Herman van Keulen

Resource limitations in Sahelian agriculture

Abstract In general, Africa has poor soils and unfavorable climates for agriculture. This is specially so in the Sahel of West Africa. Moreover, poor infrastructure means that fertilizer prices are higher in the Sahel than in Europe. Sahelian farmers have few incentives to maintain, let alone improve output. Nonetheless, the results of field experiments show that there are methods by which they could do this, in particular, by improving soil organic matter status, since this is often the principal way in which N, P and K are held in the soil. In the general absence of good policies to encourage fertility improvement, the Lome workshop set goals for national fertilizer plans.

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

Effect of N fertilizer top-dressing at various reproductive stages on growth, N2 fixation and yield of three soybean (Glycine max (L.) Merr.) genotypes

Soybean (Glycine max (L.) Merr.) is one of the most important food and cash crops in China and a key protein source for the farmers in northern China. Previous experiments in both the field and greenhouse have shown that N2 fixation alone cannot meet the N requirement for maximizing soybean yield, and that N top-dressing at the flowering stage was more efficient than N top-dressing at the vegetative stages. However, the effect of N fertilizer application at other reproductive stages of soybean is unknown. Thus, a field experiment was conducted to study the effects of N applications at various reproductive stages on growth, N2 fixation and yield of three soybean genotypes. The results showed that starter N at 25 kg ha−1 resulted in minimum yield, total N accumulation and total amount of N2 fixed in all three genotypes. N top-dressing at 50 kg ha−1 at either the V2 or R1 stages, significantly increased N accumulation, yield and total amount of N2 fixed in all three genotypes. However, N top-dressing at the same rate at either the R3 or R5 stage did not show this positive effect in any of the three genotypes. Thus, the best timing for N top-dressing during reproduction is at the flowering stage, which increased seed yield by 21% for Wuyin 9, 27% for You 91-19, and 26% for Jufeng, respectively, compared to the treatment without N top-dressing.

Modelling the dynamics of agricultural development at farm and regional level

Policy making, to enhance sustainable agricultural development, requires insight in the complex dynamics of agricultural systems at the farm and regional level. These include the way farmers take management decisions, the effects of these decisions on soil fertility and crop and animal production and the consequences of these production levels for prices at regional level, which in turn influence decisions at the farm level. Moreover, interactions between farms should be taken into account in an environment were an expanding agriculture is facing the limitations of space. This paper discusses a number of modelling approaches that are used to support decision-making on these issues. The paper argues that the study of such systems requires the use of non-linear dynamic models that allow simulation of the system in a qualitative way, based on a description of the underlying processes. The approach is illustrated with a regional model that has been developed to simulate agricultural development in the Koutiala region in the south-western part of Mali. The paper shows how the approach helps to better understand the dynamics of this system and how it may help to explore the effect of policies on sustainability. Finally the strong and weak points of the approach are discussed.

(Tropical) soil organic matter modelling: problems and prospects

Soil organic matter plays an important role in many physical, chemical and biological processes. However, the quantitative relations between the mineral and organic components of the soil and the relations with the vegetation are poorly understood. In such situations, the use of models is an important research tool to explore the relations between the various components, to increase insight into processes, to examine the consequences of management, and to explore the possibilities for modification. An overview is given of the state-of-the-art in modelling of soil organic matter dynamics, with special emphasis on the processes in tropical regions. Major points identified as insufficiently developed include: Methodology is lacking to quantitatively describe the impact of soil texture and soil structure on the activity of soil biota. Effects of the microfauna on modelled organic matter transformations in the soil appear to be lacking. Techniques for direct measurement of pool sizes and characterisation of the relevant properties of the variety of organic substances would represent a major step towards verification of models and the revision of inherent concepts. The non-nutrient functions of organic matter, such as structural stability, water holding capacity and cation exchange capacity, need far more attention in modelling of soil organic matter.Soil organic matter plays an important role in many physical, chemical and biological processes. However, the quantitative relations between the mineral and organic components of the soil and the relations with the vegetation are poorly understood. In such situations, the use of models is an important research tool to explore the relations between the various components, to increase insight into processes, to examine the consequences of management, and to explore the possibilities for modification. An overview is given of the state-of-the-art in modelling of soil organic matter dynamics, with special emphasis on the processes in tropical regions. Major points identified as insufficiently developed include: Methodology is lacking to quantitatively describe the impact of soil texture and soil structure on the activity of soil biota. Effects of the microfauna on modelled organic matter transformations in the soil appear to be lacking. Techniques for direct measurement of pool sizes and characterisation of the relevant properties of the variety of organic substances would represent a major step towards verification of models and the revision of inherent concepts. The non-nutrient functions of organic matter, such as structural stability, water holding capacity and cation exchange capacity, need far more attention in modelling of soil organic matter.

