International agencies have developed guidelines and predictive models to assess human exposure of pesticides during the application. However, these models are typically based on limited empirical data and may not accurately represent real-world spraying conditions. Moreover, they do not account for spraying equipment such as drones or wide-area sprayers, which limits their applicability under current field conditions. In this study, we quantified pesticide exposure among operators, residents, and bystanders during applications using drones and wide-area sprayers. Subsequently, the pesticide exposure test results were evaluated using exposure models developed in this study. Measured operator exposure was substantially higher during wide-area spraying than during drone-based application, primarily due to reduced working distance and differences in spray delivery mechanisms. Exposure levels among residents and bystanders were also elevated during wide-area spraying, although drone-based applications demonstrated potential for long-distance drift under specific meteorological conditions. Existing models, including EFSA, UK-POEM, BREAM2, and EUROPOEM, did not adequately account for spray aerodynamics or field variability, resulting in frequent underestimation or overestimation of exposure. Despite a limited dataset, this study provides clear insights into exposure patterns associated with both technologies and highlights the need for model refinement to accommodate emerging application methods.

This study was conducted to investigate the effects of cutting media blended with blast furnace slag (BFS) and commercial substrate (CS) on their physicochemical properties and the growth of chrysanthemum (Chrysanthemum morifolium) cutting. pH and bulk density of cutting media blending BFS were higher than those of CS, while electrical conductivity (EC) was lower. The correlation coefficient between BFS blending ratio and the pH and bulk density of media was significantly positive (p≤0.01). As compared to CS, the root length and root dry weight in CS:BFS = 1:1 treatment were increased by 54.7% and 76.2%, respectively. The root length and dry weight in the CS:BFS = 1:1 treatment were similar to those of the perlite treatment. These results indicated that the blend of BFS with CS in the chrysanthemum cutting substrate significantly enhanced the root growth of chrysanthemum cuttings, and their optimal ratio was found to be 1:1 (v/v).

This study evaluated the residual characteristics of the isoxazoline insecticide fluxametamide in lettuce leaves, roots, and soil under greenhouse conditions. The fluxametamide residue analysis method used in this study showed excellent accuracy (84.7-116.0%) and precision (RSD ≤ 5.7%), satisfying the SANTE guideline criteria, and matrix effects were within ±20%. Fluxametamide was chemically stable at temperatures between –70 and 40℃, but became vulnerable at temperatures above 60℃, with significantly reduced recovery. Residue levels decreased from 0.400 to 0.152 mg/kg in lettuce leaves and from 0.066 to 0.012 mg/kg in the roots over 10 days, while residues in soil were below the limit of quantification on the day of pesticide application. All fluxametamide residues in lettuce leaves were detected below the maximum residue limit (MRL; 10 mg/kg). The biological half-lives were 6.8 days in lettuce and 4.2 days in roots. When the dilution effect caused by crop growth was excluded, the half-lives were extended to 9.9 days and 7.2 days for lettuce and roots, respectively, although the dilution effect was less pronounced compared to rapidly growing crops. The results of this study may serve as fundamental data for the review of regulations, including MRLs and safety use standards, for fluxametamide in lettuce leaves and roots.

This study evaluated crop-livestock recycling and carbon reduction across four Hanwoo (Korean cattle) farm types: organic, PGS-certified, grazing-based ecological livestock farms, and conventional, based on surveys of 58 farms. Grazing-based ecological farm had the lowest baseline carbon emissions (4,994.3 kg CO₂-eq), largest farmland (35.7 ha), and highest forage self-sufficiency (31.6%). Organic farms had the highest emissions (6,764.8 kg CO₂-eq) but achieved the greatest reduction (15.3%) via organic feed and compost recycling. PGS-certified farms also demonstrated significant environmental benefits (6,284.8 kg CO₂-eq; 13.6% reduction). No statistically significant differences were observed in nutrient use efficiency among certification types. Expanding farmland, improving compost recycling, and increasing on-farm feed effectively reduced nutrient surplus and carbon footprint. These results suggest that organic and PGS-certified systems can serve as economically and environmentally sustainable models if they integrate on-farm forage production from the grazing-based ecological livestock farms model.

Synthetic pesticides have long contributed to global agricultural productivity over the past decades. However, the widespread reliance on chemical control strategies based on synthetic pesticides has raised serious concerns regarding pesticide resistance, non-target toxicity, environmental persistence, and the resulting decline in agricultural sustainability. In response, biopesticides have emerged as eco-friendly alternatives, among which biochemical pesticides acting as immune elicitors represent a promising new paradigm. Rather than exerting direct biocidal activity, these compounds activate plant innate immunity and thereby confer durable resistance with minimal ecological impact. Among immune elicitors, cell wall- and cuticle-derived damage-associated molecular patterns (hereafter, CW-DAMPs, as used in this review) are increasingly recognized as key endogenous signals linking structural integrity sensing to immune activation. Upon damage to the extracellular barrier, CW-DAMPs are released and recognized by cell-surface pattern recognition receptors (PRRs), which initiate downstream immune signaling involving Ca²⁺ influx, reactive oxygen species (ROS) production, and mitogen-activated protein kinase (MAPK) activation. Recent studies have begun to elucidate the molecular mechanisms underlying CW-DAMP generation and perception. However, the structural diversity and full spectrum of CW-DAMPs derived from complex extracellular polymers remain insufficiently characterized. This review integrates recent findings on the biogenesis, perception, and signaling of CW-DAMPs, highlights their potential applications, and discusses the current challenges and future perspectives for developing CW-DAMP-based biopesticides as sustainable tools for crop protection.

