The contamination of phytopharmaceuticals and herbal teas with toxic plants is an increasing problem. Senecio vulgaris L. is a particularly noxious weed in agricultural and horticultural crops due to its content of toxic pyrrolizidine alkaloids (PAs). Since some of these compounds are carcinogenic, the distribution of this plant should be monitored. The amount of PAs in S. vulgaris is affected by various factors. Therefore, we investigated the occurrence of PAs depending on the developmental stage and season. A systematic study using field-plot experiments (four seasons, five developmental stages of the plants: S1 to S5) was performed and the PA concentration was determined via LC-MS/MS analysis. The total amount of PAs in the plant increased with the plant development, however, the total PA concentrations in µg/g dry matter remained nearly unchanged, whilst trends for specific PAs were observed. The concentrations of PA-N-oxides (PANOs) were much higher than that of tertiary PAs. Maximal amounts of the PA total were 54.16 ± 4.38 mg/plant (spring, S5). The total amount of PAs increased strongly until later developmental stages. Therefore, even small numbers of S. vulgaris may become sufficient for relevant contaminations set out by the maximal permitted daily intake levels recommended by the European Food Safety Authority (EFSA).
<p>Surface runoff from agricultural fields is a major input pathway of pesticides into surface waters. The aim of this project was to i) analyze the effectiveness of various mitigation measures to reduce pesticide runoff and erosion inputs into surface waters, ii) assess the suitability of the measures found effective for use in the quantitative environmental exposure assessment for authorization of plant protection products (PPP), and iii) make recommendations how the potentially suitable measures could be applied in risk assessment of PPP in Germany.</p><p>Following a literature analysis, 16 risk mitigation measures were presented to five experts in the field. Measures finally selected for quantitative analysis belong to 3 groups: vegetative filter strips (VFS), soil conservation measures (including no-till) and microdams in row crops. VFS effectiveness was analysed with CART (Classification and Regression Trees) using the dataset compiled by Reichenberger et al. (2019). CART was performed for three target variables: i) relative reduction of total inflow by the VFS (&#916;Q), ii) relative reduction of sediment load (&#916;E), and relative reduction of pesticide load (&#916;P). The main data sources for soil conservation measures were a plot database with annual runoff volumes and soil losses (Maetens et al., 2012), a literature review (Fawcett et al., 1994) and a field study with event-based data (Erlach, 2005), while for microdams the principal source were the data compiled by Sittig et al. (2020).</p><p>The following conclusions were drawn from the analysis:</p><p>VFS can be recommended for application in quantitative risk assessment.&#160; However, infiltration and sedimentation should be simulated with a mechanistic model such as VFSMOD.</p><p>Due to the high variability of results and limited availability of high-quality data, effectiveness of mulch-till could not be quantified sufficiently well. It can therefore not be recommended for now as a regulatory mitigation measure.</p><p>Before recommending no-till as a regulatory mitigation measure for surface runoff and erosion, the question of potentially increased pesticide loss via leaching and drainage should be clarified.</p><p>Microdams in row crops can also be recommended as a regulatory mitigation measure, since they have shown to be effective and their effect can be modelled as a reduction of the runoff Curve Number. However, elaborating a CN table for e.g. the FOCUS scenarios would require an in-depth analysis of the available data.</p>
BACKGROUNDOne of the most important sources of pesticide pollution of surface waters is runoff and erosion from agricultural fields after rainfall. This study analyses the efficacy of different risk mitigation measures to reduce pesticide runoff and erosion inputs into surface waters from arable land excluding rice fields.RESULTSThree groups of risk mitigation measures were quantitatively analyzed: vegetative filter strips, micro‐dams in row crops and soil conservation measures. Their effectiveness was evaluated based on a meta‐analysis of available experimental data using statistical methods such as classification and regression trees, and exploratory data analysis. Results confirmed the effectiveness of vegetative filter strips and micro‐dams. Contrary to common assumption, the width of vegetative filter strips alone is not sufficient to predict their effectiveness. The effectiveness of soil conservation measures (especially mulch‐tillage) varied widely. This was in part due to the heterogeneity of the available experimental data, probably resulting from the inconsistent implementation and the inadequate definitions of these measures.CONCLUSIONBoth vegetative filter strips and micro‐dams are effective and suitable, and can therefore be recommended for quantitative assessment of environmental pesticide exposure in surface waters. However, the processes of infiltration and sedimentation in vegetative filter strips should be simulated with a mechanistic model like Vegetative Filter Strip Modeling System, VFSMOD. The reduction effect of micro‐dams can be modelled by reducing the runoff curve number, e.g., in the pesticide root zone model, PRZM. Soil conservation measures are in principle promising, but further well‐documented data are needed to determine under which conditions they are effective. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
<p>Surface runoff from agricultural fields is a major input pathway of pesticides into surface waters. The aim of this project was to i) analyze the effectiveness of various mitigation measures to reduce pesticide runoff and erosion inputs into surface waters, ii) assess the suitability of the measures found effective for use in the quantitative environmental exposure assessment for authorization of plant protection products (PPP), and iii) make recommendations how the potentially suitable measures could be applied in risk assessment of PPP in Germany. Following a literature analysis, 16 risk mitigation measures were presented to five experts for evaluation of effectiveness, cost-effectiveness, controllability, current distribution and dissemination potential. Measures finally selected for quantitative analysis belong to 3 groups: vegetative filter strips (VFS), soil conservation measures and micro-dams in row crops. Subsequently, the effectiveness of the recommended measures was evaluated based on experimental data using different statistical methods (e.g. CART, MLR, graphical methods).</p><p>The quantitative analysis confirmed the effectiveness of VFS and micro-dams. For soil conservation measures (especially mulch-till), the evaluated data showed highly variable results. This was partly caused by the heterogeneity of the experimental data, which also made it difficult to aggregate the results of different studies.</p><p>The following conclusions were drawn: Both VFS and micro-dams can be recommended for application in quantitative environmental exposure assessment for pesticides.&#160; However, infiltration and sedimentation in VFS should be simulated with a mechanistic model such as VFSMOD. The effect of micro-dams can be modelled as a reduction of the runoff Curve Number (CN). The runoff modelling should be carried out with a model such as PRZM which adjusts the CN daily based on soil water content.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.