Improving Pesticide Uptake Modeling into Potatoes: Considering Tuber Growth Dynamics

Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state

In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to predict the absolute solubility of drug-like compounds. The QM-derived descriptors account for the molecular properties of the solute, i.e., the solute-solute interactions in an artificial-liquid-state (super-cooled liquid), and the solute-solvent interactions in solution. We employ two main approaches to predict solubility: (i) a hypothetical pathway that involves melting the solute at room temperature T = T¯ ([Formula: see text]) and mixing the artificially liquid solute into the solvent ([Formula: see text]). In this approach [Formula: see text] is predicted using machine learning models, and the [Formula: see text] is obtained from COSMO-RS calculations; (ii) direct solubility prediction using machine learning algorithms. The models were trained on a large number of Bayer in-house compounds for which water solubility data is available at physiological pH of 6.5 and ambient temperature. We also evaluated our models using external datasets from a solubility challenge. Our models present great improvements compared to the absolute solubility prediction with the QSAR model for the artificial liquid state as implemented in the COSMOtherm software, for both in-house and external datasets. We are furthermore able to demonstrate the superiority of QM-derived descriptors compared to cheminformatics descriptors. We finally present low-cost alternative models using fragment-based COSMOquick calculations with only marginal reduction in the quality of predicted solubility.

Global assessment of honeybee exposure to pesticides through guttation consumption: An indicator approach

Guttation consumption is a potential pathway of pesticide residue exposure in honeybees. However, modeling tools for assessing honeybee exposure to pesticide residues in guttation drops are lacking. In this study, we propose an indicator-based approach for qualitatively or quantitatively analyzing the guttation-based exposure pathway, allowing us to conduct region-specific pesticide residue exposure assessments for honeybees. Exposure scores (the product of guttation production and residue level scores) were established to compare or rank honeybee exposure to pesticide residues via guttation intake across locations using three specified indicators (i.e., air temperature, relative humidity, and precipitation intensity). Warm, dry regions had high residue level scores (indicating high residue levels in guttation), whereas cold, wet regions had high guttation production scores (indicating high possibilities of guttation formation on leaf surfaces); their exposure scores were a combination of these two values. We evaluated and ranked honeybee exposure to imidacloprid residue across regions in Brazil, China, the United States, and selected European Union member states, revealing that pesticide application in many Brazilian federative units may raise honeybee risks due to high exposure scores. We also compared the guttation pathway to other common exposure pathways (nectar and pollen), suggesting that for some moderately lipophilic compounds, the guttation exposure pathway may not be ignored and should be further evaluated.

Determination of extractable pollutants from microplastics to vegetables: Accumulation and incorporation into the food chain

The presence and impacts of microplastics (MPs) are being extensively researched and reviewed, especially in the marine environment. However, mobility, transportation routes, and accumulation of leaching compounds such as additives in plastic waste including MPs are scarcely studied. Information regarding ecotoxicity and leachability of compounds related to MPs contamination in the environment is limited. Current work presents the levels of leachates from plastic materials in edible-root and non-edible root vegetables. Samples were analyzed by static headspace and gas chromatography-mass spectrometry (SHS-GC-MS) and the presence of 93 putative compounds was accurately monitored in the samples by the usage of Mass Spectrometry-Data Independent Analysis software. The application of chemometrics to the SHS-GC-MS dataset allowed differentiation between the levels of plastic related compounds in edible root and non-edible root vegetables, the former showing a higher content of plastic leachates. For SHS sampling, 3 g of the sample were incubated at 130 °C for 35 min in the HS vial and toluene and naphthalene were added as internal standards for quantification purposes. The developed SHS-GC-MS methodology is straightforward, reliable, and robust and allowed the quantification of sixteen plastic associated compounds in the samples studied in a range from 0.14 to 28800 ng g-1 corresponding to 2,4-di-tert-butylphenol and p,α-dimethylstyrene, respectively. Several of the quantified compounds pointed out to potential contamination of polystyrene and/or polyvinyl chloride MPs.

