Abstract
Although existing simulation tools can be used to study the impact of agricultural management on production activities in specific environments, they suffer from several limitations. They are largely specialized for specific production activities: arable crops/cropping systems, grassland, orchards, agro-forestry, livestock etc. Also, they often have a restricted ability to simulate system externalities which may have a negative environmental impact. Furthermore, the structure of such systems neither allows an easy plug-in of modules for other agricultural production activities, nor the use of alternative components for simulating processes. Finally, such systems are proprietary systems of either research groups or projects which inhibits further development by third parties.
SEAMLESS aims to provide a tool to integrate analyses of impacts on the key aspects of sustainability and multi-functionality, particularly in Europe. This requires evaluating agricultural production and system externalities for the most important agricultural production systems. It also requires a simulation framework which can be extended and updated by research teams, which allows a manageable transfer of research results to operational tools, and which is transparent with respect to its contents and its functionality.
The Agricultural Production and Externalities Simulator (APES) is a modular simulation system aimed at meeting these requirements, and targeted at estimating the biophysical behavior of agricultural production systems in response to the interaction of weather and agro-technical management. APES is a framework which uses components that offer simulation options for different processes of relevance to agricultural production systems. Models are described in the associated help files of components, and a shared ontology is built on the web. Components like these, which are designed to be inherently re-usable, that is not targeted specifically to a given modelling framework, also represent a way to share modelling knowledge with other projects and the scientific community in general.
This chapter describes the current state of APES development and presents modelling options in the system, and its software architecture.
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Acutis, M., Confalonieri, R., Donatelli, M., & Rana, G. (2008). Modellazione dell’allettamento dei cereali a paglia. Proceedings of IX National Congress of Agrometeorology, pp. 84-85.
Acutis, M., Trevisiol, P., Gentile, A., Ditto, D., & Bechini, L. (2007). Software components to simulate surface runoff, water, carbon, and nitrogen dynamics in the soil. Proceedings of Farming Systems Design 2007, Catania, Italy, 10-12 September, 2007.
Alberts, E.E., Nearing, M.A., Weltz, M.A., Risse, L.M., Pierson, F.B., Zhang, X.C., Laflen, J.M., & Simanton, J.R. (1995). WEPP Model user guide. Chapter 7. Soil component.
Analytis, S. (1977). Über die Relation zwischen biologischer Entwicklung und Temperatur bei phytopathogenen Pilzen. Phytopathologische Zeitschrift, 90, 64-76.
Argent, R. M. (2004). An overview of model integration for environmental applications - components, frameworks and semantics. Environmental Modelling and Software, 19, 219-234.
Argent, R.M., & Rizzoli, A.E. (2004). Development of multi-framework model components. In C. Pahl-Wostl, S. Schmidt, A.E. Rizzoli, & A.J. Jakeman (Eds.), Transactions of the 2nd Biennial Meeting of the International Environmental Modelling & Software Society (Vol. 1, pp. 365-370). Osnabrück, Germany: InternationalEnvironmental Modelling and Software Society (iEMSs).
Athanasiadis, I.N., Rizzoli, A.E., Donatelli, M., & Carlini, L. (2006). Enriching software model interfaces using ontology-based tools. iEMSs Congress, Vermont, July 2006, http://www.iemss.org/iemss2006/papers/s5/284_Athanasiadis_1.pdf .
Aylor, D. (1982). Modeling spore dispersal in a barley crop. Agricultural Meteorology, 26(3), 215-219.
Baier, T. (2007). The rcom package. Available online at http://cran.r-project.org/doc/packages/rcom.pdf version 1.5-2.2. Retrieved September 17, 2007.
Baker, C. J., Berry, P. M., Spink, J. H., Sylvester-Bradley, R., Griffin, J. M., Scott, R. K., et al. (1998). A method for the assessment of the risk of wheat lodging. Journal of Theoretical Biology, 194, 587-603.
Balderacchi, M., Boccelli, R., & Trevisan, M. (2007). Tools to assess pesticide environmental fate - Agrochemicals/APES, EPRIP 2 and FitoMarche software. Pavia, Italy: La Goliardica Pavese, pp. 142, ISBN 978-88-7830-477-2.
Barrett, P. D., Laidlaw, A. S., & Mayne, C. S. (2005). GrazeGro, a European herbage growth model to predict pasture production in perennial ryegrass swards for decision support. European Journal of Agronomy, 23, 37-56.
