Linking icon-based models to code-based models: a case study with the agricultural production systems simulator

The traditional code-based modelling approach in agriculture and ecology has many strengths, particularly in terms of model flexibility, efficiency and power. Nonetheless code-based programming is a specialist skill and a barrier to simulation modelling to most scientists and students. Icon-based modelling systems on the other hand are easy to use and learn and have opened up simulation modelling to a much broader group of researchers. However there are limitations to the flexibility of these modelling systems and sometimes the size and complexity of models that can be constructed in them.One approach by which researchers can gain the best of both types of models is by linking icon-based models to code-based models within a modular modelling framework. By developing largely self-contained modules that communicate with other modules solely by means of defined input/output variables, modules can be developed in an easy to use icon-based modelling system and subsequently `plugged in' to a larger code-based model. In this paper, we demonstrate this approach using Vensim^TM to develop a new seed bank module for the Agricultural Production Systems Simulator (APSIM). In an example application we compare the persistence of two hypothetical annual pasture plants with differing life histories under two contrasting farming systems.This approach has the benefits of: (i) rapid and efficient model development that allows specialist scientists and programmers to focus on their respective areas of expertise; (ii) ongoing maintenance and development of modules by science specialists without need for constant recourse to programmers; (iii) ease of sharing, exchange and comparison of icon-based modules between researchers; and, (iv) ease of communication of model structure.     

An international collaborative network for agricultural systems applications (ICASA)

In the 1970s and 1980s much progress has been made in studying agricultural production systems by using simulation modelling of agronomic processes. The International Benchwork Sites Network for Agrotechnology Transfer (IBSNAT) group in the USA and the group around Professor Kees De Wit in Wageningen were active in this new area of research which created an important ‘niche’ within the agricultural sciences because of its integrative, interdisciplinary character and its focus on quantitative, process-based approaches. A first joint scientific meeting of the two groups was held in Bangkok in 1991 (SAAD1 conference: Systems Analysis for Agricultural Development). At the SAAD2 conference at IRRI in 1995, in which also other groups took part, notably the Agricultural Production Systems Research Unit (APSRU) group from Australia, the International Consortium for Agricultural Systems Applications (ICASA) was established as a forum for researchers engaged in the study of agricultural systems at different spatial scales ranging from fields, farms to regions and beyond. The ICASA is an informal network with a focus on three major activities: (1) sharing experiences and joint development of compatible software allowing more widespread use of models having been developed by various member groups; (2) organization of joint courses on different aspects of dynamic modelling of agricultural production systems. There is an increasing interest in such courses, also in developing countries, and local researchers increasingly take an active part in them; and (3) joint research on projects dealing with dynamic characterization of agronomic production systems at different spatial scales. ICASA researchers take part in eco-regional methodology development, through projects that are funded by the Dutch and Swiss governments, with ISNAR acting as the administrative agency. ICASA intends to be an effective platform on which researchers, stakeholders and policy makers can interact.     

Agronomic data: advances in documentation and protocols for exchange and use

Data from agronomy experiments are typically collected and stored in a number of minimally documented computer files, with additional information being entered and archived in field books or diaries. Data manipulation is generally cumbersome and error-prone, and data loss is frequent. Modern database technology has the potential to resolve these issues. However, experience gained by an international network of experimenters and crop modellers (the International Benchmark Sites Network for Agrotechnology Transfer; IBSNAT) in using a database for agronomic experiments conducted by many workers at different sites highlighted problems of data entry, quality control, and changing requirements for storage and output variables. In an attempt to minimize these problems, IBSNAT reduced its focus on a central database, but considerably enhanced its effort on the design and use of a set of simple, standard experiment documentation and results files that could be established and edited easily, transferred directly among workers, used as inputs to analytical software and crop models, and read by database and spreadsheet software. The standard files which were developed, and which were used in a software package termed DSSAT V3, have recently been upgraded by a consortium of experimenters and modellers (the International Consortium for Agricultural Systems Applications; ICASA). These new files are described briefly here. The ICASA files constitute an advance in the potential for good documentation and storage of agronomic data, but only partly solve the problem of overall data management and use. There is still need for central and local databases that facilitate both the searching of information from different experiments, and the examination of relationships that may be apparent in a large array of data. A number of such databases have been developed for specific applications, and a few of these are briefly touched upon. In particular, recent work with one large database currently being developed by a number of international Agricultural Research Centers, National Research Organizations, and Universities, (the International Crop Information System, ICIS), is briefly described.     

