Structure-Energetics-Property Relationships Support Computational Design of Photodegradable Pesticides

Systematic approaches to machine learning models for predicting pesticide toxicity

Pesticides play an important role in modern agriculture by protecting crops from pests and diseases. However, the negative consequences of pesticides, such as environmental contamination and adverse effects on human and ecological health, underscore the importance of accurate toxicity predictions. To address this issue, artificial intelligence models have emerged as valuable methods for predicting the toxicity of organic compounds. In this review article, we explore the application of machine learning (ML) for pesticide toxicity prediction. This review provides a detailed summary of recent developments, prediction models, and datasets used for pesticide toxicity prediction. In this analysis, we compared the results of several algorithms that predict the harmfulness of various classes of pesticides. Furthermore, this review article identified emerging trends and areas for future direction, showcasing the transformative potential of machine learning in promoting safer pesticide usage and sustainable agriculture.

Effects of Microplastics on the Transport of Soil Dissolved Organic Matter in the Loess Plateau of China

Microplastics (MPs) pollution and dissolved organic matter (DOM) affect soil quality and functions. However, the effect of MPs on DOM and underlying mechanisms have not been clarified, which poses a challenge to maintaining soil health. Under environmentally relevant conditions, we evaluated the major role of polypropylene particles at four micron-level sizes (20, 200, and 500 μm and mixed) in regulating changes in soil DOM content. We found that an increase in soil aeration by medium and high-intensity (>0.5%) MPs may reduce NH4+ leaching by accelerating soil nitrification. However, MPs have a positive effect on soil nutrient retention through the adsorption of PO43- (13.30-34.46%) and NH4+ (9.03-19.65%) and their leached dissolved organic carbon (MP-leached dissolved organic carbon, MP-DOC), thereby maintaining the dynamic balance of soil nutrients. The regulating ion (Ca2+) is also an important competitor in the MP-DOM adsorption system, and changes in its intensity are dynamically involved in the adsorption process. These findings can help predict the response of soil processes, especially nutrient cycling, to persistent anthropogenic stressors, improve risk management policies on MPs, and facilitate the protection of soil health and function, especially in future agricultural contexts.

Stability Study and Handling Recommendations for Multiresidue Pesticide Mixes under Diverse Storage Conditions for LC-MS/MS and GC-MS/MS

BACKGROUND

In response to the growing global need for pesticide residue testing, laboratories must develop versatile analytical methods and workflows to produce scientifically sound results. One of the many challenges faced by food chemists is acquiring suitable pesticide certified reference materials (CRMs) to calibrate analytical equipment, monitor method performance, and confirm the identity and concentration of hundreds of pesticide residues in food samples. CRM producers invest considerable resources to ensure the stability of their products.

OBJECTIVE

To present proper CRM handling and storage practices as guidance to ensure stability based on the results of several multiresidue pesticide stability studies.

METHODS

The open ampoule and combined multiresidue mix studies were conducted under controlled conditions. New ampoules containing multiresidue pesticide CRM mixtures were opened and compared to previously opened ampoules at multiple intervals while stored under freezing and refrigerated temperatures. Both LC- and GC-amenable pesticides (>200 residues) were combined and stored under typical laboratory conditions. Studies were performed with and without celery matrix.

RESULTS

The open ampoule study showed high levels of stability for all mixtures. All GC residues remained stable over the duration of the experiment. A week after opening LC multiresidue pesticide mixtures showed minor degradation. After combination of the multiresidue pesticide mixtures, degradation occurred rapidly for both the GC and LC mixtures.

CONCLUSION

Multiresidue pesticide mixtures are stable as ampullated until they are opened. Once the contents of a kit were opened and combined, decreasing stability was observed over time. This was true for both the LC and GC kits. Working mixtures of CRMs for instrument calibration should be made daily.

HIGHLIGHTS

This article shows a novel approach for measuring stability of CRM mixes. In-depth analysis of multiresidue pesticide mixtures and the stability that can be expected before and after mixing under typical storage conditions is described.

