作物生长模拟模型及其应用

论述了作物生长模型在国内外的研究及其发展过程,作物模型的机理及在农业生产中的作用,对作物生长模型在生产应用中存在的问题及今后的发展方向进行了讨论     

基于遥感信息的作物模型重新初始化/参数化方法研究初探

作物模型与遥感信息的结合有助于利用遥感监测的大范围植被信息解决作物模型区域应用时模型初始状态和参数值难以确定的问题。该文借助叶面积指数(LAI)将经过华北冬小麦(Triticum aestivium)适应性调整的WOFOST模型与经参数调整检验的SAIL-PROSPECT模型相嵌套,利用嵌套模型模拟作物冠层的土壤调整植被指数(SAVI),在代表点上借助FSEOPT优化程序使模拟SAVI_s与MODIS遥感数据合成SAVI_m的差异达到最小,从而对WOFOST模型重新初始化。结果表明,借助于遥感信息,出苗期的重新初始化使模拟成熟期与按实际出苗期模拟的结果相差在2天以内,模拟的LAI和总干重的误差比按实际出苗期模拟结果的误差降低3~8个百分点;返青期生物量的重新初始化使模拟LAI和地上总干重在关键发育时刻的误差降至16%以内,模拟LAI和贮存器官重在整个生育期内都更加接近实测值;对返青期生物量的动态调整显示返青到抽穗期间较少次数的遥感数据即能有效地提高作物模型的模拟效果。与国外同类研究相比,该文在作物模型本地化、重新初始化变量和优化比较对象的选择上都有所不同,而利用遥感数据动态调整作物模型初始状态或参数值更具有新意。该文对区域尺度上利用遥感信息优化作物模型的研究具有基础性、探讨性意义。     

杂草与作物竞争模型研究进展

杂草的历史与人类农业史并存。最早科学报道竞争现象是在１４世纪,而开始杂草与作物竞争关系的定量研究则是在本世纪初叶［１］。杂草科学研究较农业病虫害研究起步晚,与许多发达国家相比,我国杂草科学在基础理论方面比较落后,但应用方面发展较快。从系统生态学的高度研究杂草与作物竞争关系是杂草科学研究的一个重要领域,前人为此作了许多有益的工作,并建立了有关的模型,这些模型为解决草害问题起了应有的作用。下面就杂草与作物竞争经验模型的建立、杂草与作物竞争的动态模拟研究、杂草与作物竞争研究在杂草科学管理中的应用等三个…     

作物磷素养分的动态模拟

基于养分平衡原理,分别建立了土壤有机磷与有机肥分解磷的释放、土壤有效磷吸附的动态模型,用Langmuir方程描述土壤吸附磷量与土壤溶液磷浓度的关系,建立了植株临界磷浓度与生理发育时间的关系模型,以及基于生长潜在需要和土壤水溶性磷浓度限制的作物磷素吸收动态模型.检验结果表明,模型对小麦植株含磷率的动态变化有较好的预测效果.     

遥感信息应用于区域尺度水分限制条件下作物生长模拟的研究进展

第2生产水平(即水分限制条件)下的大范围作物生长动态模拟研究具有十分重要的现实意义.目前,区域尺度上水分限制条件下作物生长模拟存在一定的难度,而遥感信息与作物生长模拟模型的结合,可以为区域尺度水分限制条件下作物生长发育模拟及产量估算提供了一条行之有效的途径.本文简要回顾了遥感与作物生长模拟模型结合研究的发展概况,指出了区域尺度水分限制条件下作物生长模拟需要解决的问题,并在已有遥感反演土壤水分状况研究的基础上,简述了遥感信息应用于区域尺度水分限制条件下作物生长模拟的研究方法,并探讨了当前该领域研究的其他可能途径及需要进一步研究和解决的科学问题.     

