Use of available information at a European level to construct crop nitrogen response curves for the regions of the EU

Nowadays European agriculture is evolving in a context where policy-making and environmental concerns play a key role. To better assess agro-environmental policies, the AROPAj agricultural supply model needs to take into account the technical characteristics of crop management for different farms. A method to build up specific relationships between yield and nitrogen fertilization that takes into account agronomic techniques is proposed in this paper. The nitrogen response curve is based on an exponential function that integrates economic properties consistently from an agronomic point of view. In AROPAj, individual production systems (farm types) do not have a given location within a specified region and in databases technical information is scarce. The method involves determining technical and physical characteristics, inputs that allow the STICS crop model to assess the yield response to nitrogen of each crop on every farm type. From this information, a nitrogen response curve can be drawn up for each crop of each one of the farms. It can take into account both nitrogen from purchased fertilizer and nitrogen from animal effluents produced on farm. The method was designed to be adaptable to any European region, and tests carried out on two French regions covering a wide range of situations (crops, soils, climates and techniques) showed it was able to cope with varying prices and environments. The agronomic consistency of STICS inputs and curve shapes was also checked. When incorporated into the AROPAj economic model, the response curves can be used to render farms more sensitive to agricultural policy scenarios, by allowing their optimal fertilization level to be adjusted.     

Intensification of New Zealand beef farming systems

This study used whole-farm management, nutrient budgeting/greenhouse gas (GHG) emissions and feed formulation computer tools to determine the production, environmental and financial implications of intensifying the beef production of typical New Zealand (NZ) sheep and beef farming systems. Two methods of intensification, feeding maize silage (MS) or applying nitrogen (N) fertiliser, were implemented on two farm types differing in the proportions of cultivatable land to hill land (25% vs. 75% hill). In addition, the consequences of intensification by incorporating a beef feedlot (FL) into each of the farm types were also examined.Feeding MS or applying N fertiliser substantially increased the amount of beef produced per ha. Intensifying production was also associated with increased total N leaching and GHG emissions although there were differences between the methods of intensification. Feeding MS resulted in lower environmental impacts than applying N even after taking into account the land to grow the maize for silage. Based on 2007/08 prices, typical NZ sheep and beef farms were making a financial loss and neither method of intensification increased profitability with the exception of small annual applications of N, especially to the 75% hill farm. These small annual additions of N fertiliser (<50 kg N/ha/yr applied in autumn and late winter) resulted in only small increases in annual N leaching (from 11 to 14 kg N/ha) and GHG emissions (from 3280 to 4000 kg CO₂ equivalents/ha). Limited N applications were particularly beneficial to 75% hill farms because small increases in winter carrying capacity resulted in relatively large increases in the utilisation of pasture growth during spring and summer than the 25% hill farms. Intensification by incorporating a beef feedlot reduced environmental emissions per kg of beef produced but considerably decreased profitability due to higher capital, depreciation and labour costs. The lower land-use capability farm type (75% hill) was able to intensify beef production to a proportionally greater extent than the higher land-use capability farm (25% hill) because of greater potential to increase pasture utilisation associated with a lower initial farming intensity and inherent constraints in the pattern of pasture supply.     

Analysis of the uncertainty associated with the estimation of nitrogen losses from farming systems

This work describes the analysis of the uncertainty linked to the annual direct and indirect losses of different nitrogenous compounds at the scale of a group of farms. The nitrogen (N) forms taken into account are: ammonia (NH₃), nitric oxide (NO), nitrous oxide (N₂O), dinitrogen (N₂) and nitrate (NO₃). The gaseous N emissions for the different components of the farms are estimated with a selection of adapted emission factors. The NO₃ losses at the farm scale are calculated as the difference between the surplus of the farm-gate N balance and the gaseous N emissions.     

