The genetically modified maize MON89034 × MON88017 expresses different crystal (Cry) proteins with pesticidal activity against the European corn borer (Cry1.105; Cry2Ab2) and the Western corn root worm (Cry3Bb1). Non-target organisms, such as soil nematodes, might be exposed to the Cry proteins that enter the soil in course of crop growing. Therefore, the risk of those proteins for nematodes was assessed by testing their toxic effects on Caenorhabditis elegans. All three insecticidal Cry proteins showed dose-dependent inhibitory effects on C. elegans reproduction (EC50: 0.12–0.38 μmol L−1), however, at concentrations that were far above the expected soil concentrations. Moreover, a reduced toxicity was observed when Cry proteins were added jointly. A C. elegans mutant strain deficient for receptors for the nematicidal Cry5B was also resistant against Cry1.105 and Cry2Ab2, suggesting that these Cry proteins bound to the same or similar receptors as nematicidal Cry proteins and thereby affect the reproduction of C. elegans.

Evaluation of a field scale agricultural nonpoint source simulation model against field experiment data is an important step that must be considered before a model can be used as a management tool. Field soil water content and metribuzin residue adsorbed in soil profile were intensively monitored and measured by the gravimetric method and the LC-MS/MS method, respectively, for a soybean field plot located at the Asian Institute of Technology, Thailand. The Root Zone Water Quality Model (RZWQM) was evaluated based on laboratory-measured soil hydraulic properties and pesticide residue in Bangkok clay soil. Reasonable agreement exists between the soil water content measured and predicted by RZWQM for 10–20 and 30–40 cm soil depths. The model slightly overestimated the pesticide residue at 0–10 cm soil depth 1 day after application at surface, whereas pesticide residue at 10–20 and 30–40 cm soil depths was in agreement with model acceptance. These results indicate that RZWQM can be used when properly calibrated to predict the movement of water and metribuzin through the soil profile in the tropical zone.

Pesticides occupy a critical position among many chemicals to which man can be exposed; their diffusion into the environment causes killing and damaging of some forms of life. The lack of highly selective pesticide action represents risk both for man and other desirable forms of life present in the environment. The present study was designed to evaluate the relation between exposure to pesticides and disorder on hematological parameters and kidney function of male agricultural workers with the mean age 37.11 ± 9.3. Another 100 unexposed men matched for age, and socioeconomic status were recruited as a control to compare the levels of hemoglobin, hematocrit, red blood cells (RBCs), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and urea and creatinine concentration. The results indicate that there was no significant difference in hemoglobin concentration and hematocrit value among exposed group as compared to control group. However, there was a significant decrease (P < 0.05) in the RBCs count and a highly significant increase (P < 0.01) in MCV among exposed group. There was no significant difference in MCH and MCHC among exposed group. There was a significant increase (P < 0.05) in urea (39.4 ± 22 mg/dl) among exposed group as compared to control (35.7 ± 26.3 mg/dl). Also, there was a highly significant increase (P < 0.01) in creatinine among exposed group (0.953 ± 0.3 mg/dl) as compared to control (0.8 ± 0.2 mg/dl). In conclusion, exposure to pesticides produces a variety of hematological parameter disorders as well as kidney malfunction in human.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

The adsorption of 12 pesticides of the phenylurea family was studied by batch experiments in order to determine the adsorption coefficient, K d. The study was conducted in two soils chosen for their differences in organic matter and calcite contents. K d pesticide adsorption coefficients were higher for soil S1 than for soil S2 due to the presence of a higher organic matter content and a lower calcite content in soil S1. To identify pesticide properties governing retention, 18 molecular descriptors were considered. Class-specific quantitative structure–property relationship (QSPR) soil sorption models using one, two, and three descriptors were developed from our experimental data using linear regressions. One of the aims of this work was to check whether QSPR models that did not include literature values of K ₒw were able to predict K d coefficients in satisfactory agreement with our experimental data. The influence of the level of theory in determining K ₒw and polarisability predictors on the predictive performance of the model was also examined by comparing quantum chemistry and empirical (QikProp) approaches. The one-descriptor model using “quantum” polarisability α was found to perform almost as well as or better than the other models.

Forty pesticides were selected in function of their chemical families and their physico-chemical properties to represent a wide range of pesticide properties. Adsorption of these pesticides was studied on two soils by batch experiments. The two soils differed largely in organic matter and calcite contents. Distribution coefficient Kdwas determined for each pesticide on the two soils. Adsorption was higher for the soil having the highest organic matter content and the lowest calcite content. In order to identify pesticide properties governing retention, eight molecular descriptors were determined from three-dimensional (3D) structure of molecules. Class-specific quantitative structure properties relationship (QSPR) soil adsorption models using one and two parameters were developed from experimental Kd. Three properties seemed to influence most retention of pesticides: hydrophobicity, solubility, and polarisability. Models combining these properties were suggested and discussed.