• Animal Bioscience
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• v.37 no.5
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• pp.896-907
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• 2024

Objective: The potential of aqueous extract of Christ's thorn jujube (Ziziphus spina-christi) leaves (SLAE) to reduce the negative impacts of heat stress on production performance and physiological traits was investigated in dual-purpose layers under subtropical farming. Methods: A total of 200, 25-week-old laying hens (Inshas strain) were randomly assigned to four dietary treatments including SLAE at 0, 2.5, 5.0, and 7.5 mL/kg, respectively. The average temperature-humidity index value was 26.69 during the experimental period. The SLAE contained saponin (0.045%), total flavonoid content of 17.9 mg of quercetin equivalent/100 g and overall antioxidant capacity concentration of 17.9 mg of ascorbic acid equivalent/100 g. Results: The maximum final body weight (BW), BW gain, egg weight, number, and mass occurred at the level of SLAE7.5 inclusion. The egg quality was significantly higher in SLAE groups than in control, and overall, SLAE7.5 had the most favorable influence at 28 and 32 weeks. Liver and kidney function, as well as lipids profile, improved significantly by SLAE inclusion; the lowest concentrations of these parameters were in SLAE7.5 hens. Treatment with SLAE7.5 increased total antioxidant capacity and endogenous antioxidant enzymes compared to control, whereas no effect on superoxide dismutase was noticed. Conclusion: The addition of SLAE at 7.5 mL/kg diet improved egg laying performance and quality, metabolic profiles, and antioxidant status during hyperthermia conditions.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.1
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• pp.47-56
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• 1999

$^{15}N$-Isotope concentrations of groundwater from l4 wells with different land-use types in Kyonggi Province were measured to investigate the nitrate contamination sources. Water samples were collected monthly from January to December 1997 and analyzed for pH. PC, anions (fluoride, chloride, nitrate, sulfate, inorganic phosphate, and bicarbonate), and canons (calcium, magnesium, potassium, and sodium). For the analysis of the $^{15}N/^{14}N$ ratio as ${\delta}^{15}N$, $N_2$ samples were prepared through Kjeldahl-Rittenberg method and were analyzed using an isotope ratio mass spectrometer (VG Optima IRMS). Reproducibility of the method and precision of the IRMS were below 1.0‰ and 0.1‰, respectively. The ionic composition of each groundwater sample was only slightly different according to the land-use type. The nitrate concentrations of groundwater in cropland or livestock farming areas were higher than those in the residential area. The percentages of nitrate to total anions of groundwater samples from the livestock farming area were higher than those of other areas. The ${\delta}^{15}N$ values of ammonium sulfate, urea, groundwater sample in the non-contaminated area, and water from the animal manure septic tank were -2.7, 1.4, 5.5, and 27.2‰, respectively. Based on the ${\delta}^{15}N$ values, the sources of nitrate could be classified as originated from chemical fertilizers with ${\delta}^{15}N$ values below 5% and as from animal manure or municipal waste with ${\delta}^{15}N$ values over 10‰. In most cases, contamination sources investigated from ${\delta}^{15}N$ values of groundwater samples were correlated with the specific sources according to the land-use types. However, some ${\delta}^{15}N$ values did not matched the apparent land-use types, and there were seasonal variations of ${\delta}^{15}N$ values within the same well. These results suggest that the groundwater quality was affected by two or more contamination sources and the contribution of each source to the groundwater quality varied depending on the sampling season.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.221-237
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• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.238-246
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• 2005

Rice yield and protein content have been shown to be highly variable across paddy fields. In order to characterize this spatial variability of rice within a field, two-year experiments were conducted in 2002 and 2003 in a large-scale rice field of $6,600m^2$ In year 2004, an experiment was conducted to know if variable rate treatment (VRT) of N fertilizer, that was prescribed for site-specific management at panicle initiation stage, could reduce spatial variation in yield and protein content of rice while increasing yield compared to conventional uniform N topdressing (UN, 33kg N/ha at PIS) method. VRT nitrogen prescription for each grid was calculated based on the nitrogen (N) uptake (from panicle initiation to harvest) required for target rice protein content of $6.8\%$, natural soil N supply, and recovery of top-dressed N fertilizer. The required N uptake for target rice protein content was calculated from the equations to predict rice yield and protein content from plant growth parameters at panicle initiation stage (PIS) and N uptake from PIS to harvest. This model· equations were developed from the data obtained from the previous two-year experiments. The plant growth parameters for the calculation of the required N were predicted non-destructively by canopy reflectance measurement. Soil N supply for each grid was obtained from the experiment of year 2003, and N recovery was assumed to be $60\%$ according to the previous reports. The prescribed VRT N ranged from 0 to 110kg N/ha with an average of 57kg/ha that was higher than 33 kg/ha of UN. The results showed that VRT application successfully worked not only to reduce spatial variability of rice yield and protein content but also to increase rough rice yield by 960kg/ha. The coefficient of variation (CV) for rice yield and protein content was reduced significantly to $8.1\%$ and $7.1\%$ in VRT from $14.6\%$ and $13.0\%$ in UN, respectively. And also the average protein content of milled rice in VRT showed very similar value of target protein content of $6.8\%$. In conclusion the procedure used in this paper was believed to be reliable and promising method for reducing within-field spatial variability of rice yield and protein content. However, inexpensive, reliable, and fast estimation methods of natural N supply and plant growth and nutrition status should be prepared before this method could be practically used for site-specific crop management in large-scale rice field.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1486-1494
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• 2017

