Hopum is a new japonica rice cultivar developed from the cross between Milyang165 and F1 crossing Milyang165 and Iksan438 at Department of Rice and Winter Cereal Crop, NICS, RDA, in 2006. This cultivar has a short grain shape and about 141 days growth duration from direct seeding to harvesting in the southern plain including Chungcheong province. This cultivar has short culm and spikelet number per panicle is similar to that of Nampyeongbyeo, while filled grain rate is lower than standard variety. This cultivar has medium size of brown rice and shows moderate resistance to leaf blast, to bacterial blight pathogens of
This study was conducted to cultivate new Lepista nuda varieties with shorter cultivation period and better fruiting body compared to that of wild strains, for mass production and commercial application. Eighteen genetic resources of L. nuda were collected and grown in boxes using rice straw-fermented growth medium. Four lines with fruiting bodies were formed and selected as cross-breeding lines. Although 657 combinations were crossed through monospore crossing, only 17 combinations were bred between the 'CBMLN-19' line and the 'CBMLN-30' line. Among them, 8 lines with fast mycelial growth and high density were selected. After inoculating the rice straw-fermented growth medium with 14 genetic resources and 8 cross-breeding lines, their incubation period was investigated. Six of the cross-breeding lines completed their incubation in 20 days, while 7 of the 14 genetic resources took more than 40 days to complete their incubation, reducing the incubation period by more than 20 days in most cross-breeding lines. After the incubations were completed, the clay loam soil was covered with for post-cultivation, and when the mycelial cultivation was complete, the formation of fruiting bodies was induced after scraping the mycelial bodies under these environmental conditions: 14℃, 95% relative humidity or higher, and 1,500 to 2,000 ppm CO2 concentration. The temperature was reduced to 6℃ at night, resulting in a low temperature shock. Thus, 4 lines of fruiting bodies occurred from two genetic resources 'CBMLN-31' and 'CBMLN-44' and two cross-bred lines 'CBMLN-96' and 'CBMLN-103'. After inoculation, the longest period for fruiting bodies to occur was 100 days for the control:, the genetic resource 'CBMLN-31', and the shortest period (45 days) was observed for the cross-breeding line 'CBMLN-103'. The result of the investigation of the fruiting body characteristics shows that the cross-bred line 'CBMLN-103' showed a small form with 1.9 g of individual weight and 123validstipes per box, which was the highest incidence among the four lines. Another cross-bred line, 'CBMLN-96', had an individual weight of 5.5 g, which is larger than that of 'CBMLN-103'; however, the number of valid stipes per box was 30 less than that of 'CBMLN-103'. Quantity analysis showed that the control, 'CBMLN-31', had the highest quantity of 783 g per box, followed by the cross-bred line, 'CBMLN-96' with 165 g per box, and then the 'CBMLN-103' with 232 g. The quantity of the two crossbred lines was lower than that of the control 'CBMLN-31'; however, the amount of fruiting bodies was higher, and the cultivation period was shortened by 32 to 33 days. Therefore, these two lines would be selected as superior lines.
To obtain basic information on the Korean local corn lines a total of 57 lines were selected from 1,000 Korean local collection at Chungnam National University, classified by principal component analysis, and genetic nature was investigated. The results are summarized as follows. 1. There were a great variation in mean values of plant characters of the lines. The mean values of plant characters except for density of kernels varied with types of crossing. All characters except. for tasselling dates were reduced in magnitude when selfed, while those characters were increased when topcrossed. 2. The correlation coefficients among characters studied ranged front 0.99 to -0.59. The correlation coefficients among characters were not greatly changed depending upon types of crosses. 3. In order to classify the lines more effectively, selected 12 plant characters were used to classify 57 local lines by principal component analysis. The first four component could explain 86.4%, 83.4% and 81.1% of the total variations in sibbed lines, selfed lines and topcrossed lines, respectively. 4. Contribution of characters to principal component was high at upper principal components and low at lower principal components. 5. Biological meaning of the principal component and plant types corresponding to the each principal component were explained clearly by the correlation coefficient between principal components and characters. The first principal component appeared to correspond to the size of plant and ear. The second principal component appeared to correspond to the degree of differentiation in organs and the duration of vegetative growing period. But biological meaning of the third and fourth principal components was not clear. 6. The lines were classified into 4 lineal groups by the taxonomic distance. Group I included 52 lines which was 91.2% of total lines, group II 3 lines, group III 1 lines and group IV I lines, respectively. Four groups could be characterized as follows : Group I : early maturity, short-culmed, medium height plant, small ears, medium kernels and medium yielding. Group II : late maturity, medium height plant, small ears, small kernels, prolific ears and higher yielding. Group III : medium maturity, tall-culmed, small ears, small kernels and low yielding. Group IV : medium maturity, tall-calmed, large ears, one ear plant and me yielding. 7. The inbreeding depression varied with plant characters and lines. The characters such as yield, kernel weight per ear, ear weight and plant height showed great degree of inbreeding depression. Group I showed high inbreeding depression in such characters as 100 kernel weight, leaf number, plant height and days to tasselling, while group II showed high inbreeding depression in other plant characters. 8. Heterosis of plant characters varied also with lines. The ear weight, kernel weight per ear, yield, 100 kernel weight, and plant height were some of the plant characters showing high heterosis. Group II showed high values of heterosis in such characters as ear length, ear diameter, ear weight, kernel weight per ear, 100 kernel weight, and leaf length, while group I was high in heterosis in other plant characters. 9. The degree of homozgosity was highest in ear weight (79.1%) and lowest in ear number per plant (-21%). Group II showed higher degree of homozygosity than group I. 10. Correlation coefficients between characters of ribbed and topcrossed lines were positive for all characters. Highly significant. correlation coefficients between ribbed and topcrossed lines were obtained especially for characters such as ear number per plant, plant height, leaf length and yield per plot.
