作物生长模拟模型的开发应用进展

论述了作物生长模拟模型的开发研究进展和模型的应用情况，并对作物生长模拟模型今后的研究提出了自己的见解。     

作物生长模拟模型的开发应用进展

论述了作物生长模拟模型的开发研究进展和模型的应用情况，并对作物生长模拟模型今后的研究提出了自己的见解     

作物模拟模型的研究概况及展望

作物生长模拟是一门新兴的边缘学科,通过对作物生育规律的定量分析,有助于理解、预测和调控作物生长发育及其与环境的关系.概述了模型研究的目的、意义、特征及起源;详细论述了模型研究的发展历程、研究的特点及现状,并指出了现有模型的优点及缺陷;最后对作物模拟的应用前景和发展趋势作了展望.     

基于作物模型的计算机模拟软件研究

基于作物模型的计算机模拟软件是数字农业中实现农业信息化的重要基础。该文系统介绍了作物模型及作物模拟的概念,作物生长模拟技术的产生和发展,并对模拟软件的研发过程中涉及的关键技术进行阐述,指出模拟软件在农业生产和科研中的应用。     

作物生产系统的模拟模型研究进展

本文阐述了作物生产系统的概念,作物模拟研究的当前水平及广阔的应用前景,特别讨论了在我国的发展及其特色.     

作物生长发育过程的计算机模拟决策研究概述

种植业是农业的基础产业 ,作物生长发育过程的计算机模拟决策研究是种植智能化、数字化与精确化的桥梁与纽带。本文对作物计算机模型的定义、模型分类、产生和发展、应用及意义等进行了概述。作物模拟技术经历了初创、发展及完善与成熟阶段。作物模拟研究的作用主要有解释作物生长过程的机理、预测及调控指导 3个方面 ,其目的主要有定量关系、综合知识、检验假设、进行模拟、支持决策与教学及连接其它模型等 ,其意义主要表现在为人们提供了新的认知工具 ,使作物生产决策向动态、定量、目标与优化方向发展 ,实现智能化与精确化管理 ,推动农业信息化与可持续发展     

作物模拟中的常年气候数据生成子系统

以前人工作为基础，建立了常年逐日气温（包括平均，极端最高和最低气温），日照时数，降雨量，太阳辐射等气象要素的生成模型。并对降雨量和太阳辐射模型进行了改进，取得满意效果。采用VB6.0作为系统开发工具，研制成基于Windows操作平台的作物模拟中的常年气候数据生成了系统，利用南京40年和郑州30年的历史气候资料，分别对该系统进行检验。模拟值与实际情况相符，相关系数分别为0.93和0.89。     

大豆叶片生长特征的动态模拟研究

选择特定的大豆品种,在大豆种植过程中,采集叶片的生长信息,主要包括叶片的长出时间、单株叶片长、宽、叶柄长、叶面积变化等。对上述数据进行数学分析,获取叶片生长过程中其形态的变化规律,从而提出了大豆叶片生长过程的模拟方法。     

棘皮动物体内防御机制的研究进展

概述了棘皮动物体内防御机制的研究进展。棘皮动物体内具有识别不同异物的机制,体腔细胞具有吞噬、捕捉、包囊入侵外来微生物等多种功能,并介导棘皮动物有效的细胞免疫机制。棘皮动物在捕捉细菌、排出细胞物质、裂解颗粒细胞等过程中能够激活细胞的包囊反应。棘皮动物血淋巴中的溶菌酶、溶血素、类补体及凝集素等因子共同参与机体免疫反应,而感染反应能够诱导细胞因子的产生。体液免疫反应是棘皮动物抵抗微生物入侵的主要防御反应。     

