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Purpose: To reduce the environmental impact of Western diets, a reduction of meat consumption and a substitution by plant-based protein sources is needed. This protein transition will affect the quantity and quality of dietary protein. Therefore, the aim of this study was to evaluate the protein adequacy of diets optimized for nutritional health and diet-related greenhouse gas emission (GHGE). Methods: Data from 2150 adult participants of the Dutch National Food Consumption Survey were used, with diet assessed using two non-consecutive 24 h dietary recalls. Utilizable protein of current diets per day was based on meal composition and the Protein Digestibility-Corrected Amino Acid Score and was compared to protein requirements. Optimized diets were derived as linear combinations of current diets that minimized GHGE and maximized the Dutch Healthy Diet 2015 score, with/without constraints to keep dietary change within 33% of current consumption. Protein adequacy was evaluated in both current and optimized diets. Results: In all age and gender strata, the healthiest diets had higher GHGE, the most sustainable diets had the lowest dietary quality, though higher than current diets, and protein adequacy remained sufficient. When limiting dietary change to 33% of current consumption, in the most promising trade-off diet GHGE was reduced by 12–16%. The current diet provided 1.4–2.2 times the required amount of utilizable protein. Conclusion: These results suggest that a realistic aim for the next decade might be to reduce diet-related GHGE to 12–16% of the current levels without compromising protein adequacy and diet quality. To achieve global targets, upstream food system transformations are needed with subsequent dietary changes. [ABSTRACT FROM AUTHOR]

Objective: The objective of this research is to propose methodology that can be used to benchmark current diets based on their nutrient intakes and to provide guidelines for improving less healthy diets in a way that is acceptable for the studied population.Design: We discuss important limitations of current diet models that use optimisation techniques to design healthier and acceptable diets. We illustrate how data envelopment analysis could be used to overcome such limitations, and we describe mathematical models that can be used to calculate not only healthier but also acceptable diets.Setting: We used data from the Nutrition Questionnaires plus dataset of habitual diets of a general population of adult men and women in The Netherlands (n 1735).Participants: Adult population.Results: We calculated healthier diets with substantial higher intakes of protein, fibre, Fe, Ca, K, Mg and vitamins, and substantially lower intakes of Na, saturated fats and added sugars. The calculated diets are combinations of current diets of individuals that belong to the same age/gender group and comprise of food item intakes in proportions observed in the sample.Conclusions: The proposed methodology enables the benchmarking of existing diets and provides a framework for proposing healthier alternative diets that resemble the current diet in terms of foods intake as much as possible. [ABSTRACT FROM AUTHOR]

Abstract Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains. Highlights • A bi-objective stochastic programming model is implemented for a real-life case. • Trade-offs between environmental and economic indicators are quantified. • Solutions of deterministic models overestimate the actual trade-off. • Accounting for uncertainty improves the environmental performance. [ABSTRACT FROM AUTHOR]

Abstract Sustainability concerns emphasise the importance of identifying eco-efficient supply chain configurations which balance economic and environmental chain objectives. The applied modelling approaches for this purpose often assume the availability of raw materials and full coordination within the supply chain studied. Some or all actors in the chain can however pursue individual objectives, making the obtained solutions unfeasible in practice. Economic incentives support aligning the objectives of the different supply chain actors. This paper explores the design of eco-efficient biomass supply chains and economic gain allocation between the supply chain partners. A case study is developed for the sugar beet processing chain in the Netherlands, in which farmers can also choose to produce other competing crops. We observe that higher yields often lead to lower carbon emissions per ton of produce. Hence, eco-efficient solutions are found to have production and processing locations in the most productive regions. Additionally, margin sharing above the minimum sugar beet price is necessary to ensure the production of the desired quantity of sugar beet. Realistic sugar beet prices are determined using a Shapley-value approach, leading to a fair distribution of margin among the farmers and processor in the supply chain. Highlights • We design eco-efficient biomass supply chains using multi-actor optimisation models. • Competing crops, production dependent prices, and regional features are considered. • We use the sugar beet processing chain in the Netherlands as an example. • Fair distribution of benefits is needed to make optimal designs attractive. • Locating refineries in regions with productive soils leads to eco-efficient chain designs. [ABSTRACT FROM AUTHOR]

