RESUMEN
Off-target pesticide drift in paddy fields following unmanned aerial vehicle (UAV) spraying was evaluated using cellulose deposition samplers (CDSs). An analytical method for quantifying ferimzone Z and E isomers deposited on CDSs was developed using LC-MS/MS. The suitability of the CDS method was confirmed by comparing deposition patterns on CDSs with residue levels in rice plant samples. To assess pesticide deposition in paddy fields, CDSs were strategically placed at varying distances from target areas, followed by UAV spraying. The fungicide agrochemicals were applied with and without adjuvants, and wind direction affected the drift trajectory for all treatment groups. Adjuvants, particularly soy lecithin as the major component, significantly enhanced pesticide deposition within the spray pathway while reducing drift rates relatively by 47.9-68.0â¯%. Higher wind speeds were found to exacerbate drift, but adjuvant-treated sprays showed less variability in deposition patterns under these conditions. Pesticide residues in harvested brown rice were found to be below the maximum residue limits (MRLs), ensuring safety for consumption. These findings highlight the importance of selecting appropriate adjuvants in UAV-based pesticide applications to optimize deposition efficiency and minimize environmental contamination.
RESUMEN
To prevent pesticides from exceeding maximum residue limits (MRLs) in crops during export and shipment, it is necessary to manage residue levels during the pre-harvest stages. Therefore, the Republic of Korea establishes pre-harvest residue limits (PHRLs) per crop and pesticide. This study was conducted to set PHRLs for penthiopyrad and tebufenpyrad in angelica leaves, where the exceedance rates of MRLs are expected to be high. The LOQ of the analytical method used was 0.01 mg/kg and it demonstrated good linearity, with a correlation coefficient of 0.999 or higher within the quantitation range of 0.005 to 0.5 mg/kg. The recovery and storage stability accuracy values were in the range of 94.5-111.1%, within the acceptable range (70-120%, RSD ≤ 20%). The matrix effect for both pesticides was in the medium-to-strong range, and it did not significantly impact the quantitative results as a matrix-matched calibration method was employed. Using the validated method, residue concentrations of penthiopyrad 20 (%) EC and tebufenpyrad 10 (%) EC were analyzed. Both pesticides exhibited a decreasing residue trend over time. In Fields 1-3 and their integrated results, the biological half-life was within 2.6-4.0 days for penthiopyrad and 3.0-4.2 days for tebufenpyrad. The minimum value of the regression coefficient in the dissipation curve regression equation was selected as the dissipation constant. The selected dissipation constants for penthiopyrad in Fields 1-3 and their integration were 0.1221, 0.2081, 0.2162, and 0.1960. For tebufenpyrad, the dissipation constants were 0.1451, 0.0960, 0.1725, and 0.1600, respectively. The dissipation constant was used to calculate PHRL per field. Following the principles of the PHRL proposal process, residue levels (%) on PHI dates relative to MRLs were calculated, and fields for proposing PHRLs were selected. For penthiopyrad, since the residue level (%) was less than 20%, the PHRL for Field 3 with the largest dissipation constant was proposed. For tebufenpyrad, as the residue level (%) exceeded 80%, the PHRL proposal could not established. It is deemed necessary to reassess the MRL and 'guidelines for safe use' for tebufenpyrad in angelica leaves.
RESUMEN
The COVID-19 pandemic has affected medical and dental care in Korea. This study aimed to investigate the factors influencing the intention to use dental care in industrial workers, an economically active population. An online questionnaire survey was completed by 301 industrial workers. Stress and anxiety to viral epidemics-6 (SAVE-6), attitude, subjective norm, perceived behavior control, and intention to use dental care, based on the theory of planned behavior (TPB), were measured. Predisposing, enabling, and need factors based on the Andersen model were measured as control variables for influencing factors. In the final hierarchical multiple regression analysis, the most significant relevant factors affecting intention to use dental care were attitude (ß = 0.598, p < 0.001), followed by experience of dental clinic visits (ß = 0.237, p < 0.001), subjective norm (ß = 0.125, p < 0.001), perceived behavior control (ß = 0.114, p = 0.004), SAVE-6 (ß = -0.073, p = 0.025), and gingival bleeding (ß = 0.062, p = 0.029). Dental care use decreased to 58.5%, and socio-psychological factors based on TPB were closely associated with the intention to use dental care. Therefore, awareness must be raised regarding oral health practices to increase the use of dental care among industrial workers.