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  • 1 Department of Food Engineering, Faculty of Engineering and Architecture, Avrasya University, 61250, Trabzon, Turkey
  • | 2 Food Safety and Agricultural Research Center, Akdeniz University, 07059, Antalya, Turkey
  • | 3 Rose and Rose Products Research and Application Center, Süleyman Demirel University, 32260, Isparta, Turkey
  • | 4 Department of Food Engineering, Faculty of Engineering, Akdeniz University, 07059, Antalya, Turkey
Open access

Abstract

Residues in animal feeds and foods of animal origin have been important safety issue concerning both human and animal health. A multiresidue method for determination of eight mycotoxins and ten antibiotics was developed and validated in animal feeds by using QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction followed by UHPLC-MS/MS. Optimisation of UHPLC-MS/MS parameters was performed to achieve good separation and resolution. The method was validated according to the European Commission Decision 2002/657/EC. Matrix matched calibration curves showed good r2 (≥0.995) values, and limit of quantification (LOQ) values varied between 1.2 and 5.2 μg kg−1. Average recoveries ranged from 60 to 102% with relative standard deviations of 2.2 and 15.6% for all type of feed samples except for tetracyclines, lincomycin, tylosin, ochratoxin A, and fumonisin (B1 and B2).

Abstract

Residues in animal feeds and foods of animal origin have been important safety issue concerning both human and animal health. A multiresidue method for determination of eight mycotoxins and ten antibiotics was developed and validated in animal feeds by using QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction followed by UHPLC-MS/MS. Optimisation of UHPLC-MS/MS parameters was performed to achieve good separation and resolution. The method was validated according to the European Commission Decision 2002/657/EC. Matrix matched calibration curves showed good r2 (≥0.995) values, and limit of quantification (LOQ) values varied between 1.2 and 5.2 μg kg−1. Average recoveries ranged from 60 to 102% with relative standard deviations of 2.2 and 15.6% for all type of feed samples except for tetracyclines, lincomycin, tylosin, ochratoxin A, and fumonisin (B1 and B2).

1 Introduction

Antibiotics are used regularly for the treatment of diseases in animals. Additionally, they are applied to animals for enhancing feed efficiency and growth rate (Greenless et al., 2012). Residues can occur in the edible tissues of the animals due to antibiotic usage in food producing animals. These residues can be toxic for humans and may develop allergic reactions or produce antibiotic-resistance pathogens in humans. Furthermore, they can even cause death (Gentili et al., 2005; Wang et al., 2006). Mycotoxins are small and toxic chemical products formed by different fungal species. These species can contaminate feedstuff with toxins during cultivation or after harvest and cause a toxic response when ingested by vertebrate species (Turner et al., 2009; Wang et al., 2015). Humans can be exposed to mycotoxins through the consumption of contaminated agricultural products or their metabolites in animal-derived products such as milk and egg. Additionally, exposure can also occur via dermal contact (Capriotti et al., 2012).

QuEChERS method consists of two steps: extraction with acetonitrile followed by liquid-liquid partitioning and purification with dispersive solid-phase extraction (d-SPE). The method was introduced as multiresidue analysis for pesticide residues in high moisture fruits and vegetables in 2002 (Rejczak and Tuzimski, 2015). However, applications of this method have been reported to additionally detect residues of antibiotics (Lopes et al., 2012; Robert et al., 2015) and mycotoxins (Dzuman et al., 2014; Qian et al., 2018) in feeds. UHPLC-MS/MS device has been extensively used for detection, identification, and quantification of multiclass antibiotic residues (Boscher et al., 2010; Zhang et al., 2013; Qian et al., 2019) or multiclass mycotoxin residues (Streit et al., 2013; Dzuman et al., 2014; Wang et al., 2015), individually. The objective of the present work was to develop a multi-residue UHPLC-MS/MS method using QuEChERS extraction to simultaneously detect and quantify antibiotics and mycotoxins in different types of animal feeds. The antibiotic and mycotoxin standards were selected according to their use in all food producing animal species (Ronquillo and Hernandez, 2017) and the degree of contamination in feed (Streit et al., 2013), respectively.

