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This study was undertaken to develop and validate a single multiresidue method for the monitoring of ten multiclass emerging contaminants, viz. ceftiofur, clopidol, florfenicol, monensin, salinomycin, sulfamethazine, sulfathiazole, sulfamethoxazole, tiamulin, and tylosin in agricultural soil. Samples were extracted using an acetate-buffered, modified quick, easy, cheap, effective, rugged, and safe method followed by liquid chromatography with tandem mass spectrometric analysis in positive ion mode. Separation on an Eclipse Plus C column was conducted in gradient elution mode using a mobile phase of methanol (A) and distilled water (B), each containing 0.1% formic acid and 5 mM ammonium formate. The linearity of the matrix-matched calibrations, expressed as determination coefficients, was good, with R ≥ 0.9908. The limits of quantification were in the range 0.05-10 μg/kg. Blank soil samples spiked with 4 × and 20 × the limit of quantification provided recovery rates of 60.2-120.3% (except sulfamethoxazole spiked at 4 × the limit of quantification, which gave 131.9%) with a relative standard deviation < 13% (except clopidol spiked at 20 × the limit of quantification, which gave 25.2%). This method was successfully applied to the monitoring of 51 field-incurred agricultural loamy-sand soil samples collected from 17 provincial areas throughout the Korean Peninsula. The detected and quantified drugs were clopidol (≤ 4.8 μg/kg), sulfathiazole (≤ 7.7 μg/kg), sulfamethazine (≤ 6.6 μg/kg), tiamulin (≤ 10.0 μg/kg), and tylosin (≤ 5.3 μg/kg). The developed method is simple and versatile, and can be used to monitor various classes of veterinary drugs in soil.

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In this study, we developed a digital shade-matching device for dental color determination using the support vector machine (SVM) algorithm. Shade-matching was performed using shade tabs. For the hardware, the typically used intraoral camera was modified to apply the cross-polarization scheme and block the light from outside, which can lead to shade-matching errors. For reliable experiments, a precise robot arm with ±0.1 mm position repeatability and a specially designed jig to fix the position of the VITA 3D-master (3D) shade tabs were used. For consistent color performance, color calibration was performed with five standard colors having color values as the mean color values of the five shade tabs of the 3D. By using the SVM algorithm, hyperplanes and support vectors for 3D shade tabs were obtained with a database organized using five developed devices. Subsequently, shade matching was performed by measuring 3D shade tabs, as opposed to real teeth, with three additional devices. On average, more than 90% matching accuracy and a less than 1% failure rate were achieved with all devices for 10 measurements. In addition, we compared the classification algorithm with other classification algorithms, such as logistic regression, random forest, and k-nearest neighbors, using the leave-pair-out cross-validation method to verify the classification performance of the SVM algorithm. Our proposed scheme can be an optimum solution for the quantitative measurement of tooth color with high accuracy.

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Research on the occurrence of perfluorochemicals (PFCs) such as perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in the agricultural environment is lacking, in spite of their potential risk via food chain transfer from aquatic and soil-plant systems to animals and/or humans. In the present study, for the first time, soil and water samples collected from 243 different agricultural sites adjacent to waste water treatment plants (WWTPs) belonging to 81 cities and 5 provinces with different levels of industrialization in South Korea were monitored for concentrations of PFOS and PFOA by use of solid phase extraction and liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Significant mean concentrations of PFOA (0.001-0.007 µg L-1 water and <0.05-1.573 µg kg-1 soil) and PFOS (0.001-0.22 µg L-1 water and <0.05-0.741 µg kg-1 soil) were found in all samples. Concentrations of PFCs in soils were high, highlighting that soil is an important sink for PFCs in the agricultural environment. Samples from near WWTPs in Gyeongsang Province contained the highest concentrations of PFOS and PFOA, reflecting the concentration of heavy industry in the province. The concentrations of PFCs in agricultural water (most samples <0.05 µg L-1) and soils (most samples <1 µg kg-1) from South Korea were less than acceptable guideline values, indicating that South Korea is not a hotspot of PFOS and PFOA contamination and that there is negligible risk to human and ecological health from these chemicals. However, further studies investigating the seasonal variation in PFOA, PFOS and other perfluorochemical concentrations in the agricultural environment are needed.

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