Establishment and Validation of Prediction Model for Rice Growth Stages

• Main Authors: Shih-Hong Lin, 林士閎
• Other Authors: Hsiu-Ying Lu
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/17638273698502170174

碩士 === 國立中興大學 === 農藝學系所 === 101 === The aim of this study is to establish the models for predicting three major growth stages (i.e., 50% tillering, panicle initiation, and 50% heading) of three mid-late maturing domestic rice varieties (i.e., TK9, TNG71, and TNGS22). Data sets were collected from field experiments planting at various transplanting dates of two crop seasons in 2006-2010. A linear regression model for predicting growth stage was established using development rate during the period as the dependent variable and its corresponded effective accumulated temperature (growing degree days, GDD) as an independent variable; the predictive capabilities using these GDD models were also validated. For every growth stage, we firstly removed each one from all data sets as calibration and used the left to build up the model. It showed that all the 95% confidence intervals (CI) of the differences between predicted and actual values of development rate included zero, which reveals an acceptable predictive error at 5% significance level. Then, we merged all data sets to build up the GDD models for predicting growth stages and found the estimated values of regression coefficient in these GDD models were within the 95% CI of estimated values obtained from those models in above calibration procedures. It was therefore suggested that our GDD models for predicting rice growth stages are robust. With these models, GDDs necessary to reach each growth stage in three rice varieties could be estimated. It was also found that three varieties were not completely identical in development rates during the periods of difference growth stages. Although they are mid-late maturing varieties, however, TNG71 is earlier and TNGS22 is later. This resulted from the growth of TNG71 was faster during the period from 50 % tillering to panicle initiation, while the growth of TNGS22 was slower during the period from 50% tillering to 50% heading in spite of rapid growth before 50% tillering. Therefore to increase paddy yield, proper field management should be arranged in critical growth periods according to different rice varieties.