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Intensification of arable farming in Northwest Europe has led to high yields. However, inadequate use of external inputs such as nutrients, irrigation water and crop protection products has contributed to several environmental problems, such as nitrate leaching and losses of crop protection products. There is a need to reduce environmental losses and contribute to a more circular and sustainable agriculture in Northwest Europe. Here, we take ware potato production in the Netherlands as an example cropping system to assess if there is scope to reduce input levels and environmental impact of nutrient, water and crop protection product use without compromising yield. We determined variability in use and use efficiency of nitrogen (N), phosphorus (P), potassium (K) and pesticides as well as water productivity (WP) and yields of 96 on-farm ware potato fields in the Netherlands, on both clay and sandy soils. In addition, we assessed if relatively high performance could be achieved on multiple environmental indicators simultaneously. Average N surplus was 265 kg N ha−1 on clay soils and 139 kg N ha−1 on sandy soils and varied among fields by a factor three. Phosphorus and K input exceeded P and K output on clay soils by 33 and 105 kg ha−1, respectively, while on sandy soils P and K balances were close to zero. Mean WP was 43 kg dry matter (DM) mm−1 ha−1 and ranged from 30 to 60 kg DM mm−1 ha−1 for both soil types. In terms of crop protection product use, lowest and highest use differed by a factor four. Unexpectedly, yields did not increase with higher input rates, suggesting that lower input rates are sufficient to obtain current yields. Consequently, input rates were the most important drivers to explain variability in resource use efficiency and environmental impacts. At the same time, a comparison across multiple indicators simultaneously showed that it was possible to achieve relatively high yields with relatively low N surplus, high WP, and low crop protection product use. Hence, environmental impact could decrease substantially if all fields performed similar to the best performing fields. This study showed that it seems feasible to maintain high yield levels while reducing resource use in a substantial share of the potato production fields in the Netherlands. If put in practice, this will reduce losses to the environment and therefore contribute to a more sustainable but still productive agriculture. [Display omitted] • Variability in nutrient, water, and crop protection products use varied up to a factor four. • Yields did not differ between low and high input rates. • Resource use efficiency was at least 50% higher in best than in worst performing fields. • Environmental targets for N surplus were met in only 8–12% of fields. • There is scope to reduce input use and environmental impact, without compromising crop yield. [ABSTRACT FROM AUTHOR]

Farming systems in Europe are experiencing multiple stresses and shocks that may push systems beyond critical thresholds after which system change is expected to occur. These critical thresholds may lie in the economic, environmental, social and institutional domain. In this paper we take a participatory approach with involvement of farming system stakeholders to assess the presence of critical thresholds in 11 European farming systems, and the potential consequence of surpassing those with regard to system sustainability and resilience. First, critical thresholds of the main challenges, key system variables and their interactions in the studied farming systems were assessed. Second, participants assessed the potential developments of the key system variables in case critical thresholds for main system challenges would be exceeded. All studied systems were perceived to be close, at or beyond at least one identified critical threshold. Stakeholders were particularly worried about economic viability and food production levels. Moreover, critical thresholds were perceived to interact across system levels (field, farm, farming system) and domains (social, economic, environmental), with low economic viability leading to lower attractiveness of the farming system, and in some farming systems making it hard to maintain natural resources and biodiversity. Overall, a decline in performance of all key system variables was expected by workshop participants in case critical thresholds would be exceeded. For instance, a decline in the attractiveness of the area and a lower maintenance of natural resources and biodiversity. Our research shows that concern for exceeding critical thresholds is justified and that thresholds need to be studied while considering system variables at field, farm and farming system level across the social, economic and environmental domains. For instance, economic variables at farm level (e.g. income) seem important to detect whether a system is approaching critical thresholds of social variables at farming system level (e.g. attractiveness of the area), while in multiple case studies there are also indications that approaching thresholds of social variables (e.g. labor availability) are indicative for approaching economic thresholds (e.g. farm income). Based on our results we also reflect on the importance of system resources for stimulating sustainability and resilience of farming systems. We therefore stress the need to include variables that reflect system resources such as knowledge levels, attractiveness of rural areas and general well-being of rural residents when monitoring and evaluating the sustainability and resilience of EU farming systems. • Concern on exceeding critical thresholds is justified as studied farming systems are perceived to be close to such thresholds. • Challenges in the environmental domain were least often perceived to have reached critical thresholds. • Economic viability at farm level is a central, interacting critical threshold observed in all farming systems. • The economic, environmental as well as social domain are important for the sustainability and resilience of farming systems. [ABSTRACT FROM AUTHOR]

Row configuration has a large influence on the intensity of species interactions in intercrops. Row configuration affects how many crop rows interact with the same species and how many rows interact with the other species, shaping the expression of plasticity, resource capture, and growth. This study aims to determine how row configuration influences radiation interception and productivity in wheat-maize intercropping under western European growing conditions. Field experiments with different row configurations were carried out in 2013 and 2014 in the Netherlands. We compared seven treatments, comprising sole crops of wheat and maize (SW and SM), a replacement intercrop (6:2WM), skip-row designs (6:0WM, 0:2WM) and add-row designs (6:3WM, 8:2WM). We determined leaf area and biomass dynamics over time, and developed a simple geometry-based model to estimate light capture in these different row configurations. The model was tested with light measurements in the field. Crop radiation use efficiency (RUE) was estimated by linear regression of above-ground biomass on the calculated cumulative intercepted light (photosynthetically active radiation – PAR). This study showed that: 1) wheat-maize intercropping had significantly higher PAR interception than sole wheat in 2013 and 2014, and sole maize in 2013, but not in 2014; 2) intercropping significantly increased RUE of wheat, whereas it significantly decreased RUE of maize; 3) both light interception and light use efficiency changed with planting configuration. Thus we showed that the row configuration of the intercrop affected light interception as well as light use efficiency by modulating the strength of competitive and compensatory interactions within and between crop species. [ABSTRACT FROM AUTHOR]