Including the bioconcentration of pesticide metabolites in plant uptake modeling

Although several models of pesticide uptake into plants are available, there are few modeling studies on the bioconcentration of metabolites in plants. Ignoring metabolites in plant uptake models can result in an underestimation of the parent compound's overall impacts on human health associated with pesticide residues in harvested food crops. To address this limitation, we offer a metabolite-based plant uptake model to predict the bioconcentration of the parent compound and its metabolites in plants. We used the uptake of glyphosate and its major metabolite (aminomethylphosphonic acid, AMPA) into potato as an example. The analysis of variability revealed that soil properties (affecting the soil sorption coefficient), dissipation half-life in soil, and metabolic half-life in the potato had a significant impact on the simulated AMPA concentration in the potato, indicating that regional variability could be generated in the plant bioconcentration process of metabolites. The proposed model was further compared using the non-metabolite model. The findings of the comparison suggested that the non-metabolite model, which is integrated with the AMPA bioconcentration process, can predict the AMPA concentration in the potato similarly to the proposed model. In conclusion, we provide insight into the bioconcentration process of metabolites in tuber plants from a modeling viewpoint, with some crucial model inputs, such as biotransformation and metabolic rate constants, requiring confirmation in future studies. The modeling demonstration emphasizes that it is relevant to consider bioaccumulation of metabolites, which can propagate further into increased overall residues of harmful compounds, especially in cases where metabolites have higher toxicity effect potency than their respective parent compounds.

Predicting pesticide residues in pod fruits with a modified peel-like uptake model: A green pea demonstration

Peas are among the most popular leguminous plants, consumed by both humans and animals in large quantities. Pesticides are widely used globally to increase pea yield, and as a result, pesticide residues can be taken up by pea plants and bioaccumulate in their fruits, including peas and pods. However, there is a lack of modeling approaches available to predict residue concentrations in peas. To address this issue, a pod fruit model (specifically designed for neutral organic compounds) was proposed to simulate the bioaccumulation process of pesticide residues in pea plants, which was developed by modifying a peel-like uptake model. The simulation results, based on green pea as the modeling demonstration, reveal that moderately-lipophilic pesticides (i.e., log KOW around 3) have higher simulated concentrations in peas at harvest compared to hydrophilic (i.e., log KOW less than 0) or highly-lipophilic (i.e., log KOW over 5) pesticides, which is due to the enhanced uptake process of moderately-lipophilic compounds in the pod-pea system, such as their ability to penetrate the pod cuticle and be transported via phloem sap. The sensitivity test and variability analysis conducted in this study revealed that the degradation kinetics, including metabolism, hydrolysis, and photolysis, had a significant impact on moderately-lipophilic pesticides due to their high simulated concentrations in the pea plant. This can result in substantial loss of residue mass via degradation. The validation of the model demonstrated that the simulation results, specifically residue concentrations in the fruit, were consistent with the harvested data. However, some inconsistency was observed immediately after pesticide application, which could be attributed to plant growth dynamics and initial surface mass distributions. The proposed pod fruit model provides new insights into the bioaccumulation process of pesticide residues in pea plants and enables high-throughput simulations of residue concentrations at harvest. To enhance the performance of the pod fruit model, future research should consider plant growth dynamics, plant uptake of ionizable compounds, and initial mass distribution functions.

Considering degradation kinetics of pesticides in plant uptake models: proof of concept for potato

BACKGROUND

Degradation kinetics of pesticides in plants are crucial for modeling mechanism-based pesticide residual concentrations. However, due to complex open-field conditions that involve multiple pesticide plant uptake and elimination processes, it is difficult to directly measure degradation kinetics of pesticides in plants. To address this limitation, we proposed a modeling approach for estimating degradation rate constants of pesticides in plants, using potato as a model crop. An operational tool was developed to backward-estimate degradation rate constants, and three pesticides were selected to perform example simulations.

RESULTS

The simulation results of thiamethoxam indicated that the growth dynamics of the potato had a significant impact on the degradation kinetic estimates when the pesticide was applied during the early growth stage, as the size of the potato determined the uptake and elimination kinetics via diffusion. Using mepiquat, we demonstrated that geographical variations in weather conditions and soil properties led to significant differences in the dissipation kinetics in both potato plants and soil, which propagated the variability of the degradation rate constant. Simulation results of chlorpyrifos differed between two reported field studies, which is due to the effect of the vertical distribution of the residue concentration in the soil, which is not considered in the majority of recent studies.