2 Materials and methods

2.1 Samples and chemicals

Twenty-seven different feed samples for poultry, cattle, and fish were collected from local feed markets in Antalya, Turkey and stored at 4 °C prior to analysis. All standards and chemicals were of high purity grade and supplied by Sigma-Aldrich (Steinheim, Germany). QuEChERS extraction-dispersive kits (Bond Elut) were supplied by Agilent (CA, USA). Individual stock solutions were prepared at 1,000 mg L−1 in methanol. A working mix from the standard solution of 5 mg L−1 was prepared by transferring an appropriate aliquot of each stock solution into methanol. All stocks and working solutions were stored at −18 °C in the dark.

2.2 QuEChERS extraction

The QuEChERS extraction method was performed according to AOAC Official Method (AOAC, 2007).

2.3 UHPLC-MS/MS

UHPLC-MS/MS analyses were performed with a triple quadrupole TSQ Quantum Access Max (Thermo Fisher Scientific, CA, USA) equipped with Accela UHPLC system (Thermo Fisher Scientific, CA, USA). Chromatographic separations were performed with a Hypersil GoldTM aQ column (100 × 2.1 mm, 1.9 µm, Thermo Fisher Scientific, CA, USA). The mobile phase A consisted of water with 0.5 mM oxalic acid and 1 mM ammonium formate, and the mobile phase B consisted of methanol with 0.2 mM oxalic acid. The gradient elution was: 90% A and 10% B for 2.5 min, then linearly changed to 0% A and 100% B in 1.5 min, and held constant for 2 min; then linearly changed 90% and 10% in 1 min, and finally held constant for 2 min. The total run time was 9 min. The flow rate of the mobile phase was 400 μL min−1, the column temperature was set at 40 °C, and the injection volume was 10 µL. Electrospray ionisation was performed in the positive ion mode (ESI+), and the mass spectrometer was operated in a multiple-reaction monitoring (MRM) mode. The ion spray voltage was set at 3.2 kV, capillary voltage at 35 V, and the tube lens voltage at 82 V. The capillary temperature and vaporiser temperature were set at 250 °C and 350 °C, respectively. Sheath and auxiliary gas flow rates were 40 and 10 units, respectively. Data acquisition was done with Xcalibur 2.1 software with Qual and Quanbrowser.

2.4 Method validation

The following parameters were evaluated during method validation within laboratory: selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy and precision (repeatability and reproducibility) (Commission Decision, 2002).

2.5 Statistical analysis

Significant differences among UHPLC parameters were evaluated with analysis of variance (ANOVA) by using SAS System Software (SAS Institue Inc., Cary, NC, USA). Duncan's Multiple Range test (P < 0.05) was used to compare significant differences observed in mean values of the results.

3 Results and discussion

3.1 UHPLC-MS/MS parameters

Hypersil GoldTM aQ column was selected to ensure good peak shape and resolution when using gradient elution with aqueous mobile phase (Konak et al., 2017). Therefore, UHPLC application was performed with reversed-phase chromatography by using Hypersil GoldTM aQ column in this study. In order to optimise the chromatographic conditions for antibiotics and mycotoxins, effects of different mobile phases (methanol and acetonitrile) and mobile phase additives (formic acid, acetic acid, and oxalic acid) on signal intensity were studied first.

In general, better separation in UHPLC was obtained with methanol than acetonitrile. In addition, the intensity of the target analytes was also higher in MS with methanol (P < 0.05). Different concentrations of formic acid (0.05 and 0.1%), acetic acid (0.1 and 0.2%), and oxalic acid (0.25 and 0.5 mM) were used to enhance ionisation of the analytes. The results showed that signal intensities of the analytes were higher at the concentrations of 0.05% for formic acid, 0.1% for acetic acid, and 0.5 mM for oxalic acid (P < 0.05). Furthermore, the highest signal intensity of the analytes was obtained by using oxalic acid instead of formic or acetic acid (P < 0.05). Moreover, optimum peak shapes and reproducible analyte signals were achieved by using oxalic acid with ammonium formate (1 mM) in methanol. The use of an acidic mobile phase with salt promoted positive ionisation and provided the stability of the analysis.

Different gradient elution programs were tested to provide the desired separation of the target analytes. Additionally, other parameters such as flow rate (400, 500, and 600 μL min−1), column temperature (20, 30, and 40 °C), and injection volume (10 and 20 µL) were also tested to get a fast separation and good peak shape. The best result was obtained when the flow rate was 400 μL min−1, column temperature was 40 °C, and injection volume was 10 µL (P < 0.05).

Mass spectrometry parameters were optimised to achieve the highest signal intensity for the target analytes (Fig. 1). Each standard solution was infused directly into the mass analyser in order to determine the precursor ion and two product ions of the target analytes in scan mode. The collision energy was optimised individually for each analyte. Retention time (RT) and MS/MS transitions for quantification and confirmation of the analytes are shown in Table 1.

Fig. 1.
Fig. 1.

UHPLC-MS/MS chromatograms for poultry (A), cattle (B), and fish (C) feed spiked with 50 μg kg−1

Citation: Acta Alimentaria AAlim 50, 1; 10.1556/066.2020.00159

Table 1.

Retention time (RT) and multiple reaction monitoring conditions for each compound

CompoundRT (min)Precursor ion (m/z)Quantifier ion (m/z)Qualifier ion (m/z)CE (eV)
Sulfamerazine1.15–2.0526515617220
Lincomycin2.30–3.30407126.235925
Sulfamethazine2.40–3.6327918615620
Tetracycline3.8044541042715
Oxytetracycline3.8446142644315
Sulfadimethoxine4.1731115624520
Chlortetracycline4.1847944446220
Sulfaquinoxaline4.23301156108.218
Aflatoxin G14.2832924321535
Aflatoxin B24.3431525928735
Aflatoxin B14.3831324126935
Tylosin4.50917174773.135
Erythromycin4.5473457655820
Aflatoxin G24.5433131328535
Fumonisin B14.61723353705.135
Ochratoxin A4.7642626127925
Fumonisin B24.7870633635435
Sterigmatocystin4.8532531028125

3.2 Method validation

Performance characteristics of the method were established by spiked blank feed samples selected from 27 samples. The linearity was evaluated by using six calibration points (0, 10, 25, 50, 75, and 100 μg kg−1) in the range of 0–100 μg kg−1. Peak area was selected as response and a coefficient of determination (r2) higher than 0.995 was obtained for all analytes. The low LOD and LOQ values of the developed method had the advantages of high selectivity, accuracy, and precision in simultaneous determination of the analytes.

Recovery experiments for the entire QuEChERS extraction and UHPLC-MS/MS procedure were carried out using blank matrix fortified at 10 and 100 μg kg−1 with six replicates for each fortification level. The obtained results showed that the extraction procedure was suitable for most of the analytes except for tetracycline, oxytetracycline, chlortetracycline, ochratoxin A, and fumonisin (B1 and B2). Likewise, lower recovery values were observed for tetracycline groups during acetonitrile extraction performed on animal feed. Researchers noticed that the high volume of acetonitrile employed caused co-precipitation of the analytes with the proteins (Aguilera-Luiz et al., 2013). On the other hand, another study showed that clean-up step after extraction led to lower recoveries for tetracyclines (Bourdat-Deschamps et al., 2014). However, a clean-up step was essential to obtain accurate results, because interfering compounds could be co-extracted with the target compounds during extraction and caused a reduction in the lifetime of the chromatographic column. Recovery, repeatability (intraday precision), and reproducibility (interday precision) values belonging to the analytes used in the validation procedure within the laboratory were calculated for each matrix and summarised in Tables 24. According to the results, the average recovery values (between 60 and 102%) were acceptable for most target compounds at two concentration levels, except for aflatoxin G2 with recovery of 58.3–59.2% in poultry feed. Additionally, RSD values were within the acceptable limit of 20%. However, low recovery values of lincomycin and tylosin were obtained, especially at the lowest concentration level. It could be due to high polarity of the analytes, which resulted in low extraction with acetonitrile. In addition, differences between the recovery values of some analytes in different matrices could be due to the matrix effect resulting from the matrix complexity.

Table 2.

Validation parameters of the method in poultry feed

Compound10 μg kg−1100 μg kg−1
Recovery (%)Intraday precision (%)Interday precision (%)Recovery (%)Intraday precisionInterday precision (%)
Tylosin12.9613.8113.7227.9019.6121.03
Lincomycin20.014.331.2823.9610.3811.72
Aflatoxin G259.155.925.3858.2914.9717.60
Aflatoxin B171.117.354.2175.4310.605.18
Aflatoxin G173.516.552.7064.0114.0914.03
Sulfadimethoxine73.803.352.1076.454.942.58
Sulfamethazine75.865.543.6889.895.405.14
Aflatoxin B276.495.211.5280.3314.566.22
Sulfaquinoxaline77.137.756.072.734.453.43
Erythromycin84.045.766.6269.4011.038.07
Sulfamerazine90.674.353.4778.546.694.15
Sterigmatocystin95.053.994.4282.954.994.36
Table 3.

Validation parameters of the method in cattle feed

Compound10 μg kg−1100 μg kg−1
Recovery (%)Intraday precision (%)Interday precision (%)Recovery (%)Intraday precision (%)Interday precision (%)
Tylosin13.8216.609.2320.7015.8817.97
Lincomycin14.9610.5513.2216.307.466.89
Aflatoxin G269.873.934.2691.5911.143.14
Aflatoxin B171.025.284.4272.457.2710.38
Aflatoxin G175.319.744.5773.508.856.33
Sulfadimethoxine75.603.432.3568.168.536.86
Sulfamethazine76.448.389.7469.432.241.61
Aflatoxin B277.887.268.2165.145.645.82
Sulfaquinoxaline78.399.085.6076.504.762.95
Erythromycin78.414.081.9079.077.186.50
Sulfamerazine84.344.012.7785.384.532.76
Sterigmatocystin89.275.296.0772.293.261.62
Table 4.

Validation parameters of the method in fish feed

Compound10 μg kg−1100 μg kg−1
Recovery (%)Intraday precision (%)Interday precision (%)Recovery (%)Intraday precision (%)Interday precision (%)
Lincomycin25.5711.2310.0845.017.252.99
Tylosin29.276.596.0943.0616.7318.41
Aflatoxin G162.1211.8111.8668.0410.837.40
Aflatoxin B266.819.4611.2569.6910.938.46
Sulfadimethoxine67.816.804.9965.794.232.84
Aflatoxin B170.0315.6010.6861.376.523.09
Sulfamethazine72.845.505.1286.018.5011.04
Sulfaquinoxaline74.183.923.1366.104.333.63
Sulfamerazine78.904.713.7092.557.008.74
Aflatoxin G279.476.695.3966.559.296.44
Erythromycin80.3510.2610.26101.5010.4113.11
Sterigmatocystin84.744.512.8768.765.412.36

4 Conclusions

A multiresidue method was developed for rapid and simultaneous determination of antibiotics and mycotoxins in animal feeds. Chromatographic separation and detection of the target analytes were achieved in a single run via UHPLC-MS/MS conditions. The developed method was applied to the analysis of 27 animal feed samples (9 for poultry, 8 for cattle, and 10 for fish) collected from local feed markets in Antalya, Turkey, and no positive results were observed in feed samples. Standard QuEChERS extraction method can be improved by applying different extraction solvents or acidifying agents to increase the extraction yield and also the number of extracted analytes. Recovery values can be increased with changing the polarity of the extraction solvents.

Acknowledgement

We thank the Scientific Research Projects Coordination Unit of Akdeniz University (Antalya, Turkey) for financial support (Grant number: FBA-2017-2718).

References

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    • Crossref
    • Search Google Scholar
    • Export Citation
  • AOAC. (2007). Official Methods of Analysis, 18th ed. Association of Official Analytical Chemists, Gaithersburg. Official Method 2007.01 Pesticide residues in foods by acetonitrile extraction and partitioning with magnesium sulfate.

    • Search Google Scholar
    • Export Citation
  • Boscher, A., Guignard, C., Pellet, T., Hoffmann, L., and Bohn, T. (2010). Development of a multi-class method for the quantification of veterinary drug residues in feedingstuffs by liquid chromatography-tandem mass spectrometry. Journal of Chromatography A, 1217: 63946404.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bourdat-Deschamps, M., Leang, S., Bernet, N., Daudin, J.J., and Nélieu, S. (2014). Multi-residue analysis of pharmaceuticals in aqueous environmental samples by online solid-phase extraction–ultra-high-performance liquid chromatography-tandem mass spectrometry: optimisation and matrix effects reduction by quick, easy, cheap, effective, rugged and safe extraction. Journal of Chromatography A, 1349: 1123.

    • Search Google Scholar
    • Export Citation
  • Capriotti, A.L., Caruso, G., Cavaliere, C., Foglia, P., Samperi, R., and Lagana, A. (2012). Multiclass mycotoxin analysis in food, environmental and biological matrices with chromatography/mass spectrometry. Mass Spectrometry Reviews, 31: 466503.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Commission Decision. (2002). 2002/657/EC of 12 August 2002 implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. OJ L 221/8–37.

    • Search Google Scholar
    • Export Citation
  • Dzuman, Z., Zachariasova, M., Lacina, O., Veprikova, Z., Slavikova, P., and Hajslova, J. (2014). A rugged high-throughput analytical approach for the determination and quantification of multiple mycotoxins in complex feed matrices. Talanta, 121: 263272.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gentili, A., Perret, D., and Marchese, S. (2005). Liquid chromatography-tandem mass spectrometry for performing confirmatory analysis of veterinary drugs in animal-food products. TrAC, 24: 704733.

    • Search Google Scholar
    • Export Citation
  • Greenless, K.J., Friedlander, L.G., and Boxall, A. (2012). Antibiotic residues in food and drinking water, and food safety regulations. In: Wang, J., MacNeil, J.D., and Kay, J.F. (Eds.), Chemical analysis of antibiotic residues in food, Wiley, New Jersey, pp. 111123.

    • Search Google Scholar
    • Export Citation
  • Konak, Ü.İ., Certel, M., Şik, B., and Tongur, T. (2017). Development of an analysis method for determination of sulfonamides and their five acetylated metabolites in baby foods by ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (Orbitrap-MS). Journal of Chromatography B, 1057: 8191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lopes, R.P., Passos, È.E.F., Filho, J.F.A., Vargas, E.A., Augusti, D.V., and Augusti, R. (2012). Development and validation of a method for the determination of sulfonamides in animal feed by modified QuEChERS and LC-MS/MS analysis. Food Control, 28: 192198.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rejczak, T. and Tuzimski, T. (2015). A review of recent developments and trends in the QuEChERS sample preparation approach. Open Chemistry, 13: 9801010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Robert, C., Gillard, N., Brasseur, P.Y., Ralet, N., Dubois, M., and Delahaut, P. (2015). Rapid multiresidue and multi-class screening for antibiotics and benzimidazoles in feed by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. Food Control, 50: 509515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ronquillo, M.G. and Hernandez, J. C. A. (2017). Antibiotic and synthetic growth promoters in animal diets: review of impact and analytical methods. Food Control, 72: 255267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, M., Yang, H., Li, Z., Liu, Y., Wang, J., Wu, H., Ji, X., and Xu, J. (2018). Detection of 13 mycotoxins in feed using modified QuEChERS with dispersive magnetic materials and UHPLC-MS/MS. Journal of Separation Science, 41: 756764.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, M., Zhang, X., Zhao, H., Ji, X., Li, X., Wang, J., Wu, H., Xu, J., and Li, Z. (2019). A high-throughput screening method for determination of multi-antibiotics in animal feed. Journal of Separation Science, 42: 29682976.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Streit, E., Schwab, C., Sulyok, M., Naehrer, K., Krska, R., and Schatzmayr, G. (2013). Multi-mycotoxin screening reveals the occurrence of 139 different secondary metabolites in feed and feed ingredients. Toxins, 5: 504523.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, N.W., Subrahmanyam, S., and Piletsky, S.A. (2009). Analytical methods for determination of mycotoxins: a review. Analytica Chimica Acta, 632: 168180.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, R.G., Su, X.O., Cheng, F.F., Wang, P.L., Fan, X., and Zhang, W. (2015). Determination of 26 mycotoxins in feedstuffs by multifunctional clean-up column and liquid chromatography-tandem mass spectrometry. Chinese Journal of Analytical Chemistry, 43: 264270.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, S., Zhang, H.Y., Wang, L., Duan, Z.J., and Kennedy, I. (2006). Analysis of sulphonamide residues in edible animal products: a review. Food Additives and Contaminants, 23: 362384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, G.J., Fang, B.H., Liu, Y.H., Wang, X.F., Xu, L.X., Zhang, Y.P., and He, L.M. (2013). Development of a multi-residue method for fast screening and confirmation of 20 prohibited veterinary drugs in feedstuffs by liquid chromatography tandem mass spectrometry. Journal of Chromatography B, 936: 1017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Aguilera-Luiz, M.M., Romero-González, R., Plaza-Bolaños, P., Vidal, J.L.M., and Frenich, A.G. (2013). Wide-scope analysis of veterinary drug and pesticide residues in animal feed by liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry. Analytical and Bioanalytical Chemistry, 405: 65436553.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • AOAC. (2007). Official Methods of Analysis, 18th ed. Association of Official Analytical Chemists, Gaithersburg. Official Method 2007.01 Pesticide residues in foods by acetonitrile extraction and partitioning with magnesium sulfate.

