An isocratic high performance liquid chromatography (HPLC) method for routine analysis of deoxynivalenol in noodles was validated and estimated the measurement uncertainty. Noodles (dried noodle and ramyeon) were analyzed by HPLC-ultraviolet detection using immunoaffinity column for clean-up. The limits of detection (LOD) and quantification (LOQ) were 7.5 μg/kg and 18.8 μg/kg, respectively. The calibration curve showed a good linearity, with correlation coefficients r² of 0.9999 in the concentration range from 20 to 500 μg/kg. Recoveries and Repeatabilities expressed as coefficients of variation (CV) spiked with 200 and 500 μg/kg were 82 ± 2.7% and 87 ± 1.3% in dried noodle, and 97 ± 1.6% and 91 ± 12.0% in ramyeon, respectively. The uncertainty sources in measurement process were identified as sample weight, final volume, and sample concentration in extraction volume as well as components such as standard stock solution, working standard solution, 5 standard solutions, calibration curve,matrix, and instrument. Deoxynivalenol concentration and expanded uncertainty in two matrixes spiked with 200 μg/kg and 500 μg/kg were estimated to be 163.8 ± 52.1 and 435.2 ± 91.6 μg/kg for dried noodle, and 194.3 ± 33.0 and 453.2 ± 91.1 μg/kg for ramyeon using a coverage factor of two which gives a level of statistical confidence with approximately 95%. The most influential component among uncertainty sources was the recovery of matrix, followed by calibration curve.

Melamine has raised international concerns for its catastrophic health effects from tainted infant formula. This report concerns the developmental validation of a sensitive HPLC/MS/MS and GC/MS methods about melamine and cyanuric acid in human urine and serum. Analytical detection ranges of LC/MS was from 0.2 to 5.0 ng/mL and 2.0 to 60.0 ng/mL about melamine and cyanuric acid, respectively. The limits of quantification and confirmation are 0.2 ng/mL for both analytes in human urine and serum by LC/MS/MS. The range of recovery was 91.6%, and 107.6% for cyanuric acid and melamine in urine, respectively. The range of precision coefficient variation was from 2.0%, to 11.8% for cyanuric acid and melamine in urine. The range of recovery was from 94.9%, to 119.0% about cyanuric acid and melamine in serum, respectively. The range of precision coefficient variation from was 3.7%, and 13.5% about cyanuric acid and melamine in serum. Analytical detection ranges of GC/MS were 5.0 to 100.0 ng/mL about melamine and cyanuric acid, respectively. The limits of quantification and confirmation are 5.0 ng/mL for both analytes in human urine and serum by GC/MS. The range of recovery was from 83.7%, to 114.5% for cyanuric acid and melamine in urine, respectively. The range of precision coefficient variation was 3.5%, and 10.7% for cyanuric acid and melamine in urine. The range of recovery was 94.4%, and 110.7% for cyanuric acid and melamine in serum,respectively. The range of precision coefficient variation from was 3.9%, and 13.8% for cyanuric acid and melamine in serum. Several changes were taken to optimize performance by this method.

Predictive mathematical models were developed for predicting the kinetics of growth of Listeria monocytogenes in smoked salmon, which is the popular ready-to-eat foods in the world, as a function of temperature (4, 10, 20 and 30℃). At these storage temperature, the primary growth curve fit well (r² = 0.989~0.996) to a Gompertz equation to obtain specific growth rate (SGR) and lag time (LT). The Polynomial model for natural logarithm transformation of the SGR and LT as a function of temperature was obtained by nonlinear regression (Prism, version 4.0,GraphPad Software). Results indicate L. monocytogenes growth was affected by temperature mainly, and SGR model equation is 365.3-31.94*Temperature+0.6661*Temperature^2 and LT model equation is 0.1162-0.01674*Temperature+0.0009303*Temperature^2. As storage temperature decreased 30℃ to 4℃, SGR decreased and LT increased respectively. Polynomial model was identified as appropriate secondary model for SGR and LT on the basis of most statistical indices such as bias factor (1.01 by SGR, 1.55 by LT) and accuracy factor (1.03 by SGR, 1.58 by LT).