Bastiaans, L. (1991). Ratio between virtual and visual lesion size as a measure to describe reduction in leaf photosynthesis of rice due to leaf blast. Phytopathology, 81(6), 611-615.
Bishop, J. (2008). C# 3.0 design patterns (p. 314). Sebastopol, CA: O’Reilly.
Blaise, P. H., & Gessler, C. (1992). An extended progeny/parent ratio model. I. Theoretical development. Journal of Phytopathology, 134, 39-52.
Braudeau, E. (2006). Le modèle Kamel. DDN.FR.001.390019.000.S.P.2006.000.31500. Paris: Agence pour la Protection des Programmes.
Braudeau, E., & Mohtar, R. H. (2006). Modeling the swelling curve for packed soil aggregates using the pedostructure concept. Journal of the Soil Science Society of America, 70, 494-502.
Braudeau, E., & Mohtar, R.H. (2009). Modeling the soil system: Bridging the gap between pedology and soil-water physics. Global and Planetary Change 67, 51-61.
Brisson, N., Gary, C., Justes, E., Roche, R., Mary, B., Ripoche, D., et al. (2003). An overview of the crop model STICS. European Journal of Agronomy, 18(3-4), 309-332.
Brisson, N., Mary, B., Ripoche, D., Jeuffroy, M. H., Ruget, F., Nicoullaud, B., et al. (1988). STICS: A generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie, 18, 311-346.
Calvière, I., & Duru, M. (1999). The effect of N and P fertilizer application and botanical composition on the leaf/stem ratio patterns in spring in Pyrenean meadows. Grass and Forage Science, 54, 255-266.
Campbell, G. S. (1985). Soil physics with BASIC (p. 150). Amsterdam: Elsevier.
Carlini, L., Bellocchi, G., & Donatelli, M. (2006). Rain, a software component to generate synthetic precipitation data. Agronomy Journal, 98, 1312-1317.
Carsel, R.F., Imhoff, J.C., Kummel, P.R., Cheplick, J.M., & Donigan, A.S.J. (1988). PRZM-3 A model for predicting pesticide and nitrogen fate in the crop root and unsatured soil zones: User manual for release 3.0. Athens, GA: National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency.
Castelan-Estrada, M. (2001). Growth and dry matter allocation in grapevine (Vitis vinifera): Radiation use efficiency and energetic costs. Ph.D. thesis, INA Paris-Grignon, France, 121 p.
Confalonieri, R., Acutis, M., Bellocchi, G., Cerrani, L., Tarantola, S., Donatelli, M., et al. (2006). Exploratory sensitivity analysis of CropSyst, WARM and WOFOST: A case-study with rice biomass simulations. Italian Journal of Agrometeorology, 3, 17-25.
Confalonieri, R., Bellocchib, G., & Donatelli, M. (2010). A software component to compute agro-meteorological indicators. Environmental Modelling and Software. (in press) Available from http://dx.doi.org/10.1016/j .envsoft.2008.11.007
Cooley, K.R. (1980). Erosivity “R” for individual design storms. In W.G. Knisel (Ed.), CREAMS: A field-scale model for chemicals, runoff, and erosion from agricultural management systems (pp. 386-397) (USDA-SEA Conservation Research Rep. No. 26). Washington, DC: USDA.
Corbeels, M., McMurtrie, R. E., Pepper, P. A., & O’Connell, A. M. (2005). A process-based model of nitrogen cycling in forest plantations. Part I. Structure, calibration and analysis of the decomposition model. Ecological Modelling, 187(4), 426-448.
Cwalina, K., & Abrams, B. (2006). Aggregate components. In Framework design guidelines: Conventions, idioms, and patterns for reusable.NET libraries (pp. 235-271). Westford, MA: Addison-Wesley.
David, O., Markstrom, S. L., Rojas, K. W., Ahuja, L. R., & Schneider, W. (2002). The object modelling system. In L. R. Ahuja, L. Ma & T. A. Howell (Eds.), Agricultural system models in field research and technology transfer (pp. 317-344). Boca Raton, FL: Lewis.
Del Furia, L., Rizzoli, A., & Arditi, R. (1995). Lakemaker: A general object-oriented software tool for modelling the eutrophication process in lakes. Environmental Software, 10(1), 43-64.
Di Guardo, A., Donatelli, M., & Botta, M. (2007). Two framework components to simulate biophysical systems. In Proceedings of Farming Systems Design 2007, Catania, Italy, 10-12 September 2007.