Temperature-controlled transport is needed to maintain the quality of products such as fresh and frozen foods and pharmaceuticals. Road transportation is responsible for a considerable part of global emissions. Temperature-controlled transportation exhausts even more emissions than ambient temperature transport because of the extra fuel requirements for cooling and because of leakage of refrigerant. The transportation sector is under pressure to improve both its environmental and economic performance. To explore opportunities to reach this goal, the Load-Dependent Vehicle Routing Problem (LDVRP) model has been developed to optimize routing decisions taking into account fuel consumption and emissions related to the load of the vehicle. However, this model does not take refrigeration related emissions into account. We therefore propose an extension of the LDVRP model to optimize routing decisions and to account for refrigeration emissions in temperature-controlled transportation systems. This extended LDVRP model is applied in a case study in the Dutch frozen food industry. We show that taking the emissions caused by refrigeration in road transportation can result in different optimal routes and speeds compared with the LDVRP model and the standard Vehicle Routing Problem model. Moreover, taking the emissions caused by refrigeration into account improves the estimation of emissions related to temperature-controlled transportation. This model can help to reduce emissions of temperature-controlled road transportation. [ABSTRACT FROM AUTHOR]

Due to tremendous losses of resources in modern food supply chains, higher priority should be given to reducing food waste and environmental impacts of food production. In practice, multiple production options are available, but must be quantitatively assessed with respect to economic and environmental performances before they are adopted in food supply chains. The objective of this paper is to develop a mathematical model that can be used for such a quantitative assessment of alternative production options that are associated with different ways to deal with waste in food supply chains, i.e. prevention, recycling, and disposal of food waste. We develop a multi-objective mixed integer linear programming model to derive the set of eco-efficient solutions corresponding to production planning decisions. Environmental performance of the chain is expressed with an indicator based on exergy analysis, which has the potential to capture other commonly used indicators, such as energy consumption, fuel consumption, and waste generation, and express them in a single value. This simplifies the calculation of the eco-efficient frontier, and enables its intuitive graphical representation, which is much easier to communicate to the involved decision makers. The applicability of the developed model is demonstrated on a real-life industrial bread supply chain in the Netherlands. Results confirm the findings from literature that prevention is the best waste management strategy from environmental perspective. The advantages of using exergy as an indicator to capture the environmental performance is demonstrated by comparing the outcomes to other commonly used indicators of environmental performance. We illustrate the potential of studying food production planning decision problems in a multi-objective context, and demonstrate the applicability of the model in the assessment of alternative production options. [ABSTRACT FROM AUTHOR]

In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenées, Zachodniopomorski and Andalucia). These analyses were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern–Central EU regions, in practically unchanged farm net incomes in the Central and Central–Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N 2 O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH 3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenées, and strongly decrease in Andalucia, except for NH 3 emissions which zero to moderately decrease in Flevoland and Denmark. [ABSTRACT FROM AUTHOR]

Abstract: The disciplinary nature of most existing farm models as well as the issue specific orientation of most of the studies in agricultural systems research are main reasons for the limited use and re-use of bio-economic modelling for the ex-ante integrated assessment of policy decisions. The objective of this article is to present a bio-economic farm model that is generic and re-usable for different bio-physical and socio-economic contexts, facilitating the linking of micro and macro analysis or to provide detailed analysis of farming systems in a specific region. Model use is illustrated in this paper with an analysis of the impacts of the CAP reform of 2003 for arable and livestock farms in a context of market liberalization. Results from the application of the model to representative farms in Flevoland (the Netherlands) and Midi-Pyrenees (France) shows that CAP reform 2003 under market liberalization will cause substantial substitution of root crops and durum wheat by vegetables and oilseed crops. Much of the set-aside area will be put into production intensifying the existing farming systems. Abolishment of the milk quota system will cause an increase of the average herd size. The average total gross margin of farm types in Flevoland decreases while the average total gross margin of farms in Midi-Pyrenees increases. The results show that the model can simulate arable and livestock farm types of two regions different from a bio-physical and socio-economic point of view and it can deal with a variety of policy instruments. The examples show that the model can be (re-)used as a basis for future research and as a comprehensive tool for future policy analysis. [ABSTRACT FROM AUTHOR]

