This study divided the area capable of producing domestic forage into grazing pasture, hay production area, and silage crop area, calculated the required area according to the forage production volume, and examined whether self-sufficiency in forage leads to cost savings. When the self-sufficiency rate of forage for dairy cows and Hanwoo is 80%, the improvement in profitability per heaf ranges from 3% to 9%, typically around 5%, which is considered a significant benefit for both corporate and individual businesses. The average profit per ranch is expected to increase about KRW 50 million per year, and the country as a whole is expected to reduce forage costs by KRW 0.9 trillion per year. Recently, efforts are being made by the government and local authorities to cultivate summer forage at the rice fields for improving self-sufficiency in forage feed to stabilize rice supply and demand. Furthermore, it is also necessary to conduct research on reducing the cost of concentrated feed and TMR (Total mixed ration).

The current survey form of grassland has not played its role in managing the grassland effectively because of the ambiguous questionnaire items and the absence of method and time of the investigation. Therefore, this study was conducted to clarify and add the items for effective of grassland management. The survey form of grassland was regulated in Article 16 of the Enforcement Rules of the Grassland Act (Survey on Grasslands Management Status, etc.). The five contents that needed improvement were the grassland owner, the survey timing and method of established grassland, grassland used livestock, grassland usage condition, and grassland grade. In the improved survey form of grassland, the grassland owner was changed to the grassland manager. In addition, ‘Survey by each land’ was added to the improved survey form in which the managers can survey each land. The dimension of each grassland establishment method was deleted in the grassland establishment time and method. In the livestock using grassland, the number of livestock and the area where livestock are used were added, and the number of other livestock was added, too. The grassland grade was decided as the combined score by three evaluation categories; grassland usage, the ratio of forage production in grassland and kinds of forage. The high, middle, and low grades were over 8, 6~7, and under 5 points in the combined score, respectively. The results show that the changed survey form of grassland can make grassland management more efficient by materializing the subject of grassland management and the survey terminology and methods.

As a means to activate eco pastoral system in alpine grassland, the government can consider public pastures, which are currently unused, to scale them up into public ranches. Depending on ownership and operation, four management models proposed as follows: 1) Government-Owned and Operated with Balanced Profit and Loss 2) Government-Owned and Operated with Revenue Generation 3) Government-Owned but Privately Operated by Outsourced to Professional Manager 4) Full Privatization (Ownership and Operation by Private Individuals). The study outlined above proposes four management models for the activation of eco pastoral system in alpine grassland. It also suggests methods for the selection and performance evaluation of manager to establish a profitable structure. Additionally, the research provides management methods for the conservation of grazing ecology in pastoral ecosystems. Particularly, the adaptation of tools commonly used in South Korean business sector for the selection and performance evaluation of manager within the system of the proposed management models. This aspect is deemed valuable as it aligns these tools with the specific characteristics of eco pastoral system in alpine grassland, contributing not only to the effective implementation of the models but also to the enhancement of the revenue structure.

This study was to investigate the cultivation technique previously conducted cultivation research for the stable production of alfalfa and to present further research. The data used in the study were 270 alfalfa cultivation experimental data from 1983 to 2008, indicating the cultivation region, field type, variety, sowing, cutting frequency, fertilization, and dry matter yield (DMY). The average DMY of alfalfa in the Republic of Korea was 12,536 kg/ha, which differed greatly depending on the cultivated region. Most of the field type was cultivated in upland. In order to increase alfalfa production, it is necessary to use reclaimed and unused land, and research on the soil amendment matter to improve the soil condition is needed. Alfalfa varieties cultivated an amount of 53, but collected data no studies considered fall dormancy, the criteria for selecting alfalfa varieties, so further research is required. The fertilizer did not consider each component at various levels, and research is needed as the demand for fertilizer. In particular, research on potassium is needed considering the increase in alfalfa production. The alfalfa cutting frequency differed in the estimated pasture production period depending on the region, and the DMY tended to increase with increasing cutting frequency. This suggests that the alfalfa DMY can be increased according to the cutting frequency in the Republic of Korea, so research is needed to present the appropriate cutting frequency.

This study was conducted to estimate the damage of Whole Crop Corn (WCC; Zea Mays L.) according to abnormal climate using machine learning as the Representative Concentration Pathway (RCP) 4.5 and present the damage through mapping. The collected WCC data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. The machine learning model used DeepCrossing. The damage was calculated using climate data from the automated synoptic observing system (ASOS, 95 sites) by machine learning. The calculation of damage was the difference between the dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCC data (1978-2017). The level of abnormal climate by temperature and precipitation was set as RCP 4.5 standard. The DMYnormal ranged from 13,845-19,347 kg/ha. The damage of WCC which was differed depending on the region and level of abnormal climate where abnormal temperature and precipitation occurred. The damage of abnormal temperature in 2050 and 2100 ranged from -263 to 360 and -1,023 to 92 kg/ha, respectively. The damage of abnormal precipitation in 2050 and 2100 was ranged from -17 to 2 and -12 to 2 kg/ha, respectively. The maximum damage was 360 kg/ha that the abnormal temperature in 2050. As the average monthly temperature increases, the DMY of WCC tends to increase. The damage calculated through the RCP 4.5 standard was presented as a mapping using QGIS. Although this study applied the scenario in which greenhouse gas reduction was carried out, additional research needs to be conducted applying an RCP scenario in which greenhouse gas reduction is not performed.