Intercropping tends to have a higher productivity than traditional sole crops, mainly due to complementary resource use in time and space among different species. Intercropping may become more important in a world that needs to produce 60–70% more food by 2050 with limited land and other agricultural resources. To assess the role of intercropping in agricultural systems and its contribution to future food security, an intercrop model is needed for growth and yield predictions of intercrops under different growing conditions. Strip intercropping is a prevalent intercropping system, but the existing intercrop models are generally built for full mixtures and are less suitable for strip intercrops. Here we describe a simple intercrop model which is developed based on a sole crop model using the radiation use efficiency (RUE) concept and a strip intercrop light partitioning module. The model allows simulating the growth and yield of each intercropped species in relay-strip intercropping under potential growing conditions (only competition for light; other resources are assumed to be non-limiting), and the intercrop could vary in species combination, planting configuration, sowing densities and sowing dates. The daily inputs of the model are temperature and radiation, and crop-specific parameters are required to simulate crop leaf area index (LAI), biomass and final yield. Data collected during two years (2013 and 2014) field experiments were used to calibrate and test the model. The experiments consisted of two sole crop treatments (sole wheat, SW and sole maize, SM) and three intercrop treatments (replacement intercrop, 6:2WM and add-row intercrops, 8:2WM and 6:3WM). The experiments were conducted in Wageningen, the Netherlands. Data of sole crops (SW and SM) and replacement intercrop (6:2WM) treatment were used to calibrate the model, and data of add-row intercrops (8:2WM and 6:3WM) were used to test the model. Bayesian analysis was applied to calibrate RUE of wheat and maize in sole crops and intercrop. This calibration procedure resulted in posterior distributions of RUE for sole crops and intercrop, on the basis of which distributions of biomass and land equivalent ratio (LER) were simulated. Biomass accumulation and yield of each species were simulated adequately but LAI was slightly overestimated compared to observations. The intercrop model allows simulating the contribution of border row effects to the productivity of intercrops. It combines a simple structure with easy calibration and enables growth and yield simulations for a wide range of relay-strip intercrops. The model thus can be of value in exploratory land use studies to assess the role of intercropping. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is a finite natural resource and is essential for food production. The amount of P involved in food production in China relative to the increase of food production has increased dramatically over the past decades, which has led to serious environmental pollution. Because of China's enormous share in global P fertilizer production (30%) and consumption (37.5%), it evidently plays a crucial role in developing a more sustainable use of this essential resource for agriculture. We performed an integrated analysis of the P flows, P stocks, P utilization efficiencies (PUE) and environmental implications at the national level in China for the year 2010, complemented with an analysis at regional, county and farm levels. The static Material Flow Analysis approach based on the law of mass balance was used. We found that P accumulation in the arable land and P losses in the livestock raising industry are the major contributors to environmental pollution. Improving the PUE in arable land and the livestock raising industry, on the basis of the actual demands combined with efforts to promote the use of residual soil P on arable land and the recycling of organic manure and wastes, will significantly reduce the consumption and losses of P from the food chain, and will slow down the depletion of this finite natural resource. [ABSTRACT FROM AUTHOR]

Intercropping is widely used by smallholder farmers in developing countries, and attracting attention in the context of ecological intensification of agriculture in developed countries. There is little experience with intercropping of food crops in Western Europe. Yields in intercrops depend on planting patterns of the mixed species in interaction with local growing conditions. Here we present data of two years field experimentation on yield and yield components of a wheat–maize intercrop system in different planting configurations in the Netherlands. Treatments included sole crops of wheat (SW) and maize (SM), a replacement intercrop consisting of strips of six wheat rows alternating with two maize rows (6:2WM), as well as subtractive or additive designs, based on skip-row (6:0WM, 0:2WM) and add-row (8:2WM, 6:3WM) configurations. The land equivalent ratio (LER) of intercrops varied from 1.18 to 1.30 in 2013 and from 0.97 to 1.08 in 2014. Wheat grown in the border rows of wheat strips had higher ear number per meter row, greater kernel number per ear, and greater yield per meter row than wheat in inner rows and sole wheat, indicating reduced competition. Wheat in the border rows in the intercrops had, however, reduced thousand kernel weight and harvest index, indicating that competition in border rows intensified over time. Intercropping negatively affected maize biomass and thousand kernel weight, especially in add-row treatments. This study indicates that there is a potential yield benefit for the wheat–maize intercropping system under Western European growing conditions. However, the LER was affected by yearly variation in weather conditions and significantly greater than one in only one of the two years of the study. [ABSTRACT FROM AUTHOR]

Highlights: [•] Bayesian network modelling for farming systems assessment of biodiesel production in Brazil. [•] Explored field, farm, industry and policy decisions impacting family farmer engagement. [•] Decisions supporting successful family farmer engagement are not singular. [•] Need to minimise trade-offs between biodiesel crop and animal production. [•] Field-level management must be complemented by higher-level management. [ABSTRACT FROM AUTHOR]

