• Weed & Turfgrass Science
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• v.5 no.1
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• pp.1-4
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• 2016

The Rural Development Administration of Korea conducted a series of surveys of paddy weeds from 1971 to 2013 in approximately 10-year cycles and the results have been used for the efficient weed management of paddy fields. In 1971, annual weeds such as Rotala indica, Eleocharis acicularis f. longiseta, and Monochoria vaginalis were dominant. In 1981, the population of Echinochloa species decreased whereas broadleaf weeds such as M. vaginalis, Sagittaria pygmaea, and S. trifolia were dominant. In 1991, perennial weeds such as Eleocharis kuroguwai, S. pygmaea, and S. trifolia were dominant over annual weeds. In 2000, M. vaginalis was the most abundant species, followed by E. kuroguwai, Echinochloa species, and S. trifolia. In 2013, herbicide-resistant Echinochloa species and M. vaginalis were most dominant, followed by E. kuroguwai, Scirpus juncoides, and S. trifolia. It has been predicted that the prevalence of Echinochloa species will continue to increase and that perennial weeds will be more abundant than annual ones in the near future. The occurrence of herbicide-resistant weeds and exotic weeds will also increase due to global warming and changes in agricultural patterns.

• Korean Journal of Agricultural Science
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• v.42 no.4
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• pp.335-339
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• 2015

This paper reviews current status of weed science in Japanese regional agricultural systems based on the 54th Annual Meeting of the Weed Science Society of Japan. About 300 researchers from 5 countries including Korea participated in the Conference and presented 100 papers in research areas. This congress has an purpose to discuss new troubles, findings and results of weed science. Weed science faces big challenges such as increase in herbicide-resistant weeds, gene-flow from transgenic crops, and invasive weeds. Major research topics were invasive weeds and their ecology, allelopathy, weed management in paddy field, weed management in field crops, and herbicide resistance. Weed control and herbicide resistance management in paddy field were a main object of research. To prevent the increase of problematic weeds and to overcome food crisis, the importance of weed-related researches has been raised. Therefore it is expected that various weed management systems and control of herbicide resistant weeds should be studied continuously in the weed science.

• The Korean Journal of Pesticide Science
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• v.3 no.3
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• pp.45-53
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• 1999

Red sorrel (Rumex acetosella L.) is a troublesome perennial weed in the alpine grasslands of Kangwon Province of Korea. A number of soil- and foliar-applied herbicides were evaluated for their efficacy of red sorrel control. In greenhouse experiments, no soil-applied herbicides, such as pendimethalin, simazine, alachlor, metolachlor, ethalfluralin controlled red sorrel, however, foliar-applied herbicides, such as glufosinate, paraquat, glyphosate, glyphosate + 2,4-D, dicamba, mecoprop, 2,4-D, bentazone controlled more than 60% of red sorrel 2 weeks after treatments. When dicamba and 2,4-D were applied to red sorrel in different growth stages, the auxin-type of herbicides cold control red sorrel regardless of growth stage. This result implies that the auxin-type herbicides can be applied between early May (early growth stage) and mid lune (before fruit maturation) at Kangwon alpine grasslands. In a field experiment, glufosinate at 1.0 kg a.i, $ha^{-1}$, glyphosate at 3.28 kg a.i. $ha^{-1}$, dicamba at 0.96 kg a.i. $ha^{-1}$, and mecoprop at 150 kg a.i. $ha^{-1}$ controlled more than 80% of red sorrel 4 weeks for treatment, suggesting such herbicides could be applied for red sorrel control at Kangwon alpine grasslands.

• The Journal of Korean Institute of Information Technology
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• v.17 no.12
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• pp.81-92
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• 2019

Weeds are a major object which is very harmful to crops. To remove the weeds effectively, we have to classify them accurately and use herbicides. As computing technology has developed, image-based machine learning methods have been studied in this field, specially convolutional neural network(CNN) based models have shown good performance in public image dataset. However, CNN with numerous training parameters and high computational amount. Thus, it works under high hardware condition of expensive GPUs in real application. To solve these problems, in this paper, a hierarchical architecture based deep-learning model is proposed. The experimental results show that the proposed model successfully classify 21 species of the exotic weeds. That is, the model achieve 97.2612% accuracy with a small number of parameters. Our proposed model with a few parameters is expected to be applicable to actual application of network based classification services.