CONCLUSIONS

Our proposed approach is adaptable to plant growth dynamics, preharvest intervals, and multiple pesticide application events. In future research, it is expected that the proposed method will enable region-specific inputs to improve the estimation of the degradation kinetics of pesticides in plants. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Modeling banana uptake of pesticides by incorporating a peel-pulp interaction system into a multicompartment fruit tree model

According to field research, banana peels have a significant impact on the uptake of pesticide residues by banana pulps. To predict pesticide residue concentrations in harvested bananas, however, current modeling approaches did not take into consideration the banana peel as a single simulating compartment. To address the problem, we incorporated a peel-pulp interaction system into a modified multicompartment fruit tree model in order to simulate pesticide residue concentrations in banana plants. The simulation results revealed that lipophilicity played a crucial role in regulating pesticide bioaccumulation in banana plants, showing that moderately- or highly-lipophilic compounds had a high potential for bioaccumulation in banana pulps and peels. Some model inputs, such as peel thickness, degradation rates in plant tissues, and dissipation rates in the soil, had a substantial impact on the bioaccumulation of pesticides in banana pulps and peels. Even if more aspects (such as dynamically morphological properties of banana plants and ionizable chemical compounds) must be considered for in future research, the proposed modeling approach can aid in the comprehension of the pesticide bioaccumulation mechanism in banana plants.

Modeling pesticide residue uptake by leguminous plants: a geocarpic fruit model for peanuts

BACKGROUND

Pesticide residues are frequently found in leguminous plants; however, no modeling approaches predict residue concentrations in edible legume seeds. In this study, a geocarpic fruit model, simplified for neutral organic compounds, was proposed for high-throughput simulations (over 700 pesticides) of the residue uptake by peanut plants, which characterized three scenarios, namely (i) pesticide foliar application during the pre-seed development stage, (ii) foliar application during the seed development stage, and (iii) soil contamination before plant germination.

RESULTS

In the foliar application scenario, in general, lipophilic pesticides have high simulated residue unit doses (RUDs, residue concentrations in plants per 1.0 kg ha^-1 of pesticide application) in peanut leaves owing to intensified uptake via surface deposition, whereas hydrophilic pesticides have high simulated RUDs in peanuts because the uptake of residues via diffusion is enhanced. For the soil-contamination scenario, organic compounds with moderate lipophilicity have a high bioconcentration potential (i.e. the soil-plant system) in leaves and peanuts, due to large transpiration stream concentration factors (TSCFs) that boost the uptake via transpiration.

CONCLUSIONS

The simulation results have some degrees of agreement with field measurements, indicating that the proposed model can be used as a screening tool for dietary risk assessment of pesticides in peanuts. In future research, pH-dependent physicochemical properties (e.g. soil-water partition coefficient and TSCF) and degradation rate constants of chemicals need to be refined to improve the simulation analysis. © 2022 Society of Chemical Industry.

Dissipation kinetics, residue modeling and human intake of endosulfan applied to okra (Abelmoschus esculentus)

The non-judicious application of the harmful pesticide endosulfan on okra, one of India's most consumed vegetable crops, has resulted in the frequent detection of residues in food samples. This can lead to resistance and the resurgence of various pests and diseases. In this context, combined dissipation and residue dynamics of different endosulfan components or mixtures (isomers and metabolites) in crop compartments are not yet well understood. To address this research gap, the present study evaluates the dissipation and persistence behavior of different endosulfan isomers (alpha-, beta-isomers) and major metabolite (endosulfan sulfate) on okra during 2017 and 2018. The half-life of endosulfan on okra leaves was found to be between 1.79 and 3.47 days. Half of the endosulfan deposits on okra fruits at the recommended doses were dissipated after 2.39 days compared to 1.99 days at double recommended doses (mean of 2017 and 2018 residue data). Measured endosulfan residues were evaluated against the dynamic plant uptake model dynamiCROP. The better fits were observed between modeled and measured residues for fruits (R² from 0.84 to 0.96 and residual standard error (ER) between 0.6 and 1.47) as compared to leaves (R² from 0.57 to 0.88). We also report fractions of endosulfan components ingested by humans after crop harvest. Intake fractions range from 0.0001-7.2 g_intake/kg of applied pesticide. Our results can evaluate pesticide residues in different crops grown for human consumption, including their isomers and metabolites. They can be combined with dose-response information to evaluate human exposure and/or health risk assessment.

