• Title/Summary/Keyword: Forest meteorology

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Study on the Characteristics of Cultivation Period, Adaptive Genetic Resources, and Quantity for Cultivation of Rice in the Desert Environment of United Arab Emirates (United Arab Emirates 사막환경에서 벼 재배를 위한 재배기간, 유전자원 및 수량 특성 연구)

  • Jeong, Jae-Hyeok;Hwang, Woon-Ha;Lee, Hyeon-Seok;Yang, Seo-Yeong;Choi, Myoung-Goo;Kim, Jun-Hwan;Kim, Jae-Hyeon;Jung, Kang-Ho;Lee, Su-Hwan;Oh, Yang-Yeol;Lee, Kwang-Seung;Suh, Jung-Pil;Jung, Ki-Yuol;Lee, Jae-Su;Choi, In-Chan;Yu, Seung-hwa;Choi, Soon-Kun;Lee, Seul-Bi;Lee, Eun-Jin;Lee, Choung-Keun;Lee, Chung-Kuen
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.3
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    • pp.133-144
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    • 2022
  • This study was conducted to investigate the cultivation period, adaptive genetic resources, growth and development patterns, and water consumption for rice cultivation in the desert environment of United Arab Emirates (UAE). R esearch on rice cultivation in the desert environment is expected to contribute to resolving food shortages caused by climate change and water scarcity. It was found that the optimal cultivation period of rice was from late November to late April of the following year during which the low temperature occurred at the vegetative growth stage of rice in the UAE. Asemi and FL478 were selected to be candidate cultivars for temperature and day-length conditions in the desert areas as a result of pre-testing genetic resources under reclaimed soil and artificial meteorological conditions. In the desert environment in the UAE, FL478 died before harvest due to the etiolation and poor growth in the early stage of growth. In contrast, Asemi overcame the etiolation in the early stage of growth, which allowed for harvest. The vegetative growth phases of Asemi were from early December to early March of the following year whereas its reproductive growth and ripening phases were from early March to late March and from late March to late April, respectively. The yield of milled rice for Asemi was 763kg/10a in the UAE, which was about 41.8% higher than that in Korea. Such an outcome was likely due to the abundant solar radiation during the reproductive growth and grain filling periods. On the other hand, water consumption during the cultivation period in the UAE was 2,619 ton/10a, which was about three times higher than that in Korea. These results suggest that irrigation technology and development of cultivation methods would be needed to minimize water consumption, which would make it economically viable to grow rice in the UAE. In addition, select on of genetic resources for the UAE desert environments such as minimum etiolation in the early stages of growth would be merited further studies, which would promote stable rice cultivation in the arid conditions.

Field Validation of PBcast in Timing Fungicide Sprays to Control Phytophthora Blight of Chili Pepper (고추 역병 방제시기 결정을 위한 PBcast 예측모델 타당성 포장 평가)

  • Ahn, Mun-Il;Do, Ki Seok;Lee, Kyeong Hee;Yun, Sung Chul;Park, Eun Woo
    • Research in Plant Disease
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    • v.26 no.4
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    • pp.229-238
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    • 2020
  • Field validation of PBcast, an infection risk model for Phytophthora blight of pepper, was conducted through a designed field experiment in 2012 and 2013. Conduciveness of weather conditions at 26 locations in Korea in 2014-2017 was also evaluated using PBcast. The PBcast estimated daily infection risk (IR) of Phytophthora capsici based on weather and soil texture data. In the designed filed experiment, four treatments including routine sprays at 7-day intervals (RTN7), forecast-based sprays when IR reached 200 (IR200) and 224 (IR224), and no spray (CTRL) were compared in terms of disease incidence and number of sprays recommended for disease control. In 2012, IR had reached over 200 twice, but never reached 224. In 2013, IR had reached over 200 three times and once higher than 224. The RTN7 plots were sprayed 17 and 18 times in 2012 and 2013, respectively. Weather conditions throughout the country were generally conducive for Phytophthora blight and 3-4 times of fungicide sprays would have been reduced if the PBcast forecast information was adopted in the decision-making for fungicide sprays. In conclusion, the PBcast forecast would be useful to reduce fungicide applications without losing the disease control efficacy to protect pepper crop from Phytophthora blight.

Spatial Usage and Patterns of Corvus frugilegus after Sunrise and Sunset in Suwon Using Citizen Science (시민과학을 활용한 수원시에 출몰하는 떼까마귀(Corvus frugilegus)의 일출 및 일몰시 선호 서식지 분석)

  • Yun, Ji-Weon;Shin, Won-Hyeop;Kim, Ji-Hwan;Yi, Sok-Young;Kim, Do-Hee;Kim, Yu-Vin;Ryu, Young-Ryel;Song, Young-Keun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.24 no.6
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    • pp.35-48
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    • 2021
  • In Suwon, the overall hygiene of the city is threatened by the emergence of the rook(Corvus fugilegus) in the city. Rooks began to appear in November of 2016 and has continued to appear from November to March every year. In order to eradicate or to prepare an alternative habitat for rooks, this study aimed to identify the preferred habitat and specific environmental variables. Therefore, in this work, we aim to understand the predicted distribution of rooks in Suwon City with citizen science and through MaxENT, the most widely utilized habitat modeling using citizen science to analyze the preferred habitat of harmful tides appearing in urban areas. In this study, seven environmental variables were chosen: biotope group complex, building floor, vegetation, euclidean distance from farmland, euclidean distance from streetlamp, and euclidean distance from pole and DEM. Among the estimated models, after the time period of sunrise (08:00~18:00) the contribution percentage were as following: euclidean distance from arable land(39.2%), DEM(25.5%), euclidean distance from streetlamp(22.3%), euclidean distance from pole(7.1%), biotope group complex(4.9%), building floor(1%), vegetation(0%). In the time period after sunset(18:00~08:00) the contribution percentage were as following: biotope group complex(437.4%), euclidean distance from pole(26.8%), DEM(13.4%), euclidean distance from streetlamp(11.8%), euclidean distance from farmland(7.9%), building floor(1.4%), vegetation(1.3%).