CropSyst, a cropping systems simulation model

CropSyst is a multi-year, multi-crop, daily time step cropping systems simulation model developed to serve as an analytical tool to study the effect of climate, soils, and management on cropping systems productivity and the environment. CropSyst simulates the soil water and nitrogen budgets, crop growth and development, crop yield, residue production and decomposition, soil erosion by water, and salinity. The development of CropSyst started in the early 1990s, evolving to a suite of programs including a cropping systems simulator (CropSyst), a weather generator (ClimGen), GIS-CropSyst cooperator program (ArcCS), a watershed model (CropSyst Watershed), and several miscellaneous utility programs. CropSyst and associated programs can be downloaded free of charge over the Internet. One key feature of CropSyst is the implementation of a generic crop simulator that enables the simulation of both yearly and multi-year crops and crop rotations via a single set of parameters. Simulations can last a fraction of a year to hundreds of years. The model has been evaluated in many world locations by comparing model estimates to data collected in field experiments. CropSyst has been applied to perform risk and economic analyses of scenarios involving different cropping systems, management options, and soil and climatic conditions. An extensive list of references related to model development, evaluation, and application is provided.     

An overview of the crop model

is a model that has been developed at INRA (France) since 1996. It simulates crop growth as well as soil water and nitrogen balances driven by daily climatic data. It calculates both agricultural variables (yield, input consumption) and environmental variables (water and nitrogen losses). From a conceptual point of view, relies essentially on well-known relationships or on simplifications of existing models. One of the key elements of is its adaptability to various crops. This is achieved by the use of generic parameters relevant for most crops and on options in the model formalisations concerning both physiology and management, that have to be chosen for each crop. All the users of the model form a group that participates in making the model and the software evolve, because is not a fixed model but rather an interactive modelling platform. This article presents version 5.0 by giving details on the model formalisations concerning shoot ecophysiology, soil functioning in interaction with roots, and relationships between crop management and the soil–crop system. The data required to run the model relate to climate, soil (water and nitrogen initial profiles and permanent soil features) and crop management. The species and varietal parameters are provided by the specialists of each species. The data required to validate the model relate to the agronomic or environmental outputs at the end of the cropping season. Some examples of validation and application are given, demonstrating the generality of the model and its ability to adapt to a wide range of agro-environmental issues. Finally, the conceptual limits of the model are discussed.     

基于APSIM模型模拟水氮调控对旱地春小麦(Triticum aestivum)叶面积的影响

本研究针对水氮调控对旱地春小麦(‘定西42号’)叶面积的影响,采用大田试验数据与农业生产系统模型(agricultural production system simulator, APSIM)的结合,分别设定不同降水和施氮梯度对叶面积的变化趋势进行研究,试验获取2015-2017年定西田间试验不同水氮肥施入的试验数据,并对模型予以检验。APSIM模型对叶面积模拟精度较高,决定系数(R2=0.96)、归一化均方根误差(NRMSE=27.37%)、模型一致性指标(D=0.91)。结果表明:(1)随施氮量的增加,叶面积指数呈现先增后减的趋势;(2)随降水量的增加,叶面积整体呈现单一增长趋势;(3)水氮耦合作用中,降水量在自然降水基础上增加20%,施氮量为157.5 kg/hm2时,叶面积指数最高达2.766。本研究为田间试验水氮肥的施入量提供科学依据,为旱地春小麦增产提供了理论参考。     

节水农作制度综合效益评价的研究

不同的自然以及社会经济条件是形成各种节水农作制度的基础。文章主要从自然生态、经济、社会三个方面探讨节水农作制度形成的影响因素,将所涵盖的因素又具体细分为几类,从理化机制方面以及国内外实践经验出发,科学地分析了各种因素对节水农作制度形成与发展的制约形式,建立我国旱作地区节水农作制度形成机制的基本理论框架,并提出节水农作制度综合效益评价的构想。     

The Fortran simulation translator, a simulation language

The Fortran simulation translator (FST) is a simulation language, that enables the researcher to develop concepts, in terms of mathematical equations, e.g. about agro-ecological systems, that are converted in a Fortran program with data files (Fortran simulation environment, FSE). This generated Fortran program is well-structured and can be executed using both user developed and standard mathematical library subroutines (e.g. IMSL). The possibility to use the generated Fortran program as a starting point for further model development makes FST a valuable tool, both for research and education.     