Modeling plant uptake of organic contaminants by root vegetables: The role of diffusion, xylem, and phloem uptake routes

The uptake of organic contaminants by root vegetables involves diffusion, transport by xylem and phloem saps, degradation, and volatilization. To understand the role of uptake and elimination routes in the bioconcentration modeling of organic contaminants, a two-compartment uptake model (root and leaf compartments) was proposed. The results showed that for the root compartment, logarithm values of bioconcentration factors (log BCF, the concentration ratio between plant tissues and soil) of chemicals fell within a narrow range when the logarithm of octanol-water partition coefficient (log K_OW) was less than 3.0, whereas log BCF values decreased rapidly with increasing log K_OW values when log K_OW was greater than 3.0. This is because the diffusion route had a significant impact on the root uptake of chemicals, wherein the first-order rate constant dropped rapidly for high-lipophilicity chemicals, resulting in very low log BCF values. For the leaf compartment, chemicals with moderate lipophilicity (log K_OW of 3.0-4.0) had the highest simulated log BCF values. This is because moderate log K_OW values generated the highest transpiration stream concentration factors (TSCFs, the concentration ratio between xylem or phloem saps and water), resulting in high uptake efficiency of chemicals by leaves. Furthermore, we improved the uptake model by considering the surface-deposition route for pesticides (foliar spray), and the simulation results indicated that this uptake route cannot be neglected for lipophilic compounds. Although the simulations agreed with an experimental study and some reported data, future studies should focus on factors, such as plant physiology (plant varieties, periderm effects and compositions of xylem and phloem saps) and environmental conditions (soil properties and weather conditions), to improve the plant uptake model.

Modeling pesticide residues in nectar and pollen in support of pesticide exposure assessment for honeybees: A generic modeling approach

Pesticide residues in nectar and pollen of plants can damage honeybees; however, few modeling approaches have simulated residue levels in nectar and pollen in support of exposure assessment for honeybees. This study introduced a generic modeling approach based on plant uptake models and simple partitioning rules that specifies soil incorporation and foliar spray application scenarios of pesticides and is flexible for conducting variability analysis for various environmental conditions, pesticide application patterns, chemical individuals, and plant varieties. The results indicated that, in general, systemic or moderate lipophilicity (log K_OW of ~2.5) pesticides have relatively high simulated residue levels in nectar and pollen because of the enhanced residue uptake process from soil. For non-systemic or highly lipophilic pesticides, the residue uptake via leaf surface deposition pathway can be enhanced, and more residues will be bioaccumulated in pollen than nectar due to a relatively high lipid content of pollen (as compared to nectar), but the overall residue levels in nectar and pollen are lower than systemic or moderately lipophilic pesticides. The variability analysis showed that environmental conditions, pesticide application patterns, chemical properties, and plant varieties cause considerable variations in simulated residue levels in nectar and pollen, indicating that spatiotemporal, chemical, and plant-related factors must be considered in pesticide exposure assessment for honeybees. Moreover, the comparison between the simulated and measured data showed a high degree of consistency, indicating that the proposed model could be used to conduct a screening-level pesticide exposure assessment for honeybees.