Donatelli M., Acutis M., Bregaglio S., Rosenmund A., & Casellas E. (2009). A framework and a software component to simulate agricultural management. Environmental Modelling and Software (submitted).
Donatelli, M., Bellocchi, G., & Carlini, L. (2006a). A software component for estimating solar radiation. Environmental Modelling and Software, 21(3), 411-416.
Donatelli, M., Bellocchi, G., & Carlini, L. (2006b). Sharing knowledge via software components: Models on reference evapotranspiration. European Journal of Agronomy, 24(2), 186-192.
Donatelli, M., Bolte, J., van Evert, F., & Wang, W. (2003). Which software designs for evolution. In M.K. van Ittersum & M. Donatelli (Eds.), Modelling cropping systems: Science, software and applications. European Journal of Agronomy, 18, 193-195.
Donatelli M., Bellocchi G., Habyarimana E., Confalonieri R., & Micale F. (2009). An extensible model library for generating wind speed data. Computers and Electronics in Agriculture, 69 (2009) 165-170.
Donatelli, M., Bellocchi G., Habyarimana E., Bregaglio S., Confalonieri R. & Baruth B., (2009b). CLIMA: a weather generator framewor. In Anderssen, R.S., R.D. Braddock and L.T.H. Newham (eds) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009, pp. 2377-2383. ISBN: 978-0-9758400-7-8. http://www.mssanz.org.au/modsim09/C3/donatelli_C3a.pdf
Donatelli, M., Confalonieri R., Cerrani I., Fanchini D., Acutis M., Tarantola S. & Baruth B., (2009c). LUISA (Library User Interface for Sensitivity Analysis): a generic software component for sensitivity analysis of bio-physical models. In Anderssen, R.S., R.D. Braddock and L.T.H. Newham (eds) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009, pp. 2377-2383. ISBN: 978-0-9758400-7-8. http://www.mssanz.org.au/modsim09/C3/donatelli_C3b.pdf
Donatelli, M., Omicini, A., Fila, G., & Monti, C. (2004). Targeting reusability and replaceability of simulation models for agricultural systems. In S.E. Jacobsen, C.R. Jensen, & J.R. Porter (Eds.), Proceedings of the 8th European Society for Agronomy Congress (pp. 237-238), 11-15 July, Copenhagen, Denmark.
Donatelli, M., & Rizzoli, A. (2008). A design for framework-independent model components of biophysical systems International Congress on Environmental Modelling and Software iEMSs 2008. Proceedings of the iEMSs Fourth Biennial Meeting, Barcelona, Catalonia, 7-10 July 2008, pp. 727-734.
Duru, M. (2008). Improvement of time-driven models of lamina cocksfoot digestibility by a process-based model to take account of plant N nutrition and defoliation. Journal of Agronomy and Crop Science, 194(5), 401-412.
Duru, M., Adam, M., Cruz, P., Martin, G., Ansquer, P., Ducourtieux, C., Jouany, C., Theau, J.P., & Viegas, J. (2009a). Modelling above-ground herbage mass for a wide range of grassland community types. Ecological Modelling, 220, 209-225.
Duru, M., Al Haj Khaled, R., Ducourtieux, C., Theau, J.P., Quadros, F., & Cruz, C. (2009). Do plant functional types based on leaf dry matter content allow characterizing native grass species and grasslands for herbage growth pattern? Plant Ecology, 201, 421-433.
Duru, M., Cruz, P., Haj Khaled, R., Ducourtieux, C., & Theau, J. P. (2008). Relevance of plant functional types based on leaf dry matter content for assessing digestibility of native grass species and species-rich grassland communities in spring. Agronomy Journal, 100, 1622-1630.
Ferrer-Alegre, F., & Stockle, C. O. (1999). A model for assessing crop response to salinity. Irrigation Science, 19, 15-23.
Georgiadis, T., Rossi, S., & Nerozzi, F. (1995). Inferring ozone deposition on agricultural surfaces: An application to herbaceous and tree canopies. Water, Air, and Soil Pollution, 84, 117-128.
Green, W.H., & Ampt, G.A. (1914). Studies on soil physics. Journal of Agricultural Science, 4(1), 1-24. Hydrology. Transactions American Society Agricultural Engineering, 20, 1100-1104.
