基于同伸关系的水稻群体茎蘖和叶面积动态模拟模型
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摘要
作物生长模拟模型的研究,对作物栽培管理系统的发展有重要的理论意义和实际价值。本研究在总结、提炼和借鉴前人研究成果和建模理念的基础上,通过不同生态地区、不同稻作方式、不同类型品种、不同播期、氮肥和密度等试验,对水稻主茎叶龄、群体茎蘖数和叶面积与环境因子之间的关系进行了定量解析和综合。基于水稻器官和形态发生的同伸规律,构建了水稻群体茎蘖数和叶面积指数模拟模型。这些研究结果,为水稻栽培管理决策支持系统的研制奠定了基础。
为筛选出适应性较广泛的水稻主茎出叶模型,本文利用南京和丽江两个生态点,多个品种类型,多个播期的水稻出叶动态和温光条件资料,对前人提出的基于热时间的线性模型(TTLM)和幂函数模型(TTPM)、基于辐热指数的线性模型(PTILM)、基于时间和温度的水稻钟模型(RCM)和基于Beta方程的出叶模型(BBM)等5种有代表性的出叶模型进行了比较和检验。结果表明,BBM和RCM模型拟合精度高,模型参数在同一地区具有较好的通用性,但用于生态条件相差较大的不同地区时需要重新订正；而基于热时间的TTPM模型,其参数对生态条件不敏感,同一组参数可以用于多种生态条件下同一品种水稻出叶动态的模拟。
为了解决基于叶蘖同伸规律的水稻群体茎蘖动态模拟模型的高估问题,本文提出了相对母茎分蘖发生率的概念,并依据叶蘖同伸原理,推导出了分蘖鞘发生分蘖品种和分蘖鞘不发生分蘖品种的茎蘖增长模型和相对母茎分蘖发生率计算公式。根据田间试验数据,建立了相对母茎分蘖发生率与叶片氮含量和群体叶面积指数的定量关系,进而构建了包含分蘖缺位后效应的水稻茎蘖增长过程模拟模型,用以预测水稻群体茎蘖数的增长和主茎各叶龄期群体内不同蘖龄分蘖的数量。通过分析拔节期不同LAI群体中不同蘖龄分蘖在齐穗期的存活状况,初步建立了拔节期4叶及以下小分蘖的死亡率与拔节期LAI的定量关系,用以预测抽穗期的穗数。利用多个生态点和多种栽培条件下获得的试验资料对模型进行了检验,根均方差(RMSE)均在32以下,模型能较好地模拟水稻茎蘖增长和预测抽穗期的穗数。
通过盆栽条件下对水稻叶片尺寸的详细观察和分析,明确了水稻分蘖叶片与同伸的主茎叶片尺寸之间的定量关系,为依据主茎叶片尺寸估计分蘖叶片的尺寸和叶面积提供了途径。在此基础上,结合主茎叶龄模型和茎蘖动态模型,建立了以主茎叶片尺寸和群体茎蘖构成为输入的无衰亡条件下的叶面积指数模拟模型,再将该模型与前人提出的氮限制下的叶面积指数模型相结合,建立起了误差相对较小的水稻叶面积指数模拟模型。初步的检验结果表明,分蘖叶片与同伸的主茎叶片在尺寸上的相关性普遍存在,且不受氮素水平的影响；用不同地区、不同品种、不同施氮水平和不同密度的试验数据对模型整体的预测效果进行检验,RMSE均在0.4以下,表明模型具有较好的预测效果。
最后,对本文筛选的水稻主茎叶龄模型,群体茎蘖和叶面积动态模拟模型进行了集成,并用多品种、多年、多点及多种稻作方式的大田生产数据对模型进行了综合检验,结果表明,本文构建的水稻群体叶蘖动态模拟模型具有较好的预测效果,能够应用于各种品种和生态条件下水稻叶龄和群体叶蘖动态的预测。
The research of crop growth simulation model would be important for facilitating development for crop cultivation and management system. In the present study, the relationships of growth and development especially indexes of rice population development including leaf emergence, tillering dynamics and LAI developing dynamics to environment factors were analyzed and integrated by using the field experiments data with different genotypes, different sowing dates, different eco-sites, different cultivation methods, different nitrogen application levels and different planting densities.By summing up, refining and adopting the results of previous labors and the methodology and technology of crop growth modeling, a simulation model on rice tillering and LAI development based on Synchronously Emerging characteristic of rice was developed.These results provide basis for construction of rice digital management system.
