Mycotoxins are toxic substances naturally produced by various fungi, and these compounds not only inflict economic damage, but also pose risks to human and animal health. The goal of the present study was to optimize the QuEChERS-based extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the analysis of 11 mycotoxins, such as aflatoxins (AFs), ochratoxin A (OTA), fumonisins (FBs), T-2 toxin, HT-2 toxin, zearalenone (ZEN), and deoxynivalenol (DON), commonly found in feed. The QuEChERS method, characterized by being “quick, easy, cheap, effective, rugged, and safe”, has become one of the most common extractions and clean-up procedures for mycotoxin analyses in food. Therefore, in this experiment, an optimal method for the analysis of 11 mycotoxins in feed was established by modifying the general QuEChERS method. In this process, it was confirmed that even if feed samples of different weights were extracted, the quantitative value of mycotoxins in the feed was not affected. To reduce matrix effects, 13C-labeled compounds and deuterium were used as internal standards. This optimized method was then applied in the determination of 11 mycotoxins in 736 feed ingredients and compound feeds obtained from South Korea. The results showed that the occurrence rates of FBs, ZEN, and DON were 59.4%, 38.0%, and 32.1%, respectively, and OTA, AFs, and T-2 toxin and HT-2 toxin were found in fewer than 1% of the 736 feeds. The mean concentration ranges of FBs, ZEN, and DON were 757–2387, 44–4552, and 248–9680 μg/kg, respectively. Among the samples in which DON and ZEN were detected, 10 and 12 samples exceeded the management recommendation standards presented by the Ministry of Agriculture, Food and Rural Affairs (MAFRA). However, when the detected concentrations of DON and ZEN were compared with guideline levels in foreign countries, such as the US, Japan, China, and the EU, the number of positive samples changed. In addition, the co-occurrence of mycotoxins in the feed was analyzed, and the results showed that 43.8% of the samples were contaminated with two or three mycotoxins, among which the co-occurrence rate of FBs, ZEN, and DON was the highest. In conclusion, these results suggest the need for stricter management standards for FBs, DON, and ZEN in South Korea, and emphasize the importance of the continuous monitoring of feeds.

Pesticides have been used to control pests in agricultural fields and storage systems before circulating agricultural products to markets. A tandem mass spectrometry, equipped with gas chromatographic separation (GC–MS/MS) or ultra-performance liquid chromatographic separation (LC–MS/MS), was used to monitor residual pesticides in Korean rice paddy soils. Selective multiple reaction monitoring was employed during the analyses to achieve multiresidue pesticide analysis using GC–MS/MS and LC–MS/MS of 342 pesticides. In this study, QuEChERS extraction was employed with a dSPE clean-up to establish an effective pretreatment process. The limit of detection (LOD) and limit of quantification (LOQ) were set up for all pesticides, and method validation was performed for linearity and recovery at levels of 10 and 50 mg kg⁻¹ in the untreated soil sample. All pesticides satisfied the acceptable recovery range of 70–120%, within less than 20% RSD values, except for ametoctradin and gibberellic acid. In the paddy soil analyses, tricyclazole was the most frequently detectable pesticide, followed by oxadiazon, endosulfan, and chlorantraniliprole. Continuous monitoring of residual pesticides in paddy soils should be conducted due to the translocation of some systemic pesticides from soils to crop plants, and the impact of residual pesticides on the environment.