In this study, two duplex real-time PCR approach with melting curve analysis is presented for the detection of Escherichia coli O157:H7, Listeria monocytogenes, Salmonella spp. and Staphylococcus aureus, which are important food-borne bacterial pathogens usually present in fresh and/or minimally processed vegetables. Reaction conditions were adjusted for the simultaneous amplification and detection of specific fragments in the β-glucuronidase (uidA, E. coli), thermonuclease (nuc, S. aureus), hemolycin (hly, L. monocytogenes) and tetrathionate reductase (ttr, Salmonella spp.) genes. Melting curve analysis using a SYBR Green I real-time PCR approach showed characteristic Tm values demonstrating the specific and efficient amplification of the four pathogens; 80.6 ± 0.9 ℃,86.9 ± 0.5 ℃, 80.4 ± 0.6 ℃ and 88.1 ± 0.11 ℃ for S. aureus, E. coli O157:H7, L. monocytogenes and Salmonella spp.,respectively. For all the pathogens, the two duplex, real-time PCR was equally sensitive to uniplex real-time PCR,using same amounts of purified DNA, and allowed detection of 10 genome equivalents. When our established duplex real-time PCR assay was applied to artificially inoculated fresh lettuce, the detection limit was 10³ CFU/g for each of these pathogens without enrichment. The results from this study showed that the developed duplex real-time PCR with melting curve analysis is promising as a rapid and cost-effective test method for improving food safety.

Plantago asiatica L. (PA), which is widely distributed in Korea, Japan and China, has traditionally been used as a popular folk medicine for the treatment of liver diseases. A variety of activities of PA was reported, that is hepatoprotective, anti-inflammatory, anti-glycation and anti-oxidant effect. Ferric nitrilotriacetate (Fe-NTA) is a potent nephrotoxic agent and has been reported to induce renal proximal tubular necrosis. In the present study, pretreatment with PA extract (PAE) in Wistar rat followed by Fe-NTA i.p. treatment (13.5 mg Fe/kg body weight) was performed to detect the renal protective effect of PAE. Only Fe-NTA treated group showed increases in the level of serum blood urea nitrogen (BUN) and serum creatinine (Cr), and renal tissue malondialdehyde (MDA), product of lipid peroxidation. Moreover, the level of biomarkers indicate the antioxidants status, reduced glutathione (GSH), glutathione-S-transferase (GST) and glutathione reductase (GR) were decreased. However, PAE pre-treated group showed decreases in the levels of serum BUN, serum Cr and renal tissue MDA in concentration dependent manner and increases in the level of GSH, GST and GR. These results are significantly different (p < 0.05) to the other groups. Our data suggest that PAE may be used as an chemopreventive material against Fe-NTA-mediated renal oxidative stress.

This study was conducted to investigate the residue amount of harmful materials on the 113 commercial fruit teas (Gugija, Omija, Sansuyu) in Gwangju area. It was performed using the GC-ECD, GC-NPD, GCMSD and the LC-UVD, LC-FLD, LC-MSD to analyze 200 pesticides. The heavy metals were determined using a Mercury analyzer and AAS. The sulfur dioxides were analyzed by modified Monnier-Williams method. The residual pesticides were detected in 4 samples (Gugija). The mean values of heavy metal contents (mg/kg) were Pb, 0.024; Cd,0.031; As, 0.010; Hg, 0.003. The measured values of Pb, Cd, As, Hg showed within MRLs. The sulfur dioxides were over MRLs in 4 samples (Gugija). These results will be used to establish on the regulation of commercial fruit teas in Gwangju area.

This study examines the effects of lightemitting diode (LED) light and temperature on lettuce growth. For plant growth, we used an LED bar composed of red, white and blue LEDs (4:1:2). Six types of cultivation equipment were used to measure the temperature. To compare their effects, the heights of the lettuces and the water temperatures were measured. The results demonstrated that the lettuce growth was optimal at 25ºC.

