I would like to thank Javier Hern&#225;ndez-Borges and Cecilia Ortega-Zamora for their invaluable support. I also want to thank the Universidad EAN and the Universidad de La Laguna.

1. Preparation of the stock solutions
NOTE: It is recommended to wear nitrile gloves, a lab coat, and safety glasses during the entire protocol.
<ol>
	<li>Prepare a stock solution in acetone at 400 mg/L from a commercial mix of OCPs (see Table of Materials) at 2,000 mg/L in hexane:toluene (1:1) in a 25 mL volumetric flask. Table 1 shows each of the selected OCPs.</li>
	<li>Prepare the subsequent stock solutions in acetone at concentrations of 50 mg/L, 1 mg/L, and 0.08 mg/L in 10 mL volumetric flasks, and store them in amber glass vials at &#8722;18 &#176;C. 
	NOTE: The same solutions can be used throughout the work, but it is important to store them under these conditions just after each use.</li>
	<li>Prepare the stock solutions in acetone at concentrations of 20 mg/L and 0.4 mg/L from a commercial standard of 4,4&#39;-DDE-d8 at 100 mg/L in acetone in 10 mL volumetric flasks, and store in amber glass vials at &#8722;18 &#176;C. Use 4,4&#39;-DDE-d8 as an internal standard (IS).</li>
</ol>
2. Sample collection
<ol>
	<li>Collect approximately 0.5 kg of the upper 10 cm layer of an agricultural soil in a glass container. The soil object of this study was collected in a traditional agricultural zone of potato crops. 
	NOTE: Surface sampling with a spatula was carried out. However, the depth of the soil could influence its physicochemical characteristics. Therefore, if the organic carbon content varies with the depth, it is necessary to take samples at different depths.</li>
	<li>Take the soil sample to the laboratory, sift it with a 1 mm diameter sieve, and store it until analysis at 4 &#176;C in an amber glass container. 
	&#8203;NOTE: The same soil sample can be used throughout the work, but it is important to store it under these conditions just after each use.</li>
</ol>
3. Sample preparation via the modified QuEChERS method using ammonium formate
NOTE: Figure 1 shows a schematic representation of the modified QuEChERS method.
<ol>
	<li>Weigh 10 g of the soil sample in a 50 mL centrifuge tube, and add 50 &#181;L of the IS solution at 20 mg/L to yield 100 &#181;g/kg. For recovery purposes, also add the pesticide solutions prepared in step 1.2 to yield 10 &#181;g/kg, 50 &#181;g/kg, and 200 &#181;g/kg (n = 3 each).</li>
	<li>Shake the tube using a vortex for 30 s to better integrate the spike into the sample.</li>
	<li>Add 10 mL of water. Shake the tube using an automated shaker at 10 x g for 5 min.</li>
	<li>Add 10 mL of acetonitrile. Shake the tube again at 10 x g for 5 min.</li>
	<li>Add 5 g of ammonium formate (see Table of Materials), shake the tube vigorously for 1 min by hand, and centrifuge at 1,800 x g for 5 min.</li>
	<li>Transfer 1 mL of the acetonitrile extract to a 2 mL centrifuge tube containing 150 mg of anhydrous MgSO4, 50 mg of primary-secondary amine (PSA), and 50 mg octadecylsilane (C18) (see Table of Materials) for clean-up purposes by dispersive-solid phase extraction (d-SPE)8, vortex for 30 s, and centrifuge at 1,800 x g for 5 min.</li>
	<li>Transfer 200 &#181;L of the extract to an appropriately labeled autosampler vial with a 300 &#181;L fused insert, and perform an instrumental analysis using a GC-MS system (step 4). 
	&#8203;NOTE: Matrix-matched calibration is carried out following the same steps as previously using blank extracts, but 5 mL of the supernatant is cleaned in 15 mL tubes in the d-SPE step (step 3.6)&#160;and the spike and IS solutions are not added until step 3.7. Add the calibration standard solutions in the autosampler vials to yield 5 &#181;g/kg, 10 &#181;g/kg, 50 &#181;g/kg, 100 &#181;g/kg, 200 &#181;g/kg, and 400 &#181;g/kg, evaporate to dryness, and add 200 &#181;L of the matrix extracts.</li>
</ol>
4. Instrumental analysis by GC-MS
<ol>
	<li>Perform the GC-MS analyses using a GC-MS system with a single quadrupole mass spectrometer and an electron ionization interface (&#8722;70 eV) (see Table of Materials).</li>
	<li>Set the MS transfer line at 280 &#176;C and the ion source at 230 &#176;C.</li>
	<li>Use a 5%-phenyl-methylpolysiloxane 30 m x 250 &#181;m x 0.25 &#181;m column (see Table of Materials) and ultrahigh purity He as the carrier gas at a 1.2 mL/min constant flow rate.</li>
	<li>Maintain the GC oven at 60 &#176;C initially for 2 min, then ramp up the temperature to 160 &#176;C at 25 &#176;C/min, and hold for 1 min. Then, increase the temperature to 175 &#176;C at 15 &#176;C/min, and hold for 3 min. Then, increase to 220 &#176;C at 40 &#176;C/min, and hold for 3 min. Again, increase to 250 &#176;C at 30 &#176;C/min, and hold for 2 min. Finally, take the temperature to 310 &#176;C at 30 &#176;C/min, and hold for 2 min. The total analysis time is 22.125 min.</li>
	<li>Conduct a full autotune and an air and water check of the MS before each sequence.
	<ol>
		<li>Open the MassHunter acquisition software that controls all the parameters of the GC-MS system. 
		NOTE: The instrument system includes the MassHunter acquisition software by default.</li>
		<li>Open the &#34;View&#34; option on the toolbar, and click on Vacuum control, click on Tune, and click on Autotune. The autotune will end after a few minutes.</li>
		<li>Open the &#34;View&#34; option, and click on Instrument control.</li>
		<li>Click on Yes, and save the new tune file for the autotune.</li>
		<li>Open the &#34;View&#34; option on the toolbar, and click on Vacuum control, click on Tune again, and click on Air &#38; Water check. The air and water check will end after a few seconds.</li>
		<li>Open the &#34;View&#34; option, and click on Instrument control.</li>
		<li>Click on Yes, and save the new tune file for the air and water check.</li>
	</ol>
	</li>
	<li>Perform the injection using an autosampler (see Table of Materials) at 280 &#176;C in the splitless mode, keeping the injection volume 1.5 &#181;L. After 0.75 min of the injection, open the split at a 40 mL/min flow rate. 
	NOTE: Between injections, the 10 &#181;L syringe must be washed three times with ethyl acetate and three times with cyclohexane. All the injections are in duplicate.</li>
	<li>Analyze the analytes in selected ion monitoring (SIM) mode. This is the standard mode used in MS systems with a single quadrupole. 
	&#8203;NOTE: Table 1 shows the retention times (min) and the quantification parameters based on using one quantitation and two identification ions for the OCPs and the IS. The quantitative analysis is based on the ratio of the peak area of the quantitation ion to the ion of IS.</li>
</ol>
5. Data acquisition
<ol>
	<li>Open the MassHunter acquisition software that controls all the parameters of the GC-MS system.</li>
	<li>Open the &#34;Sequence&#34; option on the toolbar, and edit the sequence, including the sample name, the vial number, the number of injections, the instrumental method, and the name of the file to be generated. Add as many rows as necessary.</li>
	<li>Click on OK, and save the new sequence.</li>
	<li>Open the &#34;Sequence&#34; option on the toolbar again, and click on Run Sequence in the dropdown menu. A new window will open to confirm the injection method and the folder where the samples will be saved. Click on Run Sequence again, and the injection will begin.</li>
</ol>