To select the best leaf emergence models from the5representative models which were Linear model based on thermal time (TTLM), Power function based on thermal time (TTPM), Linear model based photo-thermal index (PTILM), Time and temperature based Rice clock model (RCM) and Time and temperature-and Beta function-based model (BBM), tests and comparisons of them were made with data from experiments of different genotypes, sowing dates and eco-sites. The results show that, BBM and the RCM model are of of high fitting precision, model parameters in the same area has good versatility, but for the large difference in ecological conditions in different regions need to re-revised; Parameters of the TTPM model based on thermal time was not sensitive to the ecological conditions, the same set of parameters can be used for the leaf number prediction of the same variety under different ecological conditions.
In order to solve this problem, the concept of Tillering Rate Relative to Mother Tiller (TRRM) was proposed. According to the Synchronously Emerging Characteristics of leaf and tillers, a new tillering model and the calculation equation for TRRM were deduced. By analyzing data from filed experiments, the quantitative relationships of TRRM to leaf nitrogen content and LAI were clear, based on which TRRM under conditions without other limitations could be estimated, then newe tillers number of each leaf age could be estimated. By analyzing the death rate of tillers from jointing to heading stage with1to4leaves at jointing stage under rice populations with different LAI, equations for predicting panicles number per unit land area were proposed. Using data from different ecological and cultivation conditions to verify the model, the results showed that RMSE was lower thant32, which indicated that the model could simulate the rice tilling dynamics well and give barely passable result for panicles number prediction.
Through detailed observations and analysis of leaves size of rice plants under pot-cultivation condition, the quantitative relationships between size of leaves on tillers and that of the leaves synchronously emerging on the main stem were clear. This offered a way to calculate leaf size of tillers according to that of the main stem. Further, by integrating with the leaf emergence model and tillering model, the model with size of leaves on main stem and tiller components as inputs for simulating LAI with no leaf death was proposed. By integrating a Nitrogen-limited-LAI model for predicting LAI after the start of leaf death, a new LAI model for the whole rice development stage was established. The results showed that the relationships between size of leaves on tillers and that of the leaves synchronously emerging on the main stem existed commonly and were not affected by nitrogen levels; Verifying the model with data from different genotypes, different seasons and different nitrogen application levels, RMSE is less than0.4, which indicated that the model could predict LAI dynamics well.
Finally, the realization method of the integration of the rice leaf emergence model, rice tillering mode and LAI model was proposed. Data from filed rice production of differnent varieties, diffenent years, different eco-sites and different cultural methods were used to test the integrated model system.The results showed that models established in this study could give good prediction results and could be used for different varieties in various ecological conditions.
为筛选出适应性较广泛的水稻主茎出叶模型,本文利用南京和丽江两个生态点,多个品种类型,多个播期的水稻出叶动态和温光条件资料,对前人提出的基于热时间的线性模型(TTLM)和幂函数模型(TTPM)、基于辐热指数的线性模型(PTILM)、基于时间和温度的水稻钟模型(RCM)和基于Beta方程的出叶模型(BBM)等5种有代表性的出叶模型进行了比较和检验。结果表明,BBM和RCM模型拟合精度高,模型参数在同一地区具有较好的通用性,但用于生态条件相差较大的不同地区时需要重新订正；而基于热时间的TTPM模型,其参数对生态条件不敏感,同一组参数可以用于多种生态条件下同一品种水稻出叶动态的模拟。
为了解决基于叶蘖同伸规律的水稻群体茎蘖动态模拟模型的高估问题,本文提出了相对母茎分蘖发生率的概念,并依据叶蘖同伸原理,推导出了分蘖鞘发生分蘖品种和分蘖鞘不发生分蘖品种的茎蘖增长模型和相对母茎分蘖发生率计算公式。根据田间试验数据,建立了相对母茎分蘖发生率与叶片氮含量和群体叶面积指数的定量关系,进而构建了包含分蘖缺位后效应的水稻茎蘖增长过程模拟模型,用以预测水稻群体茎蘖数的增长和主茎各叶龄期群体内不同蘖龄分蘖的数量。通过分析拔节期不同LAI群体中不同蘖龄分蘖在齐穗期的存活状况,初步建立了拔节期4叶及以下小分蘖的死亡率与拔节期LAI的定量关系,用以预测抽穗期的穗数。利用多个生态点和多种栽培条件下获得的试验资料对模型进行了检验,根均方差(RMSE)均在32以下,模型能较好地模拟水稻茎蘖增长和预测抽穗期的穗数。
通过盆栽条件下对水稻叶片尺寸的详细观察和分析,明确了水稻分蘖叶片与同伸的主茎叶片尺寸之间的定量关系,为依据主茎叶片尺寸估计分蘖叶片的尺寸和叶面积提供了途径。在此基础上,结合主茎叶龄模型和茎蘖动态模型,建立了以主茎叶片尺寸和群体茎蘖构成为输入的无衰亡条件下的叶面积指数模拟模型,再将该模型与前人提出的氮限制下的叶面积指数模型相结合,建立起了误差相对较小的水稻叶面积指数模拟模型。初步的检验结果表明,分蘖叶片与同伸的主茎叶片在尺寸上的相关性普遍存在,且不受氮素水平的影响；用不同地区、不同品种、不同施氮水平和不同密度的试验数据对模型整体的预测效果进行检验,RMSE均在0.4以下,表明模型具有较好的预测效果。
最后,对本文筛选的水稻主茎叶龄模型,群体茎蘖和叶面积动态模拟模型进行了集成,并用多品种、多年、多点及多种稻作方式的大田生产数据对模型进行了综合检验,结果表明,本文构建的水稻群体叶蘖动态模拟模型具有较好的预测效果,能够应用于各种品种和生态条件下水稻叶龄和群体叶蘖动态的预测。