A simultaneous analytical method, which used LC/MSMS for imidazolinone herbicides from livestock products (egg, milk, beef, pork, and chicken) for monitoring, was developed with a QuEChERS preparation. A weighed sample (5 g) in a 50 mL conical tube was added to 0.1 M potassium phosphate dibasic solution (5 mL) and shaken for 10 min. After shaking, 0.5 mL of 6 N HCl and 5 mL of acetonitrile were added, and this solution was shaken for 10 min. Additionally, QuEChERS extraction salts (original method, 4 g MgSO₄, 1 g NaCl) were added to the sample in a 50 mL conical tube. The mixture was strongly shaken for 1 min and centrifuged at 3000× g for 10 min. The acetonitrile layer was purified with dSPE (150 mg MgSO₄, 25 mg C₁₈) and was centrifuged at 13,000× g for 5 min. The supernatant was filtered with a membrane filter (pore size: 0.2 μm) before analysis. The ME (%, matrix effect) range for almost all analytes was −6.56 to 7.11%. MLOD (method limit of detection) and MLOQ (method limit of quantitative) values were calculated by the S/N ratio. MLOQs were 0.01 mg/kg. The linear correlation coefficients (R²) were >0.99 with the range of 0.5~25 μg/kg for all of the imidazolinone herbicides. The recoveries (of imidazolinone herbicides) were in the range of 76.1~110.6% (0.01 mg/kg level), 89.2~97.1% (0.1 mg/kg level), and 94.4~104.4% (0.5 mg/kg level). These are within the validation criteria (to recover 70–120% with RSD <20%). The method demonstrated the simple, rapid, high throughput screening and quantitative analysis of imidazolinone herbicide residues for monitoring in livestock products.

A robust analytical method was developed for the simultaneous detection of 504 pesticide multiresidues in various crops using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF). The method integrates both MS¹ and MS² levels through sequential window acquisition of all theoretical mass spectra (SWATH) analysis, allowing for accurate mass measurements and the construction of a spectral library to enhance pesticide residue identification. An evaluation of the method was carried out according to international standards, including the FAO guidelines and SANTE/11312/2021. Validation across five representative crops—potato, cabbage, mandarin, brown rice, and soybean—demonstrated exceptional sensitivity, with over 80% of the analytes detected at trace levels (≤2.5 μg/kg). Moreover, an impressive 96.8% to 98.8% of the compounds demonstrated LOQs of ≤10 μg/kg. Most compounds exhibited excellent linearity (r² ≥ 0.980) and satisfactory recovery rates at spiking levels of 0.01 and 0.1 mg/kg. Among 42 crop samples analyzed, pesticides were detected in 1 cabbage, 3 mandarin, and 6 rice samples, with a mass accuracy within ±5 ppm and a Fit score ≥ 70.8, confirming the method’s practical applicability and reliability. The detected residues ranged from 12.3 to 339.3 μg/kg, all below the established maximum residue limits (MRLs). This comprehensive approach offers an efficient, reliable, and scalable solution for pesticide multiresidue monitoring, supporting food safety programs and regulatory compliance.

Despite considerable efforts in recent years to quantify the trophic magnification factor (TMF) of organophosphate flame retardants (OPFRs), definitive conclusions regarding their biomagnification potential have not yet been reached. This study hypothesizes that sampling uncertainty may affect TMF calculations. To overcome the limitations of traditional regression-based methods (TMF_R), we applied a Monte Carlo simulation-based probabilistic method (TMF_M), which provides more reliable estimates of OPFR bioaccumulation in freshwater ecosystems. The concentrations of tributyl phosphate (TNBP), tris(2-chloroethyl) phosphate (TCEP), and tris(2-chloroisopropyl) phosphate (TCIPP) were analyzed in relation to the amino acid stable isotope-based trophic position in fish from four major rivers in Korea. The TMF_M values were 1.2 ± 0.3, 1.4 ± 0.9, and 2.0 ± 1.9 for TNBP, TCEP, and TCIPP, respectively, with TCIPP exhibiting a relatively higher biomagnification potential, consistent with previous findings. In contrast, the TMF_R produced extreme values (e.g., 17.8 for TCIPP), whereas TMF_M moderated by approximately 50 %, reducing spatial and temporal variability. A meta-analysis of literature data further supported the TMF_M estimates, revealing that 80 % of TMFs ranged between 0 and 2, while higher values were observed for top predators and specific ecosystems. These results advance the understanding of OPFR bioaccumulation by improving TMF estimation accuracy and highlight the need for ongoing monitoring and mechanistic studies. The probabilistic approach presented here offers a valuable tool for environmental risk assessment and supports informed chemical management.