• 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.

• 핵의학기술
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• 제18권1호
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• pp.43-48
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• 2014

PET/CT검사에서 표준섭취계수(standardized uptake value, SUV)는 병소의 악성 여부를 판별하는 지표로서 인체내 각 장기의 생리적인 변화에 대한 정량분석을 가능하게 한다. 따라서 그 결과에 영향을 줄 수 있는 매개변수를 올바르게 입력하는 것이 매우 중요하다. 본 연구에서는 그 매개변수 중 방사능량, 체중, 방사성 동위원소 섭취시간의 입력오류에 따른 결과의 차이를 측정하여 수용 가능한 결과의 오차범위를 평가하고자 한다. 1994 NEMA 모형 내부에 열소, 테프론, 그리고 공기 3개의 삽입물을 위치시켰다. 총 27.3 MBq의 $^{18}F$를 열소와 배후 방사능 비율이 4:1로 되도록 채우고 GE Discovery STE 16(GE Healthcare, Milwaukee, USA)로 촬영하였다. 촬영 후 입력된 방사능량, 체중, 섭취 시간의 값을 기준 값에서 ${\pm}5%$, 10%, 15%, 30%, 50% 만큼 오차를 발생시킨 후 영상을 다시 재구성하였다. 재구성된 영상에서 각 삽입물 부위에 한 개, 배후방사능 부위에 총 네 개의 관심영역을 그린 후 $SUV_{mean}$과 백분율오차를 측정하여 비교 평가하였다. 기준 영상의 열소, 테프론 그리고 공기와 배후방사능에서의 $SUV_{mean}$은 각각 4.5, 0.02, 0.1 그리고 1.0이였다. 방사능량 오차 변화에 따른 $SUV_{mean}$의 최대값과 최소값은 열소에서 9.0, 3.0, 테프론에서 0.04, 0.01, 공기에서 0.3, 0.1, 배후 방사능에서 2.0, 0.6로 변화된 값을 보였다. 이 때 백분율오차는 모두 동일하게 최대 100%에서 최소 -33%로 나타났다. 체중 오차 변화의 경우 열소에서 2.2, 6.7, 테프론에서 0.01, 0.03, 공기에서 0.09. 0.28, 배후방사능에서 0.5, 1.5로 변화된 값을 보였다. 이 때 백분율오차는 테프론의 최소 -50%, 최대 52%를 제외하고 모두 최소 -50%에서 최대 50% 로 동일하게 나타났다. 섭취시간 오차의 경우 열소에서 3.8, 5.3, 테프론에서 0.01, 0.02, 공기에서 0.1, 0.2, 배후방사능에서 0.8에서 1.2로 변화된 값을 보였다. 백분율오차는 열소와 배후방사능은 최소 -14%에서 최대 17%로 동일하게 나타났으며 테프론의 경우 최소 -11%에서 최대 21%, 공기의 경우 최소 -12%에서 최대 20%로 나타났다. 일반적으로 수용 가능한 오차의 범위를 5%로 설정할 경우, 본 실험 결과에서 방사능량과 체중의 오차가 ${\pm}5%$ 이내 일 때 $SUV_{mean}$의 오차가 5% 범위에 포함되었다. 이러한 결과들을 고려해 볼 때 검사장비에 입력되는 방사능량과 체중에 직접적인 영향을 줄 수 있는 선량검량계와 체중계의 검교정은 오차범위 5% 이내로 이루어져야 한다. 섭취 시간의 경우 삽입물의 종류에 따라 서로 다른 오차 범위를 보였으며 열소와 배후방사능에서 오차가 ${\pm}15%$ 이내일 때 $SUV_{mean}$에 5% 내의 오차가 발생하였다. 따라서 검사 시 촬영용 스캐너를 포함하여 두 개 이상의 시계를 사용할 경우 각각의 시간 오차들도 함께 고려되어야 할 것이다.