作物生长模型WOFOST在华北平原的适用性研究

 简要介绍了荷兰瓦赫宁根大学开发的WOFSOT模型,为了评价其在华北平原的适用性,2000～2001年在中国科学院禹城综合试验站进行了水分处理实验。水分池分为8个处理,分别是： ≥40%、≥50%、≥60%、≥70%、≥80%田间持水量及返青-拔节受旱、抽穗-灌浆受旱、灌浆-成熟受旱,每个处理重复1次,共16个实验小区。其中2001年的实验数据用于参数校正,到一套模型的参数值,2000年的实验数据用于模型的验证。主要结论如下：1) WOFOST模型适于描述作物的光合作物过程,对潜在生长的模拟较好,用于华北平原的作物生长与水分利用的研究是适宜的;2) 华北平原的光温生产潜力为8100kg·hm-2左右,目前冬小麦的产量仅相当于潜在产量的65%;3) WOFOST模型在一些细节问题上考虑较粗,比较适合于大面积、区域范围内的模拟;4) WOFOST存在不少需要改进的地方,如干物质分配系数考虑可能过于简单、未计算冬小麦发育后期茎叶干物质向籽粒的转移等。     

水稻生长模拟模型的组建与验证

在模型L1D和TIL的基础上,利用田间试验和文献资料,组建了水稻生长过程的动态模拟模型．验证结果显示,模型运行后生育期的模拟值与实测值吻合良好,干物重、叶面积系数和分蘖数的模拟值与实测值也基本一致,表明该模型能较好地模拟水稻生长过程的动态变化．     

作物生长温度效应的非线性模型及其比较研究

通过严密的数学证明,发现了前人关于作物生长温度效应非线性模型之间的内在联系,修正了有关学者对模型参数定义的局限性,提出了一个通用的作物生长温度效应非线性模型,本研究还将该模型与笔者最近提出的基于高斯方程的非线性模型进行了比较研究,介绍了应用SAS软件求取两个模型相关参数的方法,并以马铃薯生育期模拟为例进行了实证研究,表明这两个模型均有良好的适用性。     

中国作物低温冷害监测与模拟预报研究进展

低温冷害是影响中国粮食生产的重要灾害之一,气候变化使中国特别是东北地区的低温冷害时有发生,东北中部冷害每8年发生一次,开展作物低温冷害研究对于中国粮食安全具有重要意义.从冷害形成机理上可以分为延迟型冷害、障碍型冷害及混合型冷害3类,其冷害指标主要针对不同作物有所差别.基于站点的冷害监测小尺度,GIS等新技术提供的精确温度指标可进行区域监测.遥感技术通过监测下垫面温度(LST)和植被指数(如NDVI)可监测障碍型冷害.基于数理统计、气候模式和作物模型耦合、天气预报的发育期和产量预报的低温冷害预报方法已得到应用.作物模型可依据作物发育进程和产量损失等对冷害损失评估,同时与遥感信息等结合可进行区域灾害评估.最后讨论了中国低温冷害监测和预报新技术的发展方向.     

作物模型区域应用两种参数校准方法的比较

区域模拟的目的是利用有限的空间数据模拟出产量等作物性状的时空变异规律.然而站点作物模型应用到区域范围时涉及到数据归一化、参数简化、模型的校准和验证等问题.利用CERES-Rice模型对作物模型在我国的区域应用进行了尝试并对部分参数进行了校准.首先利用田间观测数据在各实验点上对模型进行了详细的站点校准,以验证模型在我国的模拟能力;其次,以我国水稻种植区(精确到亚区)为单位,运用平均值和标准差(RMSE)两种方法进行了区域校准和验证,即找出能反映出品种空间差异的代表性品种参数集;然后分别运用两种方法的校准结果,模拟水稻产量和成熟期,并将模拟结果与实测值进行了比较.结果表明:区域校准能反映出水稻生育期和产量的时空变化规律,其中RMSE法较平均值法效果好.目前作物模型区域应用过程中还存在大量的误差来源,有待进一步研究.     

