• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.7
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• pp.599-607
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• 2006

The experiments were carried out to develop simulation model for estimating the yield of soybean in upland and paddy field condition. Field experiments were done at National Institute of Crop Science in 2005. The evaluated soybean cultivars were Taekwangkong, Daewonkong, and Hwangkeumkong. Soybean seeds were planted by hill seeding with 3-4 seeds and row and hill spacing were $60{\times}10cm$ in upland and $60{\times}15cm$ in paddy field. Seeds were sown on row (without making ridge) and on the top of ridge in upland and paddy field, respectively. Field parameters were measured yield components ($plants/m^{2}$, pod no./plant, and 100-seed weight, seed yield and growth characteristics (stem length, leaf area at each stage, and dry weight of shoot) and after measuring they were compared the relationships with seed yield and yield components and seed yield and growth characteristics. Seed yield of soybean was affected by cultivars and planting density. Seed yield was higher in upland than paddy field due to the higher planting density in upland field. The upland soybeans generally had lower 100-seed weight than that of paddy field. Seed yield of soybean in a paddy field was greatest in Taekwangkong and followed by Daewonkong and Hwangkeumkong. The harvest index of taekwangkong and Hwanggumkong was higher in upland than paddy field, however, it was higher in paddy field than upland in Daewonkong. Seed yield was greatest in Daewonkong in both experimental fields. The greatest stem length was observed in taekwangkong and Hwanggumkong (R6) in late growth stage in paddy field. Dry weight of shoot and pod, pod number, stem length, and stem diameter were higher grown in paddy field than grown in upland. Crop growth rate (CGR) of cultivars was higher in paddy field after 8 WAS(weeks after sowing) and it was greatest at 13 WAS in Daewonkong among the cultivars. In upland field, CGR was greatest in Taekwangkong and then followed by Daewonkong and Hwanggumkong during 12 and 15 WAS. There was no significant relationships between 100-seed weight and seed yield in both experimental fields. A significant positive relationship was observed between seed number and seed yield. The correlation coefficients between leaf area and shoot dry weight were about 0.8 during the whole growth stage except 5 WAS and 4-5 WAS in paddy field and upland, respectively. This experiment was done just one year and drained paddy field condition was not satisfied drained condition successfully at 7th leaf age of soybean by the heavy rain, so we suggest that the excessive soil water reduced seed yield in paddy field and the weather condition should be considered for utilizing of these results.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.89-96
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• 2014

We aimed to evaluate the effects of climatic elements on potato yield and create a model with climatic elements for estimating the potato yield, using the results of the regional adjustment tests of potato. We used 86 data of the yield data of a potato variety, Sumi, from 17 regions over 11 years. According to the results, the climatic elements showed significant level of correlation coefficient with marketable yield appeared to be almost every climatic elements except wind velocity, which was daily average air temperature (Tave), daily minimum air temperature (Tmin), daily maximum air temperature(Tmax), daily range of air temperature (Tm-m), precipitation (Prec.), relative humidity (R.H.), sunshine hours (S.H.) and days of rain over 0.1 mm (D.R.) depending on the periods of days after planting or before harvest. The correlations between these climatic elements and marketable yield of potato were stepwised using SAS, statistical program, and we selected a model to predict the yield of marketable potato, which was $y=7.820{\times}Tmax_-1-6.315{\times}Prec_-4+128.214{\times}DR_-8+91.762{\times}DR_-3+643.965$. The correlation coefficient between the yield derived from the model and the real yield of marketable yield was 0.588 (DF 85).

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.2
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• pp.54-61
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• 2017

Rice yield of South Korea in 2015 was the highest in last 30 years. The future direction of food policy in South Korea can be determined depending on whether the historically highest yield in 2015 can be continued or just one-off event. Therefore, it is necessary to understand whether such a high yield as 2015 can be reoccurred and how often it can occur. This study used the yield monitoring data from National Institute of Crop Science, Rural Development Administration and the meteorological data provided by Korea Meteorological Administration to identify the weather conditions, which could cause high yield, and how often these conditions occurred in the past. Our results showed that significantly high yield in 2015 could occur only when the mean sunshine hours of July and the mean sunshine hours from the end of August to early September are 5.1 hours and 6 hours, respectively. The probability of satisfying these weather conditions was 8/35 (23%) over the past 35 years. And the probability of successive high yield for two years was 1/35 (2.9%). The probability of recurrence of high yield within the next 5 years or 10 years after high yield was 4/35 (11.4%).

