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TechnoGIN, a tool for exploring and evaluating resource use efficiency of cropping systems in East and Southeast Asia
Abstract
Agricultural research in East and Southeast Asia is increasingly challenged by the search for land-use options that best match multiple development objectives of rural societies (e.g., increased income, food security, and reduced environmental pollution). In order to support the identification of sustainable land-use options and to support decision making with respect to land use, a tool was developed for quantifying inputs and outputs of cropping systems at the field level. TechnoGIN, the tool described in this paper, integrates systems analytical and expert knowledge and different types of agronomic data enabling the assessment of inputs and outputs of a broad range of cropping systems and the evaluation of their resource use efficiencies. By using methods of spatial aggregation in combination with linear programming, results can also be used to explore trade-offs in resource-use efficiencies at higher levels such as the farm household, municipality and province. New features in TechnoGIN compared with similar tools include the annual rotation of up to three crops, the distinction between aerobic and anaerobic growing conditions of crops, and the procedure for estimating crop nutrient uptake. TechnoGIN is illustrated with results from the Tam Duong district in North Vietnam. The design of TechnoGIN enables easy access to its data, parameters and assumptions, and rapid generation and evaluation of input–output relationships of cropping systems in order to add new information and to improve data. TechnoGIN raises awareness about the assumptions incorporated and thus supports data collection and setting of the research agenda with respect to agro-ecological processes for which knowledge is incomplete, and is relevant for showing trade-offs between production, economic and environmental impacts of different land-use systems.
... Supplementary Information (SI) Figure S1: Illustration of the core concepts of WGII AR5. TechnoGIN, developed in the framework of the Systems Research Network for Ecoregional Land use planning (SysNet) project applies a target-oriented approach (Ponsioen et al., 2006). That, in first place mean, fine-tuning of (mixes of) inputs to realize a specified 'target' yield level under certain environmental and management conditions. ...
... Source: Ponsioen et al., 2006); the arrows represent flows of data ...
... For the pre-defined (estimated/simulated) 'target' yield levels, TechnoGIN calculates the technical coefficients (i.e. required inputs, environmental pollution) and hence, TechnoGIN may be applied for comparing resource use efficiency, labour demand, cost/benefit ratios and environmental pollution from different land use types and production techniques (Ponsioen et al., 2006). ...
Reimund P. Rötter, Fanou L. Sehomi, Jukka G. Höhn, Jarkko K. Niemi, and Marrit van den
Berg, On the use of agricultural system models for exploring technological innovations
across scales in Africa: A critical review, ZEF – Discussion Papers on Development Policy
No. 223, , Bonn, July 2016, pp. 85.
ISSN:
... A technical coefficient generator (TCG) is a tool for creating an input and output matrix for all relevant combinations of land management units, land use types and production techniques that form part of a (regional) land use modelling framework (Ponsioen et al, 2003). TechnoGIN is a TCG developed for South-East Asia and has been applied in several case studies (Ponsioen et al., 2006). This technical coefficient generator calculates the technical coefficients such as monthly water and labour requirements, nitrogen, phosphorous and potassium fertiliser requirements, nitrogen losses by leaching and by gas, nutrient surplus in the soil, biocide index, different costs in the production of crops, and returns of crops in different rotations. ...
... The Solver optimisation module is also used to select an optimal mix of fertilizer types for supplying the nutrients as mentioned in fertilizer gifts bases on data or as estimated by QUEFTS. Fig 2.1 Model structure of TechnoGIN (Ponsioen et al., 2006). ...
... comm.) based on his expert knowledge. These crop data are derived from the crop data files of the WOFOST model (Lazar & Genovese, 2004) and TechnoGIN system (Ponsioen et al., 2003(Ponsioen et al., , 2006. It is expressed in the unit tons/ hectare (t/ha). ...
... This would complement the existing literature assessing the feasibility of biodiesel production on family farms in Brazil, much of which is qualitative in nature (Abramovay and Magalhães, 2008;César and Batalha, 2010;Garcez and Vianna, 2009;Hall et al., 2011;Padula et al., 2012;Watanabe and Zylbersztajn, 2012). Such analysis is based on the description of production activities under specific biophysical and technological conditions in terms of inputs and outputs which are known as technical coefficients (Hengsdijk et al., 1999;Ponsioen et al., 2006). Inputs may include external nutrients, biocides and labour which together with the outputs can be expressed in their own physical units, and in monetary units. ...
... To generate such combinations and calculate the inputs and outputs a computer program (TechnoGIN) was used. TechnoGIN (Ponsioen et al., 2006) is a technical coefficient generator which allows for the quantification of inputs and outputs of a large number of current and alternative production activities. Although TechnoGIN was first developed for Ilocos Norte, Philippines (Ponsioen et al., 2003), it has recently been re-designed as a more generic and flexible tool for further applications in other regions of Asia and Africa (Patil et al., 2014;Reidsma et al., 2012;Wolf et al., 2004). ...
... There are three main types of technical coefficients which can be generated: (i) input requirements in Table 4 Relative change (%) of production activities characteristics under different production techniques (current, best farmers, improved and irrigated) and land units (Chapada Gaúcha and Montes Claros). Positive (+), negative (−) or neutral (0) physical and economic terms, i.e. fertiliser, biocide, seed, labour, and costs; (ii) physical production, mainly referring to crop yield; (iii) environmental impacts, i.e., biocide use, water requirement and nutrient balances (Ponsioen et al., 2006). In this study socioeconomic (crop production, labour requirements and gross margins) and environmental (nutrient balance and biocide use) indicators were assessed. ...
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.
... Data were collected at household level in the year 2009, and complemented with literature and expert knowledge. The tool that was used in this paper is the technical coefficient generator, TechnoGIN (Ponsioen et al., 2006), which will be further explained in the methodology section. The results lead to recommendations to farmers and policy makers, on the consequences of change to organic farming from prevailing conventional practices. ...
... In this study, we used TechnoGIN (Ponsioen et al., 2006), a technical coefficient generator (TCG) developed for South-East Asia. A TCG estimates input-output relationships of all relevant combinations of land units, crop rotations and production techniques (Ponsioen et al., 2003). ...
... TechnoGIN (Fig. 2) is a tool for land-use analysis and is widely used to calculate input-output relationships of agricultural activities. It was developed specifically for South-East Asia (Ponsioen et al., 2006), but has also been used in other regions (e.g. Wolf, 2004). ...
Karnataka is one of the south-western Indian states where agrarian distress as a major problem. Crop yields have been stagnant in the last decade, and coupled with increased input costs, this has led to reduced incomes and debts. There is an urgent need to study options to improve the sustainability of farming systems in Karnataka. One adopted strategy to stabilize agriculture in the state is organic farming, which is less dependent on external inputs. In this paper, we assess the sustainability of conventional and organic farming practices using the model TechnoGIN. TechnoGIN calculates inputs and outputs of farming practices, allowing assessment of its impacts on economic and environmental indicators. Data on inputs and yields have been collected in two districts in 2009 from farms with conventional and organic cultivation at the same time. Additional data were collected from literature and experts. Next, the current situation was assessed and projections were made towards 2015 for two scenarios per village, using either conventional or organic practices.
... In order to assess the impacts of agricultural policies, we have adapted, linked and used the technical coefficient generator TechnoGIN (Ponsioen et al., 2006), and the bioeconomic farm model FSSIM (Louhichi et al., 2010). An extensive farm survey has been carried out to provide input data for this modelling study, and policy fora have been held to discuss policies, indicators and model results. ...
... The modelling framework (Fig. 2) that has been applied in this study, consists of two main components: (i) the technical coefficient generator TechnoGIN (Ponsioen et al., 2006) and (ii) the bio-economic farm model FSSIM (Louhichi et al., 2010). ...
... In order to assess the impact of different agricultural activities on economic, environmental and social indicators, their input-output relationships need to be assessed. TechnoGIN (Ponsioen et al., 2006) has been used for this (Kang, 2009;Reidsma et al., 2011). TechnoGIN applies a target (yield) oriented approach (Van Ittersum and Rabbinge, 1997), and calculates nutrient emissions and balances and gives fertilizer recommendations using the built-in QUEFTS model (Janssen et al., 1990). ...
... One of these model-based approaches is dynamic crop growth or cropping systems simulation models (Van Ittersum et al., 2003). The other group delivering agricultural input-output matrices or coefficients as input to bio-economic models (Rötter et al., 2005) are the so-called technical coefficient generators (Ponsioen et al., 2006). Some of the input-output relations are usually generated by dynamic simulation models. ...
... The required information on the current production organisation is provided by farm level databases and studies. The numerical calculation from crop level cultivation requirements in different climate scenarios can be done by calculation procedures similar to those applied in TechnoGIN (Ponsioen et al. 2006). The main importance of such calculations is to define the necessary input use structure for feasible cultivation of specific crops (cultivars) in specific conditions. ...
... It must be realised that existing farm level models rely much on observed, widely spread farm level production organisation and use of inputs derived from aggregated databases. Elsewhere, knowledge about future alternative production activities has been formalized in input-output coefficient generators (Ponsioen et al. 2006; Pathak & Wassmann, 2007). Development of such tools for Finnish conditions should receive priority. ...
