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Mohammad Rezaee Nuclear Fuel Cycle Research School, Nuclear Science and Technology Research Institute, Tehran, Iran

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Faezeh Khalilian Department of Chemistry, College of Basic Science, Yadegar -e- Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran

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Mohammad Reza Pourjavid Nuclear Fuel Cycle Research School, Nuclear Science and Technology Research Institute, Tehran, Iran

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Abstract

A new pretreatment method termed ultrasound-assisted extraction (UAE) which is combined with solid-phase extraction which is combined with dispersive liquid-liquid microextraction (SPE-DLLME) followed by gas chromatography-flame ionization detector (GC-FID) analysis has been developed for the determination of diazinon in garden parsley as vegetable samples. The analyte was extracted from garden parsley sample using ultrasound-assisted extraction followed by solid-phase extraction followed by dispersive liquid-liquid microextraction. Various parameters that affect the efficiency of the extraction techniques have been optimized. The calibration plot was linear in the range of 5.0–1,000 μg kg−1 with detection limit of 1.0 μg kg−1 for diazinon in garden parsley samples. The results confirm the suitability of the UAE-SPE-DLLME-GC-FID as a sensitive method for the analysis of the targeted analyte in garden parsley samples.

Abstract

A new pretreatment method termed ultrasound-assisted extraction (UAE) which is combined with solid-phase extraction which is combined with dispersive liquid-liquid microextraction (SPE-DLLME) followed by gas chromatography-flame ionization detector (GC-FID) analysis has been developed for the determination of diazinon in garden parsley as vegetable samples. The analyte was extracted from garden parsley sample using ultrasound-assisted extraction followed by solid-phase extraction followed by dispersive liquid-liquid microextraction. Various parameters that affect the efficiency of the extraction techniques have been optimized. The calibration plot was linear in the range of 5.0–1,000 μg kg−1 with detection limit of 1.0 μg kg−1 for diazinon in garden parsley samples. The results confirm the suitability of the UAE-SPE-DLLME-GC-FID as a sensitive method for the analysis of the targeted analyte in garden parsley samples.

Introduction

Diazinon (o,o-diethyl o-2-isopropyl-6-methylprimidin-4-ylphosphorothioate) is an organophosphorous compound often used in agriculture [1]. In different vegetables, for better yield and quality, pesticides are repeatedly applied during the entire period of growth. These are absorbed by the vegetables and turned out to be noxious when consumed by human beings. This compound is also known as a reducer of the activity of neuro transmitters and cause irreversible effects on the nervous system [2].

The accumulation of pesticides in agricultural products is of great concern because plants act as intermediates in the transport of contaminants from soil, water, and air to humans and fauna.

Pesticides are used widely in agriculture to enhance food production by controlling unwanted insects and disease vectors. The excessive use of pesticides in public health and agriculture programs has caused severe acute cases of poisonings in humans and animals [3]. Diazinon is a neurotoxic chemical agent that inhibits acetylcholine esterase (AChE) activity [4]. This inhibition causes accumulation of acetylcholine in cholinergic synapses leading to increased activation of nicotinic and muscarinic receptors. It has some toxic effects such as delirium, headache, dizziness, weakness, tiredness convulsions, and depression [5]. Also, other toxic effects of diazinon on hepatocytes, spleen, thymus, blood cells, lymph nodes, and heart have been reported in human and animals [6].

