Technical Coefficient Generators Research Articles

Socioeconomic and environmental assessment of biodiesel crops on family farming systems in Brazil

In Brazil, local agricultural research agendas are increasingly challenged by the search for sustainable biodiesel crop options for family farmers, especially under semi-arid conditions. The aim of this paper is to explore the suitability of different biodiesel crops (i.e. soybean, castor bean and sunflower) through a set of environmental and socioeconomic indicators in a semi-arid (Montes Claros) and a more humid (Chapada Gaúcha) municipality in the state of Minas Gerais, southeast Brazil. A technical coefficient generator (TechnoGIN) was used to assess current (maize, beans, soybean and grass seed) and alternative (castor bean and sunflower) crops grown with current and alternative production techniques. The quantification of the inputs and outputs was based on farm surveys, expert knowledge, literature and field experiments. Although castor bean and sunflower are economically competitive with maize in Montes Claros, feed and labour requirements may hinder farmers' adoption. In Chapada Gaúcha, the double cropping system soybean/sunflower presented small economic gains when compared to soybean; it also increased nitrogen losses and biocide residues. We conclude that the scope for alternative and sustainable biodiesel crops on family farms is limited. Their economic benefits are small or absent, while their introduction can lead to higher environmental impacts and there may be trade-offs with food and feed availability at the farm level.

Integrated assessment of biodiesel policies aimed at family farms in Brazil

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 140kg per farm, which is very low compared to the 41% increase and more than 48,000kg 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.

Integrated assessment of agricultural land use policies on nutrient pollution and sustainable development in Taihu Basin, China

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.

Exploring options for farm-level strategic and tactical decision-making in fruit production systems of South Patagonia, Argentina

In South Patagonia, Argentina, sweet cherry is the main fruit-tree crop grown for export, resulting in a highly seasonal labour demand. Managers of deciduous perennial fruit orchards must consider both biological and economic relationships in selecting crop species and orchard design. This makes decisions at the farm-level extremely complex, as especially in such perennial crops, strategic (‘what to plant’, ‘with which technology’ and ‘how much area of each activity’, i.e. the final design) and tactical (‘when, what and how to plant in time’, the pathway to the planned farm) decisions have a long-term effect. The objective of this study was to explore the consequences of different strategic and tactical decisions at farm scale in fruit production systems of South Patagonia, considering the variation in interests and aims of different stakeholders, and using a sensitivity analysis to evaluate the consequences of possible changes in external conditions. A dynamic farm-scale optimization model called OPTIFROP was developed to generate alternative farm development plans, by allocating, in the course of the time horizon of the run, production activities to different land units, while optimising different objective functions, subject to several constraints. Although time-dependent, dynamic, mathematical programming models for analysing farming systems have been described in literature, the dynamic aspects of long-term decision-making in orchard design and their impact on the sequential (annual) nature of orchards in different growth phases (i.e. medium-term decision-making), need a higher time-staged dynamic approach with a staircase matrix structure. The model includes two objective functions at farm level: (1) maximization of the present value of cumulative financial result, which is the main objective for growers, and (2) maximization of cumulative farm labour, which is an objective often mentioned by policy makers. The inter-months deviation for labour demand (during the period of high labour demand, November–April) was included as an upper-bound. Input and output coefficients for the land use options considered in OPTIFROP were quantified using the Technical Coefficient Generator FRUPAT. Model results indicated that the present value of cumulative financial result and the cumulative farm labour are conflicting to a very limited extent. Timing and feasibility of implementing certain combinations of production technologies are affected by resource endowments and initial conditions, but these factors do not influence land use selection in the long term. Land use selection is driven by the objectives of the stakeholders. OPTIFROP showed that, through introduction of alternative crops, substantial reductions in labour peaks in the period November–April could be achieved with a relatively small reduction in farm income. The sensitivity of the model solution to the cherry price suggests that the fruit production sector of South Patagonia should pay more attention to the robustness of their land use plans and take preventive measures to avoid being caught by a possible crisis due to changes in the context.

Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: II. Cost–benefit assessment for different technologies, regions and scales

New tools for land use analysis including detailed cost–benefit assessments are needed to integrate resource management for enhancing farmers’ income and mitigating greenhouse gas (GHG) emissions. The paper comprises an assessment of GHG emissions and economic returns under different mitigation technologies in three rice growing regions in Asia, i.e., Ilocos Norte province (Philippines), Zhejiang province (China) and Haryana state (India). Site-specific data on soil, climate and socio-economics were integrated in the previously developed spreadsheet model TechnoGAS (Technical Coefficient Generator for Mitigation Technologies of Greenhouse Gas Emissions from Agricultural Sectors). Three baseline technologies that differed in terms of inorganic/organic N supply have been compared to different mitigation technologies in form of Marginal Abatement Cost Curves (MACCs). For the baseline technology of inorganic N (urea) fertilization, amendment with phosphogypsum and nitrification inhibitors are the most promising mitigation options resulting in shadow prices of less than US$10 per ton of carbon dioxide equivalent (CE). Assuming a mix of urea and farm yard manure for the baseline, we have tested several options including different irrigation patterns and husk used as fossil fuel. Mid-season drainage had a better cost–benefit ratio (ca. US$20 per t CE) than alternate flooding, but was less profitable than husk utilization (ca. US$4 per t CE). Assuming high organic inputs, biogas technology is, in most cases, the preferable option (ca. US$10 per t CE). Finally, we compiled regional abatement cost curves for selected administrative units using the outcome from regional optimization models. Implementing the three most promising technologies required US$6000 for Dingras municipality, Ilocos Norte, in the Philippines (ca. 10 3 ha of rice land potentially providing emission savings of ca. 3000 t CE), US$50,000 for Pujiang county in China (ca. 10 4 ha providing ca. 27,000 t CE), and US$1.2 million for Karnal district in India (ca. 10 5 ha providing ca. 220,000 t CE).

Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: I. Generation of technical coefficients

This study presents a modeling tool to assess emission of greenhouse gases (GHG) from the agricultural sector as affected by land-use and residue utilization options. The overall purpose of this tool is twofold: (i) a spreadsheet model for comprehensive compilation of the direct and indirect emissions from land management, residue-burning and fossil fuel consumption through on-farm and off-farm operations and (ii) a decision support tool to explore economically viable mitigation options through detailed cost–benefit analysis of different technological options. We developed TechnoGAS (technical coefficient generator for mitigation technologies of greenhouse gas emissions from agricultural sectors), which integrates analytical and expert knowledge with regional databases on bio-physical, agronomic and socio-economic features to establish input–output relationships (‘Technical Coefficients’) related to GHG emissions in agriculture. The approach includes emissions of methane (CH 4) from rice fields, rice straw burning and cattle; carbon dioxide (CO 2) from fossil fuel and soil organic carbon decline as well as nitrous oxide (N 2O) from soil, rice straw burning and fertilizer use. To illustrate the approach of the spreadsheet model for comprehensive compilation of emissions, we applied TechnoGAS for an entire rice–wheat cropping cycle in the state of Haryana in northern India as a case study. Twenty technologies of rice production, which can be adopted by farmers, are analysed for their operation-specific emissions including their global warming potential (GWP). The technologies differ in terms of water regime, residue management/utilization, soil management and additives, which represent different mitigation options for GHG emissions. With the current farmers’ practice in various districts in Haryana, soil-borne emissions are the major source of GHG contributing 53% of the average GWP (3288 kg CO 2 equivalent ha −1) in rice followed by burning of rice straw (13% of the GWP). Cattle, farm operations, off-farm and inorganic fertilizer contributes 12%, 10%, 10% and 2% of the GWP, respectively. Emissions from wheat are relatively low (1204 kg CO 2 equivalent ha −1) as there is no CH 4 emission and wheat straw is not burnt. Different mitigation technologies show pronounced effects on the GWP of the rice crop and varied between 1715 kg CO 2 equivalent ha −1 with continuous flooding, urea and rice straw used for building materials and 10,020 kg CO 2 equivalent ha −1 with continuous flooding, and application of nutrients through organic manure. Compared to current farmers’ practice, 13 technologies are found to have the potential to reduce the GWP by 8–51%, but they also reduce the net income of farmers. Upscaling of the estimates to the entire state of Haryana shows that the GWP with the current farmers’ practice in rice is 2617 Gg CO 2 equivalent. Modification of water management from continuous flooding to alternate flooding or application of urea alone instead of urea plus FYM will reduce the GWP by 15% and 29%, respectively, while feeding of rice straw to cattle and supplying N through urea will reduce it by 41% compared to the current practice of burning rice straw and use of FYM. The study shows that the TechnoGAS tool can be used for estimating GHG emission from various land-use types and for identifying promising mitigation options. A detailed cost/benefit analysis is supplied by Wassmann and Pathak [Wassmann, R., Pathak, H., this volume. Introducing greenhouse gas mitigation as a development objective in rice-based agriculture: II. Cost–benefit assessment for different technologies, regions and scales.].