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Comparison with accelerated solvent extraction.</a> Talanta. 93, 336-344 (2012).</li><li>Lesueur, C., Gartner, M., Mentler, A., Fuerhacker, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+four+extraction+methods+for+the+analysis+of+24+pesticides+in+soil+samples+with+gas+chromatography-mass+spectrometry+and+liquid+chromatography-ion+trap-mass+spectrometry.">Comparison of four extraction methods for the analysis of 24 pesticides in soil samples with gas chromatography-mass spectrometry and liquid chromatography-ion trap-mass spectrometry.</a> Talanta. 75 (1), 284-293 (2008).</li><li>&#208;urovi&#263;-Pej&#269;ev, R. D., Bursi&#263;, V. P., Zeremski, T. 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I have no conflicts of interest to disclose.

The original9 and the two official versions13,14 of the QuEChERS method use magnesium sulfate together with sodium chloride, acetate, or citrate salts to promote acetonitrile/water mixture separation during extraction. However, these salts tend to be deposited as solids on the surfaces in the mass spectrometry (MS) source, which causes the need for increased maintenance of liquid chromatography (LC)-MS-based methods. In terms of overcoming these disadvantages, Gonz&#225;lez-Curbelo et al.15 reported that the more volatile ammonium formate worked well to induce phase separation and the extraction of pesticide residues for both LC- and GC-tandem mass spectrometry (MS/MS). Subsequent studies have also used 0.5 g of ammonium formate per gram of sample to extract pesticide residues from various complex matrices16,17,18,19. In addition, the use of ammonium formate has been shown to provide lower amounts of co-extracted material20, which justifies its use for GC-MS-based methods. The present study, for the first time, reports this version to analyze pesticide residues in soils21.
The GC analysis of pesticide residues in complex matrices such as soils has some limitations because of the action of the co-extracted matrix components on the instrumental response of the pesticides, which causes inaccurate determination and lower sensitivity22,23. Hence, several improvements have been made to minimize the matrix effect, including optimized clean-up steps21. Nevertheless, the matrix effect still takes place and should be corrected as much as possible. In this sense, matrix-matched calibration has been the main approach used because it is very practical in compensating for the enhancement of the chromatographic signal with respect to that of pure solvents24. Thus, in this study, linearity was evaluated by building the calibration curves in pure acetonitrile and using soil extracts, and R2 values higher than or equal to 0.99 for all the OCPs were obtained using both approaches. However, when both calibration curves were compared, appreciable matrix effects were found in the range of &#8211;49% to 191% (Figure 2). Although the number of pesticides that suffered a strong matrix effect was only 3 of 17 (endrin, endrin ketone, and methoxychlor), subsequent studies were carried out using the matrix-matched calibration curves to compensate for the matrix effects to a greater extent.
No maximum residue limits (MRLs) have been established for pesticide residues in soils, but an LCL of 5 &#181;g/kg was set for all the OCPs, which is lower than the very demanding standard MRL set at 10 &#181;g/kg by the international legislation for the analysis of pesticide residues in agri-food products (Regulation 396/2005)11. In addition, the LCL of 5 &#181;g/kg provided a signal-to-noise ratio (S/N) of around 10 for all the OCPs. The high sensitivity of this method is similar to or even better than that obtained in other studies that have also analyzed OCPs in soils using the QuEChERS method followed by GC-MS. For example, in one study, 34 OCPs were analyzed using the official version of the QuEChERS method that uses a citrate buffer, and the limits of quantification (LOQs) were equal to or higher than 7 &#181;g/kg25. In particular, the LOQ values of &#945;-BHC, &#946;-BHC, lindane, and &#948;-BHC were between 206 &#181;g/kg and 384 &#181;g/kg. In another work, lindane and dieldrin were analyzed using the same version of the QuEChERS method, and LOQ values of 42 &#181;g/kg and 292 &#181;g/kg were obtained, respectively26. Likewise, another research work also determined aldrin and heptachlor using QuEChERS and GC-MS, with LOQ values of 13 and 23 &#181;g/kg, respectively27.
The recovery and reproducibility assessment was developed at three concentration levels (low, medium, and high) in triplicate (n = 9). For this purpose, the overall recovery values were determined by comparing the pesticide peak area/IS (4,4&#39;-DDE-d8) peak area ratios obtained from the soil samples spiked at the beginning of the application of the QuEChERS method using ammonium formate with those of matrix-matched calibration. In all cases, each replicate was injected twice in the same sequence. It should be noted that using an IS, an isotopically labeled standard, allows for compensating for the possible losses of the pesticides that take place during the whole procedure, as well as the matrix effect and/or possible variability in the instrument. According to the results, most pesticides met the acceptability criteria of 70%-120% recovery values with RSD &#8804;20% at each spiking level28, which demonstrated the effectiveness and repeatability of the method. Nevertheless, the overall recovery values (n = 9) were slightly higher than 120% for heptachlor (122%), endrin (121%), and &#946;-endosulfan (130%), though they were consistent (RSDs &#60;13%). In this sense, considering the overall recovery values at three spiking levels, an acceptability criterion of 30%-140% with RSD values &#8804;20% has been established28.
In conclusion, the QuEChERS method using ammonium formate coupled with GC-MS can successfully determine OCPs in agricultural soil samples. It was shown in this study that the simple addition of 5 g of ammonium formate to induce phase separation between the water and acetonitrile layers ensured suitable extraction with high recoveries of the selected pesticides. However, the matrix effect continued to take place, so other approaches, such as the addition of analyte protectants, should be studied in subsequent works. In any case, this alternative to the official QuEChERS versions may be used to avoid the undesirable solids deposited in the analytical system due to the use of magnesium and sodium salts, especially in routine LC-MS-based analysis. In the latter case, it would be even more interesting since ammonium formate is an aid for ionization in positive electrospray ionization and may enhance the formation of ammonium adducts instead of sodium adducts.