Recently, a new liquid-liquid microextraction method termed dispersive liquid-liquid microextraction (DLLME) was reported by Rezaee et al. [7]. DLLME has been applied for the analysis of a variety of trace organic pollutants and metal ions in environmental samples [8–12]. The objective of the sample preparation is often not only to isolate the target analytes from the samples and concentrate the analytes, but also simultaneously to reduce or even eliminate the interferences originally present in the sample and to facilitate their determination at low levels. The main disadvantages of the DLLME is that it is not a selective extraction method. On the other hand, the interferences from matrix co-extractives are often present, especially for the determination of trace analytes in a complex matrix sample. This is the main reason that the most reported applications of DLLME have been focused on simple water samples. Therefore, the exploration of the potential applications of the DLLME technique in more complex matrix sample is desirable. SPE is widely used as a sample clean-up and concentration technique in sample preparations. The application of SPE-DLLME to solid samples had received minor attention. However, for solid samples such as vegetables SPE-DLLME can not be used. The main disadvantages of the SPE-DLLME in vegetable sample is that it is not a suitable extraction technique and also fails because phases do not separate even after centrifugation (because of dirty extracts). Therefore, in the analysis of this sample a first step is necessary before SPE-DLLME. Ultrasound-assisted extraction (UAE) is considered a good alternative for organic compound extraction from different matrices which provides a more efficient contact between the solid and solvent. One of the advantages of such a combination is that it can be used for complex matrix samples at low levels concentrations. Therefore, This combination of UAE and SPE and DLLME methods as a novel sample pretreatment method have some advantages. Firstly, it leads to high preconcentration factor, secondly, DLLME can be easily applied for complex matrices such as garden parsley as vegetable samples and thirdly, solving the main problems of SPE that have poor recovery, reproducibility issues, and sample extracts being insufficiently clean. Diazinon is the most popular pesticide used to control insects and disease vectors in garden parsley as vegetable samples in Mazandaran province in Sari, Iran. As important for determining diazinon, it was selected for the application of the proposed method. Also, in our country (Iran) most of the laboratories do not have very sensitive detection system for GC such as MS because of high cost of MS detector system. Therefore, we have to develop the new sample preparation method for determination of the trace amounts of diazinon in garden parsley samples by using simple GC instrument with simple FID detector which most of laboratories have GC-FID system. The developed method was subsequently applied for the assessment of pesticide levels in vegetable samples from local markets in Mazandaran, Iran.

Sample preparation is a crucial step in chemical analysis. Among many treatment methods, liquid-liquid extraction (LLE) [13], supercritical fluid extraction (SFE) [14], microwave-assisted extraction (MAE) [15] and solid-phase microextraction (SPME) [16] have been used for the determination of diazinon. However, LLE require large amounts of solvent and large sample sizes, in contradiction to the principles of sustainable “green” practices in modern laboratories. SFE and MAE incur high costs of operation and machinery, which discourage popular usage. Due to the intrinsic nature of SPME, namely that it is based on analyte equilibration between binary solid and liquid phases, lengthy extraction time is often required.

Extraction solvents often used in DLLME are toxic and have higher density than water. However, many of common liquid-liquid extraction solvents are less dense than water. The application of these solvents in dispersion-based microextraction like DLLME will be problematic. We used home-designed glass centrifuge vial, which has a conic head and a glass tube fixed on the side of the vial, to explore the possibility of applying low-density organic solvents. After centrifugation, the organic solvents floated on the surface of samples, lifting-up in the conic head by adding a few microliters of doubly distilled water into the side tube of the vial, were collected prior to gas chromatography analysis.

Experimental

Chemicals and reagents

Diazinon was purchased from polyscience (Niles, USA). A stock solution of the studied pesticide was prepared in methanol at a concentration of 1,000 mg L−1. Working standard solutions were prepared daily by appropriate dilutions of the stock solution with deionized water. Toluene, 1-dodecanol, n-hexane, 1-octanol, cyclohexane and sodium chloride were obtained from Merck company (Darmstadt, Germany). Youngling ultra pure water purification system (aqua maxTM-ultra, Korea) was used for purification of water. Ten kilograms of garden parsley as vegetable samples were obtained from local markets in sari, Mazandaran province, Iran. They were chopped and homogenized in a laboratory homogenizer at high speed before use.

Apparatus

A 40 kHz and 0.138 kW ultrasonic water bath with temperature control (Tecno-Gaz SpA, Italy) was applied to emulsify the organic solvent. One hundred and 25 μL Hamilton syringes (Bonaduz, Switzerland) were used to inject the organic solvent into aqueous samples. Twenty milliliters home-designed centrifuge glass vials were used for extraction and collection procedure. A 10.0 μL Hamilton gas-tight syringe was applied for the collection of floated organic solvent and injection into the GC. A gas chromatograph (Agilent GC-7890) equipped with a split/splitless injector system and flame ionization detector, was used for separation and determination of diazinon. Ultra pure helium gas (99.999%, Air products, UK) was passed through a molecular sieve and oxygen trap (Crs, USA) and was used as carrier gas with a flow rate of 2 mL min−1. The injection port was held at 250 °C and operated in the splitless mode for 1 min then split valve was opened and split ratio of 1:5 was applied. Separation was carried out on a DB5, 25 m × 0.32 mm i.d. and 0.25 μm film thickness from SGE (Victoria, Australia) Capillary column. The oven temperature was kept at 150 °C for 2 min and then increased to 200 °C at the rate of 5 °C min−1, and was held for 5 min. The FID oven temperature was maintained at 270 °C. Hydrogen was generated by hydrogen generator (OPGU-2200S, Shimadzu) for FID at a flow rate of 40 mL min−1. The flow of air (99.999%, Air products) for FID was 400 mL min−1.