Modelling the fate of water and nitrogen in the mixed vegetable farming systems of northern Tasmania, Australia

A combination of high input management systems, high annual rainfall and deep, permeable soils in northern Tasmania create conditions that are conducive to high drainage and nitrogen losses below the root zone. An understanding of the extent and mechanism of such losses will enable farm managers and their consultants to identify and implement more sustainable management practices that minimise potential adverse financial and environmental consequences. Analysing the fate of water and nutrients in farming systems is complex and influenced by a wide range of factors including management, soil characteristics, seasonal climate variability and management history of the paddock/farm in question. This paper describes a novel farm system modelling approach based on the model APSIM, for analysing the fate of nitrogen and water in mixed vegetable-based farming enterprises. The study was based on seven case farms across the Panatana catchment in northern Tasmania. Substantial simulated drainage losses (>100 mm average seasonal loss) were apparent for all crop and rotation elements across all farms in response to the surplus between crop water supply and crop water use. Crop nitrogen demand was found to be close to crop nitrogen supply for all crop and pasture rotation elements with the exception of potato, which had an average surplus nitrogen supply of 89 kg N/ha. This resulted in potato having much higher nitrate nitrogen leaching losses (32 kg N/ha) compared to other crops (<10 kg N/ha). Simulations suggest that practicable management options such as deficit-based irrigation and reduced N fertiliser rates will maintain current levels of productivity while reducing potential offsite N loss and generating significant financial savings via reduced input costs.     

A systems approach to analyse the effects of Flemish manure policy on structural changes and cost abatement in pig farming

Animal production in the Flemish region and pig production in particular is intensive and causing external problems related to manure disposal. At a regional level, manure disposal can be regarded as a problem of distributing the manure from farms with a surplus to farms with a shortage or to disposal alternatives. Total disposal costs will depend on the amount of manure surplus and on the location dependent disposal cost per unit. Disposal costs are an economic incentive for structural changes and cost abatement investments at farm level which will, in turn, influence the regional disposal. In order to simulate these interactions, an integrated system of models describing the regional manure disposal coordination system is developed, composed of a farm level component, an aggregation module and a regional disposal model. The possibilities for disposal cost abatement at farm level are analysed through LP modelling of representative farms. Incentives for structural change are derived from the shadow prices of the housing and land constraints in the model. Manure separation is analysed as an example of cost abatement investments.     

The impact of water and agriculture policy scenarios on irrigated farming systems in Italy: An analysis based on farm level multi-attribute linear programming models

The objective of this paper is to evaluate the impacts of agriculture and water policy scenarios on the sustainability of selected irrigated farming systems in Italy, in the context of the forthcoming implementation of the directive EC 60/2000. Directive EC 60/2000 (Water Framework Directive) is intended to represent the reference norm regulating water use throughout Europe. Five main scenarios were developed reflecting aspects of agricultural policy, markets and technologies: Agenda 2000, world market, global sustainability, provincial agriculture and local community. These were combined with two water price levels, representing stylised scenarios for water policy. The effects of the scenarios on irrigated systems were simulated using multi-attribute linear programming models representing the reactions of the farms to external variables defined by each scenario. The output of the models consists of economic, social and environmental indicators aimed at quantifying the impact of the scenarios on different aspects of sustainability relevant for irrigated farming systems. Five Italian irrigated farming systems were considered: cereal, rice, fruit, vegetables and citrus. The results show the diversity of irrigated systems and the different effects that water pricing policy may produce depending on the agricultural policy, market and technological scenarios. They also highlight a clear trade-off between socio-economic sustainability and environmental (water, nitrogen, pesticide) sustainability. Water pricing will have, in most cases, less impact than agricultural markets and policy scenarios, though it appears to be an effective instrument for water regulation in the least intensive irrigated systems considered. This emphasises the need for a differentiated application of the Water Framework Directive at the local level as well as a more careful balance of water conservation, agricultural policy and rural development objectives.     

GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises Part I – Whole-farm dynamic model