Improved assessment methods for agriculture production systems are needed to identify the risks andopportunities related to global changes in climate, markets and policies, and the consequences of alternativeoptions of coping with and mitigating the changes. This paper presents the AGRISIMU modelling frameworkdeveloped for ex-ante assessment of alternative policy and management options meant to support farms andagrifood sector adapt to climate change, maintain biodiversity and reduce nutrient emissions under Finnishconditions. The modelling framework represents a novel approach to the integration of data and output fromseveral existing models like a dynamic regional sector model of Finnish agriculture, a farm-level optimisationmodel, a dynamic crop growth simulation model and models describing the nutrient dynamics in agriculturalsystems and a hydrological rainfall-runoff model. The framework is particularly aimed for Nordic conditions andto serve as an assessment tool that considers multiple factor and scale interactions.
... This paper deals with methods and information required for quantifying resource use efficiencies and target yield levels of actual and future-oriented land use systems. As an example of estimating resource use efficiencies, the approach and results from the TCG TechnoGIN (Ponsioen et al., 2005) are described in Section 2. The methods for yield calculation are described in Section 3, which is followed by a general discussion and conclusion section. ...
... Schematic representation of the structure of TechnoGIN. The arrows represent flows of data (Source: Ponsioen et al., 2005). cropping systems (current systems) and from field experiments and outstanding farmers using improved techniques (future-oriented systems). ...
... Harvesting; U = Nutrient uptake by the crop; AD = Ash deposition; M = Mineralization from crop residues and manure (Source: Ponsioen et al., 2005). ...
... Combinations of these can be selected in the Select form (see Figure 8), and after running the output will be exported to an Excel or ASII file. The model is described in detail in Ponsioen et al. (2003) and in Ponsioen et al. (2006). For complete information including all the equations, codes and other details the reader is referred to these references. ...
... Especially data and assumptions in the model that are difficult to quantify are accessible through user forms and can be modified directly in the spreadsheets, so calculations are transparent for the user. Table 1 in Ponsioen et al. (2006) gives a clear overview of the data requirements per datasheet in TechnoGIN, indicating whether values are generally applicable and can be considered as fixed (e.g. dry matter content of crops), whether values should be established specifically (e.g. ...
... The applied modelling framework in this study is a combination of a technical coefficient generator, TechnoGIN (Ponsioen et al., 2006), and a bio-economic farm model, FSSIM . TechnoGIN runs at crop and field level and uses a mechanistic approach based on knowledge of the agro-ecological processes to simulate the input-output coefficients of different production activities. ...
... TechnoGIN (Ponsioen et al., 2006) was used to quantify inputs and outputs of current and alternative production activities. Although TechnoGIN was first developed for Ilocos Norte, Philippines, it has recently been re-designed as a more generic and flexible tool for applications in other regions of Asia and Africa (Patil et al., 2014;Reidsma et al., 2012;Wolf et al., 2004). ...
... This model integrates biophysical, agronomic, and socioeconomic data to establish input-output relationships related to water, fertilizer, labor, and biocide uses; GHGs emissions in the rice-wheat system. The inputs and outputs are calculated on a season basis using the target-oriented approach (Ponsioen et al., 2006; Pathak and Wassmann, 2007). With this, an optimal combination of inputs was identified to realize a target yield based on the biophysical environment and production techniques such as RCTs. ...
... The model integrates biophysical, agronomic, and socioeconomic data to establish input-output relationships related to water, fertilizer, labour, and biocide uses; GHG emissions; biocide residue in soil; and N fluxes in the rice-wheat system. The inputs and outputs such as GHG emissions were calculated on a season basis using the target-oriented approach (Ponsioen et al., 2006; Pathak and Wassmann, 2007; Pathak et al., 2010). The global warming potential (GWP) was calculated using the following equation (IPCC, 2007). ...
... Similarly, snow cover is also believed to be gradually decreasing. The current concentrations of CO 2 , CH 4 , and N 2 O in the atmosphere are 380 000, 1774, and 319 ppbV; atmospheric life times are [9][10][11][12][13][14][15], and 116 years; and global warming potential are 1, 25, and 298, respectively. 5 Recent research eff orts have attempted to develop alternative tillage and crop establishment techniques, termed resource-conserving technologies (RCTs), which are more effi cient, use fewer inputs, and improve production and income compared with conventional practices. ...
... Th e inputs and outputs are calculated on a season basis using the target-oriented approach. 9,10 With this, an optimal combination of inputs is identifi ed to realize a target yield based on the biophysical environment and production techniques such as RCTs. Outputs such as GHG emissions, N losses, and biocide residue are then calculated based on the amount of input used and the related soil-plant-atmospheric processes. ...
The rice-wheat system is the main source of food and income for millions of people in South
Asia. However, because of increasing pressure of biotic and abiotic stresses in response to soil degradation
and changing climate, crop productivity and farmers’ profi ts are on a downward trend. Recent
efforts have attempted to develop and deliver resource-conserving technologies (RCTs) with effi cient
and environmentally friendly tillage/crop establishment and water use compared with the conventional
practices of farmers. No tool, however, is available to evaluate the RCTs quantitatively, particularly in
terms of greenhouse gas (GHG) emissions and other environmental impacts. A simulation model,
named InfoRCT (Information on Use of Resource-Conserving Technologies), has been developed
integrating biophysical, agronomic, and socio-economic data to establish input-output relationships
related to water, fertilizer, labor, and biocide uses; GHG emissions; biocide residue in soil; and N fl uxes
in the rice-wheat system. The model provided a comparative assessment of RCTs in yield, income,
global warming potential (GWP), biocide residue index, and N loss. The assessment showed that
mid-season drying and no-till systems increased income, and also reduced the GWP. The model could
be used for assessing impact of crop management practices on productivity and GHG emissions in
rice-wheat systems.
... The interest of farmers to achieve maximum profit from the (often meager) resources generally collides with the demand from the industrial/urban sector. New tools for land use analysis and planning, therefore, are needed to reconcile the legitimate aims of (1) enhancing food production with (2) environmental concerns on soil, water and air quality alongside with (3) economic returns for the new land use systems (Ponsioen et al. 2006;Pathak and Wassmann 2007). The objectives of the present study were to (1) develop a decision support system to quantify N budget with various N management technologies in rice, (2) assess the environmental implications in terms of N loss and greenhouse gas (GHG) emission with the technologies and (3) estimate the economic feasibility of using the technologies to reduce N loss and GHG emission. ...
... In InfoNitro, the technical coefficients (TC), which refer to the inputs and outputs of land-use systems in economic and physical terms, are specifically developed to quantify differences in resource use of conventional and technological options aimed at improving RE N and reducing N losses. The input-output relationships are based on interpretation of survey, experimental data and published literature for a target output (i.e., yield) level (Ponsioen et al. 2006;Pathak and Wassmann 2007). ...
Several technologies have been developed to improve the recovery efficiency of N (REN) but their impacts on greenhouse gas (GHG) emission, N loss and economic implication are rarely analysed. A decision support system (DSS) has been developed to quantify inputs, outputs and balance of N in soil; GHG emission and REN with the prominent N management technologies in rice. This DSS, named InfoNitro (Information on Nitrogen Management Technologies in Rice), integrated analytical and expert knowledge with databases on bio-physical, agronomic and socio-economical features to establish input-output relationships related to N management in rice. Sixteen technologies, which differed in terms of water regime, method of N application, forms of N and tools of fertilizer recommendation were analysed for their REN, N losses, GHG emission and economic return in Haryana, a rice growing region in India. In the current farmers' practice, REN was 32.7%, which increased up to 40.8% with various technologies except in mid-season drainage and alternate flooding technologies where it decreased up to 29.3%. Loss of N through leaching, volatilization and denitrification in the farmers' practice (67.5 kg N ha-1) decreased up to 40.5 kg N ha-1 except in mid-season drainage and alternate flooding technologies where it increased. The technologies also reduced global warming potential (GWP) by 1 to 9%. However, the technologies except no tillage, mid-season drying and alternate flooding reduced the net income of the farmers. When the environmental cost (cost of N loss and GWP) was included net income with various technologies was either at par or more than the farmers' practice. The marginal abatement cost of N loss was Rs.8 to 134 kg-1 N and for GWP was Rs.766 to 4854 Mg-1 CO2 eq. Resource conserving technology was the most cost effective strategy to reduce N loss and GHG emission whereas integrated N management cost high for mitigating GHG emission.
... The constraints in the model refer to resource endowments and consumption requirements. Production activities are defined using TechnoGIN, a technical coefficient generator that integrates empirical data with production-ecological and expert knowledge in defining efficiencies in input use (Ponsioen et al., 2006 ). This methodological approach of combining linear programming models with technical coefficient generators has been extensively applied to analyse resource use options in various geographical regions, including The Netherlands (Van de Ven, 1996), West Africa (Kruseman and Bade, 1998), Costa Rica (Bouman et al., 1999) and Asia (Roetter et al., 2005). ...