UAE-SPE-DLLME procedure

After the sample was homogenized, 1.0 g of the sample was accurately weighed in 25 mL vial followed by the addition of 10 mL acetonitrile/water (2:3, v/v) as extraction solvent. Ultrasound-assisted extraction was carried out for 20 min using a 40 kHz and 0.138 KW ultrasonic water bath with temperature control (Tecno-Gaz SPA, Italy). Samples were centrifuged for 4 min at 5,000 rpm. The extracts were filtered on a filter paper (Whatman No 44) and then the supernatant solution was collected. The final extractant was passed through a octadecyl (C18) sorbent (3 mL syringe barrel, Waters, USA), previously activated with 2 mL methanol followed by 2 mL water. After sample loading at flow rate of about 6.7 mL min−1 with the aid of a vacuum pump (Rotavac, Heidolph, Germany), the sorbent was dried at pressure 5 psi for 2 min. Pesticide was eluted with 1.5 mL acetonitrile and the eluent was collected into the test tube. The elution solvent was used as disperser solvent in the subsequent DLLME procedure. 1.5 mL acetonitrile (disperser solvent) containing 20.0 µL toluene (extraction solvent) was injected into 10 mL aqueous solution in home-designed glass centrifuge vial. A cloudy solution, resulting from the dispersion of the fine toluene droplets in the aqueous solution was formed in the test tube. In this step, diazinon extracted into fine toluene droplets in a few seconds. Then, it was centrifuged at 3,500 rpm for 5 min to separate the phases. After separation of the two phases, a few microliters of doubly distilled water were added into the vial through the glass tube fixed on the side of the vial. The floated organic solvent was raised into the capillary tube attached to the top of the vial and collected by a gas-tight syringe. Two microliters of collected organic solvent was injected into GC-FID instrument. Schematic of the proposed method for the determination of diazinon in garden parsley samples was shown in Fig. 1.

Fig. 1.
Fig. 1.

Schematic of the proposed method for the determination of diazinon in garden parsley samples

Citation: Acta Chromatographica 2022; 10.1556/1326.2022.01086

Results and discussion

UAE-SPE-DLLME combined with GC-FID was developed for determination of diazinon in garden parsley as vegetable samples. In order to obtain a high recovery and enrichment factor, effects of different parameters were optimized. Optimization of the variables was performed using one variable at a time method. UAE-SPE-DLLME method provided higher purification ability and selectivity and high enrichment factor.

Ultrasound-assisted extraction

The optimization of the UAE was developed with free of pesticide-samples. For this purpose, different extraction solvents such as acetonitrile, acetone and methanol were used. Different amounts of samples (between 1.0 and 5.0 g) were sonicated with the solvents between 5 and 30 min. Results showed that the best recovery was achieved using acetonitrile as an extracting solvent. Among the different mixtures tested, the extraction of 1.0 g of the sample for 20 min with 10 mL of acetonitrile was enough to provide a good extraction of pesticide. Different amounts of water were used with acetonitrile as an extraction solvent in UAE method. The ration of solvent (acetonitrile:water, v/v) were 2:3, 1:4, 3:2 and 4:1. The results (Table 1) show that when the ratio of acetonitrile:water, v/v was 2:3, a good extraction of diazinon was obtained.

Table 1.

Extraction recovery (%) of different ratio of Acetonitrile and water for the extraction of diazinon

Ratio of solvent (Acetonitrile:water) Extraction recovery (%)
2:3 86
1:4 21
3:2 66
4:1 47

Effect of type and volume of the extraction solvent

The selection of a suitable extraction solvent is critical for the DLLME process. The extraction solvent should have following characteristics: 1) lower density than that of water, 2) low solubility in water, 3) the ability to extract interest analyte. Based on these requirements, five organic solvent candidates, including toluene, 1-octanol, cyclohexane, n-hexane and 1-dodecanol were investigated. The results (Table 2) revealed that the extraction recovery obtained for the analyte using toluene were higher than those with the other solvents. Therefore, toluene was selected as the extraction solvent for the study.