The need to increase food production has led to the intensive and widespread use of pesticides worldwide over the last few decades. Pesticides are applied to the crops to protect them from pests and increase crop yields, but their residues usually end up in the soil environment, especially in agricultural areas1. Furthermore, some pesticides, such as organochlorine pesticides (OCPs), have a very stable structure, so their residues do not decompose easily and persist in the soil for a long time2. Generally, the soil has a high capacity to accumulate pesticide residues, especially when it has a high content of organic matter3. As a result, the soil is one of the environmental compartments most contaminated by pesticide residues. As an example, one of the complete studies to date found that 83% of 317 agricultural soils from across the European Union were contaminated with one or more pesticide residues4. 
Soil pollution by pesticide residues may affect non-target species, soil function, and consumer health through the food chain because of the high toxicity of the residues5,6. Consequently, the evaluation of pesticide residues in soils is essential to assess their potential negative effects on the environment and human health, particularly in developing countries due to a lack of strict regulations on the use of pesticides7. This makes pesticide multi-residue analysis increasingly important. However, the rapid and accurate analysis of pesticide residues in soils is a difficult challenge due to the large number of interfering substances, as well as the low concentration level and the diverse physicochemical properties of these analytes4. 
Of all the pesticide residue analysis methods, the QuEChERS method has become the quickest, easiest, cheapest, most effective, robust, and safest option8. The QuEChERS method involves two steps. In the first step, a microscale extraction based on partitioning via salting-out between an aqueous and an acetonitrile layer is performed. In the second step, a cleaning process is carried out employing a dispersive solid phase extraction (dSPE); this technique uses small amounts of several combinations of porous sorbents to remove matrix-interfering components and overcomes the disadvantages of conventional SPE9. Hence, the QuEChERS is an environmentally friendly approach with little solvent/chemical going to waste that provides very accurate results and minimizes potential sources of random and systematic errors. In fact, it has been successfully applied for the high-throughput routine analysis of hundreds of pesticides, with strong applicability in almost all types of environmental, agri-food, and biological samples8,10. This work aims to apply and validate a new modification of the QuEChERS method that was previously developed and coupled to GC-MS to analyze OCPs in agricultural soil.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>15 mL disposable glass conical centrifuge tubes</td>
			<td>PYREX</td>
			<td>99502-15</td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL centrifuge tubes</td>
			<td>Eppendorf</td>
			<td>30120094</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL centrifuge tubes with screw caps</td>
			<td>VWR</td>
			<td>21008-169</td>
			<td></td>
		</tr>
		<tr>
			<td>5977B mass-selective detector</td>
			<td>Agilent Technologies</td>
			<td>1617R019</td>
			<td></td>
		</tr>
		<tr>
			<td>7820A gas chromatography system</td>
			<td>Agilent Technologies</td>
			<td>16162016</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetone</td>
			<td>Supelco</td>
			<td>1006582500</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile</td>
			<td>VWR</td>
			<td>83642320</td>
			<td></td>
		</tr>
		<tr>
			<td>Ammonium formate</td>
			<td>VWR</td>
			<td>21254260</td>
			<td></td>
		</tr>
		<tr>
			<td>Automatic shaker KS 3000 i control</td>
			<td>IKA</td>
			<td>3940000</td>
			<td></td>
		</tr>
		<tr>
			<td>Balance</td>
			<td>Sartorius Lab Instruments Gmbh &#38; Co</td>
