• KOREAN POULTRY JOURNAL
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• v.41 no.6
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• pp.98-102
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• 2009

닭의 피부는 땀샘(汗腺)이 없어서 증산작용으로 체온발산이 불가능하기 때문에 고온의 환경하에서는 입을 벌려 헐떡거림(panting)을 위주로 체온을 발산시키고, 일부는 볏, 고기수염, 얼굴 등을 통하여 증발작용을 한다. 특히 육계는 증체가 빠르고 이를 뒷받침하기 위한 체내 대사가 활발하기 때문에 여름철을 슬기롭게 대처하기 위한 세심한 주의가 요구된다. 우리나라와 같이 여름철 고온다습(高溫多濕)한 기후조건에서 계사 환경온도 유지가 어렵고, 열 스트레스를 줄이는 것이 쉽지 않다. 농장주는 여름철 더위에 의한 생산성 저하는 물론이고, 짧은 시간에 닥칠 수도 있는 혹서기 대량폐사를 막기 위하여 외부환경 변화상황을 주지하고서 각자가 소유하고 있는 계사의 환경과 닭의 상태를 주의 깊게 관찰함은 물론 피해를 최소한으로 감소시키기 위한 나름대로의 노하우를 가지고 대처하지 않으면 애써 노력한 결과가 혹서기 잠깐 사이에 큰 피해를 초래할 수도 있다는 인식을 가지고 있어야 한다. 환경온도와 상대습도 등의 생활에 큰 영향을 미친다. 환경온도, 상대습도 등이 닭의 생리에 미치는 영향을 알아보고 혹서기와 우기에 닭 사양관리를 알아보자.

• Proceedings of the Korean Society of Food and Cookery Science Conference
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• 2001.06a
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• pp.298-308
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• 2001

장류는 콩을 주재료로 하는 우리 나라의 전통적인 발효식품으로서 중요한 조미료로 사용되고 있다. 장의 종류는 우리 고유의 전통식 제법에 의한 재래형과 일본식 또는 중국식 제법에 의한 외래형으로 나눌 수 있는데 간장, 된장, 청국장, 고추장 등이 포함된다. 또한 가정에서 담그는 장류와 산업체에서 다량 제조하는 것으로 나눌 수 있다. 장류는 그 원료, 지방의 기후, 환경 등 기타 요인에 의해 변화를 보이며 제조법이 차이가 나는데 맛은 메주에 의해 좌우된다 우리 나라에서 장류가 산업적으로 생산하기 시작한 것은 일본인의 정치 침투와 더불어 시작되었으며, 해방이후 국군이 창설되면서 수요가 갑자기 증가하였다. 또한 서구화의 영향으로 사회구조가 바뀌고 인구의 도시집중화, 주택구조 변화와 자가 제조 등의 어려움으로 공장제품에 대한 수요가 따라서 증가하였다. 최근에는 장류는 조미료로서의 역할 이외에 영양 강화나 생리활성물질을 함유한 식품으로서 그 가치를 찾을 수 있다. 우선 장류가 어떻게 발전되어 왔으며, 가정에서 담가먹지 않고 시판 중인 제품을 구입하는 경우 어떤 종류의 장이 판매되고 있으며 어느 산업체에서 생산되고 있는지 알아본다. 현재 장류를 상품화하고 또 편의식품화 하려고 할 때 문제점과 장류 산업이 나아가야 할 방향에 대해 소개하고자 한다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.234-235
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• 2019

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.105-107
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• 2014

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.298-306
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• 2016

Planting date shift is one of the means of adapting to climate change in Kimchi Cabbage growers in major production areas in Korea. This study suggests a method to estimate the potential yield of Kimchi Cabbage based on daily temperature accumulation during the growth period from planting to maturity which is determined by a plant phenology model tuned to Kimchi Cabbage. The phenology model converts any changes in the thermal condition caused by the planting date shift into the heat unit accumulation during the growth period, which can be calculated from daily temperatures. The physiological maturity is estimated by applying this model to a variable development rate function depending either on growth or heading stage. The cabbage yield prediction model (Ahn et al., 2014) calculates the potential yield of summer cabbage by accumulating daily heat units for the growth period. We combined these two models and applied to the 1km resolution climate scenario (2000-2100) based on RCP8.5 for South Korea. Potential yields in the current normal year (2001-2010) and the future normal year (2011-2040, 2041-2070, and 2071-2100) were estimated for each grid cell with the planting dates of July 1, August 1, September 1, and October 1. Based on the results, we divided the whole South Korea into 810 watersheds, and devised a three - dimensional evaluation chart of the time - space - yield that enables the user to easily find the optimal planting date for a given watershed. This method is expected to be useful not only for exploring future new cultivation sites but also for developing cropping systems capable of adaptation to climate change without changing varieties in existing production areas.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.82-87
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• 2019

