An entropy approach to spatial disaggregation of agricultural production

While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.     

Systematic design and evaluation of crop rotations enhancing soil conservation, soil fertility and farm income: a case study for vegetable farms in South Uruguay

Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer’s income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelón Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelón Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer’s income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale.     

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。     

Crop rotations in Argentina: Analysis of water balance and yield using crop models

Cropping schemes have developed in east-central Argentina for rainfed soybean (Glycine max Merr.) production that invariably employ no-tillage management. Often these schemes include growing soybean in a sequence of crops including wheat (Triticum aestivum L.) and maize (Zea mays L.). The full impact of various rotation schemes on soil water balance through a sequence of seasons has not been explored, although the value of these rotations has been studied experimentally. The objective of this work was to investigate through simulations, potential differences in temporal soil water status among rotations over five years. In this study, mechanistic models of soybean (Soy), maize (Maz), and wheat (Wht) were linked over a five-years period at Marcos Juárez, Argentina to simulate soil water status, crop growth, and yield of four no-till rotations (Soy/Soy, Soy/Wht, Soy/Maz, and Soy/Maz/Wht). Published data on sowing dates and initial soil water contents in the first year from a no-till rotation experiment were used as inputs to the model. After the first year, soil water status output from the model was used to initiate the next crop simulation in the sequence. The results of these simulations indicated a positive impact on soil water balance resulting from crop residue on the soil surface under no-till management. Continuous soybean and the two-year soybean/maize rotation did not efficiently use the available water from rainfall. Residue from maize was simulated to be especially effective in suppressing soil evaporation. Thus, the Soy/Maz simulation results indicated that this rotation resulted in enhanced soil water retention, increased deep water percolation, and increased soybean yields compared with continuous soybean crops. The simulated results matched well with experimental observations. The three-crop rotation of Soy/Maz/Wht did not increase simulated soybean yields, but the additional water retained as a result of decreased soil evaporation resulting from the maize residue allowed the addition of a wheat crop in this two-year rotation. Simulated soybean yields were poorly correlated with both the amount of soil water at sowing and the rainfall during the cropping period. These results highlight the importance of temporal distribution of rainfall on final yield. These models proved a valuable tool for assessing the consequences of various rotation schemes now being employed in Argentina on temporal soil water status, and ultimately crop yield.     

Maize ethanol feedstock production and net energy value as affected by climate variability and crop management practices

Ethanol from various plant resources, especially maize, is increasingly being used as a substitute for fossil fuels. The production potential of ethanol from maize varies with weather and climatic conditions and crop management practices. The merits and prospects of ethanol production have been evaluated based on its impact on greenhouse gas emissions, economic viability and national energy security. The net energy value (NEV), i.e. the output energy after all non-renewable energy inputs have been accounted for, is a measure of energy gain. At the same time, the NEV can be an indicator for the long-term sustainability of bio-ethanol production, regardless of other conditions e.g. climate change scenarios, global trade restrictions, or local variability in natural resources such as water availability. Crop management practices directly affect the NEV of ethanol. Moreover, both crop management practices and climate variability affect the NEV through the grain yield. The objective of this study was to assess the impact of crop management practices and climate variability on grain yield of maize for ethanol production and ethanol NEV for conditions that represent the southeastern USA. Maize grain yield was simulated with the dynamic crop growth model CSM–CERES–Maize and ethanol NEV was calculated using the simulated yield levels and crop management practices. The simulations were conducted for conditions representing Mitchell County, Georgia, USA, using weather data from 1939 to 2006 and local soil profile information. The impact of irrigation, nitrogen fertilizer, planting date and El Niño Southern Oscillation (ENSO) phases were determined for the maize cultivars DeKalb DKC 61-72 (RR2), Pioneer 31D58 and Pioneer 31G98. Crop management practices and ENSO phase had a significant impact on ethanol feedstock production and NEV. The NEV of ethanol produced from irrigated maize was more than two times higher and varied less than the NEV of ethanol from rainfed maize. NEV of ethanol produced from maize grown during La Niña years was significantly higher than maize grown during El Niño years, both under rainfed and irrigated conditions. This study showed the importance of crop management practices and climate variability on ethanol feedstock productivity and long-term energy sustainability as assessed by the NEV. We discuss methods of implementing the findings of this study in practical farming e.g. through market mechanisms and governmental initiatives.     