Characterizing microbial community succession in anaerobic environments is essential for elucidating ecosystem dynamics and establishing predictive ecological models. However, identifying specific bacterial biomarkers that drive these temporal transitions remains a significant challenge, as traditional univariate statistical methods often struggle with the high dimensionality and small sample sizes typical of microbiome datasets. In this study, a Random Forest (RF) classifier was applied to high-throughput sequencing data from anaerobically incubated paddy soil across three time points (days 1, 15, and 56) to identify core predictive operational taxonomic units (OTUs) that govern microbial succession. From a total of 13,497 OTUs, the RF model successfully identified 30 key OTUs whose combined feature importances enabled temporal classification. Leave-one-out cross-validation (LOOCV) demonstrated a classification accuracy of 66.67% using the top 30 OTUs, compared to 0% when using all OTUs. The high scored taxa such as Deltaproteobacteria and Rhodospirillales provided consistent results with transition to anaerobic conditions. This study suggests that machine learning-based feature selection provides a robust complement to typical statistical methods for biomarker discovery in time-series microbiome research.

Antimicrobial resistance is a major One Health issue, and marine environments are increasingly recognized as important reservoirs of antibiotics and resistance genes. However, antimicrobial susceptibility testing for marine-derived microorganisms still relies largely on clinical standard protocols, and the effects of NaCl concentration on test results have not been sufficiently evaluated. In this study, we examined the effects of NaCl concentration on antimicrobial susceptibility testing using standard reference strains, including Escherichia coli and Enterococcus faecalis. Disk diffusion and minimum inhibitory concentration (MIC) assays were performed using Mueller–Hinton agar, Marine agar, and Mueller–Hinton media supplemented with 0.0–2.0% NaCl. Significant differences in inhibition zone diameters were observed between Mueller–Hinton agar and Marine agar, particularly for erythromycin, tetracycline, and trimethoprim/sulfamethoxazole. In both E. coli and E. faecalis, inhibition zones for streptomycin and erythromycin decreased as NaCl concentration increased. In MIC assays, most antibiotics remained relatively stable at NaCl concentrations up to 2.0%, whereas gentamicin showed greater sensitivity to strain, NaCl concentration, and incubation temperature. Additional validation with other standard reference strains also revealed condition-dependent variation in several strain–antibiotic combinations. These findings indicate that NaCl concentration can affect antimicrobial susceptibility testing and should be carefully considered when evaluating marine-derived microorganisms.

Fertilization practices are key management factors influencing greenhouse gas (GHG) emissions through soil microbial communities; however, the extent of these effects remains debated. We evaluated the impacts of different fertilization methods—standard, conventional, deep-placement, organic, and non-fertilization—on microbial community structure and GHG-related functional potential in paddy and field soils using 16S rRNA gene-based analysis and functional prediction. β-diversity analysis revealed that microbial communities were clearly separated by land-use type (paddy vs. field), with no significant differences among fertilization methods or soil depths within the same land-use type. α-diversity indices similarly showed no significant variation across fertilization treatments. LEfSe analysis identified selective shifts in specific taxa associated with GHG-related processes, including Methanocella, Methylocystis, Nitrospira, and Rhodanobacteraceae. Despite these taxonomic responses, PICRUSt2-based functional prediction revealed highly consistent metabolic module distributions across fertilization treatments, corroborated by stable patterns of functional genes involved in methanogenesis, methane oxidation, nitrification, and denitrification. These results demonstrate a decoupling between taxonomic shifts and functional potential, suggesting that fertilization practices exert limited influence on GHG-related functional capacity. Instead, functional redundancy within microbial communities, together with land-use type and environmental constraints, appears to maintain functional stability.

This study investigated the effects of nitrogen (N) deep fertilization and biochar placement depth on growth and nitrogen use efficiency (NUE) of Chinese cabbage (Brassica rapa L.) in a pot experiment. Biochar was applied either to the topsoil (5-10 cm) or at the fertilizer placement depth (25 cm) under a deep fertilization system. The results demonstrated that top biochar application in combination with deep fertilization significantly enhanced shoot biomass, nitrogen uptake, and NUE, which may be attributed to improved soil physical conditions that facilitated more efficient utilization of deep placed nitrogen. In contrast, biochar applied at the fertilizer placement depth increased root biomass but did not enhance shoot growth or NUE, likely due to adsorption of inorganic nitrogen by biochar. The response under reduced nitrogen input varied depending on biochar placement depth. These results indicate that the combined effect of biochar and deep fertilization depends on biochar placement depth and nitrogen supply level.