作物生长模拟模型参数校正与有效化的理论和实践

以ＧＯＳＳＹＭ 模型为例系统阐述了作物生长模拟模型有关参数校正和模型有效化的一般原理和方法,同时用新疆棉区的试验具体校正了品种参数、土壤参数和修改了部分模块,并对校正结果进行了验证．结果表明,两个试点土壤２０ ～４０ 、６０ ～８０ｃｍ 两个土层生长季水分动态观测值与土壤参数校正后模型的模拟值吻合较好;系５ 品种试验生育期６ 项生物指标动态模拟结果与实测值拟合的相关系数都在０ ．９ 以上,并且不同栽培条件的３ 个处理的模拟产量的相对误差平均为７ ．５ ％ ,模拟结果较理想．     

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．     

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.     

大麦叶面积指数模拟模型

准确模拟叶面积指数是作物生长模拟模型预测作物生长和产量的关键.本文通过系统分析扬州和武汉地区不同大麦品种高产群体叶面积指数变化动态,建立了大麦群体的叶面积指数模拟模型.大麦叶面积指数是品种叶面积指数扩展的遗传参数和气温日较差、日照时数、辐射量等气候因子及水肥丰缺因子的函数.孕穗抽穗期最大叶面积指数与该期最适叶面积指数是不同的概念,二者之间存在着极显著差异.利用扬州、南京和昆明地区不同品种的播期试验及氮肥试验资料对模型进行了检验,结果表明,模型对大麦叶面积指数的模拟效果较好,模拟值与观测值吻合度高,根均方差RMSE介于0.742～2.865,平均值为1.348.对模拟值与观测值进行y=x的线性回归分析,相关系数R²介于0.511～0.954,均呈极显著正相关.     

温室甜瓜营养生长期日蒸腾量估算模型

建立了基于温室环境参数、甜瓜生长发育参数和土壤水分参数的温室甜瓜日蒸腾量估算模型,以研究温室条件下甜瓜蒸腾量的估算方法.根据温室内特定环境对Penman-Monteith方程中空气动力项进行修正,推导出了适于计算温室条件下参考作物蒸腾量的温室环境因子子模型;以甜瓜叶面积指数为自变量构建了作物因子子模型,模型形式为线性函数;以土壤相对有效含水量为自变量构建了土壤水分因子子模型,模型形式为对数函数.采用分期播种法,根据周年不同播期实测数据对模型参数进行估计和分析.采用土壤相对含水量分别为80%、70%、60%的实测蒸腾数据,对模型在充分灌溉和节水灌溉条件下的预测精度进行了检验,模拟值的平均相对误差分别为11.5%、16.2%、16.9%.所建蒸腾模型是对Penman-Monteith公式在温室环境和节水灌溉条件下的有益探索,具有重要推广应用价值.     

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。     

不同空间尺度下的ALMANAC模型验证

ALMANAC模型最早作为EPIC模型的一部分,用于模拟土壤侵蚀导致的土地生产力的下降．它将试验数据的统计过程和作物生长的机理过程结合起来,是一种典型的基于过程模拟的应用型作物生长模型．如能在不同的空间尺度上验证模型的适用性,无疑会大大扩展模型的应用范围．从这一目的出发,利用美国得克萨斯州19个试验田和9个县的玉米和高粱产量资料及其相关的作物、土壤、田问管理等数据,模拟了1998年田间尺度,1989～1998年县级尺度的平均作物产量．模拟结果表明,ALMANAC模型能够很好地模拟两种不同空间尺度的作物产量,其相对误差在田问尺度上分别为8．9％(高粱)和9．4％(玉米),在县级尺度上分别达到2．6％(玉米)和—0．6％(高粱)．该模型在进行产量预测、掌握作物生长动态,指导农业生产管理和土地利用等方面具有很好的应用前景．     

油菜绿色面积指数动态模拟模型

准确模拟绿色面积指数是作物生长模拟模型可靠预测作物生长和产量的关键。该研究的目的是以生理生态过程为基础,构建油菜(Brassica napus)叶面积指数和角果面积指数变化动态的模拟模型。油菜叶面积指数模型综合考虑了库或源限制下的叶面积增长模式,其中库限制下叶面积指数的增长呈指数方程,且受到温度、水分和氮素因子的影响;源限制下叶面积指数增长用比叶面积法来模拟。油菜角果面积指数由比角果面积和角果干物重来决定。比叶面积和比角果面积均为生理发育时间的函数。利用不同类型品种的播期试验及氮肥试验资料分别对模型进行了校正和检验,结果表明模型能较好地模拟不同条件下油菜叶面积指数和角果面积指数。     

