Using decision support systems to optimize barley management on spatial variable soil.

Increasing awareness of possible pollution, due to agricultural practices, has resulted in ‘precision agriculture’. Precision agriculture allows the farmer to use soil spatial variability to site-specifically adjust farm management strategies, e.g. spatial variable fertilization or irrigation applications. The aim of precision agriculture is to optimize crop yields and to make more efficient use of agrochemicals by reducing leaching. The CERES-Barley model from the decision support system DSSATv3 (Decision Support System for Agrotechnology Transfer) was used to simulate crop and soil responses on the experimental farm, the ‘Professor van Bemmelenhoeve’ in The Netherlands. DSSAT was subsequently used to simulate and analyse different farm management scenarios. Barley yields, economic benefits and possible leaching of fertilizers (as a result of the different management scenarios) were quantified. The use of this type of decision support system, for analysing agroecological systems, allows farmers, extension services and scientists to define agricultural practices for different crops which balance production and ecological interests in various climatological zones.

[1]  Modelling,et al.  Wheat Growth and Modelling , 1985, NATO ASI Science.

[2]  Ralph H. Sprague,et al.  Building Effective Decision Support Systems , 1982 .

[3]  D. C. Godwin,et al.  Nitrogen dynamics in soil-plant systems. , 1991 .

[4]  J. Bouma,et al.  A procedure to identify different groups of hydraulic-conductivity and moisture-retention curves for soil horizons , 1986 .

[5]  M. J. Kropff,et al.  Applications of Systems Approaches at the Field Level , 1997, Systems Approaches for Sustainable Agricultural Development.

[6]  A. Stein,et al.  Spatial variability and sampling of cyanide polluted soil on former galvanic factory premises , 1992 .

[7]  Peter Finke,et al.  Field scale variability of soil structure and its impact on crop growth and nitrate leaching in the analysis of fertilizing scenarios , 1993 .

[8]  I. Ohlsson.  Book reviewSite-specific management for agricultural systems: P.C. Robert, R.H. Rust and W.E. Larson (Editors). American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Madison, WI, 1995. ISBN 0-89118-127-X, Paperback, 993 pp., US$ 39 , 1996 .

[9]  G. Y. Tsuji,et al.  The IBSNAT project , 1993 .

[10]  H. C. Andrews.  Jones, J. W. , 1948 .

[11]  P. K. Thornton,et al.  Linking crop models to geographical information systems to assist decision making: a prototype for the Indian semiarid tropics , 1993 .

[12]  Paul Teng,et al.  Systems approaches for agricultural development , 1993, Systems Approaches for Sustainable Agricultural Development.

[13]  Gedeon Dagan,et al.  Unsaturated flow in spatially variable fields: 1. Derivation of models of infiltration and redistribution , 1983 .

[14]  Application of disjunctive cokriging to compare fertilizer scenarios on a field scale , 1994 .

[15]  J. Ritchie,et al.  Modeling Plant and Soil Systems , 1991 .

[16]  Philip J. Bauer,et al.  Spatial Corn Yield During Drought in the SE Coastal Plain , 1995 .

[17]  H.W.G. Booltink,et al.  Site-specific management: balancing production and environmental requirements at farm level. , 1995 .

[18]  James W. Jones,et al.  Decision support systems for agricultural development , 1993 .

[19]  James W. Jones,et al.  WeatherMan: a utility for managing and generating daily weather data , 1994 .