• Korean journal of applied entomology
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• v.43 no.3 s.136
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• pp.211-215
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• 2004

Temperature-fecundity of the melon aphid, Aphis gossypii Glover, was studied at constant temperatures ranging from 15 to $32.5^{\circ}C$ under $60-70\%$ RH and a photoperiod of 16 : 8 (L : D) A life table parameters were constructed using the results. The longevity of A. gossypii gradually increased with decreasing temperature below $27.5^{\circ}C$. Also fecundity increased with decreasing temperature and the highest fecundity was 61.8 nymphs per female at $17.5^{\circ}C$. However. daily fecundity increased with increasing temperatures up to $22.5^{\circ}C$ showing 5.9 nymphs per day and thereafter decreased. Longevity and fecundity of the adult in the greenhouse with an average temperature of $21^{\circ}C$ and $65.6\%$ RH, were 20.0 days and 59.6, respectively, which were longer and higher than those in the growth chamber with similar conditions. net reproductive rate (Ro) was 54.9 at $17.5^{\circ}C$ while intrinsic rate of increase ($r_m$) and finite rate of increase ($\lambda$) were the highest 0.5 and 1.6 at $30^{\circ}C$, respectively. doubling time (DT) and mean generation time (T) were the shortest 1.4 and 6.8 at $30^{\circ}C$ indicating that optimal temperature for the development is $30^{\circ}C$.

• Journal of Bio-Environment Control
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• v.24 no.4
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• pp.317-325
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• 2015

This paper attempts to present a review about simulation of different greenhouse parameters and energy supplying techniques by using building energy simulation, to find out the optimal solution for keeping greenhouse microclimate favorable for the crop production. The objectives of conducting this study were, to describe the various energy systems and techniques used for the greenhouse energy management and efficiency analysis of these technologies by using building energy simulation. We describe different models to understand the behavior of the energy saving technologies with respect to the resources available and different outside climatic conditions. We identified main features of the building energy simulation software, that enable users, to simulate hybrid agricultural building projects by using user defined parameters. At the end of the paper we draw some important concluding remarks on the basis of reviewing all the investigators contributions for the developments of simulation model of agricultural greenhouse energy management, using a building energy simulation software specifically TRNSYS. In conclusion, this paper provides information that TRNSYS have great potential for agricultural buildings energy simulation along with the renewable energy resources and energy saving techniques. This review paper provides aid to greenhouse researcher and energy planner for the future studies of greenhouses energy planning.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.1
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• pp.9-15
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• 2000

The objective of this study is to evaluate the use of RADARSAT and Landsat TM data for the monitoring of rice growth. The relationships between backscatter coefficients($\sigma$$^{0}$ ) of RADARSAT data and digital numbers (DN) of Landsat TM and rice growth parameters were investigated. Radar backscatter coefficients were calculated by calibration process and then compared with rice growth parameters; plant height, leaf area index (LAI), and fresh and dry biomass. When radar backscatter coefficient ($\sigma$$^{0}$ ) of rice was expressed as a function of time, it is shown that the increasing trend ranged from -22--20dB to -9--8dB as growth advances. The temporal variation of backscatter coefficient was significant to interpret rice growth. According to the relationship between leaf area index and backscatter coefficient, backscatter coefficient underestimated leaf area index at the beginning of life history and overestimated, at the reproductive stage. The same increasing trend between biomass and backscatter coefficient was shown. From these results, RADARSAT data appear positive to the monitoring of rice growth. Each band of time-series Landsat TM data had a significant trend as a rice crop grows during its life cycle. Spectral indices, NDVI[(TM4-TM3)/(TM4+TM3)] and RVI(TM4/TM2), derived from Landsat TM equivalent bands had the same trend as leaf area index.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.422-433
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• 2017

