Modeling of grain filling processes for high yielding rice
Grant-in-Aid for Scientific Research (C).
|Research Institution||Shimane University|
OHNISHI Masao Shimane-University, Faculty of Life and Environmental Science, Associate Professor, 生物資源科学部, 助教授 (80185339)
|Project Fiscal Year
1998 – 2000
Completed(Fiscal Year 2000)
|Budget Amount *help
¥3,400,000 (Direct Cost : ¥3,400,000)
Fiscal Year 2000 : ¥500,000 (Direct Cost : ¥500,000)
Fiscal Year 1999 : ¥500,000 (Direct Cost : ¥500,000)
Fiscal Year 1998 : ¥2,400,000 (Direct Cost : ¥2,400,000)
|Keywords||Rice / Model / Spikelet / Heading / Flowering / Nitrogen / Non-structural carbohydrate / 水稲 / モデル / 穎花数 / 出穂 / 開花 / 窒素 / 非構造性炭水化物|
1. Synthesis of model for predicting rice spikelet density
A model was developed to predict rice spikelet density as determined by plant nitrogen content at spikelet differentiation stage and mean temperature from panicle initiation to spikelet differentiation stage. This model successfully explained all observed spikelet density data obtained under widely different environment conditions. Further, it has been clarified that the estimated values of parameters were physiologically reasonable.
2. Synthesis of model for predicting daily percentage of panicle emergence
A model was developed for predicting daily percentage of paniclc emcrgence in relation to ontogenetic developmental stage. Ontogenetic development stage is quantified by a variable termed developmental index (DVI). The value of DVI is obtained by integrating the daily developmental rate, which is a function of daily mean temperature and day length. This model satisfactorily simulated daily percentage of panicle emergence (heading)
3. Synthesis of model for predicting daily flowering percentage
A model was developed for predicting daily percentage of flowering spikelet in relation to flowering stage of each panicle. Flowering stage is quantified by a variable termed flowering index (FI). The value of FI is obtained by integrating the daily flowering rate, which is a function of daily mean temperature. The simulated percentage of flowering is generally in good agreement with the measured data.
4. Model development for predicting daily number of flowering spikelet for the grain filling processes
A model was formulated to simulate daily number of flowering spikelet of rice by combining panicle emergence model and flowering model. This model can be combined with dynamic model for simulating rice growth and yield.
Research Output (9results)