... The model is a typical explorative land use model, aimed at exploring bio-physical potentials and limitations, rather than at predicting likely developments. All models can be run with only current crop production activities or with both current and alternative crop production activities (Ponsioen et al., 2006 ). For livestock activities , only current practice is available. ...
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.
... Social targets aim to ensure food security, a healthy environment including safe drinking water, and the provision of work/livelihood to the rural households. These were related to the indicators rice yield, a biocide residue index (Ponsioen et al., 2006) and the labour use. As off-farm employment gives higher profitability than agriculture, a reduction in labour use was considered positive. ...
... A major requirement as input into bio-economic models, is the quantification of agro-ecological relationships. For this, we used the Technical Coefficient Generator developed for South-East Asia, TechnoGIN (Ponsioen et al., 2006 ). TechnoGIN simulates inputoutput relationships of agricultural activities on a hectare basis. ...
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.
... The constraints in the model refer to resource endowments and consumption requirements. Production activities are defined using TechnoGIN, a technical coefficient generator that integrates empirical data with production-ecological and expert knowledge in defining efficiencies in input use ( Ponsioen et al., 2006). This methodological approach of combining linear programming models with technical coefficient generators has been extensively applied to analyse resource use options in various geographical regions, including The Netherlands (Van de Ven, 1996), West Africa ( Kruseman and Bade, 1998), Costa Rica ( Bouman et al., 1999) and Asia ( Roetter et al., 2005). ...
... All models can be run with only current crop production activities or with both current and alternative crop production activities (Ponsioen et al., 2006). For livestock activities, only current practice is available. ...
Pressures on the natural resources, especially land and water, continue to increase as a result of an ever-increasing world population and continuing economic growth. These pressures originate from the many claims of stakeholders at different scales on the limited resources, and are aggravated by their different and often conflicting goals. Discussions on alternative resource uses, prioritizing different goals, and formulation and implementation of land use policies would greatly benefit from a quantitative assessment of the economic, social and environmental benefits and costs associated with the alternatives. In this study, a multi-scale and model-based approach was developed and applied in support of joint-learning, policy discussions and decision-making with respect to agricultural land use. The methodology was operationalized, in consultation with stakeholders, for the province of Ilocos Norte in the northwest of the Philippines, and its most populous municipality, Batac. Six optimization models with different specifications were developed for different spatial scales: one for the farm, four for the municipal and one for the provincial scale. Results of the farm household analysis show the comparative attractiveness of alternative agricultural technologies, although adoption behaviour with respect to these technologies is different for poor, average and better-off households. The provincial analysis provides a quantitative assessment of the trade-off involved in prioritizing economic goals over social goals of food self-sufficiency and increased employment in agriculture. Results of the municipal analysis show that limited markets, inadequate infrastructure and resource endowments of farm households strongly affect resource use and goal achievement in Batac. As the effects of these factors in the model are significant, ignoring them may result in misleading simulation results and, hence, policy conclusions. The multi-scale approach was used to quantify the effects of agricultural policies pertaining to attainment of food self-sufficiency goals, liberalization of rice prices, infrastructure improvements and volumetric water pricing on income, food production, resource use, and environmental indicators at the farm, municipal and provincial scales. Food self-sufficiency goals can be achieved but conflict with economic objectives. Liberalization of rice prices results in lower income for farmers but benefits rice consumers as a result of lower rice prices. Irrigation improvements can contribute to increased rice production, however, at the expense of income. Similarly, volumetric water pricing can result in more efficient water use at the farm and municipal scale, but at the expense of income in the short-run. Many of these results seem trivial, but the model-based analyses result in quantitative estimates for the effects on the economic, agricultural and environmental dimensions of the problem. It is anticipated that model-based analyses has a potential to play a key role in participatory land use policy formulation. Results from the multi-scale approach presented in this thesis can provide valuable information for policy development and assessment. This may enhance transparent discussions among stakeholders on the implications of various objectives and priorities at different scales for resource use. This also allows ex-ante analysis of agricultural and natural resource use policies, including assessment of the potentials of new agro-technologies. Keywords: Linear programming; Natural resource use; Policy analysis; Farm household modelling; Regional modelling; Philippines
... Social targets aim to ensure food security, a healthy environment including safe drinking water, and the provision of work/livelihood to the rural households. These were related to the indicators rice yield, a biocide residue index (Ponsioen et al., 2006) and the labour use. As off-farm employment gives higher profitability than agriculture, a reduction in labour use was considered positive. ...
... A major requirement as input into bio-economic models, is the quantification of agro-ecological relationships. For this, we used the Technical Coefficient Generator developed for South-East Asia, TechnoGIN (Ponsioen et al., 2006). TechnoGIN simulates inputoutput relationships of agricultural activities on a hectare basis. ...
Author's personal copyLand Use Policy28 (2011) 604–617
... Low maize productivity in Ethiopia is mostly due to sub-optimal crop management such as nutrients (Getnet et al., 2022;Seyoum et al., 2019;Seyoum et al., 2018)). Agricultural models that follow target-oriented approach for example QUantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) are believed to optimize N, P and K nutrients in balanced proportion (Ponsioen et al., 2006). However, previous research on maize management practices hardly addressed the use of models for optimizing nutrients. ...
... Low maize productivity in Ethiopia is mostly due to sub-optimal crop management such as nutrients (Getnet et al., 2022;Seyoum et al., 2019;Seyoum et al., 2018)). Agricultural models that follow target-oriented approach for example QUantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) are believed to optimize N, P and K nutrients in balanced proportion (Ponsioen et al., 2006). However, previous research on maize management practices hardly addressed the use of models for optimizing nutrients. ...
... In brief, compared to the conclusions that would have been reached in study based only on surveys among farmers, or using trials or crop modelling (Ponsioen et al., 2006;Snapp et al., 2018;Cui et al., 2021;Mwambo et al., 2020;Debaeke et al., 2009;Guo et al., 2022), the approach used in this study has several advantages in regions where data to estimate indicators are not readily available. First, on-farm monitoring provides robust data measured in a diversity of fields over several years and this is of utmost importance in areas where it is difficult to compare the results of interviews with local references. ...
Maize cropping has often become the only way for many family farmers in Southeast Asia to rapidly obtain a cash income. However, the intensification of maize-based cropping systems is raising concerns about its environmental sustainability. This study contributed to field-based approaches for ex post sustainability assessment of current cropping systems on farms and for the design of more sustainable prototypes, in conditions where the information required for estimating sustainability indicators are not readily available. A 3-year regional agronomic diagnosis was combined with a multicriteria assessment and a prototyping procedure. The latter aimed to increase the performances on the indicators that showed critical levels on current systems. A local diversity of maize fields in Laos was used to test the approach. We defined and used indicators representing farmers’ socio-economic objectives and risks for the environment. Sustainability indicators were calculated using data extracted from farm surveys, direct measurements in fields managed by the farmers and crop modelling. Our analysis showed that the most frequent weaknesses in all current maize-based cropping systems were (i) low land and labour productivity, (ii) high susceptibility to weed infestation, (iii) high risk of herbicide leaching, (iv) risk of soil fertility depletion, (v) risk of soil erosion. None of the current cropping systems performed well simultaneously on both indicators of land/labour productivity and control of herbicide leaching. These sustainability issues mainly resulted from difficulties in mastering mechanised crop establishment. Taking the current cropping system as a starting point, prototypes with successful crop establishment thanks to well mastered mechanisation would significantly improve the following sustainability indicators: control of herbicide leaching (improved by 130–340%), yield (multiplied by 1.3–2.3), gross margin (multiplied by 1.3–2.2), weed control (improved by 180–430%) and labour productivity (multiplied by 1.4–3.4). However, it would increase erosion (erosion control divided by 1.6–7) and seasonal cash outflow would increase (multiplied by 1.1–2). Overall, improving crop establishment would increase sustainability (overall sustainability score multiplied by 1.1–1.6). Our results suggest that providing farmers with enhanced capacity to master crop establishment would not solve all sustainability issues of maize cultivation, but at least help avoid a catastrophic overuse of herbicides in that context.
... Additionally, FarmDESIGN did not simulate dynamic response of crop yield to soil nutrient availability or other management operations (Groot et al., 2012). If necessary, this limitation could be overcome by linking FarmDESIGN with dynamic crop simulation models such as APSIM and CropSyst, or technical coefficient generators such as TechnoGIN (Keating et al., 2003;Ponsioen et al., 2006;Stöckle et al., 2003). Another modelling assumption was that double cropping had a very narrow time span between the two crops, overlapping in some growing periods. ...
1. CONTEXT: Policy-based or technological interventions are more likely to be effective if aligned with farmers’ objectives, constraints, and decision-making processes.
2. OBJECTIVE: The objective of this study was to explore trade-offs and synergies of farming systems in response to innovative rice cultivation activities by understanding current farming systems, main drivers impacting farm management and farmers’ perspectives on rice intensification. Understanding these interrelations is key in rice production areas, where smallholder farmers largely depend on growing rice to subsist.