模块化数控编程在复杂零件中的应用

编程人员在进行手工编程时,遇到复杂零件往往无从下手,用常规的编程方法进行编程,数值计算相当繁琐,工作量大,很容易出错,且程序很难校对.针对此类问题,本文提出了一种模块化数控编程,并以一薄壁零件为例对模块化数控编程在复杂零件中的应用进行了探讨和阐述.在进行模块化编程时,首先对复杂零件进行分析,确定加工工艺过程,之后对零件进行模块化分析,将零件分成若干个模块,分别对每个模块进行编程,通过分析可以发现模块化编程省时快速,不容易出错,且程序容易校对,极大地提高了编程效率.     

Development and evaluation of an integrated simulation model for assessing smallholder crop-livestock production in Yucatán, Mexico

Mixed farming systems constitute a large proportion of agricultural production in the tropics, and provide multiple benefits for the world’s poor. However, our understanding of the functioning of these systems is limited. Modeling offers the best approach to quantify outcomes from many interacting causal variables in these systems. The objective of this study was to develop an integrated crop-livestock model to assess biophysical and economic consequences of farming practices exhibited in sheep systems of Yucatán state, Mexico. A Vensim™ dynamic stock-flow feedback model was developed to integrate scientific and practical knowledge of management, flock dynamics, sheep production, partitioning of nutrients, labor, and economic components. The model accesses sheep production and manure quantity and quality data generated using the Small Ruminant Nutrition System (SRNS), and interfaces on a daily basis with an Agricultural Production Systems Simulator (APSIM) model that simulates weather, crop, and soil dynamics. Model evaluation indicated that the integrated model adequately represents the complex interactions that occur between farmers, crops, and livestock.     

基于ECAS控制的模块式车辆空气悬架高度控制系统的设计与仿真

以ECAS为基础,以WABCO4728800010两位三通电磁阀和Freescale的MC9S12D64微处理器为核心元器件,开发了一种模块式的空气悬架高度控制系统,并在matlab/simulink环境下进行了仿真验证。该系统的高度控制策略分为启动控制模块、动态调节模块、手动调节模块以及误差调节模块,由模式选择开关来决定不同模块的工作状态,逻辑控制准确、调试方便。模块式的设计大幅降低了系统的复杂程度,同时也将降低软件的开发周期和成本。     

Systems approaches for the design of sustainable agro-ecosystems

The complexity of agricultural systems and the need to fulfil multiple objectives in sustainable agro-ecosystems call for interdisciplinary analyzes and input from a wide variety of disciplines in order to better understand the complete agronomic production system. Systems approaches have been developed to support these interdisciplinary studies; their development and use have increased strongly in the past decades. Agronomic systems have pronounced spatial and temporal dimensions. Spatial aspects can be distinguished at crop, field, farm, regional and higher levels while processes at each spatial level have characteristic temporal components. Systems analysis in agronomic systems implies the use of various types of knowledge, such as expert knowledge including stakeholder expertise and knowledge derived from scientific measurements and model-simulations. The latter two can be derived from different types of studies: simple, rapid and cheap procedures, which are often relatively unreliable, at one end of the scale and complex, cumbersome and expensive data-intensive procedures at the other end. Selection of proper procedures for specific issues, both in terms of measurements and in applying simulation models, needs attention. Each problem requires its own research approach. Based on the output requirements and data availability, the proper systems approach has to be selected. Examples of these different procedures are given in this paper. Considering the type of problems to be studied in agronomic systems, different procedures can be followed to address the issues raised at a specific scale. These procedures start with a proper analysis of the system followed by studies that are projectory, exploratory, predictive, or are focused on decision support. Examples will be provided. Increasingly, systems approaches include stakeholders to fine-tune problem definition, the research itself, and the implementation of results. Stakeholders are farmers and citizens on farm and community levels and policy makers and planners at higher levels of aggregation. A comprehensive interdisciplinary analysis of agricultural production systems is seen as a necessary condition for the development of innovative, sustainable systems for the future. Systems for improving crop production systems are presented in this paper as well as applications of systems approaches at the farm and regional levels with emphasis on selecting the right approach.     