    • Search Google Scholar
    • Export Citation
  • Boscher, A., Guignard, C., Pellet, T., Hoffmann, L., and Bohn, T. (2010). Development of a multi-class method for the quantification of veterinary drug residues in feedingstuffs by liquid chromatography-tandem mass spectrometry. Journal of Chromatography A, 1217: 63946404.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bourdat-Deschamps, M., Leang, S., Bernet, N., Daudin, J.J., and Nélieu, S. (2014). Multi-residue analysis of pharmaceuticals in aqueous environmental samples by online solid-phase extraction–ultra-high-performance liquid chromatography-tandem mass spectrometry: optimisation and matrix effects reduction by quick, easy, cheap, effective, rugged and safe extraction. Journal of Chromatography A, 1349: 1123.

    • Search Google Scholar
    • Export Citation
  • Capriotti, A.L., Caruso, G., Cavaliere, C., Foglia, P., Samperi, R., and Lagana, A. (2012). Multiclass mycotoxin analysis in food, environmental and biological matrices with chromatography/mass spectrometry. Mass Spectrometry Reviews, 31: 466503.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Commission Decision. (2002). 2002/657/EC of 12 August 2002 implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results. OJ L 221/8–37.

    • Search Google Scholar
    • Export Citation
  • Dzuman, Z., Zachariasova, M., Lacina, O., Veprikova, Z., Slavikova, P., and Hajslova, J. (2014). A rugged high-throughput analytical approach for the determination and quantification of multiple mycotoxins in complex feed matrices. Talanta, 121: 263272.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gentili, A., Perret, D., and Marchese, S. (2005). Liquid chromatography-tandem mass spectrometry for performing confirmatory analysis of veterinary drugs in animal-food products. TrAC, 24: 704733.

    • Search Google Scholar
    • Export Citation
  • Greenless, K.J., Friedlander, L.G., and Boxall, A. (2012). Antibiotic residues in food and drinking water, and food safety regulations. In: Wang, J., MacNeil, J.D., and Kay, J.F. (Eds.), Chemical analysis of antibiotic residues in food, Wiley, New Jersey, pp. 111123.

