Modelling kinetics of plant canopy architecture—concepts and applications

Most crop models simulate the crop canopy as an homogeneous medium. This approach enables modelling of mass and energy transfer through relatively simple equations, and is useful for understanding crop production. However, schematisation of an homogeneous medium cannot address the heterogeneous nature of canopies and interactions between plants or plant organs, and errors in calculation of light interception may occur. Moreover, conventional crop models do not describe plant organs before they are visible externally e.g. young leaves of grasses. The conditions during early growth of individual organs are important determinants of final organ size, causing difficulties in incorporating effects of environmental stresses in such models. Limited accuracy in describing temporal source-sink relationships also contributes to difficulty in modelling dry matter distribution and paramaterisation of harvest indices. Functional-architectural modelling aims to overcome these limitations by (i) representing crops as populations of individual plants specified in three dimensions and (ii) by modelling whole plant growth and development from the behaviour of individual organs, based on models of organs such as leaves and internodes. Since individual plants consist of numerous organs, generic models of organ growth applicable across species are desirable. Consequently, we are studying the development of individual organs, and parameterising it in terms of environmental variables and plant characteristics. Models incorporating plant architecture are currently applied in education, using dynamic visual representation for teaching growth and development. In research, the 3D representation of plants addresses issues presented above and new applications including modelling of pesticide distribution, fungal spore dispersal through splashing and plant to plant heterogeneity.     

A model for simulating the height of rice plants

A reliable approach for modelling rice plant height would allow the simulation of processes with a significant impact on yields, e.g., lodging, floodwater effect on leaves temperature, crop–weeds competition for radiation interception. In this paper we present a new model for the simulation of rice plant height based on the integral of the percentage of biomass partitioned to stems. The model was compared with four alternative approaches using data collected during eight experiments carried out in Russia, Japan and US between 1991 and 2000, proving to be the most accurate in reproducing plant height during the whole crop cycle. RRMSE ranged between 8.02% and 20.87%, modelling efficiency was always close to one and the absolute value of coefficient of residual mass never exceeded 0.16. It resulted also the most robust and the less complex (according to the Akaike's Information Criterion) among those compared. The model presents a lower level of empiricism with respect to the other approaches found in the literature, deriving plant height from the allocation of biomass to stems, which are the plant organs most involved in determining canopy height. This model represents a suitable base for further developments aiming at including the effect of management practices (e.g., fluctuating water depth) and environmental factors (e.g., crop–weeds competition for radiation interception). Moreover, the low input requirements favour its inclusion in operational cropping systems models.     

Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

Evaluating irrigation strategies for lettuce by simulation: 1. Water flow simulations

Among crop systems, vegetable crops with high inputs of fertilizer and water represent an important threat to the quality of the water. To give guidelines to growers and decision-makers for crop management, numerous fertilization and irrigation practices in various situations should be evaluated with regard to their production and pollution effects.

Here, we used a model of water flow and solute transport (Lafolie, 1991) to compare three irrigation strategies with regard to their effects on the water balance. The model was run for a lettuce crop for two growing periods (summer and autumn) and over 100 years in French Mediterranean conditions. The three strategies were (1) the current strategy based on the occurrence of rainfall, (2) a strategy based on a simplified modelling of the soil water balance and (3) a strategy based on tensiometer readings.

As expected, strategy 1 was very water and time-consuming. Compared with strategy 2, strategy 3 appeared as a good choice, minimizing the waste of water: it involved less irrigation and less drainage loss. The crop was also less stressed by this strategy.     

Modelling the impacts of climate change and methane emission reductions on rice production: a review

Rice agriculture is not only affected by climate change, but also contributes to global warming through the release of methane into the atmosphere. In 1989, a major research project was initiated at the International Rice Research Institute in the Philippines to investigate relationships between climate change and rice production. A second project started in 1993 to investigate, in more detail, mitigation options that could be employed to help reduce CH₄ emissions from rice cultivation. An important component of all of this work was the quantification of these interactions between climate change and rice production into simulation models, and their subsequent use to upscale field measurements to national and regional levels. The first project developed such a model to integrate existing knowledge of effects of increased levels of CO₂ and temperature on rice growth, and used this to predict the impact of various climate change scenarios on rice production in SE Asia. In the second project, routines describing the dynamics of CH₄ production and emission from the soil were linked to a crop simulation model to estimate the effect of different crop management scenarios on national CH₄ emissions from various countries in the region. With the recent completion of the second project, it is timely to review this modelling work describing the relationships between the global environment and rice production, a task which we attempt in the present paper. The advantages and disadvantages of the modelling approaches used and other issues relating to the upscaling of field measurements to national and regional levels are discussed. Future research directions in this area are also identified.     

