• The Plant Pathology Journal
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• 제38권1호
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• pp.12-24
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• 2022

In this study, we conducted whole-genome sequencing with six species of Pectobacterium composed of seven strains, JR1.1, BP201601.1, JK2.1, HNP201719, MYP201603, PZ1, and HC, for the analysis of pathogenic factors associated with the genome of Pectobacterium. The genome sizes ranged from 4,724,337 bp to 5,208,618 bp, with the GC content ranging from 50.4% to 52.3%. The average nucleotide identity was 98% among the two Pectobacterium species and ranged from 88% to 96% among the remaining six species. A similar distribution was observed in the carbohydrate-active enzymes (CAZymes) class and extracellular plant cell wall degrading enzymes (PCWDEs). HC showed the highest number of enzymes in CAZymes and the lowest number in the extracellular PCWDEs. Six strains showed four subsets, and HC demonstrated three subsets, except hasDEF, in type I secretion system, while the type II secretion system of the seven strains was conserved. Components of human pathogens, such as Salmonella pathogenicity island 1 type type III secretion system (T3SS) and effectors, were identified in PZ1; T3SSa was not identified in HC. Two putative effectors, including hrpK, were identified in seven strains along with dspEF. We also identified 13 structural genes, six regulator genes, and five accessory genes in the type VI secretion system (T6SS) gene cluster of six Pectobacterium species, along with the loss of T6SS in PZ1. HC had two subsets, and JK2.1 had three subsets of T6SS. With the GxSxG motif, the phospholipase A gene did locate among tssID and duf4123 genes in the T6SSa cluster of all strains. Important domains were identified in the vgrG/paar islands, including duf4123, duf2235, vrr-nuc, and duf3396.

• Mycobiology
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• 제51권1호
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• pp.36-48
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• 2023

Xanthoria elegans is a lichen symbiosis, that inhabits extreme environments and can absorb UV-B. We reported the de novo sequencing and assembly of X. elegans genome. The whole genome was approximately 44.63 Mb, with a GC content of 40.69%. Genome assembly generated 207 scaffolds with an N50 length of 563,100 bp, N90 length of 122,672 bp. The genome comprised 9,581 genes, some encoded enzymes involved in the secondary metabolism such as terpene, polyketides. To further understand the UV-B absorbing and adaptability to extreme environments mechanisms of X. elegans, we searched the secondary metabolites genes and gene-cluster from the genome using genome-mining and bioinformatics analysis. The results revealed that 7 NR-PKSs, 12 HR-PKSs and 2 hybrid PKS-PKSs from X. elegans were isolated, they belong to Type I PKS (T1PKS) according to the domain architecture; phylogenetic analysis and BGCs comparison linked the putative products to two NR-PKSs and three HR-PKSs, the putative products of two NR-PKSs were emodin xanthrone (most likely parietin) and mycophelonic acid, the putative products of three HR-PKSs were soppilines, (+)-asperlin and macrolactone brefeldin A, respectively. 5 PKSs from X. elegans build a correlation between the SMs carbon skeleton and PKS genes based on the domain architecture, phylogenetic and BGC comparison. Although the function of 16 PKSs remains unclear, the findings emphasize that the genes from X. elegans represent an unexploited source of novel polyketide and utilization of lichen gene resources.

• 한국가스학회지
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• 제27권4호
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• pp.19-26
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• 2023

지진은 지하 구조물에 영향을 미치는 가장 중요한 재해 중 하나이다. 도시가스 지하 매설 배관은 지진 발생 시 구조물의 안전성 문제가 발생할 수 있다. 우리나라는 디지털 관측을 시작한 이래로 지진 발생 횟수가 꾸준히 증가하고 있다. 도시가스배관의 내진 설계 기준은 2008년에 KGS GC204 가스배관 내진설계 기준이 제정되었지만 이는 배관 설치 시 기준으로 지진 발생 시 배관의 영향을 추정하기는 어렵다. 본 연구에서는 국내에서 매설배관으로 주로 사용하고 있는 PE(폴리에틸렌관)배관과 PLP(폴리에틸렌 피복강관) 배관을 대상으로 지진 발생 시 환경 및 배관의 변수에 따른 구조해석을 수행하였다. 본 연구는 CAE(Computer Aided Engineering)를 통해 배관을 모델링하고 지반에 변위를 발생시켜 가장 취약한 매설배관의 변수를 찾고자하였다. 이 연구를 통해 토양은 탄성계수가 클 수록, 매설심도는 깊을 수록, 관경은 작을 수록, 압력은 높을 수록, PE 보다 PLP 배관이 더 지진에 영향을 많이 받는 것을 확인할 수 있었다. 이 결과를 토대로 매설 도시가스배관의 취약지점을 유추하여 지진발생 시 매설배관의 특별점검에 활용하고자한다.[1]

