• Korean Journal of Agricultural Science
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• v.44 no.1
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• pp.40-49
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• 2017

Cultural practices for adzuki bean and the distribution of weed species in the south-west regions of Korea were surveyed to provide information on effective weed management. Approximately 27.5% of the farm households were growing adzuki bean in an area larger than 1 ha while the rest grew the crop in an area smaller than 1 ha. Of all adzuki bean growers, 17.1% seeded in early June, 8.6% in mid June, 34.3% in late June, 17.1% in early July, 20.0% in mid July, and 2.9% in late July. The average planting distance was $71.0{\times}29.5cm$. From the 40 surveys in adzuki bean fields, 35 weed species in 17 families were identified. According to the occurrence frequency, the dominant weed species were Digitaria sanguinalis, Acalypha australis, Cyperus amuricus, Echinochloa crus-galli, and Amaranthus nangostanus in decreasing order of dominance. However, based on dry weight, Chenopodium album (34.4%) was the most dominant followed by Acalypha australis (21.9%), Amaranthus nangostanus (19.1%), Digitaria sanguinalis (7.5%), and Portulaca oleracea (6.1%). The exotic weeds found in the field of adzuki were Ipomoea hederacea, Abutilon avicennae, and Celosia argentea. The plant heights of I. hederacea, A. avicennae, and C. argentea were 259 cm, 98 cm, and 76 cm, respectively, while the fresh weights were 850 g, 66 g, and 101 g, respectively. Integrated weed management systems utilizing mechanical, chemical, and biological control techniques need to be developed for effective weed management in adzuki bean production.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.749-760
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• 2018

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, the Korean government has pursued cultivating upland crops in paddy fields to reduce overproduced rice in Korea. For this policy to succeed, it is critical to understand the topographic information of paddy fields and its effects on upland crops cultivated in the soils of paddy fields. The objective of this study was to characterize the growth properties of sesame and perilla from paddy fields with three soil topographic features and soil water effects which were induced by the topographic features of the sesame and perilla. The crops were planted in paddy fields located in Miryang, Gyeongnam with different topographies: mountain foot slope, local valley and alluvial plain. Soil water contents and groundwater levels were measured every hour during the growing season. The paddy field of the mountain foot slope was significantly effective in alleviating wet injury for the sesame and perilla in the paddy fields. The paddy field of the mountain foot slope had a decreased average soil water content and groundwater level during cultivation. Stress day index (SDI) from the alluvial plain paddy field had the greatest values from both crops and the smallest from the ones from the paddy field of the mountain foot slope. This result means that sesame and perilla had the smallest stress from the soil water content of the paddy field on the mountain foot slope and the greatest stress from the soil water content of the alluvial plain. It is important to consider the topography of paddy fields to reduce wet injury and to increase crop yields.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• The Plant Pathology Journal
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• v.39 no.1
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• pp.136-140
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• 2023

Rice panicle blast is one of the most serious diseases threatening stable rice production by causing severe damage to rice yields and quality. The disease is easy to occur under low air temperature and frequent heavy rainfall during the heading season of rice. In 2021, a rice panicle blast severely occurred in the Jeonbuk province of Korea. The incidence area of panicle blast accounted for 27.7% of the rice cultivation area of Jeonbuk province in 2021, which was 13.7-times higher than in 2019 and 2.6-times higher than in 2020. This study evaluated the incidence areas of rice panicle blast in each region of Jeonbuk province in 2021. The weather conditions during the heading season of rice, mainly cultivated rice cultivars, and the race diversity of the Jeonbuk isolates were also investigated. It will provide important information for the effective control of the rice panicle blast.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.186-186
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• 2022

Phytophthora root and stem rot (PRSR) and wildfire disease (WFD) of soybean are frequently observed in the field of South Korea. The most environmentally friendly way to control PRSR and WFD is to use soybean varieties with resistance to Phytophthora sojae (P. sojae) and Pseudomonas amygdali pv. tabaci. Plant germplasm is an important gene pool for soybean breeding and improvement. In this study, hundreds of soybean accessions were evaluated for the two pathogens, and genome-wide association analyses were conducted using 104,955 SNPs to identify resistance loci for the two pathogens. Of 193 accessions, 46 genotypes showed resistance reaction, while 143 did susceptibility for PRSP. Twenty SNPs were significantly associated with resistance to P. sojae on chromosomes (Chr.) 3 and 4. Significant SNPs on Chr.3 were located within the known Rps gene region. A region on Chr. 4 is considered as a new candidate resistance loci. For evalation of resistance to WFD, 18, 31,74,36 and 34 genotypes were counted by a scale of 1-5, respectively. Five SNP markers on Chrs 9,11,12,17 and 18 were significantly associated with resistance to P. amygdali pv. tabaci. The identified SNPs and genomic regions will provide a useful information for further researches and breeding for resistance to P. sojae and P. amygdali pv. tabaci.