Composite farming systems in an era of change: Nagaland, Northeast India

Composite farming systems, first clearly identified by Rambo, are those in which radically different technologies are found together in a single farming complex. Data from diaries kept by groups of farming families in two Angami Naga villages in northeast India, Khonoma and smaller Tsiesema, detailing inputs into and outputs from wet-rice terraces and jhum (swidden) fields in the years 2000 and 2001, are presented and discussed to detail the workings of related but different composite systems. The 2000–2001 survey caught an important set of changes in midstream. Although returns to labour from the first-year jhums were much higher than those from the wet-rice terraces in 2000–2001, jhums were declining in significance as a growing non-farm economy joined the production of cool-climate vegetables and a spice crop for the Indian market as principal sources of livelihood. This story is told in the light of recent writing on the demise of swidden in the larger Southeast Asian region, and it is suggested that greater attention be paid to the composite systems, which are not uncommon in this region. This might help diversify what has perhaps been an oversimplified discussion.     

A global sensitivity analysis of cultivar trait parameters in a sugarcane growth model for contrasting production environments in Queensland,Australia

New sugarcane cultivars are continuously developed to improve sugar industry productivity. Despite this sugarcane crop models such as the ‘Sugar’ module in the Agricultural Productions System sIMulator (APSIM-Sugar) have not been updated to reflect the most recent cultivars. The implications of misrepresenting cultivar parameters in APSIM-Sugar is difficult to judge as little research has been published on the likely values of these parameters and how uncertainty in parameter values may affect model outputs. A global sensitivity analysis can be used to better understand how cultivar parameters influence simulated yields. A Gaussian emulator was used to perform a global sensitivity analysis on simulated biomass and sucrose yield at harvest for two contrasting sugarcane-growing regions in Queensland, Australia. Biomass and sucrose yields were simulated for 42 years to identify inter-annual variability in output sensitivities to 10 parameters that represent physiological traits and can be used to simulated differences between sugarcane cultivars. Parameter main effect (S_i) and total effect (ST_i) sensitivity indices and emulator accuracy were calculated for all year-region-output combinations. When both regions were considered together parameters representing radiation use efficiency (rue), number of green leaves (green_leaf_no) and a conductance surrogate parameter (k_L) were the most influential parameters for simulated biomass in APSIM-Sugar. Simulated sucrose yield was most sensitive to rue, sucrose_fraction (representing the fraction of biomass partitioned as sucrose in the stem) and green_leaf_no. However, climate and soil differences between regions changed the level of influence cultivar parameters had on simulation outputs. Specifically, model outputs were more sensitive to changes in the transp_eff_cf and k_L parameters in the Burdekin region due to lower rainfall and poor simulated soil conditions. Collecting data on influential traits that are relatively simple to measure (e.g. number of green leaves) during cultivar development would greatly contribute to the simulation of new cultivars in crop models. Influential parameters that are difficult to measure directly such as transp_eff_cf and sucrose_fraction are ideal candidates for statistical calibration. Calibrating crop models either through direct observation or statistical calibration would allow crop modellers to better test how new cultivars will perform in a range of production environments.     

ROTOR,a tool for generating and evaluating crop rotations for organic farming systems