• Journal of The Korean Society of Grassland and Forage Science
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• v.8 no.2
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• pp.110-116
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• 1988

The response of forage yield was studied with various growth indices to develop yield model and to determine optimum cutting time in three cultivars of orchardgrass. 1. Number of tiller per plant was the highest at 3rd cutting stage. But, it was decreased rapidly at 4th cutting stage. Leaf Area Index (LAI) was the highest at 3rd cutting stage. LAI was increased slowly during 15 days to 20 days after cutting and thereafter increased rapidly. 2. In dry matter yield over cutting stages, 1st cutting and 3rd cutting stages were higher yield than others. Change of dry matter yield was similar to that of LAI in all cutting stages. 3. Leaf Elongation Rate (LER) and Specific Leaf Weight (SLW) were reached to maximum at 20 to 25 days and 25 to 30 days after cutting, respectively. 4. Dry matte yield was highly correlated with LAI (r-0.905)and with CGR (r-0.962) over three cultivars. Also, LAI was significantly with LER. The best-fit yield model was obtained in multiple regression equation which included both dependent variables of LAI and CGR. 5. Optimum cutting times which were determined by the relationships between D.M. yield and LAI, and between D.M. yield and CGR, were ranged from 32 days to 36 days depend on each cutting stages.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1741-1754
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• 2020

Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and -0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.7
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• pp.1029-1035
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• 2005

A 3${\times}$4 factorial field experiment with a complete randomised split-plot design with four replicates was conducted from June 2002 to March 2003 at the experimental farm of the Nong Lam University, Ho Chi Minh City, Vietnam, to determine effects of different harvesting heights (10, 30 and 50 cm above the ground) and cutting intervals (45, 60, 90 and 285 days) on yield of foliage and tubers, and chemical composition of the foliage. Cassava of the variety KM 94 grown in plots of 5 m${\times}$10 m at a planting distance of 30 cm${\times}$50 cm was hand-harvested according to respective treatments, starting 105 days after planting. Foliage from the control treatment (285 days) and all tubers were only harvested at the final harvest 285 days after planting. Dry matter and crude protein foliage yields increased in all treatments compared to the control. Mean foliage dry matter (DM) and crude protein (CP) yields were 4.57, 3.53, 2.49, and 0.64 tonnes DM $ha^{-1}$ and 939, 684, 495 and 123 kg CP $ha^{-1}$ with 45, 60, 90 and 285 day cutting intervals, respectively. At harvesting heights of 10, 30 and 50 cm the DM yields were 4.27, 3.67 and 2.65 tonnes $ha^{-1}$ and the CP yields were 810, 745 and 564 kg $ha^{-1}$, respectively. The leaf DM proportion was high, ranging from 47 to 65%. The proportion of leaf and petiole increased and the stem decreased with increasing harvesting heights and decreasing cutting intervals. Crude protein content in cassava foliage ranged from 17.7 to 22.6% and was affected by harvesting height and cutting interval. The ADF and NDF contents of foliage varied between 22.6 and 30.2%, and 34.2 and 41.2% of DM, respectively. The fresh tuber yield in the control treatment was 34.5 tonnes $ha^{-1}$. Cutting interval and harvesting height had significant negative effects on tuber yield. The most extreme effect was for the frequent foliage harvesting at 10 cm harvesting height, which reduced the tuber yield by 72%, while the 90 day cutting intervals and 50 cm harvesting height only reduced the yield by 7%. The mean fresh tuber yield decreased by 56, 45 and 27% in total when the foliage was harvested at 45, 60 and 90 day cutting intervals, respectively. It is concluded that the clear effects on quantity and quality of foliage and the effect on tuber yield allow alternative foliage harvesting principles depending on the need of fodder for animals, value of tubers and harvesting cost. An initial foliage harvest 105 days after planting and later harvests with 90 days intervals at 50 cm harvesting height increased the foliage DM and CP yield threefold, but showed only marginal negative effect on tuber yield.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.57-74
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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, the 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 prescribed N for site-specific fertilizer management at panicle initiation stage (VRT) could reduce spatial variation in yield and protein content of rice while increasing yield compared to conventional uniform N topdressing (UN, ,33 kg N/ha at PIS) method. The trial field was subdivided into two parts and each part was subjected to UN and VRT treatment. Each part was schematically divided in $10\times10m$ grids for growth and yield measurement or VRT treatment. 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 this calculation 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 average of 57kg/ha that was higher than 33kg/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 $6.8\%$. Although N use efficiency of VRT compared to UN was not quantified due to lack of no N control treatment, the procedure used in this paper for VRT estimation was believed to be reliable and promising method for managing within-field spatial variability of yield and protein content. The method should be received further study before it could be practically used for site-specific crop management in large-scale rice field.