利用遥感技术实现作物模拟模型区域应用的研究进展

作物模拟模型从单点发展到区域应用时,模型中一些宏观资料的获取和参数的区域化方面出现困难,利用遥感技术将实现作物模拟模型的区域应用．文中综述了近年来遥感反演作物模型所需的地表生物物理参数的方法、利用遥感信息直接获取生物量的途径和遥感信息与作物模拟模型之间时空匹配问题等方面的研究概况,重点介绍了利用遥感技术实现作物模拟模型区域应用的3种解决方案(强迫型、调控型和验证型)及其研究进展,并讨论了目前存在的问题和今后研究的方向．     

Agroclimatic modeling for the simulation of phenology,yield and quality of crop production

This paper describes the development of basic simulation concepts that can be used in models aimed at forecasting. The objective is to demonstrate the utility of considering the crop's basic environmental requirements or climatic normals in producing a self-contained comprehensive model. We seek to develop a model in which regularly measured weather data can be used to provide information on the crop performance. Following an abbreviated overview of modeling alternatives, the model design is described. The results of this study are a set of criteria and functions needed to predict the temporal evolution of phenological stages, fruit growth, fruit maturation, and fruit coloration for two varieties of oranges (Navel and Valencia). The major factors considered are the effect of temperature and solar radiation on flowering time, and flowering duration and the number of flowers; the effect of past stress, temperature, evaporation, wind, and rain, planting density, and tree age on fruit set. Given the number of fruits set, growth, maturation and coloration are modeled as responding primarily to temperature and water balance. Possible damage due to freezes is also modeled. These form the basis of a time dependent model (reported elsewhere) which uses daily air temperature and wind data for the prediction of these quantities. These criteria and functions are derived from an extensive body of published observations from many parts of the world, and are selected to be variety specific and independent of local climatology or other site-specific effects.     

Support vector machine-based open crop model (SBOCM): Case of rice production in China

Existing crop models produce unsatisfactory simulation results and are operationally complicated. The present study, however, demonstrated the unique advantages of statistical crop models for large-scale simulation. Using rice as the research crop, a support vector machine-based open crop model (SBOCM) was developed by integrating developmental stage and yield prediction models. Basic geographical information obtained by surface weather observation stations in China and the 1:1000000 soil database published by the Chinese Academy of Sciences were used. Based on the principle of scale compatibility of modeling data, an open reading frame was designed for the dynamic daily input of meteorological data and output of rice development and yield records. This was used to generate rice developmental stage and yield prediction models, which were integrated into the SBOCM system. The parameters, methods, error resources, and other factors were analyzed. Although not a crop physiology simulation model, the proposed SBOCM can be used for perennial simulation and one-year rice predictions within certain scale ranges. It is convenient for data acquisition, regionally applicable, parametrically simple, and effective for multi-scale factor integration. It has the potential for future integration with extensive social and economic factors to improve the prediction accuracy and practicability.     

Radiostereometric analysis using clinical radiographic views: Development of a universal calibration object

Radiostereometric analysis (RSA) is a highly accurate technique used to provide three-dimensional (3D) measurements of orthopaedic implant migration for clinical research applications, yet its implementation in routine clinical examinations has been limited. Previous studies have introduced a modified RSA procedure that separates the calibration examinations from the patient examinations, allowing routine clinical radiographs to be analyzed using RSA. However, in order to calibrate the wide range of clinical views, a new calibration object is required. In this study, a universal, isotropic calibration object was designed to calibrate any pair of radiographic views used in the clinic for RSA. A numerical simulation technique was used to design the calibration object, followed by a phantom validation test of a prototype to verify the performance of the novel object, and to compare the measurement reliability to the conventional calibration cage. The 3D bias for the modified calibration method using the new calibration object was 0.032 ± 0.006 mm, the 3D repeatability standard deviation was 0.015 mm, and the 3D repeatability limit was 0.042 mm. Although statistical differences were present between the universal calibration object and the conventional cage, the differences were considered to be not clinically meaningful. The 3D bias and repeatability values obtained using the universal calibration object were well under the threshold acceptable for RSA, therefore it was successfully validated. The universal calibration object will help further the adoption of RSA into a more routine practice, providing the opportunity to generate quantitative databases on joint replacement performance.     

