globalchange  > 全球变化的国际研究计划
DOI: 10.1186/s13765-019-0447-z
WOS记录号: WOS:000477648600001
论文题名:
A statistical model for determining zearalenone contamination in rice (Oryza sativa L.) at harvest and its prediction under different climate change scenarios in South Korea
作者: Joo, Yongsung1; Ok, Hyun Ee2; Kim, Jihyun1; Lee, Sang Yoo2; Jang, Su Kyung2; Park, Ki Hwan2; Chun, Hyang Sook2
通讯作者: Chun, Hyang Sook
刊名: APPLIED BIOLOGICAL CHEMISTRY
ISSN: 2468-0834
EISSN: 2468-0842
出版年: 2019
卷: 62
语种: 英语
英文关键词: Climate change ; Predictive map ; Rice ; Statistical model ; Zearalenone
WOS关键词: FUSARIUM-GRAMINEARUM ; MYCOTOXIN ; MAIZE ; GRAIN ; DEOXYNIVALENOL
WOS学科分类: Food Science & Technology
WOS研究方向: Food Science & Technology
英文摘要:

Mycotoxin contamination of food grains is a food safety hazard, and zearalenone (ZEN) is one such mycotoxin affecting rice grains (Oryza sativa L.). A statistical model for estimating the impacts of climate change on ZEN contamination of rice grains in South Korea was constructed. Observational data on ZEN concentrations in rice grains at harvest and local weather information from 241 rice fields in South Korea were collected. To estimate the impact of weather variables on ZEN concentrations, multiple regression analyses were conducted along with variable selection procedure. The final model included the following variables: average temperature and humidity over the flowering period, daily (between days) change in temperature over the harvest period, degree of milling, and the climate region. On the basis of this regression model, maps showing ZEN contamination were produced for South Korea in the present day, the 2030s, and the 2050s, using the representative concentration pathway (RCP) emission scenarios RCP 2.6, 4.5, and 8.5. The predictive maps project that in the 2030s and 2050s, ZEN contamination in rice grains will increase nationwide, particularly more so on the western side of South Korea. Our research results might be helpful in developing effective control measures against ZEN contamination due to climate change.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/143778
Appears in Collections:全球变化的国际研究计划

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作者单位: 1.Dongguk Univ Seoul, Dept Stat, Pil Dong 3 Ga, Seoul, South Korea
2.Chung Ang Univ, Dept Food Sci & Technol, Anseong 456756, South Korea

Recommended Citation:
Joo, Yongsung,Ok, Hyun Ee,Kim, Jihyun,et al. A statistical model for determining zearalenone contamination in rice (Oryza sativa L.) at harvest and its prediction under different climate change scenarios in South Korea[J]. APPLIED BIOLOGICAL CHEMISTRY,2019-01-01,62
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