Hearn, A.B. (1994). The principles of cotton water relations and their application in management. In G.A. Constable & N.W. Forrester (Eds.), Proceedings World Cotton Research Conference, 1st, Brisbane, Australia (pp. 66-92), 14-17 February 1994. Melbourne, Australia: CSIRO.
Hillyer, C., Bolte, J., van Evert, F., & Lamaker, A. (2003). The MODCOM modular simulation system. European Journal of Agronomy, 18(3-4), 333-343.
Jantunen, A. P. K., Trevisan, M., & Capri, E. (2005). Computer models for characterizing the fate of chemicals in soil: Pesticide leaching models and their practical applications. In J. Alvarez-Bendì & R. Muñoz-Carpena (Eds.), Soil-Water-Solute process characterisation: An integrate approach (pp. 715-756). Boca Raton, FL: CRC Press.
Johnsson, H., Bergström, L., Jansson, P. E., & Paustian, K. (1987). Simulated nitrogen dynamics and losses in a layered agricultural soil. Agriculture, Ecosystems, and Environment, 18, 333-356.
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., et al. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4), 235-265.
Jones, J. W., Keating, B. A., & Porter, C. H. (2001). Approaches to modular model development. Agricultural Systems, 70, 421-443.
Karlberg, L., Ben-Gal, A., Jansson, P.-E., & Shani, U. (2006). Modelling transpiration and growth in salinity-stressed tomato under different climatic conditions. Ecological Modelling, 190, 15-40.
Keating, B. A., Carberry, P. S., Hammer, G. L., Probert, M. E., Robertson, M. J., Holzworth, D., et al. (2003). An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18(3-4), 267-288.
Lavorel, S., & Garnier, E. (2002). Predicting changes in community composition and ecosystem functioning from plant traits, revisiting the Holy Grail. Functional Ecology, 16, 545-556.
Magarey, R. D., Sutton, T. B., & Thayer, C. L. (2005). A simple generic infection model for foliar fungal plant pathogens. Phytopathology, 95(1), 92-100.
Makowski, D., Hillier, J., Wallach, D., Andrieu, B., & Jeuffroy, M. H. (2006). Parameter estimation for crop models. In D. Wallach, D. Makowski & J. W. Jones (Eds.), Working with dynamic crop models (pp. 101-150). Amsterdam: Elsevier.
Martin, P., Mohtar, R. H., Clouvel, P., & Braudeau, E. (2006, July). Modeling soil-water dynamics for diverse environmental needs. Vermont: iEMSs Congress.
McCall, D. G., & Bishop-Hurley, G. J. (2003). A pasture growth model for use in a whole-farm dairy production model. Agricultural Systems, 76, 1183-1205.
Mesketer, S. J. (2004). Design patterns in C#. Boston: Addison-Wesley.
Meyer, B. (1991). Design by contract. In D. Mandrioli & B. Meyer (Eds.), Advances in object-oriented software engineering. Englewnod Cliffs, NJ: Prentice Hall.
Monteith, J. L. (1977). Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 281, 277-294.
Monteith, J. L., & Unsworth, M. H. (1990). Principles of environmental physics. Woburn, MA: Butterworth-Heinemann.
Morgan, R. P. C., Quinton, J. N., Smith, R. E., Govers, G., Poesen, J. W. A., Auerswald, K., et al. (1998). The European soil erosion model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. Earth Surface Processes and Landforms, 23, 527-544.
Mulia, R. (2005). Modélisation tri-dimensionnelle de la croissance du système racinaire des plantes en milieu hétérogène avec l’approche de l’automate voxellaire. Ph.D. thesis, USTL, Montpellier 2, p. 86.
Mulia, R., & Dupraz, C. (2006). Unusual fine root distributions of two deciduous tree species in southern France: What consequences for modelling of tree root dynamics? Plant and Soil, 281(1/2), 71-85.
Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R., & King, K.W. (2002). Soil and water assessment tool. Theoretical Documentation. Temple, TX: Grassland, Soil and Water Research Laboratory, p. 506.
Nendel, C., & Kersebaum, K. C. (2004). A simple model approach to simulate nitrogen dynamics in vineyard soils. Ecological Modelling, 177, 1-15.
Ollat, N., Diakou-Verdin, P., Garde, J. P., Barrieu, F., Gaudillière, J. P., & Moing, A. (2002). Grape berry development: A review. Journal International des Sciences de la Vigne et du Vin, 36(3), 109-131.
