| Project/Area Number |
10660042
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
植物保護
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| Research Institution | IBARAKI UNIVERSITY |
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Principal Investigator |
SAGO Ryuichi IBARAKI Univ. Fuc. Of Agriculture Associate Professor, 農学部, 助教授 (30261746)
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| Project Period (FY) |
1998 – 1999
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| Project Status |
Completed (Fiscal Year 1999)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 1999: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1998: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Keywords | Seedbank in soil / seedbank dynamics / herbicide / weed management / weed competition / rice yield / 防除予測 / 水田雑草 / 雑草発生診断 / 雑草防除 |
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| Research Abstract |
More than 30years have passed since a herbicides effective for annual weeds was used to control weeds in Japan. Recently, we can find the paddy rice fields where are few annual weeds and decrease the number of weed seeds in soil after application of effective herbicides. A potential use of seedbank information in weed management is the use of models that incorporate seedbank dynamics and prediction of weed emergence into the decision making process.
In 1998, I tried to estimate the seed density in soil based on the number of seedlings emerging from paddy soil samples collected from 25 paddy fields. At first, we make sure of the tendency toward the seedbank change of the rice field. When herbicides were applied consecutively, the seedbank decreased 12.7% per year at the rice field. Where the seed contained more than 30,000 in plow layer soil. And the decreased rate was 12.7〜2.3% per year in the rice field contained less than 30,000 seeds in plow layer soil.
In 1999, I conducted to clear the weed competion in rice cultivation and to define precisely the number of weed seedbank in soil. And I proved that the loss of grain yield was under 10% in rice plow layer soil contained less than 34,000/mィイD12ィエD1 of weed seeds. We will be able to develop the computerized decision -aid software to predict the economic weed management from these results
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