• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.246-254
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• 2022

Domestic facility agriculture grows rapidly, such as modernization and large-scale. And the production scale increases significantly compared to the area, accounting for about 60% of the total agricultural production. Greenhouses require energy input to create an appropriate environment for stable mass production throughout the year, but the energy load per unit area is large because of low insulation properties. Through the rooftop greenhouse, one of the types of urban agriculture, energy that is not discarded or utilized in the building can be used in the rooftop greenhouse. And the cooling and heating load of the building can be reduced through optimal greenhouse operation. Dynamic energy analysis for various environmental conditions should be preceded for efficient operation of rooftop greenhouses, and about 40% of the solar energy introduced in the greenhouse is energy exchange for crops, so it should be considered essential. A major analysis is needed for each sensible heat and latent heat load by leaf surface temperature and evapotranspiration, dominant in energy flow. Therefore, an experiment was conducted in a rooftop greenhouse located at the Korea Institute of Machinery and Materials to analyze the energy exchange according to the growth stage of crops. A micro-meteorological and nutrient solution environment and growth survey were conducted around the crops. Finally, a regression model of leaf temperature and evapotranspiration according to the growth stage of leafy vegetables was developed, and using this, the dynamic energy model of the rooftop greenhouse considering heat transfer between crops and the surrounding air can be analyzed.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.749-759
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• 2012

A field experiment was conducted to selection of ground-based remote sensor and reflectance indices to estimate rice production, estimation of suitable season for ground-based remote sensor and N top dressing fertilizer application rate in 2010. Fertilizer application was determined by "Fertilizer management standard for crops" (National Academy of Agricultural Science, 2006). Four levels of N-fertilizer were applied as 0%, 70%, 100% and 130% by base N-fertilizer application and were fertilized as 70% of basal dressing and 30% as top dressing. Rice (Oryza sativa L.) of Chucheong and Joonam (Korean cultivar) were planted on May 22, 2010 in sandy loam soil and harvested on October 6, 2010. Reflectance indices were measured 7 times from July 5 to August 23 by Crop circle-amber and red version and GreenSeeker-green and red version. Remote sensing angle from the sensor head to the canopy of rice was adjusted to $45^{\circ}$, $70^{\circ}$ and $90^{\circ}$ degree because of difference in the density of plant and the sensing angle. The reflectance indices obtained ground-based remote sensor were correlated with the biomass of rice at the early growth stage and at the harvest with $70^{\circ}$ and $90^{\circ}$ degree of sensor angle. The reflectance indices at the 52th Day After Transplanting (DAT) and the 59th DAT, critical season, were positively correlated with dry weight and nitrogen uptake. Specially NDVI at the 59th was significantly correlated with the mentioned parameters. Based on the result of this study, rNDVI by GreenSeeker on $70^{\circ}$ degree of angle at the 59th DAT in Chucheong and rNDVI by Crop Circle on $70^{\circ}$ degree of angle and gNDVI by GreenSeeker on $70^{\circ}$ degree of angle at the 59th DAT in Joonam can be useful for estimation of dry weight and nitrogen uptake. Moreover, sufficiency index estimated by reflectance index at the 59th DAT can be useful for the estimation of N-fertilizer level application and can be used as a model for N-top dressing fertilizer management.

• Korean journal of applied entomology
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• v.48 no.2
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• pp.237-243
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• 2009