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.
This paper studies the time-space and appreciation of the performance culture of Gwanseo region, which is considered to have formed a characteristic culture in late Joseon period. For this purpose, 4 gasa written in hangeul (Korean alphabet), as well as 4 yeonhaeng gasa, 108 articles of Gwanseoakbu were examined. Plus, among the 9 types of yeonhaengrok (Documents of Performance culture) written in Chinese character, those parts which describe the performance traits have been analyzed. Then, 'main list of terminology' has been deduced based on the categorization according to the following points : 1) subjects of performance and appreciation 2) time and period of performance 3) space of performance 4) contents of performance 5) background and motive for performance and 6) method of performance. Through this process, various 'nouns' and 'predicate verbs' in relation to performance culture emerged, which were systemized according to types of performance elements and categories. Major terminology includes predicate verbs and symbolic verbs such as nokuihongsang,' 'baekdaehongjang,' 'jeolsaekgeumga,' 'cheonga,' 'hwaryu,' 'gamuja,' and 'tongsoja,' as well as the terms already known such as gisaeng, iwon, yangbang, akgong, and jeonak, which refer to musicians and dancers. Subjects of performance were divided into performers and listeners, categorized into concert, music, and dance, according to performance form. In the case for music, it was divided into instrumental or vocal, solo or accompanied (byeongju, self-accompaniment). In the case for vocal music, noteworthy was the inclusion of profesional artist's singing (called gwangdae or uchang). The record of 23 names of popular artists from Gwanseo region, with mention of special talents for each person, reflects the degree of activeness and artistic level of the province. Depending on the appreciating patrons, the audience were indicated as the terms including 'yugaek (party guest),' jwasang,' 'on jwaseok,' and 'sonnim (guests).' It seems that appraisal for a certain performance was very much affected by the tastes, views, and disposition of the appreciating patrons. Therefore it is interesting to observe different comparative reviews of concerts of different regions given by literary figures, offering various criticism on identical performance. In terms of performance space, it has been divided into natural or architectural space, doing justice to special performance sites such as a famous pavilion or an on-the-boat performance. Specific terms related to the scale and brightness of stage, as well as stage props and cast, based on descriptions of performance space were found. The performance space, including famous pavilions; Yeongwangjeong, Bubyeokru, Baeksangru, Wolparu, and Uigeomjeong, which are all well-known tourist sites of Gwanseo province, have been often visited by viceroys. governors, and envoys during a tour or trip. This, and the fact that full-scale performances were regularly held here, and that more than 15 different kinds of boats which were used for boat concert are mentioned, all confirm the general popularity of boat concerts at the time. Performance time, categorized by season or time of day (am/pm/night) and analyzed in terms of time of occurrence and duration, there were no special limitation as to when to have a performance. Most morning concerts were held as part of official duties for the envoys, after their meeting session, whereas evening concerts were more lengthy in duration, with a greater number of people in the audience. In the case of boat concert, samples include day-time concert and performances that began during the day and which lasted till later in the evening. Major terminology related to performance time and season includes descriptions of time of day (morning, evening, night) and mention of sunset, twilight, moonlight, stars, candles, and lamps. Such terms which reflect the flow of time contributed in making a concert more lively. Terminology for the contents of performance was mostly words like 'instrumental,' 'pungak,' or 'pungnyu.' Besides, contextual expressions gave hints as to whether there were dance, singing, ensemble, solo, and duets. Words for dance and singing used in Gwanseo province were almost identical to those used for gasa and jeongjae in the capital, Hanyang. However, many sentences reveal that performances of 'hangjangmu' of hongmunyeon, sword dance, and baettaragi were on a top-quality level. Moreover, chants in hanmun Chinese character and folk songs, which are characteristic for this region, show unique features of local musical performance. It is judged that understanding the purpose and background of a performance is important in grasping the foundation and continuity of local culture. Concerts were usually either related to official protocol for 'greeting,' 'sending-off,' 'reports,' and 'patrols' or for private enjoyment. The rituals for Gwanseo province characteristically features river crossing ceremony on the Daedong river, which has been closely documented by many. What is more, the Gwanseo region featured continued coming and goings of Pyeongan envoys and local officers, as well as ambassadors to and fro China, which required an organized and full-scale performance of music and dance. The method of performance varied from a large-scale, official ones, for which female entertainers and a great banquet in addition to musicians were required, to private gatherings that are more intimate. A performance may take the form of 'taking turns' or 'a competition,' reflecting the dynamic nature of the musical culture at the time. This study, which is deduction of terminology in relation to the time-space and appreciation culture of musical performances of Gwanseo region in late Joseon period, should be expanded in the future into research on 'the performance culture unique to Gwanseo region,' in relation to the financial and administrative aspects of the province, as well as everyday lifestyle. Furthermore, it could proceed to a more intensive research by a comparative study with related literary documents and pictorial data, which could serve as the foundation for understanding the use of space and stage, as well as the performance format characteristic to Korean traditional performing arts.