The aim of this study was to understand the effects of skin pigmentation on physiological parameters of thermoregulation and grazing behaviour of dairy goats in a hot and humid climate. The study used 26 crossbred Saanen yearling goats (95% Saanen+5% Local Hair Breed). The animals were raised at semi-intensive private farms in Adana (36 59'N, 35 18'E). Groups were selected 2 d before the start of observations. Goats were categorized as predominantly pigmented (P) skin and unpigmented (UP) skin. All observations and measurements were collected on grassland during the grazing period of June and July 2007 (60 d). Air temperature and relative humidity were recorded at 10 min intervals by a portable data logger. The physiological data (rectal temperature, respiration and pulse rate, and skin temperatures from head and udder) were recorded twice weekly in the morning (07:00-08:00); at midday (13:00-14:00); and in the evening (18:00-19:00). Additionally, the activity of the animals was observed and classified (eating, ruminating, drinking, standing, walking, lying) for 12 h during the day twice weekly, using a portable camera system linked directly to a computer. Panting behaviour was also observed. According to the THI values, the experimental goats were subjected to stressful conditions. The pigmented goats had significantly lower rectal temperatures (39.68 vs. $29.89^{\circ}C$), pulse rate (74.08 vs. 84.10 beat/min) and respiration rate (65.65 vs. 88.23 breath/min.) compared with unpigmented goats at midday when the THI exceeded 92. The rectal, head and udder temperatures, pulse and respiration rates of the non-pigmented group exceeded $40^{\circ}C$, $37^{\circ}C$, $37.5^{\circ}C$, 84 beats/min and 78 breaths/min, respectively. Higher activity was observed among pigmented compared with unpigmented goats. Unpigmented goats grazed (4.3 vs. 5.6 h), ruminated (2.0 vs. 2.4 h), and stood (0.8 vs. 1.2 h) less, but lay down (2.2 vs. 1.8 h) more than pigmented goats. The data obtained in this experiment support the hypothesis that unpigmented goats are more adversely affected by climatic stress, likely due to their decreased activity and increased water consumption, as demonstrated by previous studies.
This study examined temporal and spatial patterns of bioclimatic perceived sultriness in South Korea by analyzing the climatology of heat index calculated from ambient temperature and relative humidity for the period of 26 years (1973-1998). As results, spatially, bioclimatic sultriness above all thresholds frequently occurred mainly in the central western inner area, the southwestern inner area, and the southeastern inner area of South Korea. Especially, Miryang in the southeastern inner area of South Korea was proved to be, bioclimatically, the sultriest area in South Korea that has recorded frequent high heat index. Temporally, frequency of sultriness in the contiguous South Korea significantly increased in the 1990s. Specifically, In 1994, frequencies of heat index exceeding each threshold was the highest all over South Korea. Normally, the sultriness with high heat index exceeding 40.6$^{circ}C$ occurred mainly for the period of between the end of July generally after Summer Changma and the beginning of August before another small rainy season of years. These temporal-spatial distributions of bioclimatic sultriness in South Korea showed various patterns regionally, affected by physical and anthropogenic climatic factors such as topography, latitude, altitude, water bodies or aforestration, urbanization, and industrialization as well as movements of large-scale air masses.
Son, Yeong Mo;Jeon, Ju Hyeon;Lee, Sun Jeong;Yim, Jong Su;Kang, Jin Taek
Journal of Korean Society of Forest Science
/
v.106
no.4
/
pp.450-456
/
2017
This study was conducted to develop estimated equation for mortality rates (volume of dead trees, %) on coniferous and broad-leaved forests, representative forest types of South Korea. There were 6 equation models applied for estimating mortality such as a exponential equation, a Hamilton equation and variables using were DBH, basal area, and site index. Raw data used for estimating mortality were $5^{th}$ and $6^{th}$ national forest inventory data, and mortality was calculated with the difference of stocks between lived trees and dead trees by each sample plots. The most applicable equation to describe mortality on coniferous forest and broad-leaved forest was indicated as $P=(1+e^{(a+b{\times}DBH+c{\times}BA+d{\times}no\_ha+e{\times}density)})^{-1}$ and their goodness of fit showed 34% and 51% respectively. Goodness of fit in both equations were not much high because there were various factors which affect the mortality such as topographic conditions, soil characteristic, climatic factors, site quality, and competition. Therefore, it is considered that explaining mortality in forest with only 2 or 3 variables like DBH, basal area used in this analysis could be very difficult facts. However, this study is certainly worth in that there is no useful information on mortality by each forest type throughout the country at the present, and we would make an effort to promote the fitness of estimated equation for mortality adding competition index, tree crown density etc.
