• 제목/요약/키워드: crop growth experiment

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기후변화에 따른 작물 생산성반응과 기술적 대응 (Impact of climate variability and change on crop Productivity)

  • 신진철;이충근;윤영환;강양순
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2000년도 추계 학술대회지
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    • pp.12-27
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    • 2000

  • During the recent decades, he problem of climate variability and change has been in the forefront of scientific problems. The objective of this study was to assess the impact of climate variability on crop growth and yield. The growth duration was the main impact of climate variability on crop yield. Phyllochronterval was shortened in the global worming situations. A simple model to describe developmental traits was provided from heading data of directly seeded rice cultivars and temperature data. Daily mean development rate could be explained by the average temperature during the growth stage. Simple regression equation between daily mean development rate(x) and the average temperature(y) during the growth period as y = ax + b. It can be simply modified as x = 1/a $\ast$ (y-b). The parameters of the model could depict the thermo sensitivity of the cultivars. On the base of this model, the three doubled CO2 GCM scenarios were assessed. The average of these would suggest a decline in rice production of about 11% if we maintained the current cultivars. Future cultivar's developmental traits could be suggested by the two model parameters.

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벼 출아묘 기계이앙 재배기술 확립에 관한 연구 II. 벼출아묘 육묘온도에 따른 적정육묘일수 및 배유양분 잔존량이 초기생육에 미치는 영향 (Studies on the Cultivation Establishment of Sprouted Seedling for Machine Transplanting of Rice Plant II. Optimum Days of Raising Sprouted Seedling and Effects of Endosperm Rate on Rice Growth in Paddy Field)

  • 양원하;윤용대;송문태;이문희;임무상;박래경
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 1989년도 추계 학술대회지
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    • pp.20-21
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    • 1989

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Growth Simulation of Ilpumbyeo under Korean Environment Using ORYZA2000: I. Estimation of Genetic Coefficients

  • Lee Chung-Kuen;Shin Jae-Hoon;Shin Jin-Chul;Kim Duk-Su;Choi Kyung-Jin
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2004년도 춘계 학술대회지
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    • pp.100-101
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    • 2004

  • [ $\bigcirc$ ] In the growth simulation using genetic coefficients calculated with fooled data under various condition, WAGT was not higher and LAI, WLVG, WSO were higher, but WST was similar before grain-filling stage after the became lower because of higher translocation of carbohydrates than in the growth simulation using genetic coefficients calculated with data under high nitrogen applicated condition. $\bigcirc$ Genetic coefficients should be calculated with data showing potential in ORYZA2000, but under 180 kg and 240 kg N condition in 2003, plants were infected by panicle blast and also yield was not higher than under 120 kg N condition showing not potential condition and therefore not appropriate for genetic coefficients estimation compared with pooled data from various condition.

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