS USED SERS, surface-enhanced Raman spectroscopy; ppm, parts per million; ppb, parts per billion; LOD, limit of detection; SPR, surface plasmon resonance

and easy-to-use to help protect humans and the environment from the harmful effects of pesticide exposure.

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ASSOCIATED CONTENT

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S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.9b01544.

(1) Ahmed Azmi, M.; Naqvi, S. N. H. Pesticide pollution, resistance and health hazards. In PesticidesThe Impacts of Pesticide Exposure; Stoytcheva, M., Ed.; InTech: Rijeka, Croatia, 2011; pp 1−25, DOI: 10.5772/13758. (2) Van Maele-Fabry, G.; Lantin, A. C.; Hoet, P.; Lison, D. Childhood leukemia and parental occupational exposure to pesticides: A systematic review and meta-analysis. Cancer Causes Control 2010, 21 (6), 787−809. (3) Pimentel, D.; Culliney, T. W.; Bashore, T. Public Health Risks Associated with Pesticides and Natural Toxins in Foods. IPM World Textbook; Regents of the University of Minnesota: Minneapolis, MN, 2013; https://ipmworld.umn.edu/pimentel-public-health (accesssed March 1, 2019). (4) Kim, K. H.; Kabir, E.; Jahan, S. A. Exposure to pesticides and the associated human health effects. Sci. Total Environ. 2017, 575, 525− 535. (5) Colborn, T.; vom Saal, F. S.; Soto, A. M. Developmental effects of endocrine-disrupting chemicals in wildlife and humans. Environ. Health Perspect. 1993, 101, 378−384. (6) Xu, M. L.; Gao, Y.; Han, X. X.; Zhao, B. Detection of pesticide residues in food using surface-enhanced Raman spectroscopy: A review. J. Agric. Food Chem. 2017, 65, 6719−6726. (7) Ellis, D. I.; Muhamadali, H.; Haughey, S. A.; Elliott, C. T.; Goodacre, R. Point-and-shoot: Rapid quantitative detection methods for on-site food fraud analysisMoving out of the laboratory and into the food supply chain. Anal. Methods 2015, 7, 9401−9414. (8) Craig, A. P.; Franca, A. S.; Irudayaraj, J. Surface-enhanced Raman spectroscopy applied to food safety. Annu. Rev. Food Sci. Technol. 2013, 4, 369−380. (9) Cordella, C.; Moussa, I.; Martel, A.; Sbirrazzuoli, N.; LizzaniCuvelier, L. Recent developments in food characterization and

High-resolution TEM images and lattice spacing analysis (Figure S1), absorption spectra of nanoparticles with and without pesticides (Figure S2), SERS spectra to demonstrate the reproducibility of the technique (Figures S3 and S4), SERS spectra of pesticides at other concentrations (Figure S5), peak intensity variation curves for the different mixture concentrations (Figure S6), and table listing the % RSD values for the reproducibility data (Table S1) (PDF)

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*Telephone: 1-407-502-6921, ext. 1133. E-mail: anne-marie. [email protected]. ORCID

A. M. Dowgiallo: 0000-0001-6997-5234 Funding

Financial support is provided by Ocean Optics, Inc. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank Y. Emirov for collecting TEM images at the Nanotechnology Research & Education Center (NREC), University of South Florida. I

DOI: 10.1021/acs.jafc.9b01544 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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