Abstract: Yields of crops must increase substantially over the coming decades to keep pace with global food demand driven by population and income growth. Ultimately global food production capacity will be limited by the amount of land and water resources available and suitable for crop production, and by biophysical limits on crop growth. Quantifying food production capacity on every hectare of current farmland in a consistent and transparent manner is needed to inform decisions on policy, research, development and investment that aim to affect future crop yield and land use, and to inform on-ground action by local farmers through their knowledge networks. Crop production capacity can be evaluated by estimating potential yield and water-limited yield levels as benchmarks for crop production under, respectively, irrigated and rainfed conditions. The differences between these theoretical yield levels and actual farmers’ yields define the yield gaps, and precise spatially explicit knowledge about these yield gaps is essential to guide sustainable intensification of agriculture. This paper reviews methods to estimate yield gaps, with a focus on the local-to-global relevance of outcomes. Empirical methods estimate yield potential from 90 to 95th percentiles of farmers’ yields, maximum yields from experiment stations, growers’ yield contests or boundary functions; these are compared with crop simulation of potential or water-limited yields. Comparisons utilize detailed data sets from western Kenya, Nebraska (USA) and Victoria (Australia). We then review global studies, often performed by non-agricultural scientists, aimed at yield and sometimes yield gap assessment and compare several studies in terms of outcomes for regions in Nebraska, Kenya and The Netherlands. Based on our review we recommend key components for a yield gap assessment that can be applied at local to global scales. Given lack of data for some regions, the protocol recommends use of a tiered approach with preferred use of crop growth simulation models applied to relatively homogenous climate zones for which measured weather data are available. Within such zones simulations are performed for the dominant soils and cropping systems considering current spatial distribution of crops. Need for accurate agronomic and current yield data together with calibrated and validated crop models and upscaling methods is emphasized. The bottom-up application of this global protocol allows verification of estimated yield gaps with on-farm data and experiments. [Copyright &y& Elsevier]

Abstract: Continuing interest in sustainable biofuel production is linked with sustainable farming and begs for insights from farming systems research on sustainability assessment and the role of family farms. The aims of this work were two-fold. First, to present a tools and methods selection framework supporting indicator-based sustainability assessment. Second, to apply the framework to the case of castor beans (Ricinus communis L.), family farmers and the biodiesel industry in the southeast of Brazil. The framework synthesizes existing work on sustainability assessment within the agricultural domain. Transparent selection of tools and methods is supported by sequentially accounting for the context of sustainability, dealing with space, classifying the ‘nature of research’ and the degree of integration of different facets of sustainability. The framework is demonstrated with an exploratory assessment of the potential for castor bean cultivation within the current farm type of extensive pasture and fodder crops for dairy cattle. The study accounted for the range of productivity levels within the current farm type and for different management decisions when including castor beans. Assessment was made against economic development, livelihood stability and soil fertility criteria. Selected tools and methods included farm surveys, alternative farming system design and input–output calculations. The results demonstrate the greatest opportunity for castor bean cultivation by currently low productive farms. There is a trade-off of income derived from milk production that is supported by fodder production, and income from castor beans. Decisions regarding areal extent of castor beans and supplementing animal feed, are shown to be farm-specific, and depend upon the interactions between current farm productivity and prioritisation of sustainability criteria. However, generally it is shown that castor bean cultivation should be linked to animal production so that current risk management and income levels can be supported and improved. Further, to maintain soil fertility, castor bean cultivation with nitrogen inputs is necessary. The cyclic nature of the framework supports the next contextualisation of the sustainability question. For our application, constructive future work in a next cycle could include extending to regional level and accounting for temporal variability. [Copyright &y& Elsevier]

Abstract: Water pollution in Chinese lakes is a major problem. To reduce nutrient pollution and enhance sustainable development in Taihu Basin, China, an integrated assessment of the impacts of agricultural land use policies has been performed, using the technical coefficient generator TechnoGIN and the bio-economic farm model FSSIM. Results show that although promotion of site-specific nutrient management (SSNM), the first policy, can improve regional objectives such as nutrient pollution reduction and food security, its adoption is constrained by labour productivity and availability at farm level. SSNM is more knowledge and labour intensive than conventional management, whereas labour availability is decreasing due to off-farm employment possibilities. In policy scenarios for 2015, environmental impacts are projected to decrease compared to 2008, partly due to the adoption of SSNM. However, the main reason is the decreasing labour availability towards 2015 which causes a switch from double to single cropping already in the baseline scenario for 2015. This leads to lower food production. Abolishing fertilizer subsidies for farmers that do not adopt SSNM, in combination with training appears to be the best way to stimulate SSNM adoption for improving the different land use functions. A second policy, stimulating mechanical transplanting of rice, reduces labour use and can become profitable when subsidized, but on most farm types it will not reverse the trend towards single cropping and has little influence on nutrient pollution. Thirdly, the regional policy of creating riparian buffer zones along water bodies appears to be promising, as it can strongly reduce nutrient leaching from farm land to rivers and lakes. Concluding, the integrated assessment performed in this study showed that policies can reduce nutrient pollution and improve sustainable development, but the changing labour context has a large impact on their impacts and on agriculture in the region. [Copyright &y& Elsevier]

Abstract: For stimulating sustainable development in developing countries, land use patterns and land use changes are considered critical, and therefore effective and efficient land use policies are needed. In this paper we present a methodological framework that has been developed in a joint European and developing countries project (LUPIS – Land Use Policies and Sustainable Development in Developing Countries), to assess the impact of land use policies on sustainable development in developing countries. An illustrative application is presented for a case study in China, where water pollution due to agriculture in Taihu Basin is a major problem. We argue that an integrated assessment is required, considering multiple drivers and indicators that determine the objectives and constraints of the stakeholders involved. Therefore, the sustainability impact assessment (SIA) is based on the concept of Land Use Functions (LUFs), and impacts on these LUFs are discussed with stakeholders based on a multi-criteria analysis. LUFs comprise economic, environmental and social indicators relevant for stakeholders at multiple scales. Instead of focusing only on the indicators that determine the problem (e.g., nutrient leaching in the Chinese case study), we take a broader perspective (considering also social, economic and institutional objectives and constraints), such that feasible policy options can be recommended. Stakeholders have a large role in discussing the selection of indicators and policies (pre-modelling), evaluating the impacts on indicators (modelling), and the weighing of indicators and LUFs (post-modelling). For the assessment of impacts on indicators (modelling), quantitative and qualitative approaches are combined. We present and discuss an impact assessment of policy options in Taihu Basin, for the current situation and towards 2015. The methodological framework as presented here proved to be useful to guide a sustainability impact assessment in China and six other case study regions. [Copyright &y& Elsevier]