A novel validation and calibration method for motion capture systems based on micro-triangulation

Motion capture systems are widely used to measure human kinematics. Nevertheless, users must consider system errors when evaluating their results. Most validation techniques for these systems are based on relative distance and displacement measurements. In contrast, our study aimed to analyse the absolute volume accuracy of optical motion capture systems by means of engineering surveying reference measurement of the marker coordinates (uncertainty: 0.75 mm). The method is exemplified on an 18 camera OptiTrack Flex13 motion capture system. The absolute accuracy was defined by the root mean square error (RMSE) between the coordinates measured by the camera system and by engineering surveying (micro-triangulation). The original RMSE of 1.82 mm due to scaling error was managed to be reduced to 0.77 mm while the correlation of errors to their distance from the origin reduced from 0.855 to 0.209. A simply feasible but less accurate absolute accuracy compensation method using tape measure on large distances was also tested, which resulted in similar scaling compensation compared to the surveying method or direct wand size compensation by a high precision 3D scanner. The presented validation methods can be less precise in some respects as compared to previous techniques, but they address an error type, which has not been and cannot be studied with the previous validation methods.     

Paediatric bed fall computer simulation model development and validation

Falls from beds and other household furniture are common scenarios stated to conceal child abuse. Knowledge of the biomechanics associated with short-distance falls may aid clinicians in distinguishing between abusive and accidental injuries. Computer simulation is a useful tool to investigate injury-producing events and to study the effect of altering event parameters on injury risk. In this study, a paediatric bed fall computer simulation model was developed and validated. The simulation was created using Mathematical Dynamic Modeling^® software with a child restraint air bag interaction (CRABI) 12-month-old anthropomorphic test device (ATD) representing the fall victim. The model was validated using data from physical fall experiments of the same scenario with an instrumented CRABI ATD. Validation was conducted using both observational and statistical comparisons. Future parametric sensitivity studies using this model will lead to an improved understanding of relationships between child (fall victim) parameters, fall environment parameters and injury potential.     

作物群体边际效应规律及其应用

对作物边际效应的研究表明,有利生态因子的作用大于不利生态因子的作用时,作物群体发生正边际效应,表现为边际优势;不利生态因子的作用大于有利生态因子的作用时,作物群体发生负边际效应,表现为边际劣势．在作物群体内部条件一致的情况下,边际效应的绝对值随边距递增而递减．     

Development and validation of a simulation model for blowfly strike of sheep

A comprehensive simulation model for sheep blowfly strike due to Lucilia sericata (Meigen) (Diptera: Calliphoridae), which builds on previously published versions but also incorporates important new empirical data, is used to explain patterns of lamb and ewe strike recorded on 370 farms in south-west, south-east and central England and Wales. The model is able to explain a significant percentage of the variance in lamb strike incidence in all four regions, and ewe strike in three of the four regions. The model is able to predict the start of seasonal blowfly strike within one week in three of the four regions for both ewes and lambs, and within 3 weeks in the fourth region. It is concluded that the accuracy of the model will allow it to be used to assess the likely efficacy of new control techniques and the effects of changes in existing husbandry practices on strike incidence. The model could also be used to give sheep farmers advance warning of approaching strike problems. However, the ability to forecast future strike patterns is dependent on the accuracy of the weather projections; the more long-term the forecast, the more approximate the prediction is likely to be. When applied on a regional basis, model forecasts indicate expected average patterns of strike incidence and may not therefore be appropriate for individual farmers whose husbandry practices differ substantially from the average.