Table 2.

Extraction recovery of different extraction solvents evaluated for the extraction of diazinon

Extraction solvent Extraction recovery (%)
Toluene 86
Cyclohexane 25
n-Hexane 11
1-Dodecanol 41
1-Octanol 65

The effect of the volume of the extracting solvent on the proposed method of diazinon was investigated in the range of 20.0–48.0 µL. According to Fig. 2, by increasing the volume of toluene, extraction recovery decrease, because the volume of collected solvent increases. Hence, high extraction recovery are obtained using the 20.0 µL volume of extraction solvent. In the following studies, 20.0 µL was selected as the optimal volume of extraction solvent.

Fig. 2.
Fig. 2.

Effect of the extraction solvent (toluene) volume on the extraction recovery of the analyte

Citation: Acta Chromatographica 2022; 10.1556/1326.2022.01086

Effect of type and volume of disperser solvent

The elution solvent in the SPE step is used as the disperser solvent in DLLME. The disperser solvent should be miscible with both extraction solvent and aqueous phase. The main criterion for selecting the disperser solvent was its miscibility with the extraction solvent and aqueous sample. For this purpose, different solvents such as acetonitrile, ethanol, methanol and acetone were examined. The extraction was performed using 1.5 mL of each disperser solvent containing 20.0 µL toluene. Table 3, indicates that acetonitrile exhibits the highest extraction efficiency. Thus, acetonitrile was selected as the disperser or eluent solvent for subsequent experiment.

Table 3.

Extraction recovery of different disperser solvents evaluated for the extraction of diazinon

Disperser solvent Extraction recovery (%)
Acetone 58
Acetonitrile 86
Methanol 74
Ethanol 72

In order to study the effect of disperser solvent volume, different volumes of acetonitrile (0.5, 1.0, 1.5 and 2.0 mL) were used. It is clear from Fig. 3 that 1.5 mL acetonitrile had the highest recovery. It seems that, at the volume of 1.5 mL, the amount of acetonitrile was enough for effective elution of diazinon. At a low volume of acetonitrile, cloudy solution was not properly formed resulting in a decrease in the extraction recovery. At a high volume of acetonitrile, the solubility of the analyte in the sample increased resulting in a decrease in extraction efficiency. Thus, 1.5 mL was selected as the optimum volume of acetonitrile.

Fig. 3.
Fig. 3.

Effect of the disperser solvent (acetonitrile) volume on the extraction efficiency of the analyte

Citation: Acta Chromatographica 2022; 10.1556/1326.2022.01086

Effect of the flow rate of the sample solution

The flow rate of the sample solution through the SPE column controls the analytical time and affects the retention capacity of the analyte. The flow rate must be high enough to reduce the analytical time. On the other hand, it must be slow enough to perform an effective retention of the analyte. Therefore, the optimized flow rate should consider the two factors mentioned previously. The effect of flow rate on recovery of diazinon was investigated in the range of 0.65–8.6 mL min−1. Figure 4 shows that the analyte recovery did not change significantly from the range of 0.65–6.7 mL min−1, although an increase in the flow rate decreased the recovery. Therefore, 6.7 mL min−1 was selected as the optimized flow rate.

Fig. 4.
Fig. 4.

Effect of the flow rate on the extraction efficiency of the analyte

Citation: Acta Chromatographica 2022; 10.1556/1326.2022.01086

Effect of salt addition

The influence of ionic strength was evaluated at 0–8% (w/v) NaCl. The experimental results showed that the addition of salt had no significant effect on the extraction efficiency of the analyte. This is probably due to the opposite effects of the addition of salt. One is to increase the volume of the collected solvent and dilution effect, this reduces the extraction efficiency; another is the salting out effect, that increases the extraction efficiency. It is to be noted that by increasing the salt concentration, the volume of the collected solvent phase increased, due to the decrease in the solubility of the extraction solvent. Therefore, the following experiments were carried out without addition of salt.