3. METHODS: A rapid system analysis was conducted interviewing 20 farmers in 4 villages along the Senegal River Valley (SRV) to obtain a general view on farm functioning and farmers’ perspectives on farming systems. A detailed system analysis with four farmers was subsequently conducted to provide an insight into the underlying processes regulating farm management. A multi-objective optimization model was used to quantitatively evaluate and explore farm performances based on four selected indicators representing: rice production, household agricultural profit, household labour and farm nutrient balance.
4. RESULTS AND CONCLUSIONS: The results of this study showed that government programmes and farmers’ Unions were strongly influencing farmers’ decision-making in agricultural production. Farmers also reported that although rice was still essential for their livelihoods, there were transitions towards less rice production in the wet season with short duration rice varieties and more vegetable production. Both farmers’ interviews and the modelling results suggested that farmers would be unlikely to increase or even maintain the area of rice double cropping, which has been strongly promoted by the Senegalese government. Instead, farmers would rather keep investing in vegetable production.
5. SIGNIFICANCE: This modelling study shows the consequences of policy-based and technological interventions for farming systems and may inform both policy makers and farmers in situations where objectives are strongly divergent. Hence, modelling outcomes may be used to inspire discussion and innovation in order to align the government priority of ensuring national food security and farmers’ objectives and constraints in the SRV.
... The model integrates information on climate, crop, soil type and inputs used to calculate GHGs emission. The inputs and outputs are calculated on a season basis using the targetoriented approach [17,20]. GHGs emission was calculated based on the amount of input used and its related soil-plant-atmospheric processes. ...
Water, carbon (C) and nitrogen (N) are important natural resources required for crop production. Footprints of these three natural resources are useful indicators of consumption and pollution. The present project is aimed to determine the water, carbon and nitrogen footprints of major crops of the Indo-Gangetic Plains (IGPs). Field experiments were conducted, and modelling tools were used to quantify water, C and N footprints of rice and wheat crops in IGP. Four locations (Karnal, Delhi, Varanasi and Kalyani) were selected for the study representing different transects of IGP. Carbon footprint (CFP) of rice crop in Karnal and Delhi was found to be higher than Varanasi and Kalyani due to application of more amounts of agri-inputs and more use of farm machineries leading to higher GHG emission. Although GHG emission in wheat is also more in Karnal, higher yield of wheat crop led to lower CFP than Varanasi. Water footprint (WFP) of rice production was higher in Karnal, Delhi and Varanasi than Kalyani region mainly due to higher evapotranspiration. QGIS software was used to prepare geospatial maps of carbon and water footprint for IGP. The study will help in identifying regions and crops having higher footprints and also select alternative management practices which will help in lowering water, C and N footprints of agricultural production.
... To identify the sample of frameworks that must be included in this study, we consider differences in terms of the sustainability dimensions they evaluate. In fact, while some frameworks consider the ecological, economic and societal dimension of sustainability, other instruments focus on one dimension, for example, the Life Cycle Assessment tool, INDIGO (Thiollet-Scholtus and Bockstaller, 2014) and TechnoGIN (Ponsioen et al., 2006). Still others include additional dimensions such as entrepreneurship Meul et al., 2008); governance (FAO, 2013a); or quality and culture (Peano et al., 2014). ...
In the review of academic literature, numerous papers present either a list of indicator criteria or partially revised sustainability assessment tools of agri-food systems. However, neither a complete analysis and discussion about the criteria utilised by evaluators nor a compared examination and subsequent frameworks categorisation have been fully developed by researchers. This study aims to fill this twofold gap by investigating the main issues related to the choice of a tool for the
sustainability assessment of an agri-system. This task is conducted in three steps: firstly, we analyse the criteria an indicator should match to be included in an evaluation; secondly, we categorise 15 of the most important agriculture sustainability frameworks to discuss effectiveness in evaluating sustainability for each category, finally, we compare the categories and emphasise differences to highlight the possible application of each framework and hence guide the practitioner in the framework selection process. Our analysis identifies the complementarity between bottom-up and top-down approach and the impossibility of identifying a priori the best framework, although a
combination of both approaches could prove to be a valuable, alternative option.
... InfoRCT (Information on Use of Resource-Conserving Technologies), integrates biophysical, agronomic, and socioeconomic data to establish input-output relationships related to water, fertilizer, labor, and biocide uses; GHG emissions; in the rice-wheat system. The inputs and outputs are calculated on a season basis using the target-oriented approach (Ponsioen et al., 2006;Pathak and Wassmann, 2007). ...
... It generally included only the time required for in-field operations, with no quantification of the time required for transport, field observations, the exchange of knowledge or administrative tasks. Some authors (Pardo et al., 2010;Ponsioen et al., 2006) analysed the distribution of workload over the seasons and quantified workload peaks. This approach was useful for assessing the ease with which cropping systems could be adopted and implemented as a function of the organisation of labour at the farm level. ...
The multiple new challenges facing agriculture require the development of innovative cropping systems with high environmental, economic and social performances. Many research programmes are currently focusing on the design of such cropping systems. Some include the multicriteria assessment of cropping systems by diverse methods and approaches. Some of these research programmes are supported by experimental or farmers' networks, generating new opportunities for data analysis and raising new research and methodological questions. In this article, we provide an overview based on a review of 56 articles, comparing the various methods for sustainability assessment in single- and multi-site studies. Articles were classified according to three characteristics: (i) their objectives, (ii) the study design (single- vs. multi-site), (iii) the type of system assessed (fictitious vs. real). Our analysis was structured around four items: (i) the variables used to describe cropping systems and production situations and the use of these variables in the assessment process, (ii) the criteria and associated indicators assessed, (iii) the methods used to explore multiple aspects of the performance of cropping systems, (iv) the use of reference values. We identified key points to be taken into account in multi-site studies. The application of the proposed guidelines to experimental networks should facilitate the identification of high-performance cropping systems and the identification of the drivers of cropping system performance.
... Following the introduction of the 'đổi mới' strategy, and stimulated by the growing demand for agricultural products from population centres, such as Vinh Yen town, farmers intensified production. To make a livelihood from the relatively small areas of land available, high-value crops, such as vegetables, became a major commodity, as horticulture generated a much higher income than traditional double rice and winter maize (Hengsdijk et al., 2005;IRMLA, 2005;Ponsioen et al., 2006;Van den Berg et al., 2007). In addition to soil erosion, nutrient leaching is an important problem in these intensive systems on sloping terraces with sandy soils, causing environmental problems, such as eutrophication and pollution of drinking water sources, with potential health risks, and contributing to low fertilizer use efficiencies. ...
... One such tool is the Technical Coefficient Generator, developed for south-east Asian agricultural systems, or TechnoGIN as it is widely known (Ponsioen et al., 2006). TechnoGIN uses information from actual measurements of activities on farm, scientific literature, reports and expert consultation. ...
... One of these model-based approaches is dynamic crop growth or cropping systems simulation models (Van Ittersum et al., 2003). The other group delivering agricultural input-output matrices or coefficients as input to bio-economic models (Rötter et al., 2005) are the so-called technical coefficient generators (Ponsioen et al., 2006). Some of the input-output relations are usually generated by dynamic simulation models. ...
Improved assessment methods for agriculture production systems are needed to identify the risks and opportunities related to global changes in climate, markets and policies, and the consequences of alternative options of coping with and mitigating the changes. This paper presents the AGRISIMU modelling framework developed for ex-ante assessment of alternative policy and management options meant to support farms and agrifood sector adapt to climate change, maintain biodiversity and reduce nutrient emissions under Finnish conditions. The modelling framework represents a novel approach to the integration of data and output from several existing models like a dynamic regional sector model of Finnish agriculture, a farm-level optimisation model, a dynamic crop growth simulation model and models describing the nutrient dynamics in agricultural systems and a hydrological rainfall-runoff model. The framework is particularly aimed for Nordic conditions and to serve as an assessment tool that considers multiple factor and scale interactions.
... The IASA defined ecological security as the condition where people's lives, health, wellbeing, basic rights, living necessities, essential resources, social order, and adaptability to environmental changes are not threatened. Ponsioen et al. [19] described ecological security as a state where the ecological environment required for the survival and development of a country is not or barely threatened. In other words, ecological security is when the natural ecological environment can satisfy the sustainable development requirements of individuals and communities, without damaging the natural ecological environment. ...
Kinmen National Park is the only battle memorial-themed natural resource conservation park in Taiwan. With the rapid growth in tourism, Kinmen National Park faces the challenge of managing with the resulting environmental impact. For this study, we adopted the tourism ecological footprint (TEF) and tourism ecological capacity (TEC) to evaluate the ecological conditions of Kinmen National Park from 2002 to 2011. The empirical results indicated the following findings: (a) TEF increased by 8.03% over 10 years; (b) Regarding the environmental sustainability index (ESI), per capita tourism ecological deficit (PTED) yielded a deficit growth rate of 45.37%. In 2011, the ecological footprint index (EFI) was at Level 4 with 1.16, and the ESI was at Level 3 with 0.495. According to the aforementioned results, with the increased scale of tourism to Kinmen National Park, the pressure that ecological occupancy exerted on the national ecosystem exceeded its ecological capacity.