基于遥感的农业用水效率评价方法研究进展

遥感技术的发展为区域尺度蒸散发计算、作物分布识别及估产提供了一条有效途径,为基于遥感信息的灌区灌溉水利用效率及作物水分利用效率定量评价奠定了基础。回顾总结了遥感蒸散发模型、瞬时蒸散发升尺度方法、日蒸散发插值方法、作物分布识别方法及作物估产模型的研究进展,评述了遥感蒸散发及作物估产结果在灌区灌溉水利用效率及作物水分利用效率评价中的应用情况。提出了相关领域需要进一步研究的问题,包括适合非均匀下垫面特点且具有较强物理基础的灌区遥感蒸散发模型、日蒸散发插值中灌溉或降雨引起土壤含水量突变情况的处理、农田蒸散发中灌溉水有效消耗量的准确估算、能适应复杂种植结构并且适用于多年的作物分布遥感识别模型以及精度较高且可操作性强的遥感估产模型等。     

Redirecting technology to support sustainable farm management practices

Agricultural technology has increased farm production to unprecedented levels. However, return on investment is diminishing and environmental concerns conflict with current input intensive farm practices. Conventional technologies and their application such as crop breeding and management practices have focused on monocultural systems that are dependent on chemical inputs to produce optimum yields. Current profit margins are low or non-existent with these conventional non-sustainable practices and must be changed if the family farm is to survive. We propose an ecologically based approach to farm management that strives to reduce reliance on chemically intensive inputs through better use of multiple attributes inherent within agroecosystems. This approach requires a redirection in the development and application of current and emerging technologies. Examples of redirections in research and development programs for pest management practices, genetic engineering, and precision agriculture necessary to provide a more ecologically-based and sustainable farming approach are illustrated.     

How does research address the design of innovative agricultural production systems at the farm level? A review

In trying to respond to societal demands for sustainable development, farming systems worldwide face a range of environmental, technical and economic challenges. These challenges call for renewed methodologies that can be used to support farmers in designing innovative agricultural production systems at the farm level. This paper aims to analyze the various methods described in scientific literature. The review is based on the analysis of 80 reference papers published in international scientific journals between 1999 and 2010. We focused in particular on the purpose of the research, which fell into two broad categories: “design” and “design support”. We also examined the use of models to represent production systems and to evaluate ex-ante the impact of innovations on these systems’ functioning and performance. In so doing, we developed a classification system to organize the studies into five sub-categories according to the type of methodology followed, namely: prototyping and design modelling for design orientated studies; participation, support modelling and advisory for design-support orientated studies. We found that very few studies attempt to address the three main components of an innovation process in agricultural production systems (biotechnical processes, farm management, and advisory services) within a single research framework. We therefore developed such a framework by connecting the design and design support orientations together with biotechnical research and conducting integrated research both at farm and advisory service levels.     

Livestock water productivity in mixed crop–livestock farming systems of the Blue Nile basin: Assessing variability and prospects for improvement

Water scarcity is a major factor limiting food production. Improving Livestock Water Productivity (LWP) is one of the approaches to address those problems. LWP is defined as the ratio of livestock’s beneficial outputs and services to water depleted in their production. Increasing LWP can help achieve more production per unit of water depleted. In this study we assess the spatial variability of LWP in three farming systems (rice-based, millet-based and barley-based) of the Gumera watershed in the highlands of the Blue Nile basin, Ethiopia. We collected data on land use, livestock management and climatic variables using focused group discussions, field observation and secondary data. We estimated the water depleted by evapotranspiration (ET) and beneficial animal products and services and then calculated LWP. Our results suggest that LWP is comparable with crop water productivity at watershed scales. Variability of LWP across farming systems of the Gumera watershed was apparent and this can be explained by farmers’ livelihood strategies and prevailing biophysical conditions. In view of the results there are opportunities to improve LWP: improved feed sourcing, enhancing livestock productivity and multiple livestock use strategies can help make animal production more water productive. Attempts to improve agricultural water productivity, at system scale, must recognize differences among systems and optimize resources use by system components.     