Using linear programming in bio-economic farm modelling often results in overspecialised model solutions. The positive mathematical programming (PMP) approach guarantees exact calibration to base year data but the forecasting capacity of the model is affected by necessary but arbitrary assumptions imposed during calibration. In this article, a new PMP variant is presented which is based on less arbitrary assumptions that, from a theoretical point of view, are closer to the actual decision making of the farmer. The PMP variant is evaluated according to the predictions of the bio-economic farm model, developed within the framework for integrated assessment of agricultural systems in Europe (SEAMLESS). The forecasting capacity of the model calibrated with the standard PMP approach and the alternative PMP variant, respectively, is tested in ex-post experiments for the arable farm types of Flevoland (the Netherlands) and Midi-Pyrenees (France). The results of the ex-post experiments, in which we try to simulate farm responses in 2003 using a model calibrated to 1999 data, show that the alternative PMP variant improves the forecasting capacity of the model in all tested cases. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to identify diets with improved nutrient quality and environmental impact within the boundaries of dietary practices. Design: We used Data Envelopment Analysis to benchmark diets for improved adherence to food-based dietary guidelines (FBDG). We then optimised these diets for dietary preferences, nutrient quality and environmental impact. Diets were evaluated using the Nutrient Rich Diet score (NRD15.3), diet-related greenhouse gas emission (GHGE) and a diet similarity index that quantified the proportion of food intake that remained similar as compared with the observed diet. Setting: National dietary surveys of four European countries (Denmark, Czech Republic, Italy and France). Subjects: Approximately 6500 adults, aged 18–64 years. Results: When dietary preferences were prioritised, NRD15·3 was ~6 % higher, GHGE was ~4 % lower and ~85 % of food intake remained similar. This diet had higher amounts of fruit, vegetables and whole grains than the observed diet. When nutrient quality was prioritised, NRD15·3 was ~16 % higher, GHGE was ~3 % lower and ~72 % of food intake remained similar. This diet had higher amounts of legumes and fish and lower amounts of sweetened and alcoholic beverages. Finally, when environmental impact was prioritised, NRD15·3 was ~9 % higher, GHGE was ~21 % lower and ~73 % of food intake remained similar. In this diet, red and processed meat partly shifted to either eggs, poultry, fish or dairy. Conclusions: Benchmark modelling can generate diets with improved adherence to FBDG within the boundaries of dietary practices, but fully maximising health and minimising GHGE cannot be achieved simultaneously. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to identify diets with improved nutrient quality and environmental impact within the boundaries of dietary practices.Design: We used Data Envelopment Analysis to benchmark diets for improved adherence to food-based dietary guidelines (FBDG). We then optimised these diets for dietary preferences, nutrient quality and environmental impact. Diets were evaluated using the Nutrient Rich Diet score (NRD15.3), diet-related greenhouse gas emission (GHGE) and a diet similarity index that quantified the proportion of food intake that remained similar as compared with the observed diet.Setting: National dietary surveys of four European countries (Denmark, Czech Republic, Italy and France).Subjects: Approximately 6500 adults, aged 18-64 years.Results: When dietary preferences were prioritised, NRD15·3 was ~6 % higher, GHGE was ~4 % lower and ~85 % of food intake remained similar. This diet had higher amounts of fruit, vegetables and whole grains than the observed diet. When nutrient quality was prioritised, NRD15·3 was ~16 % higher, GHGE was ~3 % lower and ~72 % of food intake remained similar. This diet had higher amounts of legumes and fish and lower amounts of sweetened and alcoholic beverages. Finally, when environmental impact was prioritised, NRD15·3 was ~9 % higher, GHGE was ~21 % lower and ~73 % of food intake remained similar. In this diet, red and processed meat partly shifted to either eggs, poultry, fish or dairy.Conclusions: Benchmark modelling can generate diets with improved adherence to FBDG within the boundaries of dietary practices, but fully maximising health and minimising GHGE cannot be achieved simultaneously. [ABSTRACT FROM AUTHOR]

