• Journal of Climate Change Research
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• v.9 no.1
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• pp.31-45
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• 2018

This study implemented the prediction of drought properties (number of drought events, intensity, duration) using the user-oriented systematical procedures of downscaling climate change scenarios based the multiple global climate models (GCMs), AIMS (APCC Integrated Modeling Solution) program. The drought properties were defined and estimated with Effective Drought Index (EDI). The optimal 10 models among 29 GCMs were selected, by the estimation of the spatial and temporal reproducibility about the five climate change indices related with precipitation. In addition, Simple Quantile Mapping (SQM) as the downscaling technique is much better in describing the observed precipitation events than Spatial Disaggregation Quantile Delta Mapping (SDQDM). Even though the procedure was systematically applied, there are still limitations in describing the observed spatial precipitation properties well due to the offset of spatial variability in multi-model ensemble (MME) analysis. As a result, the farther into the future, the duration and the number of drought generation will be decreased, while the intensity of drought will be increased. Regionally, the drought at the central regions of the Korean Peninsula is expected to be mitigated, while that at the southern regions are expected to be severe.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.2
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• pp.109-127
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• 2014

Maize is one of the most important food and feed crops in the world including Southeast Asia. In spite of numberous efforts with conventional breeding, the maize productions remain low and the loss of yields by drought and downy mildew are still severe in Asia. Genetic improvement of maize has been performed with molecular marker and genetic engineering. Because maize is one of the most widely studied crop for its own genome and has tremendous diversity and variant, maize is considered as a forefront crop in development and estimation of molecular markers for agricultural useful trait in genetics and breeding. Using QTL (Quantitative Trait Loci) and MAS (Marker Assisted Breeding), molecular breeders are able to accelerate the development of drought tolerance or downy mildew resistance maize genotype. The present paper overviews QTL/MAS approaches towards improvement of maize production against drought and downy mildew. We also discuss here the trends and importance of molecular marker and mapping population in maize breeding.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1412-1412
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• 2003

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.51-61
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• 2020

Drought events are not clear when those start and end compared with other natural disasters. Because drought events have different timing and severity of damage depending on the region, various studies are being conducted using satellite images to identify regional drought occurrence differences. In this study, we investigated the applicability of drought assessment using the Evaporative Stress Index (ESI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The ESI is an indicator of agricultural drought that describes anomalies in actual and reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of Land Surface Temperature (LST) and Leaf Area Index (LAI). However, these approaches have a limited spatial resolution when mapping detailed vegetation stress caused by drought, and drought hazard in the actual crop cultivation areas due to the small crop cultivation in South Korea. For these reasons, the development of a drought index that provides detailed higher resolution ESI, a 500 m resolution image is essential to improve the country's drought monitoring capabilities. The newly calculated ESI was verified through the existing 5 km resolution ESI and historical records for drought impacts. This study evaluates the performance of the recently developed 500 m resolution ESI for severe and extreme drought events that occurred in South Korea in 2001, 2009, 2014, and 2017. As a result, the two ES Is showed high correlation and tendency using Receiver Operating Characteristics (ROC) analysis. In addition, it will provide the necessary information on the spatial resolution to evaluate regional drought hazard assessment and and the small-scale cultivation area across South Korea.

• Atmosphere
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• v.31 no.5
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• Korean Journal of Agricultural Science
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• v.38 no.2
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• pp.199-204
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• 2011

This study was conducted to map quantitative trait loci (QTLs) related to drought stress tolerance. An introgression line population derived from a cross, "Ilpum" / "Moroberekan" was used in this study. $F_1$ plants were backcrossed three times to Ilpum to produce $BC_3F_1$ plants. These plants were advanced by selfing for four generation and a total of 117 $BC_3F_5$ introgression lines were developed. These lines were evaluated for percent seed set and spikelets per panicle under the control (field) and drought condition. To identify QTLs related to drought tolerance, 134 SSR markers showing polymorph isms between the parents were genotyped for the 117 $BC_3F_5$ lines. A total of 6 QTLs associated with drought stress were detected on chromosomes 1, 3, 4, 7 and 10. These include two QTLs for phenotypic acceptability, two QTLs for percent seed set ($R^2$ = 19.0 - 20.9%), and two QTLs for spikelets per panicle ($R^2$ = 22.3 - 23.10%). The Moroberekan alleles at three loci contributed the positive effect for drought tolerance. The SSR markers linked to drought stress tolerance can not only facilitate the selection of valuable genes from Moroberekan, but also allow identification of lines with drought tolerance.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.3-12
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• 2004