			<td>ENTRIS224I-1S</td>
			<td></td>
		</tr>
		<tr>
			<td>Bondesil-C18, 40 &#181;m</td>
			<td>Agilent Technologies</td>
			<td>12213012</td>
			<td></td>
		</tr>
		<tr>
			<td>Bondesil-PSA, 40 &#181;m</td>
			<td>Agilent Technologies</td>
			<td>12213024</td>
			<td></td>
		</tr>
		<tr>
			<td>Cyclohexane</td>
			<td>VWR</td>
			<td>85385320</td>
			<td></td>
		</tr>
		<tr>
			<td>EPA TCL pesticides mix</td>
			<td>Sigma Aldrich</td>
			<td>48913</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethyl acetate</td>
			<td>Supelco</td>
			<td>1036492500</td>
			<td></td>
		</tr>
		<tr>
			<td>G4567A automatic sampler</td>
			<td>Agilent Technologies</td>
			<td>19490057</td>
			<td></td>
		</tr>
		<tr>
			<td>HP-5ms Ultra Inert (5%-phenyl)-methylpolysiloxane 30 m x 250 &#181;m x 0.25 &#181;m column</td>
			<td>Agilent Technologies</td>
			<td>19091S-433UI</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium sulfate monohydrate</td>
			<td>Sigma Aldrich</td>
			<td>434183-1KG</td>
			<td></td>
		</tr>
		<tr>
			<td>Mega Star 3.R centrifuge</td>
			<td>VWR</td>
			<td>521-1752</td>
			<td></td>
		</tr>
		<tr>
			<td>Milli-Q gradient A10</td>
			<td>Millipore</td>
			<td>RR400Q101</td>
			<td></td>
		</tr>
		<tr>
			<td>p,p&#39;-DDE-d8</td>
			<td>Dr Ehrenstorfer</td>
			<td>DRE-XA12041100AC</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 2 - 200 &#181;L</td>
			<td>BRAND</td>
			<td>732008</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 5 mL</td>
			<td>BRAND</td>
			<td>702595</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette tips 50 - 1000 uL</td>
			<td>BRAND</td>
			<td>732012</td>
			<td></td>
		</tr>
		<tr>
			<td>Pippette Transferpette S variabel 10 - 100 &#181;L</td>
			<td>BRAND</td>
			<td>704774</td>
			<td></td>
		</tr>
		<tr>
			<td>Pippette Transferpette S variabel 100 - 1000 &#181;L</td>
			<td>BRAND</td>
			<td>704780</td>
			<td></td>
		</tr>
		<tr>
			<td>Pippette Transferpette S variabel 20 - 200 &#181;L</td>
			<td>BRAND</td>
			<td>704778</td>
			<td></td>
		</tr>
		<tr>
			<td>Pippette Transferpette S variabel 500 - 5000 &#181;L</td>
			<td>BRAND</td>
			<td>704782</td>
			<td></td>
		</tr>
		<tr>
			<td>Vials with fused-in insert</td>
			<td>Sigma Aldrich</td>
			<td>29398-U</td>
			<td></td>
		</tr>
		<tr>
			<td>OCPs</td>
			<td></td>
			<td>CAS registry number</td>
			<td></td>
		</tr>
		<tr>
			<td>&#945;-BHC</td>
			<td></td>
			<td>319-84-6</td>
			<td></td>
		</tr>
		<tr>
			<td>&#946;-BHC</td>
			<td></td>
			<td>319-85-7</td>
			<td></td>
		</tr>
		<tr>
			<td>Lindane</td>
			<td></td>
			<td>58-89-9</td>
			<td></td>
		</tr>
		<tr>
			<td>&#948;-BHC</td>
			<td></td>
			<td>319-86-8</td>
			<td></td>
		</tr>
		<tr>
			<td>Heptachlor</td>
			<td></td>
			<td>76-44-8</td>
			<td></td>
		</tr>
		<tr>
			<td>Aldrin</td>
			<td></td>
			<td>309-00-2</td>
			<td></td>
		</tr>
		<tr>
			<td>Heptachlor epoxide</td>
			<td></td>
			<td>1024-57-3</td>
			<td></td>
		</tr>
		<tr>
			<td>&#945;-Endosulfan</td>
			<td></td>
			<td>959-98-8</td>
			<td></td>
		</tr>
		<tr>
			<td>4,4&#39;-DDE-d8 (IS)</td>
			<td></td>
			<td>93952-19-3</td>
			<td></td>
		</tr>
		<tr>
			<td>4,4&#39;-DDE</td>
			<td></td>
			<td>72-55-9</td>
			<td></td>
		</tr>
		<tr>
			<td>Dieldrin</td>
			<td></td>
			<td>60-57-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Endrin</td>
			<td></td>
			<td>72-20-8</td>
			<td></td>
		</tr>
		<tr>
			<td>&#946;-Endosulfan</td>
			<td></td>
			<td>33213-65-9</td>
			<td></td>
		</tr>
		<tr>
			<td>4,4&#39;-DDD</td>
			<td></td>
			<td>72-54-8</td>
			<td></td>
		</tr>
		<tr>
			<td>Endosulfan sulfate</td>
			<td></td>
			<td>1031-07-8</td>
			<td></td>
		</tr>
		<tr>
			<td>4,4&#39;-DDT</td>
			<td></td>
			<td>50-29-3</td>
			<td></td>
		</tr>
		<tr>
			<td>Endrin ketone</td>
			<td></td>
			<td>53494-70-5</td>
			<td></td>
		</tr>
		<tr>
			<td>Methoxychlor</td>
			<td></td>
			<td>72-43-5</td>
			<td></td>
		</tr>
	</tbody>
</table>