This study was conducted to develop economic injury level (ElL) and economic threshold (ET) of Cabbage armyworm, Mamestra brassicae L. on cabbage (Brassica oleracea L. var). The changes of cabbage biomass and M. brassicae density were investigated after introduction of larval M. brassicae (2nd instar) at different densities: 0, 1, 2, 4, 8, and 16 larvae per plant at 40 d after planting for an open field experiment, and 0, 2, 5, 8 and 12 larvae per plant at 25 d after planting for a glass house experiment. In the field experiment, the yield loss of cabbage was not significantly different among treated-plots at 30 d after the larval introduction, showing an over-compensatory response of cabbage plants to M. brassicae attack. In the glasshouse experiment, however, the biomass of cabbage at 15 d after the larval introduction significantly decreased with increasing the initial introduced number of M. brassicae, resulting in 38.3, 36.7, 21.7, 23.3 and 16.7g in above treated-plots, respectively. The relationship between cumulative insect days (CID) and yield loss (%) of cabbage was well described by a nonlinear logistic equation. Using the estimated equation, ElL of M. brassicae on cabbage was estimated at 44 CID per plant based on the yield loss 14%, which take into account of an empirical gain threshold 5% and marketable rate 91% of cabbage. Also, ET was calculated at 80% of the EIL: 35 CID per plant. Until a more elaborate EIL-model is developed, the present result may be useful for M. brassicae management at early growth stage of cabbage.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.77-83
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• 2016

The measurement of total fresh weight of plants provides an essential indicator of crop growth for monitoring production. To measure fresh weight without damaging the vegetation, image-based methods have been developed, but they have limitations. In addition, the total plant fresh weight is difficult to measure directly in hydroponic cultivation systems because of the amount of nutrient solution. This study aimed to develop a real-time, precise method to measure the total fresh weight of Romaine lettuce (Lactuca sativa L. cv. Asia Heuk Romaine) with growth stage in a plant factory using a nutrient film technique. The total weight of the channel, amount of residual nutrient solution in the channel, and fresh shoot and root weights of the plants were measured every 7 days after transplanting. The initial weight of the channel during nutrient solution supply (Wi) and its weight change per second just after the nutrient solution supply stopped were also measured. When no more draining occurred, the final weight of the channel (Ws) and the amount of residual nutrient solution in the channel were measured. The time constant (${\tau}$) was calculated by considering the transient values of Wi and Ws. The relationship of Wi, Ws, ${\tau}$, and fresh weight was quantitatively analyzed. After the nutrient solution supply stopped, the change in the channel weight exponentially decreased. The nutrient solution in the channel slowly drained as the root weight in the channel increased. Large differences were observed between the actual fresh weight of the plant and the predicted value because the channel included residual nutrient solution. These differences were difficult to predict with growth stage but a model with the time constant showed the highest accuracy. The real-time fresh weight could be calculated from Wi, Ws, and ${\tau}$ with growth stage.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.236-241
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• 2016

The common ice plant (Mesembryanthemum crystallinum L.) has some medicinal uses and recommended plant in closed-type plant factory. The objective of this study was to estimate the cardinal temperatures for seed germination of the common ice plant using bilinear, parabolic, and beta distribution models. Seeds of the common ice plant were germinated in the dark in a growth chamber at four constant temperatures: 16, 20, 24, and $28^{\circ}C$. For this, four replicates of 100 seeds were placed on two layers of filter paper in a 9-cm petri dish and radicle emergence of 0.1 mm was scored as germination. The times to 50% germination were 4.3, 2.5, 2.0, and 1.8 days at 16, 20, 24, and $28^{\circ}C$, respectively, indicating that the germination of this warm-weather crop increased with temperature. Next, the time course of germination was modeled using a logistic function. For the selection of an accurate model, seeds were germinated in the dark at constant temperatures of 6, 12, 32, and $36^{\circ}C$. Germination started earlier and increased rapidly at temperatures above $20^{\circ}C$. The minimum, optimal, and maximum temperatures were estimated by regression of the inverse of time to 50% germination rate, as a function of the temperature gradient. The different functions estimated differing minimum, optimal and maximum temperatures, with 5.7, 27.7, and $36.5^{\circ}C$, respectively for the bilinear function, 13.4, 25.0, and $36.6^{\circ}C$, respectively, for the parabolic function and 7.8, 25.9, and $36.0^{\circ}C$, respectively, for the beta distribution function. The models estimated that the inverse of time to 50% germination rate was 0 at 6 and $36^{\circ}C$. The observed final germination rates at 12 and $32^{\circ}C$ were 62 and 97%, respectively. Our data show that a beta distribution function provides a useful model for estimating the cardinal temperatures for germination of seed from the common ice plant.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.185-185
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• 2019