Quantifying exposure source allocation factors of pesticides in support of regulatory human health risk assessment

One of the challenges while assessing the aggregate exposure risk of pesticides is quantifying exposure doses from various exposure pathways. To address this issue, a regulatory screening approach is proposed for evaluating pesticide allocation factors (AFs) for major exposure pathways for rural and urban residents. This was achieved by integrating dynamiCrop and other screening models to estimate the potential human intake of residues from major crops at harvest, livestock products, and main environmental media (air, water, and soil). The AFs were calculated from the average daily dose factors (ADDFs) of pesticides via major exposure pathways, where a large AF of an exposure pathway indicates that a greater margin of exposure should be given to that exposure pathway. The simulated results for many current-use pesticides showed that the ingestion of crops had pesticide AFs close to 1.0, which indicated that the crop exposure pathway contributed to a significant portion of the total exposure to pesticides. In contrast, for legacy pesticides with high lipophilicity and low degradability in the environment, the simulated AFs for major environmental compartments (air, freshwater, and soil) accounted for relatively large exposures. As legacy pesticides have been banned globally, exposure pathways via the food web and environmental media cannot be neglected because of their high lipophilicity and environmental persistence. Although other factors such as geographical conditions and living habits should be considered to improve the spatial resolution of the model, the method proposed in this study can serve as a preliminary tool to conduct screening-level risk assessments for populations by considering the allocated exposure to pesticides via major exposure pathways.

Simulation modeling the effects of peels on pesticide removal from potatoes during household food processing

The impact of crop peels on reducing pesticide residue levels in crops during household food processing was evaluated in this study. We proposed a series of pesticide fate models to simulate the removal efficiency of residues in crop peels and medullas (i.e., pulps) via soaking and washing. The simulated results indicated that the variation in the peel thickness had a significant impact on residue removal from the peel compartment. However, the peel compartment had a low impact on the removal efficiency of pesticide residues from the medulla compartment, as demonstrated by the simulated results from the non-peel model (i.e., already peeled crops). In addition, we observed that even though systemic pesticides have a higher potential to penetrate from the peel into the medulla, the increasing residue level caused by the mass transfer from the peel into the medulla is too low to cause human health damage, because the absolute mass of residues in the peel is considerably small. Based on the simulation results, we concluded that washing or soaking crops with or without peels using water is not effective in reducing residue levels in crop medullas. Modifying crops into slices, instead of directly washing or soaking crops, could significantly improve the removal efficiency of pesticide residues inside the medulla. The models proposed in this study can improve our understanding on the fate of pesticides in crops during household food processing.

Improving pesticide fate models for a simple household food processing: considering multiple crop units

To understand the fate of pesticides in crops during household cooking processes and human health risks associated with the ingestion of pesticide-contaminated crops, we propose unit-variability-enhanced models, which are capable of evaluating the removal efficiency of pesticides in multiple crop units by soaking in water. The approach integrates the lognormal production model to reveal the modeling mechanics of internal contamination among two crop units in one soaking bowl. The simulated results for 197 pesticides indicate that pesticides with larger unit-to-unit variability factors (VF) at the residue levels and diffusivity rates in water (D_W) are more likely to cause internal contamination. Although internal contamination of pesticide residues between two crop units may occur, we find that the overall removal factor ([Formula: see text]) for two crop units is independent of the ratio of initial residue levels between the two crop units. Based on this discovery, we propose the unit-variability-based (UVB) rule to generalize the [Formula: see text] for an n-crop-unit system, where n crop units soak simultaneously in one container. In addition, we demonstrate that under the same consumable and recycling resources, the soaking of two crop units together in one container can yield a maximum mass removal of pesticides if the two units are randomly sampled. Although other factors, such as temperature and the nature of solutions in the cooking process, should be considered in future studies, our models suggest that this soaking method can be conveniently realized in households to reduce negative health effects.

Nanopesticide Formulation from Pyraclostrobin and Graphene Oxide as a Nanocarrier and Application in Controlling Plant Fungal Pathogens