Given that agriculture is a key economic activity of the majority of people living in rural Africa, agricultural development is at the top of the agenda of African leaders. Intensification of agriculture is considered an entry point to improve food security and income generation in sub-Saharan African (SSA). We used a farm optimization model to perform ex-ante assessment of scenarios that could improve gross margin, a farmer's objective, and maize sales, a national policy objective to improve food security, of large and small farms in maize-based farming systems in two posts representative of rural Mozambique (Dombe and Zembe Administrative Posts in Central Province). For selling maize, farmers first had to be maize self-sufficient. We explored two options for increasing agricultural productivity: (i) extensification, to expand the current cultivated area; and (ii) intensification, to increase input use per unit of land. We considered two scenarios for each of the two options. Extensification: current situation (SC1), hired labour (SC2) and labour-saving (SC3). Intensification: land-saving (SC4) and combined improvement (SC5). For each scenario, we maximized gross margin and maize sales for large and small farms and assessed the trade-offs between the two goals. We further explored the impact of increasing labour and land availability at farm level beyond the current observed levels. SC4 substantially increased both gross margin and maize sales of large and small farms in both posts. Minor trade-offs were observed between the two goals on large farms whereas we saw synergies between the goals for small farms. In Dombe, the gross margin of large farms increased from $ 5550 to $ 7530 y -1 and maize sales from 12.4 t to 30.4 t y -1 . In Zembe, the annual gross margin increased from $ 1130 up to $ 2410 per farm and annual maize sales from 5.1 t up to 9.5 t per farm. For small farms in Dombe, the gross margin increased from $ 1820 to $ 2390 y -1 and maize sales from 3.0 t to 9 t y -1 . In Zembe, the annual gross margin increased from $ 260 to $ 810 and annual maize sales from 2.0 t to 3.6 t per farm. With the most optimistic scenarios and conditions of more hired labour and labour-saving technologies, both farm types substantially increased both gross margin and maize sales. We conclude that with available resources, the possibilities for increasing gross margin and maize sales are greater where agroecological conditions are more favourable and are much higher for larger farms. Without interventions that allow small farms to access more labour and land, intensification of agriculture is likely to happen only on farms of better-resourced households, indicating the need for alternative forms of on- and off-farm income generation for poorer farmers. The contribution of agriculture to national food security has to come from the large farms, requiring policy support. [ABSTRACT FROM AUTHOR]

• New approach for optimizing post-harvest preprocessing operations. • New variant of vehicle routing problem with heterogeneous service types. • Efficient multi-level struct-based solution representation to improve solution times. • Customized adaptive large neighborhood search based on problem characteristics. • Identification of new best solutions for HFVRPTW benchmark instances. This study focuses on the post-harvest preprocessing of fruits and vegetables, aiming to provide an effective way to conduct preprocessing operations in short food supply chains. We consider both a heterogeneous fleet of mobile preprocessing units and the possibility to pick up products for centralized preprocessing. The resulting problem is a variant of the classic heterogeneous fleet vehicle routing problems with time windows (HFVRPTW), with the additional consideration of multi-depot and heterogeneous service types, which we refer to as HFVRPTW-MDHS. These additional considerations are important to include in the development of more efficient food supply chains, but lead to a challenging routing problem. In this paper, we formulate the HFVRPTW-MDHS using a mixed-integer linear programming model. Due to the complexity of the model, we propose a customized adaptive large neighborhood search (ALNS) metaheuristic. We design a multi-level struct-based solution representation to improve the efficiency of the ALNS and develop customized methods for solution evaluation, feasibility checks, and neighborhood search. Comparing our results with the results of an exact algorithm and solutions in the existing literature, we find that our ALNS algorithm can obtain high-quality solutions quickly when solving HFVRPTW-MDHS and related variants of the VRP. Finally, we study the application of our approach in the case of precooling, which is a commonly used preprocessing operation, to illustrate the effectiveness of our approach in a relevant practical context. [ABSTRACT FROM AUTHOR]