... In tropical areas, low fertility is often found in deforested areas, where critical topsoil has washed away. The replacement of traditional slash and burn cultivation by more diversified production systems based on forest products , orchard products, and forages and food products (Barrett et al., 2001; Ponsioen et al., 2006; Smaling and Dixon, 2006) and applying agroecological principles creatively (Altieri, 2002; Dalgaard et al., 2003) can improve soil fertility. The adoption of agroforestry can maintain land productivity , decrease land degradation and improve rural people's livelihood (Albrecht and Kandji, 2003; Oelberman et al., 2004; Schroth et al., 2004; Reyes et al., 2005; Jiambo, 2006; Rasul and Thapa, 2006). ...
... Once this is achieved, the model will expand its usability to smallholder coffee producers. Another option would be to incorporate (parts of) SAFERNAC into a general coffee growth simulation model in the similar way that QUEFTS was incorporated in TechnoGIN [33]. ...
The aim of this study was to develop a simple and quantitative system for coffee yield estimation and nutrient input advice, so as to address the problem of declining annual coffee production in Tanzania (particularly in its Northern coffee zone), which is related to declining soil fertility. The study was conducted between 2010 and 2013 at TaCRI Lyamungu, with source data taken from Hai and Lushoto districts, Northern Tanzania. An earlier model QUEFTS, developed for maize but under similar conditions as those of Arabica coffee (Coffea arabica) in the study areas was used as a benchmark. Secondary fertilizer trial data were used in model calibration for coffee, while adding two more steps related to balanced nutrition and the economics of integrated soil fertility management (ISFM). Primary soil analytical data and calculated yields on basis of tree number were used for model testing. The result was a new model which we hereby call SAFERNAC (Soil Analysis for Fertility Evaluation and Recommendation on Nutrient Application to Coffee). The model consists of three modules: SOIL (the soil properties of interest), PLANT (all the crop and crop management parameters such as physiological nutrient use efficiency, plant density, maximum yields per tree) and INPUT (nutrient inputs – organic and inorganic). It consists of two subsequent parts – a baseline approach (no input) for coffee land evaluation; and an integrated soil fertility management (ISFM) approach that involves application of nutrient inputs, for ISFM planning and design of fertilizer experiments. The model was checked for accuracy of the adjusted equations, and found to be capable of reproducing the actual yields by 80-100%. The new model is a useful tool for use in coffee farms
... Assessing both these changes (in indicators as well as in the interactions across criteria) as policy impacts could employ different approaches. These assessments generally make use of agricultural household models (Taylor and Adelman 2003;Bouman et al. 1999;Bhende and Kalirajan 2007;Ray 2007;Vashisth et al. 2007;Singh et al. 1986), rural system change models (Ali 2007), multi-market limited general equilibrium models (Croppenstedt et al. 2007), or bio-physical models (Thomas et al. 2006). Agricultural household models require extensive data to generate equations for output, consumption, input demand, and prices. ...
The classical approach of assessing sustainability with respect to its three underlying pillars, ecological, economic, and social, is adopted in this paper, with an added emphasis on estimating the simultaneous effects of each pillar on the other two. The paper assesses the impact of policy-driven changes in cultivation practices in five districts in the south-western Indian state of Karnataka. A comparative statics analysis using a simultaneous equations model is developed to capture the stability of each pillar into the future and their concurrent interactive impacts and trade-offs. Ecological and economic impacts of policies favoring organic farming are estimated to be uniformly significant and positive in the study districts. However, the impact on socio-cultural criteria is subjective to the eco-regional context. Cost savings, through producing organic inputs on-farm, maximizes synchrony among the three pillars vis-à-vis sourcing these inputs from the market. With more reliance on organic inputs, better prospects are estimated for small and rain-fed farms compared to large and irrigated farms.
... The inputs (irrigation, fertilizer, pesticide, labor, etc.) and outputs (GHG emissions, crop residues, etc.) were calculated on a season basis to achieve a desired yield of rice. Similar approaches for calculating inputs and outputs in crop production systems were used in models such as InfoGIN (Ponsioen et al. 2006), TechnoGAS (Pathak and Wassmann 2007), and InfoNitro (Pathak 2010). The global warming potential (GWP) was calculated by the following equation (IPCC 2007). ...
Conventional puddled transplanted rice (TPR) is a major source of greenhouse gas (GHG), particularly methane, causing global warming. Direct-seeded rice (DSR) is a feasible alternative to mitigate methane emission, besides saving water and labor. A 2-year field experiment was carried out to quantify GHG mitigation and water- and labor-saving potentials of the DSR crop compared to TPR in three villages in Jalandhar district of Punjab, India. The InfoRCT simulation model was used to calculate the emission of CO2 besides CH4 and N2O in different districts of Punjab, India. Total global warming potential (GWP) in transplanted rice in various districts of Punjab ranged from 2.0 to 4.6 t CO2 eq. ha−1 and in the DSR it ranged from 1.3 to 2.9 t CO2 eq. ha−1. Extrapolation analysis showed that if the entire area under TPR in the state is converted to DSR, the GWP will be reduced by 33 %, and if 50 % area is converted to DSR the GWP will be reduced by 16.6 % of the current emission. The DSR crop saved 3–4 irrigations compared to the transplanted rice without any yield penalty. Human labor use also reduced to 45 % and tractor use to 58 % in the DSR compared to TPR.
... .accounting for uncertainty and integrating different types of information and different stakeholder perspectives.) -Technical coefficient generation/input-output calculations: e.g. a tool that enables calculation of inputs and outputs of a land-use system (Ponsioen et al., 2006 -Mathematical programming: e.g. bio-economic household modelling to link farmers' resource management decisions with current and alternative production possibilities (Janssen and van Ittersum, 2007). ...
... Agriculture which is closely related with the nature has the characteristic of resources recycling. Many researches in agricultural economics or farm management are about crop yield which is the most important problem in agriculture [1, 17] . Some papers research the environment and management factors influencing the yield, such as climate, tillage methods, residue management, row spacing, water irrigation, fertilizer, cropping patterns [10, 14, 21] . ...
In the dry land agricultural systems, single-, double- and triple-cropped lands play different roles on ecological function, economic function and social function. In Sichuan province of China, the land area for various cropping patterns for three land types is in large proportion of Sichuan's cultivated land. It is extraor- dinarily important to obtain an optimal crop planting scheme based on the character of Sichuan province. In this kind of situation, this paper presents how multi-objective programming can be efficiently used for mod- eling and solving crop planning problems for optimal production of several seasonal crops in a planning year based on the scientific principle of circular economy and the character of Sichuan province dry land agricul- ture. The crop planning problem in agriculture is usually formulated as a single objective linear programming model. The objective is either the maximization of net revenue from cultivated land or the minimization of cost of cultivation. According to the national policies that ensure the stable growth of grain yield, this paper considers grain yield as an objective, use " - constraint method and converts the multi-objective programming to a linear programming. The paper takes the Sichuan province of China into account as an illustrative case example and obtain some significative results by using RCGA.
... The object of calculation within the FECG is the production technique , which is defined as a common method to grow a crop and is specific to the crop management and its intensity (Ponsioen et al., 2006). Different variety groups (e.g. for winter wheat: bread and feed wheat, quality wheat, elite quality wheat) are further distinguished by different cultivation methods (ploughed, surface tilled, no-tillage/direct seeding). ...
A Farm Economy Coefficient Generator (FECG) is presented as a post-processing tool for agro-ecological simulation models (ASMs) that deliver yields and consumption figures for nitrogen fertiliser and irrigation water use. The FECG carries out simple cost accountancy calculations using typical production techniques, costs and prices for the selected area. The default settings can be adjusted by the user to specifically describe local farm management. Together with various ASMs, the FECG is embedded in a web-based, geo-referenced decision support system to enable users to extract information on future yields and net returns on a regional or farm-level basis. Using the example of a winter wheat–winter barley–silage maize crop rotation in Germany and downscaled A1B climate data it was demonstrated how the ASM–FECG tandem can be used to analyse the cost and benefit of irrigation. In this example the irrigation costs would still outweigh the yield increase today, while in around 2070 the increased difference between potential and water-limited yield is likely to make irrigation profitable, provided that costs and price levels remain constant. The susceptibility of these results to changing market conditions is discussed.
... Following the introduction of the 'đổi mới' strategy, and stimulated by the growing demand for agricultural products from population centres, such as Vinh Yen town, farmers intensified production. To make a livelihood from the relatively small areas of land available, high-value crops, such as vegetables, became a major commodity, as horticulture generated a much higher income than traditional double rice and winter maize (Hengsdijk et al., 2005;IRMLA, 2005;Ponsioen et al., 2006;Van den Berg et al., 2007). In addition to soil erosion, nutrient leaching is an important problem in these intensive systems on sloping terraces with sandy soils, causing environmental problems, such as eutrophication and pollution of drinking water sources, with potential health risks, and contributing to low fertilizer use efficiencies. ...