棘皮动物体内防御机制的研究进展

概述了棘皮动物体内防御机制的研究进展。棘皮动物体内具有识别不同异物的机制,体腔细胞具有吞噬、捕捉、包囊入侵外来微生物等多种功能,并介导棘皮动物有效的细胞免疫机制。棘皮动物在捕捉细菌、排出细胞物质、裂解颗粒细胞等过程中能够激活细胞的包囊反应。棘皮动物血淋巴中的溶菌酶、溶血素、类补体及凝集素等因子共同参与机体免疫反应,而感染反应能够诱导细胞因子的产生。体液免疫反应是棘皮动物抵抗微生物入侵的主要防御反应。     

基于遥感反演作物冠层温度的作物生长模拟和预报

利用作物冠气温差可以计算作物生长水分胁迫系数.用遥感信息估算作物冠层温度并且利用气象站的气温资料,通过冠气温差计算作物水分胁迫系数,并引入作物生长模拟模型,就实现动态和连续的作物监测及预报作物产量.本文对建立遥感-作物模拟复合模型的基本原理进行了探讨,并提出建立遥感-作物模拟复合模型所涉及的计算方法,但整体研究方法还有待进一步的验证.     

Integrating remote sensing information with crop model to monitor wheat growth and yield based on simulation zone partitioning

Research into crop growth models at the spatial scale is of great significance for evaluating crop growth, predicting grain yield and studying global climate change. Coupling spatial remote sensing (RS) data can effectively promote the simulation of growth models at spatial scales. However, the integration of RS data and crop models to produce a coupled model based on pixel by pixel requires a large amount of calculations. Simulation zone partitioning is used to separate and cluster the large area into a few relatively uniform zones. Then, the growth model can run on the basis of these units. This method both reflects spatial heterogeneity and avoids repeated simulations of regions with similar attributes, improving the simulation efficiency. In this study, simulation partitioning was performed using soil nutrient indices (organic matter content, total nitrogen content and available potassium content) and corresponding spatial characteristics of wheat growth, as indicated by RS data. A coupled model, integrating RS information and the WheatGrow model, using vegetation indices as the coupling parameters (based on the Particle Swarm Optimization algorithm and PROSAIL model), was developed. The aim was to realize accurate prediction of wheat growth parameters and grain yield at the spatial scale. Good zone partitions were obtained by partitioning with the spatial combination of soil nutrient indices and the wheat canopy vegetation index, calculated during the main growth (jointing, heading and filling) stages. The variation coefficients of each index within individual simulation sub-zones were much smaller than those of the indices across the whole area. An analysis of variance showed that the indices were significantly different between the simulation sub-zones, which indicated that appropriate simulated sub-zones had been defined. The minimum root mean square error of the leaf area index, leaf nitrogen accumulation and yield between the predicted values and the values simulated by the coupled model were 0.92, 1.12 g m^?2, and 409.70 kg ha^?1, respectively, which were obtained when the soil-adjusted vegetation index was used as a partitioning zone and assimilating parameter. These results demonstrated that the coupled model of the crop model and RS data, based on the simulation sub-zones had a good prediction accuracy. The results provide important technical support for increasing model efficiency, when crop models need to be applied at the spatial scale.     

西藏发展复种潜力研究

本文从影响西藏复种的自然条件、耕地潜力、历史与传统和技术措施等三个方面对西藏发展复种的潜力进行了分析研究,并论述了复种对西藏农业的重要性、必要性和对三农的意义。指出西藏发展复种所需的海拔、水热等资源条件,适宜发展复种的地区及技术关键。     

Frontiers in crop production: chemical research objectives

The science of chemistry and chemicals will continue to be an integral part of future crop production technologies. In assessing and defining the future role of chemistry three imperatives must be considered: (i) the necessity to preserve natural resources, (ii) the complementary solutions offered by the rapidly advancing biological sciences, and (iii) the specific requirements of developing regions where increasing crop productivity is most important. Chemical research objectives for improving crop protection and crop growth must take into account the perceivable and potential changes in crop production techniques, which, in turn, are dictated by a number of accentuating constraints.