A mathematical approach to comparing environmental and economic goals in dairy farming: Identifying strategic development options

Instead of continuously adapting current dairy farming systems according to the ruling legal instruments, exploring strategic development options for the farming system with a focus on the final environmental goals may provide better perspectives for farm continuation. To identify promising options, the dairy farming model was developed. The model describes options of different intensities for producing feed in the field, for processing or buying feed and for converting feed into milk. The combinations of different intensities result in different types of income levels, different nutrient emissions into the ecosystem and different abilities to manage the landscape. The model reconciles economic objectives (maximizing income per ha) with ecological objectives (minimizing nutrient leakages and maximizing landscape values). The multiple-objective model is in turn fed by other models, such as technical coefficient generators for grass, maize and fodder beets. The dairy farming model is applied to assess the type of farming systems that meet environmental policy objectives and analyse the perspectives of dairy farming on sandy soils in the Netherlands. It is shown that many different dairy farming systems are possible meeting the environmental goals (maximum 34 kg N leached, 30 kg N volatilized and a P surplus below 2.2 kg ha −1), with a range in environmental and economic performance. The scenario selected depends on the preference of the stakeholder. General characteristics are low N application rates on grazed grassland, associated with the restriction on nitrate leaching, animals housed in low-emission stables, associated with the restriction on ammonia volatilization, and a substantial part of the concentrates produced in the region, associated with the restriction on P surplus. Production and utilization of hay is an option to reduce N excretion by the animals. Regional or on-farm concentrate production is economically only attractive if land is in surplus under pressure of environmental goals.

The effect of temporal variation on inputs and outputs of future-oriented land use systems in West Africa

The (semi-) arid area of West Africa is characterized by erratic rainfall that causes highly variable performances of cropping systems. This creates difficulties in strategic decision-making based on future-oriented production systems. In this paper, the degree of variation in inputs and outputs of future-oriented millet ( Pennisetum glaucum L.) systems is quantified using a dynamic crop growth simulation model and a static technical coefficient generator. To determine inputs and outputs of future-oriented millet systems under (semi-) arid conditions, the target-oriented approach was operationalized for low-yielding conditions. Economic yield, N-loss and labor requirement were used as benchmarks for outputs and inputs of future-oriented land use systems. Weather data for 31 year characterize two sites in the (semi-) arid zone of Mali, while for each site two soil types with distinct properties were considered. In all four physical environments, inputs and outputs of millet systems have coefficients of variation (CV) exceeding 50%. Consequences of the variable performances of these systems are discussed for both policy-makers and designers of future-oriented systems. Engineering tools exist which help policy-makers to quantify consequences of variability at different scale levels so that variability can be reduced or better managed. Examples are given of future-oriented cropping systems aimed at less variable yield. At one site, fine tuning of the sowing date to seasonal water availability reduced CVs yield to 20–30% while long-term average yields increased with 40 to more than 130%. Water conservation measures increased yields by 40–230% and reduced their CVs by 28–50% in all four physical environments. Effects of various cultivation methods on the variability in inputs and outputs of future-oriented cropping systems can be rapidly explored using these tools. In addition, systematic analysis using such tools allows explicit analysis of gains and costs of various alternatives simultaneously.

Can forestry be a competitive land use option?: Model simulations from humid tropical Costa Rica

Model simulations are carried out to study options for managed natural forest and melina ( Gmelina arborea) and teak ( Tectona grandis) plantations on land suited for agriculture in the humid tropical Atlantic lowlands of Costa Rica. Tools used are a linear programming model that maximizes regional economic surplus, and the so-called technical coefficient generators that quantify input and outputs of forestry and competing crop and pasture-based beef cattle production systems. Model scenarios are carried out for varying prices of wood, beef and labor, under conditions of unlimited and restricted wood markets. Results indicate that teak and melina plantations are attractive land use options while managed natural forest is not. With unlimited wood demand, teak occupies 70% of the study area and total yearly teak production exceeds current Costa Rican wood consumption, indicating the need to include market mechanisms in the study. The area under teak is relatively insensitive to price changes between –40 and +60% of the base value of $95 m −3 (1996 stumpage price). The area under melina changes considerably with price changes of ±20% of the base value of US$16 m −3. Natural forest revenues must rise by 440% of the current $32 m −3 to make it economically more attractive than other land use options, especially pasture for beef production and melina plantations. Increasing labor costs are likely to favor tree plantations. Increasing beef prices considerably reduce the competitiveness of melina, though not that of teak.