• 한국수자원학회논문집
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• 제54권9호
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• pp.719-730
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• 2021

본 연구에서는 상류의 휴·폐광산을 비롯한 다양한 점오염원과 비점오염원으로부터 유실되는 오염물질의 영향을 받는 안동호를 대상으로 수질 및 수생태 모델인 SWAT-WET을 구축하고, 적용성을 평가하고자 한다. 안동호르 유입되는 오염물질에 대한 정량적인 평가를 위해 유역모델인 SWAT을 안동댐 유역(1,584 km²)을 대상으로 구축하여, 검보정을 수행하였다. 유출량과 수질 부하량(SS, T-N, T-P)에 대한 검보정 결과 R²는 각각 0.76, 0.69, 0.84, 0.60 이상으로 분석되었다. 검보정된 SWAT의 유출량과 영양물질의 농도를 WET의 입력자료로 적용하여 안동호에 대한 수질, 수생태 모델 WET을 구축하였다. WET의 매개변수 민감도 분석 결과를 이용하여, 안동호의 수온, 용존산소, 수질농도(T-N, T-P)를 대한 검보정을 수행하였다. 검보정 결과 PBIAS는 각각 +19%, -13%, +4%, +26.5% 로 분석되었으며, 관측 자료를 유의한 수준으로 모의하는 것을 확인하였다. 저서동물의 관측 건중량(gDW/m²)은 0.5 이하였으나 모의 건중량의 평균은 0.8로 분석되었으며, 이는 WET 모델이 더 넓은 개념의 저서동물을 고려하기 때문으로 나타났다. 관측자료 부족으로 정확한 검보정은 어렵지만, 유역모델과의 연계를 통한 장기간 모의와 상류 유역환경변화가 호소에 미치는 영향을 분석할 수 있으므로 안동호의 수환경 관리를 위한 기초 자료로 활용될 수 있을 것으로 판단된다.

• 한국임상약학회지
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• 제11권2호
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• pp.49-56
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• 2001

Acetyl-L-carnitine (ALC), an endogenous component of the L-carnitine family, is a naturally existing molecule synthesized from L-carnitine (LC) by carnitine acetyl transferase. ALC has been shown to improve the cognitive performance of patients suffering from dementia of the Alzheimer's type and proposed for treating Alzheimer's disease in pharmacological doses. The purpose of the present study was to evaluate the bioefuivalence of two ALC tablets, $Nicetile^{TM} (Dong-A Pharmaceutical Co.) and $L-Cartin^{TM}$ (Kuhn Il Pharmaceutical Co.), according to the guidelines of Korea Food and Drug Administration (KFDA). The ALC release from the two ALC tablets in vitro was tested using KP VII Apparatus II method in various dissolution media (pH 1.2, 6.0 and 6.8). Twenty six normal male volunteers, $24.46\pm3.67$ years in age and $64.45\pm5.54$ kg in body weight, were divided into two groups and a randomized $2\times2$cross-over study was employed. After one tablet containing 500 mg of ALC was orally administered, blood was taken at predetermined time intervals and the concentrations of ALC in serum were determined using HPLC with fluorescence detector. Because of the presence of endogenous ALC, the calibration was performed using dialyzed serum. The dissolution profiles of the two ALC tablets were similar in all the dissolution media. The pharmacokinetic parameters such as $AUC_t,\;C_{max}\;and\;T_{max}$ were calculated and ANOVA was utilized for the statistical analysis of the parameters. The results showed that the differences in $AUC_t,\;C_{max}\;and\;T_{max}$ between two tablets were $0.35\%,\;0.93\%\;and\;2.34\%$ respectively, when calculated against the $Nicetile^{TM} tablet. The powers $(1-\beta)\;for\;AUC_t$ , and Cmax were $98.72\%\;and\;85.48\%$, respectively. Minimum detectable differences $(\Delta)\;at\;\alpha=0.05\;and\;1-\beta=0.8$ were less than $20\%,\;(e.g.,\;13.21\%\;and\;18.42\%\;for\;AUC_t,\;and\;C_{max}$ respectively). The $90\%$ confidence intervals were within $\pm20\%\;(e.g.,\;-7.38\sim8.09\;and\;-9.86\sim11.72\;for\;AUC_t,\;and\;C_{max}$, respectively). These two parameters met the criteria of KFDA for bioequivalence, indicating that $L-Cartin^{TM}$ tablet is bioequivalent to $Nicetile^{TM} tablet.