Abstract: A major bottleneck for data-based policy making is that data sources are collected, managed, and distributed by different institutions, residing in different locations, resulting in conceptual and practical problems. The use of dispersed data for agricultural systems research requires the integration of data sources, which means to ensure consistency in data interpretations, units, spatial and temporal scales, to respect legal regulations of privacy, ownership and copyright, and to enable easy dissemination of data. This paper describes the SEAMLESS integrated database on European agricultural systems. It contains data on cropping patterns, production, farm structural data, soil and climate conditions, current agricultural management and policy information. To arrive at one integrated database, a shared ontology was developed according to a collaborative process, which facilitates interdisciplinary research. The paper details this process, which can be re-used in other research projects for integrating data sources. [Copyright &y& Elsevier]

Abstract: Agriculture is interrelated with the socio-economic and natural environment and faces increasingly the problem of managing its multiple functions in a sustainable way. Growing emphasis is on adequate policies that can support both agriculture and sustainable development. Integrated Assessment and Modelling (IAM) can provide insight into the potential impacts of policy changes. An increasing number of Integrated Assessment (IA) models are being developed, but these are mainly monolithic and are targeted to answer specific problems. Approaches that allow flexible IA for a range of issues and functions are scarce. Recently, a methodology for policy support in agriculture has been developed that attempts to overcome some of the limitations of earlier IA models. The proposed framework (SEAMLESS-IF) integrates relationships and processes across disciplines and scales and combines quantitative analysis with qualitative judgments and experiences. It builds on the concept of systems analysis and attempts to enable flexible coupling of models and tools. The present paper aims to describe progress in improving flexibility of IAM achieved with the methodology developed for SEAMLESS-IF. A brief literature review identifying limitations in the flexibility of IAM is followed by a description of the progress achieved with SEAMLESS-IF. Two example applications are used to illustrate relevant capabilities of SEAMLESS-IF. The examples refer to (i) the impacts on European agriculture of changes in world trade regulations and (ii) regional impacts of the EU Nitrates Directive in combination with agro-management changes. We show that improving the flexibility of IAM requires flexibility in model linking but also a generic set up of all IA steps. This includes problem and scenario definition, the selection and specification of indicators and the indicator framework, the structuring of the database, and the visualization of results. Very important is the flexibility to integrate, select and link models, data and indicators depending on the application. Technical coupling and reusability of model components is greatly improved through adequate software architecture (SEAMLESS-IF uses OpenMI). The use of ontology strongly supports conceptual consistency of model linkages. However, the scientific basis for linking models across disciplines and scales is still weak and requires specific attention in future research. We conclude that the proposed framework significantly advances flexibility in IAM and that it is a good basis to further improve integrated modelling for policy impact assessment in agriculture. [Copyright &y& Elsevier]

Abstract: Agricultural systems continuously evolve and are forced to change as a result of a range of global and local driving forces. Agricultural technologies and agricultural, environmental and rural development policies are increasingly designed to contribute to the sustainability of agricultural systems and to enhance contributions of agricultural systems to sustainable development at large. The effectiveness and efficiency of such policies and technological developments in realizing desired contributions could be greatly enhanced if the quality of their ex-ante assessments were improved. Four key challenges and requirements to make research tools more useful for integrated assessment in the European Union were defined in interactions between scientists and the European Commission (EC), i.e., overcoming the gap between micro–macro level analysis, the bias in integrated assessments towards either economic or environmental issues, the poor re-use of models and hindrances in technical linkage of models. Tools for integrated assessment must have multi-scale capabilities and preferably be generic and flexible such that they can deal with a broad variety of policy questions. At the same time, to be useful for scientists, the framework must facilitate state-of-the-art science both on aspects of the agricultural systems and on integration. This paper presents the rationale, design and illustration of a component-based framework for agricultural systems (SEAMLESS Integrated Framework) to assess, ex-ante, agricultural and agri-environmental policies and technologies across a range of scales, from field–farm to region and European Union, as well as some global interactions. We have opted for a framework to link individual model and data components and a software infrastructure that allows a flexible (re-)use and linkage of components. The paper outlines the software infrastructure, indicators and model and data components. The illustrative example assesses effects of a trade liberalisation proposal on EU’s agriculture and indicates how SEAMLESS addresses the four identified challenges for integrated assessment tools, i.e., linking micro and macro analysis, assessing economic, environmental, social and institutional indicators, (re-)using standalone model components for field, farm and market analysis and their conceptual and technical linkage. [Copyright &y& Elsevier]

Abstract: Decisions and policies that have implications on allocation of resources are made at different levels. Goals at different scales may be conflicting and decisions at one scale have consequences for those at other scales. Performing analyses at more than one scale is, therefore necessary in analysing future options for resource use. This paper illustrates the use of a multi-scale method enabling assessment of multi-purpose natural resource management options. Three examples of analyses that it allows are presented for Ilocos Norte province in the Philippines, at the farm household, municipal (Batac municipality) and provincial levels. Results show that: (1) Differences in resource endowments of farm households strongly affect the potential adoption rates of five well-defined alternative technologies. (2) Limited markets, inadequate infrastructure and resource endowments of farm households have large effects on resource use and goal achievement in the municipality. Not including these factors in a resource use analysis results in a so-called aggregation bias. As these are significant, ignoring them may result in misleading simulation results and policy conclusions. The aggregation bias resulting from assuming spatially fixed input and output prices is significant for Batac, which has poor farm-to-market roads. This suggests large potential benefits from improving infrastructure. The factors investigated suggest that aggregate income in the municipality is most strongly affected by the size of the market for some vegetables. (3) The differences in resource allocations resulting from prioritizing objectives at different levels reveal potential conflicts. The municipal income was highest with crops which pose more risk to farmers; our farm household analysis shows that farmers tend not to select too much of these crops. Similarly, the provincial income is highest when resources in the province are allocated such that more of the staple crop rice and less of the highly profitable cash crops are cultivated in Batac, resulting in lower income for the municipality. It is anticipated that the presented multi-scale approach will provide valuable information for joint-learning, policy discussions and decision-making regarding agricultural land use. [Copyright &y& Elsevier]

