Fajun
Tian‡
*,
Zhenzhen
Zhou‡
,
Junfeng
Lu
,
Chengkui
Qiao
,
Caixia
Wang
,
Tao
Pang
,
Linlin
Guo
,
Jun
Li
,
Rongli
Pang
and
Hanzhong
Xie
*
Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou 450009, China. E-mail: xiehanzhong@caas.cn; tianfajun@caas.cn
First published on 19th February 2025
Diamide insecticides are being widely registered worldwide, yet most of them lack established maximum residue limits (MRLs) in agricultural products. In this study, we combined a QuEChERS (quick, easy, cheap, efficient, rugged, and safe) extraction method with high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) analysis to simultaneously identify and quantify ten diamide insecticides in seven matrices for the first time. The method was validated in accordance with SANTE/11312/2021 guidelines, including sensitivity, linearity, trueness, and precision. Excellent linearity (R2 > 0.99) was obtained for all diamide insecticides within the concentration range of 5–1000 µg kg−1. The limit of detection (LOD) and limit of quantification (LOQ) were 0.01–1 µg kg−1 and 5 µg kg−1, respectively. The recoveries of the ten diamide insecticides at three levels (5, 100, and 1000 µg kg−1) ranged from 76.6% to 108.2% with good intra-day relative standard deviation (RSDr) (1.0–13.4%) and inter-day relative standard deviation (RSDR) (2.3–15.7%). The proposed method was applied to analyze 70 real agricultural product samples, and only six samples contained diamide insecticides. The results demonstrated that the method was both convenient and reliable for detecting diamide insecticides in agricultural products. The method was then applied to analyze agricultural product samples collected in a field trial to estimate the MRLs for the next step.
Pests have a devastating effect on food security across the world. Up to 40% of global crop production is destroyed by pests annually.10 For crops, including cereals, vegetables, and fruits, pests can lead to a decrease in crop yield and quality.11 To our knowledge, the use of chemical pesticides is still the main method to reduce losses caused by pests.12 Thus, the monitoring of pesticide residues in crops is necessary to accomplish with MRLs for new pesticides. And it also helps to ensure food safety and reduce the impact of crop export trade.
Diamide insecticides are the most popular insecticidal products in the market after neonicotinoid insecticides. It is predicted that, in 2024, they will surpass neonicotinoid insecticides and occupy the top position in global insecticide products.13 Diamide insecticides were developed and registered in 2001. They can be used to control Lepidoptera, Coleopteran, and Dipteran pests and have low toxicity to mammals.14 Diamide insecticides have been paid more and more attention because of their unique specific structure, high insecticidal activity, and long persistent control. At present, there are ten diamide insecticides around the world, of which 9 have been officially registered and approved for pest control in different countries, and 1 has been temporarily approved by the International Organization for Standardization (ISO). In addition, there are two compounds belonging to the class of phthalimides (flubendiamide and cyhalodiamide), seven compounds belonging to the class of o-carboxamidobenzamide (chlorantraniliprole, cyantraniliprole, tetrachlorantraniliprole, tetraniliprole, thiorantraniliprole, cyclaniliprole, and fluchlordiniliprole), and one compound belonging to the class of m-formamidobenzamide (broflanilide).13 Due to the high activity and no cross-resistance with traditional pesticides of diamide insecticides, more than 200 crops have been registered for these insecticides, which have great application prospects. However, diamide insecticides have a long residual period and strong mobility in soil, and long-term and large-scale application may lead to enrichment. The Environmental Protection Agency (EPA) has reported that flubendiamide poses acute and chronic risks to aquatic invertebrates.13 China only has set MRLs of flubendiamide, chlorantraniliprole, cyantraniliprole, and tetrachlorantraniliprole in crops. There is no corresponding MRL value for the other six diamide insecticides. However, many countries and organizations, such as the EU and Codex Alimentarius Commission (CAC), have stipulated the MRLs for diamide insecticides (except for fluchlordiniliprole) in various foods to ensure food and environmental safety. Furthermore, there are some studies for the determination of these insecticides. Most of them are the methods for analyzing one or several compounds.14–22 Thus, analyzing these ten diamide insecticides with comprehensive and simultaneous techniques is imperative to provide a technical basis for the routine detection of insecticides in crops (GB 2763-2021, 2021).
Several methods have been validated for the quantitative and qualitative analyses of diamide insecticides, including Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS),14,15 Liquid Chromatography (LC),23 Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS),24 Gas Chromatography (GC),25 and electrochemical methods.26 However, GC and GC-MS/MS are unsuitable for analyzing the ten diamide insecticides as some of them are difficult to vaporize. LC analysis takes a lot of time and has low sensitivity.27 Compared with previously established methods, the LC-MS/MS method has the best sensitivity and efficiency in trace analysis of diamide insecticides and has been widely used. Therefore, in this study, LC-MS/MS was selected to analyse diamide insecticides. A lot of sample preparation techniques have been reported, including solid-phase extraction (SPE), gel permeation chromatography (GPC), and QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe).28–31 SPE is labor-intensive and time consuming. GPC requires the use of a large amount of organic solvents, including n-hexane and acetone. In recent years, QuEChERS has become a commonly used method in laboratories around the world because of its good extraction efficiency for various compounds and its wide applicability in various matrices.32,33 Thus, the QuEChERS technique was the first choice in this study to extract the ten diamide insecticides.
There are no defined MRLs for cyhalodiamide, broflanilide, tetraniliprole, thiorantraniliprole, cyclaniliprole, and fluchlordiniliprole in crops in China. This study is the first try to establish the MRLs for these diamide insecticides in vegetables, fruits, and cereals. The aim of the present study was to develop and validate an improved QuEChERS method combined with LC-MS/MS analytical method for simultaneous determination of the ten diamide insecticides in vegetables, fruits, and cereals. The extraction solvent and clean-up process of QuEChERS were investigated to obtain higher recoveries. The LC-MS/MS conditions were also optimized for the qualification and quantitation of each target compound within 6 min. As far as we know, this is the first time that a method for simultaneous determination of the ten diamide insecticides in different matrices has been established. Finally, the developed method was used to determine the residual status of the diamide insecticides in real crop samples.
Solutions of the ten diamide insecticides were prepared by weighing 10 mg of the active component of each target insecticide into volumetric flasks and then dissolving them in 10 mL of acetonitrile to obtain a concentration of 1000 mg L−1. The volumetric flasks required ultrasonication for 20 min at 40 °C to dissolve the fluchlordiniliprole. They were sealed and stored at −20 °C in the dark until use. The solutions were stable over one month under these conditions. When ready for use, the solutions were thawed and ultrasound treated at room temperature. Afterwards, the solutions were mixed in equal volumes to obtain a mixed standard solution with a concentration of 100 mg L−1. This solution was used to prepare the working solutions for recovery studies, calibration, and optimization and for matrix-matched calibration. For matrix-matched calibration, standard multi-component solutions were prepared at different concentrations (5, 10, 50, 100, 500, and 1000 µg kg−1) by appropriate dilution of the mixed solution with the extraction blank samples. An individual solution at 100 µg kg−1 was prepared to optimize MS parameters. Vegetables and fruits (tomatoes, cucumbers, peppers, cabbages, and apples) were supplied from an organic food store in Zhengzhou. Rice and corn were acquired form the experimental base in Xinxiang, Henan Province, China. The seven matrices were previously checked to ensure that they did not contain the ten diamide insecticides. As expected, no residues of the ten diamide insecticides were detected in seven matrices. All solutions and matrices were stored at −20 °C in the dark until analysis.
An Agilent Poroshell 120 EC-C18 column, 2.1 × 100 mm, 2.7 µm particle diameter, was used to separate the ten diamide insecticides, with a flow rate of 0.30 mL min−1. The mobile phases A and B were water and acetonitrile, respectively. Starting with 10% acetonitrile, the gradient for mobile phase B was established as follows: the mobile phase B was increased to 70% in 1 min. Then, isocratic conditions were kept for 2 min. Afterwards, the mobile phase B was increased to 90% in 2 min. Finally, the mobile phase B was reduced to 10% at 5.1 min (initial conditions) and kept for 0.9 min to ensure that the column was fully re-equilibrated. The running time of the chromatographic system was 6 min. The temperature of the column compartment and autosampler was set at 35 °C and 4 °C, respectively. The injection volume was 5 µL.
Regarding the conditions of the mass spectrometer, dynamic multiple reaction monitoring (MRM) was selected as the acquisition mode. Two MRM ion transitions in each target compound were selected for the quantifier and qualifier. And the high response values were used for quantitative analysis, while low response values were used for qualitative analysis. All samples were analyzed in both positive and negative modes with the following parameters: capillary voltage, 4000 V; drying gas temperature, 350 °C; drying gas flow, 8 L min−1; sheath gas temperature, 350 °C; sheath gas flow, 12 L min−1; nebulizer gas pressure, 35 psi. The fragments voltage and collision energy were also optimized during the infusion of each target analyte (0.1 mg L−1). Table 1 shows all the parameters for the ten diamide insecticides. Instrument control and data acquisition and processing were performed with Agilent MassHunter Workstation software, version B.03.01 (Agilent Technologies, Inc.).
Compound | Molecular formula | Ion source | Ion polarity | Precursor ion | Fragments (V) | Product ion | Collision energy (V) | RT (min) |
---|---|---|---|---|---|---|---|---|
a Quantifier. b Qualifier. | ||||||||
Flubendiamide | C23H22F7IN2O4S | ESI− | [M − H]− | 681.0 | 170 | 254.1 a | 30 | 3.1 |
274.0 b | 10 | |||||||
Cyhalodiamide | C22H17ClF7N3O2 | ESI− | [M − H]− | 522.2 | 140 | 254.1 a | 20 | 3.0 |
274.1 b | 10 | |||||||
Chlorantraniliprole | C18H14BrCl2N5O2 | ESI+ | [M + H]+ | 484.0 | 90 | 453.0 a | 20 | 2.4 |
286.0 b | 10 | |||||||
Cyantraniliprole | C19H14BrClN6O2 | ESI+ | [M + H]+ | 475.0 | 100 | 286.0 a | 10 | 2.2 |
444.1 b | 18 | |||||||
Tetrachlorantraniliprole | C17H10BrCl4N5O2 | ESI− | [M − H]− | 535.8 | 100 | 202.0 a | 10 | 2.8 |
499.9 b | 10 | |||||||
Tetraniliprole | C22H16ClF10N10O2 | ESI+ | [M + H]+ | 545.2 | 110 | 356.0 a | 10 | 2.4 |
376.0 b | 20 | |||||||
Thiorantraniliprole | C19H15BrCl3N5OS | ESI+ | [M + H]+ | 548.0 | 110 | 285.9 a | 10 | 3.4 |
177.3 b | 30 | |||||||
Cyclaniliprole | C21H17Br2Cl2N5O2 | ESI− | [M−H]− | 599.9 | 110 | 255.9 a | 18 | 3.0 |
257.9 b | 10 | |||||||
Broflanilide | C25H14BrF11N2O2 | ESI+ | [M + H]+ | 665.1 | 150 | 625.0 a | 30 | 4.0 |
555.6 b | 30 | |||||||
Fluchlordiniliprole | C17H10BrCl3FN5O2 | ESI− | [M − H]− | 520.0 | 100 | 204.0 a | 10 | 2.3 |
261.0 b | 15 |
![]() | (1) |
Many studies have found that the composition of the mobile phase in HPLC-MS/MS analysis could affect the peak shape, retention time, and peak area of the target analytes.14,33 In the present study, the chromatographic separation of the ten diamide insecticides was carried out using an injection of 100 µg kg−1 mixed standard solution. Four commonly used mobile phase compositions (acetonitrile and water, acetonitrile and 0.1% formic acid aqueous solution, methanol and water, and methanol and 0.1% formic acid aqueous solution) were compared to acquire better peak shapes and sensitivities of the target analytes. Compared with acetonitrile and water, methanol and water delayed the retention time and produced a poorer peak shape for some analytes (peak splitting and tailing). Acetonitrile and water, as well as acetonitrile and 0.1% formic acid aqueous solution, can produce better peak shapes for the target compounds, and the overall time was reduced. As observed in Fig. 2, the mobile phase of acetonitrile and 0.1% formic acid aqueous solution produced a lower peak area than acetonitrile and water. In addition, some target compounds were determined in negative ESI mode. Thus, the mobile phase of acetonitrile and water was selected to acquire the best peak shapes and sensitivities. Under the optimized MS and chromatography conditions, typical MRM chromatograms of the ten diamide insecticides in acetonitrile and black samples are shown in Fig. S1–S3.† No interferences were found at the retention times of the target compounds, and the analysis times were shorter than 6 min.
![]() | ||
Fig. 2 The peak area of the ten diamide insecticides (at 0.01 mg L−1 concentration using four different mobile phase compositions). |
First, the volume of water was optimized. Some studies have found that adding an appropriate volume of water can improve the extraction efficiency of pesticides in dry samples.37–39 Different volumes (5, 10, and 20 mL) of water were added to compare the extraction effect. The extraction effect with 10 mL and 20 mL of water was better than that with 5 mL of water. However, there was no difference in the extraction effect between 10 mL and 20 mL of water. In addition, using 20 mL water required adding more MgSO4. Hence, taken together, 10 mL water was added in rice and corn before the QuEChERS extraction.
Besides, the extraction solvents were optimized. The extraction solvent had a significant effect on the recoveries of the target analytes in the samples, especially for the complex matrices. Acetonitrile and methanol were frequently used to extract pesticide residues from food samples.7,28 In addition, for multi-residue analysis, the use of acid may protect the base-sensitive pesticides and improve the extraction efficiency.40 In the current study, the extraction effects of four extraction solvents (methanol, acidified methanol (1% formic acid), acetonitrile, and acidified acetonitrile (1% formic acid)) were compared. Tomato was chosen as the representative of the blank sample, which was spiked with 10 µg kg−1 mixed standard solution. Then, the tomato samples were extracted and purified according to the methods mentioned in Section 2.3. As shown in Fig. 3, the recoveries of the ten target compounds were satisfactory when acetonitrile was used as the extraction solvent. 1% formic acid and acetonitrile also produced a remarkable recovery efficiency of the ten target compounds except for thiorantraniliprole and fluchlordiniliprole. However, the recovery was below 70% when methanol and acidified methanol were used. Thus, acetonitrile was selected to extract the target analytes from the seven matrices.
![]() | ||
Fig. 3 Effect of different types of extraction solvents for the targeted compounds in the tomato matrix at 10 µg kg−1 level (n = 3). |
Finally, different sorbents were compared and optimized to reduce the interferences. PSA, C18, and GCB were often used to remove interfering substances in various complex matrices.41 Vegetables, fruits, and cereals contained a lot of interferences, such as fats, proteins, pigments, fatty acids, and sugars. Some researchers have found that using PSA can remove sugars, organic acids, and other polar components; using C18 can remove fats, lipids, and other non-polar organic compounds; using GCB can remove polyphenols, chlorophyll, carotenoids, and other visible pigments.42–44 Nevertheless, some studies also found that a single sorbent might not be able to fully purify the samples.15,43,45 In addition, several studies have proved that the combination of PSA with other sorbents (C18 and GCB) can improve the removal efficiency for the extracts of many matrices.33,35,46 The purification effect of each sorbent was compared by mixing them with 150 mg anhydrous MgSO4. In the current study, the purification effects of six different types of sorbents (sorbent 1:
50 mg PSA; sorbent 2
:
50 mg C18; sorbent 3
:
5 mg GCB; sorbent 4
:
50 mg PSA + 5 mg GCB; sorbent 5
:
50 mg C18 + 5 mg GCB; sorbent 6
:
20 mg PSA + 30 mg C18) were tested, and the results are shown in Fig. 4. In the tomato matrix, the average recoveries of the ten diamide insecticides were acceptable (70–120%) under the use of six different sorbents. In the pepper matrix, the average recoveries of target insecticides were 70–120% under the use of 50 mg PSA. In the cucumber, cabbage, and apple samples, the recovery and RSD were both satisfactory when 50 mg PSA or 20 mg PSA + 30 mg C18 were used. In the rice matrix, the average recoveries of each target compound were satisfactory with the use of 50 mg C18 or 20 mg PSA + 30 mg C18. In the corn matrix, only when 50 mg PSA was used, the recoveries of the ten diamide insecticides were within the acceptable range. For GCB, the recoveries of compounds 1–9 were <70%. PSA and C18 presented good recoveries for most compounds in all matrices. Possibly, GCB absorbed some target compounds in addition to polyphenols, chlorophyll, and carotenoids, resulting in low recoveries. Some studies also found that the recoveries of some pesticides were relatively low when GCB was used.15,35,44 In addition, C18 was relatively cheaper than PSA. And considering other factors, including the recoveries, matrix effect, and purification effect, 50 mg PSA was selected for tomato, pepper, and corn extracts, while 20 mg PSA + 30 mg C18 was selected as the most appropriate absorbent for cucumber, cabbage, apple, and rice extracts in this study.
![]() | ||
Fig. 4 Comparison of recoveries of the ten diamide insecticides with different sorbents in different matrices at 100 µg kg−1 concentration. |
Compound | Matrix | Regression equation | R 2 | Matrix effectb (%) | LOD (µg kg−1) | LOQ (µg kg−1) | MRL (mg kg−1) | |
---|---|---|---|---|---|---|---|---|
EU | China | |||||||