• 한국식품위생안전성학회지
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• 제28권3호
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• pp.222-226
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• 2013

Chloropicrin은 국내에서는 사용되지 않으며, 잔류허용기준이 불검출로 설정된 농약이다. 그러나 중국에서는 훈증제, 살균제, 살선충제 및 저장 곡물의 살충제로 사용되고 있으며, 잔류허용기준이 설정되어 있다. 따라서 본 연구에서는 중국 등에서 수입하는 식품 중 국내에서 사용하지 않는 농약에 대한 안전성을 확보하기 위하여 해당 농약을 신속하고 빠르게 검출할 수 있는 시험법을 개발하고자 하였다. Chloropicrin은 분자량이 작고 휘발성이 큰 화합물이므로 헤드스페이스 추출법을 활용하여 검체 추출액을 직접 GC에 주입하는 시험법을 개발하였으며, 확립된 시험법을 검증한 결과 회수율이 77.7~79.3%로 조사되어 코덱스 국제가이드라인(CAC/GL 40)에 적합함을 확인하였다. 정량한계 또한 0.05 mg/kg 이하로 매우 우수한 감도를 가지고 있음을 확인하였으며, GC-MS를 이용한 재확인과정을 추가로 확립하여 본 시험법의 신뢰도를 높였다. 확립된 시험법은 식품에 잔류할 수 있는 농약의 기준 준수여부에 대한 적합성을 판단하기 위한 공정시험법으로 활용되고 있다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1281-1281
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• 2001

Near-infrared (NIR) spectra have bean measured for high-density (HDPE), linear low-density (LLDPE), and low-density (LDPE) polyethylene in pellet or thin films. The obtained spectra have been analyzed by conventional spectroscopic analysis methods and chemometrics. By using the second derivative, principal component analysis (PCA), and two-dimensional (2D) correlation analysis, we could separate many overlapped bands in the NIR. It was found that the intensities of some bands are sensitive to density and crystallinity of PE. This may be the first time that such bands in the NIR region have ever been discussed. Correlations of such marker bands among the NIR spectra have also been investigated. This sort of investigation is very important not only for further understanding of vibration spectra of various of PE but also for quality control of PE by vibrational spectroscopy. Figure 1 (a) and (b) shows a NIR reflectance spectrum of one of the LLDPE samples and that of PE, respectively. Figure 2 shows a PC weight loadings plot of factor 1 for a score plot of PCA for the 16 kinds of LLDPE and PE based upon their 51 NIR spectra in the 1100-1900 nm region. The PC loadings plot separates the bands due to the $CH_3$ groups and those arising form the $CH_2$ groups, allowing one to make band assignments. The 2D correlation analysis is also powerful in band enhancement, and the band assignments based upon PCA are in good agreement with those by the 2D correlation analysis.(Figure omitted). We have made a calibration model, which predicts the density of LLDPE by use of partial least square (PLS) regression. From the loadings plot of regression coefficients for the model , we suggest that the band at 1542, 1728, and 1764 nm very sensitive to the changes in density and crystalinity.

• 대한화장품학회지
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• 제40권4호
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• pp.359-364
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• 2014

본 연구에서는 합성보존제로 흔히 쓰이는 메칠파라벤과 방부효능을 가지는 천연추출성분인 p-아니식애씨드를 HPLC를 통해 분리분석 하는 방법을 개발하였다. 메칠파라벤과 p-아니식애씨드는 같은 분자량(152.15 g/mol)과 비슷한 구조, 같은 최대흡수파장(250 nm)을 보이기 때문에 HPLC로 분석 시 동일한 RT값(13.3 min)을 갖는다. 본 연구 저자들은 아세틸화 반응을 통해 메칠파라벤을 선택적으로 유도체화 한 후 C18 컬럼을 통해 분석했을 때 두 물질이 분리됨을 확인하였다. 아세틸화반응을 거치면서 메칠파라벤의 피크유지시간이 13.3 min에서 23.9 min으로 이동하였으며, 평균값은 $23.9{\pm}0.1min$, 피크면적 값은 $5042882{\pm}4778$로 일정하게 나타났다. 또한 직선성의 평가에서 결정계수값은 0.9999658로 1에 가까운 값을 보였다. 시료의 검출한계는 $1.47{\mu}g/mL$이었고 정량한계는 $4.44{\mu}g/mL$이었다. 결론적으로 본 연구를 통해 개발된 분석법은 화장품 분야에서 유사한 구조를 가진 보존제 분석에 유용하게 사용될 수 있을 것으로 기대된다.