Analytical performance

The calibration curve of diazinon with a linear range of 5.0–1,000 μg kg−1 and a suitable coefficient of determination (r 2 = 0.9987), were obtained under the optimized condition. The relative standard deviations (RSD, n = 5) for diazinon extraction and its determination was 10.2%. The limit of detection (LOD), based on signal-to-noise (S/N) of 3 was 1.0 μg kg−1. It is remarkable that the studied pesticide can be determined at very low concentration (5 μg kg−1) by the proposed method in garden parsley as vegetable samples, clearly below the minimum MRL stated by the EU legislation (10 μg kg−1).

Table 4 compare the proposed method with other extraction methods for the determination of the target analyte. The quantitative results of the proposed method are comparable with microwave-assisted extraction (MAE) [18] and solid-phase microextraction (SPME) [17] without using very sensitive detector such as MS and ECD detectors. MAE incur high costs of operation and machinery, which discourage popular usage The quantitative results of the proposed method are better with quick, easy, cheap, effective, rugged, and safe method (QuEChERS) [19, 20] without using very sensitive detector such as MS. The comparison of extraction time of the proposed method with SPME [17] for the extraction of the target analyte indicates that this novel method needs less time compare with it. Finally, the proposed method has great potential to determine the selected analyte at trace levels in garden parsley as vegetable samples.

Table 4.

Comparison of the proposed method with other extraction methods for determination of the target analyte in garden parsley as vegetable samples

Methods R.S.D.% Dynamic linear range (µg kg −1) Limit of detection (µg kg−1) Extraction time (min) Ref.
SPME-GC-ECD <10 10–1,000 0.2 30 [17]
Microwave-assisted extraction-GC-MS <8.7 5–500 1.38 10 [18]
QuEChERS-GC-MS 3.2 10.2–400 3.9 5 [19]
QuEChERS-HPLC-UV <9 0.05–3 (mg kg−1) 0.05 (mg kg−1) 5 [20]
UAE-SPE-DLLME-GC-FID 10.2 5–1,000 1 20 This work

Extraction of the diazinon from garden parsley as vegetable samples

Due to the importance of the analysis of diazinon in garden parsley as vegetable samples, the proposed method was applied to determine the concentration of diazinon in garden parsley as vegetable samples, the obtained results are summarized in Table 5. The chromatograms (A) without spike of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (B) 10.0 μg kg−1 spiked of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (C) 20.0 μg kg−1 spiked of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (D) garden parsley sample (3) with low concentration of diazinon (5.0 μg kg−1) after extraction via proposed method at optimum conditions are shown in Fig. 5. The relative recoveries were between 90–93% (Table 5) and showed that the matrices had negligible effect on the performance of the proposed method. It is mentioned that tailing factor or symmetry peak value for obtained chromatogram was 1.1.

Table 5.

Determination of diazinon (Dia) in garden parsley as vegetable samples

Sample Concentration of Dia (µg Kg−1) ± SD, n = 3 Added of Dia (µg Kg−1) Found Dia (µg Kg−1) ± SD, n = 3 Relative recovery (%)
Sample 1 n.d. 20.0 18.2 ± 2.0 91
n.d. 10.0 9.0 ± 1.0 90
Sample 2 n.d. 50.0 46.5 ± 4.6 93
Sample 3 5.0 ± 0.5 10.0 14.0 ± 1.5 90
Fig. 5.
Fig. 5.

GC-FID chromatograms of (A) without spike of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (B) 10.0 μg kg−1 spiked of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (C) 20.0 μg kg−1 spiked of the analyte in garden parsley as vegetable sample (1) after extraction via proposed method at optimum conditions (D) garden parsley sample (3) with low concentration of diazinon (5.0 μg kg−1) after extraction via proposed method at optimum conditions

