Editorial 19; John V. Stafford; Keynotes 21; Field effect transistors in precision agriculture 23; