Pesticides In Samples Research Articles

Measurements of Heavy Elements and Radioactivity Concentration Levels in Types of Fertilizers and Pesticides Commonly Used in Sana’a Yemen

This study aims to measure heavy metals (HMs) concentration and radioactivity concentration levels in fertilizer and pesticide samples collected from local markets in Sana’a, Yemen. Gamma spectroscopy employing a Survey Sodium Iodide NaI (TI) RIIDEYM-G detector was used for radiation and dose assessments. As for heavy metal analyses, this study used Inductively Coupled Optical Emission Spectroscopy (ICP-OES). Thirty samples were collected from local markets in Sana’a, Yemen. Radioactivity measurements show low levels of radioactivity concentration. The average dose rates due to fertilizer and pesticide samples were 1.14 and 1.07 mSv/y, respectively. These values are nearly equal to the recommended annual radiation dose rate limit (1mSv/y) recommended by the International Commission on Radiological Protection (ICRP). For heavy metal analysis, it was found that the average concentrations of heavy metals (HMs) (cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), nickel (Ni), lead (Pb), and zinc (Zn)) in the fertilizer samples were 1.08 mg/kg, 4.944 mg/kg, 13.8495 mg/kg, 274.371 mg/kg, 3.30446 mg/kg, 15.35686 mg/kg, and 24.4547 mg/kg, respectively. Heavy metal concentrations in fertilizer samples were mainly less than European (EU) guideline limits, with the exception of a few samples. The average concentrations of heavy metals (Cd, Cr, Cu, Fe, Ni, Pb, and Zn) in the pesticide samples were 0.8 mg/kg, 0.5784 mg/kg, 52.280 mg/kg, 73.4651 mg/kg, 2.4482 mg/kg, 3.199 mg/kg, and 1.1309 mg/kg, respectively. The heavy metal concentrations in pesticide samples were less than the corresponding values in fertilizer samples.

Quantitative analysis of acetamiprid and thiacloprid in green tea using enhanced SERS and neural networks

Neonicotinoids (NEOs) are widely used in agricultural cultivation, and the presence of residual NEOs poses a serious threat to consumer health. Therefore, trace detection of NEOs is particularly important. In this study, a response surface experimental design was employed to develop AgNP with high enhancement factor and surface height anisotropy, effectively enhancing the Raman signals of acetamiprid (ACE) and thiacloprid (THI) through densely populated hotspots on the surface. Gaussian simulation calculations were used to assign peaks in the ACE and THI spectra. Subsequently, convolutional neural network, backpropagation neural network, and AlexNet neural network were employed to identify the ACE, THI, and mixed component spectra, successfully distinguishing the spectra of the three compounds and achieving qualitative analysis of unknown spectra. Furthermore, genetic algorithm-partial least squares was used to model the spectral data, achieving a correlation coefficient of 0.97. The method was applied for the detection of spiked tea samples, achieving a precision RSD of 4.84 %. Therefore, this sensor combined with intelligent algorithms can be used for spectral identification and trace detection of mixed pesticide samples with structurally similar compounds.

Personal air sampling for pesticides in the California San Joaquin Valley.

California is a leading agricultural state and with that, has significant applications of pesticides. Levels of exposure have been measured to be higher among residents in agricultural areas, but measures of personal inhalation exposure to a wide range of pesticides are lacking. Community members in the San Joaquin Valley have expressed concern over pesticide exposures. Working with community members, a wide range of pesticides in personal air samples were measured. Adult and school-aged participants were recruited from small agricultural towns in the San Joaquin Valley. Participants wore a backpack sampler for 8-14 h on 1-3 days. Samples were collected on two tubes, one with Tenax-TA resin and the other with XAD-2 resin. In total, 21 pesticides were analyzed using both LC/MS and GC/MS methods. Thirty-one adult participants and 11 school aged participants were recruited, and sampling occurred on a total of 92 days. Seven adults, 22% of adult participants, and one school child had detectable levels of at least one pesticide. Pesticides detected above the limit of detection were 1,3-dichloropropene, chlorpyrifos, pyrimethanil, burprofezin and penthiopyrad. When these samples were collected, chlorpyrifos was not permitted to be used in California. California, a leading agricultural state, has significant pesticide use, leading to concern about exposures among community members. Thirty-one adult and 11 school aged participants wore personal air sampling backpacks from 1-3 days. Twenty-two percent of adult participants had detectable levels of at least one pesticide. Two pesticides with established toxicity, 1,3-dichloropropene and chlorpyrifos were detected, along with first time measurements of pyrimethanil, burprofezin and penthiopyrad in the United States, which all have potential indications of toxicity. This study suggests the need to expand which pesticides are measured in agricultural communities.

Indicators of Radioactive Contamination by Radionuclides for Samples of Plant Fertilizers and Pesticides

Abstract: This study aims to evaluate the radiation levels resulting from plant fertilizers and pesticides in Babylon City, Iraq. The specific activity of the studied radionuclides (e.g. 238U, 232Th, and 40K) was identified using the spectroscopy approach of the sodium-activated iodide thallium (NaI (Tl)) with dimensions of 3" × 3". The resulting data revealed that the specific activities for the aforementioned nuclides were 6.254 Bq/kg, 4.3694 Bq/kg, and 112.751 Bq/kg, respectively. The results indicated that the average radiation hazard metrics for fertilizers (i.e., gamma index, alpha index, absorbed dose rate, ambient dose equivalent rate, annual gonadal dose equivalent, and excess lifetime cancer risk) were lower than the reference levels. Keywords: Radiation hazard, Fertilizer, Pesticides, Risk parameters, Gamma activity.

Xác định acetamiprid bằng phương pháp quang học sử dụng dung dịch nano vàng được ổn định bằng Polydiallyldimethylammoni clorua

On this research, the development of a simple, cost-efective and highly sensitive spectrophotometric method for acetamiprid detection based on the localized surface plasmon resonance of polydiallyldimethylammonium chloridestabilized gold nanoparticles. By naked eyes, one can detect acetamiprid by the visual change of gold solution color from red to purple, corresponding to the shift of maximum absorbance wavelength in the UV-Vis spectrum. Quantification of acetamiprid is possible through a linear relationship between the maximum absorbance wavelength and the acetamiprid concentrations in the range of 8×10-8 -2×10-6 M. Under the optimum conditions including pH 5, NaCl concentration of 0.02 M and incubation time 20 min, the present method has high precision (RSD < 5%), very low limit of detection (LOD) of 2.7×10-8 M, limit of quantification (LOQ) of 8.2×10-8 M. This method has been successfully applied to determine acetamiprid in several pesticide samples and vegetable samples. The measurement results of acetamiprid in the pesticide samples of the research method with the HPLC-UV method showed a difference of < 2%, while for the vegetable sample, the difference between the research method and the LC-MS/method method/ MS < 5% shows that the method has high accuracy and reliability.

Enhancing LC×LC separations through multi-task Bayesian optimization

Method development in comprehensive two-dimensional liquid chromatography (LC×LC) is a challenging process. The interdependencies between the two dimensions and the possibility of incorporating complex gradient profiles, such as multi-segmented gradients or shifting gradients, make trial-and-error method development time-consuming and highly dependent on user experience. Retention modeling and Bayesian optimization (BO) have been proposed as solutions to mitigate these issues. However, both approaches have their strengths and weaknesses. On the one hand, retention modeling, which approximates true retention behavior, depends on effective peak tracking and accurate retention time and width predictions, which are increasingly challenging for complex samples and advanced gradient assemblies. On the other hand, Bayesian optimization may require many experiments when dealing with many adjustable parameters, as in LC×LC. Therefore, in this work, we investigate the use of multi-task Bayesian optimization (MTBO), a method that can combine information from both retention modeling and experimental measurements. The algorithm was first tested and compared with BO using a synthetic retention modeling test case, where it was shown that MTBO finds better optima with fewer method-development iterations than conventional BO. Next, the algorithm was tested on the optimization of a method for a pesticide sample and we found that the algorithm was able to improve upon the initial scanning experiments. Multi-task Bayesian optimization is a promising technique in situations where modeling retention is challenging, and the high number of adjustable parameters and/or limited optimization budget makes traditional Bayesian optimization impractical.

Removal of organochlorine pesticides by nanofiltration membranes modified with NH2-MWCNTs

Excessive use of pesticides and therefore the spread of pesticides in the environment with destructive effects on human and animal health is a very great problem in the world. In this study, the removal of three samples of organochlorine pesticides including aldrin, lindane, and endosulfan was investigated using nanofiltration membranes modified with NH2-MWCNTs. The properties of the prepared membranes were investigated by scanning electron microscopy (SEM), contact angle, water content, porosity, and mechanical strength. The performance of the membranes was evaluated by analysis of the rejection and flux of pesticide solutions at different pH. The addition of NH2-MWCNTs to the polymer matrix significantly improved the hydrophilic properties of the membranes and reduced the contact angle. Membrane flux was also improved by increasing the concentration of carbon nanotubes to 0.2 wt%. The highest flux at pH 10 is related to lindane pesticide. The modified membrane with 0.5 wt% functionalized carbon nanotubes showed a 98% rejection for endosulfan at neutral pH compared to the pure membrane. In the pH range experiment, lindane rejection was lower than of other pesticides. The steric hindrance due to the structure and molecular size of pesticides and interaction with membrane surface was very important in membrane efficiency. The M3 membrane with 0.3 wt% NH2-MWCNTs revealed high antifouling performance.

Dose Estimate of radon radioactive pollutants in samples of phosphate fertilizers and pesticides

Proceeding from the fact that agriculture is a long process of intensification through which society sought to meet its ever-increasing needs for food, and the necessity of countries to meet the needs of their populations, which made them resort to various means to meet these needs and as a result of the steady increase in the use of phosphate fertilizers in particular so that agriculture does not become a cause of exacerbation of environmental pollution with materials Radioactive substances and toxins that pose a significant danger to human life and living organisms, with the accompanying dangerous pathological phenomena. This research measured the concentration of radioactive pollutants in phosphate fertilizers. A s well as analyzing the radon levels in phosphate fertilizers and pesticide samples obtained from marketplaces in Iraq. Radiological parameters were measured using nuclear track detectors to calculate yearly effective exposure levels and the corresponding cancer risk. The acquired data were compared to the UNSCEAR's recommended limits and were determined to be within them.

Capillary-flow driven microfluidic sensor based on tyrosinase for fast user-friendly assessment of pesticide exposures.

Pesticides are primarily used in agriculture to protect crops and extend their longevity. However, pesticide exposure has been linked to various acute and chronic health effects, raising significant environmental concerns. Current detection methods are often expensive and time-consuming, relying on complex instruments. Although enzyme-inhibition-based microfluidic paper-based analytical device (mPAD) platforms offer an easier alternative, they suffer from slow analyte transport and analyte adsorption issues in microchannels. Consequently, there is a need for a fast, simple, and cost-effective point-of-need platform for pesticide sensing. In this study, we present a rapid microfluidic platform for on-site pesticide residue detection. Unlike traditional mPAD platforms, our system transports pesticide samples through hollow capillary channels within seconds without adsorption of pesticides in the microchannels. While much research has focused on acetylcholinesterase inhibition on paper, this study is the first to introduce a tyrosinase inhibition-based assay on a paper platform for pesticide detection. Ziram, a representative dithiocarbamate pesticide, was detected using a colorimetric enzymatic inhibition assay. A limit of detection (LoD) of 1.5 ppm was obtained. In this study, we optimized the fast-flow device, assessed its stability and susceptibility to various interferences, and conducted real-sample tests using glove extraction to evaluate its capability in real-world settings. Spike recovery analysis revealed an extraction efficiency of 82.5% to 87.5% for leather gloves and 68.9% to 71.9% for nitrile gloves. This platform demonstrates strong selectivity against interferences, with the enzyme retaining 90% activity even after a week under the established storage protocols with room for further investigation. While primarily a proof of concept, this device shows promise as an additional tool for pesticide detection, with potential future integration into multiplexed devices.

A multi-city study of indoor air quality in green vs non-green low-income housing

ObjectivesThe condition of the home is a strong predictor of exposure to environmental contaminants, with low-income households being particularly vulnerable. Therefore, improving housing standards is a priority. Housing built to “green” standards, with improved building methods and materials, has been suggested to reduce contaminants. However, evidence is limited as to which contaminants are reduced. The Green Housing Study was conducted to address this issue. The study hypothesis was that housing built using green components has lower concentrations of environmental contaminants compared to conventional housing. MethodsA repeated-measures, 12-month cohort study was performed in three U.S. cities. Data were collected in the home at three time points throughout a year. The level of contaminants were estimated using air samples for particulate matter and black carbon, dust samples for aeroallergens and pesticides, and resident or study staff reporting evidence of mold. To investigate source(s) of PM2.5 and black carbon, multivariable models using stepwise variable selection were developed. ResultsIn adjusted generalized estimating equations (GEE) models, black carbon concentration (μg/m3) (β = −0.22, 95% CI = −0.38 to −0.06, p = 0.01), permethrin (OR = 0.28, 95% CI = 0.15–0.49, p < 0.0001), and reported mold (OR = 0.29, 95% CI = 0.13–0.68, p = 0.003) were significantly lower in green homes. Cockroach antigen was also lower in green homes (OR = 0.59, 95% CI = 0.33–1.08, p = 0.09), although not statistically significant. We found that 68% of PM2.5 was explained by dwelling type and smoking and 42% of black carbon was explained by venting while cooking and use of a gas stove. ConclusionsThis study provides quantitative data suggesting benefits of incorporating green building practices on the level of numerous environmental contaminants known to be associated with health. Occupant behavior, particularly smoking, is an important contributor to indoor air pollution.

Determination of pesticide residue in marginal lagoons of natural parks in Brazil using an improved calibrate passive sampler

Passive sampling is a sensitive and efficient method for analyzing pesticides in water. This article describes a hollow fiber liquid-phase microextraction (HF-LPME) device that was improved using polypropylene membranes grafted with nanocellulose for the passive sampling of pesticides in water. A comprehensive gas chromatography time-of-flight mass spectrometry (GCxGC/Q-TOFMS) system was used to separate, identify, and quantify pesticides. The sampling rates of 38 moderately hydrophobic to hydrophobic agricultural pesticides (2.18 < log Kow < 6.89) from different chemical classes, including the main triazine, organochlorine and organophosphate compounds, were calculated. A calibration process was applied to evaluate the role of flow velocity and select potential candidates for a possible performance reference compound (PRC). Sampling rates varied between 0.17 mL d−1 and 23.15 mL d−1. The accumulation curves identified linear periods ranging from 3 to 18 days. The new passive sampler device was applied for 8 days in rivers and marginal lagoons of natural parks of the São Francisco basin in Minas Gerais, Brazil and identified 10 target pesticides. Furthermore, 10 non-targeted pesticides were detected by the GCxGC/Q-TOFMS method.

Simultaneous Analysis of 53 Pesticides in Safflower (Carthamus tinctorius L.) by Using LC–MS/MS Coupled with a Modified QuEChERS Technique

Objective: An optimized quick, easy, cheap, effective, rugged, and safe (QuEChERS) technique was investigated and compared with the conventional QuEChERS technique for the simultaneous analysis of fifty-three pesticide residues in safflower using ultra-high performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS). Method: Graphitic carbon nitride (g-C3N4) consisting of a major amount of carbon and nitrogen with a large surface area was used as a QuEChERS adsorbent instead of graphitized carbon black (GCB) for safflower extraction purification. Validation experiments were performed using spiked pesticide samples, and real samples were analyzed. Results: The linearity of the modified QuEChERS technique was evaluated with high coefficients of determination (R-2) being higher than 0.99. The limits of detection were &lt;10 μg/kg. The spiked recoveries ranged from 70.4% to 97.6% with a relative standard deviation of less than 10.0%. The fifty-three pesticides exhibited negligible matrix effects (&lt;20%). Thiamethoxam, acetamiprid, metolachlor, and difenoconazole were detected in real samples using an established method. Conclusion: This work provides a new g-C3N4-based modified QuEChERS technique for multi-pesticide residue analysis in complex food matrices.

Quantitative analysis of the minimum days of dietary survey to estimate dietary pesticide exposure: Implications for dietary pesticide sampling strategy

Populations are exposed to pesticides through diet on a daily basis. However, there is no research guiding how to evaluate dietary pesticide exposure, and researchers used 1-day, 3-days, 7-days or even longer dietary survey to evaluate without any consensus. It is important for dietary pesticide evaluation to identify the minimum survey days. To increase knowledge of this, a data combination was applied between a two-wave consecutive repeated-measures study in Baoding City and the Fifth China Total Diet Study. Further policy consistency on pesticides were evaluated to explain its credibility. We computed the sensitivity and specificity to evaluate how well different days of dietary survey classify participants with high exposure, and calculated the minimum days required to estimate the participant-specific mean at different acceptable error range. With 1 day of dietary survey, the classification sensitivity was low (<0.6) for total HCH, endosulfan, chlordane, cyhalothrin, allethrin, and prallethrin; that for the other pesticides was high sensitivity (≥0.6). Sensitivity increased as the number of days increased, and the maximum marginal sensitivity increase (≥0.039) occurred from 1 to 2 days for all pesticides except phenothrin, whose maximum marginal sensitivity increase (0.042) occurred from 2 to 3 days. The specificity increased gradually from 0.8 to 0.9 from 1 to 7 days. Under the acceptable error range of 0.5%, 3–28 days were required for participant-specific mean estimation and 1–7 days were required when acceptable error range was shrunk in 1%. Only 1 day was enough if 5% error range was acceptable. In conclusion, 3 days in the study period was cost-effective to distinguish high exposure group, and it rose to 7 when estimating participant-specific mean from a conservative perspective. This study can serve as a reference to determine the minimum survey days for epidemiological studies employing dietary surveys.

Simultaneous and Sensitive Detection of Three Pesticides Using a Functional Poly(Sulfobetaine Methacrylate)-Coated Paper-Based Colorimetric Sensor.

Chlorpyrifos (CHL), profenofos (PRO) and cypermethrin (CYP) are widely used in combination to increase crop yields. However, these three pesticides can cause serious harm to human health and do not easily degrade. In this study, a novel visible paper sensor has been prepared successfully and different colorimetric reactions were utilized to detect the three pesticides simultaneously. The sensor was constructed by grafting a zwitterionic polymer onto a cellulose filter (CF) and placing it on a glass surface modified with PDMS. The branch shape was designed to form multiple detection areas, which were modified with specific pesticides and corresponding chromogenic reagents. The as-prepared colorimetric platform exhibited high sensitivity, a short detection time, a good linear response and a low detection limit (LOD) for the three pesticides (chlorpyrifos: y = 46.801 - 1.939x, R2 = 0.983, LOD = 0.235 mg/L; profenofos: y = 40.068 + 42.5x, R2 = 0.988, LOD = 4.891 mg/L; cypermethrin: y = 51.993 + 1.474x, R2 = 0.993, LOD = 4.053 mg/L). The comparison of the results obtained by the proposed paper sensor and those obtained by spectrophotometry further revealed the stability and reliability of the paper sensor. In particular, the color intensity of the interaction between the pesticides and coloring agents could be directly observed by the human eye. The consistency of the colorimetric/optical assay was proven in real target pesticide samples. Thus, this sensing strategy provides a portable, cost-effective, accurate and visualized paper platform, which could be suitable for application in the fruit and vegetable industry for monitoring CHL, PRO and CYP in parallel.

The elimination and extraction of organosulfur compounds from real water and soil samples using metal organic framework/graphene oxide as a novel and efficient nanocomposite

In the present work, an efficient metal organic framework/graphene oxide (MOF-801/GO) sorbent was fabricated and employed for the detection of organosulfur pesticides (OSPs) in real samples using gas chromatography-flame photometric detection (GC-FPD). The optimal extraction parameters for the suggested solid-phase extraction (SPE) include sorbent amount (60 mg), extraction solvent (acetonitrile) and extraction time (5 min). The linear dynamic ranges and detection limits for organosulfur pesticides (OSPs) samples under above extraction conditions were ranged from 0.5 to 300 μg L−1 and 0.1–1.1 μg L−1, respectively. Moreover, the proposed SPE/GC-FDP method was applied for the analysis of pesticides in different real environmental water and soil samples. The obtained recoveries of the analytes in were between 92.0 and 106.8% and relative standard deviation (RSD) values were lower than 9.2%. The application of the MOF-801/GO as a sorbent in dSPE of OSPs analytes showed to be reliable, fast and sensible methodology for pesticides monitoring in different environmental samples.

Passive sampling of diverse pesticides in water by hydrophilic–lipophilic balance sorbent-embedded cellulose acetate membrane: Kinetics, equilibrium partitioning and field application

Pesticides are useful products for agriculture and human life, but they are often released into surface waters and are hazardous to aquatic ecosystems. Pesticides monitoring in surface waters is challenging due to the great variety, ultratrace levels and nonpoint source pollution of pesticides; however, continuous passive sampling may be conducive to solving these problems. This work evaluated the performance of a newly developed passive sampler (hydrophilic–lipophilic balance sorbent-embedded cellulose acetate membrane, HECAM) for six types of currently used/present pesticides. The uptake kinetics and equilibrium partitioning of nineteen pesticides in different dissolved concentrations were studied by dynamic accumulation and equilibrium partitioning experiments, respectively. In the dynamic accumulation experiments, pesticides gradually accumulated in the HECAM and followed a first-order kinetic model. The same type of pesticides had roughly comparable accumulation concentrations. The estimated uptake rate constants ranged from 1.04 to 13.5 L g−1 d−1, and sampling rates ranged from 0.02 to 0.31 L d−1 for the pesticides in the HECAM (size of 2 cm × 3 cm). Pesticide accumulation concentrations in the HECAM increased linearly with increasing dissolved concentrations, which means that varying concentrations can also be monitored by the HECAM. In the equilibrium partitioning experiments, the pesticide partitioning behavior at varying dissolved concentrations can be described by the Freundlich model. The calculated equilibrium partition coefficients (log KD) for pesticides ranged from 3.32 to 4.54, and different pesticide types showed different changes with log Kow. Comparable results were found when estimating chemical equilibrium partition coefficients by the dynamic accumulation and equilibrium partitioning methods. Field deployment of the HECAM in river waters resulted in the detection of four pesticides, and the measured results were comparable to those of active sampling coupled with liquid–liquid extraction. These results suggest that the HECAM would be a promising strategy for simultaneously monitoring diverse pesticides in waters.

Surface-enhanced Raman scattering of a gold core-silver shell-sponge substrate for detection of thiram and diquat.

Aiming at the difficulty of traditional pesticide sampling, a low-cost and convenient flexible surface enhanced Raman scattering (SERS) gold core-silver shell-sponge (Au-Ag-sponge) substrate was synthesized by chemical reduction. The SERS substrate consisted of Au-AgNPs and a melamine sponge. The sponge had a rich open pore structure, which could well "capture" Au-AgNPs, generating a large number of "hot spots". The SERS enhancement activity of the flexible substrate was characterized with rhodamine 6G (R6G) Raman probe molecules. The substrate showed good activity to 10-12 M rhodamine 6G with an enhancement factor (EF) of 7.72 × 106. Applying this substrate to the qualitative and quantitative detection of pesticide residues, the results showed that the Raman intensity was well related to the concentration of pesticide solution with the range of 0.1-10 mg L-1 of thiram and 1-10 mg L-1 of diquat. Furthermore, the substrate was analyzed by finite difference time domain (FDTD) simulation and the results were in good agreement with the experimental results. The reason for the difference in Raman signals of pesticide molecules on the same substrate was the different binding modes of Au-AgNPs on the sponge. Finally, we pointed out the advantages of flexible substrates in the field of pesticide residues, as well as future opportunities and challenges.

Biodegradation of Carbofuran and Paraquat by Indigenous Soil Microorganisms

Aim: It aimed at the biodegradation of Carbofuran and Paraquat using the active microbial population resident in a farmyard soil in the Federal University of Petroleum Resources (FUPRE), Ugbomoro Community, Delta State.&#x0D; Study Design: Microcosms were set-up in triplicates; sampling for pesticides’ loss and microbial counts were done bi-weekly. &#x0D; Place and Duration of Study: Study was done in Environmental Management and Toxicology Department, FUPRE and Chemistry Department, University of Benin between June 2019 and July 2019.&#x0D; Methodology: Carbofuran and Paraquat were applied to farmyard soil containing active microbial population at recommended and four times the recommended doses. A sterile control was equally setup. Biodegradation was monitored with the High Performance Liquid Chromatography (HPLC). Microbial counts were monitored using standard methods.&#x0D; Results: Carbofuran decreased from 108.6 ± 0.69 μg/kg (day 0) to 39.2 ± 3.8 μg/kg (day 28) and 301.4 ± 1.29 μg/kg (day 0) to 241.4 ± 2.83 μg/kg (day 28) for recommended and four times recommended rates, respectively. Also, there were complete removal of Paraquat in treatments with the recommended rate while it decreased from 268.3 ± 5.21μg/kg (day 0) to 144.4 ± 2.38 μg/kg (day 28) at four times the recommended rate. In the abiotic control, were little losses of both pesticides. Total heterotrophic bacterial, fungal and actinomycetes counts increased (day 14 to 21) in contaminated soils. Significant differences in degradation with respect to pesticides treatment and time were observed.&#x0D; Conclusion: The microorganisms grew at different concentrations reducing both Carbofuran and Paraquat in contaminated soils. Their presence and high numbers confirmed that they are ubiquitous, diverse and can adjust to any harsh environment. Increased microbial counts showed that they grew in presence of the chemicals and degraded them. Thus, these indigenous microbial population can be used for the clean-up of these pesticides pollution in farms to improve such environment.

Impact of agrochemicals application on lead and cadmium concentrations in shallot fields and their remediation with biochar, compost, and botanical pesticides

Excessive use of agrochemicals in shallot soil can contaminate the environment and reduce the quality of agricultural products because it is suspected that fertilizers and some pesticides contain heavy metals. The study purpose: 1) determine Pb and Cd content in fertilizers and pesticides used by shallot farmers in Wanasari, Brebes Regency, 2) decide the agrochemicals effect on Pb and Cd concentrations in soil and shallot, then provide environmentally friendly technology with biochar, compost, and botanical pesticides. The study was conducted in Wanasari, Brebes Regency, Central Java from March until October 2020. These studies include a sampling of fertilizers and pesticides that are widely used by shallot farmers in Wanasari Brebes and plot research in the field. The technological approaches used in this study are using biochar, compost, and botanical pesticides. Shallot seed used was the Bima Brebes variety. Analyzes of total Pb and Cd content in the soils and plants were determined using the HNO3:HClO4 extract and measured with an atomic absorption spectrometer (AAS). In this study, analysis was carried out on 11 pesticides with Pb and Cd content of 2.70-22.31 mg/kg and 0.04-0.50 mg/kg, respectively. The Pb and Cd contents in six fertilizers were 10.53-28.09 mg/kg and 0/07-0.52 mg/kg, respectively. Total Pb and Cd in soil are still below the critical limit of heavy metal required for agricultural soil. Heavy metal concentrations of Pb and Cd accumulated in the root > leaf > bulb for all treatments. The use of botanical pesticides, biochar, and compost needs to be developed at the shallot farmer level in several growing seasons so that it is expected to increase crop yields, reduce the cost of chemical pesticides, and be environmentally friendly.

Identification of Toxic Heavy Metals and Trace Elements in Pesticides Used by Shallots &lt;i&gt;(Allium Cepa Var. Aggregatum)&lt;/i&gt; Farmers in Brebes District, Indonesia

This study aims to identify the toxic heavy metals and trace elements in pesticides which are suspected to be a source of environmental pollution. The Neutron Activation Analysis method was used to identify and determine the concentration of toxic heavy metals and trace elements in pesticide samples. The pesticides used in this study consist of pesticides that are widely used by onion farmers in Brebes District, Central Java – Indonesia. These pesticides consist of two types (fungicides and insecticides) and in two different forms (solid and liquid). The results indicates that pesticides contain large levels of trace elements (Mg, Ti, Cl, Al, Ca, Br, Na, U, Mn, Br, La, Se, Hg, Rb, Fe, Eu, and Sb), and toxic heavy metals (As, Co, Cr, Ni, Zn, Cu, Hg). Generally, solid pesticides contain higher concentration of elements than liquid pesticides. In addition to releasing organic compounds, pesticides are also proven to be a source of certain trace elements (especially Mn, Br, Ti, Fe, Al) and toxic heavy metals (Cu, Zn, and Cr). They can affect the presence of these elements in the environment. *Corresponding author: sjuari@ugm.ac.id