• 농약과학회지
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• 제19권1호
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• pp.32-40
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• 2015

본 연구는 유통 농산물의 잔류 실태를 조사하여 잔류농약에 대한 안전성을 평가하기 위해 수행되었다. 전국 9개 지역에서 수거된 농산물 15개 품목 232건을 식품공전 다종농약다성분 분석법으로 분석하였으며, GC/MSMS로 분석 가능한 농약 196종을 대상으로 하였다. 그 결과 53건의 시료에서 64종의 농약이 검출되었고 이 중 chlorpyrifos와 procymidone이 가장 빈번히 검출되었다. 검출된 64종 중 깻잎에서 검출된 chlorpyrifos와 복숭아에서 검출된 picoxystrobin은 잔류허용기준을 초과하였으며, 나머지는 각각의 잔류허용기준을 초과하지 않았다. 잔류허용기준을 초과한 chlorpyrifos와 picoxystrobin을 포함한 검출 농약에 대해 위해평가를 수행한 결과, 1일 섭취허용량(acceptable daily intake, ADI) 대비 1일 추정섭취량(estimated daily intake, EDI)이 0.001~0.902%로 조사되어 매우 낮은 수준임을 확인할 수 있었다. 이번 연구 결과 유통 농산물에서 잔류농약은 안전하게 관리되고 있음을 확인 할 수 있었고, 향후 식품안전 정책 수립의 기초 자료로 활용할 수 있을 것을 생각된다.

• 한국식품과학회지
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• 제42권3호
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• pp.269-276
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• 2010

국내 유통되는 어류, 연체동물(두족류, 패류), 갑각류, 해조류에서 총 15종, 231건의 수산식품을 수거하여 총수은 및 메틸수은 오염량을 모니터링하고 조사대상 수산식품의 위해도를 평가하였다. 총수은 분석법(총수은분석기 사용)을 검토한 결과, 직선성($R^2$)은 0.999 이상이었고 검출 및 정량한계는 각각 $0.017\;{\mu}g/kg$, $0.051\;{\mu}g/kg$이었으며 표준인증물질 분석에 대한 정확도는 98% 이상이었다. 메틸수은 분석법(GC-ECD 사용)을 검토한 결과, 직선성($R^2$)은 0.990 이상이었고 회수율은 평균 70% 이상이었으며 검출 및 정량한계는 각각 0.003, 0.010 mg/kg이었다. 모니터링 결과, 수산식품 중 총수은 평균(단위: mg/kg)은 고등어 0.088, 갈치 0.061, 조기 0.030, 명태 0.032, 메기 0.059, 가물치 0.110, 오징어 0.030, 낙지 0.026, 꽃게 0.035, 굴 0.009, 바지락 0.011, 홍합 0.008, 미역 0.018, 김 0.007, 다시마 0.019 이었다. 메틸수은 평균(단위: mg/kg)은 고등어 0.034, 갈치 0.016, 조기 0.005, 명태 0.008, 메기 0.023, 가물치 0.045, 오징어 0.011, 낙지 0.009, 꽃게 0.008이었으며 굴, 바지락, 홍합, 미역, 김, 다시마에서는 검출되지 않았다. 본 연구에서 조사된 수산식품별 총수은 및 메틸수은의 오염량 평균과 국민건강영양조사의 일일식품섭취량을 근거로 하여 15종의 수산식품에서 섭취되는 총수은과 메틸수은의 총 주간추정섭취량(total estimated weekly intake)을 각각 산출하였다. 이를 JECFA의 PTWI(총수은: $5\;{\mu}g/kg$ b.w./week, 메틸수은: $1.6\;{\mu}g/kg$ b.w./week)와 비교했을 때 각각 3.57, 3.34% 수준으로서, 15종의 수산식품 섭취에 의한 수은 노출량은 낮은 수준으로 나타났다. 결론적으로 수은 섭취에 주로 기여하는 식품군이 수산식품이며 조사대상 수산식품 15종의 섭취량은 전체 수산식품 섭취량에서 높은 비중을 차지하는 것을 고려하였을 때 수은 오염에 대한 국내 유통 수산식품의 위해도는 낮은 것으로 판단된다.