Sustaining future wheat production is challenged by anthropogenically forced climate warming and drying led by increased concentration of greenhouse gases all around the globe. Warming stresses, originating from the elevated $CO_2$ concentration, are continuously reported to have negative impacts on wheat growth and yield. Yet, elevated $CO_2$ concentration, despite being disparagingly blamed for promoting warming, is also associated with a phenomenon called $CO_2$ enrichment; in which wheat yield can improve due to the enhanced photosynthesis rates and less water loss through transpiration. The conflicting nature of climate warming and $CO_2$ enrichment and their interplay can have specific implications under different environments. It is established form the field and simulation studies that the two contrasting phenomena would act severely in their own respect under arid and semi-arid environments. Wheat is a dietary staple for masses in Pakistan. The country's wheat production system is under constant stress to produce more from irrigated agricultural lands, primarily lying under arid to semi-arid environments, to meet the rapidly growing domestic needs. This work comprehensively examines the warming impacts over wheat yield and water productivity (WP), with and without the inclusion of $CO_2$ enrichment, under semi-arid environment of Punjab which is the largest agricultural province of Pakistan. Future wheat yields and WPs were simulated by FAO developed AquaCrop model v 5.0. The model was run using the bias-correction climate change projections up to 2080 under two representative concentration pathways (RCP) scenarios: 4.5 and 8.5. Wheat yield and WPs decreased without considering the $CO_2$ enrichment effects owing to the elevated irrigation demands and accelerated evapotranspiration rates. The results suggested that $CO_2$ enrichment could help maintain the current yield and WPs levels during the 2030s (2021-2050); however, it might not withhold the negative climate warming impacts during the 2060s (2051-2080). Furthermore, 10 - 20 day backward shift in sowing dates could also help ease the constraints imposed by climate warming over wheat yields and WPs. Although, $CO_2$ enrichment showed promises to counteract the adverse climate warming impacts but the interactions between climate warming and $CO_2$ concentrations were quite uncertain and required further examination.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.305-312
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• 2018

The crops cultivated and consumed in Korea require specific climate conditions corresponding to their own growth characteristics. This study aims to analyze the relationship between climate change and agricultural productivity. According to growing concern about climate change internationally, many agricultural studies are developing technology to prevent damage from climate change. Before developing technology, we should figure out what kind of crop gets huge damage and how much caused by climate change. In the context of agricultural economics, we can define the reduction of agricultural product yield as a decline in productivity. As a result, this study analyzes the effects of climate change on agricultural productivity using Stochastic Frontier Analysis model. There are several kinds of climate change phenomena that increase the inefficiency of production. In other words, there are several kinds of crops that get negative influence by climate change. The result of this study can be used as basic guideline for producers to prepare for changing weather prior to developing disaster tolerance technology coping actively with special weather report.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.4
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• pp.386-408
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• 1988