 Crop-livestock farms are complex systems. The interactions operating in such systems involve decisional, biophysical, structural, and environmental factors. Moreover, as farmers face a large range of management options, tools are needed to support their decision-making to enable them to reach production levels meeting their objectives and compatible with their human and physical resources, while controlling their effects on the environment. Gamede, a whole-dairy-farm model, has been developed to explore this complexity and to represent dynamically the effect of management decisions on biomass and nitrogen flows and on numerous sustainability indicators, such as milk and forage crop productivity, labour requirements, nitrogen balance, and nitrogen efficiency.This article describes the integration of six modules accounting for biophysical processes in a dairy farm (forage production; forage conditioning; herd demography; milk, excreta and animal biomass productions; grazing, quality of fertilisers; and nitrogen gaseous emissions) together with a decision system accounting for the farmer’s strategy and technical operations. Most of the six biophysical modules incorporate mathematical models from the literature, but the decision system stems from our own original work.Six commercial farms with different structures, agro-climatic conditions and management strategies were used for validation. The model can explain the differences found in their sustainability indicators at the year scale. The intra-year variability of the main biomass stocks and flows is also well explained. This quantitative validation was completed by a qualitative validation from researcher, adviser and farmer points of view, including simulations of prospective scenarios.     

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.     

Economic and environmental evaluation of three goal-vision based scenarios for organic dairy farming in Denmark

The objective of this study was to explore the sustainability of future organic dairy farming systems in Denmark, by evaluating the economic and environmental consequences of three scenarios at the farm level based on different visions of future sustainability leading to different farm-based goals. The future sustainable organic dairy farming systems were deduced from participative sessions with stakeholders, and used to define specific scenarios and related key parameters. Parameterization of the scenarios was based on model simulations and the invoking of expert knowledge. Each scenario was designed to fulfil different aspects of sustainability. The business as usual scenario (BAU) was driven by economic incentives and implemented new technologies and measures to enhance productivity and efficiency. This scenario was expected to be the mainstream strategy of future organic dairy production in Denmark. In the animal welfare scenario (ANW), economic efficiency was subordinate to animal welfare, and measures to improve animal welfare, such as lower milk yield, extra grazing area and a deep-litter barn, were incorporated. The environmental scenario (ENV) was designed to minimize N losses into the environment, reduce emission of greenhouse gases and the use of fossil energy, and was based on self-sufficiency regarding nutrients and feed. The economic evaluation of the scenarios was based on quantification of farm profitability (i.e. net profit), whereas environmental evaluation was based on the quantification of the N-surplus per ha, emission of greenhouse gases, and use of fossil energy per kg energy-corrected milk (ECM).Compared to prolonging the current main stream strategy (BAU), the evaluation of scenarios revealed that investing in animal welfare comprised trade-offs regarding farm profitability, climate change and the use of fossil energy. In ANW, net profit per farm was almost 39 k€ lower than in BAU, whereas emission of greenhouse gases and energy per kg ECM was 8% and 3% higher, respectively. Minimizing environmental impact in ENV reduced local as well as global environmental impact without an economic trade-off. Greenhouse gas emission per kg ECM was 5% lower and fossil energy use was 11% lower than in BAU. The N-surplus of ENV was 80 kg per ha, whereas the N-surplus was approximately 116 in both BAU and ANW. Prolonging the current main stream strategy (BAU) resulted in a high local environmental impact, a moderate global environmental impact and a high economic risk related to changes in milk price or costs.     

The impact of agriculture on ground water quality in Slovenia: standards and strategy

Ground water and water from springs are sources used for water supply in Slovenia. The quality of these waters has been monitored since 1987. Among 12 main ground water aquifers in Slovenia the amount of nitrate exceeds the allowable level (50 mg/l) for drinking water in areas with more intensive agricultural production with higher concentrations of animals (two livestock unit – LU/ha) and where drainage of sewage water is not excellently arranged or where quality of river water that effluent ground water is not well. The identification of nitrogen surpluses has been done on regional and farm level (using normative approach). This method is taking into account nitrogen input from mineral fertiliser, animal wastes and the deposition from the atmosphere minus nitrogen uptake of harvested crops and ammonia losses to the atmosphere. On an average nitrogen input from mineral fertiliser is low, while input from organic manure is rather high – 90 kg/ha. Average net-balance surplus for Slovenia is about 56 kg N/ha. The differences between regions are relatively high. In the most intensive arable region with high intensity of animal husbandry (2 LU/ha) nitrogen surplus is about 90 kg/ha. This region can be identified as vulnerable for nitrogen leaching into ground water. In regions with limited growing conditions for agriculture plants (climate, soil depth) just small increase of livestock density can cause high nitrogen surpluses. Our Slovenian legislation, which almost entirely corresponds to EC Nitrate Directive and Code of Good Agricultural Practice intends to reduce mineral surpluses in agriculture and meet the standards of nitrate in drinking water.     