a The calibration ranges of all the target compounds are 1–1000 µg L−1. b Matrix effect (%) = ((slope matrix/slope solvent) − 1) ×100. c Temporary maximum residue limit. | ||||||||
Flubendiamide | Acetonitrile | y = 3734.6x + 85749.9 | 0.9971 | — | — | — | — | — |
Tomato | y = 3468.3x + 110137.8 | 0.9928 | −7.13 | 0.2 | 5 | 2 | 2 | |
Cucumber | y = 3094.7x + 80240.6 | 0.9953 | −17.13 | 0.2 | 5 | 0.2 | — | |
Pepper | y = 3427.5x + 116214.7 | 0.9925 | −8.22 | 0.5 | 5 | 0.7 | 0.7 | |
Cabbage | y = 3162.2x + 98408.8 | 0.9944 | −15.33 | 0.1 | 5 | 0.01 | 0.2 | |
Apple | y = 2189.3x + 70385.5 | 0.9932 | −41.38 | 0.1 | 5 | 0.9 | 0.8c | |
Rice | y = 2046.4x + 66135.2 | 0.9920 | −45.20 | 0.2 | 5 | 0.3 | 0.01 | |
Corn | y = 3361.5x + 137129.6 | 0.9928 | −9.99 | 0.2 | 5 | 0.02 | 0.02 | |
Cyhalodiamide | Acetonitrile | y = 3640.0x + 89277.5 | 0.9951 | — | — | — | — | — |
Tomato | y = 3551.2x + 118457.6 | 0.9929 | −2.44 | 0.05 | 5 | — | — | |
Cucumber | y = 3418.5x + 82004.5 | 0.9943 | −6.09 | 0.05 | 5 | — | — | |
Pepper | y = 3591.3x + 121914.1 | 0.9922 | −1.34 | 0.05 | 5 | — | — | |
Cabbage | y = 3350.7x + 100639.1 | 0.9927 | −7.95 | 0.05 | 5 | — | — | |
Apple | y = 2438.7x + 76483.3 | 0.9936 | −33.00 | 0.05 | 5 | — | — | |
Rice | y = 2544.2x + 62167.1 | 0.9960 | −30.10 | 0.1 | 5 | — | — | |
Corn | y = 3195.5x + 53609.5 | 0.9975 | 12.21 | 0.1 | 5 | — | — | |
Chlorantraniliprole | Acetonitrile | y = 8931.9x + 128703.9 | 0.9926 | — | — | — | — | — |
Tomato | y = 1766.4x + 37707.1 | 0.9985 | −80.22 | 0.01 | 5 | 0.6 | 0.6c | |
Cucumber | y = 3182.7x + 79694.7 | 0.9940 | −64.37 | 0.05 | 5 | 0.3 | 0.6c | |
Pepper | y = 1418.7x + 20912.9 | 0.9979 | −84.12 | 0.1 | 5 | 1 | 0.6c | |
Cabbage | y = 4602.1x + 122165.2 | 0.9929 | −48.48 | 0.05 | 5 | 20 | 2c | |
Apple | y = 5142.5x + 114771.6 | 0.9964 | −42.43 | 0.05 | 5 | 0.4 | 2c | |
Rice | y = 3773.15x + 66200.7 | 0.9947 | −57.76 | 0.1 | 5 | 0.4 | 0.04c | |
Corn | y = 1411.9x − 2723.8 | 0.9991 | −84.19 | 0.1 | 5 | 0.01c | 0.02 | |
Cyantraniliprole | Acetonitrile | y = 1549.3x + 34837.1 | 0.9961 | — | — | — | — | — |
Tomato | y = 474.4x + 6639.8 | 0.9964 | −69.38 | 0.5 | 5 | 1 | 0.2c | |
Cucumber | y = 678.0x + 1988.9 | 0.9978 | −56.24 | 0.5 | 5 | 0.4 | 0.2c | |
Pepper | y = 494.1x + 6585.7 | 0.9970 | −68.11 | 0.5 | 5 | 1.5 | 1c | |
Cabbage | y = 1055.4x + 16146.3 | 0.9964 | −31.88 | 0.2 | 5 | 30 | 0.5c | |
Apple | y = 1216.7x + 24539.2 | 0.9952 | −21.47 | 0.1 | 5 | 0.8 | 0.8c | |
Rice | y = 825.8x + 12185.5 | 0.9943 | −46.70 | 0.2 | 5 | 0.01c | 0.2c | |
Corn | y = 153.0x − 145.3 | 0.9997 | −90.12 | 1 | 5 | 0.01c | — | |
Tetrachlorantraniliprole | Acetonitrile | y = 228.9x + 178.4 | 0.9987 | — | — | — | — | — |
Tomato | y = 362.5x + 8862.4 | 0.9954 | 58.37 | 0.5 | 5 | — | — | |
Cucumber | y = 256.7x + 6186.1 | 0.9943 | 12.15 | 0.5 | 5 | — | — | |
Pepper | y = 319.9x + 10312.5 | 0.9927 | 39.76 | 0.5 | 5 | — | — | |
Cabbage | y = 315.9x + 7534.2 | 0.9947 | 38.01 | 0.5 | 5 | — | 3c | |
Apple | y = 228.6x + 5034.2 | 0.9969 | −0.13 | 0.5 | 5 | — | — | |
Rice | y = 233.0x + 2880.5 | 0.9966 | 1.79 | 0.5 | 5 | — | 0.5c | |
Corn | y = 350.9x + 10361.0 | 0.9952 | 53.30 | 0.2 | 5 | — | 0.05c | |
Tetraniliprole | Acetonitrile | y = 1317.2x + 49033.2 | 0.9921 | — | — | — | — | — |