Changes in climate, technology, policy and prices affect agricultural and rural development. To evaluate whether this development is sustainable, impacts of these multiple drivers need to be assessed for multiple indicators. In a case study area in the Netherlands, a bio-economic farm model, an agent-based land-use change model, and a regional emission model have been used to simulate rural development under two plausible global change scenarios at both farm and landscape level. Results show that in this area, climate change will have mainly negative economic impacts (dairy gross margin, arable gross margin, economic efficiency, milk production) in the warmer and drier W + scenario, while impacts are slightly positive in the G scenario with moderate climate change. Dairy farmers are worse off than arable farmers in both scenarios. Conversely, when the W + scenario is embedded in the socio-economic Global Economy (GE) scenario, changes in technology, prices, and policy are projected to have a positive economic impact, more than offsetting the negative climate impacts. Important is, however, that environmental impacts (global warming, terrestrial and aquatic eutrophication) are largely negative and social impacts (farm size, number of farms, nature area, odour) are mixed. In the G scenario combined with the socio-economic Regional Communities (RC) scenario the average dairy gross margin in particular is negatively affected. Social impacts are similarly mixed as in the GE scenario, while environmental impacts are less severe. Our results suggest that integrated assessments at farm and landscape level can be used to guide decision-makers in spatial planning policies and climate change adaptation. As there will always be trade-offs between economic, social, and environmental impacts stakeholders need to interact and decide upon most important directions for policies. This implies a choice between production and income on the one hand and social and environmental services on the other hand. [ABSTRACT FROM AUTHOR]

In northern West Bengal and southern Bangladesh, Rabi crops, sown in winter and harvested in the spring, are an important source of income and nutrition for the target communities. In the study areas, NGOs and extension services have been engaging with farming communities on selecting suitable crops for the upcoming season. This engagement took place in the absence of quantitative tools to discuss trade offs and what-if scenarios to support an informed discussion. The objective of this study was to design a crop-choice model to support extension agronomists in engaging with the farming communities more effectively using a quantitative analysis tool. In this process, we explored how agricultural system models can be inclusive and allow participation and eventual application by NGO and government extension agents, using a process of gender sensitive contribution. The crop-choice model includes several constraints related to available resources, including land, labour, capital and technologies to calculate optimal crop areas within the Rabi season. The crop choices are determined considering gender specific community perceptions of risks, labour use, market, price-volatility, self-consumption, water use and cash flow. The model was used to explore the consequences of different crop choices on income, gender specific labour, use of inputs and markets, and to reveal the trade-offs of pursuing different crop choice pathways in the context of agricultural intensification. The initial model was demonstrated to the farmers and the extension agents, and based on their reflections, it was fine-tuned further to make the engagement process more effective. For better communication with the participating farmers, the model related questions and findings were translated in the local language (Bengali). We found that the modelling process can be made more inclusive from the outset by including farmers, NGO and extension agents as co-contributors of the model at each of the modelling steps and incorporating their reflections. Such an inclusive and reflective approach provides easy-to-use interfaces and enables translation of model results in ways that more effectively benefit farming communities. The process of engagement with farmers during tool development has been very valuable to farmers and researchers alike and the use of the tool has made the farmers informed about alternative scenarios and led to actual benefits for crop choice decision making. Inclusive farming systems models need to consider the gender dimension and its critical role in farm decision making and how this can be included in models to reflect the diversity of decision process. To maximise relevance of the model for next users and farmers, it was important that these key stakeholders were part of the model development from the beginning, this study has focused on the same throughout. This study demonstrated that appropriate design and development principles enabled bioeconomic farming systems models to be used by NGO and government extension agents to engage with farming communities as discussion support tools in farming decisions. Such an approach would make the engagement process more convincing and effective. Besides, it would also provide useful insights to the NGO and extension agents in revising their intervention strategies. [Display omitted] • We developed a crop-choice model to support extensionists in engaging with the farming communities more effectively • Model used to explore consequences of different crop choices on income, gender specific labour, use of inputs and markets • Gender sensitive co-contribution/participatory model is inclusive allowing participation and application by practitioners • Inclusive model development facilitated better communication between extension partners and farming communities [ABSTRACT FROM AUTHOR]