analysis of organochlorine pesticides in a soil sample by a modified quechers approach using ammonium formate

Currently, the QuEChERS method represents the most widely used sample preparation protocol worldwide for analyzing pesticide residues in a broad variety of matrices both in official and non-official laboratories. The QuEChERS method using ammonium formate has previously proven to be advantageous compared to the original and the two official versions. On the one hand, the simple addition of 0.5 g of ammonium formate per gram of sample is sufficient to induce phase separation and achieve good analytical performance. On the other hand, ammonium formate reduces the need for maintenance in routine analyses. Here, a modified QuEChERS method using ammonium formate was applied for the simultaneous analysis of organochlorine pesticide (OCP) residues in agricultural soil. Specifically, 10 g of the sample was hydrated with 10 mL of water and then extracted with 10 mL of acetonitrile. Next, phase separation was carried out using 5 g of ammonium formate. After centrifugation, the supernatant was subjected to a dispersive solid-phase extraction clean-up step with anhydrous magnesium sulfate, primary-secondary amine, and octadecylsilane. Gas chromatography-mass spectrometry was used as the analytical technique. The QuEChERS method using ammonium formate is demonstrated as a successful alternative for extracting OCP residues from a soil sample.

The full validation of the analytical method was performed in terms of linearity, matrix effects, recovery, and repeatability.
Matrix-matched calibration curves with spiked blank samples at six concentration levels (5 &#181;g/kg, 10 &#181;g/kg, 50 &#181;g/kg, 100 &#181;g/kg, 200 &#181;g/kg, and 400 &#181;g/kg) were used for the linearity assessment. The determination coefficients (R2) were higher than or equal to 0.99 for all the OCPs. The lowest calibration level (LCL) was set at 5 &#181;g/kg, which meets the maximum permissible limit established at 10 &#181;g/kg for monitoring purposes in food applications11.
The matrix effect assessment was carried out by comparing the slopes of the OCP calibration curves in pure solvent and the matrix-matched calibration curves. The matrix effect was calculated using the following equation12:
Matrix effect (%) = (slope of the matrix-matched calibration curve&#8239;&#8722;&#8239;slope of the pure solvent-based calibration curve)/(slope of the pure solvent-based calibration curve)&#8239;&#215;&#8239;100.
Figure 2&#160;shows the matrix effect distributions for the OCPs studied by applying a modified QuEChERS method using ammonium formate to soil samples. Positive matrix effect percentages correspond to a signal enhancement, while negative percentages mean that there is signal suppression. Specifically, (1) values ranging between &#8722;20% and 20% correspond to a soft matrix effect; (2) values ranging between &#8722;20% and -50% or between 20% and 50% correspond to a medium matrix effect; (3) and values higher than 50% or lower than &#8722;50% mean that there is a strong matrix effect. As observed, more OCPs suffered soft or medium matrix effects, while fewer OCPs suffered strong matrix effects.
The recovery and repeatability were evaluated by spiking blank samples with pesticides at three concentration levels (10 &#181;g/kg, 50 &#181;g/kg, and 200 &#181;g/kg). Figure 3 shows the overall recovery values and relative standard deviation (RSD) values for all the pesticides and spiking levels (n = 9). As can be observed, the great majority of the OCPs studied presented average recovery percentages in the range of 70%-120%, with RSDs lower than 20%, except heptachlor, endrin, and &#946;-endosulfan, which gave slightly higher average recoveries.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64901/64901fig01.jpg" /> 
Figure 1: Representation of the modified QuEChERS method using ammonium formate to extract pesticide residues from the soil sample. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64901/64901fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64901/64901fig02.jpg" /> 
Figure 2:&#160;Distribution of the matrix effects versus retention times (min) for the 17 OCPs. A soft matrix effect corresponds to values between &#8722;20% and 20%; a medium matrix effect corresponds to values ranging between &#8722;20% and &#8722;50% or between 20% and 50%; a strong matrix effect corresponds to values that are greater than 50% or less than &#8722;50%. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64901/64901fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64901/64901fig03.jpg" /> 
Figure 3: Average recoveries for the 17 OCPs after spiking 10 &#181;g/kg, 50 &#181;g/kg, and 200 &#181;g/kg (n = 9) in the soil sample. The number of analytes within the acceptable recovery (70%-120 %) and RSD (&#60;20 %) range are provided, along with those labeled outside of that range. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/64901/64901fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Analyte</td>
			<td>Retention time (min)</td>
			<td>Quantifier ion</td>
			<td>Qualifier ion 1</td>
			<td>Qualifier ion 2</td>
		</tr>
		<tr>
			<td>&#945;-BHC</td>
			<td>11.35</td>
			<td>181</td>
			<td>219</td>
			<td>111</td>
		</tr>
		<tr>
			<td>&#946;-BHC</td>
			<td>11.90</td>
			<td>181</td>
			<td>219</td>
			<td>109</td>
		</tr>
		<tr>
			<td>Lindane</td>
			<td>12.01</td>
			<td>181</td>
			<td>183</td>
			<td>219</td>
		</tr>
		<tr>
			<td>&#948;-BHC</td>
			<td>12.39</td>
			<td>181</td>
			<td>219</td>
			<td>111</td>
		</tr>
		<tr>
			<td>Heptachlor</td>
			<td>13.24</td>
			<td>272</td>
			<td>100</td>
			<td>274</td>
		</tr>
		<tr>
			<td>Aldrin</td>
			<td>13.94</td>
			<td>263</td>
			<td>66</td>
			<td>265</td>
		</tr>
		<tr>
			<td>Heptachlor epoxide</td>
			<td>14.86</td>
			<td>353</td>
			<td>355</td>
			<td>81</td>
		</tr>
		<tr>
			<td>&#945;-Endosulfan</td>
			<td>15.71</td>
			<td>241</td>
			<td>239</td>
			<td>195</td>
		</tr>
		<tr>
			<td>4,4&#39;-DDE-d8 (IS)</td>
			<td>16.09</td>
			<td>254</td>
			<td>184</td>
			<td>326</td>
		</tr>
		<tr>
			<td>4,4&#39;-DDE</td>
			<td>16.12</td>
			<td>246</td>
			<td>318</td>
			<td>248</td>
		</tr>
		<tr>
			<td>Dieldrin</td>
			<td>16.18</td>
			<td>79</td>
			<td>263</td>
			<td>81</td>
		</tr>
		<tr>
			<td>Endrin</td>
			<td>16.57</td>
			<td>263</td>
			<td>317</td>
			<td>345</td>
		</tr>
		<tr>
			<td>&#946;-Endosulfan</td>
			<td>16.73</td>
			<td>195</td>
			<td>241</td>
			<td>159</td>
		</tr>
		<tr>
			<td>4,4&#39;-DDD</td>
			<td>16.89</td>
			<td>235</td>
			<td>237</td>
			<td>165</td>
		</tr>
		<tr>
			<td>Endosulfan sulfate</td>
			<td>17.61</td>
			<td>387</td>
			<td>227</td>
			<td>272</td>
		</tr>
		<tr>
			<td>4,4&#39;-DDT</td>
			<td>17.65</td>
			<td>235</td>
			<td>237</td>
			<td>165</td>
		</tr>
		<tr>
			<td>Endrin ketone</td>
			<td>18.64</td>
			<td>317</td>
			<td>67</td>
			<td>315</td>
		</tr>
		<tr>
			<td>Methoxychlor</td>
			<td>18.86</td>
			<td>227</td>
			<td>228</td>
			<td>212</td>
		</tr>
	</tbody>
</table>
Table 1:&#160;Retention times (min) and quantification parameters for the GC-MS analysis of the OCPs. Alpha-benzenehexachloride (&#945;-BHC); beta-benzenehexachloride (&#946;-BHC); lindane; delta-benzenehexachloride (&#948;-BHC); heptachlor; aldrin; heptachlor epoxide; &#945;-endosulfan; 4,4&#39;-dichlorodiphenyldichloroethylene-d8 (4,4&#39;-DDE-d8) (IS); 4,4&#39;-dichlorodiphenyldichloroethylene (4,4&#39;-DDE); dieldrin; endrin; &#946;-endosulfan; 4,4&#39;-dichlorodiphenyldichloroethane (4,4&#39;-DDD); endosulfan sulfate; 4,4&#39;-dichlorodiphenyltrichloroethane (4,4&#39;-DDT); endrin ketone; methoxychlor.