异迟眼蕈蚊在不同植物上的生长发育及种群参数

【目的】异迟眼蕈蚊Bradysia difformis Frey的幼虫取食为害作物的地下部分,影响作物的品质,为了明确韭菜、蚕豆、生菜、白菜和甘蓝5种植物对异迟眼蕈蚊生长发育以及繁殖的影响。【方法】本试验采用室内人工饲养测定的方法,研究了5种不同植物对异迟眼蕈蚊生长发育,繁殖力和存活率的影响,并统计了其对异迟眼蕈蚊种群参数的影响。【结果】结果表明:卵到蛹的发育历期依次为甘蓝、白菜、韭菜、生菜、蚕豆;5种植物对雌雄虫寿命影响不显著,对雌虫产卵量以及蛹重均有影响,其中在韭菜上的产卵量最大,甘蓝最少,在韭菜上蛹最重,生菜上蛹最轻;异迟眼蕈蚊的存活率随着生长发育降低,总体在韭菜上的存活率高于其他寄主植物,在生菜上的存活率均最低。统计分析不同植物对异迟眼蕈蚊种群参数的影响,净增殖率和内禀增长率在韭菜上最大而在甘蓝上最小;平均世代周期在蚕豆上最短,甘蓝上最长;种群加倍时间在韭菜上最短,而在甘蓝上最长。【结论】由此可知,异迟眼蕈蚊均可以在韭菜,蚕豆,生菜,白菜和甘蓝上完成生长发育及繁殖,其对5种植物的适应性依次为:韭菜、蚕豆、白菜、甘蓝和生菜。     

水稻生长动态模拟研究进展

在查阅了国内外水稻生长动态模拟研究领域大量献的基础上,主要就气候变化对水稻生长的影响的模拟,水稻生产潜力的估算,生育期预测,氮肥的优化管理,水稻群体质量指标的模拟与优化以及水稻干物质生产模拟等6个方面的研究动态进行了综述。提出了水稻生长动态模拟模型研究和应用中存在的建模方法,参数确定和生产应用等3个方面的问题,最后对该领域今后的攻关内容进行了探讨,认为进一步研制和完善包括营养元素,病虫害在内的,以作物生理生态为基础的水稻生产系统综合性模拟模型,充分利用以信息技术为主体的现代科学技术,组织全国范围的协作试验以建立水稻品种参数数据库和研制估算水稻品种参数的数学方法,将水稻生长动态模拟模型和专家系统结合,组建水稻生产优化管理决策支持系统,是提高水稻生长动态模拟模型实用性的关键。     

Evaluation of a Dynamic Simulation Model for Tomato Crop Growth and Development

A dynamic simulation model for tomato crop growth and development,TOMSIM, is evaluated. Potential crop growth and daily crop grossassimilation rate (P_gc,d) is computed by integration of leafassimilation rates over total crop leaf area throughout theday. Crop growth results fromP_gc,dminus maintenance respirationrate (R_m), multiplied by the conversion efficiency. Dry matterdistribution is simulated, based on the sink strength of theplant organs, which is quantified by their potential growthrate. Within the plant, individual fruit trusses and vegetativeunits (three leaves and stem internodes between two trusses)are distinguished. Sink strength of a truss or a vegetativeunit is described as a function of its developmental stage.In this paper, emphasis is on the interactions between the twosubmodels of, respectively, dry matter production and dry matterdistribution. Sensitivity analysis showed that global radiation,CO₂concentration, specific leaf area (SLA) and the developmentalstage of a vegetative unit at leaf pruning had a large influenceon crop growth rate, whereas temperature, number of fruits pertruss, sink strength of a vegetative unit and plant densitywere less important. Leaf area index (LAI) was very sensitiveto SLA and the developmental stage of a vegetative unit at leafpruning. Temperature did not influence the simulated R_m, asincreased respiration rate per unit of biomass at higher temperatureswas compensated by a decrease in biomass. The model was validatedfor four glasshouse experiments with plant density and fruitpruning treatments, and on data from two commercially growncrops. In general, measured and simulated crop growth ratesfrom 1 month after planting onwards agreed reasonably well,average overestimation being 12%. However, crop growth ratesin the first month after planting were overestimated by 52%on average. Final crop dry mass was overestimated by 0–31%,due to inaccurate simulation of LAI, resulting partly from inaccurateSLA prediction, which is especially important at low plant densityand in a young crop.Copyright 1999 Annals of Botany Company Crop growth, dry matter production, glasshouse, leaf area,Lycopersicon esculentum, partitioning, simulation model, tomato, TOMSIM.     