• 한국환경보건학회지
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• 제40권2호
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• pp.114-126
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• 2014

Objectives: We aimed to develop a measurement method of five metabolites of trichloroethylene (TCE) in a concurrent biological sample, e.g., trichloroacetic acid (TCA), dichloroacetic acid (DCA), S-(1,2-dichlorovinyl) glutathione (DCVG), S-(1,2-dichlorovinyl)-L-cysteine (DCVC), and N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NAcDCVC) and to validate the method before application to pharmacokinetic study. Methods: TCE metabolites were simultaneously analyzed using high performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC-ESI-MS/MS) with as little as 50 ${\mu}L$ of serum and urine. DCA, TCA and NAcDCVC were extracted with diethyl ether, while DCVC and DCVG were extracted by solid phase extraction. This method was validated according to the guidelines for bioanalytical method validation of the Korean National Institute of Toxicological Research. Then, we determined the five metabolites in five strains of mice at 24 hr after exposure to 1 g TCE /kg body weight. Results: The limits of detection for the five metabolites in biological samples ranged from 0.001 to 0.076 nmol/mL, which is comparable to or better than those previously reported. Most calibration curves showed good linearity ($R^2=0.99$), and between-batch variation was less than 20% expressing acceptable robustness and reproducibility. Using this method, we found TCA and DCA were detected in all test mice at 24 hr after the oral administration while NAcDCVC and DCVC were detected in some strains, which showed strain-dependent metabolism of TCE. Conclusions: The present method could provide robust and accurate measurements of major key metabolites of TCE in biological media, which allowed concurrent analysis of TCE metabolism for limited amounts of biospecimens.

• 한국융합학회논문지
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• 제8권11호
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• pp.49-56
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• 2017

컬링 스위핑 동작은 컬링 스톤의 위치를 조절하는 중요한 동작 중 하나이며, 스위핑 속도와 브룸 패드에 가해지는 힘이 중요한 연구 대상이다. 본 연구에서는 컬링 스위핑 동작에서 컬링 브룸 패드에 가해지는 힘을 측정할 수 있는 장비를 개발하였으며, 두 개의 로드셀을 브룸 패드와 패드 홀더 사이에 장착하는 구조를 이용하였다. 로드셀에서 발생되는 아날로그 신호는 마이크로 제어기를 이용하여 초당 약 300회의 속도로 샘플링을 수행한 후 10 bit 디지털 신호로 변환하였다. 3개의 M1 급 분동을 이용하여 로드셀의 교정과 측정된 전기 신호를 질량(힘)으로 환산하는 회귀 방정식을 추출하였으며, 브룸의 무게 증가를 최소화하기 위해서 웨어러블 장비로 구성하였다. 스포츠 분야에서 힘 측정 시 기준 장비로 사용하는 지면 반력기와 개발된 장비에 동일한 힘을 가하면서 측정된 측정값 차이는 약 $0.909{\pm}1.375N$ (평균과 표준 편차)로 측정되었다. 개발된 장비는 스위핑 동작과 유사한 힘 측정을 필요로 하는 다른 종류의 연구에도 적용이 가능할 것으로 판단된다.

• 생물환경조절학회지
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• 제24권1호
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• pp.39-44
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• 2015

무토양재배에서 작물의 생산성 향상을 위하여 최적의 수분관리가 중요하기 때문에, 배지의 종류에 따른 수분 이동을 포함한 배지의 물리적 특성의 분석이 필요하다. 본 연구의 목적은 현재 상업적으로 많이 이용되고 있는 대표적인 배지를 대상으로 물리적 특성을 분석하고 수분의 이동 형태 및 함수율과 FDR 센서 측정값과의 관계를 파악하는 것이다. 로드셀을 이용하여 배지의 중량을 측정하고, 이 데이터를 바탕으로 배지의 기본적인 물리적 특성을 파악하고자 하였다. 중량에 따른 실제 함수율과 FDR 센서값의 비교를 통해 배지 종류에 따른 FDR의 정확성을 비교하였다. 암면에 비하여 코이어 배지는 입자가 크고 거친 특성 때문에 전체적으로 보수력이 낮았다. 중량 기준의 동일 함수율 조건에서 FDR센서 측정값은 코이어에서 큰 오차를 보였으므로 FDR센서 사용전 보정이 필요하다. 그리고 코이어의 낮은 보수력과 재수화력 때문에 관수제어에 적합한 함수율 범위도 암면에 비하여 좁았다. 무토양재배에서 최적 관수제어를 위한 관수전략 수립에 실험을 통한 위와 같은 데이터가 유용하게 이용될 수 있을 것으로 기대된다.