• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.123-130
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• 2014

A simultaneous determination was developed for 9 aminoglycoside antibiotics (amikacin, apramycin, dihydrostreptomycin, gentamicin, hygromycin B, kanamycin, neomycin, spectinomycin, and streptomycin) in meat by liquid chromatography tandem mass spectrometry (LC-MS/MS). Each parameter was established by multiple reaction monitoring in positive ion mode. The developed method was validated for specificity, linearity, accuracy, and precision based on CODEX validation guideline. Linearity was over 0.98 with calibration curves of the mixed standards. Recovery of 9 aminoglycosides ranged on 60.5~114% for beef, 60.1~112% for pork and 63.8~131% for chicken. The limit of detection (LOD) and limit of quantification (LOQ) were 0.001~0.009 mg/kg and 0.006~0.03 mg/kg, respectively in livestock products including beef, pork and chicken. This study also performed survey of residual aminoglycoside antibiotics for 193 samples of beef, pork and chicken collected from 9 cities in Korea. Aminoglycosides were not found in any of the samples.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.477-487
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• 2010

In North Korea, forests were intensively degraded by forest land reclamation for food production and firewood collection since the mid-1970s. These degraded forests have to be certainly recovered for economic support, environmental protection and disaster prevention. In order to provide detailed land cover information of forest recovery project (A/R CDM), this study was focused to develop an improved classification method for degraded forest using 2.5m SPOT-5 pan-sharpened image. The degraded forest of North Korea shows various different types of texture. This study used GLCM texture bands of segmented image with spectral bands during forest cover classification. When scale factor 40/shape factor 0.3 was used as a parameter set to generate segment image, segment image was generated on suitable segment scale that could classify types of degraded forest. Forest land cover types were classified with an optimum band combination of Band1, Band2, band3, GLCM dissimilarity (band2), GLCM homogeneity (band2) and GLCM standard deviation (band3). Segment-based classification method using spectral bands and texture bands reached an 80.4% overall accuracy, but the method using only spectral bands yielded an 70.3% overall accuracy. As using spectral and texture bands, a classification accuracy of stocked forest and unstocked forest showed an increase of 23~25%. In this research, SPOT-5 pan-sharpened high-resolution satellite image could provide a very useful information for classifying the forest cover of North Korea in which field data collection was not available for ground truth data and verification directly. And segment-based classification method using texture information improved classification accuracy of degraded forest.