Analysis of nitrate pollution control policies in the irrigated agriculture of Apulia Region (Southern Italy): A bio-economic modelling approach

Nitrate leaching is one of the many forms of environmental pollution resulting from irrigation and intensive agriculture. In this work, a method of combining an agronomic simulation model (EPIC) and a mathematical multi-objective programming model is used to analyse the effects of three agricultural policies on farmer’s revenue and nitrate leaching. An evaluation of the net social costs associated with the different policy measures is also given. The farmer’s behaviour in different policy scenarios was studied in terms of selected crops, irrigation technique and method, and adopted management practices with focus on farm management practices and water application efficiency. Irrigation water pricing, subsidies to adopt improved management levels, and taxation on the use of nitrogen fertilizer were examined. A trade-off emerges between the levels of nitrate leaching and net farmer’s revenue more pronounced for nitrogen tax policies than for water pricing. The results obtained indicate that nitrate leaching can be reduced by about 40% with an associated net social cost of 269 €/ha for the water pricing policy, 183 €/ha for the tax on fertilizer and 95 €/ha for subsidies to high efficiency management.     

The environmental performance of milk production on a typical Portuguese dairy farm

The activities associated with raw milk production on dairy farms require an effective evaluation of their environmental impact. The present study evaluates the global environmental impacts associated with milk production on dairy farms in Portugal and identifies the processes that have the greatest environmental impact by using life cycle assessment (LCA) methodology. The main factors involved in milk production were included, namely: the dairy farm, maize silage, ryegrass silage, straw, concentrates, diesel and electricity. The results suggest that the major source of air and water emissions in the life cycle of milk is the production of concentrates. The activities carried out on dairy farms were the major source of nitrous oxides (from fuel combustion), ammonia, and methane (from manure management and enteric fermentation). Nevertheless, dairy farm activities, which include manure management, enteric fermentation and diesel consumption, make the greatest contributions to the categories of impact considered, with the exception of the abiotic depletion category, contributing to over 70% of the total global warming potential (1021.3 kg CO₂ eq. per tonne of milk), 84% of the total photochemical oxidation potential (0.2 kg C₂H₄ eq. per tonne of milk), 70% of the total acidification potential (20.4 kg SO₂ eq. per tonne of milk), and 41% of the total eutrophication potential (7.1 kg eq. per tonne of milk). The production of concentrates and maize silage are the major contributors to the abiotic depletion category, accounting for 35% and 28%, respectively, of the overall abiotic depletion potential (1.4 Sb eq. per tonne of milk). Based on this LCA case study, we recommend further work to evaluate some possible opportunities to improve the environmental performance of Portuguese milk production, namely: (i) implementing integrated solutions for manure recovery/treatment (e.g. anaerobic digestion) before its application to the soil as organic fertiliser during maize and ryegrass production; (ii) improving manure nutrient use efficiency in order to decrease the importation of nutrients; (iii) diversifying feeding crops, as the dependence on two annual forage crops is expected to lead to excessive soil mobilisation (and related impacts) and to insignificant carbon dioxide sequestration from the atmosphere; and (iv) changing the concentrate mixtures.     

Climate change affects farm nitrogen loss – A Swiss case study with a dynamic farm model

The response of arable crops and grasslands to climatic changes and increasing CO₂ concentration has implications for the operation of farms, in particular for the management of resources such as nitrogen. A simple dynamic farm model (Stella^© model ‘CH-Farm’) was used to analyze the shift in the ratio of N lost via leaching, denitrification and volatilization to N exported with products from dairy or arable production (here defined as relative N loss). The model was run for two types of farms typical of Swiss conditions. Growth parameters for two sequentially grown crops (winter wheat and maize) and grass were determined with the process-oriented models Pasture Simulation Model (PaSim) and CropSyst, respectively. CH-Farm was forced with two assumptions about the transient change in temperature and precipitation, and with or without CO₂ effects. Relative N loss for the baseline was around 1.33 for the dairy-type farm and around 1.05 for the arable-type farm and increased progressively over the 100-year simulation period, with the largest shift in response to the dry/hot scenario. Soil N pools decreased with all scenarios, but at different rates. CO₂ fertilization alleviated the effect of climate change due to increased productivity and N fixation in plants. Adjustment of the growth parameters to progressively increasing temperatures reduced the difference between farm types and positively affected relative N losses mainly through increased productivity and reduced fallow periods between crops. The results suggest that the impact of climate change on relative farm-level N loss depends on physiological adjustments to climatic scenarios, whereas the distribution of land between dairy and arable crop production is less important, and that simple cultivar adjustments can help to mitigate negative effects of climate change on farm-level N use.     