气候变化影响下作物模型的不确定性

作物生理生长过程准确描述及产量的精确估计在社会食品安全和农业生产中起着至关重要的作用.作物生长模型作为一种监测作物生长的数值模拟方法,已被证明是作物生长、产量预测和情景分析的有力工具.然而,在当前气候变化背景下,气候走向的不确定性以及极端气候事件的增加,都对粮食生产产生了重大影响,如何对作物生长进行准确模拟成为当前的热点关注话题.同时,除了气候变化的不确定性外,由于作物模型本身是实际作物生长过程的简化,物理结构并不完美,同时数据采集的随机性和初始条件的区域异质性,导致模拟结果不确定性较大.因此,在论述作物模型的国内外研究进展的基础上,探讨气候变化的不确定性对作物模型的影响以及作物模型本身的不确定性,概述了模型-数据融合方法的类型及特点,以及区域尺度上作物模型与遥感数据结合所采用的减小不确定性的方法,以期为相关研究提供一定参考.     

Using EPIC model to manage irrigated cotton and maize

Simulation models are becoming of interest as a decision support system for management and assessment of crop water use and of crop production. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of cotton and maize under South Texas conditions. Simulation of the model was performed to determine crop yield, crop water use, and the relationships between the yield and crop water use parameters such as crop evapotranspiration (ETc) and water use efficiency (WUE). We measured actual ETc using a weighing lysimeter and crop yields by field sampling, and then calibrated the model. The measured variables were compared with simulated variables using EPIC. Simulated ETc agreed with the lysimeter, in general, but some simulated ETc were biased compared with measured ETc. EPIC also simulated the variability in crop yields at different irrigation regimes. Furthermore, EPIC was used to simulate yield responses at various irrigation regimes with farm fields’ data. Maize required ∼700 mm of water input and ∼650 mm of ETc to achieve a maximum yield of 8.5 Mg ha⁻¹ while cotton required between 700 and 900 mm of water input and between 650 and 750 mm of ETc to achieve a maximum yield of 2.0-2.5 Mg ha⁻¹. The simulation results demonstrate that the EPIC model can be used as a decision support tool for the crops under full and deficit irrigation conditions in South Texas. EPIC appears to be effective in making long-term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for in-season irrigation management.     

Application of a simulation software to the analysis of a peasant farming system

A simulation software, GRANJAS was utilized to analyze a Chilean peasant farming system. The purpose of this simulation experiment was to test the impact of the technological innovations being proposed to the peasant family within the context of a Farming Systems Research and Development (FSRD) project.The use of GRANJAS allowed the timely detection of erroneous assumptions concerning the feasibility of solving the present labor shortages in the peasant farm while at the same time intensifying the use of the available irrigated land. It also permitted the comparison of two general options for the development of this particular farming system: development based on the intensification of the crop subsystem, or development based on the intensification of both crop and livestock production.It is concluded that GRANJAS, if properly combined with other analytical tools and techniques, can be a useful and cost efficient instrument for the design of development proposals for peasant farming systems such as the one analyzed in this paper.     

Simulating the effects of tax exemptions on fertiliser use in Benin by linking biophysical and economic models

The sluggish increase in the area productivity of staple crops is a major factor causing increased dependence of African countries on food imports. The increased use of mineral fertiliser may dramatically improve the food balance of many countries and result in lower food prices, higher food supply and consumption, and improved food security and nutritional status. In Benin, West Africa, political measures to improve farmers’ access to fertiliser are biased in favour of cotton production. This article simulates the impact of universal tax exemptions for fertiliser use on crop yields, food balances, and the use of land resources for the most important staple crops in Benin using a crop growth model and an agricultural sector model. The simulation results indicate that tax exemptions on fertiliser use could have positive effects on physical productivity and would increase food security until 2025 as compared to a baseline scenario. At the same time, the pressure on land resources would not be aggravated, so that better access to fertiliser may help to curb excessive cropland expansion in Benin.     