Estimating deep drainage and nitrate leaching from the root zone under sugarcane using APSIM-SWIM

The Burdekin Delta (BD) is located on the dry-tropical coastal strip in North Queensland, Australia. It is one of Australia's premier sugar producing districts with approximately 40,000 ha of land under sugarcane. Because the BD borders the Great Barrier Reef World Heritage Area (GBRWHA), industry, community, regulatory, and environmental organisations are interested in ascertaining the magnitude of deep drainage and nitrate leaching from the root zone and potential implications for the GBRWHA.Direct measurement of deep drainage and nitrate leaching is difficult, and modelling is likely to play an ever-increasing role in guiding experimental work and decision-making. Here, we describe the collection of drainage and nitrate-leaching related data collected over two cropping seasons at a specific field site within the BD and its use in the calibration and application of a drainage and nitrate-leaching model created within the Agricultural Production Systems Simulator (APSIM) modelling framework with constituent crop-growth, soil–water, and nitrogen transformation modules (Sugar, APSIM-SWIM, Soiln2).Model application indicated that the simulated amount of drainage and nitrate leached over a cropping season compared favourably to that derived from inferred drainage and observed soil–water nitrate concentrations. Subsequent investigation of fertilizer management options using the model identified the timing and amount of both irrigation and fertilizer application as key parameters over which management control might be exploited to minimise deep drainage and flux of nitrate to groundwater.     

基于F-B-S模型的SAM产品可重构模块设计

提出了一种小型农业作业机(SAM)产品可重构模块开发的新方法,将公理化设计技术(AD)应用于产品模块设计过程中,针对模块功能分解进行了F-B-S模型的构建和分析,以SAM产品核心模块变速箱为实例,进行了公理化设计和可重构模块的F-B-S模型验证。结果证明上述设计方法在SAM可重构模块开发中能实现模块的快速设计和重组,为产品的快速设计和建立SAM产品可重构模块资源提供了一种开发方法。     

Simulation of the soil-water dynamics and corn yields under deficit irrigation

Summary A simulation model capable of predicting the yield response of corn to a limited water supply was developed by combining two existing mathematical models. The resulting computer model was evaluated using experimental data taken under a wide range of soil moisture conditions. The soil profile water balances was simulated using SWATRE and SUCROS was used to model the crop growth in response to environmental conditions. In addition to the integration of the two existing models, some minor changes were made to each in an effort to improve the accuracy of the combined models. The model input parameters were derived entirely from published literature. The experimental data necessary for model validation were available from irrigation studies at the Sandhills Agricultural Laboratory of the University of Nebraska. These experiments not only provided the required input soil and climatic data, but also the observed irrigation levels, soil moisture distributions and crop yield required for model validation. Initial evaluation of the computer model indicates that the combined model adequately describes crop evapotranspiration, soil moisture extraction and crop yield under a fairly wide range of soil moisture stress. Additional modifications for the prediction of leaf area expansion and senescence, especially under moisture stress, are needed to improve the accuracy of the model.     

Integrated decision making for reservoir,irrigation, and crop management

An integrated approach to reservoir, irrigation, and cropping management which links four different models—a hydrologic model (PRMS), a crop growth simulation model (EPIC), an economic model based on linear programming, and a dynamic programming model—is developed and demonstrated. The demonstration is based on an irrigation district located in a subhumid climate with an irrigation reservoir large enough for over-year storage. The model is used to make repeated simulations for various planning horizons. Two different types of results are presented. The first provides the probability that each of the various farm plans (land/crop/water allocation) will be chosen as the optimum in the first year of the planning horizon. The second approach provides probability distributions of accumulated revenues over a chosen length of planning horizon. Each distribution is associated with an initial reservoir level and a particular farm plan in the first year of the planning horizon. The consequence of selecting certain farm plans at the beginning of a specified planning horizon is therefore quantified in a probabilistic way. Based on families of probability–revenue curves, an irrigation manager can simultaneously evaluate crop, irrigation, and reservoir management options.     

Modelling multiple objectives of land use for sustainable development

Sustainability is a human-centred concept that comprises multiple aspects and objectives of different interest groups. Sustainable development is not readily measurable, except as a compromise between different parts of society, of which some may try to represent future generations of mankind. To determine a sustainable development path in the relationship between agriculture and its natural environment, a profound knowledge of this complex system and its behaviour under different socio-economic conditions is necessary. We present a modelling system which consists of a set of hierarchically linked modules. These modules describe production activities in a way that allows an economic and ecological analysis of these techniques. The heart of the modelling system is a multiple goal linear programming model, which is generated by data base modules. Simulation of single farm models as well as regional models based on simultaneously optimised farm types is possible. The modelling system appears to be a highly flexible tool with respect to the number and type of farms, sites and production techniques. Environmental objectives can easily be included and different levels of goal achievement can be simulated. It is well suited for single farm analysis as well as for regional models, for static as well as dynamic approaches. It allows rapid adoption of the model and rapid calculation of scenarios. Therefore, it is suited for use in interactive environments with users which are interested in repeated runs with little changes in the goal function, prices, subsidies or technical coefficients. The results can be used for policy decisions as well as the strategic planning of individual farmers. Applications of the modelling system will be presented in following papers. In this paper the kind of information the model can generate and the circumstances of their usage are shown. ©     