The environmental and economic consequences of nitrogen (N) lost in rice-based systems in Vietnam is important but has not
been extensively studied. The objective of this study was to quantify the amount of N lost in major cropping systems in the
Red River Delta. An experiment was conducted in the Red River Delta of Vietnam, on five different crops including rose, daisy,
cabbage, chili, and a rice–rice–maize rotation during 2004 and 2005. Core soil samples were taken periodically in 20-cm increments
to a depth of 1m and analyzed for nitrate–nitrogen and ammonium–nitrogen. The results indicate appreciable leaching losses
on N in high-rainfall and irrigation conditions, especially when fertilizer application was not well synchronized with crop
N demand. Highest annual leaching losses of N were recorded in flowers with 185–190mm of percolation and 173–193kgN ha−1, followed by vegetable (cabbage and chili) with 120–122mm of percolation and 112–115kgN ha−1, while it was lowest in rice with about 50kgN ha−1. We developed a simple N transport model that combined water and N movement through the soil profile. In most cases, the
model accurately predicted the seasonal dynamics of N as well as N flow between soil layers and the amounts of N lost from
the soil profile. The simulated results of N leaching with soil “puddling” conditions illustrate the advantage of an impermeable
or hardpan layer in increasing water and nutrient use efficiencies in these soils. These model results also showed that it
is possible to accurately estimate N losses with only a few parameters and helped us identify the risks of N leaching.
KeywordsHorticulture-Flowers-Vegetables-Rice-Nitrate-Nitrogen losses-Modeling
... These coefficients are generated using the survey data described in Section 2.3. and TechnoGIN (Ponsioen et al., 2003(Ponsioen et al., , 2006, a generic expert tool for integrating different types of information on crop production (Hengsdijk and Van Ittersum, 2003). The survey data are used to assess yields, labour and capital inputs, the use of biocides, and seed costs. ...
Economic growth in China’s agricultural sector lags behind growth in industry and services, creating an ever widening rural–urban income gap. Development of the non-agricultural sectors offers new opportunities for farmers in China’s more advanced provinces such as Zhejiang. Increased income in the urban sector creates markets for new products, and migrating farmers rent their land to those staying. Until now, the prevailing rice-based systems have been managed mainly using manual labour and animal traction, but the larger farms resulting from migration may facilitate, or even require mechanization. In this study, we use a simulation model of the farm household to analyse the effects of increasing farm size and the transition from rice to vegetable production, while also studying the effects of mechanization.Our results show that at the present scale of farming, the dual government objectives of increasing rural incomes and increasing rice production are clearly conflicting. Farmers can generate incomes comparable to non-farm wages, but only when they switch completely to production of more remunerative crops, such as vegetables. At larger farm sizes, however, labour constraints inhibit farmers from specialization in non-rice crops, and rising per capita incomes and increasing rice production go hand in hand. Mechanization is necessary to allow substantial increases in farm size.
... Ittersum, 2001; Bouman et al., 1998; Ponsioen et al., 2005). These technical coefficients can be incorporated in a spreadsheet tool to assess inputs and outputs under different technologies (Table 2). ...
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. 103 ha of rice land potentially providing emission savings of ca. 3000 t CE), US$50,000 for Pujiang county in China (ca. 104 ha providing ca. 27,000 t CE), and US$1.2 million for Karnal district in India (ca. 105 ha providing ca. 220,000 t CE).
... For quantification of inputs and outputs of production systems two expert tools were developed, one for livestock systems and one for cropping systems, called TechnoGIN (Ponsioen et al., 2003(Ponsioen et al., , 2006. TechnoGIN calculates for all specified cropping systems, on the basis of soil, crop and technology characteristics, relevant inputs and outputs, such as yield, crop residue production, nutrient and biocide use, labour and machinery requirements (Hengs-dijk and Van Ittersum, 2002). ...
Both, poverty reduction and preservation of biodiversity are high on the global agenda on sustainable development. The relationships between poverty, biodiversity of agro-ecosystems and agricultural development are complex and poorly understood. In this paper, we present an integrated framework for analysis of agricultural development and natural resource management options at agro-ecosystem level, using Pujiang county, in Zhejiang province, China as a case study area to perform the analysis. A regional linear programming (LP) model is applied, maximizing regional economic surplus, given production and labour market conditions in Pujiang. We use the model to examine the consequences for a set of regional poverty and biodiversity indicators, of four so-called poverty reduction strategies, i.e., (i) intensification of production, (ii) diversification towards livestock production, (iii) land expansion, and (iv) an exit from agriculture. The analysis indicates that diversification is the most promising poverty reduction strategy, but requires efficient use of animal manure in cropping systems to avoid environmental problems. Improved nutrient management in cropping systems is effective in reducing the regional nitrogen surplus, but less effective in increasing per capita income. The exit strategy is effective in reducing poverty and achieving biodiversity goals, but may have important social consequences that are not addressed in this study. Further reduction in rural poverty is hampered by labour constraints during the harvesting period in high value crops such as vegetables and fruits, which calls for research and development in the field of agricultural mechanization.
... One important objective of the study was to develop a technical coefficient generator (TCG) to explore future land-use options to mitigate GHG emission. The term technical coefficient (TC) refers to the inputs and outputs of land-use systems in economic and physical terms as quantified by this type of tool (Bouman et al., 1998; 1999; Ponsioen et al., 2005). In TCMGAS, TCGs are specifically developed to quantify differences in resource use of conventional and future land-use options aimed at mitigating GHG emission. ...
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 (CH4) from rice fields, rice straw burning and cattle; carbon dioxide (CO2) from fossil fuel and soil organic carbon decline as well as nitrous oxide (N2O) 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 CO2 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 CO2 equivalent ha−1) as there is no CH4 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 CO2 equivalent ha−1 with continuous flooding, urea and rice straw used for building materials and 10,020 kg CO2 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 CO2 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.].
... For quantification of inputs and outputs of production systems two expert tools were developed, one for animal systems and one for cropping systems, called TechnoGIN (Ponsioen et al., 2003Ponsioen et al., , 2005). TechnoGIN calculates, on the basis of soil, crop and technology characteristics, relevant inputs and outputs of all specified cropping systems, such as yield, crop residue production, nutrient and biocide use, labour and machinery requirements (Hengsdijk and Van Ittersum, 2002). ...
Both, poverty reduction and preservation of biodiversity are high on the global agenda on sustainable development. The relationships between poverty, biodiversity of ecosystems and agricultural development are complex and poorly understood. In this paper we present an integrated framework for analysis of agricultural development and natural resource management options at ecosystem level. We use Pujiang county, in Zhejiang province, China as a case study area to perform the analysis. A regional Linear Programming (LP) model is applied maximizing regional economic surplus given product and labour market conditions in Pujiang. We use the model to determine the consequences of four so-called poverty reduction strategies, i.e. (i) intensification of production, (ii) diversification towards livestock production, (iii) land expansion, and (iv) an exit from agriculture, for a set of regional poverty and biodiversity indicators. Diversification seems the most promising poverty reduction strategy, but requires an efficient use of animal manure in cropping systems to avoid environmental problems.
Paddy circular economic system, edible fungus economic system and dry land economic system constitute of the typical circular agricultural system. In the process of developing the circular economy, it is necessary to build a mathematical model to optimize the circular production of the system both on economic and ecological benefits. Based on building a multi-objective linear programming model of the typical circular agricultural system, this paper get some significant results and conclusion combining with genetic algorithm. The conclusions show that comprehensive utilization the agricultural wastes can bring huge economic and ecological benefits.
This manuscript presents 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: 1. interactions between achievement of objectives at provincial and municipal scales; 2. effects of farm structure, infrastructure and markets for agricultural goods on natural resource use options at municipal scale, and 3. differences across farm types in possible technology adoption and the effect of technology adoption. Finally, the multi-scale method and results from the analyses for Ilocos Norte are discussed, in the wider context of important opportunities and shortcomings of today's multi-scale assessment of natural resource management.
The efficiency with which applied resources are utilized in sub-Saharan African cropping systems is especially critical as the resources are generally scarce. Research efforts to improve farm productivity increasingly focus on resource interactions and trade-offs operating at farm-scale. Farm-scale models that integrate summary models of the various subsystems (crops, livestock, household) are proposed to analyse the complexity of management systems. NUANCES-FIELD is a summary model of the crop/soil system that calculates seasonal crop production based on resource availability, capture and utilization efficiencies. A detailed mechanistic crop growth model, APSIM, was used to generate parameters and variables that can be introduced as descriptive functions in NUANCES-FIELD. To such end, we first parameterized and tested APSIM based on several field experiments carried out on different soil types in western Kenya farms where nitrogen and/or phosphorus were applied. The model was further configured to generate nitrogen and phosphorus response curves as a function of soil condition (carbon content, clay content, phosphorus-sorption characteristics) and the effects of alternative weed management scenarios in relation to labour availability. Nitrogen, phosphorus and rainfall capture efficiencies ranged between 0.22–0.85 kg kg−1, 0.05–0.29 kg kg−1 and 0.10–0.53 mm mm−1, respectively, depending on soil nutrient and physical conditions. Variation in the integrated seasonal fraction of radiation intercepted (intFRINT) with plant density was adequately described by the function y = 0.058x + 0.11 within a range of 1.5–5.5 maize plants per m2. Investigation of weed management using the APSIM model identified a weed-free period of at least five weeks from maize emergence for minimum yield loss from weed–crop competition. The simulation exercises confirmed that resource-use efficiencies sharply decrease on moving from relatively fertile fields ‘close’ to the homestead towards degraded ‘remote’ fields within the same farm, giving impetus to expedite the search for better targeted management strategies for spatially-heterogeneous farms.