A study was conducted to develop a model for estimating evapotranspiration and yield of Chinese cabbages from meteorological factors from 1981 to 1986 in Suweon, Korea. Lysimeters with water table maintained at 50cm depth were used to measure the potential evapotranspiration and the maximum evapotranspiration in situ. The actual evapotranspiration and the yield were measured in the field plots irrigated with different soil moisture regimes of -0.2, -0.5, and -1.0 bars, respectively. The soil water content throughout the profile was monitored by a neutron moisture depth gauge and the soil water potentials were measured using gypsum block and tensiometer. The fresh weight of Chinese cabbages at harvest was measured as yield. The data collected in situ were analyzed to obtain parameters related to modeling. The results were summarized as followings: 1. The 5-year mean of potential evapotranspiration (PET) gradually increased from 2.38 mm/day in early April to 3.98 mm/day in mid-June, and thereafter, decreased to 1.06 mm/day in mid-November. The estimated PET by Penman, Radiation or Blanney-Criddle methods were overestimated in comparison with the measured PET, while those by Pan-evaporation method were underestimated. The correlation between the estimated and the measured PET, however, showed high significance except for July and August by Blanney-Criddle method, which implied that the coefficients should be adjusted to the Korean conditions. 2. The meteorological factors which showed hgih correlation with the measured PET were temperature, vapour pressure deficit, sunshine hours, solar radiation and pan-evaporation. Several multiple regression equations using meteorological factors were formulated to estimate PET. The equation with pan-evaporation (Eo) was the simplest but highly accurate. PET = 0.712 + 0.705Eo 3. The crop coefficient of Chinese cabbages (Kc), the ratio of the maximum evapotranspiration (ETm) to PET, ranged from 0.5 to 0.7 at early growth stage and from 0.9 to 1.2 at mid and late growth stages. The regression equation with respect to the growth progress degree (G), ranging from 0.0 at transplanting day to 1.0 at the harvesting day, were: $$Kc=0.598+0.959G-0.501G^2$$ for spring cabbages $$Kc=0.402+1.887G-1.432G^2$$ for autumn cabbages 4. The soil factor (Kf), the ratio of the actual evapotranspiration to the maximum evapotranspiration, showed 1.0 when the available soil water fraction (f) was higher than a threshold value (fp) and decreased linearly with decreasing f below fp. The relationships were: Kf=1.0 for $$f{\geq}fp$$ Kf=a+bf for f$$I{\leq}Esm$$ Es = Esm for I > Esm 6. The model for estimating actual evapotranspiration (ETa) was based on the water balance neglecting capillary rise as: ETa=PET. Kc. Kf+Es 7. The model for estimating relative yield (Y/Ym) was selected among the regression equations with the measured ETa as: Y/Ym=a+bln(ETa) The coefficients and b were 0.07 and 0.73 for spring Chinese cabbages and 0.37 and 0.66 for autumn Chinese cabbages, respectively. 8. The estimated ETa and Y/Ym were compared with the measured values to verify the model established above. The estimated ETa showed disparities within 0.29mm/day for spring Chinese cabbages and 0.19mm/day for autumn Chinese cabbages. The average deviation of the estimated relative yield were 0.14 and 0.09, respectively. 9. The deviations between the estimated values by the model and the actual values obtained from three cropping field experiments after the completion of the model calibration were within reasonable confidence range. Therefore, this model was validated to be used in practical purpose.

• Journal of Bio-Environment Control
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• v.21 no.3
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• pp.271-275
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• 2012

The average annual and winter ambient air temperatures in Korea have risen by $0.7^{\circ}C$ and $1.4^{\circ}C$, respectively, during the last 30 years. The continuous rise in temperature presents a challenge in growing certain horticultural crops. Chinese cabbage, one most important cool season crop, may well be used as a model to study the influence of climate change on plant growth, because it is more adversely affected by elevated temperatures than warm season crops. This study examined the influence of transplanting time, nitrogen fertilizer level and climate parameters, including air temperature and growing degree days (GDD), on the performance of a Chinese cabbage cultivar (Chunkwang) during the spring growing season to estimate crop yield under the unfavorable environmental conditions. The chinese cabbage plants were transplanted from Apr. 8 to May 13, 2011 when 3~4 leaves were occurred, at internals of 7 days and cultivated with 3 levels of nitrogen fertilization. The data from plants transplanted on Apr. 22 and 29, 2012 were used for the prediction of yield as affected by planting date and nitrogen fertilization for spring production. In our study, plant dry weight was higher when the seedlings were transplanted on 15th (168 g) than on 22nd (139 g) of April. There was no significant difference in the yield when plants were grown with different levels of nitrogen fertilizer. The values of correlation coefficient ($R^2$) between GDD and number of leaves, and between GDD and dry weight of the above-ground plant parts were 0.9818 and 0.9584, respectively. Nitrogen fertilizer did not provide a good correlation with the plant growth. Results of this study suggest that the GDD values can be used as a good indicator in predicting the top biomass yield of Chinese cabbage.