Abstract: Bio-economic farm models (BEFMs) are developed to enable assessment of policy changes and technological innovations, for specific categories of farming systems. A rapidly growing number of research projects is using these models and there is increasing interest for application. The paper critically reviews past publications and applications of BEFMs on their strengths and weaknesses in assessing technological innovation and policy changes for farmers and policy makers and highlights key issues that require more attention in the use and methodology of BEFMs. A BEFM is defined as a model that links formulations describing farmers’ resource management decisions to formulations that represent current and alternative production possibilities in terms of required inputs to achieve certain outputs, both yield and environmental effects. Mechanistic BEFMs are based on available theory and knowledge of farm processes and these were the focus of our study. Forty-eight applications of mechanistic BEFMs were reviewed as to their incorporation of farmer decision making and agricultural activities, comprehensiveness, model evaluation, and transferability. A clear description of end-use of the BEFM, agricultural activities, model equations and model evaluation are identified as good practices and a research agenda is proposed including the following issues: 1. development of a thorough and consistent procedure for model evaluation; 2. better understanding and modelling of farmer decision making and possible effects of the social milieu; 3. inclusion of several economic and environmental aspects of farming including multifunctionality and 4. development of a generic, modular and easily transferable BEFM. [Copyright &y& Elsevier]

• The framework of the EU N Expert Panel was applied to farmer field data covering the period 2015–2017. • N-use efficiency (NUE) was on average 0.7–1.0 kg N kg−1 N for Dutch arable crops. • Annual N surplus (Ns) was on average 20–80 kg N ha−1 for Dutch arable crops. • In Dutch farming, technological advances without reducing N inputs are unlikely to improve NUE or N surplus. • Highest NUE and lowest Ns can be achieved with mineral fertilisers, which comes with trade-offs at national level. Nitrogen (N) management is important for farmers to balance production, economic and environmental performance of their farms. This is particularly true in the intensive cropping systems of northwest Europe where tuber, root and bulb crops are cultivated in rotation with cereal crops and where an intensive livestock sector makes organic manures available at low cost for arable farmers. Here, we build upon a large database of farmer field data to assess mineral and organic fertiliser N performance, and its determinants, for the major arable crops in the Netherlands according to the guidelines provided by the EU N Expert Panel (EUNEP). The EUNEP framework quantifies N outputs and N inputs, N-use efficiency as the ratio between N outputs and N inputs (NUE in kg N output harvested per kg N input) and N surplus as the difference between N inputs and N outputs (Ns in kg N ha−1). As a next step, biophysical and crop management determinants of N performance were explored using data from different years, soil types and N management in relation to the amount, source, time and method of N applied. NUE was on average ca. 0.95 kg N kg−1 N for seed potato, sugar beet and spring onion, 0.87 kg N kg−1 N for ware potato, ca. 0.80 kg N kg−1 N for starch potato and winter wheat and, ca. 0.70 kg N kg−1 N for spring barley, all within or above the target range of 0.50–0.90 kg N kg−1 N proposed by the EUNEP. Ns was on average below the EUNEP threshold of 80 kg N ha−1 for all crops: 78 kg N ha−1 for ware potato and winter wheat, ca. 70 kg N ha−1 for starch potato, ca. 50 kg N ha−1 for spring barley, ca. 25 kg N ha−1 for sugar beet and spring onion and less than 20 kg N ha−1 for seed potato. Although average Ns was below 80 kg N ha−1, ca. 40% of the ware potato, starch potato and winter wheat fields analyzed had Ns above this threshold. The relatively high NUE combined with high Ns for most crops are the result of high N outputs (yields) combined with high N application rates. Moreover, high NUE and small Ns were mostly associated with smaller N application rates and with the use of mineral fertilisers instead of organic fertilisers, while there were no clear relationships between the two indicators on the one hand with N application time or method on the other. We conclude NUE and Ns were on average within the EUNEP target range for most crops, but there are still a considerable number of under-performing farms where increases in NUE and reductions in Ns are possible through reducing N inputs. We recommend future research to assess the benefits of organic fertilisers from a circularity perspective at regional and national levels and to cross-validate the crop-specific results presented in this study with NUE assessments at cropping systems level. [ABSTRACT FROM AUTHOR]

Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on farming systems analysis and integrated assessment. With a case study for arable farming in Flevoland, the Netherlands (Reidsma et al., 2015), we illustrate that 1) crop models cannot account for all relevant climate change impacts and adaptation options, and 2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semi-quantitative and participatory method assessing impacts of extreme events, shows that there are nevertheless several climate risks (Schaap et al., 2013). A range of adaptation measures are however available to reduce possible negative effects at crop level. In addition, at farm level, farmers can change cropping patterns, and adjust inputs and outputs (Kanellopoulos et al., 2014). Also farm structural change will influence impacts and adaptation (Mandryk et al., 2012). While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at farm level, impacts may be less negative and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world. [ABSTRACT FROM AUTHOR]