东北地区春玉米气候适宜度模型

农作物生长是一个连续的动态过程,因而作物生长的最适宜气象指标也是连续变化的.据此,本文提出作物生长日可利用降水量的推算方法和气象指标时间插值算法,构建了日尺度气候适宜度模型,利用东北地区农业气象站的多年玉米观测资料进行检验.结果表明： 模型计算的气候适宜度与株高、百粒重存在显著正相关;在春玉米营养生长期间,气候适宜度与株高的相关系数(R²)在0.58以上;春玉米生殖生长期间,气候适宜度与春玉米百粒重的R²在0.45以上.本文建立的日尺度气候适宜度模型能客观地反映营养生长阶段及生殖生长阶段作物与气候条件的相互作用关系.
     

Modelling crop growth and biomass partitioning to shoots and roots in relation to nitrogen and water availability,using a maximization principle

Many crop models relate the allocation of dry matter between shoots and roots exclusively to the crop development stage. Such models may not take into account the effects of changes in environment on allocation, unless the allocation parameters are altered. In this paper a crop model with a dynamic allocation parameter for dry matter between shoots and roots is described. The basis of the model is that a plant allocates dry matter such that its growth is maximized. Consequently, the demand and supply of carbon, nitrogen, and water is maintained in balance. This model supports the hypothesis that a functional equilibrium exists between shoots and roots.This paper explains the mathematical computation procedure of the crop model. Moreover, an analysis was made of the ability of a crop model to simulate plant dry matter production and allocation of dry matter between plant organs. The model was tested using data from a greenhouse experiment in which spring wheat (Triticum aestivum L.) was grown under different soil moisture and nitrogen (N) levels.Generally, the model simulations agreed well with data recorded for total plant dry matter. For validation data the coefficient of determination (r²) between simulated and measured shoot dry weight was 0.96. For the validation treatments r² was slightly lower, 0.94. In addition to dry matter production the model succeeded satisfactorily in simulating the dry weight of different plant organs. The response of simulated root to shoot ratio to the level of soil moisture was mainly in accordance with the measured data. In contrast, the simulated ratio seemed to be insensitive to the changes in the levels soil N concentration used in the experiment.The data used in the present study were not extensive, and more data are needed to validate the model. However, the results showed that the model responses to the changes in soil N and water level were realistic and mostly agreed with the data. Thus, we suggest that the model and the method employed to allocate dry matter between roots and shoots are useful when modelling the growth of crops under N and water limited conditions.     

计算机模拟渍水时期及持续时间对春玉米生产及产量的影响

借助田间、水槽试验的结果结合Penning de Vries的MACROS模型建立玉米生长发育与水分动态耦合的模拟模型,通过验证后用于模拟不同渍水时期及持续时间对春玉米生长及产量影响的动态,模拟结果表明在田间全程控制水分为田间持水量90％以下,春玉米孕穗期为渍水危害的敏感期,其次为4－6叶期,在自然降水及土壤状况影响下,春玉米幼苗期4－6叶时为渍水的敏感期,8叶及孕穗期相对较耐渍,在玉米4、6叶期时,渍害造成产量下降的临界期为5天;而在8叶、孕穗期为10－15天,但持续20天的渍水对任何时期的春玉米生长都造成严重的影响,因此在生产中应注意在苗期及孕穗期及时排除田间多余的水分及降低地下水位。     