It is necessary to manage water resources in rural areas in order to achieve proper development of new water resources, sustainable usage and reasonable distribution. This paper aims to analyze multi-temporal Landsat-7 ETM+data for soil moisture that is essential for crops in Ahnsung area. The ETM data was also fused with KOMPSAT-1 images in order to be used as backdrop watershed maps at first. Multi-temporal Images showed also the characteristics of soil moisture distribution. Images taken in April showed that rice paddy had as low reflectance as artificial features. Compared with April scenes, those taken in Hay and June showed wetness index increased in the rice paddies. The mountainous areas have almost constant moisture index, so the difference between the dates was very low while reservoirs and livers had dramatic changes. We can calculate total potential areas of distribution of moisture content within the basin and estimate the areas being sensitive to drought. Finally we can point out the sites of small rice paddies lack of water and visualize their distribution within the same basin. It can be said that multi-temporal Landsat-7 ETM+ and KOMPSAT data can be used to show broad drought with quick and simple analysis. Drought sensitiveness maps may enable the decision makers on rural water to evaluate the risk of drought and to measure mitigation, accompanied with proper data on the hydrological and climatic drought.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.25-25
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• 2022

Drought becomes frequent and severe because of continuous global warming, leading to a significant loss of crop yield. In soybean (Glycine max [L.]), most of quantitative trait loci (QTLs) analyses for drought tolerance have conducted by investigating yield changes under water-restricted conditions at the reproductive stages. More recently, the necessity of QTL studies to use physiological indices responding to drought at the early growth stages besides the reproductive ones has arisen due to the unpredictable and prevalent occurrence of drought throughout the soybean growing season. In this study, we thus identified QTLs conferring wilting scores and moisture contents of soybean subjected to drought stress in the early vegetative stage using an recombinant inbred line (RIL) population derived from a cross between Taekwang (drought-sensitive) and SS2-2 (drought-tolerant). For the two traits, the same major QTL was located on chromosome 10, accounting for up to 11.5% of phenotypic variance explained with LOD score of 12.5. This QTL overlaps with a reported QTL for the limited transpiration trait in soybean and harbors an ortholog of the Arabidopsis ABA and drought-induced RING-D UF1117 gene. Meanwhile, one of important features of plant drought tolerance is their ability to limit transpiration rates under high vapor pressure deficiency in response to mitigate water loss. However, monitoring their transpiration rates is time-consuming and laborious. Therefore, only a few population-level studies regarding transpiration rates under the drought condition have been reported so far. Via employing an Arduino-based platform, for the reasons addressed, we are measuring and recording total pot weights of soybean plants every hour from the 1^st day after water restriction to the days when the half of the RILs exhibited permanent tissue damage in at least one trifoliate. Gradual decrease in moisture of soil in pots as time passes refers increase in the severity of drought stress. By tracking changes in the total pot weights of soybean plants, we will infer transpiration rates of the mapping parents and their RILs according to different levels of VPD and drought stress. The profile of transpiration rates from different levels of severity in the stresses facilitates a better understanding of relationship between transpiration-related features, such as limited maximum transpiration rates, to water saving performances, as well as those to other drought-responsive phenotypes. Our findings will provide primary insights on drought tolerance mechanisms in soybean and useful resources for improvement of soybean varieties tolerant to drought stress.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.1
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• pp.8-16
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• 2015

The objective of this study was to evaluate the drought tolerance in maize seedling using leaf rolling. Nineteen maize resources, seven Nested Association Mapping parents lines, six Korean commercial cultivars, and six Southeast Asia commercial cultivars, were used to examine drought tolerance. The leaf rolling scores were measured on each leaf in three stress conditions with moderate drought (10%), severe drought (7%), and extreme drought (5%). Generally leaf rolling score of seedlings increased at the lower soil water potentials (5~7%). As a result, drought-tolerant cultivars showed lower leaf rolling score (below 2.5) than the drought sensitive cultivars (above 3.5). Nine varieties, NK4043, CML322, DK9955, NK4300, Ki11, DK8868, CML228, LVN99, and LVN10, have been selected for tolerance to drought stress. These results suggest that the leaf rolling score in maize seedling has been made available to indirect index for drought tolerance.

• Plant Breeding and Biotechnology
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• v.6 no.4
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• pp.354-362
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• 2018

Maize has high food and industrial value, whereas has difficulties in research because of their complex and huge size genome. Nested association mapping (NAM) was constructed to better understand maize genetics. However, most studies were conducted using the reference genome B73, and only a few studies were conducted on tropical maize. Ki3, one of the founder lines of the NAM population, is a tropical maize. We analyzed the genetic characteristics of Ki3 by using RNA sequencing and bioinformatics tools for various genetic studies. As results, a total of 30,526 genes were expressed, and expression profile were constructed. A total of 1,558 genes were differentially expressed in response to drought stress, and 513 contigs of them come from de novo assemblies. In addition, high-density polymorphisms including 464,930 single nucleotide polymorphisms (SNPs), 21,872 multiple nucleotide polymorphisms (MNPs) and 93,313 insertions and deletions (InDels) were found compared to reference genome. Among them, 15.0 % of polymorphisms (87,838) were passed non-synonymous test which could alter amino acid sequences. The variants have 66,550 SNPs, 5,853 MNPs, and 14,801 InDels, also proportion of homozygous type was higher than heterozygous. These variants were found in a total of 15,643 genes. Of these genes, 637 genes were found as differentially expressed genes (DEGs) under drought stress. Our results provide a genome-wide analysis of differentially expressed genes and information of variants on expressed genes of tropical maize under drought stress. Further characterization of these changes in genetic regulation and genetic traits will be of great value for improvement of maize genetics.