Policy objectives of attaining food self-sufficiency and improving the well-being of subsistence farmers while protecting the environment have stimulated the development of many improved agricultural production technologies. With a choice of technologies, farm household decisions are governed not only by productivity and profitability considerations but also by factors such as available resources and their quality, family consumption preferences and attitudes towards risks, and prevailing policies. It is therefore necessary to analyse the adoption of such technologies from a whole-farm perspective. In this paper, a farm household model is used to assess possible technology adoption behaviour of farmers in Ilocos Norte Province, Philippines. Four alternative technologies were evaluated: hybrid rice production (HYR), balanced fertilization strategy (BFS), site-specific nutrient management (SSNM) and integrated pest management (IPM). Possible impacts of price policies and infrastructure improvements on technology adoption were assessed. The results show that all four alternative technologies considered are attractive to farmers, although simulations show differential adoption rates for poor, average and better-off households. IPM and HYR appear the most attractive amongst all technologies considered. In all technology simulations, relative profitability and risks, labour and capital requirements and availabilities are decisive factors in the adoption of alternative technologies. Adoption of alternative technologies would result in higher discretionary income, higher rice production and lower biocide use and nitrogen loss. Amongst policy simulations considered, availability of low-cost credit shows the largest improvements in farmer welfare for poor and average households, but its effect on simulated adoption of alternative technologies was variable. We argue that the methodology and results presented can contribute to ex ante assessments of policies targeted at stimulating technology adoption by farmers.
Economic growth in Chinas agricultural sector lags behind growth in industry and services, creating an ever widening rural-urban income gap. Yet growth beyond the farm offers new opportunities for farmers in Chinas more advanced provinces: markets for new crops and increasing farm size. At present, the dual government objectives of increasing rural incomes and increasing rice production are clearly in conflict. Farmers can obtain incomes comparable to non-farm wages only when they stop rice cultivation and switch to more profitable crops. Otherwise, mechanization is necessary to allow large enough increases in farm size to raise household income and maintain national rice production levels.
Site-specific nutrient management (SSNM) strategies that include site- and season-specific knowledge of crop nutrient requirements and in- digenous nutrient supplies are required to increase productivity, yields, and nutrient use efficiency in irrigated rice systems of South and Southeast Asia. The SSNM concept described here was developed and tested in more than 200 farmer fields in six Asian countries. By comparison with the large increases in yield that resulted from the introduction of green revolution technology in Asia, future yield and productivity increases in irrigated rice are likely to occur in smaller increments by fine-tuning nutrient and crop management. The SSNM approach was developed to increase mineral fertilizer use efficiency and achieve balanced plant nutrition (Dobermann and White, 1999; Witt et al., 1999; Dobermann and Fairhurst, 2000). Field- and season-specific fertilizer rates were calculated after taking into account indigenous soil nutrient supplies, plant nutrient demand (based on yield targets), and interactions among nitrogen (N), phosphorus (P), and potassium (K). This SSNM concept is valid for modern, high yielding varieties with a harvest index (ratio of grain to dry matter) of about 0.5. A recommendation is provided for the total NPK fertilizer require- ment depending on cropping season, crop establishment method, and inputs from other nutrient sources such as straw or manure. To im- prove the match between plant N requirements and fertilizer N supply, the SSNM strategy provides guidelines for splitting and timing fertilizer N applications according to crop growth stage. Nitrogen applications are fine-tuned during the season using a chlorophyll meter (SPAD) or leaf color chart (LCC) and when growing conditions in the season dif- fer from the assumptions used in the N fertilizer recommendation model. Field-specific fertilizer N, P, and K recommendations are calculated in five key steps. Step 1: Yield goal selection A yield goal is selected based on the variety-specific potential yield (Ymax), defined as the maximum possible grain yield limited only by climatic conditions when there are no other factors limiting crop growth.
A system is described for a quantitative evaluation of the native fertility of tropical soils, using calculated yields of unfertilized maize as a yardstick. The system is applicable to well drained, deep soils, that have a pH(H20) in the range 4.5–7.0, and values for organic carbon, P-Olsen and exchangeable potassium below 70 g/kg, 30 mg/kg and 30 mmol/kg, respectively (0–20 cm). Soil fertility is interpreted as the capacity of a soil to provide plants with nitrogen, phosphorus and potassium, but the methodology allows for including other nutrients.
Rice production in Asia needs to increase to feed a growing population whereas water for irrigation is getting scarcer. Major challenges are to (i) save water; (ii) increase water productivity and (iii) produce more rice with less water. This study analyzes the ways in which water-saving irrigation can help to meet these challenges at the field level. The analyses are conducted using experimental data collected mostly in central–northern India and the Philippines. Water input can be reduced by reducing ponded water depths to soil saturation or by alternate wetting/drying. Water savings under saturated soil conditions were on average 23% (±14%) with yield reductions of only 6% (±6%). Yields were reduced by 10–40% when soil water potentials in the root zone were allowed to reach −100 to −300 mbar. In clayey soils, intermittent drying may lead to shrinkage and cracking, thereby risking increased soil water loss, increased water requirements and decreased water productivity. Water productivity in continuous flooded rice was typically 0.2–0.4 g grain per kg water in India and 0.3–1.1 g grain per kg water in the Philippines. Water-saving irrigation increases water productivity, up to a maximum of about 1.9 g grain per kg water, but decreases yield. It therefore does not produce more rice with less water on the same field. Field-level water productivity and yield can only be increased concomitantly by improving total factor productivity or by raising the yield potential. Total rice production can be increased by using water saved in one location to irrigate new land in another. If this is not done, a strategy of saving water at the field level potentially threatens total rice production at large.
In the case of agricultural production, technical limitations can be used to explore future options for land use. As opposed to common economic outlooks this type of exploration provides information on the caveats and possibilities for agriculture. The options are calculated by combining a land evaluation (using a Geographical Information System, GIS), crop growth simulation models and Interactive Multiple Goal Linear Programming (IMGP). In the land evaluation, geographical information on soil types and other characteristics like steepness, stoniness, phase etc. is used to assess the suitability for different types of agriculture. Information on climate conditions and crop properties is used in the crop growth simulation models to calculate yield potentials for the suited areas. Economic, social and political goals are dealt with in a linear programming model. The result of this hierarchical modelling is a series of scenarios of optimal land use given the local properties of soils, crops and climate and given the economic, social and political considerations on topics like production costs, spreading of labor, market strategies and environmental conditions. Four different scenarios for future land use in the European Community emerge if the ongoing rise in productivity in agriculture is confronted with four partially conflicting goals of the Common Agricultural Policy (CAP). The scenarios present a picture of the end results in land use if one of these goals is taken to its logical conclusion. The goals are minimizing production costs (scenario Free market and free trade), maintaining regional employment (scenario Regional development), minimizing agricultural land use in favor of nature conservation (scenario Nature and landscape) and minimizing the stress on the environment due to pesticides and nutrients (scenario Environmental protection). All scenarios show results that are in sharp contrast with current opinions on the most probable developments in rural areas. In this paper the methodology will be exemplified and the results for possible land use in the EC will be discussed. Special attention is given to the interpretation of the results of this type of exploration.
This paper describes a formalized approach to identify and engineer future-oriented land use systems. Such land use systems can be used to explore options for strategic decision making with respect to land use policy and to do ex-ante assessment of land use alternatives to be further tested or developed in experimental settings. The so-called goal-oriented approach consists of three steps: (1) goal-oriented identification and design of land use systems; (2) quantification of biophysical production possibilities; and (3) defining the optimal mix of inputs, i.e. the production technique, required to realize production possibilities. The goal-oriented identification and design depends on the land-related objectives of a system under study, whereas plant, animal and environmental characteristics determine biophysical production possibilities. Characteristics of the production technique determine the realization of production possibilities. General guidelines are given to structure the specification and number of alternatives to be explored and to apply agro-ecological principles required for quantification of future-oriented land use systems. Concepts of the approach are illustrated with data from the northern Atlantic zone of Costa Rica and the Sudano–Sahelian zone of Mali. Finally, suggestions are given for the application of the approach at spatial and temporal scales exceeding the field level and time horizon of 1 year.
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.