홀스타인 착유우에 수입건초 대신 WCRS로 조사료 일부를 대 체 급여하였을 때 산유성적 및 수익성에 미치는 영향을 검토하였 다. 대조구(C)는 농가 관행 급여방법으로 자가 혼합건초(13kg)와 농후사료(2.6~9.6kg), 오차드그라스 및 버뮤다그라스 건초(1.8kg) 를 급여 하였고, 처리구(T)는 자가 혼합건초(9.6kg)와 농후사료 (2.6~9.6kg) 및 WCRS (2.2kg)를 급여하였다. 건물수량(DMI)을 기준으로 C에 대한 T의 조사료 대체비율은 20% 였다. CP함량은 오차드그라스 및 버뮤다그라스 건초가 각각 11.3 및 8.4%였고, WCRS는 4.6%로, WCRS에서 낮았다. 이는 벼를 수확적기보다 약 30일정도 늦게 수확한 것에 기인하고 있다. DMI는 비유초기, 중기 및 후기에서 각각 T가 C보다 유의적으로 낮게 나타났다 (p<0.05). 유량은 비유초기, 중기 및 후기 모두 처리간 유의적 차 이는 없었다(p>0.05). 실험 기간 중 평균유량도 C 및 T가 각각 26.9 및 26.3kg으로 처리간 유의적인 차이는 없었다(p>0.05). 유 지율, 유단백 및 총고형물에서 각 비유기 공히 처리 간에 유의적 인 차이는 없었다(p>0.05). 두당 조수입은 C가 21,141원, T가 21,915원으로 T에서 다소 높게 나타났다. 유사비는 T가 22.9%로 C의 27.8%보다 낮았다. 이상에서 수입산 건초 대신 WCRS로 20% 대체 급여하여도 산유량 및 유성분에 유의적인 차이가 없으 며 수익은 높아 경제성이 있는 것으로 사료된다.

The Joseon royal family considered the act of burying the placenta very important for various reasons. Accordingly, they developed their own ritual culture of burying the placenta based on the geomancy(Pungsu). In 1661, The King Sukjong's placenta chamber was built in Gong-ju, and later stone objects were added in 1683. Since its establishment, the King Sukjong’s placenta chamer have been continuously managed by the Joseon royal family, but During the Japanese colonial period, the placenta chamber was partially destroyed, and now only some stone objects remain in the original site. This study aims to estimate the original style and structure of King Sukjong's placenta chamber by focusing on the stone objects which were discovered through recent field surveys. In addition to that, the stylistic review of Joseon Dynasty's royal placenta chamber was conducted to secure a literary data basis and acquired data were comprehensively analyzed. As a result, Some of the original style and structure of King Sukjong's placenta chamber could be confirmed. The results of this study are expected to help restore the authenticity of the royal placenta chamber damaged in japanese colonial period, and are expected to be a good example in the research methodology of historical evidence of other damaged royal placenta chambers.

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMYnormal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 ㎧). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

기존 화석 연료의 고갈 및 환경오염의 문제와 대용량 발전을 위하여 해양환경 및 자원을 이용한 친환경에너지 발전에 대한 연구 및 개발이 증가하고 있으며, 이 중 높은 발전 효율을 가진 해상태양광 발전에 대한 연구가 크게 증가하고 있다. 환경하중이 비교적 약한 내수조건과 달리, 환경하중이 강한 해양에서의 태양광 발전을 위해서는 더 강한 강성의 구조재를 사용해야 한다. 하지만, 구조재의 생 산 가능성, 무게를 포함한 구조물 특성 및 경제적 효율성 등의 제약조건이 발생할 수 있다. 따라서, 본 연구에서는 부유식 방파제를 설 치함으로써 태양광구조물에 작용하는 파랑하중을 감소시켜 구조재의 강성 강화를 최소화하고자 하였다. 부유식 방파제의 크기 및 구 조물로부터의 거리를 변화하여 이에 따른 파랑하중 및 구조재 응력의 감소 정도를 확인하였다. 다수 부력체의 상호간섭을 고려한 파 랑하중의 경우, 고차경계요소법(Higher-Order Boundary Element Emthod)을 이용해 산정하였으며, 구조재에 작용하는 응력은 유한요 소법(Finite Element Method)을 통해 평가하였다. 각 조건에서의 최대응력을 분석 및 비교함으로써 해상태양광 발전 시스템에 대한 부 유식 방파제의 영향을 확인하였으며, 부유식 방파제의 크기가 파랑하중 및 구조재 응력 감소에 큰 영향을 미침을 확인하였다.