Arable farming systems in the Netherlands are characterized by crop rotations in which potato, sugar beet, spring onion, winter wheat and spring barley are the most important crops. The objectives of this study were to decompose crop yield gaps within such rotations into efficiency, resource and technology yield gaps and to explain those yield gaps based on observed cropping frequencies and alternative farmers' objectives. Data from specialized Dutch arable farms between 2008 and 2012 were used. Production frontiers and efficiency yield gaps were estimated using the stochastic frontier framework. The resource yield gap was quantified through the estimation of highest farmers' yields (Y HF , average across farms with actual yields above the 90th percentile). Crop model simulations and variety trials were compiled to assess climatic potential yields (Yp) and technology yield gaps. The contribution of crop area shares and farmers' objectives to actual yields were assessed using regression analysis and based on five different farm level indicators (N production, energy production, gross margin, nitrogen-use efficiency and labour use), respectively. The average yield gap per crop (as percentage of Yp which is given in parentheses) was: 29.2% (of 72.6 t ha −1 ) for ware potato, 39.7% (of 71.6 t ha −1 ) for starch potato, 26.4% (of 107.1 t ha −1 ) for sugar beet, 32.3% (of 88.3 t ha −1 ) for spring onion, 25.2% (of 12.3 t ha −1 ) for winter wheat and 37.5% (of 10.4 t ha −1 ) for spring barley. The efficiency yield gap ranged between 6.6% (starch potato) and 18.1% (spring onion) of Yp. The resource yield gap was lower than 10% of Yp for all the crops and the technology yield gap ranged between 7.1% (ware potato) and 30.7% of Yp (starch potato). There were statistically significant effects of potato (positive quadratic) and onion (positive) area shares on ware potato, sugar beet and winter wheat yields, of sugar beet area share (positive quadratic) on winter wheat yield and of cereal area share (negative) on sugar beet and winter wheat yields. Farmers' objectives explain part of the variability observed in crop yields which were 7–24%, 13–24% and 12–32% lower than Y HF , respectively, for gross margin maximising, labour minimising and N use efficiency maximising farms. In addition, there was a significant positive relationship between gross margin and the yield of ware potato, sugar beet and winter wheat. By contrast, no significant relationships were found between crop yields and NUE or labour use. We conclude that most of the yield gap is explained by the efficiency yield gap for ware potato and spring onion and by both the efficiency and technology yield gaps for sugar beet and cereals. The resource yield gap explains most of the yield gap of seed potato, and the technology yield gap of starch potato. The results regarding the effects of cropping frequency and crop rotations to crop yields are not very conclusive which suggest that agronomic principles become less evident at ‘systems level’ given the number of interacting factors at crop rotation level. Finally, although N and energy production are lower for gross margin maximising farms, most crop yields are not significantly different between farms with the highest N and energy production compared to farms performing best on economic (gross margin) objectives. [ABSTRACT FROM AUTHOR]

Climate change is expressed in both a shift of mean climatic conditions and an increase in the frequency and severity of weather extremes. The weather extremes are often projected to have a larger impact on agricultural production than the average increase in temperature or average change in precipitation. To cope with the impacts of future climate change, farmers will have to apply adaptation measures at crop and farm level. The choice of the adaptation measures is determined by farm resources, current layout and performance of the farm and farmers' objectives. Here we present a method to assess the importance of crop and farm level measures to adapt to climate change and extreme events considering farmers' different objectives. We used a multi-objective optimization model to generate alternative farm plans and assess the impacts of crop and farm level adaptation measures in terms of farm performance on the objectives of maximizing farm economic result (gross margin) and soil quality (soil organic matter balance); these objectives were previously identified as most important to farmers. Two local scenarios were investigated: one based on a 2 °C increase in global temperature in 2050, including changes in air circulation resulting in drier summers, and one based on a 1 °C increase in global temperature, without changes in air circulation. Our results for six surveyed arable farms in the province of Flevoland (the Netherlands) suggest that average climate change improves farm performance in terms of farm economic result. The degree of improvement varies per scenario and per farm, depending on the cropping pattern. At the same time, extreme events may reverse positive impacts of average climate change, and can pose large risks. A combination of crop and farm level adaptation is needed for the surveyed farms in terms of improving both farm economic result and organic matter balance. A shift to (more) winter wheat, in systems dominated by root crops, is an estimated effective strategy to improve the organic matter balance and maintain farm economic result under climate change and extreme events. [ABSTRACT FROM AUTHOR]

With many of the poor people in Brazil living in rural areas, local governments have intensified their efforts to design and implement effective policies that boost rural development. In 2004, a national program for production and use of biodiesel was launched aiming at increasing income among less endowed family farmers across the country. With expectations building on further expansion of the mandatory blending of biodiesel with fossil diesel, national and local government bodies are challenged by the search for policies able to foster biodiesel crop production through the wider cultivation of crops that produce more oil than soybean (e.g. sunflower and castor bean) and by improving the participation of less endowed farmers, especially in semi-arid regions. Therefore, the objective of this study was to perform an ex-ante integrated assessment of the socioeconomic and environmental impacts of four biodiesel policy scenarios towards different farm types in a semi-arid and more humid region of southeast Brazil. The applied modelling framework was a combination of a technical coefficient generator (TechnoGIN) and a bio-economic farm model (FSSIM). We explored the impact of market-driven (bonus price policy), input provision (fertiliser and land preparation policy) and oil production (oil mill policy) policy scenarios on soybean farmers in Chapada Gaúcha and maize/beans farmers in Montes Claros. The impacts of the different policies on farm gross margins, oil crop production, labour requirements, nitrogen losses and biocide residues were assessed against the baseline scenario. Our results indicated that the scope for biodiesel crops on smallholder, non-soybean producers in Montes Claros is less evident than in Chapada Gaúcha, particularly among the less endowed farmers for whom the increase in farm gross margin in all scenarios is limited to only 6% while oil production was 140 kg per farm, which is very low compared to the 41% increase and more than 48,000 kg of oil of soybean producers. The most effective policy scenario was the provision of inputs such as fertiliser and land preparation. Because in Montes Claros farmers have limited access to fertiliser, machinery and biocides, strategies that enable farmers to increase their cropped area (i.e. land preparation policy more than doubled the crop area) and crop yield levels (i.e. fertiliser policy almost quadrupled crop yields) have highest potential to benefit these farming systems. [ABSTRACT FROM AUTHOR]