Watch this Scientific Journal Video about Analysis of Organochlorine Pesticides in a Soil Sample by a Modified QuEChERS Approach Using Ammonium Formate at JoVE.com

Analysis of Organochlorine Pesticides in a Soil Sample by a Modified QuEChERS Approach Using Ammonium Formate

The present protocol describes the utilization of ammonium formate for phase partitioning in QuEChERS, together with gas chromatography-mass spectrometry, to successfully determine organochlorine pesticide residues in a soil sample.

Currently, the QuEChERS method represents the most widely used sample preparation protocol worldwide for analyzing pesticide residues in a broad variety ...

analysis-organochlorine-pesticides-soil-sample-modified-quechers

Nanyang Technological University

Research

JoVE Journal

Chemistry

2.9K Views.  Universidad EAN. The present protocol describes the utilization of ammonium formate for phase partitioning in QuEChERS, together with gas chromatography-mass spectrometry, to successfully determine organochlorine pesticide residues in a soil sample. 

Video: Analysis of Organochlorine Pesticides in a Soil Sample by a Modified QuEChERS Approach Using Ammonium Formate

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted metabolomics provides a hypothesis generating snapshot of a metabolic profile. This protocol will demonstrate the extraction and analysis of metabolites from cells, serum, or tissue. A range of metabolites are surveyed using liquid-liquid phase extraction, microflow ultraperformance liquid chromatography/high-resolution mass spectrometry (UPLC-HRMS) coupled to differential analysis software.

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first ...

Covalent Binding of BMP-2 on Surfaces Using a Self-assembled Monolayer Approach

Bone morphogenetic protein 2 (BMP-2) is a growth factor embedded in the extracellular matrix of bone tissue. BMP-2 acts as trigger of mesenchymal cell differentiation into osteoblasts, thus stimulating healing and de novo bone formation. The clinical use of recombinant human BMP-2 (rhBMP-2) in conjunction with scaffolds has raised recent controversies, based on the mode of presentation and the amount to be delivered. The protocol presented here provides a simple and efficient way to deliver BMP-2 for in vitro studies on cells. We describe how to form a self-assembled monolayer consisting of a heterobifunctional linker, and show the subsequent binding step to obtain covalent immobilization of rhBMP-2. With this approach it is possible to achieve a sustained presentation of BMP-2 while maintaining the biological activity of the protein. In fact, the surface immobilization of BMP-2 allows targeted investigations by preventing unspecific adsorption, while reducing the amount of growth factor and, most notably, hindering uncontrolled release from the surface. Both short- and long-term signaling events triggered by BMP-2 are taking place when cells are exposed to surfaces presenting covalently immobilized rhBMP-2, making this approach suitable for in vitro studies on cell responses to BMP-2 stimulation.

We describe a method for accomplishing efficient immobilization of BMP-2 on surfaces. Our approach is based on the formation of a self-assembled monolayer to achieve the covalent binding of BMP-2 via its free amine residues. This method is a useful tool to study signaling at the cell membrane.

Bone morphogenetic protein 2 (BMP-2) is a growth factor embedded in the extracellular matrix of bone tissue. BMP-2 acts as trigger of mesenchymal cell ...