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we developed for estimating garlic growth at field scale model in major cultivation regions. We used the $NDVI_{UAV}$ that reflects the crop conditions, and seven meteorological elements for 3 major cultivation regions from 2015 to 2017. For this study, UAV imagery was taken at Taean, Changnyeong, and Hapcheon regions nine times from early February to late June during the garlic growing season. Four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.), and fresh weight (F.W.) were measured for twenty plants per plot for each field campaign. The multiple linear regression models were suggested by using backward elimination and stepwise selection in the extraction of independent variables. As a result, model of cold type explain 82.1%, 65.9%, 64.5%, and 61.7% of the P.H., F.W., L.N., P.D. with a root mean square error (RMSE) of 7.98 cm, 5.91 g, 1.05, and 3.43 cm. Especially, model of warm type explain 92.9%, 88.6%, 62.8%, 54.6% of the P.H., P.D., L.N., F.W. with a root mean square error (RMSE) of 16.41 cm, 9.08 cm, 1.12, 19.51 g. The spatial distribution map of garlic growth was in strong agreement with the field measurements in terms of field variation and relative numerical values when $NDVI_{UAV}$ was applied to multiple linear regression models. These results will also be useful for determining the UAV multi-spectral imagery necessary to estimate growth parameters of garlic.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.55-63
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• 2001

N fertilizer recommendations to optimize with consideration to maximum crop yields, maximum profits, and minimum N losses to ground or runoff water, an advisory system. Nitrogen Expert System (NES), was developed. The system was to estimate the optimal rate of N fertilizer application cornfields in Illinois. NES was constructed using Smart Elements, a knowledge-based system that manages the expertise of human experts. NES was reinforced by addition of the effect of a productivity index (PI), soil organic matter content (SOM), and pre-sidedressing of nitrate concentration (PSNT) to the optimal N fertilizer recommendation. NES contains 49 rules, 1 class, 14 objects, and 2 properties. NES was successfully operated, showing N recommendations with inputs of three soil properties including PI, SOM, and PSNT. NES can reduce N loss to the environment, but adherence to the recommendations may also reduce farmers income. Therefore, NES will be more effective by evaluating both environmental damage assessment and other economic agricultural management parameters and other soil physico-chemical parameters.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.10
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• pp.1528-1539
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• 2019

Objective: To evaluate the effects on microbial diversity and biochemical parameters of gradually increasing temperatures, from $5^{\circ}C$ to $25^{\circ}C$ on corn silage which was previously fermented at ambient or low temperature. Methods: Whole-plant corn silage was fermented in vacuum bag mini-silos at either $10^{\circ}C$ or $20^{\circ}C$ for two months and stored at $5^{\circ}C$ for two months. The mini-silos were then subjected to additional incubation from $5^{\circ}C$ to $25^{\circ}C$ in $5^{\circ}C$ increments. Bacterial and fungal diversity was assessed by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) profiling and biochemical analysis from mini-silos collected at each temperature. Results: A temperature of $10^{\circ}C$ during fermentation restricted silage fermentation compared to fermentation temperature of $20^{\circ}C$. As storage temperature increased from $5^{\circ}C$ to $25^{\circ}C$, little changes occurred in silages fermented at $20^{\circ}C$, in terms of most biochemical parameters as well as bacterial and fungal populations. However, a high number of enterobacteria and yeasts (4 to $5\;log_{10}$ colony forming unit/g fresh materials) were detected at $15^{\circ}C$ and above. PCR-DGGE profile showed that Candida humilis predominated the fungi flora. For silage fermented at $10^{\circ}C$, no significant changes were observed in most silage characteristics when temperature was increased from $5^{\circ}C$ to $20^{\circ}C$. However, above $20^{\circ}C$, silage fermentation resumed as observed from the significantly increased number of lactic acid bacteria colonies, acetic acid content, and the rapid decline in pH and water-soluble carbohydrates concentration. DGGE results showed that Lactobacillus buchneri started to dominate the bacterial flora as temperature increased from $20^{\circ}C$ to $25^{\circ}C$. Conclusion: Temperature during fermentation as well as temperature during storage modulates microorganism population development and fermentation patterns. Silage fermented at $20^{\circ}C$ indicated that these silages should have lower aerobic stability at opening because of better survival of yeasts and enterobacteria.