Citation: Acta Chromatographica 2022; 10.1556/1326.2022.01086

Conclusions

In this study, UAE and SPE clean-up methods combined with dispersive liquid-liquid microextraction by using low density solvent has been developed as a new approach for extracting diazinon in garden parsley as vegetable samples by GC analysis. The combination of UAE with SPE with DLLME makes it possible for the selective determination of trace analyte in complex matrices to be done easily. The evaluation of the analytical performance of the proposed method provided satisfactory linearity, precision and detection limits and it was successfully applied in the analysis of real samples. The proposed methodology offers a time-saving in comparison with solid-phase microextraction and requires lower volumes of toxic and cost solvents in comparison with QuEChERS method. UAE-SPE-DLLME employs simple and inexpensive equipment, and it is applicable for most of the analytical laboratories in comparison with microwave-assisted extraction-GC-MS methodology. UAE-SPE-DLLME-GC-FID showed better dynamic linear range in comparison with SPME-GC–ECD, QuEChERS-GC–MS and QuEChERS-HPLC-UV methodologies without using sensitive detectors such as MS and ECD. The limit of detection (LOD) was 1.0 μg kg−1, allowing application of the procedure for detection below the level imposed by existing regulations. Therefore, it has the potential of being a powerful tool for the analysis of targeted analyte at trace level in garden parsley as vegetable samples.

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    Cortada, C. ; Vidal, L. ; Pastor, R. ; Santiago, N. ; Canals, A. Anal. Chim. Acta 2009, 649, 218.

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    Garcia-Lopez, M. ; Rodriguez, I. ; Cela, R. J. Chromatogr. A. 2007, 1166, 9.

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    Nagaraju, D. ; Huang, S. D. J. Chromatogr. A. 2007, 1161, 89.

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    Rezaee, M. ; Assadi, Y. ; Milani Hosseini, M. R. ; Aghaee, E. ; Ahmadi, F. ; Berijani, S. J. Chromatogr. A. 2006, 1116, 1.

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    • Search Google Scholar
    • Export Citation
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    Lehotay, S. J. ; Valverde-Garcia, A. J. Chromatogr. A. 1997, 765, 69.

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    Zhao, X. ; Xu, X. ; Su, R. ; Zhang, H. ; Wang, Z. J. Chromatogr. A. 2012, 1229, 6.

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    Sang, Z. Y. ; Wang, Y. T. ; Tsoi, Y. K. ; Leung, K. S. Y. Food Chem. 2013, 136, 710.

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    Chai, M. ; Tan, G. ; Lal, A. Anal. Sci. 2008, 24, 273.

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    Wu, L. ; Hu, M. ; Li, Z. ; Song, Y. ; Yu, C. ; Zhang, H. ; Yu, A. ; Ma, Q. ; Wang, Z. Food Chem. 2016, 192, 596.

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    Farshidi, M. ; Moludi, J. ; Mohebbi, A. ; Ebrahimi, B. ; kamali shojaei, A. J. Food Bioproc. Eng. 2021, 4, 19.

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    Gotah, A. ; Garcia, C. V. ; Lee, S. P. ; Whang, K. Korean J. Food Preserv. 2018, 25, 446.

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Senior editors

Editor(s)-in-Chief: Kowalska, Teresa

Editor(s)-in-Chief: Sajewicz, Mieczyslaw

Editors(s)

  • Danica Agbaba (University of Belgrade, Belgrade, Serbia)
  • Ivana Stanimirova-Daszykowska (University of Silesia, Katowice, Poland)
  • Monika Waksmundzka-Hajnos (Medical University of Lublin, Lublin, Poland)