Efficiency of controlled drainage and subirrigation in reducing nitrogen losses from agricultural fields

In northeast Italy, a regimen of controlled drainage in winter and subirrigation in summer was tested as a strategy for continuous water table management with the benefits of optimizing water use and reducing unnecessary drainage and nitrogen losses from agricultural fields.To study the feasibility and performance of water table management, an experimental facility was set up in 1996 to reproduce a hypothetical 6-ha agricultural basin with different land drainage systems existing in the region. Four treatments were compared: open ditches with free drainage and no irrigation (O), open ditches with controlled drainage and subirrigation (O-CI), subsurface corrugated drains with free drainage and no irrigation (S), subsurface corrugated drains with controlled drainage and subirrigation (S-CI). As typically in the region free drainage ditches were spaced 30 m apart, and subsurface corrugated drains were spaced 8 m apart.Data were collected from 1997 to 2003 on water table depth, drained volume, nitrate-nitrogen concentration in the drainage water, and nitrate-nitrogen concentration in the groundwater at various depths up to 3 m.Subsurface corrugated drains with free drainage (S) gave the highest measured drainage volume of the four regimes, discharging, on average, more than 50% of annual rainfall, the second-highest concentration of nitrate-nitrogen in the drainage water, and the highest nitrate-nitrogen losses at 236 k ha⁻¹.Open ditches with free drainage (O) showed 18% drainage return of rainfall, relatively low concentration of nitrate-nitrogen in the drainage water, the highest nitrate-nitrogen concentration in the shallow groundwater, and 51 kg ha⁻¹ nitrate-nitrogen losses.Both treatments with controlled drainage and subirrigation (O-CI and S-CI) showed annual rainfall drainage of approximately 10%. O-CI showed the lowest nitrate-nitrogen concentration in the drainage water, and the lowest nitrogen losses (15 kg ha⁻¹). S-CI showed the highest nitrate-nitrogen concentration in the drainage water, and 70 kg ha⁻¹ nitrate-nitrogen losses. Reduced drained volumes resulted from the combined effects of reduced peak flow and reduced number of days with drainage.A linear relationship between daily cumulative nitrate-nitrogen losses and daily cumulative drainage volumes was found, with slopes of 0.16, 0.12, 0.07, and 0.04 kg ha⁻¹ of nitrate-nitrogen lost per mm of drained water in S-CI, S, O, and O-CI respectively.These data suggest that controlled drainage and subirrigation can be applied at farm scale in northeast Italy, with advantages for water conservation.     

大田无人农场关键技术研究现状与展望

无人农场是智慧农业的一种表现形式,也是建设农业强国和实现农业现代化的重要探索。无人农场以数据、知识和智能装备为核心要素,将现代信息技术与农业深度融合,实现农业全过程生产所需的信息感知、定量决策、智能控制、精准投入及个性化服务一体化。本文系统地阐述了大田无人农场的概念与总体技术架构,讨论了信息感知与智能决策、精准作业系统与装备、自动驾驶、无人化农机装备以及无人农场管控平台等五项大田无人农场的关键技术与装备,深入分析了发展中国大田无人农场亟待解决的关键科学与技术问题。以吉林省公主岭市玉米无人农场为例介绍了物联网、大数据、云计算以及人工智能等技术在玉米全程无人化生产中的具体应用及效果。最后,展望了无人农场在解决全球农业生产面临的“无人种田”等共性问题中发挥的重要作用,分析了中国发展无人农场存在的机遇和挑战,提出了中国发展无人农场的战略目标与思路。     

