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Cabbage or ‘pesticide’ on the platter? Chemical analysis reveals multiple and excessive residues in African vegetable markets

Cabbage or ‘pesticide’ on the platter? Chemical analysis reveals multiple and excessive residues... Overuse of pesticides in vegetables and related fresh products raises serious public health concerns. However, the recognition and assessment of the magnitude of public health risk remains a low priority in low income African communities. Brassicas are a cosmopolitan crop in African horticulture, and equally so, is the major economic pest, the diamondback moth, Plutella xylostella (L.). In consequence, insecticide use on P. xylostella in brassica production systems presents persistent pesticide overuse on produce directly destined for public consumption. Using the quick easy cheap effective rugged and safe (QuEChERS) multi-residue analysis method, followed by gas chromatography- mass spectrometry (GC-MS) or liquid chromatography-tandem mass spectrometry (LC-MS/MS), we investigated the occurrence and magnitude of pesticide residues at three vegetable market levels (farmgates, vendors and supermarkets) in Botswana. We detected pesticide residues in 74.1% of the samples while 33.4% had multiple compounds. Farmgates recorded higher pesticide residues than other markets. We multi-detected 10 low-highly hazardous pesticides [World Health Organisation (WHO)] (classes 1B & II), that included Organophosphates, Pyrethroids, Neonicotinoids and Carbamates. Fifty percent of the detected pesticides from farms and supermarkets had residue quantities exceeding the Codex Maximum Residue Limit thresholds; although estimated daily per capita consumption was lower than the WHO Average Daily Intake (ADI) and Acute Reference Doses (ARfDs). These results indicate presence of multiple and excessive pesticide residues in routinely consumed vegetables on the markets, and points to an imminent public health hazard. Urgent attention is needed to develop and enforce effective policies and regulations on pesticide use practices and investment in non-chemical pest management alternatives. Keywords: Pesticide residues, Brassica, Public health risk, Codex Alimentarius Maximum Residue Limits, Diamondback moth Introduction (Newton et al. 2011) and pesticide overuse (Machekano Sustainable agriculture under rapidly changing climate et al. 2017, 2019) in an effort to increase crop productiv- (IPCC 2014) and increasing human population (FAO ity and profitability. This malpractice has resulted in 2009) remains a big challenge in Africa. However, it production of pesticide laden agricultural produce, with remains critical that food and nutrition challenges be ad- negative implications on food safety and public health dressed using sustainable approaches. For the horticul- (Donkor et al. 2016). While human exposure to pesticide tural industry, changes in temperature associated with residues can be through different modes (Semple 2005), climate change have created increased pest pressure contaminated food remains the main exposure route (about five orders higher) (Nougadère et al. 2012; Szpyrka et al. 2015, reviewed in Donkor et al. 2016; * Correspondence: nyamukondiwac@biust.ac.bw Mebdoua et al. 2017). In brassicas, pesticide overuse is Department of Biological Sciences and Biotechnology, Botswana International University of Science and Technology, Private Bag 16, Palapye, mainly associated with the high and stigmatic pesticide Botswana resistance history of the diamondback moth, Plutella Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 2 of 13 xylostella (L.) (Lepidoptera: Plutellidae) (Furlong et al. of many horticultural farmers in most African countries 2013; Machekano et al. 2017). This is further aggravated is skewed towards increasing quantity and not safety of by vegetables being consumed fresh as salads or partially the produce (Leroy et al. 2015). In addition, the technical processed e.g. cauliflower and cabbages (Mwanja et al. sophistication of residue analysis makes the regulation, 2017) with no rigorous cooking process that could po- enforcement and compliance with the WHO/FAO Max- tentially degrade pesticide compounds. In addition, bras- imum Residue Limits (MRLs) under the Codex Alimen- sicas have been reported to capture more chemical tarius standards a big challenge at each level of the value content during direct spray and drift because of their chain to most developing countries (Amoah et al. 2006; large leaf surface area (Alla et al. 2015). Damallas and Eleftherohorinos 2011; Mwanja et al. With the growing global health concerns on meat and 2017). related products, there is an increasing demand for vege- Studies carried out to date were mostly focused on oc- tables because of their health benefits and affordability cupational exposure (Magauzi et al. 2011;Hinsonetal. (see FAO 2004; Donkor et al. 2016). This has made bras- 2017), neglecting the vulnerable passive exposure to con- sica crops gain popularity in developing countries sumers (Repetto and Baliga 1996;Semple 2005)through (Madisa et al. 2010; Mazhawidza and Mvumi 2017), consumption of chemical residues on consumer-ready making them a significant daily dietary component due ‘fresh’ vegetable products procured from the markets to their richness in vitamins, minerals, fibre and antioxi- (Nougadère et al. 2012). Generally, quantifying pesticide dants (FAO 2004). Simultaneously however, brassicas exposure is currently the quickest way of assessing and have become a major source of public health risk due to quantifying the risk of public exposure to pesticides in high incidence of pesticides residues (Szpyrka et al. Africa (Semple 2005). Direct acute or chronic health ef- 2015; Donkor et al. 2016; Jallow et al. 2017) associated fects are difficult to measure due to chemical interactive with pesticide abuse (Ngowi et al. 2007; Machekano et or dose-addition effects caused by continuous consump- al. 2019). In the drive to sustain food production in Af- tion of multiple chemicals in different products that then rica, the use of insecticides in horticultural production mar diagnostic accuracy especially in ill-equipped devel- systems is indispensable (Bhanti et al. 2004; Obopile et oping countries’ laboratories (Ngowi et al. 2007;Boobiset al. 2008; Williamson et al. 2008; Madisa et al. 2010). In al. 2008;Machariaetal. 2015). In addition, there are syn- Botswana for example, farmers are increasing the use of ergistic complexities associated with multiple pesticide synthetic pesticides (Obopile et al. 2008; Machekano et toxicity, mycotoxicity and interaction with existing al. 2019) to sustain horticultural yields and cope with in- chronic illnesses (e.g. HIV and AIDS) that further obfus- creased demand for brassicas caused by increasing rural cates recognition and quantification of pesticide exposure to urban migration (Madisa et al. 2010). risks (Repetto and Baliga 1996; Mostafalou and Abdollahi In a survey recently conducted in Botswana, P. xylos- 2013). Therefore, methodologies to assess public health tella accounted for the need to apply pesticides on risks from exposure to multiple residues simultaneously, brassica crops in 71.6% of the cases (Machekano et al. including their possible chemical interactive effects within 2019). Forty one moderate to highly hazardous insecti- the human body are currently lacking, especially under cide active ingredients (see WHO, 2009) targeted on P. African contexts (Ngowi et al. 2007;Boobiset al. 2008; xylostella control alone were recorded; some applied as Macharia et al. 2015). Since policy enforcement (Damallas pesticide ‘cocktails’ of more than two pesticides to re- and Eleftherohorinos 2011) and public awareness may be spond to P. xylostella high pest pressure (Machekano et the most effective way to minimize the problem through al. 2019). High residues may be exacerbated by the appli- enforcing farmers’ behavioural change (Williamson et al., cation of these pesticides too close to harvesting time 2008), there is urgent need to generate convincing evi- without due consideration for the recommended with- dence for policymakers on the nature and magnitude of drawal periods because of market competition and the the problem and the associated potential health need to protect a clean supply reputation. Farmers may threats (e.g. cholinergic syndrome (Fulco et al. 2000), sell their brassica crops before recommended withdrawal different types of cancers, cardiovascular diseases periods; a practice that then exposes the unsuspecting (CVDs), birth defects, reproductive disorders and Par- public to pesticide-contaminated food. Moreover, in de- kinson’s disease (Mostafalou and Abdollahi 2013)). veloping countries, consumers purchase directly from Chemical analysis of fresh produce on the market for farm-gates, apart from vendors and retailers (Madisa et detection and quantification of pesticide residues al. 2010); all devoid of means to detect and quantify therefore, brings warning evidence that can be used pesticide residues on the produce. The indiscriminate as early warning system by policymakers to take mea- application of different types and quantities of pesticides sures that will protect public health. on vegetables calls for an urgent need for evaluation of In Botswana, and indeed other developing countries, the magnitude of the public health risk. The main focus pesticide related health issues constitute a serious threat to Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 3 of 13 development (Ngowi et al. 2007;Macharia etal. 2015; were skipped (depending on the size of the field) and the Jallow et al. 2017), yet, data on public health risk assess- process was repeated until a compound sample of nine ment, detection and quantification of potentially harmful cabbages was obtained. Sampled plot sizes ranged pesticide residues in vegetables or related products remain roughly from 0.3–0.6 ha typical of small scale farmers’ scarce. Cognizant of the uncontrolled injudicious use of acreage in Botswana. The farm field sampling was based pesticides against P. xylostella (see details in Machekano et on the notion that when consumers are purchasing from al. 2019) and using cabbages as a case study, we farms, the cabbages are immediately harvested from the hypothesize that chemical residues are present on field following payment. To avoid field edge bias, the consumer-ready-cabbages at all three types of dominant first three rows on either side of the field and the first domestic vegetable markets in Botswana. We further hy- 10 cabbage heads within a row were discarded. pothesise that the quantities of pesticide residues may ex- From each of the compound sample of whole cabbage ceed the permissible Codex Alimentarius MRLs. The heads, 4 equidistant slices were cut from the surface to objective of this study was therefore to detect, characterize the core of each cabbage head and pulled out (synonym- and quantify potential pesticide residues in fresh African ous of ‘cake slice’) using a laboratory knife. These were cabbage markets using Botswana as a sampling point. This further sliced into small pieces and mixed in 45 × 35 cm information is critical in advising policy-makers, pesticide laboratory trays to obtain a sliced composite sample (see regulators, consumers and farmers alike on the potential Mwanja et al. 2017). A 1 kg subsample was then mea- health risks associated with exposure to high levels of toxic sured out using a laboratory balance (RADWAG Wagi chemical residues in fresh produce and the urgent need Elektronikczne, Model PS 4500.R2, Poland) and placed for respective remedial action. into sterile 44 × 30 cm ziploc bags which were immedi- ately sealed and placed on ice in a laboratory cooler box Methods maintained at about 0 ± 1 °C. The trays were washed and Sample collection and preparation lined with new plastic (> 100 μm thick) before preparing Cabbage samples were collected from three high brassica the next sample to avoid contamination. production districts of Botswana vis Central; North East and South East districts (Table 1). All samples were pro- Sample preparation cured under normal consumer-ready-purchasing-conditions Samples were prepared using the quick easy cheap ef- to take into account realistic consumer (public) expos- fective rugged and safe QuEChERS method (Anasta- ure conditions and to reduce bias (Nougadère et al. 2012; siades et al. 2003). Briefly, samples were processed using Mwanja et al. 2017). Sampling was done from a three-tier Foss food cutter and homogenized (Ultra Turrax T25). market system (vendors, supermarkets and farms), to cater Thereafter 10 g of each homogenate was placed in 50 for all types of markets used by vegetable consumers under mL polypropylene tubes with screw caps. The extrac- an African context (see Osei-Fosu et al. 2017). At each sam- tion solvent acetonitrile was then added to each sub- pling point, peripheral data such as the Global Positioning sample and shaken for 1 min until uniform. Buffering System (GPS) coordinates, the name of the sampling point citrate salts and sodium chloride (pH 5–5.5), were also (vendor, supermarket or farm) as well as the dates when the added and the mixture shaken intensively for 1 min sampled consignment was delivered to the retailer (in the followed by centrifugation at 5000 rpm to allow for case of vendors or supermarkets) were recorded. Sampling phase separation. The organic phase was thereafter was done following standardized random sampling methods cleaned-up using the dispersive solid phase extraction (Fernandez-Alba 2005; Amoah et al. 2006;Bempahetal. (d-SPE) method. Briefly, 1 ml of the supernatant of the 2011; Osei-Fosu et al. 2017;Mwanjaet al. 2017). subsample was transferred into a new 2 ml centrifuge Most vendors kept their stock on tables or at the back tube containing primary and secondary amine (PSA) of trucks/vans. After normal purchasing process, nine and magnesium sulphate. PSA was added for the re- whole cabbage heads were randomly picked from a ven- moval of sugar, fatty acids and organic acids, while dor’s table, truck or van. The process was repeated three magnesium sulphate was used as a drying agent; to re- times in each district (3 vendors) to yield three vendor move any residual water see also (Paya et al. 2007). Fi- replicates for each district (Table 1). The same process nally the mixtures were shaken followed by was repeated for the supermarkets (Fernandez-Alba centrifugation to produce clear supernatant for GC-MS 2005; Amoah et al. 2006). At farm level, only farm-fields and LC-MS/MS analysis as required (Table 2). that had physiologically mature cabbages that were already being harvested for marketing were sampled. Stock and standards solutions preparations Three whole cabbage heads were randomly picked from All solvents, namely acetonitrile, methanol and water each cabbage row by picking every 10th cabbage within were of HPLC grade. A single composite working stand- a row from a random starting point. Three or five lines ard solution at 100 μg/mL was prepared in methanol Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 4 of 13 Table 1 Summary details of the sampling sites, including the type of sampling market, district, village and geographic positioning of the site Type of market Sample code District Village/Mall/Town GPS Coordinates Supermarket NEsup North East Sunshine Plaza mall S21. 11,115, E027. 32,117 Supermarket NEsup North East Nzano Centre Mall S21. 10,697, E027. 30,700 Supermarket NEsup North East Sunshine Plaza mall S21. 11,115, E027. 32,117 Vendor NEven North east Francistown Block 6 S21. 12,328, E027. 32,177 Vendor NEven North East Francistown bus rank S21. 10,296, E027.30688 Vendor NEven North East Gallo Mall S21. 10,391, E027. 30,883 Farm NEfar North East Ditladi S21. 26,013, E027. 28,170 Farm NEfar North East Gulushabe S21. 28,718, E027. 31,533 Farm NEfar North East Gulushabe S21. 26,013, E027. 32,100 Supermarket Csup Central Palapye S22. 33,336, E027. 07718 Supermarket Csup Central Boiteko junction mall S22. 25,261, E026. 44,709 Supermarket Csup Central Mahalapye S23. 06551, E026. 50,014 Vendor Cven Central Serorome ward S22. 32,644, E027. 06175 Vendor Cven Central Mahalapye Bus rank S23. 06672, E026. 49,973 Vendor Cven Central Shoshong S23. 01806, E026. 30,813 Farm Cfar Central Serowe S22. 26,013, E026. 44,709 Farm Cfar Central Palapye S22. 34,965, E027. 05266 Farm Cfar Central Modiane village S23. 06628, E026. 43,079 Supermarket SEsup South East Pakhalane S24. 33,836, E025. 58,572 Supermarket SEsup South East Rail Park Mall S24. 39,582, E025. 54,124 Supermarket SEsup South East Riverwalk Mall S24. 40,548, E025. 56,036 Vendor SEven South East Gaborone bus rank S24. 39,516, E025. 54,137 Vendor SEven South East Gaborone West S24. 39,575, E025. 54,047 Vendor SEven South East Tlogatloga ward S24. 39,089, E025. 53,259 Farm SEfar South East Glen Valley S24. 36,864, E025. 58,149 Farm SEfar South East Glen Valley S24. 36,500, E025. 58,293 Farm SEfar South East Glen Valley S24. 36,256, E025. 58,574 NEven North East District vendor, NEsup North East district supermarket, NEfar North East district farm, Cven Central district vendor, Csup Central district supermarket, Cfar Central district farm, SEsup South East district supermarket, SEven South East district vendor, SEfar South East district farm; numbers 1, 2, 3 represent replications and stored at − 20 °C. LC-MS/MS the stock solutions LC-MS/MS analysis − 3 − 4 (1 × 10 g/mL or 5 × 10 g/mL) of each of the single LC-MS/MS was run using the South African Bureau of compounds were prepared in acetonitrile. Stock work di- Standards (SABS) inhouse method no. 029/2006 vali- − 5 lution mixtures (1 × 10 g/mL) were prepared in aceto- dated for the determination of pesticides in fruits and nitrile and kept for the preparation of the work vegetables at concentration range of 0.01–1.0 mg/kg on dilutions. The following work dilutions were prepared: LM-MS/MS with a limit of quantitation (LOQ) of 0.01 − 6 − 6 − 7 − 7 − 7 − 8 (2 × 10 ,1×10 ,5×10 ,3×10 ,1×10 ,5×10 , mg/kg. Summary of the validation data and compounds − 8 − 8 − 8 3×10 ,2×10 and 1 × 10 g/mL) in acetonitrile. For included are provided (Additional file 1: Table S1). − 3 − 4 GC-MS, stock solutions (1 × 10 g/mL or 5 × 10 g/ 100 μL of supernatant was injected into a Kinetex col- mL) of each of the single compounds were prepared in umn (Phenomenex, United States) of particle sizes 150 − 5 toluene. Work dilution mixtures of 5 × 10 g/mL were mm × 4.6 mm. The mobile phase consisted of a mixture prepared in toluene and kept for the preparation of the of high-purity water with 0.1% formic acid (A) and work dilutions. The following work dilutions were pre- acetonitrile (B). In order to separate the ions, a gradient − 6 − 6 − 7 − 7 − 7 pared: (2 × 10 ,1×10 ,5×10 ,3×10 ,1×10 , programme started with 90% A and 10% B for 2 min, − 8 − 8 − 8 − 8 5×10 ,3×10 ,2×10 and 1 × 10 g/mL) in thereafter, there was a gradual change in mobile phase hexane. which took 26 min until 5% A and 95% B was reached. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 5 of 13 Table 2 Sample analysis techniques (GC-MS and LC-MS/MS) Data analysis and limit of quantitation (LOQ) used to detect and quantify Mass Hunter® quantitation software (Agilent Technolo- different types of pesticides in our experiments gies, United States) was used for quantification. Data Pesticide Pesticide group Technique used (LOQ ) (mg/kg) were analysed in STATISTICA 13.3 (TIBCO Software Chlorpyriphos Organophosphate GC-MS 0.01 Inc. USA). Data that did not meet linear model assump- tions of constant variance and normal errors were ana- Triazophos Organophosphate 0.01 lysed using generalized linear models (GLZ) and Cypermethrin Pyrethroid 0.02 Kruskal-Wallis post-hoc tests were used to separate sta- Fenvarelate Pyrethroid 0.02 tistically different medians. For multi-detected individual Chlorfenapyr Pyrole 0.01 pesticides, the data satisfied the ANOVA assumptions, Acephate Organophosphate LC-MS/MS 0.01 therefore, one-way ANOVA was used. Tukey-Kramers Methamidophos Organophosphate 0.01 HSD test was used to separate statistically significant means. Linear regression analysis using 2D scatterplots Methomyl Carbamate 0.01 was done in STATISTICA to assess the correlation be- Chorantraniliprole Diamide 0.01 tween detected quantities and number of days after de- Imidacloprid Neonicotinoids 0.01 livery. To measure the magnitude of public exposure, we LOQ Limit of quantitation calculated per capita residue consumption following Mwanja et al. (2017) only for the six detected highly haz- Thereafter, the mobile phase was kept constant at 5.0% ardous pesticides that exceeded the Codex MRLs, and A and 95% B for 32 min, and finally, gradually increased compared the figures to the recommended acceptable back to 90% A and 10% B which took 38 min. A tandem daily intake (ADI) and the acute reference doses mass spectrometer (Agilent 6460, Germany) was used (ARfD) for the individual pesticides based on recom- for detection using Mass Hunter® quantitation software mended per capita consumption of leafy vegetables in (Agilent Technologies, United States). Africa of 0.7 g/person/annum (WHO/GEMS/FOODS 2006) and 60kg body weight (BW) as in Alla et al. (2015). Gas chromatography mass spectrometry (GC-MS) The GC-MS was run using the South African Bureau of Results Standards (SABS) in-house method no. 029/2006 vali- Detections, identification and quantification dated for the determination of organochlorines (OCs), Retention time (RT) and mass-to-charge ratio (m/z) organophosphates (OPs) and synthetic pyrethroids in were used to identify positive peaks for detected com- fruits and vegetables at concentration range of 0.01– pounds in both GC-MS and LC-MS/MS analyses (Fig. 1). 0.05 mg/kg by GC-ECD and FPD with a limit of quanti- Figure 1a shows the LC-MS/MS multiple chromato- tation (LOQ) of 0.01 mg/kg for both OCs and OPs and grams for a sample from a vendor based at Shoshong 0.02 mg/kg for synthetic pyrethroids. Summary of the (see details in Table 1). The graph shows positive peaks validation data and compounds included are provided for methamidophos (RT = 4.161 min, concentration = (Additional file 1: Table S2). The analysis was per- 0.0262 mg/kg), methomyl (RT = 10.163 min, concentra- formed with an Agilent technologies 6890 gas chro- tion = 0.0140 mg/kg), chlorantraniliprole (RT = 20.282 matography equipped with an inert mass selective min, concentration = 0.0350 mg/kg). All the other de- detector (MSD), model 5975 (Agilent Technologies, tected LC-MS/MS amenable compounds were identified USA). The system was operated in a splitless mode. in the same manner. The GC-MS chromatograms for a The GC column was an Agilent J &W GC column single detection for a sample from a supermarket in (model: Agilent 19091S-433, HP-5MS) of length 30 m, Gaborone are shown in Fig. 1b exemplified by chlorfena- internal diameter of 0.250 mm and film thickness of pyr (RT = 20.269 min, concentration = 0.5721 mg/kg). 0.25 μm. The column was kept at a constant flow rate Pesticide residues were detected in 74.1% of the tested of 0.9 ml/min. Helium was used as the carrier gas. samples at all market levels, i.e. farms, vendors and su- The inlet and detector temperatures were maintained permarkets combined (Fig. 2a) across all the sampled at 250 °C and 325 °C respectively. The temperature districts (Fig. 2b). Samples from the farms showed program started at an initial temperature of 80 °C for higher KW-H = 10.255, (p = 0.0059) detected quan- (2, 34) 1 min, followed by a gradient programme to an elu- tities of pesticide residues than samples from both su- tion temperature of 325 °C for a total runtime of 38 permarkets and vendors (Fig. 2a). However, there were min. The validation data for both GC-MS and no significant differences KW-H = 2.8411, (p = (2, 34) LC-MS/MS are presented in electronic supplementary 0.2416) in the quantity of pesticides detected across all materal, Additional file: 1. sampled districts (Fig. 2b). Generally, the number of Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 6 of 13 Fig. 1 Chromatograms for (a) LC-MS/MS showing peaks for 3 multi-detected pesticide residues for a sample from a vendor at Shoshong shopping centre in Central District (S23. 01806, E026. 