Editorial Board

  • R. Bhushan (The Indian Institute of Technology, Roorkee, India)
  • J. Bojarski (Jagiellonian University, Kraków, Poland)
  • B. Chankvetadze (State University of Tbilisi, Tbilisi, Georgia)
  • M. Daszykowski (University of Silesia, Katowice, Poland)
  • T.H. Dzido (Medical University of Lublin, Lublin, Poland)
  • A. Felinger (University of Pécs, Pécs, Hungary)
  • K. Glowniak (Medical University of Lublin, Lublin, Poland)
  • B. Glód (Siedlce University of Natural Sciences and Humanities, Siedlce, Poland)
  • A. Gumieniczek (Medical University of Lublin, Lublin, Poland)
  • U. Hubicka (Jagiellonian University, Kraków, Poland)
  • K. Kaczmarski (Rzeszow University of Technology, Rzeszów, Poland)
  • H. Kalász (Semmelweis University, Budapest, Hungary)
  • K. Karljiković Rajić (University of Belgrade, Belgrade, Serbia)
  • I. Klebovich (Semmelweis University, Budapest, Hungary)
  • A. Koch (Private Pharmacy, Hamburg, Germany)
  • Ł. Komsta (Medical University of Lublin, Lublin, Poland)
  • P. Kus (Univerity of Silesia, Katowice, Poland)
  • D. Mangelings (Free University of Brussels, Brussels, Belgium)
  • E. Mincsovics (Corvinus University of Budapest, Budapest, Hungary)
  • Á. M. Móricz (Centre for Agricultural Research, Budapest, Hungary)
  • G. Morlock (Giessen University, Giessen, Germany)
  • A. Petruczynik (Medical University of Lublin, Lublin, Poland)
  • R. Skibiński (Medical University of Lublin, Lublin, Poland)
  • B. Spangenberg (Offenburg University of Applied Sciences, Germany)
  • T. Tuzimski (Medical University of Lublin, Lublin, Poland)
  • Y. Vander Heyden (Free University of Brussels, Brussels, Belgium)
  • A. Voelkel (Poznań University of Technology, Poznań, Poland)
  • B. Walczak (University of Silesia, Katowice, Poland)
  • W. Wasiak (Adam Mickiewicz University, Poznań, Poland)
  • I.G. Zenkevich (St. Petersburg State University, St. Petersburg, Russian Federation)

 

KOWALSKA, TERESA
E-mail: kowalska@us.edu.pl

SAJEWICZ, MIECZYSLAW
E-mail:msajewic@us.edu.pl

Indexing and Abstracting Services:

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2021  
Web of Science  
Total Cites
WoS
652
Journal Impact Factor 2,011
Rank by Impact Factor Chemistry, Analytical 66/87
Impact Factor
without
Journal Self Cites
1,789
5 Year
Impact Factor
1,350
Journal Citation Indicator 0,40
Rank by Journal Citation Indicator Chemistry, Analytical 72/99
Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0,27
Scimago Quartile Score Chemistry (miscellaneous) (Q3)
Scopus  
Scopus
Cite Score
2,8
Scopus
CIte Score Rank
General Chemistry 210/409 (Q3)
Scopus
SNIP
0,586

2020
 
Total Cites
650
WoS
Journal
Impact Factor
1,639
Rank by
Chemistry, Analytical 71/83 (Q4)
Impact Factor
 
Impact Factor
1,412
without
Journal Self Cites
5 Year
1,301
Impact Factor
Journal
0,34
Citation Indicator
 
Rank by Journal
Chemistry, Analytical 75/93 (Q4)
Citation Indicator
 
Citable
45
Items
Total
43
Articles
Total
2
Reviews
Scimago
28
H-index
Scimago
0,316
Journal Rank
Scimago
Chemistry (miscellaneous) Q3
Quartile Score
 
Scopus
393/181=2,2
Scite Score
 
Scopus
General Chemistry 215/398 (Q3)
Scite Score Rank
 
Scopus
0,560
SNIP
 
Days from
58
submission
 
to acceptance
 
Days from
68
acceptance
 
to publication
 
Acceptance
51%
Rate

2019  
Total Cites
WoS
495
Impact Factor 1,418
Impact Factor
without
Journal Self Cites
1,374
5 Year
Impact Factor
0,936
Immediacy
Index
0,460
Citable
Items
50
Total
Articles
50
Total
Reviews
0
Cited
Half-Life
6,2
Citing
Half-Life
8,3
Eigenfactor
Score
0,00048
Article Influence
Score
0,164
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,05895
Average
IF
Percentile
20,349
Scimago
H-index
26
Scimago
Journal Rank
0,255
Scopus
Scite Score
226/167=1,4
Scopus
Scite Score Rank
Chemistry (miscellaneous) 240/398 (Q3)
Scopus
SNIP
0,494
Acceptance
Rate
41%

 

Acta Chromatographica
Publication Model Online only
Gold Open Access
Submission Fee none
Article Processing Charge 400 EUR/article
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Acta Chromatographica
Language English
Size A4
Year of
Foundation
1992
Volumes
per Year
1
Issues
per Year
4
Founder Institute of Chemistry, University of Silesia
Founder's
Address
PL-40-007 Katowice, Poland, Bankowa 12
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2083-5736 (Online)

Monthly Content Usage

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Sep 2022 0 39 9
Oct 2022 0 0 0