• Journal of Biosystems Engineering
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• v.23 no.3
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• pp.285-290
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• 1998

Growth information of crops is essential for efficient control of greenhouse environment. However, a few non-invasive and continuous monitoring methods of crop growth has been developed. A computer vision system with a CCD camera and a frame grabber was developed to conduct non-destructive and intact plant growth analyses. The developed system was evaluated by conducting the growth analysis of lettuce. A linear model that explains the relationship between the relative crop coverage by the crop canopy and dry weight of a lettuce was presented. It was shown that this measurement method could estimate the dry weight from the relative crop coverage by the crop canopy. The result also showed that there was a high correlation between the projected top leaf area and the dry weight of the lettuce.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.43-48
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• 1998

In order to provide basic information for the estimation of evapotranspiration for grass (Joycia Japonica), both field lysimeter experiment and model prediction were performed to estimate daily ET Various methods were used to predict daily reference crop ET and crop coefficients. Measured mean daily ET during the 1997 growing season was 4.5mm Model predicted mean daily ET during the 1997 growing season varied from 3.6 to 4.7mm depending on the prediction model Crop coefficients varied from 0.96 to 1.27 depending on the prediction model Comparison of the seven reference crop ET prediction methods used in this study shows that the Penman-Monteith method gave the smallest ET while the Hargreaves method gave the largest ET. The crop coefficient by the corrected Penman method was 1.03, which is closest to 1.0, suggesting that this method may he the best prediction method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.353-362
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• 1993

The purpose of this study is to develop a crop-row detector which can be applied to an automatic row following control for cultivators or thinning machines. In this report, a possibility of new crop-row detecting method was discussed. This detecting method consists of two principal means. One is the hardware means to convert the two dimensional crop-row vision to the compacted one dimensional information. The conversion is achieved by a color line sensor and a rotating mirror. In order to extract crop-row , R and G signals of RGB color system are used. The locations of two different points on the target row are detected by this means. Another is the software means to estimate the offset value and the heading angle between the detector and the target row which can be assumed as a straight line. As a result of discussion, it was concluded that this detecting method would be accurate enough for practical use.

• The Korean Journal of Food And Nutrition
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• v.31 no.5
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• pp.712-719
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• 2018

This study was carried out to obtain basic data on Korean traditional Meju collected from 18 regions (TM1~TM18) in Korea and to define and control quality. The shape of Meju was mostly rectangular and the weight was 0.84~2.04 kg. The physicochemical analysis showed: pH, 5.31~8.21; total acidity, 0.91~2.74%; moisture content, 4.79~42.16%; and soluble protein content, 41.37~23.48%. Hunter color values for L (lightness), a (redness), and b (yellowness) ranged from 39.07~67.92, 3.57~8.87, and 7.48~20.67, respectively. The amino nitrogen contents of all samples were in the range of 257.29 to 839.58 mg% and TM13 showed the highest content (839.58 mg%). Total viable cells, yeast and mold counts of Meju were 8.43~5.91 log CFU/g, 2.48~5.19 log CFU/g, and 3.42~7.48 log CFU/g, respectively. Based on the results, it is proposed that quality standards and management of Meju fermentation conditions and information about different varieties of soybeans used should be made available.

• Korean Journal of Agricultural Science
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• v.46 no.2
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• pp.405-416
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• 2019

Weeds are a serious problem in crop production. Use of synthetic herbicides is rapidly increasing in weed management worldwide including Korea. Herbicide application reduces the time spent on weed control. However, the evolution of resistance to herbicides in weeds has become widespread as a natural response to selection pressure imposed by agricultural management activities. If an herbicide with the same mechanisms of action is used repeatedly and intensively, it can rapidly select for a weed biotype that shifts toward difficult-to-control becoming a more tolerant weed and lead to the evolution of herbicideresistant weeds. Moreover, agricultural and biological factors have an important role in the development of herbicide-resistant weed populations. Mitigating the evolution of herbicide resistance in weeds relies on reducing selection through the diversification of weed control techniques. The resistance management of weeds in the future will strongly depend on intensive cropping systems. The current situation of intensive cropping systems with their heavy reliance on the efficacy of chemical weed control will not lead to significant containment of this problem. Therefore, management strategies need to overcome the further spread of herbicide resistance in weeds in Korean crop production. This review presents the current information on herbicide resistance in Korea and factors controlling the development of herbicide resistant weeds.