宁波市农业节水区划中模糊聚类分析与应用

农业节水区划是农业水资源高效利用规划和实施的重要依据。根据宁波市自然与社会情况,选取地貌形态、土壤类型、农业结构、缺水程度等指标组成农业节水分区指标体系,并建立相应评判标准,专家评议确定各项指标权重。采用模糊聚类方法,将宁波市划分5大类型区,针对各类型区特点提出相应的农业节水措施,用于指导农业灌溉和生产。     

Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain

In the North China Plain (NCP), while irrigation using groundwater has maintained a high-level crop productivity of the wheat-maize double cropping systems, it has resulted in rapid depletion of groundwater table. For more efficient and sustainable utilization of the limited water resources, improved understanding of how crop productivity and water balance components respond to climate variations and irrigation is essential. This paper investigates such responses using a modelling approach. The farming systems model APSIM (Agricultural Production Systems Simulator) was first calibrated and validated using 3 years of experimental data. The validated model was then applied to simulate crop yield and field water balance of the wheat-maize rotation in the NCP. Simulated dryland crop yield ranged from 0 to 4.5 t ha⁻¹ for wheat and 0 to 5.0 t ha⁻¹ for maize. Increasing irrigation amount led to increased crop yield, but irrigation required to obtain maximum water productivity (WP) was much less than that required to obtain maximum crop yield. To meet crop water demand, a wide range of irrigation water supply would be needed due to the inter-annual climate variations. The range was simulated to be 140-420 mm for wheat, and 0-170 mm for maize. Such levels of irrigation applications could potentially lead to about 1.5 m year⁻¹ decline in groundwater table when other sources of groundwater recharge were not considered. To achieve maximum WP, one, two and three irrigations (i.e., 70, 150 and 200 mm season⁻¹) were recommended for wheat in wet, medium and dry seasons, respectively. For maize, one irrigation and two irrigations (i.e., 60 and 110 mm season⁻¹) were recommended in medium and dry seasons, while no irrigation was needed in wet season.     

作物生长模型研究现状与展望

作物生长模型由最初的作物生长发育模型发展到农业决策支持模型,在科学研究、农业管理、政策制定等方面发挥着越来越重要的作用。本文首先回顾了作物生长模型的发展过程,并按照模型主要驱动因子,将作物生长模型分为土壤因子、光合作用因子和人为因子驱动3类并分别进行了归纳阐述;然后对典型的模型分别从模型模块、时空尺度、可模拟的作物类型等方面进行列表式对比;并对作物生长模型在气候变化评估、生产管理决策支持、资源管理优化等方面的应用,以及面临的极端条件、复杂农业景观和模型复杂度等挑战进行了总结,在此基础上认为遥感数据同化和孪生农场是其发展方向。     

基于接口的小型农业作业机模块划分方法

产品模块化设计时模块划分的合理性直接影响实现大规模定制生产的效果。提出了一种通过接口关系进行模块划分的方法,将零件接口关系用模糊隶属度函数进行定量化描述,在模糊图上通过割集的方法实现模块的合理划分。以SF5系列小型农业作业机产品为例,通过模块化设计将不同模块进行组合,可满足农林牧多行业用户的功能需求。     

DéciBlé, a software package for wheat crop management simulation

DéciBlé is a simulation tool intended to support the design and evaluation of technical management for the wheat crop. Crop management is here considered from a strategic planning point of view, as the choice of technical decision rules for the whole growing period rather than day-by-day decisions for each operation. DéciBlé simulates the consequences for technical operations and crop production of a set of decision rules over a wide range of possible contexts (regions, year-to-year weather variation, fields, etc.). It is a simulation in which two models interact: a decision and a crop model. The decision model represents the decision rules through a specific formalisation and generates the operations for each context. The crop model is a set of modules simulating plant development, crop environment and yield accumulation implied by these operations in this context through the generation of loss functions or risk estimates. The crop model consists of a set of empirical models based on agronomic diagnosis and experimental references widely used in France. A general validation of DéciBlé is carried out using observed data from a network of field trials. The wheat development stages are simulated within 4 days of the observed dates in more than 80% of the cases and the yield components and final yield with differences of less than 15% from the real values in more than 75% of the cases. We discuss (i) the causes of unsatisfactory predictions and the prospects for improving the various modules of the crop model; (ii) the use of the simulator in some decision problems; and (iii) the position of DéciBlé among the existing models for crop management decision help, emphasising the originality of the method of decision representation.     