Assessing the sustainability of cropping systems in single- and multi-site studies. A review of methods

The multiple new challenges facing agriculture require the development of innovative cropping systems with high environmental, economic and social performances. Many research programmes are currently focusing on the design of such cropping systems. Some include the multicriteria assessment of cropping systems by diverse methods and approaches. Some of these research programmes are supported by experimental or farmers’ networks, generating new opportunities for data analysis and raising new research and methodological questions. In this article, we provide an overview based on a review of 56 articles, comparing the various methods for sustainability assessment in single- and multi-site studies. Articles were classified according to three characteristics: (i) their objectives, (ii) the study design (single- vs. multi-site), (iii) the type of system assessed (fictitious vs. real). Our analysis was structured around four items: (i) the variables used to describe cropping systems and production situations and the use of these variables in the assessment process, (ii) the criteria and associated indicators assessed, (iii) the methods used to explore multiple aspects of the performance of cropping systems, (iv) the use of reference values. We identified key points to be taken into account in multi-site studies. The application of the proposed guidelines to experimental networks should facilitate the identification of high-performance cropping systems and the identification of the drivers of cropping system performance.     

The DSSAT cropping system model

The decision support system for agrotechnology transfer (DSSAT) has been in use for the last 15 years by researchers worldwide. This package incorporates models of 16 different crops with software that facilitates the evaluation and application of the crop models for different purposes. Over the last few years, it has become increasingly difficult to maintain the DSSAT crop models, partly due to fact that there were different sets of computer code for different crops with little attention to software design at the level of crop models themselves. Thus, the DSSAT crop models have been re-designed and programmed to facilitate more efficient incorporation of new scientific advances, applications, documentation and maintenance. The basis for the new DSSAT cropping system model (CSM) design is a modular structure in which components separate along scientific discipline lines and are structured to allow easy replacement or addition of modules. It has one Soil module, a Crop Template module which can simulate different crops by defining species input files, an interface to add individual crop models if they have the same design and interface, a Weather module, and a module for dealing with competition for light and water among the soil, plants, and atmosphere. It is also designed for incorporation into various application packages, ranging from those that help researchers adapt and test the CSM to those that operate the DSSAT–CSM to simulate production over time and space for different purposes. In this paper, we describe this new DSSAT–CSM design as well as approaches used to model the primary scientific components (soil, crop, weather, and management). In addition, the paper describes data requirements and methods used for model evaluation. We provide an overview of the hundreds of published studies in which the DSSAT crop models have been used for various applications. The benefits of the new, re-designed DSSAT–CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.     

In-field development of a conceptual crop functioning and management model: A case study on cotton in southern Mali

West African cotton production has increased rapidly in recent years. Cotton is being cropped under new ecological conditions by new cotton-producing farmers, but the cropping techniques recommended by developers have essentially remained the same. Methodologies are needed to generate a broad scope of recommendations on cropping techniques to deal with the increasing diversity concerning farmers and cropping conditions.

A conceptual model of a cotton field was developed that approaches a crop field as a biophysical system under the influence of a “technical system” (i.e. the combination of farmers’ practices implemented in the field). The system outputs were restricted to yield and the main yield components. A theoretical model was first designed on the basis of published data and expert knowledge on cotton physiology, local soil–climate conditions and farmers’ practices. It was based on five specific hypotheses on links between technical and biophysical systems. The hypotheses were tested in a local farmers’ network. Thirty “cropping situations” (soil–crop–technique combinations) were selected in farmers’ fields around Katogo village (Mali), a village that had been previously selected for a cotton crop management prototyping program. Homogeneous groups of situations were drawn up on the basis of the dynamics of crop aerial biomass accumulation. They were compared for their management and environment features. The initial conceptual model was then simplified, while taking the measured variability in its components and the sensitivity of the outputs to these components into account. This conceptual model is being evaluated in other villages, where we have partnerships with farmers, in order to develop a version adapted to a broad range of situations.     

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.     

Estimating the environmental footprint of barley with improved nitrogen uptake efficiency—a Swedish scenario study

Plant breeding is a powerful tool for improving nitrogen (N) uptake efficiency and thus reducing the environmental impact relating to crop production. This study evaluated the environmental impact of current barley production systems in two Swedish agricultural areas (South and East) compared with scenarios with improved N uptake efficiency at two levels, in which the fraction of mineral N available for daily crop uptake was increased by 50 and 100%. Life cycle assessment (LCA) methodology was used to quantify energy use, global warming potential (GWP) and acidification and eutrophication potentials along the production chain for spring barley with differing N uptake efficiency, but similar N application rate. The functional unit, to which all energy use and emissions were related, was 1 Mg barley grain. Energy use, GWP and acidification proved to be higher for the East production system, mainly due to lower yield, while eutrophication was higher for South. The two impacts most affected by improved N uptake efficiency were eutrophication and GWP, with GWP decreasing due to a combination of higher yield, soil carbon sequestration and lower indirect emissions of N₂O due to lower N leaching. Accounting for land savings due to increased yield, reducing the pressure to transform land elsewhere, would further lower the carbon footprint. Potential eutrophication per Mg grain was reduced by 15% in the production system with the highest N uptake efficiency in southern Sweden. Crops with improved N uptake efficiency can thus be an important complementary measure for reducing N losses to water, provided that the N application rate does not increase. However, incentives for farmers to maintain or even lower the N application rate might be required. Using simulation modelling is a promising approach for assessment of expected effects of improved crop varieties when no long-term experimental data are available. However, advanced crop models are required to better reflect the effect of plant breeding on e.g. expected yield. Future model development should involve expertise in plant breeding, plant physiology and dynamic crop and soil modelling.     

