A Quantitative Knowledge-based Model for Designing Suitable Growth Dynamics in Rice(Crop Physiology and Ecology)

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概要

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• Quantifying growth dynamics in rice (Oryza saliva L.) is important for precision design and diagnosis in cultural management. The primary objective of this study was to develop a general knowledge-based model to design the time-course growth dynamics including stem number, leaf area index (LAI) and aboveground dry matter accumulation with desired target yield under different conditions in rice. Driven by physiological development time (PDT)-based growing degree-days (GDD), the fundamental algorithms of rice growth indices, which vary with the variety, environmental factors and production levels, were formulated from the existing literature and research data. The stem number curve was established according to the dynamic pattern of the stem development and the principle of determining stem number from final panicle number. Under the principle of realizing the maximal photosynthetic production during forty days before and after heading, we obtained the optimum LAI at heading was calculated, and the LAI dynamic from the ratios of LAIs at different growth stages to optimum LAI at heading with linear interpolation method. The aboveground dry matter accumulation curve was described by a logistic curve. Case studies with the typical data sets and variety types at different eco-sites indicated a good performance of the model system, with the root mean square error (RMSE) of 2.5×10^4 ha^<-1>, 0.37 and 700kg ha^<-1>, for the stem number, LAI and aboveground dry matter accumulation, respectively. This model overcome

著者

• Cao Weixing

  Jiangsu Key Laboratory For Information Agriculture Nanjing Agricultural University

• Zhu Yan

  Jiangsu Key Laboratory For Information Agriculture Nanjing Agricultural University

• Zhu Yan

  Hi-Tech Key Lab of Information Agriculture of Jiangsu Province, Nanjing Agricultural University

• Cao Weixing

  Hi-Tech Key Lab of Information Agriculture of Jiangsu Province, Nanjing Agricultural University

• Wang Shaohua

  Hi-tech Key Lab Of Information Agriculture Of Jiangsu Province Nanjing Agricultural University

• Yan Dingchun

  Hi-Tech Key Lab of Information Agriculture of Jiangsu Province, Nanjing Agricultural University

• Yan Dingchun

  Hi-tech Key Lab Of Information Agriculture Of Jiangsu Province Nanjing Agricultural University

• Cao Weixing

  Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University

関連論文

• A Knowledge-Based Model for Nitrogen Management in Rice and Wheat(Agronomy)
• Predicting the Protein Content of Grain in Winter Wheat with Meteorological and Genotypic Factors(Agronomy)
• A Quantitative Knowledge-based Model for Designing Suitable Growth Dynamics in Rice(Crop Physiology and Ecology)
• Analysis of Common Canopy Reflectance Spectra for Indicating Leaf Nitrogen Concentrations in Wheat and Rice(Crop Physiology and Ecology)
• Spatial Distribution of Leaf Area Index and Leaf N Content in Relation to Grain Yield and Nitrogen Uptake in Rice(Agronomy)
• A Knowledge-Based Model for Nitrogen Management in Rice and Wheat

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