Kim, Yun-Sam;Park, Kyung-Woo;Park, Jung-Won;Jeune, Kyung-Hee;Kim, Mi-Kyung
Korean Journal of Environmental Biology
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v.28
no.4
/
pp.202-211
/
2010
The variations of physico-chemical factors and the species compositions of phytoplanktons were investigated to analyze the marine ecosystem at the depths during summer in the coast of Dokdo (stations DOK 1-3). The mean values of conductivity (48.9 mS $cm^{-1}$), salinity (32.9 psu) and total suspended solids (57.9 mg $L^{-1}$) were the highest in DOK 1. The biomass (Chl-a) of phytoplanktons was the highest in the surface of DOK 1 (2.61 ${\mu}gL^{-1}$). By the means of physicochemical factors (salinity, turbidity, Chl-a, TN, TP and Si), the water estimated in the coast of Dokdo was more eutrophicated than that in 2008. The phytoplanktons were a total of 42 species in Dokdo, which were composed of 33 species (78.6%) for Bacillariophyceae and 9 species (21.4%) for Dinophyceae. The standing crops of phytoplanktons were the highest ($18{\times}10^3$ cells $L^{-1}$) in the surface of DOK 2 and in the surface of DOK 3, while they were the lowest ($2{\times}10^3$ cells $L^{-1}$) at depth of 40 m of DOK1 and at depth of 30 m of DOK 3. The dominant species of phytoplanktons were Chaetoceros castracanei ($6{\times}10^3$ cells $L^{-1}$) in the surface, Rhizosolenia alata f. gracillima ($3{\times}10^3$ cells $L^{-1}$) at depth of 20 m and Protocentrum compressum ($4{\times}10^3$ cells $L^{-1}$) at the depth of 30 m of DOK 1. At the surface of DOK 2, the dominant species was Bacillaria paxillifer ($6{\times}10^3$ cells $L^{-1}$), while it was Hemiaulus indicus ($12{\times}10^3$ cells $L^{-1}$) at the surface of DOK 3. The DOK 1, which is affected by upwelling, whirlpool and circulation due to the East Korean Warm Current, was the most eutrophicated water body among three stations. The monitoring of marine ecosystem in the coast of Dokdo should be continued to propose the alternatives for water quality and species conservation and to purify the eutrophicated water body due to artificial pollutants as well as natural effectors by the global warming, the climatic change, etc.
Journal of the Korean association of regional geographers
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v.18
no.4
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pp.473-493
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2012
Malaria infection is sensitively influenced by regional meteorological conditions along with global climate change. Remote sensing techniques have become an important tool for extraction of climatic and environmental factors, including rainfall, temperature, surface water, soil moisture, and land use, which are directly linked to the habitat qualities of malaria mosquitoes. Improvement of sensor fidelity with higher spatial and spectral resolution, new multinational sensor development, and decreased data cost have nurtured diverse remote sensing applications in malaria research. In 1984, eradication of endemic malaria was declared in Korea, but reemergence of malaria was reported in mid-1990s. Considering constant changes in malaria cases since 2000, the epidemiological management of the disease needs careful monitoring. Geographically, northmost counties neighboring North Korea have been ranked high in the number of malaria cases. High infection rates in these areas drew special attention and led to a hypothesis that malaria dispersion in these border counties might be caused by north-origin, malaria-bearing adult mosquitoes. Habitat conditions of malaria mosquitoes are important parameters for prediction of the vector abundance. However, it should be realized that malaria infection and transmission is a complex mechanism, where non-environmental factors, including human behavior, demographic structure, landscape structure, and spatial relationships between human residence and the vector habitats, are also significant considerations in the framework of medical geography.