Highlights: [•] Miscanthus and black locust are resource-efficient, low impact biofuel crops. [•] Black locust produces biomass on degraded soils and rehabilitates these soils. [•] Sugarbeet and rapeseed are resource-inefficient, high impact biofuel crops. [ABSTRACT FROM AUTHOR]

In the Central Rift Valley of Ethiopia (CRV), actual productivity of most cereals is less than 3 t ha−1 associated with low input use and poor crop management. After calibrating and validating the Agricultural Production System Simulator (APSIM) using experimental data, we explored and prioritized promising intensification options for rainfed maize and wheat that enable to narrow prevailing yield gaps in the CRV, and quantified trade-offs with the water balance and gross margins. We set up a factorial simulation experiment combining Genetic x Environment x Management factors that influence crop yield and water use at field scale to simulate yield and water balance components under current and future climate scenarios (pessimistic scenario for mid-century). Varietal selection and nitrogen (N) fertilization were the most important factors contributing to yield gap closure. Although yields were maximized with N application rates up to 250 kg−1 in most soils and varieties, maximum gross margin and maximum water use efficiency (WUE) were attained at lower N rates, associated with a small yield reduction compared to the maximum. There was a trade-off between intensification and increased absolute water use through transpiration, while the water use per kg product was decreased. However, location-specific N application rates that allow producing at least 80% of the water-limited potential yield (Yw) of maize and wheat resulted in high water use efficiencies as well as favorable cost-benefit ratios. Climate change was projected to lower yield as it advanced maturity, and to result in decreased drainage and increased soil evaporation across all variety, location and management combinations for both crops. Climate change reduced crop yield by 15–25% for wheat and 2–30% for maize. We conclude that the locally-calibrated APSIM model could be used to derive key lessons from the genetic, environment and management interactions, and generate information on sustainable intensification pathways that combine narrowing yield gaps with maximizing WUE and gross margins. • Variety selection and N fertilization contribute most to closing yield gaps (Yg) • Yg can be narrowed at N rates that maximize water use efficiency and gross margin • The potential for yield gap closure is crop, variety, soil and climate specific • Crop intensification increases total water use but decreases water per kg product • Climate change reduces land productivity by 15–25% for wheat and 2–30% for maize [ABSTRACT FROM AUTHOR]

Abstract: A key issue in the debate on the contribution of organic agriculture to the future of world agriculture is whether organic agriculture can produce sufficient food to feed the world. Comparisons of organic and conventional yields play a central role in this debate. We therefore compiled and analyzed a meta-dataset of 362 published organic–conventional comparative crop yields. Our results show that organic yields of individual crops are on average 80% of conventional yields, but variation is substantial (standard deviation 21%). In our dataset, the organic yield gap significantly differed between crop groups and regions. The analysis gave some support to our hypothesis that the organic–conventional yield gap increases as conventional yields increase, but this relationship was only rather weak. The rationale behind this hypothesis is that when conventional yields are high and relatively close to the potential or water-limited level, nutrient stress must, as per definition of the potential or water-limited yield levels, be low and pests and diseases well controlled, which are conditions more difficult to attain in organic agriculture. We discuss our findings in the context of the literature on this subject and address the issue of upscaling our results to higher system levels. Our analysis was at field and crop level. We hypothesize that due to challenges in the maintenance of nutrient availability in organic systems at crop rotation, farm and regional level, the average yield gap between conventional and organic systems may be larger than 20% at higher system levels. This relates in particular to the role of legumes in the rotation and the farming system, and to the availability of (organic) manure at the farm and regional levels. Future research should therefore focus on assessing the relative performance of both types of agriculture at higher system levels, i.e. the farm, regional and global system levels, and should in that context pay particular attention to nutrient availability in both organic and conventional agriculture. [Copyright &y& Elsevier]

Abstract: We compared the production–ecological sustainability of biofuel production from several major crops that are also commonly used for production of food or feed, based on current production practices in major production areas. The set of nine sustainability indicators focused on resource use efficiency, soil quality, net energy production and greenhouse gas emissions, disregarding socio-economic or biodiversity aspects and land use change. Based on these nine production–ecological indicators and attributing equal importance to each indicator, biofuel produced from oil palm (South East Asia), sugarcane (Brazil) and sweet sorghum (China) appeared most sustainable: these crops make the most efficient use of land, water, nitrogen and energy resources, while pesticide applications are relatively low in relation to the net energy produced. Provided there is no land use change, greenhouse gas emissions of these three biofuels are substantially reduced compared with fossil fuels. Oil palm was most sustainable with respect to the maintenance of soil quality. Maize (USA) and wheat (Northwest Europe) as feedstock for ethanol perform poorly for nearly all indicators. Sugar beet (Northwest Europe), cassava (Thailand), rapeseed (Northwest Europe) and soybean (USA) take an intermediate position. [Copyright &y& Elsevier]

The difference between the theoretical maximum (potential) production and the actual production realized by farmers is referred to as the yield gap. The objectives of this study are to develop a mechanistic model for dairy cows that allows yield gap analysis in dairy production systems and to evaluate model performance. We extended and adapted an existing model for beef cattle to dairy cattle, and the new model was named Livestock simulator for Generic analysis of Animal Production Systems—Dairy cattle (LiGAPS-Dairy). Milk production and growth of an individual cow over its entire lifespan were described as a function of the animal's genotype, the ambient climate, feed quality, and available feed quantity. The model was parameterized for Holstein-Friesian cows. After calibration, we evaluated model performance by comparing simulated results and measured results from experimental farms in the Netherlands, which were not used for model calibration. Cows were permanently housed in stables, where the diet consisted of predetermined amounts of concentrates and ad libitum high-quality roughage. The mean absolute error (MAE) for simulated milk production per lactation was 12% of the measured milk production, whereas the MAE for simulated daily milk yields was 19%. The MAE for simulated feed intake per lactation was 10% of the measured feed intake, whereas the MAE for simulated daily feed intake was 19%. The average yield gap for dairy cows was 11% of the potential milk production (Y P). Yield gap analysis indicated that for experimental farms in the Netherlands, the difference between Y P and feed quality limited milk production (Y L) of 1,009 kg fat- and protein-corrected milk was mainly explained by feed intake capacity (33%), protein deficiency (25%), cow weight at the start of experiments (23%), and heat stress (19%). The LiGAPS-Dairy model also indicated the periods during lactation in which these factors affected milk production. In our opinion, the overall model performance is acceptable for permanently housed cows under Dutch conditions. The model needs to be evaluated further for other production systems, countries and breeds. Thereafter, LiGAPS-Dairy can be used for yield gap analysis and exploration of options to increase resource use efficiency in dairy production. [ABSTRACT FROM AUTHOR]