Designing crop management systems by simulation

To help agricultural advisors to propose innovative crop management systems, simulation models can be a complementary tool to field experiments and prototyping. Crop management systems can be modelled either by using a vector representing dates and quantities used as input parameters in crop models or by developing specific decision models linked with biophysical models. The general design process of crop management systems by simulation follows a four-step loop (GSEC): (i) generation; (ii) simulation; (iii) evaluation; (iv) comparison and choice. The Generation step can follow different approaches: from blind generation before simulation to optimization procedures using artificial intelligence algorithms during the loop process. Simulation is mainly an engineering problem. Evaluation process means assigning a vector of indicators to the simulated crop management systems. A three-point evaluation can be carried out on the simulated crop management systems: global, agronomic and analytical. Comparison and choice of different simulated crop management systems raise the question of “monetary” versus “non-monetary” comparison and how to aggregate different quantities such as drainage, nitrogen fertilisers, labour, etc. Different examples are given to illustrate the GSEC loop on the basis of research programs conducted in France. Methodological advances and challenges are then discussed.     

Model suitability to assess regional potato yield patterns in northern Ecuador

A wide range of scenario studies aiming at rural development require regional patterns of crop yield. This study aims to evaluate three different modeling approaches for their suitability to assess regional potato yield patterns. The three model approaches include (1) an empirical model; (2) a process-based crop growth simulation model; and (3) a metamodel derived from the crop growth simulation model. Scenario studies have specific requirements for these modeling approaches including (1) their ease to use, (2) a realistic sensitivity, (3) the relevance in terms of generating the desired system property, and (4) their credibility in producing recognizable plausible outputs for stakeholders. The modeling approaches were applied to assess patterns of potato yields in a major production area in northern Ecuador. All three modeling approaches require significant expert knowledge for their development and calibration. However, after this initial phase, the empirical model and the metamodel are very easy to use and transparent. However, their application domain is limited to the case study area. The application of the crop growth simulation model remains complex and the model functions as a black box. The results show that regional patterns of potato yield are determined by a limited number of variables. The sensitivity of all three modeling approaches to climatic factors and water holding capacity suggest that the potato production in the area is constrained by water availability and temperature. All models generate similar yield patterns. However, the empirical model derives quality adjusted potato yields that correlate highly to the observed yields, whereas the crop growth simulation model and the derived metamodel produce potential, water and nutrient limited yields. Scenario studies may require yield patterns at different levels of resolution. All results could be aggregated to different resolutions but in general the patterns remained very similar. All three modeling approaches were capable to reproduce the observed regional pattern of potato yield and are therefore considered to be credible. In analyzing the effect of spatial aggregation on the performance of the modeling approaches, the results show that aggregation improves the overall correspondence between model output and interpolated, observed yields. It can be concluded that the various modeling approaches have their unique value. They are therefore complementary to each other for the interpretation of the observed patterns. The patterns themselves do not vary much and as such the most convenient modeling approach can be selected (based on available expertise and data).     

CropRota – A crop rotation model to support integrated land use assessments

Crop rotations influence the sustainability of agricultural systems. Integrated land use modeling frameworks increasingly acknowledge their role when analyzing economic and environmental impacts of agricultural production systems. However, insufficient data on crop rotations often challenge their consideration. In this article, we present the crop rotation model CropRota, which integrates agronomic criteria and observed land use data to generate typical crop rotations for farms and regions. The article describes the model and data requirements as well as an application of CropRota to 579 farms in the Austrian Mostviertel region. Model validation and sensitivity analysis are conducted to reveal robustness and accuracy of model outputs as well as its appropriateness for supporting integrated land use analyses. Comparisons between modeled and observed crop sequences from seven years of field observations show that the average area-weighted deviations range between 11% and 105% depending on the procedure of comparison and model specifications. The results indicate that CropRota is a suitable tool for the estimation of typical crop rotations from observed land use data. In addition, the model is sufficiently flexible to spatial scales and research contexts as frequently required in integrated land use analyses.     

