Leah S. Riter

Agricultural and digital innovations are advancing rapidly, creating new opportunities to explore how regulatory review processes can become more efficient, transparent, and scalable while maintaining rigorous oversight. This perspective introduces Rules-as-Code (RaC), the practice of translating regulatory requirements into machine-executable logic as a mechanism to realize this transition. Two case studies illustrate how RaC can support automated compliance checks in pesticide and crop biotechnology risk assessments. By providing a standardized digital representation of regulatory requirements, RaC offers a framework to enhance consistency, efficiency, and regulatory preparedness in an increasingly data-rich scientific landscape.

Validation of analytical methods to assess figures of merit and other key performance parameters is a fundamental requirement within the fitness-for-purpose concept. By combining generative AI and subject matter review, this perspective article provides insights into analytical trends, technological advancements, and the current state of analytical reporting with respect to validation of published pesticide residue methods involving mass spectrometry in agricultural applications. Reporting trends of analytical parameters and technological advancements were evaluated across a data set of 391 studies published in the Journal of Agricultural and Food Chemistry from 1970 to 2024. This feasibility study demonstrated that with properly optimized prompts and performance verification, AI can efficiently and accurately evaluate scientific literature.

Dicamba is an important herbicide for controlling post-emergent resistant weeds in soybean farming. Recently, the scientific community and general public have further examined off-target transport mechanisms (e.g., spray drift, volatilization, and tank contamination) and the visual responses of soybeans to ultralow dicamba concentrations. This paper synthesizes key chemical concepts and environmental processes associated with dicamba formulations, transport mechanisms, drift measurements, and plant responses. This paper proposes additional areas of research and actions to increase our understanding and communicate the science findings, which should provide farmers with more robust tools and practices for sustainable dicamba use.

This study summarizes 23 field trials (over 6 geographic locations, with each trial comprised of a separate field site and application event) for quantifying the post-application volatilization of dicamba from fields treated with an array of dicamba-containing formulations and tank adjuvants at application rates of 0.56 or 1.12 kg dicamba acid equivalents (a.e.) per hectare (0.5 or 1.0 lb dicamba a.e. per acre). The data span three years of testing over a range of locations, field types, and environmental conditions. The Aerodynamic (AD) and the Integrated Horizontal Flux (IHF) methodologies were employed (and then averaged) for estimating the vertical flux from the field, for periods extending to approximately 72 hrs post application. In all cases, the vertical flux peaked within 24 hrs of application and then decayed to much lower levels by day three. Total volatile losses among all formulations and conditions ranged from 0.023% ± 0.003% to 0.302% ± 0.045% of the applied dicamba (median = 0.08%). Analysis of the recorded meteorological and soil conditions for each field trial failed to identify any single soil or weather parameter as a dominant driver of flux. Air concentrations of dicamba observed in the course of these trials were all below the NOAEC (No Observed Adverse Effect Concentration) for conventional soybean plant height or yield, indicating that air concentrations directly above or outside of the dicamba-treated area would not cause a reduction in plant height or yield of conventional soybean.

Quantitative assessment of the volatility of field applied herbicides requires orchestrated sampling logistics, robust analytical methods, and sophisticated modeling techniques. This manuscript describes a comprehensive system developed to measure dicamba volatility in an agricultural setting. Details about study design, sample collection, analytical chemistry, and flux modeling are described. A key component of the system is the inter-laboratory validation of an analytical method for trace level detection (limit of quantitation of 1.0 ng/PUF) of dicamba in polyurethane foam (PUF) air samplers. Validation of field sampling and flux methodologies was conducted in a field trial that demonstrated agreement between predicted and directly measured dicamba air concentrations at a series of off-target locations. This validated system was applied to a field case study on two plots to demonstrate the utility of these methods under typical agricultural conditions. This case study resulted in a time-varying volatile flux profile which showed that less than 0.2 ±0.05% of the applied dicamba was volatilized over the three-day sampling period.

Dramatic process-efficiency gains for residue analysis of glyphosate in raw agricultural commodities (RACs) were achieved by development and validation of a two-stage fine-milling process. This secondary milling produced a uniform and consistent product that could be reproducibly measured with 75 mg analytical test portions. The milligram scale sample size enabled the direct weighing of sample into a liquid-handler-compatible 96-well format. A high-throughput workflow based on this innovative comminution approach for the quantitation of glyphosate, a nonselective herbicide, and its main degradation product, aminomethylphosphonic acid, was validated in various RACs and used to demonstrate the applicability of the two-step milling process. The precision and reproducibility of 75 mg analytical portions taken through this assay was used to demonstrate the feasibility of using a two-stage fine-milling technique for pesticide residue applications. An RSD of less than 10% was achieved in endogenous glyphosate residues in multiple RACs. Comparable recoveries and superior precision were achieved with this new method as compared with a validated 10 g scale method.