Farm types for beef production and their economic success in a mountainous province of northern Vietnam

The objective of this study was to compare the management and economic success of beef production by three types of farm in northwestern Vietnam. The potential of household farms to supply beef for the market and their competition with large farms were examined.The fieldwork was done in 2007 on 73 farms consisting of 58 small mixed farms (small farms), 10 medium mixed farms (medium farms) and 5 specialised large-scale beef farms (large farms) in Son La province. The three types of farm differed in ethnicity (Thai, H’mong, and Kinh), remoteness (lowland, highland), production objectives (subsistence, market output), degree of specialization (mixed farm, specialised beef farm) and integration of production (single farmers, cooperative). Data on biological productivity, inputs and outputs, and the social contribution of cattle production were collected by household and key person interviews, participatory rural appraisal tools and cattle body measurements. Economic values were derived by assessment of market or replacement costs. Quantitative data analysis was done with linear models (PROC GLM) in the SAS software (version 9.1).Lowland small farms had higher costs for cattle production than the highland farms (0.8 Mill. VND head⁻¹ year⁻¹ compared with 0.02 Mill. VND head⁻¹ year⁻¹, respectively). The large farms had high production costs, with an average of 2.5-3.6 Mill. VND head⁻¹ year⁻¹. Cattle brought high benefits of non-cash values to the household farms. The total revenue from cattle was in the range 4.5-11.5 Mill. VND head⁻¹ year⁻¹, which depended on the use of non-market functions of cattle on the household farm. The value of net benefit/kg live weight (LW) of lowland small farms with an average of 39,000 VND/kg LW was significantly higher than that of the medium and small farms in the highlands (26,000 VND/kg LW). However, the small farms kept fewer cattle than the medium farms (average of 2-4 cattle/farm compared with 9 cattle/farm, respectively) because of forage and labour shortages and have no option to further develop cattle production. Keeping larger numbers of cattle based on available natural pasture brought high benefit from stock value as farm liquidity to only the medium farms. This was the most promising type of farm for future development of beef production, given its actual success and the availability of underutilised resources. Large-scale farms suffered high economic losses of 0.3-1.4 Mill. VND cattle⁻¹ year⁻¹, due to the lack of professional management, high feed costs and low animal performance, and showed no potential for developing cattle production.     

Life cycle assessment of greenhouse gas emissions from beef production in western Canada: A case study

A life cycle assessment (LCA) was conducted to estimate whole-farm greenhouse gas (GHG) emissions from beef production in western Canada. The aim was to determine the relative contributions of the cow-calf and feedlot components to these emissions, and to examine the proportion of whole-farm emissions attributable to enteric methane (CH₄). The simulated farm consisted of a beef production operation comprised of 120 cows, four bulls, and their progeny, with the progeny fattened in a feedlot. The farm also included cropland and native prairie pasture for grazing to supply the feed for the animals. The LCA was conducted over 8 years to fully account for the lifetime GHG emissions from the cows, bulls and progeny, as well as the beef marketed from cull cows, cull bulls, and progeny raised for market. The emissions were estimated using Holos, a whole-farm model developed by Agriculture and Agri-Food Canada. Holos is an empirical model, with a yearly time-step, based on the Intergovernmental Panel on Climate Change methodology, modified for Canadian conditions and farm scale. The model considers all significant CH₄, N₂O, and CO₂ emissions and removals on the farm, as well as emissions from manufacture of inputs (fertilizer, herbicides) and off-farm emissions of N₂O derived from nitrogen applied on the farm. The LCA estimated the GHG intensity of beef production in this system at 22 kg CO₂ equivalent (kg carcass)⁻¹. Enteric CH₄ was the largest contributing source of GHG accounting for 63% of total emissions. Nitrous oxide from soil and manure accounted for a further 27% of the total emissions, while CH₄ emissions from manure and CO₂ energy emissions were minor contributors. Within the beef production cycle, the cow-calf system accounted for about 80% of total GHG emissions and the feedlot system for only 20%. About 84% of enteric CH₄ was from the cow-calf herd, mostly from mature cows. It follows that mitigation practices to reduce GHG emissions from beef production should focus on reducing enteric CH₄ production from mature beef cows. However, mitigation approaches must also recognize that the cow-calf production system also has many ancillary environmental benefits, allowing use of grazing and forage lands that can preserve soil carbon reserves and provide other ecosystems services.     

