• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.36-36
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• 2019

• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.96-96
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• 2020

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.10a
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• pp.106-106
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• 2021

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.80-80
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• 2022

Estimation of heading date of paddy rice is laborious and time consuming. Therefore, automatic estimation of heading date of paddy rice is highly essential. In this experiment, deep learning classification models were used to classify two difference categories of rice (vegetative and reproductive stage) based on the panicle initiation of paddy field. Specifically, the dataset includes 444 slanted view images belonging to two categories and was then expanded to include 1,497 images via IMGAUG data augmentation technique. We adopt two transfer learning strategies: (First, used transferring model weights already trained on ImageNet to six classification network models: VGGNet, ResNet, DenseNet, InceptionV3, Xception and MobileNet, Second, fine-tuned some layers of the network according to our dataset). After training the CNN model, we used several evaluation metrics commonly used for classification tasks, including Accuracy, Precision, Recall, and F1-score. In addition, GradCAM was used to generate visual explanations for each image patch. Experimental results showed that the InceptionV3 is the best performing model in terms of the accuracy, average recall, precision, and F1-score. The fine-tuned InceptionV3 model achieved an overall classification accuracy of 0.95 with a high F1-score of 0.95. Our CNN model also represented the change of rice heading date under different date of transplanting. This study demonstrated that image based deep learning model can reliably be used as an automatic monitoring system to detect the heading date of rice crops using CCTV camera.

• Environmental Engineering Research
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• v.22 no.2
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• pp.193-202
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• 2017

The study estimated the relationship between carbon dioxide, crop and livestock production index in Ghana: Estimating the long-run elasticities and variance decomposition by employing a time series data spanning from 1960-2013 using both fit regression and ARDL models. There was evidence of a long-run equilibrium relationship between carbon dioxide emissions, crop production index and livestock production index. Evidence from the study shows that a 1% increase in crop production index will increase carbon dioxide emissions by 0.52%, while a 1% increase in livestock production index will increase carbon dioxide emissions by 0.81% in the long-run. There was evidence of a bidirectional causality between a crop production index and carbon dioxide emissions and a unidirectional causality exists from livestock production index to carbon dioxide emissions. Evidence from the variance decomposition shows that 37% of future fluctuations in carbon dioxide emissions are due to shocks in the crop production index while 18% of future fluctuations in carbon dioxide emissions are due to shocks in the livestock production index. Efforts towards reducing pre-production, production, transportation, processing and post-harvest losses are essential to reducing food wastage which affects Ghana's carbon footprint.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.2
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• pp.134-142
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• 2017

Crop production in rice paddy fields is of great importance because of declining rice consumption and the low self-sufficiency ratio for field crops in Korea. A controlled drainage system (CDS) is recognized as an effective means to adjust water table (WT) levels as needed and control soil water content to improve the soil environment for optimum crop growth. The present study evaluated the effects of a CDS on soil characteristics, including soil water distribution and soybean development in paddy fields. The CDS was installed with two drain spacing (3 m and 6 m) at the experimental paddy field at the National Institute of Crop Science, Miryang, Korea. It was managed with two WT levels (0.3 m and 0.6 m) during the growing season. Soil water content, electrical conductivity and plant available nitrogen content in the soil were significantly greater in the 0.3 m WT management plots than in the 0.6 m plot and the control. At the vegetative stage, chlorophyll content was significantly lower with higher WT control because of excess soil moisture, but it recovered after the flowering stage. Soybean yield increased with WT management and the 0.6 m WT treatment produced the greatest grain yield, $3.38ton\;ha^{-1}$, which was 50% greater than that of the control. The CDS directly influenced outflow through the drains, which significantly delayed nutrient loss. The results of this study indicated that WT management by CDS can influence soil characteristics and it is an important practice for high yielding soybean production in paddy fields, which should be considered the crop growth stages for stable crop 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 CROP SCIENCE
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• v.61 no.2
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• pp.104-112
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• 2016

A double-cropping system with soybean (Glycine max) following the cultivation of potato, garlic, and onion is widely adopted in the southern region of Korea. For this system, marginal dates for planting must be determined for profitable soybean yields, because the decision to plant soybean as a second crop is occasionally delayed by harvest of the first crop and weather conditions. In order to investigate the effect of planting date on soybean yield, three cultivars (early and late maturity) were planted on seven different dates from May 1 to July 30 in both paddy and upland fields across 2012 and 2013. Soybean yields were significantly different among the planting dates and the cultivars; however, the interaction between cultivar and planting date was not significant. Based on linear regression, the maximum yield of soybean was reached with a June 10 planting date, with a sharp decline in yield for crops planted after this date. The results of this study were consistent with those of a previous one that recommends early and mid-June as the optimum planting period. Regardless of soybean ecotype, a reduction in yield of greater than 20% occurred when soybean was planted after mid-July. Frost during soybean growth can reduce yields, and the late maturity cultivars planted on July 30 were damaged by frost before completing maturation and harvest; however, early maturity cultivars were safely harvested. For sufficient time to develop and reach profitable yields, the planting of soybean before mid-July is recommended.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.326-326
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• 2017

Climate warming is the issue on the global scale. Soybean can be seriously damaged when high temperature occurs during a reproductive stage such as the flowering and pod-setting period according to the Representative Concentration Pathway (RCP) (2021~2100) 8.5 scenarios. The weather in 2016 was very different from other years (average for 30 years from 1980 to 2010) ; the highest temperature was $33.7^{\circ}C$ which was higher $3.29^{\circ}C$ than average temperature from last 30 years and average rainfall was 26.5 mm, lower 140.9 mm than average rainfalls from other years. Especially, the highest temperature during soybean flow-ering and pod setting stage was $26.8^{\circ}C$ which was higher $0.1^{\circ}C$ and rainfall was 172.2 mm, higher 47.8 mm than other years from the first to the 20th in the October at soybean seed elongation stage. Soybean leaves were turned upside down by the drought stress during the flowering and pod-setting stage. The numbe-r of pods and seeds per unit area decreased 11.0% and 30.3% compared with the previous year, respectively. The ripening period was prolonged by 21 days because of high temperature and soil moisture contents due to the continual rainmade increase of the seed weight up to 15.6% and the yield decreased 7.1% compared to the previous year.