基于GIS的黄土丘陵沟壑区作物生产潜力模拟研究

从YIELD模型的来源、输入文件及基本参数,模型中作物生产力计算各个子模型以及计算流程4个方面作了简单的叙述,以黄土丘陵沟壑区典型小流域晋西狼窝沟为例,在地理信息系统（GIS）技术十,应用YILD模型对该流域的作物生产潜力进行了模拟,并从作物类型,地类,耕作措施及气候条件4个方面对影响该流域作物产量的因素进行了分析。结果表明,该模型对不同作物的模拟产量在总体上与实体产量基本相符合,表明模型可以应用于黄土丘陵沟壑区的作物产量模拟之中,对于不同地类来说,坝地的土壤水分和以力条件明显高于梯田和坡耕地,因而坝地的模拟产量地高于梯田和坡地,但三者之间的差距没有实测产量显著,耕作措施是提高作物生产力的有效途径,对地膜覆盖,梯田以及施肥等耕作措施的模拟产量表明,这3种耕作措施均能有效的物生产力;其产量提高率均平均在85％以上,其中以施肥对作物的增产作用最大,增产率高达95％,,这与实测产量资料基本一致;气候条件是影响作物生产的直接因素,模拟结果表明模型对降水量和温度等气候条件十分敏感,不同年份降水量和温度的差异将直接导致作物生产力的显著不同。对YIELD模型的模拟结果分析表明,该模型可以有效地应用于黄土丘陵沟壑区的作物生产潜力研究。     

Dry Matter Production in a Tomato Crop: Measurements and Simulation

Simulation of dry matter production by the explanatory glasshousecrop growth model SUKAM (Gijzen, 1992, Simulation Monographs),based on SUCROS87 (Spitters, Van Keulen and Van Kraalingen,1989, Simulation and systems management in crop protection),was validated for tomato. In the model, assimilation rates arecalculated separately for shaded and sunlit leaf area at differentcumulative leaf area in the canopy, taking into account thedifferent interception of direct and diffuse components of light.Daily crop gross assimilation rate (P_gd) is computed by integrationof these rates over total crop leaf area and over the day. Leafphotochemical efficiency and potential gross assimilation rateat saturating light depend on temperature and CO₂ concentrationand are approximated as being identical in the whole canopy.Crop growth results from P_gd minus maintenance respiration rate(R_m; dependent on temperature and crop dry weight), multipliedby the conversion efficiency (carbohydrates to structural drymatter; C_f). Growth experiments (periodic destructive harvest) with differentplanting dates and plant densities and two data-sets from commerciallygrown crops, were used for model validation. Hourly averagesfor global radiation outside the glasshouse, glasshouse temperatureand CO₂ concentration, together with measured leaf area index,dry matter distribution (for calculation of C_f) and organ dryweights (for calculation of R_m) were the inputs to the model. Dry matter production (both level and dynamic behaviour) wassimulated reasonably well for most experiments, but final drymatter production was under-estimated by about 27% for the commerciallygrown crops. At low irradiance and with large crop dry weight,growth rate was under-estimated, probably as a result of over-estimationof R_m. This could almost completely explain the large under-estimationfor the commercially grown crops, which had large dry weight.Final dry matter production was over-estimated by 7-11% if dailyaverages instead of hourly input of climatic data were used. It is concluded that SUKAM is a reliable model for simulatingdry matter production in a tomato crop, except for those situationswhere R_m has a large influence on crop growth rate (low irradianceand large crop dry weight). An improved estimate of R_m wouldtake into account the influence of metabolic activity. A preliminaryattempt to relate maintenance costs to relative growth rate(a measure for metabolic activity), showed promising results.Copyright1995, 1999 Academic Press Crop growth, dry matter production, glasshouse, maintenance respiration, metabolic activity, model, relative growth rate, respiration, simulation, tomato, model validation     

The GP problem: quantifying gene-to-phenotype relationships

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.     

物候模式识别在生态动力预报中的应用

以物候资料和数值天气预报模式输出图为基础,应用模式识别和数理逻辑判断的自动化技术,阐述制作生态动力预报的原理、方法和步骤.生态动力预报技术使传统的物候学在气象学和自动化技术支持下,扩展应用到生态预报业务领域,使物候预报从单站预报阶段发展到区域预报阶段,同时促进了农业气象预报方法从定性、统计阶段向动力预报阶段发展.该方法在农作物播种、长势、灌溉与施肥、病虫害防治等方面具有广阔的应用前景.     

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。