Proceedings of the 4th field robot event 2006, Stuttgart/Hohenheim, Germany, 23-24th June 2006

Zeer uitgebreid verslag van het 4e Fieldrobotevent, dat gehouden werd op 23 en 24 juni 2006 in Stuttgart/Hohenhei

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

This paper considers linear programming problems (LPPs) where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables). New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

GIS-based modeling of land use systems - Common Agricultural Policy reform and its impact on agricultural land use and plant species richness

An assessment of agricultural policy measures and their sustainability needs to consider economic, social, and ecological aspects. The current paradigm shift of the European Union’s Common Agricultural Policy (CAP) from coupled to decoupled transfer payments calls for such an evaluation. Land users have to reevaluate their production program and its spatial allocation. Consequently, agricultural policy influences regional land use patterns and shares of land use systems, which in turn influence regional plant species richness. Connecting land use and ecological models allows to assess socioeconomic and ecologic effects of policy measures by identifying interactions and estimating potential trade-offs. The paper presents the land use model ProLand and the fuzzy expert system UPAL. ProLand models the regional distribution of land use systems while UPAL predicts plant species richness. The models are connected through a GIS and applied to a study area in Hesse, Germany, in order to simulate the effects of changing conditions on land use, economic and social key indicators, and plant species richness. ProLand is a spatially explicit comparative static model that simulates a region’s land use pattern based on natural, socioeconomic, political, and technological parameters. The model assumes land rent maximizing behavior of land users. It calculates and assigns the land rent maximizing land use system for every investigated decision unit, generally a field. A land use system is characterized through crop rotation, corresponding outdoor operations, animal husbandry if applicable, and the relevant political and socioeconomic attributes. The fuzzy expert system derives the values of ecologically relevant parameters from several site specific attributes and land use operations. Land use dependent site characteristics that influence plant species richness are derived from predictions generated by ProLand. Detailed information on crop rotation, fertilization and pesticide strategy, and outdoor operations are considered. The expert system then classifies natural and land use dependent site characteristics into aggregate factors. Based on a set of rules it assigns the number of species to the classes and thus to the decision units. Simulation results for the study area show that the CAP reform causes a rise in grassland area. These land use changes mainly occur in areas currently used for arable farming but with natural conditions favoring grassland. Plant species richness is positively influenced by the increase in extensive grassland area.

Hybrid linear programming to estimate CAP impacts of flatter rates and environmental top-ups

This paper examines evolutions of the Common Agricultural Policy (CAP) decoupling regime and their impacts on Greek arable agriculture. Policy analysis is performed by using mathematical programming tools. Taking into account increasing uncertainty, we assume that farmers perceive gross margin in intervals rather than as expected crisp values. A bottom-up hybrid model accommodates both profit maximizing and risk prudent attitudes in order to accurately assess farmers’ response. Marginal changes to crop plans are expected so that flatter single payment rates cause significant changes in incomes and subsidies. Nitrogen reduction incentives result in moderate changes putting their effectiveness in question.Interval Linear Programming, Min-Max Regret, Common Agricultural Policy, Arable cropping, Greece

Insecticidal and repellant activities of Southeast Asia plants towards insect pests: a review

Crops are being damaged by several plant pests. Several strategies have been developed to restrict the damage of cultivated plants by using synthetic pesticides and repellants. However, the use to control these insects is highly discouraged because of their risks on humans. Therefore, several alternatives have been developed from plant extracts to protect crops from plant pests. Accordingly, this review focuses on outlining the insecticidal and repellant activities of Southeast Asia plants towards insect pests. Several extracts of plants from Southeast Asia were investigated to explore their insecticidal and repellant activities. Azadiracha indica (neem) and Piper species were highly considered for their insecticidal and repellant activities compared to other plants. This review also addressed the investigation on extracts of other plant species that were reported to exert insecticidal and repellant activities. Most of the conducted studies have been still in the primarily stage of investigation, lacking a focus on the insecticidal and repellant spectrum and the identification of the active constituents which are responsible for the insecticidal and repellant activity

Abstracts of Invited and Selected Papers and Organized Symposia, WAEA Annual Meetings, San Francisco, California, July 6-8, 2005

Teaching/Communication/Extension/Profession,

Farm level environmental indicators; are they useful? An overview of Green Accounting Systems for European farms

Green accounts or Input-Output Accounting systems (IOA) have been developed in countries with intensive agricultural production to facilitate voluntary improvements in farm environmental performance. There is a need for an overview of indicators used and a review of results and experiences reported. Ten IOA systems covering the topics of the farm's use of nutrients, pesticides and energy were selected from a survey of 55 systems and compared in this paper. The approaches and indicators used vary from systems based on Good Agricultural Practices (GAP) to accounts based systems that use physical input-output units. Many IOA systems use farm gate nutrient balances, pesticide use per ha and energy use per kg product. These indicators are easy to calculate but the resulting value needs separate interpretation for the farmer. Other systems include modelled emissions and rate the yearly farm results using closed scales, which allows for easy interpretation but builds on implicit normative assumptions of best practices. Participating farmers were most often reported to be motivated for the use of IOA but empirical evidence of improved environmental farm performance was scarce. IOA systems should be linked with production planning tools used by the advisory services. Farmers and advisors needs better reference values to evaluate the indicator levels (environmental performance) on the individual farm possibly based on analysis of a larger number of farms. The statistical properties of IOA indicators need to be researched regarding: (1) The relation between changed management practice and changes in indicator values on a given farm over a period of time. (2) The relative importance of systematic vs. coincidental differences in environmental performance of a set of farms. It is concluded that IOA systems could become effective tools for agri-environmental improvement of European farms given further development and standardisation