30,813) (methamidophos: RT = 4.161 min, concentration = 0.0262 mg/kg; methomyl: RT = 10.163, concentration = 0.0140 mg/kg and chlorantraniliprole: RT = 20.282 min, concentration = 0.0350 mg/kg). b GC-MS showing peaks residues for chlorfenapyr (RT = 20.269 min, concentration = 0.5271 mg/kg) from a sample from a supermarket in South East District (S24.39582, E025. 54,124). The insertion in 1b shows the extracted and zoomed GC-MS peaks and mass-to-charge ratios for Chlorfenapyr. (Batch 3876_7A14.d and 3876a07D represents laboratory sample coding. RT = Retention time in minutes) a b 3.5 3.5 Median Median 25%-75% 25%-75% Non-Outlier Range 3.0 3.0 Non-Outlier Range Outliers Outliers Extremes Extremes 2.5 2.5 2.0 2.0 1.5 1.5 a a 1.0 1.0 ab 0.5 0.5 0.0 0.0 Farm s Superm arkets Vendors Central North East South East Type of market District Fig. 2 Median ± 95%CLs of the detection of pesticide residues across (a)markets and(b) districts Kuskall-Wallis post-hoc tests were used to separate heterogenous groups at P = 0.05. Group medians with the same letter(s) are not statistically different Detected Quantity (mg/kg) Detected Quantity mg/kg Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 7 of 13 samples with pesticide residues (% proportion of detec- Central district only. For individual pesticides, overall tions per type of market) were higher in the farms and proportion of detections was higher for methamidophos, supermarkets compared to vendors. followed by cypermethrin; methomyl and chlorantranili- A total of ten different active ingredient residues were prole (see Fig. 3a). Most of the samples included only multi-detected from 27 cabbage samples including four one detectable pesticide, while at least two detected pes- organophosphates (methamidophos, triazophos, ace- ticides were found in 33.4% of the samples (Fig. 3b). The phate and chlorpyriphos), two pyrethroids (cypermethrin detected quantity of pesticides were negatively correlated and fenvarelate), one carbamate (methomyl), one pyrrole (r = − 0.269, p < 0.001) to the length of time (number of (chorfenapyr), one neonicotinoid (imidacloprid) and one days) between the vendor or supermarket’s date of re- diamide (chlorantraniliprole) (see Table 3). Methamido- ceiving supply and the time of sampling. phos, triazophos and methomyl fall in hazard class 1B, classified as highly hazardous (WHO 2009). Methomyl Risk assessment and methamidophos were multi-detected across all types A total of 50% (17/34) of total detections, dominated by of markets in all sampled districts while triazophos was organophosphates were above the Codex Alimentarius detected only from vendors in one district (North East) MRLs. Detected residue quantities for methomyl were (Table 3). Six of the detected pesticides; cypermethrin, significantly higher (p < 0.001) on samples from the fenvarelate, acephate, chlorpyriphos, chlorfenapyr and farms (0.67 mg/kg) compared to supermarkets (0.045 imidacloprid belong to WHO toxicity class II, described mg/kg) and vendors (0.01 mg/kg). On the other hand, as moderately hazardous (WHO 2009) (Table 3). The residues from supermarkets were significantly higher (p ‘unlikely hazardous’ (WHO 2009) chlorantraniliprole < 0.001) than samples from vendors. Methomyl residues was detected 4 times across all types of markets in the from both supermarkets and farms exceeded the FAO/ Table 3 Summary information on the detected insecticides, the pesticide classification group, its classification according to toxicity, the source (district and market type) of sampling and the number of times each compound was detected Pesticide Pesticide Group WHO Hazard class Description District Type of market No. of times Total (sample source) detected detections Methamidophos Organophosphate IB Highly hazardous Central South East Farm 1 10 Farm 3 South East Supermarkets 2 Central South East Vendor 1 Vendor 3 Triazophos Organophosphate IB Highly hazardous North East Vendor 1 1 Methomyl Carbamate IB Highly hazardous Central Farm 1 5 Central Supermarket 2 South East Vendor 2 Cypermethrin Pyrethroid II Moderately hazardous Central Farms 1 5 Central North East Supermarket 1 Supermarket 1 South East Vendor 2 Acephate Organophosphate II Moderately hazardous Central Farm 2 3 South East Vendor 1 Chlorfenapyr Pyrrole II Moderately hazardous Central Farm 1 3 South East Supermarket 1 South East Vendor 1 Chlorpyrifos Organophosphate II Moderately hazardous South East Farm 1 2 Central Supermarket 1 Fenvalerate Pyrethroid II Moderately hazardous North East Supermarket 1 1 Imidacloprid Neonicotinoid II Moderately hazardous North East Vendor 1 1 Chlorantraniliprole Anthranilic diamides N/A Unlikely hazardous Central Farms 1 4 Central Supermarket 1 Central Vendor 2 Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 8 of 13 a b Number of detected pesticides per sample Pesticide Fig. 3 Summary results showing proportion of (a) detections per pesticide and (b) samples with specific number of pesticides detected per sample Fig. 4 The mean detected quantities for pesticides above the FAO/WHO Codex Alimentarius (MRL) thresholds for methomyl, chlorfenapyr, methamidophos, chlorpyriphos and acephate. The Codex Alimentarius MRL thresholds are indicated by the arrow. Data on MRL thresholds were derived from Codex Alimentarius online database (Codex Alimentarius, 2017) Proportion of detections (%) Proportion of samples (%) Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 9 of 13 WHO Codex MRL of 0.01 mg/kg (see Fig. 4). For chlor- times each pesticide exceeded the Codex MRL varied fernapyr, mean detected residue quantities in samples across the types of markets (Fig. 5). For methomyl, from the supermarkets (0.39 mg/kg) were significantly methamidophos and acephate, the mean quantity of de- higher (p < 0.001) than both farms and vendors. How- tected residues were higher in samples from farms, ex- ever, mean residue quantities in samples from the farms ceeding the Codex MRL by 67, 80 and 87.7 times (0.23 mg/kg) were significantly higher (p < 0.001) than respectively (see Fig. 5). However, chlorpyriphos and those from the vendors (0.01 mg/kg). Similar to metho- chorfenapyr exceeded the thresholds more in supermar- myl, chlorfenapyr had residues exceeding the FAO/ kets, 16 and 39-times respectively. Samples from ven- WHO Codex MRLs in samples from both farms and su- dors mostly did not exceed the Codex MRLs for all of permarkets (p < 0.001) but not in samples from vendors the pesticide residues except acephate which exceeded (Fig. 4). 5-fold (Fig. 5). Using the potential daily vegetable con- Methamidophos had a wide range of residue quantities sumption of 0.7 g/person/day, an average body weight of detected especially in samples from the farms (0.04–2.9 60 kg (WHO/GEMS/FOODS) (2006), and the grand mg/kg) with a mean of 0.8 mg/kg which was significantly mean of detected amount (mg/kg) for each pesticide, we higher (p = 0.005) than both supermarkets (0.02 mg/kg) estimated the pesticide daily intake (ADI) and Acute and vendors (0.018 mg/kg). Residues from all the three Reference Doses (ARfD) (as in Alla et al. 2015) (Table 4). types of markets exceeded the FAO/WHO Codex MRLs Both the mean detected quantity and the estimated per although at different magnitudes (see Fig. 4). Similar to capita consumption/day were below the WHO ADI and chlorfenapyr, chlorpyriphos mean residues quantities ARfD for all pesticides (Table 4). were significantly higher (p < 0.001) in samples from the supermarkets (0.16 mg/kg) compared to farms and ven- Discussion dors both of which were not significantly different from Our study showed multiple and excessive pesticide resi- each other. Both farms and supermarkets exceeded the dues on ‘fresh’ cabbage vegetable markets in Botswana; Codex MRLs. As observed in the other two organo- and to our knowledge, this is the first report to date, de- phosphates (methamidophos and methomyl), acephate tailing such in an arid African context. We detected or- mean detected residue quantities were significantly ganophosphates, pyrethroids, carbamates, pyrroles, higher (p < 0.001) on samples from the farms (0.88 mg/ neonicotinoids and a diamide in 74.1% of the tested kg) than both supermarkets and vendors. Supermarket samples with 33.4% showing multiple pesticide residue residues (0.05 mg.kg) were however significantly higher detections per individual sample. These results resonate (p < 0.001) than vendors (Fig. 4). with 66.5% total detections and 35% multi-pesticides de- Residues from both farms and supermarkets exceeded tections observed in apples in Poland (Lazowicka 2015) the FAO/WHO Codex MRLs by different number of and also concur with recent findings from Ghana times-as-great (magnitudes or folds). The number of (Amoah et al. 2006; Osei-Fosu et al. 2017), Zambia Supermarkets Farms Vendors Name of pesticide (active ingredient) Fig. 5 Summary results showing the number of times (folds) each pesticide exceeded the Codex Alimentarius MRL threshold at each type of market. Data on MRL thresholds were derived from Codex Alimentarius online database (Codex Alimentarius, 2017) Fold above Codex MRL threshold Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 10 of 13 Table 4 An indication of the magnitude of exposure to selected detected hazardous pesticides based on the estimate of per capita consumption/day compared to WHO’s Acceptable daily intake ADI and Acute reference dose (ARfD) limits. Data are based on recommended per capita consumption of 0.7 g/person/annum for leaf vegetable consumption in Africa (see WHO/GEMS/FOODS, 2006; Alla et al. 2015). Data on (ADI) and (ARfD) obtained from WHO online database (WHO, 2017) a b b Active ingredient Range of detected Overall mean Codex Percapita Acceptable daily Acute reference quantity (mg/kg) detected quantity Alimentarius consumption/day intake (ADI) dose (ARfD) (mg/kg) MRLs (mg/kg) (mg/kg) (mg/kg bw/day) (mg/kg bw) Acephate 0.05–0.89 0.60 0.01 0.0042 0.03 0.1 Chlorpyriphos 0.02–0.16 0.09 0.01 0.00063 0.01 0.1 Methamidophos 0.02–2.90 0.33 0.01 0.00231 0.004 0.01 Methomyl 0.01–0.67 0.19 0.01 0.00133 0.02 0.02 Chlorfenapyr 0.01–0.39 0.21 0.01 0.00147 0.03 0.03 Based on recommended per capita consumption of 0.7 g/person/annum (WHO/GEMS/FOODS) (2006) for leaf vegetable consumption in Africa (see also Alla et al. 2015) Data on (ADI) and (ARfD) obtained from WHO online database based on 60 kg average body weight (bw) (WHO/GEMS/FOODS) (2006; WHO, 2017) (Mwanja et al. 2017) and Kuwait (Jallow et al., 2017). Cypermethrin and fenvarelate detected here, are type Fifty percent of total pesticide detections were above the II pyrethroids with extremely high toxicity (Bradberry et Codex Alimentarius MRLs permitted by law and these al. 2005; WHO 2005). Exposure of humans to pyre- were dominated by organophosphates; classified as throids has been reported to disrupt the endocrine sys- highly hazardous (Class 1B) (WHO, 2009). We docu- tem, e.g. through its estrogen mimicry affecting ment that farmgate sales were the major market source reproductive functions (reviewed in Bradberry et al. of high levels of residue contaminated vegetables com- 2005). We also detected a neonicotinoid (imidacloprid) pared to supermarkets and vendors. Although vendors in our samples, human exposure to moderate or high and supermarkets got their vegetables from the doses has been observed to affect central nervous sys- farms, the protracted time lag between buying from tem function causing tremors, impaired pupillary the farm and selling to consumers may enable fur- function, hypothermia, drowsiness and dizziness (Wu ther degradation of the pesticide. The similarity in et al. 2001; Sheets et al. 2015). Similarly, the pyroles, the types and quantities of detected pesticides in e.g. chlorfenapyr detected here, is highly toxic and space confirmed the uniform rampant, uncontrolled environmentally persistent. In humans, it affects me- and injudicious pesticide abuse behaviour in the tabolism (Albers et al. 2006), e.g. causes loss of body African vegetable production systems, as previously fat, muscle wasting and bile retention. If unchecked, reported by Machekano et al. (2017, 2019). the bio-accumulation of these residues in human The multi-detectetion and dominance of organophos- body due to continued and multiple (product) con- phates and carbamates at quantities above the Codex sumption may have deleterious effects on public MRLs in our findings is a cause for concern. Organo- health that may be difficult to trace back and link phoshates and cabarmates have high mammalian toxicity with pesticide exposure in the future (Albers et al. (WHO 2009) through the inhibition of Acetylcholine Es- 2006). terase (AChE), an enzyme that catalyses the hydrolysis Our results showed that residue levels in cabbage sam- of Acetylcholine (Ach), an essential neurotransmitting pled from supermarkets were not significantly different agent in humans (Fukuto 1990; Rathnayake and from those sampled from farms. The high stock turn- Northrup 2016; Medscape 2017). Low AChE activity in over, supported by frequent re-stocking and refrigerated the blood is used as a biomarker for body organophos- storage facilities may explain this trend. Both the low phate accumulation (Repetto and Baliga 1996; Magauzi temperature storage facilities and the frequent ‘fresh’ et al. 2011). Inhibition of (Ach) causes short (Anand et supplies from the farms, keep pesticide residues in al. 2009) and long (Hung et al. 2015) term heart and re- supermarket produce higher compared to vendors. Con- spiratory functions (Fukuto 1990; Medscape 2017)as versely, vendors had the least quantities of detected well as retarded cognitive development in children pesticide residues and lowest total number of detections (Engel et al. 2011). However, for the African consumers, owing to their low stock turnover allowing for pesticide ‘lack of knowledge’ on pesticide residues on food, ‘lack of degradation over time (protracted marketing period). consciousness’ on the link between consumption and or- Furthermore, the vegetable produce is often exposed to ganophosphate poisoning, as well as other social ills the outside and sunny environment, which may facilitate mask the visibility of the chronic effects of pesticide resi- faster dispersion and photo-degradation of chemicals. As due exposure (Macharia et al. 2015). a whole, this observation may point to the notion that Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 11 of 13 “the ‘fresher’ the vegetables, the more contaminated they for recent per capita consumption data, on which to may, and vice-versa” as reinforced by the negative cor- base calculations of 'realistic' toxicological reference relation observed between quantity of detected pesti- values. This is a critical concern given the current high cides and length of time between delivery and sampling. consumption of raw cabbage (salad) and/or as a cooked This meant that the shorter the time lag between deliv- vegetable. Detection of multi-residues in one sample poses ery and sampling, the higher the detected pesticide a high but yet neglected risk of bio-accumulation, quantity. However, due to public quality demands and bio-reaction, high human-pesticide burden and ‘lack of knowledge’, most consumers prefer the more bio-magnification (Repetto and Baliga 1996; Boobies et al., contaminated ‘fresh’ farm or supermarket produce, while 2008; Alla et al. 2015) with unknown human health conse- denigrating the supposedly stale but safer stocks from quences (Alla et al. 2015). Ito et al. (1996)reported an in- the vendors or often organically produced produce. crease in the number and size of liver lesions in rats Our study is the first to compare vegetable pesticide exposed to diverse rather than single pesticide(s). Simi- residues across different domestic markets to unravel larly, occupational multiple pesticide exposure has been evidence of potential public health risks. Irrespective of reported to cause short term (e.g. headaches, nausea, ab- the market source, Thompson et al. (2017) showed the dominal pains) to long term cancers, reproductive, ner- occurrence of organochlorines in 13 African countries vous and endocrine system disruptions (Macharia et al. not only in vegetables but also in human breast milk 2011; reviewed in Donkor et al. 2016). In African systems, and blood serum. This calls for an urgent need for inter- there is scarcity of laboratory equipment and skills to de- vention to prevent insurmountable pesticide related tect pesticides in food let alone diagnosing patient symp- public health burdens on already resource constrained toms to multi-pesticide residue exposure (Boobis et al. African governments. Higher residue contamination on 2008). samples from the farms may be because on-farm sales To protect public health, market regulation of pesti- are made more immediate to spraying time, not allowing cide residues may be the only viable solution currently. for pesticide degradation in time. It could also be due to This can be achieved through policy regulatory frame- high frequency of application or higher than recom- works and consumer empowerment to induce market mended dosages (Ngowi et al. 2007; Williamson et al. rejection and enforce farmers’ behavioural change. Agro- 2008; Machekano et al. 2019) or a combination thereof. chemicals Regulation Acts e.g. Botswana, has stringent Moreover, high residues reported here, may also be due regulations on proper handling of pesticides, human and to the intentional or unintentional failure to adhere to environmental protection. However, we feel that the recommended pesticide withdrawal periods (as in e.g. weaknesses may be in (1) the inability by the govern- Williamson et al. 2008; Ngowi et al. 2007; Machekano et ments to monitor farmers’ activities and (2) the penalty al. 2019) owing to lack of knowledge and market compe- for breaking the regulations is not prohibitive enough to tition (Williamson et al. 2008; Machekano et al. 2019). enforce compliance. These challenges need to be ad- Withdrawal periods for some of the pesticides detected dressed to comply with regional efforts, e.g. the recently here are high, e.g. 14 days for imidachloprid and 21 days formed Southern African Pesticide Regulators Forum for both methamidophos and chlorantraniliprole. How- (SAPReF) under Southern African Development Com- ever, Machekano et al. (2019) reported that 71.6% of munity (SADC) may be the key regional coordinator in farmers waited for a mean ~ 10 days, indiscriminate of regional policy harmonization, to improve the manage- the applied active ingredient. Moreover, some pesticides, ment, movement and use of pesticides. Promotion and e.g. fenvalerate, are not recommended for use in crucif- funding of safer alternatives to pesticides such as Inte- erous crops. Nevertheless, these have been reported to grated Pest Management (IPM) can be advocated be used indiscriminate of the crop type (see Machekano through such regional bodies to increase impact and et al. 2019). Thus, existing regulations on pesticide mis- tighten regional policies on pesticide risk management use are not being observed, and this malpractice exposes and risk reduction. Furthermore, pesticide half-life stud- the public to indirect ‘pesticide’ consumption through ies for compounds detected here need further investiga- highly contaminated ‘fresh’ produce as evidenced by our tion under Botswana climatic conditions, and explore results. the pesticide degradation period as a possible tool to en- Although there was no violation of the toxicological ref- sure safe pesticide levels in marketed vegetable products erence values in the short (>ARfDs) and long terms (as in e.g. Donkor et al. 2016). Based on the results re- (>ADIs), we nevertheless believe the WHO/GEMS/ ported here, long term epidemiological studies may be FOODS (2006) leaf vegetable per capita consumption esti- needed to quantify the public health risk by ascertaining mation of 0.7-g/kg/person in Africa used to calculate ex- the degree of correlation and association between cumu- posure risk in this study was an underestimation, lative pesticide dietary exposure and chronic ill-health cognizant of current consumption trends. There is need occurrences both in space and time. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 12 of 13 Conclusion Availability of data and materials Collected and analysed data are available upon request from the corresponding Multiple and excessive pesticide residues were present in author. consumer-ready cabbages across the three common markets in Botswana. Although with caveats, this sce- Authors’ contributions HM and CN contributed to project conceptualization and WM contributed nario may be the same across other African vegetable the methodology; CN contributed to funding acquisition, project value chain systems. We recorded the most toxic pesti- administration, and resources. CN and BMM contributed to supervision; cide residues e.g. organophosphates and carbamates, HM, CN and WM contributed to investigation and writing of the original draft, data curation, validation, formal analysis and writing. HM, CN, BMM occuring in quantities higher than the Codex MRLs. and WM contributed to review and editing. All authors read and approved the These results mean that the public are exposed and final manuscript. highly vulnerable to health risks associated with pesti- Authors’ information cide toxicity. Farmgate-sold produce had higher quan- HM: PhD, Botswana International University of Science and Technology tities of pesticide residues compared to supermarkets (BIUST). and vendors. To safeguard public health to pesticide ex- BMM: PhD, and Professor, University of Zimbabwe. WM: PhD, and Professor, BIUST. posure, we recommend investment in initiatives that im- CN: PhD and Senior Lecturer, BIUST. prove small scale farmers’ pesticide use behaviour and control pesticide misuse. The diverse and multi-detected Competing interests The authors declare that they have no competing interests. above threshold pesticide residues reported here are also a cause for concern. We recommend that policymakers Publisher’sNote and other stakeholders alike, put in place stringent moni- Springer Nature remains neutral with regard to jurisdictional claims in published toring, regulating and enforcing frameworks on existing maps and institutional affiliations. laws for good pesticide use practices by farmers. This may Author details include (1) enforcing withdrawal periods (2) enforcing Department of Biological Sciences and Biotechnology, Botswana stricter misconduct penalties, (3) developing rapid pesti- International University of Science and Technology, Private Bag 16, Palapye, cide residue testing kits across the value chain, (4) pro- Botswana. Department of Soil Science and Agricultural Engineering, Faculty of Agriculture, University of Zimbabwe, P. O Box MP167, Mt Pleasant, Harare, moting awareness and funding sustainable bio-rational Zimbabwe. Department of Chemical and Forensic Sciences, Botswana pest management methods e.g. biological control and (5) International University of Science and Technology, Private Bag 16, Palapye, developing regulation and certification systems for fresh Botswana. produce marketing. Received: 24 September 2018 Accepted: 22 January 2019 Additional file References Albers PH, Klein PN, Green DE, Melancon MJ, Brian P, Bradley BP, Noguchi G. Chlorfenapyr and mallard ducks: overview, study design, macroscopic effects, Additional file 1: Table S1. Validation performance parameters for the and analytical chemistry. Environ Toxicol Chem. 2006;25:438–45. detected compounds using LC-MS/MS performed with cabbage sample Alla SAG, Loutfy NM, Shendy AM, Ahmed MT. Hazard index, a tool for a long matrices fortified at various concentrations. Table S2. Validation term risk assessment of pesticide residues in some commodities, a pilot performance parameters for the detected compounds using GC-MS study. 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Food Addit Contam B. 2017;10:91–8. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Food Contamination Springer Journals

Cabbage or ‘pesticide’ on the platter? Chemical analysis reveals multiple and excessive residues in African vegetable markets

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Springer Journals
Copyright
Copyright © 2019 by The Author(s).
Subject
Chemistry; Food Science
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2196-2804
DOI
10.1186/s40550-019-0072-y
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Abstract

Overuse of pesticides in vegetables and related fresh products raises serious public health concerns. However, the recognition and assessment of the magnitude of public health risk remains a low priority in low income African communities. Brassicas are a cosmopolitan crop in African horticulture, and equally so, is the major economic pest, the diamondback moth, Plutella xylostella (L.). In consequence, insecticide use on P. xylostella in brassica production systems presents persistent pesticide overuse on produce directly destined for public consumption. Using the quick easy cheap effective rugged and safe (QuEChERS) multi-residue analysis method, followed by gas chromatography- mass spectrometry (GC-MS) or liquid chromatography-tandem mass spectrometry (LC-MS/MS), we investigated the occurrence and magnitude of pesticide residues at three vegetable market levels (farmgates, vendors and supermarkets) in Botswana. We detected pesticide residues in 74.1% of the samples while 33.4% had multiple compounds. Farmgates recorded higher pesticide residues than other markets. We multi-detected 10 low-highly hazardous pesticides [World Health Organisation (WHO)] (classes 1B & II), that included Organophosphates, Pyrethroids, Neonicotinoids and Carbamates. Fifty percent of the detected pesticides from farms and supermarkets had residue quantities exceeding the Codex Maximum Residue Limit thresholds; although estimated daily per capita consumption was lower than the WHO Average Daily Intake (ADI) and Acute Reference Doses (ARfDs). These results indicate presence of multiple and excessive pesticide residues in routinely consumed vegetables on the markets, and points to an imminent public health hazard. Urgent attention is needed to develop and enforce effective policies and regulations on pesticide use practices and investment in non-chemical pest management alternatives. Keywords: Pesticide residues, Brassica, Public health risk, Codex Alimentarius Maximum Residue Limits, Diamondback moth Introduction (Newton et al. 2011) and pesticide overuse (Machekano Sustainable agriculture under rapidly changing climate et al. 2017, 2019) in an effort to increase crop productiv- (IPCC 2014) and increasing human population (FAO ity and profitability. This malpractice has resulted in 2009) remains a big challenge in Africa. However, it production of pesticide laden agricultural produce, with remains critical that food and nutrition challenges be ad- negative implications on food safety and public health dressed using sustainable approaches. For the horticul- (Donkor et al. 2016). While human exposure to pesticide tural industry, changes in temperature associated with residues can be through different modes (Semple 2005), climate change have created increased pest pressure contaminated food remains the main exposure route (about five orders higher) (Nougadère et al. 2012; Szpyrka et al. 2015, reviewed in Donkor et al. 2016; * Correspondence: nyamukondiwac@biust.ac.bw Mebdoua et al. 2017). In brassicas, pesticide overuse is Department of Biological Sciences and Biotechnology, Botswana International University of Science and Technology, Private Bag 16, Palapye, mainly associated with the high and stigmatic pesticide Botswana resistance history of the diamondback moth, Plutella Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 2 of 13 xylostella (L.) (Lepidoptera: Plutellidae) (Furlong et al. of many horticultural farmers in most African countries 2013; Machekano et al. 2017). This is further aggravated is skewed towards increasing quantity and not safety of by vegetables being consumed fresh as salads or partially the produce (Leroy et al. 2015). In addition, the technical processed e.g. cauliflower and cabbages (Mwanja et al. sophistication of residue analysis makes the regulation, 2017) with no rigorous cooking process that could po- enforcement and compliance with the WHO/FAO Max- tentially degrade pesticide compounds. In addition, bras- imum Residue Limits (MRLs) under the Codex Alimen- sicas have been reported to capture more chemical tarius standards a big challenge at each level of the value content during direct spray and drift because of their chain to most developing countries (Amoah et al. 2006; large leaf surface area (Alla et al. 2015). Damallas and Eleftherohorinos 2011; Mwanja et al. With the growing global health concerns on meat and 2017). related products, there is an increasing demand for vege- Studies carried out to date were mostly focused on oc- tables because of their health benefits and affordability cupational exposure (Magauzi et al. 2011;Hinsonetal. (see FAO 2004; Donkor et al. 2016). This has made bras- 2017), neglecting the vulnerable passive exposure to con- sica crops gain popularity in developing countries sumers (Repetto and Baliga 1996;Semple 2005)through (Madisa et al. 2010; Mazhawidza and Mvumi 2017), consumption of chemical residues on consumer-ready making them a significant daily dietary component due ‘fresh’ vegetable products procured from the markets to their richness in vitamins, minerals, fibre and antioxi- (Nougadère et al. 2012). Generally, quantifying pesticide dants (FAO 2004). Simultaneously however, brassicas exposure is currently the quickest way of assessing and have become a major source of public health risk due to quantifying the risk of public exposure to pesticides in high incidence of pesticides residues (Szpyrka et al. Africa (Semple 2005). Direct acute or chronic health ef- 2015; Donkor et al. 2016; Jallow et al. 2017) associated fects are difficult to measure due to chemical interactive with pesticide abuse (Ngowi et al. 2007; Machekano et or dose-addition effects caused by continuous consump- al. 2019). In the drive to sustain food production in Af- tion of multiple chemicals in different products that then rica, the use of insecticides in horticultural production mar diagnostic accuracy especially in ill-equipped devel- systems is indispensable (Bhanti et al. 2004; Obopile et oping countries’ laboratories (Ngowi et al. 2007;Boobiset al. 2008; Williamson et al. 2008; Madisa et al. 2010). In al. 2008;Machariaetal. 2015). In addition, there are syn- Botswana for example, farmers are increasing the use of ergistic complexities associated with multiple pesticide synthetic pesticides (Obopile et al. 2008; Machekano et toxicity, mycotoxicity and interaction with existing al. 2019) to sustain horticultural yields and cope with in- chronic illnesses (e.g. HIV and AIDS) that further obfus- creased demand for brassicas caused by increasing rural cates recognition and quantification of pesticide exposure to urban migration (Madisa et al. 2010). risks (Repetto and Baliga 1996; Mostafalou and Abdollahi In a survey recently conducted in Botswana, P. xylos- 2013). Therefore, methodologies to assess public health tella accounted for the need to apply pesticides on risks from exposure to multiple residues simultaneously, brassica crops in 71.6% of the cases (Machekano et al. including their possible chemical interactive effects within 2019). Forty one moderate to highly hazardous insecti- the human body are currently lacking, especially under cide active ingredients (see WHO, 2009) targeted on P. African contexts (Ngowi et al. 2007;Boobiset al. 2008; xylostella control alone were recorded; some applied as Macharia et al. 2015). Since policy enforcement (Damallas pesticide ‘cocktails’ of more than two pesticides to re- and Eleftherohorinos 2011) and public awareness may be spond to P. xylostella high pest pressure (Machekano et the most effective way to minimize the problem through al. 2019). High residues may be exacerbated by the appli- enforcing farmers’ behavioural change (Williamson et al., cation of these pesticides too close to harvesting time 2008), there is urgent need to generate convincing evi- without due consideration for the recommended with- dence for policymakers on the nature and magnitude of drawal periods because of market competition and the the problem and the associated potential health need to protect a clean supply reputation. Farmers may threats (e.g. cholinergic syndrome (Fulco et al. 2000), sell their brassica crops before recommended withdrawal different types of cancers, cardiovascular diseases periods; a practice that then exposes the unsuspecting (CVDs), birth defects, reproductive disorders and Par- public to pesticide-contaminated food. Moreover, in de- kinson’s disease (Mostafalou and Abdollahi 2013)). veloping countries, consumers purchase directly from Chemical analysis of fresh produce on the market for farm-gates, apart from vendors and retailers (Madisa et detection and quantification of pesticide residues al. 2010); all devoid of means to detect and quantify therefore, brings warning evidence that can be used pesticide residues on the produce. The indiscriminate as early warning system by policymakers to take mea- application of different types and quantities of pesticides sures that will protect public health. on vegetables calls for an urgent need for evaluation of In Botswana, and indeed other developing countries, the magnitude of the public health risk. The main focus pesticide related health issues constitute a serious threat to Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 3 of 13 development (Ngowi et al. 2007;Macharia etal. 2015; were skipped (depending on the size of the field) and the Jallow et al. 2017), yet, data on public health risk assess- process was repeated until a compound sample of nine ment, detection and quantification of potentially harmful cabbages was obtained. Sampled plot sizes ranged pesticide residues in vegetables or related products remain roughly from 0.3–0.6 ha typical of small scale farmers’ scarce. Cognizant of the uncontrolled injudicious use of acreage in Botswana. The farm field sampling was based pesticides against P. xylostella (see details in Machekano et on the notion that when consumers are purchasing from al. 2019) and using cabbages as a case study, we farms, the cabbages are immediately harvested from the hypothesize that chemical residues are present on field following payment. To avoid field edge bias, the consumer-ready-cabbages at all three types of dominant first three rows on either side of the field and the first domestic vegetable markets in Botswana. We further hy- 10 cabbage heads within a row were discarded. pothesise that the quantities of pesticide residues may ex- From each of the compound sample of whole cabbage ceed the permissible Codex Alimentarius MRLs. The heads, 4 equidistant slices were cut from the surface to objective of this study was therefore to detect, characterize the core of each cabbage head and pulled out (synonym- and quantify potential pesticide residues in fresh African ous of ‘cake slice’) using a laboratory knife. These were cabbage markets using Botswana as a sampling point. This further sliced into small pieces and mixed in 45 × 35 cm information is critical in advising policy-makers, pesticide laboratory trays to obtain a sliced composite sample (see regulators, consumers and farmers alike on the potential Mwanja et al. 2017). A 1 kg subsample was then mea- health risks associated with exposure to high levels of toxic sured out using a laboratory balance (RADWAG Wagi chemical residues in fresh produce and the urgent need Elektronikczne, Model PS 4500.R2, Poland) and placed for respective remedial action. into sterile 44 × 30 cm ziploc bags which were immedi- ately sealed and placed on ice in a laboratory cooler box Methods maintained at about 0 ± 1 °C. The trays were washed and Sample collection and preparation lined with new plastic (> 100 μm thick) before preparing Cabbage samples were collected from three high brassica the next sample to avoid contamination. production districts of Botswana vis Central; North East and South East districts (Table 1). All samples were pro- Sample preparation cured under normal consumer-ready-purchasing-conditions Samples were prepared using the quick easy cheap ef- to take into account realistic consumer (public) expos- fective rugged and safe QuEChERS method (Anasta- ure conditions and to reduce bias (Nougadère et al. 2012; siades et al. 2003). Briefly, samples were processed using Mwanja et al. 2017). Sampling was done from a three-tier Foss food cutter and homogenized (Ultra Turrax T25). market system (vendors, supermarkets and farms), to cater Thereafter 10 g of each homogenate was placed in 50 for all types of markets used by vegetable consumers under mL polypropylene tubes with screw caps. The extrac- an African context (see Osei-Fosu et al. 2017). At each sam- tion solvent acetonitrile was then added to each sub- pling point, peripheral data such as the Global Positioning sample and shaken for 1 min until uniform. Buffering System (GPS) coordinates, the name of the sampling point citrate salts and sodium chloride (pH 5–5.5), were also (vendor, supermarket or farm) as well as the dates when the added and the mixture shaken intensively for 1 min sampled consignment was delivered to the retailer (in the followed by centrifugation at 5000 rpm to allow for case of vendors or supermarkets) were recorded. Sampling phase separation. The organic phase was thereafter was done following standardized random sampling methods cleaned-up using the dispersive solid phase extraction (Fernandez-Alba 2005; Amoah et al. 2006;Bempahetal. (d-SPE) method. Briefly, 1 ml of the supernatant of the 2011; Osei-Fosu et al. 2017;Mwanjaet al. 2017). subsample was transferred into a new 2 ml centrifuge Most vendors kept their stock on tables or at the back tube containing primary and secondary amine (PSA) of trucks/vans. After normal purchasing process, nine and magnesium sulphate. PSA was added for the re- whole cabbage heads were randomly picked from a ven- moval of sugar, fatty acids and organic acids, while dor’s table, truck or van. The process was repeated three magnesium sulphate was used as a drying agent; to re- times in each district (3 vendors) to yield three vendor move any residual water see also (Paya et al. 2007). Fi- replicates for each district (Table 1). The same process nally the mixtures were shaken followed by was repeated for the supermarkets (Fernandez-Alba centrifugation to produce clear supernatant for GC-MS 2005; Amoah et al. 2006). At farm level, only farm-fields and LC-MS/MS analysis as required (Table 2). that had physiologically mature cabbages that were already being harvested for marketing were sampled. Stock and standards solutions preparations Three whole cabbage heads were randomly picked from All solvents, namely acetonitrile, methanol and water each cabbage row by picking every 10th cabbage within were of HPLC grade. A single composite working stand- a row from a random starting point. Three or five lines ard solution at 100 μg/mL was prepared in methanol Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 4 of 13 Table 1 Summary details of the sampling sites, including the type of sampling market, district, village and geographic positioning of the site Type of market Sample code District Village/Mall/Town GPS Coordinates Supermarket NEsup North East Sunshine Plaza mall S21. 11,115, E027. 32,117 Supermarket NEsup North East Nzano Centre Mall S21. 10,697, E027. 30,700 Supermarket NEsup North East Sunshine Plaza mall S21. 11,115, E027. 32,117 Vendor NEven North east Francistown Block 6 S21. 12,328, E027. 32,177 Vendor NEven North East Francistown bus rank S21. 10,296, E027.30688 Vendor NEven North East Gallo Mall S21. 10,391, E027. 30,883 Farm NEfar North East Ditladi S21. 26,013, E027. 28,170 Farm NEfar North East Gulushabe S21. 28,718, E027. 31,533 Farm NEfar North East Gulushabe S21. 26,013, E027. 32,100 Supermarket Csup Central Palapye S22. 33,336, E027. 07718 Supermarket Csup Central Boiteko junction mall S22. 25,261, E026. 44,709 Supermarket Csup Central Mahalapye S23. 06551, E026. 50,014 Vendor Cven Central Serorome ward S22. 32,644, E027. 06175 Vendor Cven Central Mahalapye Bus rank S23. 06672, E026. 49,973 Vendor Cven Central Shoshong S23. 01806, E026. 30,813 Farm Cfar Central Serowe S22. 26,013, E026. 44,709 Farm Cfar Central Palapye S22. 34,965, E027. 05266 Farm Cfar Central Modiane village S23. 06628, E026. 43,079 Supermarket SEsup South East Pakhalane S24. 33,836, E025. 58,572 Supermarket SEsup South East Rail Park Mall S24. 39,582, E025. 54,124 Supermarket SEsup South East Riverwalk Mall S24. 40,548, E025. 56,036 Vendor SEven South East Gaborone bus rank S24. 39,516, E025. 54,137 Vendor SEven South East Gaborone West S24. 39,575, E025. 54,047 Vendor SEven South East Tlogatloga ward S24. 39,089, E025. 53,259 Farm SEfar South East Glen Valley S24. 36,864, E025. 58,149 Farm SEfar South East Glen Valley S24. 36,500, E025. 58,293 Farm SEfar South East Glen Valley S24. 36,256, E025. 58,574 NEven North East District vendor, NEsup North East district supermarket, NEfar North East district farm, Cven Central district vendor, Csup Central district supermarket, Cfar Central district farm, SEsup South East district supermarket, SEven South East district vendor, SEfar South East district farm; numbers 1, 2, 3 represent replications and stored at − 20 °C. LC-MS/MS the stock solutions LC-MS/MS analysis − 3 − 4 (1 × 10 g/mL or 5 × 10 g/mL) of each of the single LC-MS/MS was run using the South African Bureau of compounds were prepared in acetonitrile. Stock work di- Standards (SABS) inhouse method no. 029/2006 vali- − 5 lution mixtures (1 × 10 g/mL) were prepared in aceto- dated for the determination of pesticides in fruits and nitrile and kept for the preparation of the work vegetables at concentration range of 0.01–1.0 mg/kg on dilutions. The following work dilutions were prepared: LM-MS/MS with a limit of quantitation (LOQ) of 0.01 − 6 − 6 − 7 − 7 − 7 − 8 (2 × 10 ,1×10 ,5×10 ,3×10 ,1×10 ,5×10 , mg/kg. Summary of the validation data and compounds − 8 − 8 − 8 3×10 ,2×10 and 1 × 10 g/mL) in acetonitrile. For included are provided (Additional file 1: Table S1). − 3 − 4 GC-MS, stock solutions (1 × 10 g/mL or 5 × 10 g/ 100 μL of supernatant was injected into a Kinetex col- mL) of each of the single compounds were prepared in umn (Phenomenex, United States) of particle sizes 150 − 5 toluene. Work dilution mixtures of 5 × 10 g/mL were mm × 4.6 mm. The mobile phase consisted of a mixture prepared in toluene and kept for the preparation of the of high-purity water with 0.1% formic acid (A) and work dilutions. The following work dilutions were pre- acetonitrile (B). In order to separate the ions, a gradient − 6 − 6 − 7 − 7 − 7 pared: (2 × 10 ,1×10 ,5×10 ,3×10 ,1×10 , programme started with 90% A and 10% B for 2 min, − 8 − 8 − 8 − 8 5×10 ,3×10 ,2×10 and 1 × 10 g/mL) in thereafter, there was a gradual change in mobile phase hexane. which took 26 min until 5% A and 95% B was reached. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 5 of 13 Table 2 Sample analysis techniques (GC-MS and LC-MS/MS) Data analysis and limit of quantitation (LOQ) used to detect and quantify Mass Hunter® quantitation software (Agilent Technolo- different types of pesticides in our experiments gies, United States) was used for quantification. Data Pesticide Pesticide group Technique used (LOQ ) (mg/kg) were analysed in STATISTICA 13.3 (TIBCO Software Chlorpyriphos Organophosphate GC-MS 0.01 Inc. USA). Data that did not meet linear model assump- tions of constant variance and normal errors were ana- Triazophos Organophosphate 0.01 lysed using generalized linear models (GLZ) and Cypermethrin Pyrethroid 0.02 Kruskal-Wallis post-hoc tests were used to separate sta- Fenvarelate Pyrethroid 0.02 tistically different medians. For multi-detected individual Chlorfenapyr Pyrole 0.01 pesticides, the data satisfied the ANOVA assumptions, Acephate Organophosphate LC-MS/MS 0.01 therefore, one-way ANOVA was used. Tukey-Kramers Methamidophos Organophosphate 0.01 HSD test was used to separate statistically significant means. Linear regression analysis using 2D scatterplots Methomyl Carbamate 0.01 was done in STATISTICA to assess the correlation be- Chorantraniliprole Diamide 0.01 tween detected quantities and number of days after de- Imidacloprid Neonicotinoids 0.01 livery. To measure the magnitude of public exposure, we LOQ Limit of quantitation calculated per capita residue consumption following Mwanja et al. (2017) only for the six detected highly haz- Thereafter, the mobile phase was kept constant at 5.0% ardous pesticides that exceeded the Codex MRLs, and A and 95% B for 32 min, and finally, gradually increased compared the figures to the recommended acceptable back to 90% A and 10% B which took 38 min. A tandem daily intake (ADI) and the acute reference doses mass spectrometer (Agilent 6460, Germany) was used (ARfD) for the individual pesticides based on recom- for detection using Mass Hunter® quantitation software mended per capita consumption of leafy vegetables in (Agilent Technologies, United States). Africa of 0.7 g/person/annum (WHO/GEMS/FOODS 2006) and 60kg body weight (BW) as in Alla et al. (2015). Gas chromatography mass spectrometry (GC-MS) The GC-MS was run using the South African Bureau of Results Standards (SABS) in-house method no. 029/2006 vali- Detections, identification and quantification dated for the determination of organochlorines (OCs), Retention time (RT) and mass-to-charge ratio (m/z) organophosphates (OPs) and synthetic pyrethroids in were used to identify positive peaks for detected com- fruits and vegetables at concentration range of 0.01– pounds in both GC-MS and LC-MS/MS analyses (Fig. 1). 0.05 mg/kg by GC-ECD and FPD with a limit of quanti- Figure 1a shows the LC-MS/MS multiple chromato- tation (LOQ) of 0.01 mg/kg for both OCs and OPs and grams for a sample from a vendor based at Shoshong 0.02 mg/kg for synthetic pyrethroids. Summary of the (see details in Table 1). The graph shows positive peaks validation data and compounds included are provided for methamidophos (RT = 4.161 min, concentration = (Additional file 1: Table S2). The analysis was per- 0.0262 mg/kg), methomyl (RT = 10.163 min, concentra- formed with an Agilent technologies 6890 gas chro- tion = 0.0140 mg/kg), chlorantraniliprole (RT = 20.282 matography equipped with an inert mass selective min, concentration = 0.0350 mg/kg). All the other de- detector (MSD), model 5975 (Agilent Technologies, tected LC-MS/MS amenable compounds were identified USA). The system was operated in a splitless mode. in the same manner. The GC-MS chromatograms for a The GC column was an Agilent J &W GC column single detection for a sample from a supermarket in (model: Agilent 19091S-433, HP-5MS) of length 30 m, Gaborone are shown in Fig. 1b exemplified by chlorfena- internal diameter of 0.250 mm and film thickness of pyr (RT = 20.269 min, concentration = 0.5721 mg/kg). 0.25 μm. The column was kept at a constant flow rate Pesticide residues were detected in 74.1% of the tested of 0.9 ml/min. Helium was used as the carrier gas. samples at all market levels, i.e. farms, vendors and su- The inlet and detector temperatures were maintained permarkets combined (Fig. 2a) across all the sampled at 250 °C and 325 °C respectively. The temperature districts (Fig. 2b). Samples from the farms showed program started at an initial temperature of 80 °C for higher KW-H = 10.255, (p = 0.0059) detected quan- (2, 34) 1 min, followed by a gradient programme to an elu- tities of pesticide residues than samples from both su- tion temperature of 325 °C for a total runtime of 38 permarkets and vendors (Fig. 2a). However, there were min. The validation data for both GC-MS and no significant differences KW-H = 2.8411, (p = (2, 34) LC-MS/MS are presented in electronic supplementary 0.2416) in the quantity of pesticides detected across all materal, Additional file: 1. sampled districts (Fig. 2b). Generally, the number of Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 6 of 13 Fig. 1 Chromatograms for (a) LC-MS/MS showing peaks for 3 multi-detected pesticide residues for a sample from a vendor at Shoshong shopping centre in Central District (S23. 