油菜生育期动态模拟模型的构建

在13个不同熟期甘蓝型油菜品种的2年大田试验中,调查不同播期条件下各品种的生育进程及发育状态。依据油菜生理发育时间恒定原理、生理生态理论及各生育阶段与温度、光周期等外部环境关系,采用Logistic曲线描述油菜光周期效应,谐波分析法分析气温昼夜变化,分段正弦指数函数分析热效应和低温春化效应,结合上述因素构建油菜生育期动态模拟模型;确定模型光周期敏感因子、温度敏感性、生理春化时间和角果期因子4个遗传参数;模型的检验分析表明,对不同播期模拟值与观测值的根均方差平均值为2.67 d,对不同品种模拟值与观测值的根均方差平均值为3.74 d;4个遗传参数值对13个油菜品种聚类分析的结果符合品种特性。因此,该模型在一定范围内可准确揭示油菜对温、光的反应规律,具有较强的可靠性和预测性。

Dynamic Simulation Model for Growth Duration of Rapeseed (Brassica napus)

Field experiments with different sowing dates were carried out for two successive years using 13 rapeseed (Brassica napus) varieties with different growth durations to focus on the growth and development processes of the varieties under different photoperiod-temperature conditions. A dynamic simulation model for predicting growth duration of rapeseed was developed by a combined analysis on different factors. The theory of rapeseed physiological ecology, the principle of constant physiological development time (PDT), and the relationships between different growth and development stages and environmental factors such as temperature and photoperiod were the basis for simulating the model. Logistic curve was used to simulate photoperiod effect, harmonic analysis was used to analyze the changes of day and night temperatures, and piecewise functions of sine exponent equation was adopted to describe thermal and vernalization effects. Four parameters with genetic characteristics, including photoperiod susceptibility, temperature sensitivity, physiological vernalization time and pod period factor, were determined and verified for the accuracy of the model. The test results showed the average of the root mean square errors (RMSE) between the observed and simulated values was 2.67 days for different sowing dates, and 3.74 days for different varieties, respectively. Clustering analysis using four genetic parameters verified the classification of 13 varieties and conformed to their characteristics. The results indicated the model can reveal relative accurately within certain range the response of rapeseed to temperature and photoperiod. Therefore, it can be used as a reliable tool for predicting the growth duration of rapeseed.