• Animal Bioscience
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• v.36 no.3
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• pp.461-470
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• 2023

Objective: Sweet sorghum is an important forage crop for ruminants, especially in low rainfall areas. Grapeseeds are an abundant by-product of wine-making and contain bioactive substances that can improve the antioxidant capacity of meat. We examined the effect of sweet sorghum forage with supplementary grapeseeds on carcass and meat quality in lambs. Methods: Twenty-eight Small-tailed Han lambs (body weight = 19.1±1.20 kg), aged 3 to 4 months, were penned, and fed individually. The lambs were divided into four groups (n = 7 each) and were offered one of four diets: i) sweet sorghum silage; ii) sweet sorghum silage + grapeseeds; iii) sweet sorghum hay; and iv) sweet sorghum hay + grapeseeds. The grapeseeds were added to the concentrate at 6% DM and the diets were fed for 100 d. Results: Sweet sorghum silage tended (p = 0.068) to increase hot carcass weight, while grapeseeds tended (p = 0.081) to decrease dressing percentage without affecting other carcass parameters. Lambs consuming supplementary grapeseeds increased (p<0.05) meat redness and tended to decrease (p = 0.075) concentration of methionine in meat. Lambs consuming sweet sorghum silage increased (p<0.001) water content of the meat and had a lower (p<0.05) concentration of n-6 polyunsaturated fatty acids (PUFA) and n-6:n-3 PUFA ratio than lambs consuming sweet sorghum hay. Saturated fatty acids content in meat was lowest (p<0.05) in lambs consuming sweet sorghum silage with grapeseeds. Lambs with supplementary grapeseeds tended (p<0.10) to increase eicosapentaenoic acid and docosahexaenoic acid and have a lower thrombogenic index than lambs not consuming grapeseeds. Conclusion: It was concluded that sweet sorghum with supplementary grapeseeds fed to lambs; i) improved the color of the meat to be more appetizing to the consumer; ii) tended to improve the fatty acids composition of the meat; and iii) lowered thrombogenic index of the meat.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.6 s.97
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• pp.615-621
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• 2005

In this paper, a model for simulating synthetic aperture radar(SAR) images of earth surfaces. The earth surfaces include forest area, rice crop field, other agricultural fields, grass field, road, and water surface. At first, the backscattering models are developed for bare soil surfaces, water surfaces, short vegetation fields such as rice fields and grass field, other agriculture areas, and forest areas. Then, the SAR images are generated from the digital elevation model(DEM) and digital terrain map. The DTM includes ten parameters, such as soil moisture, surface roughness, canopy height, leaf width, leaf length, leaf density, branch length, branch density, trunk length, and trunk density, if applicable. The scattering models are verified with measurements, and applied to generate an SAR image for an area.

• Journal of Dairy Science and Biotechnology
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• v.35 no.3
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• pp.176-183
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• 2017

Flaxseed (Linum usitatissimum L.) is an important food, oil, and fiber crop of the family Linaceae. Although flaxseed has been consumed as a food ingredient for several centuries, its nutritional benefits have not yet been completely established. Flaxseed is a good source of lignans, nonstarch polysaccharides, and high-quality proteins. Hence, in this study, we aimed to prepare a bioactive kefir containing flaxseed and to examine the physicochemical characteristics of kefir containing different concentrations of flaxseed. We investigated the pH, and sensory evaluation of bioactive Kefir containing different concentrations of flaxseed. We investigated the pH, total anthocyanins (TAs), and sensory evaluation of bioactive Kefir containing different concentrations of flaxseed. The pH of this bioactive kefir decreased, whereas the TA content increased with increasing incubation time; however, these parameters were not affected by the amount of added flaxseed. As the addition rate of flaxseed increased, the scores for overall acceptability, texture, color, flavor, and taste in sensory evaluations were generally the same as or lower than the control. There were no significant differences in overall acceptability, texture, color, flavor, and taste between the control and treated groups. Therefore, further studies are needed to develop methods for production of health-improving kefir as a dietary supplement based on the functional properties of flaxseed.