Journal of the Korea Academia-Industrial cooperation Society
/
v.19
no.5
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pp.480-488
/
2018
The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.
Win, Nan Zarchi;Mi, Khin Mi;Oo, Thi Tar;Win, Kyaw Kyaw;Park, Jinyoung;Park, Jong Kyun
Korean journal of applied entomology
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v.53
no.4
/
pp.323-329
/
2014
Population of fruit flies was monitored by using methyl eugenol trap during 2010-2011 in Yezin, Myanmar. Population numbers were analyzed with meteorological factors including rainfall, temperature, relative humidity and duration of sunshine. Samples of mango, guava, and jujube fruits were collected from orchards. The fruits were kept in containers so that the species of flies infesting the fruit could be identified when the adult insects emerged and to assess damage caused by fruit flies. Regression analyses indicated that populations of fruit flies were observed to be positively correlative with rainfall, minimum temperature and relative humidity, and negatively correlative with the duration of sunshine. Eleven species of fruit flies, Bactrocera arecae, B. carambolae, B. correcta, B. dorsalis, B. kandiensis, B. latilineola, B. malaysiensis, B. neocognata, B. raiensis, B. verbascifoliae, and Carpomya vesuvina, were identified. B. correcta and B. dorsalis were the most abundant and accounted for 29.3% and 28.6% of total emerged adults in the different fruit samples. The highest percentage of fruit damage was observed on guava ($59{\pm}15.4$), followed by mango ($35.5{\pm}12.1$) while the lowest was recorded on jujube ($18.5{\pm}7.9$).
The main purpose of this study is to understand the effects of hydroclimatic factors on annual actual evapotranspiration and to suggest the multiple linear regression (MLR) equations for the estimation of annual actual evapotranspiration from watershed. To accomplish this study purpose, 5 dam watersheds (Goesan dam, Seomjingang dam, Soyanggang dam, Andong dam, Hapcheon dam) were selected as study watersheds and annual actual evapotranspiration was estimated based on annual water balance analysis from each watershed. The estimated annual actual evapotranspiration from water balance analysis was used to evaluate the MLR equations. Furthermore, the possibility of the estimation of actual evapotranspiration using potential evapotranspiration equations (Penman equation, FAO P-M equation, Makkink equation, Preistley-Taylor equation, Hargreaves equation) was evaluated. It has turned out that it is not appropriate to use potential evapotranspiration for the estimation of actual evapotranspiration because the correlation between actual evapotranspiration and potential evapotranspiration is very low. The comparison of MLR equations with current actual evapotranspiration equations indicates that MLR equations can be used for the estimation of annual actual evapotranspiration. Furthermore, it has turned out that the effects of hydroclimatic factors on annual actual evapotranspiration from dam watersheds are different in each watershed; however, for all watersheds in common precipitation has turned out to be the most important climatic factor affecting on the estimation of annual actual evapotranspiration.
Magazine of the Korean Society of Agricultural Engineers
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v.22
no.3
/
pp.75-87
/
1980
Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.
To obtain the informations on the checking factors of the effecient utilization of paddies in chungnam province and study on the effecient working system and high productive cropping system in paddies, the utilization state of paddies including environmental conditions were investigated at sample 1,500 farms. The results obtained are summarized as follows; 1. The difficulty of drainage in paddies was the most important factor checking the utility of paddies. Delayed transplanting of rice and lack of labour were also important checking factors on the efficient utilization of paddies. 2. The utilization of paddies was rather effecient at small size farms of which farmers were almost poor, and most of them cultivated barley for their own food. 3. Considering climatic conditions, pre-crops of rice must be harvested before June 10 tho and the marginal transplanting date of rice plant is June 25 th. 4. In case of planting barley as a post-crop after rice, the spread seeding by rotary before plowing was most efficient with lowest cost. 5. Considering rice cultivation, yield of barley and net income, the most efficient cropping system was "Josaengtongil + Olbori".
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