Assessing the impact of the Nitrate Directive on farming systems using a bio-economic modelling chain

Bio-economic models can be used to assess the impact of policy and environmental measures through economic and environmental indicators. Focusing on agricultural systems, farmers’ decisions in terms of cropping systems and the associated crop management at field scale are essential in such studies. The objective of this paper is to present a study using a bio-economic model to assess the impact of the Nitrate Directive in the Midi-Pyrenees region (France) by analyzing, at the farm scale, farm income and three environmental indicators: nitrate leaching, erosion and water consumption. Two scenarios, the 2003 CAP reform (baseline scenario) and the Nitrate Directive (policy scenario), with a 2013 time horizon, were developed and compared for three representative arable farm types in the Midi-Pyrenees region. Different types of data characterizing the biophysical context in the region (soil, climate), the current cropping systems (rotation, crop management) and farm resources (irrigated land, labor) were collected to calibrate and run the models. Results showed that the implementation of the Nitrate Directive may not affect farm income. However, significant modifications to cropping systems and crop allocation to soil types were simulated. Contrary to expectations, nitrogen leaching at the farm scale did not change. Overall water consumption increased and soil erosion decreased due mainly to a modification in cropping patterns and management by soil type. This study provides an example of unanticipated effects of policy and trade-offs between environmental issues.     

How much land is needed for global food production under scenarios of dietary changes and livestock productivity increases in 2030?

Growing global population figures and per-capita incomes imply an increase in food demand and pressure to expand agricultural land. Agricultural expansion into natural ecosystems affects biodiversity and leads to substantial carbon dioxide emissions.Considerable attention has been paid to prospects for increasing food availability, and limiting agricultural expansion, through higher yields on cropland. In contrast, prospects for efficiency improvements in the entire food-chain and dietary changes toward less land-demanding food have not been explored as extensively. In this study, we present model-based scenarios of global agricultural land use in 2030, as a basis for investigating the potential for land-minimized growth of world food supply through: (i) faster growth in feed-to-food efficiency in animal food production; (ii) decreased food wastage; and (iii) dietary changes in favor of vegetable food and less land-demanding meat. The scenarios are based in part on projections of global food agriculture for 2030 by the Food and Agriculture Organization of the United Nations, FAO. The scenario calculations were carried out by means of a physical model of the global food and agriculture system that calculates the land area and crops/pasture production necessary to provide for a given level of food consumption.In the reference scenario - developed to represent the FAO projections - global agricultural area expands from the current 5.1 billion ha to 5.4 billion ha in 2030. In the faster-yet-feasible livestock productivity growth scenario, global agricultural land use decreases to 4.8 billion ha. In a third scenario, combining the higher productivity growth with a substitution of pork and/or poultry for 20% of ruminant meat, land use drops further, to 4.4 billion ha. In a fourth scenario, applied mainly to high-income regions, that assumes a minor transition towards vegetarian food (25% decrease in meat consumption) and a somewhat lower food wastage rate, land use in these regions decreases further, by about 15%.     

基于物联网实时数据的交互式虚拟现代农业园区平台软硬件构建及应用

本文利用虚拟现实/混合现实/增强现实/数字孪生等主流多媒体交互技术融入农业生产、生态、生活场景中,从北京都市型现代农业发展进程中的设施农业调控、会展农业体验、休闲农业观光、现代农业展示的各方面入手,通过获取农业物联网数据、农业园区场景数据、农作物生长点云数据等多种信息化数据,构建基于物联网实时数据的交互式虚拟休闲农业园区平台,基于平台软件,根据不同的实际需求、环境条件,配置研发满足政府、专家、市民、农民、学生等受众对于智慧化农事活动体验、农业科普知识传播、农业园区展示规划、农业景观重构展现等要求的体验设备,为设施农园、休闲农庄、农业机构等提供完整的多媒体农业信息化交互体验解决方案,达到节本增效、增收致富、知识普及、休闲观光、提升信息化水平的目的。