• 농약과학회지
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• 제18권3호
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• pp.130-140
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• 2014

본 연구는 tolclofos-methyl의 잔류양상을 이해하기 위하여 토양 및 인삼(뿌리, 잎 줄기)으로 tolclofos-methyl의 흡수 이행특성을 평가하고자 하였으며, 인삼에 대하여 tolclofos-methyl 농약이 사용 금지된 이후인 2013년에 국내 주요 인삼재배지인 홍천, 철원, 풍기, 금산 지역의 토양 및 인삼(뿌리, 잎 줄기)을 채취하여 다성분 분석방법으로 분석함으로써 잔류현황을 파악하여 tolclofos-methyl의 안전관리에 기여하고자 하였다. 인삼재배지 토양 중 tolclofos-methyl의 인삼(뿌리, 잎 줄기)으로의 흡수이행특성을 평가하기 위하여 tolclofos-methyl 50% 수화제 일정량을 $5.0mg\;kg^{-1}$ 수준으로 토양에 혼화 처리하였다. 혼화처리한 토양을 Wagner pot에 채운 뒤 묘삼을 정식하였으며 흡수 이행특성을 파악하기 위해 분기별(2013년 4월, 6월, 9월, 12월, 2014년 3월)로 토양 및 인삼(뿌리, 잎 줄기)를 채취하여 GC/MS로 분석하였다. 분석시료 중 tolclofos-methyl의 정량한계(LOQ, Limit of Quantitation)는 $0.02mg\;kg^{-1}$이었고, 회수율은 LOQ의 10배 및 50배 수준으로 3반복 수행하였으며, 70.0 %~120.0 %의 유효회수율 범위를 만족하였다. 토양 중 tolclofos-methyl의 잔류량은 2013년 4월 채취 시 $4.26mg\;kg^{-1}$이었으며, 2014년 3월 채취 시 $0.06mg\;kg^{-1}$으로 크게 감소하였다. 인삼 뿌리의 경우 tolclofos-methyl의 잔류량은 2013년 6월 채취 시 $7.09mg\;kg^{-1}$에서 2014년 3월 채취 시 $1.54mg\;kg^{-1}$으로 감소하였으며, 인삼 잎 줄기 또한 2013년 6월 채취 시 $0.79mg\;kg^{-1}$에서 2013년 9월 채취 시 $0.69mg\;kg^{-1}$으로 감소하였다. 인삼 재배지 토양 및 인삼 중 잔류농약 모니터링을 위하여 홍천, 철원, 풍기, 금산 지역에서 2013년 8월~9월에 채취한 토양 및 인삼(뿌리, 잎 줄기)을 다성분 분석법으로 분석하였다. 채취한 시료(뿌리, 잎 줄기)를 분석한 결과, pyraclostrobin, trifloxystrobin 등 총 50종의 농약이 $0.01{\sim}15.01mg\;kg^{-1}$ 수준으로 검출되었다. 검출 빈도는 pyraclostrobin 성분이 10.0% (24건)로 가장 많았으며, trifloxystrobin 6.3% (15건), tebuconazole 6.3% (15건) 순이었다. Tolclofos-methy의 경우 인삼 뿌리에서 $0.01{\sim}0.05mg\;kg^{-1}$수준으로 검출(4건, 6.6%)되어 잔류허용기준 미만으로 검출되었다. 본 연구로 이행특성을 확인한 결과, 토양 중 tolclofos-methyl이 잔류할 경우 인삼의 생육기간 동안 인삼(뿌리, 잎 줄기)으로 이행됨을 확인하였으나, 잔류양상을 살펴보면 인삼의 수확시기에는 잔류될 우려가 매우 낮을 것으로 판단되었다. 또한 국내 주요 인삼재배지역(홍천, 철원, 풍기, 금산)의 인삼재배지 토양 및 인삼(뿌리, 잎 줄기) 중 tolclofos-methyl의 잔류현황을 파악한 결과 낮은 잔류량과 검출 빈도를 확인할 수 있었다. 특히 토양과 인삼 지상부(잎 줄기)에서는 전혀 검출되지 않았다. 본 연구결과를 통하여 인삼재배지 토양 및 인삼(뿌리, 잎 줄기)에 대하여 tolclofos-methyl의 잔류농약 안전성에 대한 문제가 지속적으로 개선될 것이며, 이에 대한 안전성은 확보될 수 있을 것으로 판단된다.

