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Development of a rice growth model for early warning and decision support systems Agriculture and Food Research Organization (NARO) Japan National Agricultural.

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Presentation on theme: "Development of a rice growth model for early warning and decision support systems Agriculture and Food Research Organization (NARO) Japan National Agricultural."— Presentation transcript:

1 Development of a rice growth model for early warning and decision support systems Agriculture and Food Research Organization (NARO) Japan National Agricultural Research Center (NARC) Agroinformatics Division Hiroe Yoshida, Kou Nakazono, Hiroyuki Ohno and Hiroshi Nakagawa

2 Background Crop growth simulation models for rice have played important roles to help understand its yield responses to various environmental conditions. (Kropff et al., 1994; Horie et al., 1995; Bouman et al., 2001) ・ Evaluate plant ideotype ・ Predict potential yield ・ Asses the effect of climate change on crop performance ・ Verify physiological hypotheses for further experimental research The crop growth model has also been utilized as a part of knowledge based decision support systems. (e.g. CERES series in DSSAT) Further development of early warning and decision support systems will be synchronized with that of crop growth simulation model.

3 ・ Transplanting date ・ Cultivar ・ Management plan Early Warning and Decision Support System Decision making! Predict crop productivity based on crop model simulations for years (risk analysis) Sound early warning based on physiological knowledge and weather system Propose management strategies in response to the early warning Decision making! New needs in crop modeling ・ Water management ・ Amount of top-dressing N fertilizer

4 Contents (1) Rice Management in Japan -from statistical data (2) Development of a rice growth model for early warning and decision support systems Targets in process-based rice model

5 (1) Rice Management in Japan

6 (2) Development of a rice growth model for early warning and decision support systems

7 Crop response to N application Targets in process-based rice model Brown Rice Yield ← Spikelet #, Grain filling ratio Appearance Quality ← N and storage starch concentration Food Quality ← Protein content in brown rice N% in brown rice (protein concentration) Dynamics of storage starch accumulation

8 Vegetative Tissues (V) Storage starch (ST) Storage starch accumulation Vegetative tissue growth Grain Yield (Y) Root Photosynthesis Sugar (Su) Maintenance respiration Grain growth Vegetative tissue N (N VT ) (leaf N + stem N) Vegetative tissue N accumulation Grain N (N Y ) N uptake N pool (leaf N + stem N) Grain N accumulation Senescence Recover Translocation Root growth NDND N pool accumulation Translocation Attainable Yield Spikelet sterility Spikelet # Differentiation Degeneration Development DVI Root system development Root system Indigenous supply Soil mineral N fertilization Loss Biomass growth Yield formation Plant N dynamics Plant N uptake Phenological development Spikelet number Expansion LAI LAI development Senescence Yoshida and Horie (2010) FCR 117,

9 Fig . Decreased appearance quality of rice ‘Hatsuboshi’ grown under high air temperature condition Thank you!


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