沙棘发展模式的经济效益分析

利用沙棘特殊的生物学特性,在荒山荒坡、低产田及风沙干旱区建立沙棘生态经济林,改善农作物的耕作环境,提高农牧产量,同时结合不同发展模式来分析预期经济效益,为农业增效提供参考。     

InfoCrop: A dynamic simulation model for the assessment of crop yields,losses due to pests,and environmental impact of agro-ecosystems in tropical environments. I. Model description

The problems of agriculture in many tropical countries are gradually becoming more intense due to increasing food demand led by population growth, stagnation in farm productivity, mounting yield losses due to multiple pests, increasing vulnerability to global environmental changes and the need to reduce emission of greenhouse gases. Tools and techniques are needed to assist in developing strategies that can lead to higher food production, prevent crop production losses, and ensure minimal greenhouse gas emissions while maintaining soil fertility. Several dynamic models have been developed in recent past but most of these are generally strong either in soils and crops, or in greenhouse gases (GHG) emissions. Pest induced yield losses, a critical issue in the tropics, is not addressed in most models. InfoCrop, a generic dynamic crop model, has been developed to meet these specific requirements. It provides integrated assessment of the effect of weather, variety, pests, soil and management practices on crop growth and yield, as well as on soil nitrogen and organic carbon dynamics in aerobic as well as anaerobic conditions, and greenhouse gas emissions. The model considers the key processes related to crop growth, effects of water deficit, flooding, nitrogen management, temperature and frost stresses, crop–pest interactions, soil water and nitrogen balance and (soil) organic carbon dynamics. Its general structure relating to basic crop growth and yield is largely based on several earlier models, especially SUCROS series, and is written in Fortran Simulation Environment (FSE) programming language. The model has been validated for dry matter and grain yields of several annual crops, losses due to multiple diseases and pests, and emissions of carbon dioxide, methane and nitrous oxide in a variety of agro-environments. To increase the applications of model in research and development, an extremely simple menu driven version of InfoCrop has also been developed. The users of this version do not need any background in programming.     

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.     

Co-evolutionary scenarios of intensification and privatization of resource use in rural communities of south-western Niger

Agricultural production in the semi-arid agro-ecosystems of the Sahel centres on cereal staple crops and pastoralism with increasing crop–livestock integration. Animals mobilize soil fertility through manure production, graze crop by-products, and transfer nutrients from distant pastures to cropped areas. Yet in these systems various interacting factors, i.e. climate variability, poor soil fertility, poverty, and institutional constraints limit the capacity of agriculture to keep pace with the growing needs of an increasing human population.The major trends associated with population growth are (1) increasing area cropped at the expense of rangelands; (2) reduced availability of and access to good quality grazing resources, and (3) seasonal migration of labourers and transhumance of herds. These trends lead to co-evolution of farming systems towards increased privatisation of resource use.This study examines the implications of the development processes where farming systems co-evolve with their surroundings. It explores the impact of integrated management of livestock and crops in rural communities on both the livelihoods of differently endowed farms, and on the agro-ecosystem. Different scenarios explored the co-evolution of three sites situated in Western Niger with their environment. The sites differ in relative area cropped. The scenarios simulate the different future outcomes for varying socio-economic and biophysical criteria with either current or more intensive management.Explorative bio-economic models are used to compare a range of farm, livelihood and ecological indicators, and to reveal social and ecological trade-offs.If current agro-ecosystems and their environments co-evolve towards increased privatisation of grazing resources, then soil fertility is likely to deteriorate on the lands managed by the agro-pastoral groups. Soil fertility may improve on lands managed by the livestock-scarce farmers settled in villages, at the cost of declining farm incomes. The agro-pastoral groups are likely to resort to more distant pastures for feed. The village-based, livestock-endowed farms will resort to feeding on on-farm crop residues. Intensification, though associated with relative decreases in real incomes, will enhance food security in these new systems, except for the poorer settled farmers.     

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.