• 대한교통학회:학술대회논문집
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• 대한교통학회 1995년도 제27회 학술발표회
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• 분석과학
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• 제27권1호
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• pp.66-77
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• 2014

본 연구는 국내외에서 생산되는 다양한 식용유지에 대한 탄소 안정동위원소 비율 및 지방산 조성을 분석하고, 국내 유통 식용유지의 순수 여부 등 과학적 관리 방안을 위한 기초자료를 마련하고자 수행되었다. 본 연구에 수집된 식용유지의 탄소 안정동위원소 비율은 참기름 등 $C_3$ 식물군, $C_4$ 식물군인 옥수수유, 유의적인 차이가 인정되는 미강유 등 총 3개 그룹으로 구분이 가능하였다. 수거된 식용유지의 지방산 조성은 각각의 지방산 마다 식용유지별로 유의성을 나타내었다. 또한, 탄소 안정동위원소 비율만으로 구분이 어려웠던 $C_3$ 식물 기원의 식용유지는 지방산을 동시 활용한 산점도 분포 분석을 통해 대표적인 저가 식용유지인 콩기름과 고가 식용유지인 참기름의 구분이 가능하였다. 따라서 탄소 안정동위원소 비율과 지방산 조성을 동시 활용하여 식용유지의 판별이 부분적으로 가능하였으며, 이는 추후 식용유지류 관리 방안으로 검토할 예정이다.

• 한국작물학회지
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• 제42권1호
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• pp.7-13
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• 1997

생강나무의 향기성분 조성을 분석해 본 결과는 다음과 같다. 1. GC상에서 생강나무는 꽃, 잎, 줄기 각각 60, 80, 83개의 peak가 관찰되었으며, 주요 성분군은 생강나무의 경우는 꽃의 경우는 sabinene, $eta$-myrcene, 1-limonene, cir-3-hexanal, ${\gamma}$-terpinene, (Z)-3-hexen-1-ol acetate, ${\gamma}$-elemene, 1-borneol, $\delta$-guaiene, ledene, $\delta$-ca-dinene, elemol, 9-octadecanal, 1-(1,5diNe-4-hexenyl ) -4-mebenzene, $\alpha$-chamigrene, ${\gamma}$-selinene, $\beta$-endesmol, 1-phellandrene, 3-Me-6-(1-Me, ethyl ) -2-cyclohexen-1-one, epiglobulol의 성분이, 잎의 경우는 phellandrene, $\alpha$-terpinolene, sabinene, $\beta$-myrcene, ι-limonene, cis-3-hexanal, ${\gamma}$-terpinene, (Z)-3-hexen-1-ol acetate, ${\gamma}$-elemene, 1-borneol, $\delta$-guaiene, ledene, $\delta$-cadinene, olemol, 9-octadecanal, ${\gamma}$-selinene, o-chamigrene, 1-(1,5-diMe-4-hexenyl) -4-mebenzene, $\beta$-endesmol의 성분이, 줄기의 경우는 sabinene, $\beta$-myrcene, ι-limonene, phellamdrene, $\alpha$-terpinene, ledene, 1-borneol, ${\gamma}$-terpinene, 2,4a,5,6,7,8,9,9a-octahydroben-zocycloheptane, elemol, ${\gamma}$-selinene, cis-3-hexanal, (Z)-3-hexen-1-ol acetate, ${\gamma}$-elemene, $\delta$-guaiene, $\delta$-cadinene, 9-octadecanal, 1-(1,5-diMe-4-hexenyl) -4-mebenzeno, $\beta$-endesmol, $\alpha$-charugrene의 향기성분이 주요 성분군으로 확인되었다. 2. 생강나무에서 생강의 향기를 발산하는 성분으로는 $\beta$-myrcene, o-terpinolene, phellandrone, ι-limonene, $\beta$-eudesmol, $\delta$-cadinone, elemol, trans-caryophyllene으로 동정되었으며 그 중에서도 phellandrene, $\beta$-eudesmol이 주된 역할을 하는 성분으로 확인하였다.

• KSBB Journal
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• 제16권3호
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• pp.269-273
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• 2001

218종의 목본식물 자원으포부터 높은 항율력올 보인 Schima wallichii subsp. liukiuellsis로부터 항균활성물질을 추출, 정제하였다. Schim$\alpha$의 향균물질 추출에 가장 적합한 용매는 70% 에탄올이었으며, 계젤에 따른 항균활성은 차이를 보이지 않았고, 부위별로는 가을에 채취한 수피가 가장 좋았다. 조추출물을 유가용매로 정제하여 최종적으혹 buthanol 분획올 얻었고, 이를 silica gel과 sephadex LH-20 및 HPLC분석을 통 하여 흰색결정의 항균물질 Compound I을 얻었다. 항균물질은 UV, IR, MS분석 결과 aglycone으로 ${\alpha}$-sitosterol에 rhamnose, galactose, glucose가 1:1:1로 결합된 물질로 추정되었다. Compound I의 미생물에 대한 MIC는 3종의 bacteria에 L 1.25 g/L, 2종의 fungi에 5.0 g/L로 나타났으며, 효모에 대한 MIC는 0.04 g/L로 매우 높게 나타났다. Compound I은 천연 보존제, 의약품 등으로의 향후 개발이 기대된다.