Engineering of land use systems for policy-oriented future studies and the development of new farming systems requires various information sources. Often, both process knowledge and data are subject to uncertainty that affects quantification of land use systems in their inputs and outputs. This paper analyzes the effects of uncertainty in three important N-relationships relevant for quantification of future-oriented cropping systems: (i) N-leaching as function of crop characteristics, (ii) N-concentration as function of yield level, and (iii) the recovery of crop residue-N. Based on verifiable assumptions, uncertainty in these three N-relationships is specified in terms of N-loss and production costs of cropping systems. Data and process knowledge as applied in LUCTOR, a summary model to design and quantify inputs and outputs of cropping systems for the northern Atlantic zone of Costa Rica, are used as a case study. All three relationships and their uncertainty have a major impact on N-loss of cropping systems, while effects on costs are limited and depend on the share of costs for fertilizer management in total production costs. Analyses as presented explicitly specify uncertainty of process knowledge and data used in future-oriented studies. Therefore, such analyses enable a better management or reduction of uncertainty through the identification of cropping systems with smaller uncertainty margins, and identification of research aimed at a more complete understanding of involved processes.
This paper introduces a modeling method which simulates a village's response to population and market pressure. The method combines a recursive and dynamic linear programming model with a biophysical model of soil condition and plant growth that predicts yields and land degradation for different type of land, land use and cropping patterns. The linear programming model simulates farmers' plans aggregated at the village level under constraints of risk aversion, food consumption, land area, soil fertility, soil depth, labor and cash availability. Detailed agroecological factors determine the main processes of land degradation. A large number of technological alternatives, representing different degrees of labor and/or land-saving techniques available in the study areas, are introduced, taking into account their respective constraints, costs and advantages. The method has been calibrated for a village located in the sub-humid region of Burkina Faso. Several simulations are carried out to the Year 2030. The results show that population pressure leads to intensification and investment in land conservation practices but not necessarily to better farm incomes. Increasing market opportunities can play a more positive role in boosting productivity, but for the next decades the best way to increase production per farmer is to let farmers migrate from the high-population-density areas to the low-population-density areas because, under the current economic conditions of most Sahelian countries, intensification per hectare is stil more expensive than the fallow system.
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.
This study estimates the nitrogen (N), phosphorus (P) and potassium (K) requirements of irrigated rice (Oryza sativa L.) in South- and Southeast Asia. Grain yield and plant nutrient accumulation in above-ground plant dry matter (DM) were measured at physiological maturity of rice (n ∼ 2000) in on-station and on-farm experiments in six Asian countries between 1995 and 1997. These data were used to model the nutrient requirements for yields up to 11 t ha−1 using the QUEFTS (Quantitative Evaluation of the Fertility of Tropical Soils) approach. The model required the estimation of two borderlines describing the minimum and maximum internal efficiencies (IE, kg grain per kg nutrient in plant DM), which were estimated at 42 and 96 kg grain kg−1 N, 206 and 622 kg grain kg−1 P and 36 and 115 kg grain kg−1 K, respectively. The model predicted a linear increase in grain yield if nutrients are taken up in balanced amounts of 14.7 kg N, 2.6 kg P and 14.5 kg K per 1000 kg of grain until yield targets reached ca. 70–80% of the climate-adjusted potential yield (Ymax). The corresponding IEs were 68 kg grain kg−1 N, 385 kg grain kg−1 P and 69 kg grain kg−1 K for a balanced nutrition. The model predicted a decrease in IEs when yield targets approached Ymax. The derived borderlines are valid for current modern, high-yielding indica cultivars with a harvest index of 0.50 kg kg−1 and can be used for all methods of crop establishment. Only Ymax is required as site- or season-specific information when estimating nutrient requirements for a yield target making the model applicable for all irrigated lowlands in South- and Southeast Asia. Predicted IEs were greater than actual IEs measured in more than 200 farmers' fields (n ∼ 700), the latter averaging 59 kg grain kg−1 N (27–100 kg kg−1), 354 kg grain kg−1 P (158–1069 kg kg−1), and 64 kg grain kg−1 K (27–179 kg kg−1) with grain yields ranging from 1.5 to 9.9 t ha−1 (mean 5.2 t ha−1). Low and varying IEs in the farmers' practice were caused by nutritional imbalances, inadequate irrigation, or problems with pests and weeds.
This paper presents SysNet, a systems research network in South and South-east Asia, established to develop and evaluate methodologies for enhancing formulation of strategic land use policies. SysNet adopted theory and concepts from both natural and social science approaches. Multiple goal linear programming was used to integrate information on a broad range of alternative land use systems, resource availability and policy objectives, to reveal possibilities and limitations of agricultural resource use and trade-offs between policy objectives. The methodology was developed and applied in and with a network of researchers and stakeholders, for four case study areas in India, Malaysia, the Philippines and Vietnam. An application is presented for Haryana State (India), to illustrate the methodology and its components, as well as the type of questions that can be explored and subsequently discussed with stakeholders. We discuss lessons learnt on how to communicate LUPAS to stakeholders in interactive settings, with details for the Kedah-Perlis case region in Malaysia.
Soil loss, food insecurity, population pressure and low income of the rural population are interrelated problems in the Loess Plateau of northern China, and result in a spiral of unsustainability. This paper examines Ansai County as a case study to explore strategic land use options that may meet well-defined goals of regional development, using a systems approach that integrated the fragmented and empirical information on the biophysical, agronomic and socio-economic conditions. We used production ecological principles, simulation modeling and multiple goal linear programming as integrative tools. Four scenarios were explored, representing major directions of agricultural development in the region and views of national and local stakeholders, farmers and environmentalists. The results indicate that soil conservation, food self-sufficiency and income for the rural population can be substantially improved by efficient resource use and appropriate inputs. In the long-term, terracing and use of crop rotations with alfalfa may be the best options for soil conservation. The large rural population and the lack of off-farm employment opportunities could be the most important factors affecting rural development in Ansai. This study contributes to the understanding of regional problems and agricultural development potentials, and shows agro-technical possibilities for alleviating the unsustainability problems in this fragile and poorly endowed region. To promote actual development towards the identified options, on-farm innovation and appropriate policy measures are needed. The explored land use options enable a much more targeted innovation and development of policies.
This paper introduces the approach of the Systems research Network (SysNet) for land use planning in tropical Asia with a focus on its main scientific–technical output: the development of the land use planning and analysis system (LUPAS) and its component models. These include crop simulation models, expert systems, GIS, and multiple goal linear programming (MGLP) models for land evaluation and optimization. LUPAS was designed as a decision support system (DSS) for strategic land use planning. Integration of LUPAS components in four case studies was performed in a network with national research teams and local stakeholders. This network allowed iterative evaluation and refinement of LUPAS for scenario analysis on technical and policy changes. Several interactive sessions with stakeholders led to more detail in scenarios (goals and constraints), model features and databases. To facilitate negotiation among stakeholders, the MGLP user interface (UI) was developed. In interactive sessions, goal restrictions are tightened to quantify trade-offs between conflicting goals. Choice and degree of tightening reflect the specific priorities for sustainable land use. The development of LUPAS is exemplified for one case study, Ilocos Norte, Philippines. Weak points of the system include inadequate spatial differentiation of socio-economic characteristics, scarce database for quantifying perennials and mixed cropping systems, and insufficient consideration of long-term effects of production technologies on resource quality. However, a promising perspective for effective policy support lies in the possible link of the regional LUPAS approach with farm household models.
Definitions and concepts of production ecology are presented as a basis for development of alternative production technologies characterized by their input-output combinations. With these concepts the relative importance of several growth factors and inputs is investigated to explain actual yield levels and resource-use efficiencies. Differences between potential and actual levels are analyzed to open ways for improved production technologies. The basis of the analysis is knowledge of basic physical, chemical, physiological and ecological processes at soil, field and crop level. New production technologies and their input-output combinations can be used in studies aimed at the exploration of options for sustainable agricultural production systems and land use. The concepts allow a systematic analysis and quantification of input-output combinations and clearly discriminate between bio-physical possibilities and socio-economic constraints and objectives. They help in defining objectives and means for agricultural production and land use, and may be valuable as aids to communication between various disciplines involved in studying the possibility and feasibility of future production technologies and land use options. The concepts production level, physical environment, target-oriented approach, production technique, production activity, and production orientation are applied to identify new technologies and production systems at various levels of scale, each requiring different types of information. In this paper some examples of applications are given at field, farm and at regional level.
Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer’s income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelón Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelón Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer’s income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale.
The Netherlands Scientific Council for Government Policy (WRR) has explored possible future developments in rural land use within the European Community (EC) to support strategic policy making. Multiple goal linear programming (MGLP) was applied to evaluate different scenarios based on alternative policy views. For the MGLP-model, WRR needed information on agricultural production systems, specifically quantification of inputs like nutrients, water, pesticides, labour and machinery, and outputs like crop yields and environmental pollution. In this paper, the determination of inputs and outputs is described for a number of pre-defined cropping systems at regional level, using results of a land evaluation study for the EC. All cropping systems defined are based on the assumption that the best available production techniques are being used, taking into account that the explorations aim at possible agricultural developments in the next 25 years.
This paper describes a method of investigating development possibilities for a region under various constraints and demands. Use is made of an interactive multiple goal linear programming technique. The method is illustrated with an example from a semi-arid zone in the Mediterranean Basin. It is concluded that the method can help to decide on feasible development pathways within a wide range of technical and socio-economic scenarios, and so explore the ‘margins for policy’. It enables communication between politics, planning and research and can therefore serve as a tool for more efficient development planning.
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