Parton, W. J. (2004). Predicting soil temperatures in a shortgrass steppe. Soil Science, 138, 93-101.
Pronk, A., Goudriaan, J., Stilma, E., & Challa, H. (2003). A simple method to estimate radiation interception by nursery stock conifers: A case study of eastern white cedar. Netherlands Journal of Agricultural Science, 51, 279-295.
R Development Core Team. (2007). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
Ritchie, J. T. (1972). Model for predicting evaporation from a row crop with incomplete cover. Water Resources Research, 85, 1204-1211.
Ritchie, J.T. (1991). Wheat phasic development. In J. Hanks & J.T. Ritchie (Eds.), Modelling plant and soil systems. Agronomy Monographs 31 (pp. 31-54). Madison, WI: ASA, CSSSA, SSSA.
Ritchie, J.T., & Otter, S. (1985). Description and performance of CERES-Wheat: A user oriented wheat yield model. In ARS Wheat Yield Project. ARS-28 (pp. 159-175). Springfield, VA: National Technology Information Service.
Rizzoli, A. E., Donatelli, M., Athanasiadis, I., Villa, F., Muetzelfeldt, R., & Huber, D. (2005). Semantic links in integrated modelling frameworks. Mathematics and Computers in Simulation, 78, 412-423.
Rizzoli, A.E., Donatelli, M., Muetzelfeldt, R., Otjens, T., Svennson, M.G.E., van Evert, F., Villa, F., & Bolte, J. (2004). SEAMFRAME, a proposal for an integrated modelling framework for agricultural systems. In S.E. Jacobsen, C.R. Jensen, & J.R. Porter (Eds.), Proceedings of the 8th European Society for Agronomy Congress (pp. 331-332), 11-15 July, Copenhagen, Denmark.
Saltelli, A.,Tarantola, S., Campolongo, F. & Ratto, M. (2004). Sensitivity analysis in practice: a guide to assessing scientific models. Chichester, England: John Wiley & Sons Ltd.
Saxton, K. E., & Rawls, W. J. (2006). Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Journal of the Soil Science Society of America, 70, 1569-1578.
Schapendonk, A. H. C. M., Stol, W., Van Kraalingen, D. W. G., & Bouman, B. A. M. (1998). LINGRA, a sink/source model to simulate grassland productivity in Europe. European Journal of Agronomy, 9, 87-100.
M.E. Shibu, P.A. Leffelaar, H. van Keulen, P.K. Aggarwal (2009). LINTUL3, a simulation model for nitrogen-limited situations - application to rice European Journal of Agronomy (submitted).
Shimono, H., Hasegawa, T., Moriyama, M., Fujimura, S., & Nagata, T. (2005). Modeling spikelet sterility induced by low temperature in rice. Agronomy Journal, 97, 1524-1536.
Sitch, S., Cox, P. M., Collins, W. J., & Huntigford, C. (2007). Indirect radiative forcing of climate change through ozone effects on the land-carbon sink. Nature, 448, 791-795.
Smith, R. E., & Parlange, J. Y. (1978). A parameter-efficient hydrologic infiltration model. Water Resources Research, 14, 533-538.
Soil Conservation Service. (1972). Section 4: Hydrology. In National Engineering Handbook. SCS.
Spiker, E. C., Hosker, R. P., Comer, V. J., White, J. R., Werre, R. W., Jr., Harmon, F. L., et al. (1992). Environmental chamber for study of the deposition flux of gaseous pollutants to material surfaces. Atmospheric Environment, 26, 2885-2892.
Stockle, C. O., Donatelli, M., & Nelson, R. (2003). CropSyst, a cropping systems simulation model. European Journal of Agronomy, 18(3-4), 289-307.
Streck, N. A., Weiss, A., Xue, Q., & Baenziger, P. S. (2003). Improving predictions of developmental stages in winter wheat: A modified Wang and Engel model. Agricultural and Forest Meteorology, 115, 139-150.
Szypersky, C., Gruntz, D., & Murer, S. (2002). Component software - beyond object-oriented programming (2nd ed.). London: Addison-Wesley.
Tiktak, A., Van den Berg, F., Boesten, J.J.T.I., Van Kraalingen, D., Leistra, M., & Van der Linden, A.M.A. (2001). Manual of FOCUS PEARL v 1.1.1. RIVM Report 711401008, Alterra Report 28 (p. 144). Bilthoven, The Netherlands: RIVM.