Tomato | y = 334.4x + 8344.0 | 0.9916 | −74.61 | 0.5 | 5 | — | — | |
Cucumber | y = 813.6x + 23177.1 | 0.9933 | −38.23 | 0.2 | 5 | — | — | |
Pepper | y = 351.2x + 7281.2 | 0.9949 | −73.34 | 0.5 | 5 | — | — | |
Cabbage | y = 946.5x + 24973.8 | 0.9944 | −28.14 | 0.2 | 5 | — | — | |
Apple | y = 1782.2x + 65293.3 | 0.9913 | 35.30 | 0.1 | 5 | — | — | |
Rice | y = 893.8x + 23618.7 | 0.9934 | −32.14 | 0.2 | 5 | — | — | |
Corn | y = 189.2x + 1394.7 | 0.9968 | −85.64 | 0.2 | 5 | — | — | |
Thiorantraniliprole | Acetonitrile | y = 4274.0x + 28115.6 | 0.9941 | — | — | — | — | — |
Tomato | y = 1330.0x − 6051.3 | 0.9946 | −68.88 | 0.5 | 5 | — | — | |
Cucumber | y = 2223.6x + 7059.0 | 0.9984 | −47.97 | 0.2 | 5 | — | — | |
Pepper | y = 1034.6x − 7046.0 | 0.9926 | −75.79 | 0.5 | 5 | — | — | |
Cabbage | y = 2895.3x + 37204.8 | 0.9967 | −32.26 | 0.1 | 5 | — | — | |
Apple | y = 2340.0x + 27481.9 | 0.9970 | −45.25 | 0.1 | 5 | — | — | |
Rice | y = 1832.5x − 3485.7 | 0.9998 | −57.12 | 0.2 | 5 | — | — | |
Corn | y = 732.1x + 3967.9 | 0.9995 | −82.87 | 0.2 | 5 | — | — | |
Cyclaniliprole | Acetonitrile | y = 274.6x + 6862.8 | 0.9943 | — | — | — | — | — |
Tomato | y = 246.6x + 6873.3 | 0.9927 | −10.20 | 0.5 | 5 | 0.01c | — | |
Cucumber | y = 174.5x + 3086.9 | 0.9955 | −36.45 | 0.5 | 5 | 0.01c | — | |
Pepper | y = 226.3x + 7591.4 | 0.9918 | −17.59 | 0.5 | 5 | 0.01c | — | |
Cabbage | y = 191.7x + 6152.4 | 0.9933 | −30.19 | 0.5 | 5 | 0.01c | — | |
Apple | y = 146.7x + 3931.3 | 0.9930 | −46.58 | 0.5 | 5 | 0.01c | — | |
Rice | y = 119.3x + 2468.5 | 0.9977 | −56.55 | 1 | 5 | 0.01c | — | |
Corn | y = 247.0x + 8879.9 | 0.9939 | −10.05 | 0.2 | 5 | 0.01c | — | |
Broflanilide | Acetonitrile | y = 786.4x + 15560.3 | 0.9967 | — | — | — | — | — |
Tomato | y = 533.9x + 1206.8 | 0.9987 | −32.11 | 1 | 5 | — | — | |
Cucumber | y = 601.5x + 3261.8 | 0.9953 | −23.51 | 1 | 5 | — | — | |
Pepper | y = 415.8x − 103.7 | 0.9988 | −47.13 | 1 | 5 | — | — | |
Cabbage | y = 822.4x + 11928.1 | 0.9972 | 4.58 | 0.5 | 5 | — | — | |
Apple | y = 533.1x + 9980.3 | 0.9934 | −32.21 | 0.5 | 5 | — | — | |
Rice | y = 401.2x + 838.8 | 0.9993 | −48.98 | 1 | 5 | — | — | |
Corn | y = 229.1x + 1194.2 | 0.9984 | 70.87 | 0.5 | 5 | — | — | |
Fluchlordiniliprole | Acetonitrile | y = 722.8x + 6443.5 | 0.9973 | — | — | — | — | — |
Tomato | y = 176.4x + 7130.3 | 0.9930 | −75.59 | 0.2 | 5 | — | — | |
Cucumber | y = 487.8x + 810.9 | 0.9998 | −32.51 | 0.5 | 5 | — | — | |
Pepper | y = 168.2x + 6463.7 | 0.9925 | −76.73 | 0.2 | 5 | — | — | |
Cabbage | y = 449.7x + 11374.7 | 0.9950 | −37.78 | 0.5 | 5 | — | — | |
Apple | y = 383.4x + 3760.7 | 0.9978 | −46.96 | 0.5 | 5 | — | — | |
Rice | y = 153.6x + 4472.9 | 0.9953 | −78.75 | 0.2 | 5 | — | — | |
Corn | y = 159.2x + 6362.2 | 0.9929 | −77.97 | 0.2 | 5 | — | — |
Compound | Sorbent | 50 mg PSA | 20 mg PSA + 30 mg C18 | 50 mg PSA | 20 mg PSA + 30 mg C18 | 20 mg PSA + 30 mg C18 | 20 mg PSA + 30 mg C18 | 50 mg PSA | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Spiked level (µg kg−1) | Tomato | Cucumber | Pepper | Cabbage | Apple | Rice | Corn | |||||||||||||||
Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | Recovery | RSDra | RSDRb | ||