01806, E026. 30,813) (methamidophos: RT = 4.161 min, concentration = 0.0262 mg/kg; methomyl: RT = 10.163, concentration = 0.0140 mg/kg and chlorantraniliprole: RT = 20.282 min, concentration = 0.0350 mg/kg). b GC-MS showing peaks residues for chlorfenapyr (RT = 20.269 min, concentration = 0.5271 mg/kg) from a sample from a supermarket in South East District (S24.39582, E025. 54,124). The insertion in 1b shows the extracted and zoomed GC-MS peaks and mass-to-charge ratios for Chlorfenapyr. (Batch 3876_7A14.d and 3876a07D represents laboratory sample coding. RT = Retention time in minutes) a b 3.5 3.5 Median Median 25%-75% 25%-75% Non-Outlier Range 3.0 3.0 Non-Outlier Range Outliers Outliers Extremes Extremes 2.5 2.5 2.0 2.0 1.5 1.5 a a 1.0 1.0 ab 0.5 0.5 0.0 0.0 Farm s Superm arkets Vendors Central North East South East Type of market District Fig. 2 Median ± 95%CLs of the detection of pesticide residues across (a)markets and(b) districts Kuskall-Wallis post-hoc tests were used to separate heterogenous groups at P = 0.05. Group medians with the same letter(s) are not statistically different Detected Quantity (mg/kg) Detected Quantity mg/kg Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 7 of 13 samples with pesticide residues (% proportion of detec- Central district only. For individual pesticides, overall tions per type of market) were higher in the farms and proportion of detections was higher for methamidophos, supermarkets compared to vendors. followed by cypermethrin; methomyl and chlorantranili- A total of ten different active ingredient residues were prole (see Fig. 3a). Most of the samples included only multi-detected from 27 cabbage samples including four one detectable pesticide, while at least two detected pes- organophosphates (methamidophos, triazophos, ace- ticides were found in 33.4% of the samples (Fig. 3b). The phate and chlorpyriphos), two pyrethroids (cypermethrin detected quantity of pesticides were negatively correlated and fenvarelate), one carbamate (methomyl), one pyrrole (r = − 0.269, p < 0.001) to the length of time (number of (chorfenapyr), one neonicotinoid (imidacloprid) and one days) between the vendor or supermarket’s date of re- diamide (chlorantraniliprole) (see Table 3). Methamido- ceiving supply and the time of sampling. phos, triazophos and methomyl fall in hazard class 1B, classified as highly hazardous (WHO 2009). Methomyl Risk assessment and methamidophos were multi-detected across all types A total of 50% (17/34) of total detections, dominated by of markets in all sampled districts while triazophos was organophosphates were above the Codex Alimentarius detected only from vendors in one district (North East) MRLs. Detected residue quantities for methomyl were (Table 3). Six of the detected pesticides; cypermethrin, significantly higher (p < 0.001) on samples from the fenvarelate, acephate, chlorpyriphos, chlorfenapyr and farms (0.67 mg/kg) compared to supermarkets (0.045 imidacloprid belong to WHO toxicity class II, described mg/kg) and vendors (0.01 mg/kg). On the other hand, as moderately hazardous (WHO 2009) (Table 3). The residues from supermarkets were significantly higher (p ‘unlikely hazardous’ (WHO 2009) chlorantraniliprole < 0.001) than samples from vendors. Methomyl residues was detected 4 times across all types of markets in the from both supermarkets and farms exceeded the FAO/ Table 3 Summary information on the detected insecticides, the pesticide classification group, its classification according to toxicity, the source (district and market type) of sampling and the number of times each compound was detected Pesticide Pesticide Group WHO Hazard class Description District Type of market No. of times Total (sample source) detected detections Methamidophos Organophosphate IB Highly hazardous Central South East Farm 1 10 Farm 3 South East Supermarkets 2 Central South East Vendor 1 Vendor 3 Triazophos Organophosphate IB Highly hazardous North East Vendor 1 1 Methomyl Carbamate IB Highly hazardous Central Farm 1 5 Central Supermarket 2 South East Vendor 2 Cypermethrin Pyrethroid II Moderately hazardous Central Farms 1 5 Central North East Supermarket 1 Supermarket 1 South East Vendor 2 Acephate Organophosphate II Moderately hazardous Central Farm 2 3 South East Vendor 1 Chlorfenapyr Pyrrole II Moderately hazardous Central Farm 1 3 South East Supermarket 1 South East Vendor 1 Chlorpyrifos Organophosphate II Moderately hazardous South East Farm 1 2 Central Supermarket 1 Fenvalerate Pyrethroid II Moderately hazardous North East Supermarket 1 1 Imidacloprid Neonicotinoid II Moderately hazardous North East Vendor 1 1 Chlorantraniliprole Anthranilic diamides N/A Unlikely hazardous Central Farms 1 4 Central Supermarket 1 Central Vendor 2 Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 8 of 13 a b Number of detected pesticides per sample Pesticide Fig. 3 Summary results showing proportion of (a) detections per pesticide and (b) samples with specific number of pesticides detected per sample Fig. 4 The mean detected quantities for pesticides above the FAO/WHO Codex Alimentarius (MRL) thresholds for methomyl, chlorfenapyr, methamidophos, chlorpyriphos and acephate. The Codex Alimentarius MRL thresholds are indicated by the arrow. Data on MRL thresholds were derived from Codex Alimentarius online database (Codex Alimentarius, 2017) Proportion of detections (%) Proportion of samples (%) Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 9 of 13 WHO Codex MRL of 0.01 mg/kg (see Fig. 4). For chlor- times each pesticide exceeded the Codex MRL varied fernapyr, mean detected residue quantities in samples across the types of markets (Fig. 5). For methomyl, from the supermarkets (0.39 mg/kg) were significantly methamidophos and acephate, the mean quantity of de- higher (p < 0.001) than both farms and vendors. How- tected residues were higher in samples from farms, ex- ever, mean residue quantities in samples from the farms ceeding the Codex MRL by 67, 80 and 87.7 times (0.23 mg/kg) were significantly higher (p < 0.001) than respectively (see Fig. 5). However, chlorpyriphos and those from the vendors (0.01 mg/kg). Similar to metho- chorfenapyr exceeded the thresholds more in supermar- myl, chlorfenapyr had residues exceeding the FAO/ kets, 16 and 39-times respectively. Samples from ven- WHO Codex MRLs in samples from both farms and su- dors mostly did not exceed the Codex MRLs for all of permarkets (p < 0.001) but not in samples from vendors the pesticide residues except acephate which exceeded (Fig. 4). 5-fold (Fig. 5). Using the potential daily vegetable con- Methamidophos had a wide range of residue quantities sumption of 0.7 g/person/day, an average body weight of detected especially in samples from the farms (0.04–2.9 60 kg (WHO/GEMS/FOODS) (2006), and the grand mg/kg) with a mean of 0.8 mg/kg which was significantly mean of detected amount (mg/kg) for each pesticide, we higher (p = 0.005) than both supermarkets (0.02 mg/kg) estimated the pesticide daily intake (ADI) and Acute and vendors (0.018 mg/kg). Residues from all the three Reference Doses (ARfD) (as in Alla et al. 2015) (Table 4). types of markets exceeded the FAO/WHO Codex MRLs Both the mean detected quantity and the estimated per although at different magnitudes (see Fig. 4). Similar to capita consumption/day were below the WHO ADI and chlorfenapyr, chlorpyriphos mean residues quantities ARfD for all pesticides (Table 4). were significantly higher (p < 0.001) in samples from the supermarkets (0.16 mg/kg) compared to farms and ven- Discussion dors both of which were not significantly different from Our study showed multiple and excessive pesticide resi- each other. Both farms and supermarkets exceeded the dues on ‘fresh’ cabbage vegetable markets in Botswana; Codex MRLs. As observed in the other two organo- and to our knowledge, this is the first report to date, de- phosphates (methamidophos and methomyl), acephate tailing such in an arid African context. We detected or- mean detected residue quantities were significantly ganophosphates, pyrethroids, carbamates, pyrroles, higher (p < 0.001) on samples from the farms (0.88 mg/ neonicotinoids and a diamide in 74.1% of the tested kg) than both supermarkets and vendors. Supermarket samples with 33.4% showing multiple pesticide residue residues (0.05 mg.kg) were however significantly higher detections per individual sample. These results resonate (p < 0.001) than vendors (Fig. 4). with 66.5% total detections and 35% multi-pesticides de- Residues from both farms and supermarkets exceeded tections observed in apples in Poland (Lazowicka 2015) the FAO/WHO Codex MRLs by different number of and also concur with recent findings from Ghana times-as-great (magnitudes or folds). The number of (Amoah et al. 2006; Osei-Fosu et al. 2017), Zambia Supermarkets Farms Vendors Name of pesticide (active ingredient) Fig. 5 Summary results showing the number of times (folds) each pesticide exceeded the Codex Alimentarius MRL threshold at each type of market. Data on MRL thresholds were derived from Codex Alimentarius online database (Codex Alimentarius, 2017) Fold above Codex MRL threshold Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 10 of 13 Table 4 An indication of the magnitude of exposure to selected detected hazardous pesticides based on the estimate of per capita consumption/day compared to WHO’s Acceptable daily intake ADI and Acute reference dose (ARfD) limits. Data are based on recommended per capita consumption of 0.7 g/person/annum for leaf vegetable consumption in Africa (see WHO/GEMS/FOODS, 2006; Alla et al. 2015). Data on (ADI) and (ARfD) obtained from WHO online database (WHO, 2017) a b b Active ingredient Range of detected Overall mean Codex Percapita Acceptable daily Acute reference quantity (mg/kg) detected quantity Alimentarius consumption/day intake (ADI) dose (ARfD) (mg/kg) MRLs (mg/kg) (mg/kg) (mg/kg bw/day) (mg/kg bw) Acephate 0.05–0.89 0.60 0.01 0.0042 0.03 0.1 Chlorpyriphos 0.02–0.16 0.09 0.01 0.00063 0.01 0.1 Methamidophos 0.02–2.90 0.33 0.01 0.00231 0.004 0.01 Methomyl 0.01–0.67 0.19 0.01 0.00133 0.02 0.02 Chlorfenapyr 0.01–0.39 0.21 0.01 0.00147 0.03 0.03 Based on recommended per capita consumption of 0.7 g/person/annum (WHO/GEMS/FOODS) (2006) for leaf vegetable consumption in Africa (see also Alla et al. 2015) Data on (ADI) and (ARfD) obtained from WHO online database based on 60 kg average body weight (bw) (WHO/GEMS/FOODS) (2006; WHO, 2017) (Mwanja et al. 2017) and Kuwait (Jallow et al., 2017). Cypermethrin and fenvarelate detected here, are type Fifty percent of total pesticide detections were above the II pyrethroids with extremely high toxicity (Bradberry et Codex Alimentarius MRLs permitted by law and these al. 2005; WHO 2005). Exposure of humans to pyre- were dominated by organophosphates; classified as throids has been reported to disrupt the endocrine sys- highly hazardous (Class 1B) (WHO, 2009). We docu- tem, e.g. through its estrogen mimicry affecting ment that farmgate sales were the major market source reproductive functions (reviewed in Bradberry et al. of high levels of residue contaminated vegetables com- 2005). We also detected a neonicotinoid (imidacloprid) pared to supermarkets and vendors. Although vendors in our samples, human exposure to moderate or high and supermarkets got their vegetables from the doses has been observed to affect central nervous sys- farms, the protracted time lag between buying from tem function causing tremors, impaired pupillary the farm and selling to consumers may enable fur- function, hypothermia, drowsiness and dizziness (Wu ther degradation of the pesticide. The similarity in et al. 2001; Sheets et al. 2015). Similarly, the pyroles, the types and quantities of detected pesticides in e.g. chlorfenapyr detected here, is highly toxic and space confirmed the uniform rampant, uncontrolled environmentally persistent. In humans, it affects me- and injudicious pesticide abuse behaviour in the tabolism (Albers et al. 2006), e.g. causes loss of body African vegetable production systems, as previously fat, muscle wasting and bile retention. If unchecked, reported by Machekano et al. (2017, 2019). the bio-accumulation of these residues in human The multi-detectetion and dominance of organophos- body due to continued and multiple (product) con- phates and carbamates at quantities above the Codex sumption may have deleterious effects on public MRLs in our findings is a cause for concern. Organo- health that may be difficult to trace back and link phoshates and cabarmates have high mammalian toxicity with pesticide exposure in the future (Albers et al. (WHO 2009) through the inhibition of Acetylcholine Es- 2006). terase (AChE), an enzyme that catalyses the hydrolysis Our results showed that residue levels in cabbage sam- of Acetylcholine (Ach), an essential neurotransmitting pled from supermarkets were not significantly different agent in humans (Fukuto 1990; Rathnayake and from those sampled from farms. The high stock turn- Northrup 2016; Medscape 2017). Low AChE activity in over, supported by frequent re-stocking and refrigerated the blood is used as a biomarker for body organophos- storage facilities may explain this trend. Both the low phate accumulation (Repetto and Baliga 1996; Magauzi temperature storage facilities and the frequent ‘fresh’ et al. 2011). Inhibition of (Ach) causes short (Anand et supplies from the farms, keep pesticide residues in al. 2009) and long (Hung et al. 2015) term heart and re- supermarket produce higher compared to vendors. Con- spiratory functions (Fukuto 1990; Medscape 2017)as versely, vendors had the least quantities of detected well as retarded cognitive development in children pesticide residues and lowest total number of detections (Engel et al. 2011). However, for the African consumers, owing to their low stock turnover allowing for pesticide ‘lack of knowledge’ on pesticide residues on food, ‘lack of degradation over time (protracted marketing period). consciousness’ on the link between consumption and or- Furthermore, the vegetable produce is often exposed to ganophosphate poisoning, as well as other social ills the outside and sunny environment, which may facilitate mask the visibility of the chronic effects of pesticide resi- faster dispersion and photo-degradation of chemicals. As due exposure (Macharia et al. 2015). a whole, this observation may point to the notion that Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 11 of 13 “the ‘fresher’ the vegetables, the more contaminated they for recent per capita consumption data, on which to may, and vice-versa” as reinforced by the negative cor- base calculations of 'realistic' toxicological reference relation observed between quantity of detected pesti- values. This is a critical concern given the current high cides and length of time between delivery and sampling. consumption of raw cabbage (salad) and/or as a cooked This meant that the shorter the time lag between deliv- vegetable. Detection of multi-residues in one sample poses ery and sampling, the higher the detected pesticide a high but yet neglected risk of bio-accumulation, quantity. However, due to public quality demands and bio-reaction, high human-pesticide burden and ‘lack of knowledge’, most consumers prefer the more bio-magnification (Repetto and Baliga 1996; Boobies et al., contaminated ‘fresh’ farm or supermarket produce, while 2008; Alla et al. 2015) with unknown human health conse- denigrating the supposedly stale but safer stocks from quences (Alla et al. 2015). Ito et al. (1996)reported an in- the vendors or often organically produced produce. crease in the number and size of liver lesions in rats Our study is the first to compare vegetable pesticide exposed to diverse rather than single pesticide(s). Simi- residues across different domestic markets to unravel larly, occupational multiple pesticide exposure has been evidence of potential public health risks. Irrespective of reported to cause short term (e.g. headaches, nausea, ab- the market source, Thompson et al. (2017) showed the dominal pains) to long term cancers, reproductive, ner- occurrence of organochlorines in 13 African countries vous and endocrine system disruptions (Macharia et al. not only in vegetables but also in human breast milk 2011; reviewed in Donkor et al. 2016). In African systems, and blood serum. This calls for an urgent need for inter- there is scarcity of laboratory equipment and skills to de- vention to prevent insurmountable pesticide related tect pesticides in food let alone diagnosing patient symp- public health burdens on already resource constrained toms to multi-pesticide residue exposure (Boobis et al. African governments. Higher residue contamination on 2008). samples from the farms may be because on-farm sales To protect public health, market regulation of pesti- are made more immediate to spraying time, not allowing cide residues may be the only viable solution currently. for pesticide degradation in time. It could also be due to This can be achieved through policy regulatory frame- high frequency of application or higher than recom- works and consumer empowerment to induce market mended dosages (Ngowi et al. 2007; Williamson et al. rejection and enforce farmers’ behavioural change. Agro- 2008; Machekano et al. 2019) or a combination thereof. chemicals Regulation Acts e.g. Botswana, has stringent Moreover, high residues reported here, may also be due regulations on proper handling of pesticides, human and to the intentional or unintentional failure to adhere to environmental protection. However, we feel that the recommended pesticide withdrawal periods (as in e.g. weaknesses may be in (1) the inability by the govern- Williamson et al. 2008; Ngowi et al. 2007; Machekano et ments to monitor farmers’ activities and (2) the penalty al. 2019) owing to lack of knowledge and market compe- for breaking the regulations is not prohibitive enough to tition (Williamson et al. 2008; Machekano et al. 2019). enforce compliance. These challenges need to be ad- Withdrawal periods for some of the pesticides detected dressed to comply with regional efforts, e.g. the recently here are high, e.g. 14 days for imidachloprid and 21 days formed Southern African Pesticide Regulators Forum for both methamidophos and chlorantraniliprole. How- (SAPReF) under Southern African Development Com- ever, Machekano et al. (2019) reported that 71.6% of munity (SADC) may be the key regional coordinator in farmers waited for a mean ~ 10 days, indiscriminate of regional policy harmonization, to improve the manage- the applied active ingredient. Moreover, some pesticides, ment, movement and use of pesticides. Promotion and e.g. fenvalerate, are not recommended for use in crucif- funding of safer alternatives to pesticides such as Inte- erous crops. Nevertheless, these have been reported to grated Pest Management (IPM) can be advocated be used indiscriminate of the crop type (see Machekano through such regional bodies to increase impact and et al. 2019). Thus, existing regulations on pesticide mis- tighten regional policies on pesticide risk management use are not being observed, and this malpractice exposes and risk reduction. Furthermore, pesticide half-life stud- the public to indirect ‘pesticide’ consumption through ies for compounds detected here need further investiga- highly contaminated ‘fresh’ produce as evidenced by our tion under Botswana climatic conditions, and explore results. the pesticide degradation period as a possible tool to en- Although there was no violation of the toxicological ref- sure safe pesticide levels in marketed vegetable products erence values in the short (>ARfDs) and long terms (as in e.g. Donkor et al. 2016). Based on the results re- (>ADIs), we nevertheless believe the WHO/GEMS/ ported here, long term epidemiological studies may be FOODS (2006) leaf vegetable per capita consumption esti- needed to quantify the public health risk by ascertaining mation of 0.7-g/kg/person in Africa used to calculate ex- the degree of correlation and association between cumu- posure risk in this study was an underestimation, lative pesticide dietary exposure and chronic ill-health cognizant of current consumption trends. There is need occurrences both in space and time. Machekano et al. International Journal of Food Contamination (2019) 6:2 Page 12 of 13 Conclusion Availability of data and materials Collected and analysed data are available upon request from the corresponding Multiple and excessive pesticide residues were present in author. consumer-ready cabbages across the three common markets in Botswana. Although with caveats, this sce- Authors’ contributions HM and CN contributed to project conceptualization and WM contributed nario may be the same across other African vegetable the methodology; CN contributed to funding acquisition, project value chain systems. We recorded the most toxic pesti- administration, and resources. CN and BMM contributed to supervision; cide residues e.g. organophosphates and carbamates, HM, CN and WM contributed to investigation and writing of the original draft, data curation, validation, formal analysis and writing. HM, CN, BMM occuring in quantities higher than the Codex MRLs. and WM contributed to review and editing. All authors read and approved the These results mean that the public are exposed and final manuscript. highly vulnerable to health risks associated with pesti- Authors’ information cide toxicity. Farmgate-sold produce had higher quan- HM: PhD, Botswana International University of Science and Technology tities of pesticide residues compared to supermarkets (BIUST). and vendors. To safeguard public health to pesticide ex- BMM: PhD, and Professor, University of Zimbabwe. WM: PhD, and Professor, BIUST. posure, we recommend investment in initiatives that im- CN: PhD and Senior Lecturer, BIUST. prove small scale farmers’ pesticide use behaviour and control pesticide misuse. The diverse and multi-detected Competing interests The authors declare that they have no competing interests. above threshold pesticide residues reported here are also a cause for concern. We recommend that policymakers Publisher’sNote and other stakeholders alike, put in place stringent moni- Springer Nature remains neutral with regard to jurisdictional claims in published toring, regulating and enforcing frameworks on existing maps and institutional affiliations. laws for good pesticide use practices by farmers. This may Author details include (1) enforcing withdrawal periods (2) enforcing Department of Biological Sciences and Biotechnology, Botswana stricter misconduct penalties, (3) developing rapid pesti- International University of Science and Technology, Private Bag 16, Palapye, cide residue testing kits across the value chain, (4) pro- Botswana. Department of Soil Science and Agricultural Engineering, Faculty of Agriculture, University of Zimbabwe, P. O Box MP167, Mt Pleasant, Harare, moting awareness and funding sustainable bio-rational Zimbabwe. Department of Chemical and Forensic Sciences, Botswana pest management methods e.g. biological control and (5) International University of Science and Technology, Private Bag 16, Palapye, developing regulation and certification systems for fresh Botswana. produce marketing. Received: 24 September 2018 Accepted: 22 January 2019 Additional file References Albers PH, Klein PN, Green DE, Melancon MJ, Brian P, Bradley BP, Noguchi G. Chlorfenapyr and mallard ducks: overview, study design, macroscopic effects, Additional file 1: Table S1. Validation performance parameters for the and analytical chemistry. Environ Toxicol Chem. 2006;25:438–45. detected compounds using LC-MS/MS performed with cabbage sample Alla SAG, Loutfy NM, Shendy AM, Ahmed MT. Hazard index, a tool for a long matrices fortified at various concentrations. Table S2. Validation term risk assessment of pesticide residues in some commodities, a pilot performance parameters for the detected compounds using GC-MS study. 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