As with conventional farming, the improvement of organic farming systems requires agronomic planning tools to enhance economic performance. Crop rotation planning plays a crucial role in organic arable farming systems due to the renunciation of mineral nitrogen fertilisers and pesticides. Our objective was to develop a tool for generating and evaluating site-specific and agronomically sustainable crop rotations for organic farming systems in central Europe. The resulting static rule-based model, called ROTOR, consists of two basic steps: (A) A set of annual crop production activities (CPAs) is assembled semi-automatically from single site and crop-specific field operations using a relational data base. The database includes all relevant crops recorded separately with inputs and outputs, machinery and timing. Starting from stubble tillage and ending with the last harvest measure, the CPAs describe the current best cropping practices. Different CPAs are included for each crop according to (i) the type of crop preceding and (ii) the field operations following: whether ploughing or non-inverting tillage, undersowing crops, using catch crops, manuring, straw harvesting, or mechanical weed control. The former allows for the modelling of all possible positions of a crop within a crop rotation and the consequential effects of preceding crops. The CPAs are evaluated using rule-based assessment modules for yield, economic performance, N balance, nitrate leaching, and weed infestation risks. These modules have been developed using data from field experiments, farm trials and surveys, expert knowledge and a soil–crop simulation model. (B) Within the crop generation module, all possible sequences of CPAs are linked to 3–8-year preliminary crop rotations. Agronomically sustainable crop rotations are selected according to exclusion criteria (i.e., thresholds for N balance, weed infestation risks, phytosanitary and chronological restrictions) and ranked, e.g. by economic performance. The model was tested by comparing (i) estimated with observed yields and (ii) generated with existing rotations. These comparisons, based on data obtained from two farm surveys from North Eastern Germany, indicate the validity and usability of the model approach. ROTOR was found to support the complex crop rotation planning in organic farming systems requiring rotations with overlapping undersown main and cover crops. ROTOR is able to reduce the risk of planning failures by offering a quantitative method of optimisation of weed and site-specific N management.     

Information systems planning model and its applicationin automobile manufacturing enterprises

Effective information strategy and information systems are important for the development of automobile manufacturing enterprises. In complicated and dynamic business environment, information systems planning (ISP) faces the problem of lacking integrated optimization of enterprise strategy, business strategy, and IT strategy. A hierarchical information system planning model is developed for automobile manufacturing enterprises. A planning approach is proposed to make the information system continuously mating the enterprises' strategy. The proposed studies were applied to agile ISP of an automobile manufacturing enterprise with satisfied result.     

Use of the APSIM model in long term simulation to support decision making regarding nitrogen management for pearl millet in the Sahel

Soil fertility and climate risks are hampering crop production in the Sahelian region. Because experiments with only a few fertility management options on a limited number of sites and years cannot fully capture the complex and highly non-linear soil–climate–crop interactions, crop growth simulation models may suitably complement experimental research to support decision making regarding soil fertility and water management. By means of a long term (23 years) scenario analysis using the Agricultural Production Systems Simulator (APSIM) model, this study investigates millet response to N in view of establishing N recommendations better adapted to subsistence small-holder millet farming in the Sahel. Prior to this, the APSIM model was tested on a rainfed randomized complete block experiment carried out during the 1994 and 1995 cropping seasons, having contrasting rainfall conditions. The experiment combined, at three levels each, the application of cattle manure (300, 900 and 2700 kg ha^?1), millet residue (300, 900 and 2700 kg ha^?1) and mineral fertilizer (unfertilized control, 15 kg N ha^?1 + 4.4 kg P ha^?1 and 45 kg N ha^?1 + 13.1 kg P ha^?1) at ICRISAT Sahelian Center, Niger. The model suitably predicted plant available water PAW and the simulated water and nitrogen stress were in agreement with measurement (water) and expectation (N) regarding the fertilizer and rainfall conditions of the experiment. APSIM simulations were in satisfactory agreement with the observed crop growth except for the highest crop residue application rates (>900 kg ha^?1). For biomass and grain yield, the model performance was relatively good in 1994 but biomass yields were slightly overpredicted in 1995. The model was able to adequately reproduce the average trend of millet grain yield response to N inputs from manure and fertilizer, and to predict the overall observed higher grain yield in 1995 compared to 1994, despite the better rainfall in 1994. The 23-year, long term scenario analysis combining different application rates of cattle manure, millet residue and mineral fertilizer, showed that moderate N application (15 kg N ha^?1) improves both the long term average and the minimum yearly guaranteed yield without increasing inter-annual variability compared to no N input. Although it does imply a lower average yield than at 30 kg N ha^?1, the application of 15 kg N ha^?1 appears more appropriate for small-holder, subsistence farmers than the usual 30 kg N ha^?1 recommendation as it guarantees higher minimum yield in worst years, thereby reducing their vulnerability.     

Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice

We consider predictions of the impact of climate warming on rice development times in Sri Lanka. The major emphasis is on the uncertainty of the predictions, and in particular on the estimation of mean squared error of prediction. Three contributions to mean squared error are considered. The first is parameter uncertainty that results from model calibration. To take proper account of the complex data structure, generalized least squares is used to estimate the parameters and the variance-covariance matrix of the parameter estimators. The second contribution is model structure uncertainty, which we estimate using two different models. An ANOVA analysis is used to separate the contributions of parameter and model uncertainty to mean squared error. The third contribution is model error, which is estimated using hindcasts. Mean squared error of prediction of time from emergence to maturity, for baseline +2 °C, is estimated as 108 days², with model error contributing 86 days², followed by model structure uncertainty which contributes 15 days² and parameter uncertainty which contributes 7 days². We also show how prediction uncertainty is reduced if prediction concerns development time averaged over years, or the difference in development time between baseline and warmer temperatures.     

Effect of organic and conventional farming systems on nitrogen use efficiency of potato,maize and vegetables in the Central highlands of Kenya

Increased per capita food production in the tropics is closely tied to soil organic matter and water management, timely nitrogen (N) supply and crop N use efficiency (NUE) which are influenced by farming systems. However, there is lack of data on the effect of organic farming systems on NUE and how this compares to conventional farming systems under tropical conditions. Therefore, the objectives of this study were to determine the effect of conventional and organic farming systems at low and high management intensities on N uptake and N use efficiency of potato (Solanum tuberosum L.), maize (Zea mays L.), cabbage (Brassica oleracea var. Capitata), kale (Brassica oleracea var. Acephala) and Swiss chard (Beta vulgaris sub sp. Cicla). The organic high input (Org-High) and conventional high input (Conv-High) farming systems are managed as recommended by research institutions while organic low input (Org-Low) and conventional low input (Conv-Low) farming systems are managed as practiced by small scale farmers in the Central highlands of Kenya. The study was conducted during three cropping seasons between October 2012 and March 2014 in an ongoing long-term trial established since 2007 at Chuka and at Thika, Kenya. Synthetic N-based fertilizer and cattle manure were applied at ∼225 kg N ha⁻¹ yr⁻¹ for Conv-High and at ∼50 kg N ha⁻¹ yr⁻¹ for the Conv-Low. Composts and other organic inputs were applied at similar N rates for Org-High and Org-Low. Nitrogen uptake efficiency (NUpE) of potato was highest in Conv-Low and Org-Low at Thika and lowest in Org-High and Org-Low at Chuka site where late blight disease affected potato performance. In contrast, the NUpE of maize was similar in all systems at Chuka site, but was significantly higher in Conv-High and Org-High compared to the low input systems at Thika site. The NUpE of cabbage was similar in Conv-High and Org-High while the NUpE of kale and Swiss chard were similar in the low input systems. Potato N utilization efficiencies (NUtE) and agronomic efficiencies of N use (AE_N) in Conv-Low and Conv-High were 11–21 % and 1.4–3.4 times higher than those from Org-Low and Org-High, respectively. The AE_N of maize was similar in all the systems at Chuka but was 3.2 times higher in the high input systems compared to the low input systems at the Thika site. The AE_N of vegetables under conventional systems were similar to those from organic systems. Nitrogen harvest index (NHI) of potato was similar between Conv-High and Org-High and between Conv-Low and Org-Low. N partitioned into maize grain was similar in all the system at Chuka, but significantly lower (P < 0.001) in Conv-low and Org-Low at Thika site. The NHI of cabbage in Org-High was 24 % higher than that of Conv-High. The study concluded that for maize and vegetables, conventional and organic farming systems had similar effects on NUpE, AE_N, NUtE and NHI, while for potato conventional systems improved NUE compared to organic systems. The study recommends that management practices for potato production in organic systems should be improved for a more efficient NUE.     