    • Search Google Scholar
    • Export Citation
  • Konak, Ü.İ., Certel, M., Şik, B., and Tongur, T. (2017). Development of an analysis method for determination of sulfonamides and their five acetylated metabolites in baby foods by ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (Orbitrap-MS). Journal of Chromatography B, 1057: 8191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lopes, R.P., Passos, È.E.F., Filho, J.F.A., Vargas, E.A., Augusti, D.V., and Augusti, R. (2012). Development and validation of a method for the determination of sulfonamides in animal feed by modified QuEChERS and LC-MS/MS analysis. Food Control, 28: 192198.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rejczak, T. and Tuzimski, T. (2015). A review of recent developments and trends in the QuEChERS sample preparation approach. Open Chemistry, 13: 9801010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Robert, C., Gillard, N., Brasseur, P.Y., Ralet, N., Dubois, M., and Delahaut, P. (2015). Rapid multiresidue and multi-class screening for antibiotics and benzimidazoles in feed by ultra-high performance liquid chromatography coupled to tandem mass spectrometry. Food Control, 50: 509515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ronquillo, M.G. and Hernandez, J. C. A. (2017). Antibiotic and synthetic growth promoters in animal diets: review of impact and analytical methods. Food Control, 72: 255267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, M., Yang, H., Li, Z., Liu, Y., Wang, J., Wu, H., Ji, X., and Xu, J. (2018). Detection of 13 mycotoxins in feed using modified QuEChERS with dispersive magnetic materials and UHPLC-MS/MS. Journal of Separation Science, 41: 756764.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, M., Zhang, X., Zhao, H., Ji, X., Li, X., Wang, J., Wu, H., Xu, J., and Li, Z. (2019). A high-throughput screening method for determination of multi-antibiotics in animal feed. Journal of Separation Science, 42: 29682976.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Streit, E., Schwab, C., Sulyok, M., Naehrer, K., Krska, R., and Schatzmayr, G. (2013). Multi-mycotoxin screening reveals the occurrence of 139 different secondary metabolites in feed and feed ingredients. Toxins, 5: 504523.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, N.W., Subrahmanyam, S., and Piletsky, S.A. (2009). Analytical methods for determination of mycotoxins: a review. Analytica Chimica Acta, 632: 168180.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, R.G., Su, X.O., Cheng, F.F., Wang, P.L., Fan, X., and Zhang, W. (2015). Determination of 26 mycotoxins in feedstuffs by multifunctional clean-up column and liquid chromatography-tandem mass spectrometry. Chinese Journal of Analytical Chemistry, 43: 264270.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, S., Zhang, H.Y., Wang, L., Duan, Z.J., and Kennedy, I. (2006). Analysis of sulphonamide residues in edible animal products: a review. Food Additives and Contaminants, 23: 362384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, G.J., Fang, B.H., Liu, Y.H., Wang, X.F., Xu, L.X., Zhang, Y.P., and He, L.M. (2013). Development of a multi-residue method for fast screening and confirmation of 20 prohibited veterinary drugs in feedstuffs by liquid chromatography tandem mass spectrometry. Journal of Chromatography B, 936: 1017.

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The author instruction is available in PDF.
Please, download the file from HERE.

Senior editors

Editor(s)-in-Chief: András Salgó

Co-ordinating Editor(s) Marianna Tóth-Markus

Co-editor(s): A. Halász

       Editorial Board

  • L. Abrankó (Szent István University, Gödöllő, Hungary)
  • D. Bánáti (University of Szeged, Szeged, Hungary)
  • J. Baranyi (Institute of Food Research, Norwich, UK)
  • I. Bata-Vidács (Agro-Environmental Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • J. Beczner (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • F. Békés (FBFD PTY LTD, Sydney, NSW Australia)
  • Gy. Biró (National Institute for Food and Nutrition Science, Budapest, Hungary)
  • A. Blázovics (Semmelweis University, Budapest, Hungary)
  • F. Capozzi (University of Bologna, Bologna, Italy)
  • M. Carcea (Research Centre for Food and Nutrition, Council for Agricultural Research and Economics Rome, Italy)
  • Zs. Cserhalmi (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • M. Dalla Rosa (University of Bologna, Bologna, Italy)
  • I. Dalmadi (Szent István University, Budapest, Hungary)
  • K. Demnerova (University of Chemistry and Technology, Prague, Czech Republic)
  • M. Dobozi King (Texas A&M University, Texas, USA)
  • Muying Du (Southwest University in Chongqing, Chongqing, China)
  • S. N. El (Ege University, Izmir, Turkey)
  • S. B. Engelsen (University of Copenhagen, Copenhagen, Denmark)
  • E. Gelencsér (Food Science Research Institute, National Agricultural Research and Innovation Centre, Budapest, Hungary)
  • V. M. Gómez-López (Universidad Católica San Antonio de Murcia, Murcia, Spain)
  • J. Hardi (University of Osijek, Osijek, Croatia)
  • K. Héberger (Research Centre for Natural Sciences, ELKH, Budapest, Hungary)
  • N. Ilić (University of Novi Sad, Novi Sad, Serbia)
  • D. Knorr (Technische Universität Berlin, Berlin, Germany)
  • H. Köksel (Hacettepe University, Ankara, Turkey)
  • K. Liburdi (Tuscia University, Viterbo, Italy)
  • M. Lindhauer (Max Rubner Institute, Detmold, Germany)
  • M.-T. Liong (Universiti Sains Malaysia, Penang, Malaysia)
  • M. Manley (Stellenbosch University, Stellenbosch, South Africa)
  • M. Mézes (Szent István University, Gödöllő, Hungary)
  • Á. Németh (Budapest University of Technology and Economics, Budapest, Hungary)
  • P. Ng (Michigan State University,  Michigan, USA)
  • Q. D. Nguyen (Szent István University, Budapest, Hungary)
  • L. Nyström (ETH Zürich, Switzerland)
  • L. Perez (University of Cordoba, Cordoba, Spain)
  • V. Piironen (University of Helsinki, Finland)
  • A. Pino (University of Catania, Catania, Italy)
  • M. Rychtera (University of Chemistry and Technology, Prague, Czech Republic)
  • K. Scherf (Technical University, Munich, Germany)
  • R. Schönlechner (University of Natural Resources and Life Sciences, Vienna, Austria)
  • A. Sharma (Department of Atomic Energy, Delhi, India)
  • A. Szarka (Budapest University of Technology and Economics, Budapest, Hungary)
  • M. Szeitzné Szabó (National Food Chain Safety Office, Budapest, Hungary)
  • S. Tömösközi (Budapest University of Technology and Economics, Budapest, Hungary)
  • L. Varga (University of West Hungary, Mosonmagyaróvár, Hungary)
  • R. Venskutonis (Kaunas University of Technology, Kaunas, Lithuania)
  • B. Wróblewska (Institute of Animal Reproduction and Food Research, Polish Academy of Sciences Olsztyn, Poland)