Trevisan, M., Sorce, A., Balderacchi, M., & Di Guardo, A. (2007). A software component to simulate agro-chemicals fate. In Proceedings of Farming Systems Design 2007, Catania, Italy, 10-12 September 2007.
Van Dam, J.C., Huygen, J., Wesseling, J.G., Feddes, R.A., Kabat, P., Van Walsum, P.E.V., Groenendijk, P., & Van Diepen, C.A. (1997). Theory of SWAP version 2.0. Report 71. Wageningen, The Netherlands: Department of Water Resources, WAU.
Van Evert, F., & Lamaker, A. (2007). The MODCOM framework for component-based simulation. In proceedings of Farming Systems Design 2007, Catania, Italy, 10-12 September, 2007.
Van Ittersum, M. K., Ewert, F., Heckelei, T., Wery, J., Alkan Olsson, J., Andersen, E., et al. (2008). Integrated assessment of agricultural systems - A component-based framework for the European Union (SEAMLESS). Agricultural Systems, 96(1-3), 150-165.
Van Ittersum, M. K., Leffelaar, P. A., Van Keulen, H., Kropff, M. J., Bastiaans, L., & Goudriaan, J. (2003). On approaches and applications of the Wageningen crop models. European Journal of Agronomy, 18(3-4), 187-393.
Van Keulen, H., & Seligman, N.G. (1987). Simulation of water use, nitrogen nutrition and growth of a spring wheat crop. Simulation Monographs. Wageningen, The Netherlands: Pudoc.
Van Keulen, H., & Wolf, J. (1986). Modelling of agricultural production: Weather soils and crops. Simulation Monographs. Wageningen, The Netherlands: Pudoc.
Villa F., Donatelli, M., Rizzoli, A., Krause, P., Kralisch, S., & Van Evert, F.K. (2006, July). Declarative modelling for architecture independence and data/model integration: A case study. iEMSs congress, Vermont.
Vivin, Ph, Castelan, M., & Gaudillère, J. P. (2002). A source/sink model to simulate seasonal allocation of carbon in grapevine. Acta Horticulturae, 584, 43-56.
Von Hoyningen-Huene, J. (1981). Die Interzeption des Niederschlags in landwirtschaftlichen Pjanzenbestanden. Arbeitsbericht Deutscher Verband fur Wasserwirtschaft und Kulturbau, DVWK, Braunschweig.
Wadia, K. D. R., & Butler, D. R. (1994). Relationship between temperature and latent periods of rust and leaf-spot diseases of groundnut. Plant Pathology, 43, 121-129.
Waggoner, P. E. (1973). The removal of Helminthosporium maydis spores by wind. Phytopathology, 63(10), 1252-1255.
Waggoner, P. E., & Horsfall, J. G. (1969). EPIDEM. A simulator of plant disease written for a computer. Bulletin of the Connecticut Agricultural Experiment Station, 698, 80.
Wermelinger, B., & Koblet, W. (1990). Seasonal growth and nitrogen distribution in grapevine leaves, shoots and grape. Vitis, 29, 15-26.
Williams, J.R., & Berndt, H.D. (1977). Sediment Yield Prediction Based on Watershed Hydrology. Transactions of the American Society of Agricultural Engineers, 20, 1100-1104.
Williams, J. R., Jones, C. A., Kiniry, J. R., & Spanel, D. A. (1989). The EPIC crop growth model. Transactions of the American Society of Agricultural Engineering, 32, 497-511.
Woolhiser, D.A., Smith, R.E., & Goodrich, D.C. (1990). KINEROS, a kinematic runoff and erosion model: Documentation and user manual. United States Department of Agriculture, ARS-77.
Wosten, J. H. M., Lilly, A., Nemes, A., & Le Bas, C. (1999). Development and use of a database of hydraulic properties of European soils. Geoderma, 90, 169-185.
Zadoks, J.C., & Schein, R.D. (1979). Epidemiology and plant disease management (p. 427). London: Oxford University Press.
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The development of APES was partially funded by the EU - DG Research, Sixth Framework Research Programme, Integrated Project SEAMLESS (http://www.seamless-ip.org ), contract no. 010036-2
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Donatelli, M. et al. (2010). A Component-Based Framework for Simulating Agricultural Production and Externalities. In: Brouwer, F., Ittersum, M. (eds) Environmental and Agricultural Modelling. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3619-3_4
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