Estimating Grain Weight and Grain Nitrogen Content with Temperature, Solar Radiation and Growth Traits During Grain-Filling Period in Rice
2010
Lee, C.K., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Kim, J.H., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Son, J.Y., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Yoon, Y.H., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Seo, J.H., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Kwon, Y.U., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Shin, J.C., National Institute of Crop Science, RDA, Suwon, Republic of Korea | Lee, B.W., Seoul National University, Seoul, Republic of Korea
This experiment was conducted to construct process models to estimate grain weight (GW) and grain nitrogen content (GN) in rice. A model was developed to describe the dynamic pattern of GW and GN during grainfilling period considering their relationships with temperature, solar radiation and growth traits such as LAI, shoot dryweight, shoot nitrogen content, grain number during grain filling. Firstly, maximum grain weight (GWmax) and maximum grain nitrogen content (GNmax) equation was formulated in relation to Accumulated effective temperature (AET) × Accumulated radiation (AR) using boundary line analysis. Secondly, GW and GN equation were created by relating the difference between GW and GWmax and the difference between GN and GNmax, respectively, with growth traits. Considering the statistics such as coefficient of determination and relative root mean square of error and number of predictor variables, appropriate models for GW and GN were selected. Model for GW includes GWmax determined by AET × AR, shoot dry weight and grain number per unit land area as predictor variables while model for GN includes GNmax determined by AET × AR, shoot N content and grain number per unit land area. These models could explain the variations of GW and GN caused not only by variations of temperature and solar radiation but also by variations of growth traits due to different sowing date, nitrogen fertilization amount and row spacing with relatively high accuracy.
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