 

Acta Alimentaria
E-mail: Acta.Alimentaria@uni-mate.hu

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2020
 
Total Cites
768
WoS
Journal
Impact Factor
0,650
Rank by
Nutrition & Dietetics 79/89 (Q4)
Impact Factor
Food Science & Technology 130/144 (Q4)
Impact Factor
0,575
without
Journal Self Cites
5 Year
0,899
Impact Factor
Journal
0,17
Citation Indicator
 
Rank by Journal
Nutrition & Dietetics 88/103 (Q4)
Citation Indicator
Food Science & Technology 142/160 (Q4)
Citable
59
Items
Total
58
Articles
Total
1
Reviews
Scimago
28
H-index
Scimago
0,237
Journal Rank
Scimago
Food Science Q3
Quartile Score
 
Scopus
248/238=1,0
Scite Score
 
Scopus
Food Science 216/310 (Q3)
Scite Score Rank
 
Scopus
0,349
SNIP
 
Days from
100
sumbission
 
to acceptance
 
Days from
143
acceptance
 
to publication
 
Acceptance
16%
Rate
2019  
Total Cites
WoS
522
Impact Factor 0,458
Impact Factor
without
Journal Self Cites
0,433
5 Year
Impact Factor
0,503
Immediacy
Index
0,100
Citable
Items
60
Total
Articles
59
Total
Reviews
1
Cited
Half-Life
7,8
Citing
Half-Life
9,8
Eigenfactor
Score
0,00034
Article Influence
Score
0,077
% Articles
in
Citable Items
98,33
Normalized
Eigenfactor
0,04267
Average
IF
Percentile
7,429
Scimago
H-index
27
Scimago
Journal Rank
0,212
Scopus
Scite Score
220/247=0,9
Scopus
Scite Score Rank
Food Science 215/299 (Q3)
Scopus
SNIP
0,275
Acceptance
Rate
15%

 

Acta Alimentaria
Publication Model Hybrid
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Subscription fee 2021 Online subsscription: 736 EUR / 920 USD
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Subscription fee 2022 Online subsscription: 754 EUR / 944 USD
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Acta Alimentaria
Language English
Size B5
Year of
Foundation
1972
Publication
Programme
2021 Volume 50
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0139-3006 (Print)
ISSN 1588-2535 (Online)

 

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Abstract Views Full Text Views PDF Downloads
Apr 2021 0 55 26
May 2021 0 52 66
Jun 2021 0 49 62
Jul 2021 0 29 35
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Sep 2021 0 44 38
Oct 2021 0 0 0