Highlights • We assess benefits of cooperation in temperature controlled transportation. • An Inventory Routing Problem is applied to compare different forms of cooperation. • Joint Route Planning cooperation can reduce both costs and emissions substantially. • Vendor Managed Inventory results in a trade-off between cost and emissions. • There is a trade-off between emissions and average product age in VMI cooperation. Abstract Inefficient road transportation causes unnecessary costs and polluting emissions. This problem is even more severe in refrigerated transportation, in which temperature control is used to guarantee the quality of the products. Organizing logistics cooperatively can help decrease both the environmental and the economic impacts. In Joint Route Planning (JRP) cooperation, suppliers and customers jointly optimize routing decisions so that cost and emissions are minimized. Vendor Managed Inventory (VMI) cooperation extends JRP cooperation by optimizing routing and inventory planning decisions simultaneously. However, in addition to their economic advantages, VMI and JRP may also yield environmental benefits. To test this assertion, we perform a case study on cooperation between a number of supermarket chains in the Netherlands. The data of this case study are analyzed to quantify both the economic and environmental benefits of implementing cooperation via JRP and VMI, using vehicle routing and an inventory routing models. We found that JRP cooperation can substantially reduce cost and emissions compared with uncooperative routing. In addition, VMI cooperation can further reduce cost and emissions, but minimizing cost and minimizing emissions no longer result in the same solution and there is a trade-off to be made. [ABSTRACT FROM AUTHOR]

Highlights: [•] Empirical evidence indicates the feasibility of intensive small dairy farming. [•] Well-known technologies, not novelties, were responsible for farmers’ performance. [•] The long time lag to achieve good performance was a main constraint. [•] Dairy farming was economically competitive with soybean, sugarcane and urban jobs. [•] High productivity/area brings a new perspective for dairy farmers in the tropics. [ABSTRACT FROM AUTHOR]

Past reviews of policy impact assessment studies using bio-economic farm models (BEFM) called for the development of a generic and modular implementation that can be maintained by a network of modellers. A main reason for these calls is the project-oriented way in which model developers receive funding. It favours the development of new models with case-study specific features over the maintenance and extension of well-tested, more generic ones which allow comparing results in a consistent way across many case-studies. The demand for more generic tools also reflects the dynamic landscape of policy measures within larger policy frameworks like the Common Agricultural Policy (CAP). These policy frameworks move increasingly away from a 'one-size-fits-all' approach of policy design towards more flexible systems, giving greater freedom to shape, implement, and target policy measures to specific regions, farm management systems and farm types. This creates new challenges for model-based impact assessment as applied models have to reflect the variety of policy measures and characteristics of targeted farmers and rural communities. The aim of this paper is to first address key questions regarding the functionality and implementation of such a modular BEFM that can be maintained and expanded by a user group, and second to develop concrete proposals of necessary model features, model design and shared development. This paper builds on literature research, including a detailed review of four models that are used extensively for impact assessment within the EU and were developed by multiple teams over a longer period of time. From there, necessary and desirable features of a generic and modular BEFM are identified and requirements for model design regarding modularity, software engineering, and shared development are discussed. This feeds into the development of concrete proposals of how modularity and flexibility can be addressed in the development, application and maintenance of a BEFM. At the end, a list of design decisions and implementation steps is proposed to build a modular BEFM that can be maintained by a network of researchers. The concept for a network-based generic and modular bio-economic farm model responds to the demand for analytical tools in agricultural policy impact analysis. The paper develops a research agenda to overcome observed limitations in the current landscape of such models. [Display omitted] • Case-study driven bio-economic farm model development slows methodological progress. • This motivates a network-based and modular approach for a generic bio-economic farm model. • Four applied models are reviewed in detail and desired features of a generic one are derived. • Details of a generic and modular implementation of desired model features are developed. • This yields a concept for a network-based generic and modular bio-economic farm model. [ABSTRACT FROM AUTHOR]

Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC. [ABSTRACT FROM AUTHOR]

Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC. [ABSTRACT FROM AUTHOR]