Quantification of land use systems using technical coefficient generators: a case study for the Northern Atlantic zone of Costa Rica

This paper describes two generic so-called technical coefficient generators, PASTOR (Pasture and Animal System Technical coefficient generatOR) and LUCTOR (Land Use Crop Technical coefficient generatOR), that quantify land use systems in terms of inputs and outputs based on the integration of systems-analytical knowledge, standard agronomic and animal husbandry data and expert knowledge. PASTOR quantifies livestock systems while LUCTOR is geared towards cropping systems. Main inputs quantified include costs, labour requirements, fertiliser use and application of crop protection agents. Outputs are production and a number of associated environmental indicators. Although both PASTOR and LUCTOR were developed to generate input data for land use models, they are also useful as stand-alone tools to explore the technical efficiency of land use systems, to perform cost-benefit analyses and to quantify the trade-off among socio-economic, agronomic and environmental indicators at the field level. PASTOR and LUCTOR are illustrated with data from the Northern Atlantic zone in Costa Rica. Tools such as PASTOR and LUCTOR integrate different types of knowledge, including non-documented knowledge from field experts and make that knowledge transparent and open to critical review and discussion by others.

A framework for integrated biophysical and economic land use analysis at different scales

There is a general need for quantitative tools that can be used to support policy makers in regional rural development. Here, a framework for (sub-) regional land use analysis is presented that quantifies biophysical and economic sustainability trade-offs. The framework, called sustainable options for land use (SOLUS), was developed over a 10-year period of investigation in the Northern Atlantic Zone of Costa Rica and encompasses scale levels that range from field to region. SOLUS consists of technical coefficient generators to quantify inputs and outputs of production systems, a linear programming model that selects production systems by optimizing regional economic surplus, and a geographic information system. Biophysical and economic disciplines are integrated and various types of knowledge, ranging from empirical expert judgement to deterministic process models are synthesized in a systems-analytical manner. Economic sustainability indicators include economic surplus and labor employment, and biophysical ones include soil N, P and K balances, biocide use and its environmental impact, greenhouse gas emission and nitrogen leaching loss and volatilization. Land use scenarios can be implemented by varying properties of production inputs (e.g., prices), imposing sustainability restrictions in the optimization, and incorporating alternative production systems based on different technologies. Examples of application of SOLUS in the Northern Atlantic Zone of Costa Rica show that introduction of alternative technologies may result in situations that satisfy both economic as well as biophysical sustainability. On the other hand, negative trade-offs were found among different dimensions of biophysical sustainability themselves.

Exploring options for sustainable beef cattle ranching in the humid tropics: a case study for the Atlantic Zone of Costa Rica

Options are explored for sustainable, i.e. non-soil-nitrogen (N) mining, beef production in the humid tropical Atlantic Zone of Costa Rica using a modelling approach. Tools used are linear programming and a technical coefficient generator called PASTOR. Due to the combination of high rainfall, highly permeable soils and high N turnover rates, N losses are high and current natural pastures are calculated to mine soil N reserves with 40–60 kg ha −1 year −1. With current financial returns, there is no economic incentive for farmers to convert soil mining natural pastures to sustainable alternatives, viz. grass–legume mixtures or fertilized improved grasslands. When degradation of natural pastures over time due to soil N mining is considered in the model, it becomes economically attractive to replace these pastures with grass–legume mixtures. Sustainable beef cattle ranching is best realized by integrated intensification that raises total economic returns, i.e. use of grass–legumes or fertilized pastures, high levels of feed supplements and improved herd management techniques.

Quantifying economic and biophysical sustainability trade-offs in land use exploration at the regional level: a case study for the Northern Atlantic Zone of Costa Rica

A generic methodology is presented for exploration of sustainable land use options at the regional level by quantifying trade-offs between socio-economic and biophysical sustainability objectives. The methodology is called SOLUS (Sustainable Options for Land USe), and was developed over a ten year period of investigation in the Northern Atlantic Zone of Costa Rica. SOLUS includes a linear programming model, technical coefficient generators for livestock and cropping activities and a geographic information system. The linear programming model maximizes regional economic surplus subject to a flexible number of resource and sustainability constraints. Economic sustainability indicators are economic surplus and labor employment, and biophysical ones include soil N, P and K balances, pesticide use and its environmental impact, nutrient losses and a proxy for trace gas emissions. The capabilities of the methodology are illustrated for the Northern Atlantic Zone of Costa Rica. Though ample scope exists for reducing environmental effects and introducing sustainable production systems separately, pursuing both objectives simultaneously, considerably reduces economic surplus and agricultural employment. Agricultural area can be decreased and forested area increased without severely affecting the regional economic surplus.