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.