Sensitivity Analysis of Genetic Coefficients and Interval Prediction of Yield in CERES-Rice
Date Issued
2015
Date
2015
Author(s)
Huang, Chi-Ming
Abstract
Climate change caused that increasing extreme climate occurred and resulted in food and water shortages all over the world. Rice, with the second-highest worldwide production and as one of the most important crops in Taiwan, was usually concerned as the target crop in crop models. In addition, the indica was the main cultivating and commercial variety instead of the japonica which was widely cultivated in Taiwan. Crop models were initially used to predict crop growth and development, but researches and applications in Taiwan were still scarce. DSSAT CERES-Rice was one of the widely used crop model in rice research. But there were some difficulties to create individual variations in the simulation because the same inputs would return the same outputs by crop model simulations. In this study, we aimed to use interval estimation to substitute point estimation to predict the yield intervals of two rice varieties in Taiwan, TNG67 and TCS10. First, we created simulation data from Log Multivariate Normal distribution and Uniform distribution then selected P1, P2R, P5, P2O, G1, G2, G3 and G4 as the effective genetic coefficients by 3k factorial confounding design, regression analysis and stepwise regression analysis. Second, we simulated simulation data of TNG67 and TCS10 from Log Multivariate Normal distribution then estimated 10% to 90% percentiles as the yield intervals, (5360.4, 7049.6) and (4995.4, 6881.6) respectively. Comparing to the yields of trials, from Rice Registered Varieties Database, Taiwan Agricultural Research Institute Council of Agriculture, Executive Yuan, the yields of TNG67 were overestimated and the yields of TCS10 were underestimated. CERES-Rice is able to be implemented to predict the yields of Taiwanese rice varieties To improve the simulation outputs, parameterizing varieties in Taiwan and calibration before simulation would be essential and efficient to promote the applications of crop models to agriculture in Taiwan, such as policy assessment, management decision, plant breeding and so on.
Subjects
crop model
sensitivity analysis
interval prediction of yield
SDGs
Type
thesis
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