Efficient and environment-friendly nanopesticide delivery systems are critical for the sustainable development of agriculture. In this study, a graphene oxide nanocomposite was developed for pesticide delivery and plant protection with pyraclostrobin as the model pesticide. First, graphene oxide-pyraclostrobin nanocomposite was prepared through fast adsorption of pyraclostrobin onto graphene oxide with a maximum loading of 87.04%. The as-prepared graphene oxide-pyraclostrobin nanocomposite exhibited high stability during two years of storage, suggesting its high potential in practical application. The graphene oxide-pyraclostrobin nanocomposite could achieve temperature (25 °C, 30 °C and 35 °C) and pH (5, 7 and 9) slow-release behavior, which overcomes the burst release of conventional pyraclostrobin formulation. Furthermore, graphene oxide-pyraclostrobin nanocomposite exhibited considerable antifungal activities against Fusarium graminearum and Sclerotinia sclerotiorum both in vitro and in vivo. The cotoxicity factor assay revealed that there was a synergistic interaction when graphene oxide and pyraclostrobin were combined at the ratio of 1:1 against the mycelial growth of Fusarium graminearum and Sclerotinia sclerotiorum with co-toxicity coefficient values exceeding 100 in vitro. The control efficacy of graphene oxide-pyraclostrobin nanocomposite was 71.35% and 62.32% against Fusarium graminearum and Sclerotinia sclerotiorum in greenhouse, respectively, which was higher than that of single graphene oxide and pyraclostrobin. In general, the present study provides a candidate nanoformulation for pathogenic fungal control in plants, and may also expand the application of graphene oxide materials in controlling plant fungal pathogens and sustainable agriculture.

Improved plant bioconcentration modeling of pesticides: The role of periderm dynamics

BACKGROUND

There is a continuous need to advance pesticide plant uptake models in support of improving pest control and reducing human exposure to pesticide residues. The periderm of harvested root and tuber crops may affect pesticide uptake, but is usually not considered in plant uptake models. To quantify the influence of the periderm on pesticide uptake from soil into potatoes, we propose a model that includes an explicit periderm compartment in the soil-plant mass balance for pesticides.

RESULTS

Our model shows that the potato periderm acts as an active barrier to the uptake of lipophilic pesticides with high K_OW , while it lets more lipophobic pesticides accumulate in the medulla (pulp). We estimated bioconcentration factors (BCFs) for over 700 pesticides and proposed parameterizations for including the effects of the periderm into a full plant uptake modeling framework. A sensitivity analysis shows that both the degradation half-life inside the tuber and the lipophilicity drive the contributions of other aspects to the variability of BCFs, while highlighting distinct dynamics in the periderm and medulla compartments. Finally, we compare model estimates with measured data, showing that predictions agree with field observations for current-use pesticides and some legacy pesticides frequently found in potatoes.

CONCLUSION

Considering the periderm improves the accuracy of quantifying pesticide uptake and bioconcentration in potatoes as input for optimizing pest control and minimizing human exposure to pesticide residues in edible crops.

Regulation of pesticide soil standards for protecting human health based on multiple uses of residential soil

To help environmental agencies manage pesticides in residential soil and reduce the associated risks to human health, we developed a screening-level framework that derives pesticide soil standards (PSSs) while considering the multiple uses of residential soil. Our screening models simulated the risk from exposure to soil pesticides via direct and three major indirect (i.e., tuber crops, animal-sourced food, and groundwater) exposure pathways. Based on these models, we derived PSSs for five types of residential soil. Our results showed that, in general, indirect pathways contributed more than the direct pathway to the overall exposure to soil pesticides. Consequently, in rural environments, where residential soil is also subjected to activities such as agriculture, animal grazing, and groundwater consumption, the derived PSSs were low. In addition, we compared the derived PSSs to the current worldwide standards for 13 commonly used pesticides. We found that the current global PSSs were appropriate only for urban residential soil. In many rural environments where the boundaries between different soil uses may be indistinct, the current PSSs are insufficient to protect humans from exposure to soil pesticides. Based on this analysis and the proposed PSSs, we provide regulatory recommendations for the management of pesticides in various types of residential soils.

Improving pesticide uptake modeling and management in potatoes: A simple and approximate phloem-adjusted model

