کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4507014 | 1321336 | 2010 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A characterization of rice pests and quantification of yield losses in the japonica rice zone of Yunnan, China
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
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چکیده انگلیسی
Within any geographic area where pest management is to be improved or adapted to agricultural changes, there is a need for characterization to define constraints to crop production. The objective of this study was to assess pest injuries (diseases, insects and weeds) in farmers' fields in the japonica rice zone of Yunnan, China, explore characteristics of rice injury profiles, analyse the relationships between injury profiles and yield levels, and estimate yield losses caused by individual injuries. Seven pest injury profiles (abbreviated as IN) were determined using cluster analysis; IN1, IN2 and IN3 were lower injury levels of pest combinations in seven profiles, while IN5, IN6 and IN7 were higher injury levels. Correspondence analysis based on patterns of injury profiles yielded a path of increasing yield levels associated with varying combinations of injuries. The use of principal component analysis with multiple regression generated estimates of yield reductions due to rice diseases, insects and weeds. The analysis indicated that injuries caused by weeds that are taller than the rice canopy, white heads, leaf folder, bacterial leaf blight, army worms, leaf blast and plant hoppers should be considered as potentially most damaging in this region. Results of this study will provide some foundations for developing pest management strategies and improving rice production at the regional scale.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Crop Protection - Volume 29, Issue 6, June 2010, Pages 603-611
Journal: Crop Protection - Volume 29, Issue 6, June 2010, Pages 603-611
نویسندگان
Kun Dong, Bin Chen, Zhengyue Li, Yan Dong, Hailong Wang,