基于升尺度方法的华北冬小麦区域生长模型初步研究 Ⅰ.潜在生产水平

作物生长模型是在田间尺度上开发的,而区域尺度上的作物生长信息更受决策部门的关注。作物模拟从单点研究发展到区域应用需要解决升尺度连接（Scaling-up）等一系列技术问题。本文利用以经纬度为权重的IDW空间插值法对气象数据和与温度有关的作物参数进行空间插值;根据华北冬小麦的品种地带性分布特点进行了冬小麦品种参数     

PermVeg: A Model to Design Crop Sequences for Permanent Vegetable Production Systems in the Red River Delta,Vietnam

The constraints in current vegetable production systems in the Red River Delta, Vietnam, in which vegetables are rotated with flooded rice, called for the design of alternative systems of permanent vegetable production. The practical model, PermVeg, was developed to generate vegetable crop sequences for permanent vegetable production, as based on a set of rules and restrictions. Permanent vegetable production systems were designed based on the following five scenarios: (i) increased profit, (ii) reduced labour requirement, (iii) decreased costs of pesticide use, (iv) improved crop biodiversity and (v) selected crops with low‐perishable products. PermVeg showed that theoretically all selected crop sequences in the different alternative systems increased farmers' income compared to the traditional system. The system with the highest profitability increased profit per hectare per day by a factor of three as compared to the traditional system. Labour requirement in days per hectare per day in a crop sequence also increased in all systems. Except for the system with low costs of pesticide use, permanent vegetable production systems had higher pesticide costs than the traditional, vegetable – flooded rice crop sequence. Given the model outcomes, permanent vegetable production systems can be an option to improve farmers' income, to provide labour opportunities, and, in the case of the high crop biodiversity system, to contribute to the development of sustainable production systems. The PermVeg model can act as a practical tool to rapidly explore crop sequence options and to help farmers' decision‐making.     

Best management practices of tillage and nitrogen fertilization in Mediterranean rainfed conditions: Combining field and modelling approaches

In this work, appropriate management practices for crop production under the variable climate conditions of the Mediterranean region, in particular rainfall, were tested with the use of a modelling system applied to long-term (i.e. 18 years) field data. The calibration of the CropSyst model was performed using data collected from 1996 to 1999 at three different Mediterranean locations (i.e., HYP-Guissona, MYP-Agramunt and LYP-Candasnos, i.e. high, medium and low yield potential, respectively) within a degree of yield potential. The model simulated reasonably well barley growth and yield to different tillage and N fertilization strategies.Simulations of barley performance over 50 years with generated weather data showed that yields were often greater and never smaller under no-tillage compared to conventional tillage with a mean increase of 36%, 63% and 18% for HYP-Guissona, MYP-Agramunt and LYP-Candasnos. In MYP-Agramunt, the long-term data showed a 40% increase in grain yields when using no-tillage compared to conventional tillage, as an average of 18 years.The model also predicted that greater N applications in no-tillage were appropriate to take advantage of additional water supply. Taking into account the limited amount of soil water available, overall N fertilizer applications could be reduced to about half of the traditional rate applied by the farmers without yield loss. The 50-yr simulation, confirmed by the long-term experimental data, identified no-tillage as the most appropriate tillage practice for the rainfed Mediterranean areas. Also, N fertilization must be reduced significantly when tillage is used or when increasing aridity. Our work demonstrates the usefulness of the combination of long-term field experimentation and modelling as a tool to identify the best agricultural management practices. It also highlights the importance of posterior analysis with long-term observed field data to determine the performance of simulation results.     

作物生产潜力模型研究进展

提高粮食综合生产能力，是确保中国粮食安全的重要途径。粮食作物生产潜力，是研究粮食综合生产能力的基础，总结了粮食作物生产潜力模型的研究进展，分析了从光、温、水、气候、土壤等因素的机理性研究到农业模型以及主流的统计分析模型的研究脉络和存在的问题与模型发展方略。     

粮食作物生产系统定量调控理论与技术模式

当今作物生产正在向高产、高效、环境友好等多目标协同方向发展,进一步深化和完善作物生产调控理论与技术体系是实现多元化目标协同,促进作物生产可持续发展的重要途径。本文对当前作物生产调控理论与技术的研究进展进行了总结,并结合当今作物生产发展形势,在全面总结前人成果和笔者30余年研究结果的基础上,提出了从作物生产系统的整体性角度出发,通过定量分析作物生产系统气候、土壤、作物三要素的协同关系,将"气候-作物"、"土壤-作物"和"群体-个体"三者协同优化的作物高产高效调控途径,构建了作物生产系统气候-土壤-作物"三协同"定量优化体系,并对其生产应用和未来发展进行了探讨与展望,以期为实现我国主要粮食作物高产高效可持续生产提供理论指导。