APSIM's water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems

APSIM (Agricultural Production Systems Simulator) is a software system which provides a flexible structure for the simulation of climatic and soil management effects on growth of crops in farming systems and changes in the soil resource. The focus of this paper is the predictive performance of APSIM for simulation of soil water and nitrate nitrogen in contrasting soils (vertisols and alfisols) and environments. The three APSIM modules that determine the dynamics of water, carbon, and nitrogen in the soil system (viz. SOILWAT, SOILN and RESIDUE v.1) are described in terms of the processes represented, with particular emphasis on aspects of their coding that differ from their precursors in CERES and PERFECT. The most fundamental change is in SOILN, which now provides a formal balance of both carbon and nitrogen in the soil and includes a labile soil organic matter pool that decomposes more rapidly than the bulk of the soil organic matter. Model performance, in terms of prediction of soil water and nitrate, is evaluated during fallows, thereby avoiding complications arising from water use and nitrogen uptake by a crop. One data set is from a long-term experiment on a vertisol in southeast Queensland which studied two tillage treatments (conventional and zero tillage) in combination with fertiliser nitrogen inputs for the growth of wheat; soil water and nitrate were measured twice each year (pre-planting and post-harvest). The second comes from experiments at Katherine, Northern Territory, where legume leys growing on alfisols were chemically killed and ensuing changes in soil water and nitrate were measured during a single season. For both datasets, the predictive ability of the model was satisfactory for water and nitrate, in terms of both the total amounts in the whole profile and their distribution with depth. Since neither of these datasets included measurements of the runoff component of the water balance, this aspect of model performance was evaluated, and shown to be generally good, using data from a third source where runoff had been measured from contour bay catchments.     

农业模型发展分析及应用案例

农业模型、农业人工智能及数据分析等技术贯穿于智慧农业的信息感知、信息传输、信息处理与控制全过程,是智慧农业的核心技术。为进一步明晰农业模型的内涵和作用,促进农业模型进一步研究及应用,推动智慧农业健康、稳定和可持续发展,本研究采用系统分析、比较及关系框图等方法,分析了农业模型的内涵,阐述了农业模型和智慧农业要素与过程的关系,明确了农业模型的作用并附以应用案例,比较了农业模型的国内外重要发展动态与趋势。国内外农业模型研究与应用重要进展比较表明,农业模型研究应用需要考虑农业生物要素的4个水平、农业环境要素的6个尺度、农业技术与农业经济要素的6个层次并采用相应方法进行,农业模型环境要素空间多尺度研究应用有较大发展潜力;农业模型与分子遗传学、感知技术及人工智能技术结合,农业模型研究应用的公私有组织协作,粮食安全挑战将成为农业模型进一步发展的重要推动力,且需更注重将各种农业系统模拟、数据库、和谐性与开放数据及决策支持系统相连接。中国农业模型研究与应用已形成具有中国特色的作物模型系列,也融入农业模型的互比较与改进、智慧农业等世界潮流,需要抢抓机遇,加快发展。农业模型是农业系统要素内及要素间关系的定量化表达,是农业科学定量与综合的重要方法,具有认识论价值,它与感知技术的结合可以在智慧农业数据获取与处理中发挥不可或缺的作用,成为信息农业技术落地应用的重要桥梁和纽带。     

基于LabVIEW的氢燃料发动机检测系统开发

基于LabVIEW虚拟技术开发了一套氢发动机检测系统。整个系统采用自顶向下的模块化编程方式,由传感器信号检测、信号处理、信号模拟、模拟示波器和帮助文档等五大功能模块组成。它可对发动机的转速、气缸压力、发动机温度等工况参数进行检测,并完成数据的采集,信号的分析、处理、显示和存储等功能。以气缸压力传感器模块为例对系统的设计进行了介绍。