Dietary changes are closely intertwined with land use changes, and understanding the relative importance of different food items and their driving forces is crucial. Here, we analyzed the changes in China's global cropland footprint for food and feed consumption from 1987 to 2013 and explored the driving forces behind these changes for each food item. China's per capita protein consumption increased by 57%. The global cropland footprint of China's food and feed consumption expanded by 40% during this period. Decomposition analysis demonstrated that population growth was the primary driver of the increased total cropland footprint until 1993, with the subsequent rise in per capita protein consumption becoming the driving force. Thereafter, the increased efficiency of cropland use offset 49% of the total cropland expansion primarily due to improved management technologies. Among the food items analyzed, pork, eggs, and vegetables were identified as the main contributors to the increased total cropland footprint, primarily driven by changes in dietary patterns and their increased inclusion in the human diet. In conclusion, changing human diet towards less monogastric livestock products and improving productivity of concentrate feed crops are essential for mitigating domestic land pressure and ecological degradation in exporting countries. [ABSTRACT FROM AUTHOR]

• Estimated maize yield gaps ranged between 67% and 84% of water-limited potential yield. • Demonstration experiments showed the potential of improved varieties and fertilizers. • Farmers' yields are determined by interacting, and often strongly varying, household, soil and management factors. • Integrated assessment of yield gaps using multiple methods avoids over-simplified conclusions. Agricultural production in Ghana should more than double to fulfil the estimated food demand in 2050, but this is a challenge as the productivity of food crops has been low, extremely variable and prone to stagnation. Yield gap estimations and explanations can help to identify the potential for intensification on existing agricultural land. However, to date most yield gap analyses had a disciplinary focus. The objective of this paper is to assess the impact of crop management, soil and household factors on maize (Zea mays) yields in two major maize growing regions in Ghana through an integrated approach. We applied a variety of complementary methods to study sites in the Brong Ahafo and Northern region. Farm household surveys, yield measurements and soil sampling were undertaken in 2015 and 2016. Water-limited potential yield (Y w) was estimated with a crop growth simulation model, and two different on-farm demonstration experiments were carried out in 2016 and 2017. There is great potential to increase maize yields across the study sites. Estimated yield gaps ranged between 3.8 Mg ha−1 (67% of Y w) and 13.6 Mg ha−1 (84% of Y w). However, there was no consistency in factors affecting maize yield and yield gaps when using complementary methods. Demonstration experiments showed the potential of improved varieties, fertilizers and improved planting densities, with yields up to 9 Mg ha−1. This was not confirmed in the analysis of the household surveys, as the large yield variation across years on the same farms impeded the disclosure of effects of management, soil and household factors. The low-input nature of the farming system and the incidence of fall armyworm led to relatively uniform and low yields across the entire population. So, farmers' yields were determined by interacting, and strongly varying, household, soil and management factors. We found that for highly variable and complex smallholder farming systems there is a danger in drawing oversimplified conclusions based on results from a single methodological approach. Integrating household surveys, crop growth simulation modelling and demonstration experiments can add value to yield gap analysis. However, the challenge remains to improve upon this type of integrated assessment to be able to satisfactorily disentangle the interacting factors that can be managed by farmers in order to increase crop yields. [ABSTRACT FROM AUTHOR]

Highlights • We quantify yield gaps for major grain legume crops in East Africa. • Average yield gap represents 75% of water-limited yield potential. • There is ample room for increasing legume production on existing cropland. • Closure of exploitable yield gap meets future legume demand in Kenya and Tanzania. • Exploitable yield gap closure is not sufficient to meet future legume demand in Ethiopia. Abstract Agricultural production in East Africa (E-Afr) has to increase drastically to meet future food demand. Yield gap assessment provides important information on the degree to which production can be increased on existing cropland. Most research on yield gap analysis has focussed on cereal crops, while legumes have received less attention despite of their relatively large area, and their importance as source of protein in smallholder farming systems in E-Afr. The objectives of this study were to (i) estimate water-limited yield potential (Y w) and yield gaps (Y g) for major grain legume crops in E-Afr, and (ii) estimate how narrowing the current legume Y g can contribute to food self-sufficiency by the year 2050. We focussed on Ethiopia, Kenya, and Tanzania, and five legumes crops including chickpea, common bean, cowpea, groundnut, and pigeonpea. A bottom-up approach which entails that local weather, soil and agronomic data was used as input for crop modelling (SSM-legumes) in a spatial framework, to estimate Y w , actual on-farm yield (Y a), and Y g from local to regional scale. Future legume self-sufficiency was assessed for 2050 demand assuming different Y g closure scenarios. On average, Y a was 25% of Y w across all legume-county combinations, being 15% for Kenya, 23% for Tanzania and 41% for Ethiopia. On average, common bean had the largest Y g of 2.6 Mg ha−1and chickpea the smallest (1.4 Mg ha−1). Closure of the exploitable Y g (i.e., 80% of Y w) can help to meet future legume demand in both Kenya and Tanzania, while it seems not to be sufficient in Ethiopia. [ABSTRACT FROM AUTHOR]