Testing the performance of ORYZA1, an explanatory model for rice growth simulation, for Mediterranean conditions

ORYZA1 is an explanatory model to simulate rice growth, development and leaf area index (LAI) under potential production. The present study aims at testing the performance of ORYZA1 for Mediterranean conditions (farming practices, cultivars, weather) for fully irrigated direct-seeded rice. ORYZA1 was calibrated and validated with field data of two cultivars, a short-grain (Tebre) and a long-grain cultivar ( -202), grown in various years in the Ebro Delta of Spain. Phenological development of the rice crop, daily dry matter production and leaf area development were calibrated. Tebre and L-202 had no significant differences in the total length of the development period. The pre-heading period, however, was longer and the post-heading period shorter in L-202 than in Tebre. This induced differences in translocation characteristics, spikelet number per unit area, weight of the grains and harvest index. The following crop characteristics were similar between cultivars: extinction coefficient (increased with development stage), dynamics of nitrogen distribution, partitioning of assimilates, relative death rate of leaves, relative growth rate of leaf area during exponential growth, specific leaf area and a strongly decreasing specific stem green area. The simulated curve fitted much better the observations, which was clear from a strongly reduced value of RMSE, when considering that LAI comprises the leaf blade area only, without a photosynthetic contribution by stem green area. The model simulated rice growth very accurately until flowering. After flowering, however, divergences appeared and increased especially at the yellow ripe stage. From then on the crop did not grow much more, whereas it continued in the simulation. This reduction of growth rate was usually accompanied by an increase in the relative death rate of leaves and the drying of the grains. The main source of error may be a limited understanding of the ripening and sink limitation processes. A considerable yield gap between potential and observed yield remained. A climatic variability assessment over 10 years, from 1987 to 1996, showed a small but correlated variation (r=0.7) in both simulated and measured rice yields.     

Impacts and adaptation of the cropping systems to climate change in the Northeast Farming Region of China

The Northeast Farming Region of China (NFR) is a very important crop growing area, comprising seven sub-regions: Xing’anling (XA), Sanjiang (SJ), Northwest Songliao (NSL), Central Songliao (CSL), Southwest Songliao (SSL), Changbaishan (CB) and Liaodong (LD), which has been severely affected by extreme climate events and climatic change. Therefore, a set of expert survey has been done to identify current and project future climate limitations to crop production and explore appropriate adaptation measures in NFR. Droughts have been the largest limitation for maize (Zea mays L.) in NSL and SSL, and for soybean (Glycine max L. Merr.) in SSL. Chilling damage has been the largest limitation for rice (Oryza sativa L.) production in XA, SJ and CB. Projected climate change is expected to be beneficial for expanding the crop growing season, and to provide more suitable conditions for sowing and harvest. Autumn frost will occur later in most parts of NFR, and chilling damage will also decrease, particularly for rice production in XA and SJ. Drought and heat stress are expected to become more severe for maize and soybean production in most parts of NFR. Also, plant diseases, pests and weeds are considered to become more severe for crop production under climate change. Adaptation measures that have already been implemented in recent decades to cope with current climatic limitations include changes in timing of cultivation, variety choice, soil tillage practices, crop protection, irrigation and use of plastic film for soil cover. With the projected climate change and increasing risk of climatic extremes, additional adaptation measures will become relevant for sustaining and improving productivity of crops in NFR to ensure food security in China.     

An aeroelastic model design of ultra high voltage power transmission line systems

We present an aeroelastic model design and method creation based on the case of an ±800 kV ultra high voltage (UHV) power transmission line from Xiang Jiaba to Shanghai, P. R. Chin, Both the centralized and discreted stiffness modeling methods are unsuitable for tower aeroelastic modeling. Taking these stiffness and aerodynamic characteristics into account, we introduce a new method to create an aeroelastic model that includes a semi rigid model segment and U shaped springs. Because the span of this transmission line is too long to fit within the wind tunnel in the same proportions as the tower, the proportions of the line model is condensed further. Aeroelastic test requirements can be satisfied by comparing theoretical analysis and actual measurements of the system model dynamics.     