Dependence of Laser-induced Breakdown Spectroscopy Results on Pulse Energies and Timing Parameters Using Soil Simulants

The dependence of some LIBS detection capabilities on lower pulse energies (&lt;100 mJ) and timing parameters were examined using synthetic silicate samples. These samples were used as simulants for soil and contained minor and trace elements commonly found in soil at a wide range of concentrations. For this study, over 100 calibration curves were prepared using different pulse energies and timing parameters; detection limits and sensitivities were determined from the calibration curves. Plasma temperatures were also measured using Boltzmann plots for the various energies and the timing parameters tested. The electron density of the plasma was calculated using the full-width half maximum (FWHM) of the hydrogen line at 656.5 nm over the energies tested. Overall, the results indicate that the use of lower pulse energies and non-gated detection do not seriously compromise the analytical results. These results are very relevant to the design of field- and person-portable LIBS instruments.

LIBS detection capabilities on soil simulants were tested using a range of pulse energies and timing parameters. Calibration curves were used to determine detection limits and sensitivities for different parameters. Generally, the results showed that there was not a significant reduction in detection capabilities using lower pulse energies and non-gated detection.

The  dependence of some LIBS detection capabilities on lower pulse energies (&lt;100  mJ) and timing parameters were examined using synthetic silicate ...

An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints

The ability to directly characterize chemical transport and interactions that occur within a material (i.e., subsurface dynamics) is a vital component in understanding contaminant mass transport and the ability to decontaminate materials. If a material is contaminated, over time, the transport of highly toxic chemicals (such as chemical warfare agent species) out of the material can result in vapor exposure or transfer to the skin, which can result in percutaneous exposure to personnel who interact with the material. Due to the high toxicity of chemical warfare agents, the release of trace chemical quantities is of significant concern. Mapping subsurface concentration distribution and transport characteristics of absorbed agents enables exposure hazards to be assessed in untested conditions. Furthermore, these tools can be used to characterize subsurface reaction dynamics to ultimately design improved decontaminants or decontamination procedures. To achieve this goal, an inverse analysis mass transport modeling approach was developed that utilizes time-resolved mass spectroscopy measurements of vapor emission from contaminated paint coatings as the input parameter for calculation of subsurface concentration profiles. Details are provided on sample preparation, including contaminant and material handling, the application of mass spectrometry for the measurement of emitted contaminant vapor, and the implementation of inverse analysis using a physics-based diffusion model to determine transport properties of live chemical warfare agents including distilled mustard (HD) and the nerve agent VX.

In this paper, a procedure for quantifying the mass transport parameters of chemicals in various materials is presented. This process involves employing an inverse-analysis based diffusion model to vapor emission profiles recorded by real-time, mass spectrometry in high vacuum.

The ability to directly characterize chemical transport and interactions that occur within a material (i.e., subsurface dynamics) is a vital component in ...

Electrochemically and Bioelectrochemically Induced Ammonium Recovery

Streams such as urine and manure can contain high levels of ammonium, which could be recovered for reuse in agriculture or chemistry. The extraction of ammonium from an ammonium-rich stream is demonstrated using an electrochemical and a bioelectrochemical system. Both systems are controlled by a potentiostat to either fix the current (for the electrochemical cell) or fix the potential of the working electrode (for the bioelectrochemical cell). In the bioelectrochemical cell, electroactive bacteria catalyze the anodic reaction, whereas in the electrochemical cell the potentiostat applies a higher voltage to produce a current. The current and consequent restoration of the charge balance across the cell allow the transport of cations, such as ammonium, across a cation exchange membrane from the anolyte to the catholyte. The high pH of the catholyte leads to formation of ammonia, which can be stripped from the medium and captured in an acid solution, thus enabling the recovery of a valuable nutrient. The flux of ammonium across the membrane is characterized at different anolyte ammonium concentrations and currents for both the abiotic and biotic reactor systems. Both systems are compared based on current and removal efficiencies for ammonium, as well as the energy input required to drive ammonium transfer across the cation exchange membrane. Finally, a comparative analysis considering key aspects such as reliability, electrode cost, and rate is made.
This video article and protocol provide the necessary information to conduct electrochemical and bioelectrochemical ammonia recovery experiments. The reactor setup for the two cases is explained, as well as the reactor operation. We elaborate on data analysis for both reactor types and on the advantages and disadvantages of bioelectrochemical and electrochemical systems.

We demonstrate the extraction of ammonium from an ammonium-rich stream using an electrochemical and a bioelectrochemical system. The reactor setup, operation and data analysis are discussed.

Streams such as urine and manure can contain high levels of ammonium, which could be recovered for reuse in agriculture or chemistry. The extraction of ...

Transport of Surface-modified Carbon Nanotubes through a Soil Column

Carbon nanotubes (CNTs) are widely manufactured nanoparticles, which are being utilized in a number of consumer products, such as sporting goods, electronics and biomedical applications. Due to their accelerating production and use, CNTs constitute a potential environmental risk if they are released to soil and groundwater systems. It is therefore essential to improve the current understanding of environmental fate and transport of CNTs. The transport and retention of CNTs in both natural and artificial media have been reported in literature, but the findings widely vary and are thus not conclusive. There are a number of physical and chemical parameters responsible for variation in retention and transport. In this study, a complete procedure of selected multiwalled carbon nanotubes (MWCNTs) is presented starting from their surface modification to a complete set of laboratory column experiments at critical physical and chemical scenarios. Results indicate that the stability of the commercially available MWCNTs are critical with their attached surface functional group which can also influence the transport and retention of MWCNT through the surrounding medium.

Surface properties of a nanoparticle are important for their interaction with the surrounding medium. Therefore the surface modification of carbon nanotubes can be critical for their transport and retention through porous media. Here, lab scale column experiments are used to understand the possible transport and retention of these nanoparticles.

Carbon nanotubes (CNTs) are widely manufactured nanoparticles, which are being utilized in a number of consumer products, such as sporting goods, ...