Global warming has a significant impact on diverse ecosystems including agroecosystem through; changing of phenology, physiology and distribution. Monitoring of biological responses emanating from global warming is required to understand the challenges of biological diversity conservation posed by climate change. The Korean government selected four butterfly species as indicators of climate change in agroecosystem: Papilio xuthus, Pieris rapae, Colias erate, and Eurema mandarina. The aim of this study was to investigate the different monitoring methods of the butterflies in Korea and suggest a suitable monitoring method to track the population trends of butterflies in the agroecosystem. Butterfly monitoring was conducted in eight sites throughout Korea from April to October, 2018 using three survey methods: point census at rice paddy area, point census at the border between rice paddy and hill and line transect along the rice paddy and hill. Each method took approximately 30 min. to count the butterflies. A total of 4,691 butterflies and 92 species were counted: The most dominant species was Pieris rapae with a total count of 1,205 individuals followed by Polygonia c-aureum, Zizeeria maha, Colias erate, Cupido argiades and Papilio xuthus. Among the three census methods, the total number of species and individuals when using line transect method was statistically higher than in the other methods. However, the numbers of the four butterflies indicators showed no difference throughout three census methods. Based on the number of species and the total individuals butterflies in agroecosystem, we advocate for the application of line transect method as it can find more butterflies in agroecosystem. In addition, we advised for the implementation of education programs on the line transect method in butterfly identification to participants of the national monitoring program.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

• Journal of Aquaculture
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• v.16 no.3
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• pp.135-141
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• 2003

Physiological responses (cortisol, glucose, lactic acid, osmolality and hematology) of olive flounder (Paralichthys olivaceus) to stressors associated with confinement and subsequent transport were investigated. Specimens were subjected to confinement stress for 3 h, prior to transport for 15 h. Two different size cohorts of the fish, large (839.6$\pm$162.7 g) and small (98.2$\pm$14.8 g), were used. Experimental cohorts of the fish were divided into 3 groups for blood sampling: group A, sampled at the beginning of confinement and 3 h before transport (BT, -3 h), after confinement and at the beginning of transport (BT, 0 h), 3 h after transport had begun (AT, 3 h), and after 15 h transport (AT, 15 h); group B, sampled at BT, 0 h, at AT, 3 h, and at AT, 15 h; and, group C, sampled at AT, 3 h, and at AT, 15 h. In the cohort of large fish, plasma cortisol levels of the A group were increased over time, from 4.2 ng/ml (BT,-3 h), to 92.0 ng/ml (BT, 0 h), 118.5 ng/ml (AT, 3 h) and 105.5 ng/ml (AT, 15 h). A similar pattern was evident in the B group, in which cortisol increased from 47.5 ng/ml (BT, 0 h) to 53.5 ng/ml (AT, 15 h); and, for the C group, in which cortisol increased from 43.5 ng/ml (AT, 3 h) to 71.5 ng/ml (AT, 15 h). Glucose levels of the A group also were significantly increased, from 39.5 mg/dl (BT,-3 h), to 121.0 mg/dl (BT, 0 h),298.0 mg/dl (AT, 3 h) and 260.5 mg/dl (AT, 15 h). Lactic acid levels increased markedly during transport, from less than 1 mmol/L (BT, 0 h) to 12.0 mmol/L (AT, 15 h). Plasma osmolality increased from 405.5 mOsm/kg (BT, -3 h, for group A) to values near 500 mOsM/kg subsequent to confinement and transport. In the small-size cohort, plasma cortisol, glucose, lactic acid and osmolality levels showed similar but less pronounced trends than those observed for the large-size cohort. This research provides baseline data on cortisol, glucose, lactic acid, osmolality and hematological responses to confinement and transport, which should be useful to aquaculturists working with olive flounder and to scientists studying other flatfish species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.57-67
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• 2020

Pinus densiflora is the most widely distributed tree species in South Korea. Its ecological and socio-cultural attributes makes it one of the most important tree species in S. Korea. In recent times however, the distribution of P. densiflora has been affected by dieback. This phenomenon has largely been attributed to climate change. This study was conducted to investigate the responses of growth and physiology of P. densiflora to drought and nitrogen fertiliz ation according to the RCP 8.5 scenario. A Temperature Gradient Chamber (TGC) and CO₂. Temperature Gradient Chamber (CTGC) were used to simulate climate change conditions. The treatments were established with temperature (control versus +3 and +5℃; aCeT) and CO₂ (control: aCaT versus x1.6 and x2.2; eCeT), watering(control versus drought), fertilization(control versus fertilized). Net photosynthesis (P_n), stomatal conductance (g_s), biomass and relative soil volumetric water content (VWC) were measured to examine physiological responses and growth. Relative soil VWC in aCeT significantly decreased after the onset of drought. P_n and g_s in both aCeT and eCeT with fertiliz ation were high before drought but decreased rapidly after 7 days under drought because nitrogen fertilization effect did not last long. The fastest mortality was 46 days in aCeT and the longest survival was 56 days in eCeT after the onset of drought. Total and partial biomass (leaf, stem and root) in both aCeT and eCeT with fertiliz ation were significantly high, but significantly low in aCeT. The results of the study are helpful in addressing P. densiflora vulnerability to climate change by highlighting physiological responses related to carbon allocation under differing simulated environmental stressors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.