Objective: This research analyzed behavioral characteristics of Hanwoo (Bos taurus coreanae) steers during each season and growth stage to enable measurement of the animals' welfare level for precision livestock farming. Methods: A hundred-eight beef steers were divided into three equal groups at a Hanwoo farm according to their growth stage: growing stage (GS), 8 months; early-fattening stage (EFS), 19 months; and late-fattening stage (LFS), 30 months. Twelve behavioral categories were continuously recorded for 13 day-time hours in each four seasons with three replications. Results: Time spent standing was found to be significantly longer in summer at all growth stages (p<0.05). Hanwoos at the GS spent significantly longer standing time in spring and summer than those at the EFS and LFS (p<0.05). Lying time in summer was the shortest for all growth stages (p<0.05). Steers at the LFS spent significantly longer lying time than that at the GS (p<0.05) in summer. For GS and EFS, time spent eating in spring and autumn were longer than in summer and winter (p<0.05). Eating time was the longest for the GS in spring, autumn, and winter, excluding for the LFS in winter (p<0.05). Regarding ruminating, steers at the LFS spent significantly shorter time than those at other stages in all seasons (p<0.05). GS and EFS steers showed the longest walking time in summer compared with other seasons (p<0.05). At GS and LFS, drinking time in summer was the longest of all seasons (p<0.05). Sleeping time was significantly shorter in summer compared with the other seasons (p<0.05). Self-grooming time was the longest in winter for all growth stages (p<0.05). Conclusion: Steers were found to have more variable behavioral patterns during summer and the GS and less active behaviors during the LFS, thus extra care seems necessary during the GS, LFS, and summer period.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.42-54
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• 2001

The use of nitrogen fertilizer in intensive agricultural production is of major concern due to its role on agricultural productivity and water quality. Crop production inputs on farm are usually applied at a uniform rate across an entire field. However, actual input requirements often vary within fields. The field variations in yield potential, soil moisture, soil N status, and the efficiency of fertilizer use, uniform application of crop production inputs does not allow optimum efficiency or profitability. This occurs because uniform application often results in areas of over- and under-application which may affect water quality and crop yield. This study used biophysical and economic models to assess the economic feasibility and water quality benefits of site specific nitrogen management for 10 soil types and 35 sample fields in Goodwater Creek watershed located near Centralia, Missouri. Results showed that the economic feasibility and water quality benefits of variable rate application were sensitive to the distribution of soil types within a field. Variable rate(VR) application was not uniformly more profitable than uniform rate(UR) application for the four agricultural systems evaluated and the water quality benefits were insubstantial relative to uniform application of N.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1263-1263
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• 2001

The amounts of organic matter present in soil and the rate of soil organic matter (SOM) turnover are influenced by agricultural management practice, such as rotation, tillage, forage plow down direct seeding and manure application. The amount of nutrients released from SOM is highly dependent upon the state of the organic matter. If it contains a large proportion of light fractions (low-density) more nutrients will be available to the glowing crops. However, if it contains mostly heavy fractions (high-density) that are difficult to breakdown, then lesser amounts of nutrients will be available. The state of the SOM and subsequent release of nutrients into the soil can be predicted by NIRS as long as a robust regression equation is developed. The NIRS method is known for its rapidity, convenience, simplicity, accuracy and ability to analyze many constituents at the same time. Our hypothesis is that the NIRS technique allows researchers to investigate fully and in more detail each field for the status of SOM, available moisture and other soil properties in Alberta soils for precision farming in the near future. One hundred thirty one (131) Alberta soils with various levels (low 2-6%, medium 6-10%, and high >10%) of organic matter content and most of dry land soils, including some irrigated soils from Southern Alberta, under various management practices were collected throughout Northern, Central and Southern Alberta. Two depths (0- 15 cm and 15-30 cm) of soils from Northern Alberta were also collected. These air-dried soil samples were ground through 2 mm sieve and scanned using Foss NIR System 6500 with transport module and natural product cell. With particle size above 150 microns only, the “Ludox” method (Meijboom, Hassink and van Noorwijk, Soil Biol. Biochem.27: 1109-1111, 1995) which uses stable silica, was used to fractionate SOM into light, medium and heavy fractions with densities of <1.13, 1.13-1.37 and >1.37 respectively, The SOM fraction with the particle size below 150 microns was discarded because practically, this fraction with very fine particles can't be further separated by wet sieving based on density. Total organic matter content, mechanical texture, ash after 375$^{\circ}C$, and dry matter (DM) were also determined by “standard” soil analysis methods. The NIRS regression equations were developed using Infra-Soft-International (ISI) software, version 3.11.

• Journal of International Area Studies (JIAS)
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• v.18 no.3
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• pp.145-168
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• 2014

Given the distance from Mt. Baekdu, volcanic ash will have the direct impact on South Korea in case Mt. Baekdu erupts. Ash fall deposits or particulate matters(PM10) in the air will cause damages in various sectors. In particular, the PM10 impact on the manufacturing sector when the ash disperses in Korea is needed to be assessed since South Korea's manufacturing sector accounts for more than 30% of GDP. Meanwhile the economic impacts of PM10, including Asian dust, have been researched in Korea as the events become frequent, and losses in the manufacturing have been also reported. This study is to identify vulnerable sectors to volcanic ash in the korean industry, and to assess economic losses in case of a Mt. Baekdu eruption scenario, based on the historical loss experience with particulate matters. Study results show that airline, precision such as electronics and semiconductors, distribution, shipbuilding, car, leisure, glass, dairy farming are vulnerable to volcanic ash, or PM10. The economic losses in both car and shipbuilding industry is estimated to 46.49 billion Korean won due to shutdown for 6 hours in case of a Mt. Baekdu eruption scenario.