• Weed & Turfgrass Science
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• v.5 no.3
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• pp.111-125
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• 2016

Cordgrass (Spartina spp.) is recognized as a highly invasive plant in estuaries throughout the world because of remarkable versatility and resiliency, significant reproduction, strong adaptability, rapid spreading, and vigorous growth. In this review, therefore, to provide insights on the effective management practices, the previous research works were summarized and discussed. Spartina spp. is a perennial halophyte, warm-season (C4) grass that reproduces both sexually through seeds and asexually by rhizomes. Management strategies for cordgrass have included various physical, biological, and chemical controls. Herbicides are usually the most cost-effective means of control. Currently, glyphosate, imazapyr, fluazifop and haloxyfop have been practically used. To improve the control efficacy, a combination of two more than methods (example, mowing-spraying) is needed to be applied consistently every year for at least 3 to 4 years and to be sprayed with enough dry time (>4-6 hr) at an early growth stage (before flowering). Consistently repeated application of same herbicide have to be avoided to prevent an unexpected emergence of herbicide-resistant lines. On the other hand, Spartina spp. have many positive functions for agricultural and eco-engineering purposes. Thus, we have to give more intensive research for effectively managing advantages and disadvantages of Spartina plantations.

• Korean Journal of Weed Science
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• v.17 no.2
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• pp.163-168
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• 1997

The experiment was conducted in 1996 to investigate distribution, germination characteristics, and effective control of Abutilon theophrasti in corn fields. The regional distribution of A. theophrasti showed that it was higher in Gyenggi province than in Kangwon, Chungnam, or Chonllanambug provinces because of many dairy farms located in Gyenggi province where fresh corn was used as ensilage. The optimal temperature of the weed seed germination was around 15~$20^{\circ}C$ and germination rate was 73~93% in 1~5cm of burial depth. The weed was able to be controlled effectively when treated 10 days after seeding more than just after seeding with herbicides, pendimethalin 31.7% EC, linuron 50% WP and pendimethalin linuron 25% EC with an acceptable phytotoxicity.

• Weed & Turfgrass Science
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• v.6 no.2
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• pp.86-108
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• 2017

The nationwide weed survey was conducted in arable land, paddy field, upland, orchard and pasture, over whole country of Korea during 3 years from 2013 to 2015. Also, these survey were conducted in order to determine a change of weed community and to identify a major dominant weed species, and problem weeds. Weeds of arable land were composed of 619 species belonging to 81 families. Weeds occurred in paddy field were 90 species belonging to 28 families, upland weeds were 375 species of 50 families, orchard weeds were 492 species of 63 families and pasture weeds 275 species of 52 families. Among total 81 families, the Asteraceae (15.5%) was the biggest family, followed by Poaceae (13.1%), Fabaceae (5.5%), Cyperaceae (5.2%), Polygonaceae (6.3%), respectively. And these weed species were composed of annual weeds of 209 species (33.8%), winter annual of 102 species (16.4%) and perennial weeds of 308 species (49.8%). Exotic weeds naturalized in Korea were investigated as 166 species. Weed flora in Korean cultivation area have been increased as much as 13 families and 186 species for 10 years compared to 2000~2004 weed survey result of 68 families and 433 species. The increment could be resulted from the change of weed population such as increase of the herbicide-resistant and the difference of investigation method.

• Weed & Turfgrass Science
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• v.6 no.2
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• pp.117-123
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• 2017

Invasive alien species (IAS) can affect agricultural ecosystem negatively and critically. The geographical distributions of nine IAS plants in Korean orchards and uplands were investigated. Ambrosia artemisiifolia distributed widely in Korean peninsula and Ambrosia trifida distributed intensively in Gyeonggi-do. Aster pilosus distributed in Gyeonggi-Gangwon region and Lactuca scariola distributed linear region from the north-western to south-eastern part of Korea. Hypochaeris radicata distributed mainly in Jeju-do and Solanum carolinense distributed in eastern Gyeonggi-do. Rumex acetosella and Sicyos angulatus sporadically occurred in Korean croplands and Eupatorium rugosum was found in one region only. The distribution of IAS plants in croplands was very similar to that in non-croplands suggesting that ecological position of arable lands is not different from that of non-arable lands. Therefore, IAS plants in the croplands should be managed for not only prevention of yield reduction, but also protection or maintenance of original ecosystem. Development of management methods apposite to current Korean status are required to control IAS plants in croplands.