• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.317-317
• /
• 2017

We performed this experiment to select high quality rice adapted to wheat-rice double cropping system. We sowed barley and wheat seed in November 2, 2015. After harvesting barley and wheat, we transplanted high quality rice cultivars: 'Unkwang', 'Hopun', 'Haepum', 'Hyunoum' in June 17 and 24. We used 'sindongjin' rice as a control. As a result, 'Hyunpum' had a highest head rice yield regardless of transplanting date. Head rice yield of 'Hyunpum' was 488.1kg/10a when transplanted in June 17, and 453.6kg/10a when transplanted in June 24. The reason for this highest head rice yield was not percentage of head rice but milled rice yield. Milled rice yield of 'Hyunpum' was 526.5kg/10a when transplanted in June 17, and 490.0kg/10a when transplanted in June 24. Percentage of head rice had little differences between rice cultivars. Among yield components, only number of panicle per $m^2$ had an effect on the differences of yield between rice cultivars. The other yield components didn't have an effect on the differences of yield between rice cultivars. Compared to June 17, only 'Unkwang' had higher head rice percentage and head rice yield in June 24. Head rice percentage of 'Unkwang' changed from 67.3% to 85.0% and head rice yield changed from 324kg/10a to 393.8kg/10a when transplanting date delayed from June 17 to June 24. When transplanting date was delayed, heading date of 'Unkwang' was more delayed than other rice cultivars. By delay of heading date, mean temperature for 40days changed from $25.0^{\circ}C$ to $22.9^{\circ}C$ which improved temperature condition during grain filling stage. This improved head rice percentage and head rice yield of 'Unkwang' transplanted in June 24. If transplanting date is more delayed than June 24, 'Unkwang' could have higher head rice percentage and head rice yield. Therefore, if you transplant rice before June 24 in rice-wheat double cropping system, 'Hyunpum' is recommended as adequate rice cultivar. But if you transplant rice after June 24, further research is needed to find out adequate rice cultivar.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.5
• /
• pp.89-98
• /
• 2004

The amount of rice yield reduction due to inundation should be estimated to analyse economic efficiency of the farmland drainage improvement projects because those projects are generally promoted to mitigate flood inundation damage to rice in Korea. Estimation of rice yield reduction will also provide information on the flood risk performance to farmers. This study presented the relationships between inundated durations and rice yield reduction rates for different rice growth stages from the observed data collected from 1966 to 2000 in Korea, and developed the rice yield reduction estimation model (RYREM). RYREM was applied to the test watershed for estimating the rice yield reduction rates and the amount of expected average annual rice yield reduction by the rainfalls with 48 hours duration, 10, 20, 50, 100, 200 years return periods.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.50 no.4
• /
• pp.262-264
• /
• 2005

A study on genetic variability and association of yield attributing characters with grain yield was carried out using 35 deepwater rice genotypes. High genotypic co-efficient of variation (GCV) was observed for plot yield, $EBT/m^2$, plant height and days to $50\%$ flowering (DFF). For all the traits, estimates of the phenotypic co-efficient of variation (PCV) were higher than GCV, indicating presence of environmental influence. High heritability and genetic advance was observed for plot yield, $EBT/m^2$ and plant height. Plot yield had significant positive association with test weight, $EBT/m^2$ and DFF. However, test weight had the maximum direct effect on grain yield

• Korean Journal of Soil Science and Fertilizer
• /
• v.45 no.1
• /
• pp.16-19
• /
• 2012

Increasing rice grain yield is critical for feeding rapid increasing of Asian population. However, global warming effect may be negative for sustainable rice production. Therefore it is essential to develop technologies not only for increasing grain yield but also for reducing global warming effect. Biochar, which is carbonized biomass, has a great potential of carbon sequestration and soil quality improvement, which can contribute grain yield increasing. In this study, rice yield responses to biochar application on the rice cropping system were evaluated with field experiments under different water management practices at the research farm of the University of Missouri-Columbia Delta Research Center, Portageville, MO. Biochar (i.e., $4Mg\;ha^{-1}$) was produced using field scale pyrolyzer and incorporated into the field 4 months prior to planting. Rice was grown under three different water management practices. Result showed that no significant yield difference was found in the biochar application plots compared to rice hull and control plots from the 2 years field study at the very fertile soil. However, rainfed management results in severe reduction of yield. Research concludes that the biochar application does not significantly influence on rice yield increasing especially for very fertile soils.