The research of crop growth simulation model would be important for facilitating development for crop cultivation and management system. In the present study, the relationships of growth and development especially indexes of rice population development including leaf emergence, tillering dynamics and LAI developing dynamics to environment factors were analyzed and integrated by using the field experiments data with different genotypes, different sowing dates, different eco-sites, different cultivation methods, different nitrogen application levels and different planting densities.By summing up, refining and adopting the results of previous labors and the methodology and technology of crop growth modeling, a simulation model on rice tillering and LAI development based on Synchronously Emerging characteristic of rice was developed.These results provide basis for construction of rice digital management system.
To select the best leaf emergence models from the5representative models which were Linear model based on thermal time (TTLM), Power function based on thermal time (TTPM), Linear model based photo-thermal index (PTILM), Time and temperature based Rice clock model (RCM) and Time and temperature-and Beta function-based model (BBM), tests and comparisons of them were made with data from experiments of different genotypes, sowing dates and eco-sites. The results show that, BBM and the RCM model are of of high fitting precision, model parameters in the same area has good versatility, but for the large difference in ecological conditions in different regions need to re-revised; Parameters of the TTPM model based on thermal time was not sensitive to the ecological conditions, the same set of parameters can be used for the leaf number prediction of the same variety under different ecological conditions.
In order to solve this problem, the concept of Tillering Rate Relative to Mother Tiller (TRRM) was proposed. According to the Synchronously Emerging Characteristics of leaf and tillers, a new tillering model and the calculation equation for TRRM were deduced. By analyzing data from filed experiments, the quantitative relationships of TRRM to leaf nitrogen content and LAI were clear, based on which TRRM under conditions without other limitations could be estimated, then newe tillers number of each leaf age could be estimated. By analyzing the death rate of tillers from jointing to heading stage with1to4leaves at jointing stage under rice populations with different LAI, equations for predicting panicles number per unit land area were proposed. Using data from different ecological and cultivation conditions to verify the model, the results showed that RMSE was lower thant32, which indicated that the model could simulate the rice tilling dynamics well and give barely passable result for panicles number prediction.
Through detailed observations and analysis of leaves size of rice plants under pot-cultivation condition, the quantitative relationships between size of leaves on tillers and that of the leaves synchronously emerging on the main stem were clear. This offered a way to calculate leaf size of tillers according to that of the main stem. Further, by integrating with the leaf emergence model and tillering model, the model with size of leaves on main stem and tiller components as inputs for simulating LAI with no leaf death was proposed. By integrating a Nitrogen-limited-LAI model for predicting LAI after the start of leaf death, a new LAI model for the whole rice development stage was established. The results showed that the relationships between size of leaves on tillers and that of the leaves synchronously emerging on the main stem existed commonly and were not affected by nitrogen levels; Verifying the model with data from different genotypes, different seasons and different nitrogen application levels, RMSE is less than0.4, which indicated that the model could predict LAI dynamics well.
Finally, the realization method of the integration of the rice leaf emergence model, rice tillering mode and LAI model was proposed. Data from filed rice production of differnent varieties, diffenent years, different eco-sites and different cultural methods were used to test the integrated model system.The results showed that models established in this study could give good prediction results and could be used for different varieties in various ecological conditions.
引文
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