Overlooked Transformation of Nitrated Polycyclic Aromatic Hydrocarbons in Natural Waters: Role of Self-Photosensitization

Photochemical transformation is an important process that involves trace organic contaminants (TrOCs) in sunlit surface waters. However, the environmental implications of their self-photosensitization pathway have been largely overlooked. Here, we selected 1-nitronaphthalene (1NN), a representative nitrated polycyclic aromatic hydrocarbon, to study the self-photosensitization process. We investigated the excited-state properties and relaxation kinetics of 1NN after sunlight absorption. The intrinsic decay rate constants of triplet (³1NN*) and singlet (¹1NN*) excited states were estimated to be 1.5 × 10⁶ and 2.5 × 10⁸ s^-1, respectively. Our results provided quantitative evidence for the environmental relevance of ³1NN* in waters. Possible reactions of ³1NN* with various water components were evaluated. With the reduction and oxidation potentials of -0.37 and 1.95 V, ³1NN* can be either oxidized or reduced by dissolved organic matter isolates and surrogates. We also showed that hydroxyl (^•OH) and sulfate (SO₄^•-) radicals can be generated via the ³1NN*-induced oxidation of inorganic ions (OH^- and SO₄^2-, respectively). We further investigated the reaction kinetics of ³1NN* and OH^- forming ^•OH, an important photoinduced reactive intermediate, through complementary experimental and theoretical approaches. The rate constants for the reactions of ³1NN* with OH^- and 1NN with ^•OH were determined to be 4.22 × 10⁷ and 3.95 ± 0.01 × 10⁹ M^-1 s^-1, respectively. These findings yield new insights into self-photosensitization as a pathway for TrOC attenuation and provide more mechanistic details into their environmental fate.

Molecular Dynamics Simulation Prediction of the Partitioning Constants (KH, Kiw, Kia) of 82 Legacy and Emerging Organic Contaminants at the Water-Air Interface

The tendency of organic contaminants (OCs) to partition between different phases is a key set of properties that underlie their human and ecological health impacts and the success of remediation efforts. A significant challenge associated with these efforts is the need for accurate partitioning data for an ever-expanding list of OCs and breakdown products. All-atom molecular dynamics (MD) simulations have the potential to help generate these data, but existing studies have applied these techniques only to a limited variety of OCs. Here, we use established MD simulation approaches to examine the partitioning of 82 OCs, including many compounds of critical concern, at the water-air interface. Our predictions of the Henry's law constant (K_H) and interfacial adsorption coefficients (K_iw, K_ia) correlate strongly with experimental results, indicating that MD simulations can be used to predict K_H, K_iw, and K_ia values with mean absolute deviations of 1.1, 0.3, and 0.3 logarithmic units after correcting for systematic bias, respectively. A library of MD simulation input files for the examined OCs is provided to facilitate future investigations of the partitioning of these compounds in the presence of other phases.

Mechanistic Study of the Effects of Agricultural Amendments on Photochemical Processes in Paddy Water during Rice Growth

The photochemical properties of paddy water might be affected by the commonly used amendments in rice fields owing to the associated changes in water chemistry; however, this important aspect has rarely been explored. We examined the effects of agricultural amendments on the photochemistry of paddy water during rice growth. The amendments significantly influenced the photogenerated reactive intermediates (RIs) in paddy water, such as triplet dissolved organic matter (³DOM*), singlet oxygen, and hydroxyl radicals. Compared with control experiments without amendments, the application of straw and lime increased the RI concentrations by up to 16.8 and 11.1 times, respectively, while biochar addition had limited effects on RI generation from paddy water in in situ experiments under sunlight. Fluorescence emission-excitation matrix spectroscopy, Fourier transform ion cyclotron resonance mass spectrometry, and structural equation modeling revealed that upon the addition of straw and lime amendments, humified DOM substances contained lignins, proteins, and fulvic acids, which could produce more RIs under irradiation. Moreover, the amendments significantly accelerated the degradation rate of 2,4-dichlorophenol but led to the ³DOM*-mediated formation of more toxic and stable dimeric products. This study provides new insights into the effects of amendments on the photochemistry of paddy water and the pathways of abiotic degradation of organic contaminants in paddy fields.

Structure-to-process design framework for developing safer pesticides

Rational design of pesticides with tunable degradation properties and minimal ecotoxicity is among the grand challenges of green chemistry. While computational approaches have gained traction in predictive toxicology, current methods lack the necessary multifaceted approach and design-vectoring tools needed for system-based chemical development. Here, we report a tiered computational framework, which integrates kinetics and thermodynamics of indirect photodegradation with predictions of ecotoxicity and performance, based on cutoff values in mechanistically derived physicochemical properties and electronic parameters. Extensively validated against experimental data and applied to 700 pesticides on the U.S. Environmental Protection Agency's registry, our simple yet powerful approach can be used to screen existing molecules to identify application-ready candidates with desirable characteristics. By linking structural attributes to process-based outcomes and by quantifying trade-offs in safety, depletion, and performance, our method offers a user-friendly roadmap to rational design of novel pesticides.