• Korean Journal of Food Science and Technology
• /
• v.22 no.2
• /
• pp.199-205
• /
• 1990

With a view to improving the method of rice marketing quality estimation, vaietal milling characteristics and apparent qualities were studied and their statistical interrelationships were computed for 2 years crops, using 22 varieties of Japonica type and Japonica x Indica type (Tongil). The milling yield was the highest for Japonica, while the broken rice yields was the highest for Japa.xInd. type. But bran yield did not show any significant differences among rice types. Milling factors were volume weight of brown rice, dehulling yield, and Polishing yields; the better these factors, the higher the yield. High apparent quality milled rice with high milling yield were produced from rice types whose broken rice, chalked rice, husk yield and bran yield were little and/or low.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.42-42
• /
• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• Plant Resources
• /
• v.5 no.2
• /
• pp.104-108
• /
• 2002

In order to obtain basic information for selecting early maturing rice varieties which is suitable for early cropping before Alisma plantago in the southern part of Korea. Six rice varieties were grown from May to August in 2002 at Youngjeon Experiment Field, Sunchon and yield components and yield of plants were investingated. Early maturing rice cv. Grubyeo showed higher rough rice yield than any other varieties used in the experiment. It showed high yield components, such as culm length, panicle length, number of panicles per plant, number of spikelets per panicle and ratio of ripened grains. Therefore, it was concluded that Grubyeo was the most suitable variety with high yield for the cultivation before growing of Alisma plantago at the southern part of Korea. The heritability of culm length number of spikelets per panicle and rough rice yield were high and that of panicle length number of panicle per plant, ratio of ripened grain and 1,000 grain wt. of milled rice were low. According to the result of path coefficient analysis, characters highly correlated with rough rice yield showed large direct effects on rough rice yield.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.54 no.3
• /
• pp.141-148
• /
• 2012

Food policy is considered as the most basic and central issue for all countries, while making efforts to keep each country's food sovereignty and enhance food self-sufficiency. In the case of Korea where the staple food is rice, the rice yield prediction is regarded as a very important task to cope with unstable food supply at a national level. In this study, Korean paddy Rice yield Prediction Model (KRPM) developed to predict the paddy rice yield using meteorological element and MODIS NDVI. A multiple linear regression analysis was carried out by using the NDVI extracted from satellite image. Six meteorological elements include average temperature; maximum temperature; minimum temperature; rainfall; accumulated rainfall and duration of sunshine. Concerning the evaluation for the applicability of the KRPM, the accuracy assessment was carried out through correlation analysis between predicted and provided data by the National Statistical Office of paddy rice yield in 2011. The 2011 predicted yield of paddy rice by KRPM was 505 kg/10a at whole country level and 487 kg/10a by agroclimatic zones using stepwise regression while the predicted value by KOrea Statistical Information Service was 532 kg/10a. The characteristics of changes in paddy rice yield according to NDVI and other meteorological elements were well reflected by the KRPM.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1414-1430
• /
• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.48 no.4
• /
• pp.326-333
• /
• 2003

Transgenic rice plants expressing a Bacillus subtilis protoporphyrinogen oxidase (Protox), the last shared enzyme of the porphyrin pathway in the expressed cytoplasm or the plastids, were compared with non-trangenic rice plants in their growth characteristics such as tiller number, plant height, biomass, and yield. Transgenic rice plants of $\textrm{T}_3$ generation had 8 to 15 % and 25 to 43% increases in tiller number compared to non-transgenic rice plants at 4 and 8 weeks after transplanting(WAT); similar values were observed for $\textrm{T}_4$ generation at 4 and 8 WAT. However, the plant height in both $\textrm{T}_3$ and $\textrm{T}_4$ generations was similar between transgenic rice plants and non-transgenic rice plants at 4 and 8 WAT. Transgenic rice plants had 13 to 32% increase in above-ground biomass and 9 to 28% increase in grain yield compared to non-transgenic rice plants, demonstrating that biomass and yield correlate with each other. The increased grain yield of the transgenic rice plants was closely associated with the increased panicle number per plant. The percent of filled grain, thousand grains and spikelet number per panicle were similar between transgenic and non-transgenic rice plants. Generally, the growth and yield of transgenic generations ($\textrm{T}_2$, $\textrm{T}_3$, and $\textrm{T}_4$) and gene expressing sites (cytoplasm-expressed and plastid-targeted transgenic rice plants) were similar, although they slightly varied with generations as well as with gene expressing sites. The transgenic rice plants had promotive effects, indicating that regulation of the porphyrin pathway by expression of B. subtilis Protox in rice influences plant growth and yield.