• Journal of The Korean Society of Grassland and Forage Science
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• v.8 no.3
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• pp.110-116
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• 1988

The response of forage yield was studied with various growth indices to develop yield model and to determine optimum cutting time in three cultivars of orchardgrass 1. Number of tiller per plant was the highest at 3rd cutting stage. But, it was decreased rapidly at 4th cutting stage. Leaf Area Index (LAI) was the highest at 3rd cutting stage. LA1 was increased slowly during 15 days to 20 days after cutting and thereafter increased rapidly. 2. In dry matter yield over cutting stages, 1st cutting and 3rd cutting stages were higher yield than others. Change of dry matter yield was similar to that of LA1 in all cutting stages. 3. Leaf Elongation Rate (LER) and Specific Leaf Weight (SLW) were reached to maximum at 20 to 25 days and 25 to 30 days after cutting, respectively, 4. Dry matter yield was highly correlated with LA1 (r=0.905)and with CGR (r=0.962) over three cultivars. Also, LA1 was significantly with LER. The best-fit yield model was obtained in multiple regression equation which included both dependent variables of LA1 and CGR. 5. Optimum cutting times which were determined by the relationships between D.M. yield and LAI, and between D.M. yield and CGR, were ranged from 32 days t o 36 days depend on each cutting stages.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.112-121
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• 2007

In occasion of soil loss happened in a basin, soil in the near of a stream may flow into the stream easily, but in case that soil is far away from the stream, sediment yield transferred to rivers by rainfall diminishes. To forecast sediment yield of a stream is an essential item for management of basins and streams. Therefore, sediment yield of soil loss produced from a basin is needed to be calculated as accurate as possible. Purpose of the present research is to calculate soil erosion amount in a basin and to forecast sediment yield flowed into a stream by rainfall and analyze sediment yield in the stream. There are various methods that analyze sediment yield of rivers. In the present study, the soil erosion amount was calculated using Revised Universal Soil Loss Equation(RUSLE) and GRID, and sediment yield was calculated using sediment delivery ratio and empirical methods. DEM data, slope of basin, soil map and landuse constructed by GIS were used for input data of RUSLE. The upstream area of the Yeongsan river basin in Gwangju metropolitan city was selected for the study area. Three methods according to the calculation of LS factor were applied to estimate the soil erosion amount. Two sediment delivery ratio methods for the respective methods were applied and, correspondingly, six occasions in sediment yield were calculated. In addition, the above results were compared by relative amount with estimation by the empirical method of Ministry of Construction & Transportation. Sediment yield calculated in the present study may be utilized for the plan, design and management of dams and channels, and evaluation of disaster impact.

• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.3
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• pp.285-292
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• 2012

This experiment was carried out to determine the harvesting day after heading of barley for highest total forage yield in double cropping with corn at paddy field in middle region. The fresh barley yield was the highest at the harvest of 20 days after heading, but the dry matter yield and TDN yield were the highest at the harvest of 25 days after heading because of higher dry matter rate. The dry matter yield of corn after the harvest of 25 days after heading was decreased about 16 percent than that of the check, sowing on april 25. But total fresh yield of corn monoculture was lower about 31 percent, and decreased 28 percent of dry matter and 23 percent of TDN yield, respectively, than that of the double cropping system with corn and barley. In double cropping system at paddy field, the total forage yield was the highest at the harvest of 25 days after heading of barley and grew corn subsequently. Although yield of corn was reduced by late sowing, the total forage yield was increased by double cropping system compared with corn monoculture.