Ethylene Polymerizations Using Parallel Pressure Reactors and a Kinetic Analysis of Chain Transfer Polymerization

We demonstrate a method for high-throughput catalyst screening using a parallel pressure reactor starting from the initial synthesis of a nickel &#945;-diimine ethylene polymerization catalyst. Initial polymerizations with the catalyst lead to optimized reaction conditions, including catalyst concentration, ethylene pressure and reaction time. Using gas-uptake data for these reactions, a procedure to calculate the initial rate of propagation (kp) is presented. Using the optimized conditions, the ability of the nickel &#945;-diimine polymerization catalyst to undergo chain transfer with diethylzinc (ZnEt2) during ethylene polymerization was investigated. A procedure to assess the ability of the catalyst to undergo chain transfer (from molecular weight and 13C NMR data), calculate the degree of chain transfer, and calculate chain transfer rates (ke) is presented.

A protocol for the high-throughput analysis of polymerization catalyst, chain transfer polymerizations, polyethylene characterization, and reaction kinetic analysis is presented.

We demonstrate a method for high-throughput catalyst screening using a parallel pressure reactor starting from the initial synthesis of a nickel ...

Synthesis and Exfoliation of Discotic Zirconium Phosphates to Obtain Colloidal Liquid Crystals

Due to their abundance in natural clay and potential applications in advanced materials, discotic nanoparticles are of interest to scientists and engineers. Growth of such anisotropic nanocrystals through a simple chemical method is a challenging task. In this study, we fabricate discotic nanodisks of zirconium phosphate [Zr(HPO4)2&#183;H2O] as a model material using hydrothermal, reflux and microwave-assisted methods. Growth of crystals is controlled by duration time, temperature, and concentration of reacting species. The novelty of the adopted methods is that discotic crystals of size ranging from hundred nanometers to few micrometers can be obtained while keeping the polydispersity well within control. The layered discotic crystals are converted to monolayers by exfoliation with tetra-(n)-butyl ammonium hydroxide [(C4H9)4NOH, TBAOH]. Exfoliated disks show isotropic and nematic liquid crystal phases. Size and polydispersity of disk suspensions is highly important in deciding their phase behavior.

A two dimensional model material of discotic zirconium phosphate was developed. The inorganic crystal with lamellar structure was synthesized by hydrothermal, reflux, and microwave-assisted methods. On exfoliation with organic molecules, layered crystals can be converted to monolayers, and nematic liquid crystal phase was formed at sufficient concentration of monolayers.

Due to their abundance in natural clay and potential applications in advanced materials, discotic nanoparticles are of interest to scientists and ...

Glycan Node Analysis: A Bottom-up Approach to Glycomics

Synthesized in a non-template-driven process by enzymes called glycosyltransferases, glycans are key players in various significant intra- and extracellular events. Many pathological conditions, notably cancer, affect gene expression, which can in turn deregulate the relative abundance and activity levels of glycoside hydrolase and glycosyltransferase enzymes. Unique aberrant whole glycans resulting from deregulated glycosyltransferase(s) are often present in trace quantities within complex biofluids, making their detection difficult and sometimes stochastic. However, with proper sample preparation, one of the oldest forms of mass spectrometry (gas chromatography-mass spectrometry, GC-MS) can routinely detect the collection of branch-point and linkage-specific monosaccharides ("glycan nodes") present in complex biofluids. Complementary to traditional top-down glycomics techniques, the approach discussed herein involves the collection and condensation of each constituent glycan node in a sample into a single independent analytical signal, which provides detailed structural and quantitative information about changes to the glycome as a whole and reveals potentially deregulated glycosyltransferases. Improvements to the permethylation and subsequent liquid/liquid extraction stages provided herein enhance reproducibility and overall yield by facilitating minimal exposure of permethylated glycans to alkaline aqueous conditions. Modifications to the acetylation stage further increase the extent of reaction and overall yield. Despite their reproducibility, the overall yields of N-acetylhexosamine (HexNAc) partially permethylated alditol acetates (PMAAs) are shown to be inherently lower than their expected theoretical value relative to hexose PMAAs. Calculating the ratio of the area under the extracted ion chromatogram (XIC) for each individual hexose PMAA (or HexNAc PMAA) to the sum of such XIC areas for all hexoses (or HexNAcs) provides a new normalization method that facilitates relative quantification of individual glycan nodes in a sample. Although presently constrained in terms of its absolute limits of detection, this method expedites the analysis of clinical biofluids and shows considerable promise as a complementary approach to traditional top-down glycomics.

This article presents an enhanced form of a novel bottom-up glycomics technique designed to analyze the pooled compositional profile of glycans in unfractionated biofluids through the chemical breakdown of glycans into their constituent linkage-specific monosaccharides for detection by GC-MS. Potential applications include early detection of cancer and other glycan-affective disorders.

Synthesized in a non-template-driven process by enzymes called glycosyltransferases, glycans are key players in various significant intra- and ...

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, and that these chemical fingerprints can be used for plant species identification. The mass spectral data can be acquired rapidly and in a high throughput manner without the need for sample extraction, derivatization or pH adjustment steps. The use of this technique bypasses challenges presented by more conventional techniques including lengthy chromatography analysis times and resource intensive methods. The high throughput capabilities of the direct analysis in real time-high resolution mass spectrometry protocol, coupled with multivariate statistical analysis processing of the data, provide not only class characterization of plants, but also yield species and varietal information. Here, the technique is demonstrated with two psychoactive plant products, Mitragyna speciosa (Kratom) and Datura (Jimsonweed), which were subjected to direct analysis in real time-high resolution mass spectrometry followed by statistical analysis processing of the mass spectral data. The application of these tools in tandem enabled the plant materials to be rapidly identified at the level of variety and species.

A method for species identification of botanical material by direct analysis in real time-high resolution mass spectrometry and multivariate statistical analysis is presented.

We demonstrate that direct analysis in real time-high resolution mass spectrometry can be used to produce mass spectral profiles of botanical material, ...