a RSDr: intra-day (n = 5), which is the RSD for repeatability. b RSDR: inter-day (n = 15), which is the RSD for reproducibility. | ||||||||||||||||||||||
Flubendiamide | 5 | 99.4 | 7.9 | 7.1 | 91.5 | 2.1 | 3.4 | 96.1 | 1.2 | 7.0 | 86.0 | 5.6 | 9.5 | 98.9 | 3.9 | 13.1 | 98.3 | 7.2 | 14.4 | 87.2 | 1.7 | 3.2 |
100 | 103.2 | 6.1 | 7.5 | 90.2 | 6.6 | 9.7 | 91.7 | 2.3 | 6.5 | 92.9 | 6.7 | 5.6 | 99.2 | 4.1 | 14.0 | 90.3 | 1.8 | 8.6 | 96.1 | 2.9 | 9.0 | |
1000 | 106.0 | 4.5 | 5.5 | 89.4 | 9.0 | 6.8 | 93.6 | 1.5 | 9.3 | 90.1 | 2.4 | 5.5 | 102.8 | 2.3 | 7.4 | 86.3 | 6.3 | 8.3 | 100.7 | 6.6 | 8.5 | |
Cyhalodiamide | 5 | 100.2 | 6.5 | 6.8 | 88.7 | 2.5 | 7.5 | 96.1 | 1.3 | 3.8 | 86.4 | 6.3 | 9.2 | 108.2 | 3.0 | 9.5 | 95.1 | 3.3 | 12.8 | 90.7 | 3.4 | 3.6 |
100 | 103.9 | 2.8 | 8.4 | 90.5 | 3.4 | 7.3 | 93.9 | 2.4 | 3.0 | 93.2 | 7.9 | 8.5 | 100.1 | 12.3 | 15.7 | 89.7 | 4.2 | 7.6 | 97.4 | 2.0 | 6.0 | |
1000 | 104.2 | 4.3 | 11.5 | 86.1 | 9.5 | 9.0 | 97.0 | 1.8 | 5.7 | 91.1 | 2.2 | 5.6 | 101.4 | 2.9 | 8.7 | 90.1 | 5.4 | 7.3 | 100.2 | 2.7 | 7.5 | |
Chlorantraniliprole | 5 | 93.2 | 3.6 | 13.2 | 104.9 | 3.0 | 4.1 | 99.1 | 3.1 | 6.5 | 91.8 | 2.9 | 10.8 | 88.3 | 10.8 | 7.7 | 94.9 | 8.4 | 13.8 | 93.0 | 4.1 | 9.8 |
100 | 102.2 | 9.5 | 9.2 | 90.6 | 1.3 | 2.3 | 88.3 | 8.9 | 7.3 | 94.9 | 1.6 | 3.8 | 94.2 | 7.8 | 11.2 | 91.3 | 4.7 | 5.4 | 89.2 | 4.4 | 9.3 | |
1000 | 91.7 | 6.1 | 10.6 | 90.4 | 3.4 | 8.3 | 87.7 | 1.6 | 3.6 | 99.8 | 1.1 | 3.9 | 100.5 | 3.6 | 4.3 | 92.5 | 2.3 | 5.1 | 87.3 | 8.2 | 8.5 | |
Cyantraniliprole | 5 | 94.6 | 8.6 | 7.4 | 92.1 | 3.5 | 4.7 | 93.8 | 6.3 | 7.2 | 89.0 | 2.2 | 8.9 | 99.1 | 7.4 | 8.7 | 95.8 | 7.2 | 12.3 | 88.3 | 7.3 | 7.8 |
100 | 93.8 | 7.3 | 6.2 | 85.5 | 2.4 | 7.3 | 83.4 | 4.0 | 6.3 | 93.3 | 2.0 | 3.4 | 92.5 | 6.2 | 10.4 | 89.9 | 4.0 | 6.3 | 95.5 | 8.7 | 8.2 | |
1000 | 89.6 | 1.8 | 5.8 | 87.1 | 3.2 | 3.7 | 88.3 | 1.1 | 4.9 | 96.0 | 1.3 | 2.9 | 97.7 | 2.7 | 4.9 | 88.0 | 2.5 | 4.2 | 98.5 | 5.4 | 8.8 | |
Tetrachlorantraniliprole | 5 | 94.4 | 5.2 | 3.5 | 96.0 | 1.2 | 5.0 | 92.9 | 2.3 | 7.6 | 86.1 | 4.5 | 9.0 | 99.9 | 1.7 | 9.3 | 97.2 | 4.0 | 15.3 | 88.4 | 4.9 | 7.8 |
100 | 97.2 | 6.9 | 9.5 | 92.1 | 6.0 | 8.3 | 95.9 | 1.8 | 2.7 | 96.0 | 4.9 | 5.7 | 98.0 | 13.4 | 12.9 | 106.5 | 2.6 | 5.8 | 88.3 | 2.7 | 5.0 | |
1000 | 96.7 | 2.7 | 7.2 | 91.9 | 6.8 | 7.5 | 100.6 | 3.9 | 4.0 | 90.8 | 1.8 | 4.0 | 99.4 | 1.5 | 6.1 | 108.1 | 1.2 | 6.3 | 99.7 | 1.4 | 3.2 | |
Tetraniliprole | 5 | 93.8 | 6.1 | 10.1 | 99.3 | 1.8 | 7.0 | 97.3 | 5.7 | 12.6 | 97.7 | 4.7 | 9.1 | 89.7 | 9.7 | 9.1 | 99.1 | 5.7 | 13.4 | 95.0 | 6.0 | 10.3 |
100 | 97.1 | 5.9 | 8.6 | 95.3 | 2.1 | 4.4 | 92.3 | 11.0 | 10.5 | 94.1 | 5.6 | 6.7 | 93.0 | 9.5 | 12.5 | 95.7 | 4.7 | 4.9 | 100.4 | 3.5 | 13.7 | |
1000 | 93.1 | 5.3 | 6.8 | 95.5 | 4.4 | 5.1 | 93.9 | 1.5 | 9.8 | 95.8 | 4.4 | 7.6 | 96.8 | 2.4 | 5.1 | 95.3 | 1.3 | 7.0 | 90.1 | 7.2 | 11.2 | |
Thiorantraniliprole | 5 | 76.6 | 4.1 | 4.6 | 77.0 | 4.8 | 5.8 | 93.5 | 5.1 | 9.9 | 86.0 | 2.9 | 6.4 | 90.9 | 4.7 | 5.3 | 87.7 | 8.3 | 9.9 | 88.5 | 3.1 | 7.7 |
100 | 93.7 | 4.2 | 5.4 | 85.7 | 1.0 | 2.9 | 80.3 | 7.1 | 6.8 | 89.3 | 1.8 | 9.6 | 86.2 | 1.6 | 8.7 | 91.0 | 2.8 | 6.7 | 94.1 | 5.3 | 6.2 | |