Fuzzy adaptive tracking control for MIMO nonlinear time-varying delay systems

A fuzzy adaptive tracking control scheme is proposed for MIMO nonlinear time-varying delay systems. A fuzzy T-S model-based adaptive time-varying delay fuzzy logic systems is developed to approximate the unknown nonlinear time-varying delay functions.Thus, the modeling to nonlinear systems is implemented. The update laws for parameters of the fuzzy logic systems are derived by the tracking error. A Hcompensator is designed to eliminate fuzzy approximation errors and external disturbances. Based on Lyapunov stability theorem, the proposed control scheme can guarantee the stability of the closed loop systems and obtain anticipant Htracking performance as well. Simulation results of the manipulator demonstrate the effectiveness of the control scheme.     

MEACROS: a tool for multi-criteria evaluation of alternative cropping systems

A procedure aimed at identifying cropping systems suitable for environmentally sensitive areas has been developed within the framework of a coordinated Italian project. It has been implemented as a DSS software named Multi-criteria Evaluation of Alternative CRopping Systems (MEACROS which makes it possible for decision-makers to compare different scenarios based on alternative cropping systems. A set of default technical—agronomic, economic, and environmental criteria have been included in MEACROS to allow for the different impacts induced by each scenario. Users can select between the proposed set of criteria and/or in-putting new ones. The software performs concordance analysis, providing preference rankings for the alternatives, based on computed indices and allowing a good sensitivity analysis of weighted values as well as displaying the results in graphic form. Indicative results are presented here in a case study concerning a farm in a flat, sensitive area in Northern Italy.     

LINTUL3, a simulation model for nitrogen-limited situations: Application to rice

LINTUL3 is a crop model that calculates biomass production based on intercepted photosynthetically active radiation (PAR) and light use efficiency (LUE). It is an adapted version of LINTUL2 (that simulates potential and water-limited crop growth), including nitrogen limitation. Nitrogen stress in the model is defined through the nitrogen nutrition index (NNI): the ratio of actual nitrogen concentration and critical nitrogen concentration in the plant. The effect of nitrogen stress on crop growth is tested in the model either through a reduction in LUE or leaf area (LA) or a combination of these two and further evaluated with independent datasets. However, water limitation is not considered in the present study as the crop is paddy rice. This paper describes the model for the case of rice, test the hypotheses of N stress on crop growth and details of model calibration and testing using independent data sets of nitrogen treatments (with fertilizer rates of 0–400 kg N ha^?1) under varying environmental conditions in Asia. Results of calibration and testing are compared graphically, through Root Mean Square Deviation (RMSD), and by Average Absolute Deviation (AAD). Overall average absolute deviation values for calibration and testing of total aboveground biomass show less than 26% mean deviation from the observations though the values for individual experiments show a higher deviation up to 41%. In general, the model responded well to nitrogen stress in all the treatments without fertilizer application as observed, but between fertilized treatments the response was varying.     

The simulation of conducted EMI in the ignition system for automotives

The ignition system in automobiles is a main source of electromagnetic interference (EMI), because the electromagnetic emission from the system has the characteristics of high-energy and wide-bandwidth. A method for EMI prediction based on its components’ circuit models is presented. First, the characteristics of the components are analyzed and the equivalent circuits are drew; then, the parasitic parameters of the electromagnetic device are extracted from measurement, analytical solution or finite element method (FEM); and finally, the circuit model of the whole ignition system model in high frequency condition is established. This model is verified by the measurement and simulation results in time domain and in frequency domain.     

棉花蕾铃生长发育和脱落的模拟研究

采用车箱理论方法,根据棉花生长发育过程中光合产物的源、库、流关系和供需平衡,定量模拟了不同品种、播期棉花蕾铃发育和脱落动态。结果显示,棉花单株蕾数、成铃数、吐絮铃数的模拟值与观察值之间的RMSE分别平均为3.36、1.57和1.04（个）;单铃重的RMSE为0.15 g;脱落率的RMSE为8.15%。表明应用本系统模拟蕾铃发育和脱落