Combining farm and regional level modelling for Integrated Resource Management in East and South-east Asia

Abstract Currently, in many of the highly productive lowland areas of East and South-east Asia a trend to further intensification and diversification of agricultural land use can be observed. Growing economies and urbanization also increase the claims on land and water by non-agricultural uses. As a result, decisions related to the management and planning of scarce resources become increasingly complex. Technological innovations at the field/farm level are necessary but not sufficient – changes in resource use at regional scale will also be essential. To support decision-making in such situations, we advocate a multi-scale modelling approach embedded in a sound participatory process. To this end, the Integrated Resource Management and Land use Analysis (IRMLA) Project is developing an analytical framework and methods for resource use analysis and planning, for four sites in Asia. In the envisaged multi-scale approach, integration of results from field, farm, district and provincial level analysis is based on interactive multiple goal linear programming (IMGLP), farm household modelling (FHM), production ecological concepts and participatory techniques. The approach comprises the following steps: (i) inventory/quantification of current land use systems, resource availability, management practices and policy views, (ii) analysis of alternative, innovative land use systems/technologies, (iii) exploration of the opportunities and limitations to change resource use at regional scale under alternative future scenarios, (iv) modelling decision behaviour of farmers and identification of feasible policy interventions, and (v) synthesis of results from farm to regional level for negotiation of the most promising options by a stakeholder platform. In the current paper, the operationalisation of dual-scale analysis is illustrated by the outputs (development scenarios, promising policy measures and innovative production systems) from various component models for the case study Ilocos Norte, Philippines. An approach is discussed for the integration of results from the different model components at two different decision making levels (farm and province).

Nutrient Dynamics On Smallholder Farms In Teghane, Northern Highlands Of Ethiopia

To evaluate the sustainability of agricultural systems, the dynamics of nitrogen (N), phosphorus (P) and potassium (K) were studied at field and farm scales in Teghane micro-catchment, Northern Highlands of Ethiopia. Three farm wealth groups (rich, medium and poor) were distinguished based on farm size, capital assets and grain stocks. The NUTMON questionnaire and software have been used for data collection and calculation of partial macronutrient balances. The study indicates that total input to farm fields of all three macronutrients does not balance nutrient removal in crop yield and animal feeds. Consequently, N, P and K stocks in the soil are rapidly declining, with annual depletion rates higher for the rich group (2.4% of total N, 1.3% of total P and 1.3% of total K) than for the poor group (1.0% of total N, 0.2% of total P and 0.4% of total K), and the medium group taking an intermediate position. For all three groups, current farm management is not sustainable. The study clearly identifies the need for the development of integrated nutrient management systems to reduce the high rates of nutrient depletion and to transfer to sustainable farm management systems. Three possible measures can be suggested: First, improvements in nutrient use efficiency from manure, which could be attained through judicious management, i.e. manure must be carefully stored to minimize physical loss of the manure/compost and nutrients, and that manure must be applied to the appropriate crop with the appropriate method at the proper time. Secondly, introduction of energy-saving stoves to reduce use of cattle dung for fuel and consequently increasing manure availability for field application. Thirdly, application of more external chemical fertilizer, together with improved rainwater harvesting for supplementary moisture supply.

Climate change and drought risks for agriculture

Changes in rainfall patterns and risk of crop failure are discussed in this chapter. Agriculture is by far the most important economic activity in the region. The success of this economic activity relies heavily on water availability during the growing season. For rainfed production systems timing and the amount of precipitation determine to a large extent the success of the growing season. The projected changes in the variability and total amount of rainfall are expected to worsen the situation.

A system identification approach for developing and parameterising an agroforestry system model under constrained availability of data

This paper introduces a system identification approach to overcome the problem of insufficient data when developing and parameterising an agroforestry system model. Typically, for these complex systems the number of available data points from actual systems is less than the number of parameters in a (process-based) model. In this paper, we follow a constrained parameter optimization approach, in which the constraints are found from literature or are given by experts. Given the limited a priori systems knowledge and very limited data sets, after decomposition of the parameter estimation problem and after model adaptation, we were able to produce an acceptable correspondence with validation data from a real-world agroforestry experiment.

Designing a “Target-Tree” for Maximizing Gross Value of Product in Patagonian Sweet Cherry Orchards

Abstract A “target-tree” approach to maximize gross value of product (GVP; US