To evaluate the impact of the phloem flux on the pesticide uptake process in potatoes, this study developed a phloem-adjusted model based on the classic model that focuses mainly on the diffusion process. To achieve high-throughput simulations, we introduced an approximate method to convert the phloem flux transport process into a simple specific uptake rate of pesticides. In comparison to the classic model (non-phloem model), the phloem-adjusted model generated higher pesticide concentrations and bioconcentration factors (BCFs) in potatoes, owing to the additional pesticide uptake route introduced to the adjusted model. However, the simulation, which was conducted for 740 pesticides, indicated that for most pesticides, the phloem flux route did not contribute a significant portion of the pesticide uptake to potato tubers compared with the soil diffusion route. This was further characterized, using the differential factor (DF), to evaluate the difference in the simulated results between the proposed model and classic models. The largest DF (~0.11) was obtained for pesticides with moderate lipophilicity (i.e., log K_OW of 3.0), indicating that only a difference of 10% was generated between the two models. The 10% increase in pesticide concentration (or BCFs) in potatoes, simulated by the phloem-adjusted model, was within the acceptable uncertainty interval of the classic model, thus confirming the validity of using the classic model to predict the pesticide uptake process in potato tubers. However, we found that the negligibility of the phloem flux route was not merely due to hydrophobicity (i.e., hypothesis of the classic model), but was related to the i) plant physiology of potatoes, ii) lipophilicity of a pesticide, and iii) the diffusivity of a pesticide in water. Although future studies on pesticide concentrations in phloem sap and the dynamic growth of potatoes need to be undertaken, the model developed in this study reveals a more comprehensive pesticide uptake process in potatoes, which can promote the understanding of the pesticide uptake mechanism in potatoes.

Modeling pesticides in global surface soils: Evaluating spatiotemporal patterns for USEtox-based steady-state concentrations

To better manage pesticide pollution in surface soils, we introduced a first-order-kinetics-based screening model to evaluate the steady-state concentrations of pesticides in surface soils while considering degradation, volatilization, plant uptake, and precipitation processes. For each process, we developed a spatiotemporal-pattern-based model using spatiotemporal variables, including air temperature (T_A), relative humidity (RH_A), and rainfall intensity (I_R^A), to characterize the overall dissipation rates (k_T) of pesticides in the soil. These dissipation rates were converted to fate factors (FFs), which are commonly used in life cycle analyses. The results indicate that, in general, the k_T values increase with increasing T_A and I_R^A and decrease with increasing RH_A. This is because increased T_A boosts the degradation, volatilization, and plant uptake processes, whereas increased RH_A lowers the plant transpiration rate. Also, the simulation for over 700 pesticides indicated that the degradation process dominates the overall dissipation of most pesticides in the soil, and the volatilization process contributes the least. In addition, we simulated chlorpyrifos FFs for Brazil, China, the US, and the European Union (EU) using the annual average T_A, RH_A, and I_R^A values. The results indicate that, in general, Brazilian federal units have the smallest FFs and the narrowest simulated FF range because of their humid tropical climates. Meanwhile, the EU member states have the largest FFs and the widest FF range because of their range in locations. In addition, our simulated results show that the surface soils in the high-latitude regions could accumulate more chlorpyrifos than those in low-latitude regions because of the larger simulated FFs. Furthermore, we parameterized our model using 737 pesticides with the USEtox, thereby providing an alternative approach to simulate the steady-state concentration of pesticides in surface soils from the USEtox available data. The model developed herein is a useful screening tool for predicting pesticide concentrations in surface soil worldwide to improve soil and ecological health risk management.

Improving screening model of pesticide risk assessment in surface soils: Considering degradation metabolites

As pesticides can be degraded to toxic metabolites in the soil, metabolite toxicity should be considered in human health risk assessments. In this study, a screening-level modeling framework was developed to manage pesticides in surface soil, which was discussed under discrete and continuous emission scenarios. In addition, we selected glyphosate and its major metabolite (aminomethylphosphonic acid or AMPA) as examples to conduct screening-level risk management at regional, national, and global scales. The results indicated that if soil AMPA were not considered, human health risks could be significantly underestimated because of the large half-life of AMPA in the soil. For example, the added concentration factors of AMPA were simulated as 0.19 and 6.72 considering all major elimination pathways and considering the degradation pathway alone, respectively, indicating that AMPA formation could lead to severe extra health burdens. Furthermore, the evaluation of current glyphosate soil standards suggested that toxic metabolites should be considered in the regulatory process; otherwise, many standards could theoretically trigger high levels of soil AMPA, which could result in serious human health damage. Our proposed screening-level model can help to improve risk assessment and regulatory management of pesticides in surface soils.