In this study, the appropriate unit cost in grassland establishment was redeveloped by the grassland establishment method and work criteria. The grassland establishment method was divided into tillage establishment (all logging) and no-tillage establishment (all logging and partial logging). The price for the work criteria by the establishment method was presented for each permission/authorization and establishment work. In permission/authorization for grassland establishment, the cost of each work criteria was of environmental impact (small scale environmental impact) assessment, disaster impact assessment, cadastral serving fee, forest survey, and connection fee for control of mountainous districts. In establishment was of logging, cleaning/gruffing, plowing/soil preparation, seeding, fertilization, livestock manure compost, seed, herbicide, labor cost (fertilizer, seed and herbicide), soil consolidation, cattle trail, and fence. The unit cost of grassland establishment was KRW 115,894,212 for the tillage establishment, and KRW 110,281,572 and KRW 106,680,122 for the all and partial logging of the no-tillage establishment, respectively. The current study redeveloped the establishment method, work criteria, and estimation of the unit cost of grassland establishment. It can be usefully used to carry out government projects to support related to establishment and maintenance of grassland.

본 연구는 기계학습을 통한 수량예측모델을 이용하여 이상기상에 따른 WCM의 DMY 피해량을 산출하기 위한 목적으로 수행하였다. 수량예측모델은 WCM 데이터 및 기상 데이터를 수집 후 가공하여 8가지 기계학습을 통해 제작하였으며 실험지역은 경기도로 선정하였다. 수량예측모델은 기계학습 기법 중 정확성이 가장 높은 DeepCrossing (R2=0.5442, RMSE=0.1769) 기법을 통해 제작하였다. 피해량은 정상기상 및 이상기상의 DMY 예측값 간 차이로 산출하였다. 정상기상에서 WCM의 DMY 예측값은 지역에 따라 차이가 있으나 15,003~17,517 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 DMY 예측 값은 지역 및 각 이상기상 수준에 따라 차이가 있었으며 각각 14,947~17,571 kg/ha, 14,986~17,525 kg/ha 및 14,920~17,557 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 피해량은 각각 –68~89 kg/ha, -17~17 kg/ha 및 – 112~121 kg/ha 범위로 피해로 판단할 수 없는 수준이었다. WCM의 정확한 피해량을 산출하기 위해서는 수량예측모델에 이용하는 이상기상 데이터 수의 증가가 필요하다.

본 연구는 객토를 한 간척지에서 석고시용 수준이 알팔파의 수량과 사료성분에 미치는 영향을 알아보고자 수행하였다. 실험장소는 간척한지 17~33년 경과된 석문간척지로서 약 70 cm 정도 객토한 토양이었다. 객토에 사용한 흙은 섬토양의 제염을 하지 않은 것 이었다. 처리는 석고를 시용하지 않은 0 ton/ha 구(G0), 석 고를 2 ton/ha(G2) 및 4 ton/ha(G4) 시용한 구로 하였다. 수확은 알팔파가 개화초기(개화 10%)에 도달할 때 1차 수확하였으며 이 후 수확은 약 35일 간격으로 수확을 하였다. 알팔파의 건물수량은 1차 년도는 G2가 G0와 G4보다 유의적으로 높았으며 2차 년도는 처리간 유의적인 차이는 없었으나 G2가 G0와 G4보다 높은 경향을 보였다. G2에서 알팔파의 건물수량이 높은 이유는 토양의 pH 및 EC가 각각 재배가능 및 재배적합 수준이었고 피복도 및 알팔파 식생비율도 높은 것에 기인하였다. 1차 및 2차 년도 모두 석고 처리 간 CP, NDF 및 ADF 함량 및 RFV는 차이가 없었다. 한편 1차 및 2차 년도의 연구결과를 통해서 알팔파 건물수량에 부정적인 영향을 주는 요인은 봄의 가뭄과 여름의 집중된 강수로 나타났다. 이상으로부터 객토 간척지에서 석고 처리는 알팔파의 건물수량을 높이는데 효과적인 것으로 판단되며 2 ton/ha이 적정 수준인 것으로 사료된다.

This study was conducted to determine the possibility of estimating the daily mean temperature for a specific location based on the climatic data collected from the nearby Automated Synoptic Observing System (ASOS) and Automated Weather System(AWS) to improve the accuracy of the climate data in forage yield prediction model. To perform this study, the annual mean temperature and monthly mean temperature were checked for normality, correlation with location information (Longitude, Latitude, and Altitude) and multiple regression analysis, respectively. The altitude was found to have a continuous effect on the annual mean temperature and the monthly mean temperature, while the latitude was found to have an effect on the monthly mean temperature excluding June. Longitude affected monthly mean temperature in June, July, August, September, October, and November. Based on the above results and years of experience with climate-related research, the daily mean temperature estimation was determined to be possible using longitude, latitude, and altitude. In this study, it is possible to estimate the daily mean temperature using climate data from all over the country, but in order to improve the accuracy of daily mean temperature, climatic data needs to applied to each city and province.

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.