익산시는 KTX역세권, 국가식품클러스터, 고도지정 등에 의한 대규모 도시개발 사업으로 인해 도시경관의 급격한 변화가 예상되므로 종합적인 경관계획을 필요로 하고 있다. 본 연구는 첫째, 익산시에 내재되어 있는 경관자원을 도출하여 자원의 보존, 연계방안을 설정하고, 둘째, 시가지 환경개선과 지역특색을 강화하기 위한 종합적이고 바람직한 경관계획을수립하며, 셋째, 주민과 함께하는 경관계획 실행 방안을 제안하는데 목적이 있다.연구는 도농통합시 익산의 중심시가지인 15개 동지역을 대상으로 현장조사를 통해 경관자원을 도출하고 자원의 가치및 중요도를 펑가한 후, 계획의 방향을 설정하였다. 경관유형은 자연경관, 시가지경관, 가로 및 철도경관으로 구분하였다.자연경관에서는 배산, 탑천, 대간선 수로의 보존 및 녹지의 네트워크화 방안이 모색되었다. 주거지, 상업지, 공업지및 KTX 역세권에 대해서는 주요 지역에 대한 특정경관계획과 건축물 및 외부공간을 중심으로 한 디자인 가이드라인을설정하였다. 가로 및 철도경관에서는 하나로, 송학로의 선형공원화를 통해 녹지 네트워크를 강화하였으며 철도변 경관저해요소 제거방안을 제시하였다.계획의 실행은 경관사업과 병행하여 주거지 경관정비는 주민 주도형 경관협정을, 탑천, 폐선부지, 하나로의 공원화사업은용도지구 지정을, 배산, 역세권, 대학로는 지구단위계획을 수립함으로서 규제 및 인센티브가 상호 보완적으로 나타날수 있게 하였다.

The dissemination process of agricultural research and development (R&D) results has somewhat different characteristics from that of typical R&D results. However, these characteristics are not adequately considered on the basis of an examination of the current performance system, the resulting management plans, and strategies for the application and dissemination of the results of agricultural R&D in Korea. The performance evaluation indicator exposed the problem of the inadequate consideration of the characteristics of each of these areas, particularly the lack of unified R&D-related institutions and the inadequacy of the system to monitor outcomes. To address these shortcomings in the agricultural R&D programs in Korea, the policies pertaining to agricultural R&D performance, results management, and dissemination in the U.S. and Japan were examined. Based on these investigations, we proposed strategies to improve the agricultural R&D policies in Korea.

The development of informatization impacts all sectors, including agriculture. Agricultural informatization builds the knowledge linkage structures of agricultural innovation systems globally. This study investigated the global knowledge linkage structures in agricultural innovation pertinent to information technology (IT) for agricultural research and development (R&D) investments and activities. We explored the longitudinal trend of systemness within the networked research relationships in the triple helix (TH) of the university, industry and government (UIG). We collected data from publications in the Science Citation Index (SCI), the Social Sciences Citation Index (SSCI), and the Arts and Humanities Citation Index (A&HCI) to analyze the TH network dynamics. We also performed a scientometrics analysis to quantitatively identify the knowledge and insights of global agricultural innovation structures. These results could be informative for individual countries. Our findings reveal that the global knowledge linkage structures in the agricultural sector that are pertinent to IT fluctuate widely and fail to increase the capacity of agricultural innovation research due to a neglect of the network effects of the TH dynamics of UIG.

This study describes the development of a web-based system that collects all data generated in the research conducted to set pre-harvest residue limits (PHRLs) for agricultural product safety control. These data, including concentrations of pesticide residues, limit of detection, limit of quantitation, recoveries, weather charts, and growth rates, are incorporated into a database, a regression analysis of the data is performed using statistical techniques, and the PHRL for an agricultural product is automatically computed. The development and establishment of this system increased the efficiency and improved the reliability of the research in this area by standardizing the data and maintaining its accuracy without temporal or spatial limitations. The system permits automatic computation of the PHRL and a quick review of the goodness of fit of the regression model. By building and analyzing a database, it also allows data accumulated over the last 10 years to be utilized.

In this exploratory analysis, we investigate the genesis and the evolution of local food-purchasing networks created and operated by consumers. In details, we describe how collecting and sharing information about food-products can become a central activity for some consumers’ communities and how these communities are starting to play an active role in the food supply chain. We define this community-based food-purchasing model as collaborative food network (CFN), and we analytically describe its characteristics and differences with respect to the traditional and industrialized agrifood supply chain models. A collaborative food network community in Italy, known as GAS (“Gruppi di Acquisto Solidale” – “Solidarity Purchasing Groups”), is introduced as an example of our analytical model. We will use this empirical example to present the strengths and weaknesses of the CFN model.