1000 | 91.6 | 2.1 | 2.3 | 88.8 | 1.5 | 4.3 | 91.0 | 2.6 | 11.1 | 99.1 | 1.4 | 8.2 | 96.0 | 1.4 | 4.2 | 90.2 | 7.4 | 8.5 | 96.9 | 1.5 | 6.3 | |
Cyclaniliprole | 5 | 94.8 | 5.9 | 8.2 | 91.5 | 2.5 | 6.0 | 93.5 | 3.6 | 8.4 | 91.5 | 4.9 | 6.2 | 101.7 | 5.7 | 6.7 | 91.0 | 10.8 | 12.9 | 86.3 | 9.0 | 9.8 |
100 | 101.1 | 6.0 | 9.1 | 86.2 | 7.4 | 7.8 | 96.9 | 2.8 | 4.1 | 94.7 | 4.1 | 4.2 | 93.6 | 9.5 | 14.4 | 91.6 | 2.0 | 7.2 | 90.1 | 3.1 | 10.4 | |
1000 | 107.5 | 6.9 | 9.5 | 84.6 | 8.5 | 8.6 | 106.2 | 2.7 | 6.5 | 87.3 | 1.3 | 2.5 | 101.0 | 2.3 | 7.5 | 101.0 | 3.3 | 5.0 | 99.8 | 5.8 | 11.4 | |
Broflanilide | 5 | 90.4 | 5.0 | 6.4 | 96.3 | 3.4 | 7.5 | 99.0 | 5.4 | 9.0 | 86.9 | 4.9 | 9.1 | 96.1 | 3.5 | 9.6 | 94.6 | 10.5 | 7.6 | 86.7 | 5.4 | 6.1 |
100 | 83.7 | 3.6 | 9.0 | 90.3 | 1.1 | 6.1 | 84.8 | 1.8 | 8.2 | 94.6 | 1.7 | 4.3 | 98.9 | 1.6 | 5.5 | 96.2 | 3.3 | 7.0 | 90.3 | 11.3 | 8.7 | |
1000 | 83.0 | 3.4 | 8.0 | 97.7 | 1.4 | 7.8 | 90.2 | 5.0 | 5.5 | 96.0 | 4.2 | 7.4 | 101.1 | 2.8 | 5.3 | 88.0 | 2.5 | 4.7 | 89.7 | 5.2 | 6.5 | |
Fluchlordiniliprole | 5 | 95.8 | 4.2 | 4.6 | 87.5 | 3.9 | 9.0 | 93.5 | 5.1 | 93.5 | 93.2 | 2.4 | 9.9 | 92.2 | 5.2 | 7.7 | 97.5 | 6.9 | 7.2 | 92.1 | 3.3 | 7.6 |
100 | 89.8 | 4.7 | 5.2 | 89.2 | 5.7 | 5.4 | 92.4 | 2.9 | 92.4 | 97.1 | 1.9 | 9.2 | 104.2 | 2.3 | 11.9 | 97.8 | 1.4 | 4.6 | 98.0 | 5.9 | 9.8 | |
1000 | 92.6 | 2.9 | 4.0 | 97.6 | 11.0 | 7.9 | 8.2 | 5.2 | 6.4 | 95.3 | 7.0 | 10.7 | 98.1 | 2.7 | 3.0 | 95.9 | 2.5 | 6.8 | 89.5 | 4.4 | 5.1 |
Extracts of vegetable, fruit, and cereal matrices generally contained a lot of components, such as fats, proteins, pigments, fatty acids, and sugars. These compounds can increase the surface tension of the droplets and the viscosity of the sample, resulting in a decrease in the evaporation efficiency of the ten diamide insecticides.48,49 As is known to all, the occurrence of matrix effects should be calculated when LC-MS with ESI analysis was used to co-elute sample constituents. The ME can enhance or suppress analyte signals depending on the level of ion inhibition and may also lead to inaccurate quantitative results. The evaluation of ME was very important for LC-MS/MS analysis because it can affect the trueness and sensitivity of the proposed method.35 Therefore, to evaluate the influence of the ESI source, the ME was calculated by comparing the slopes acquired in matrix spiked calibration and those acquired in standard solution calibration. The negative and positive results suggest that the ion signal was suppressed and enhanced, respectively. As mentioned in previous studies, to obtain accurate results, the matrix-matched standard calibration was used for quantification.7,35,50 Thus, in the current study, this method was utilized to compensate the ME for quantitative analysis. All the above results show the potential of the developed QuEChERS and HPLC-MS/MS methods to detect the ten diamide insecticides for food safety analysis.
Footnotes |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4ay02117g |
‡ The authors Fajun Tian and Zhenzhen Zhou contributed equally to this study and share first authorship. |
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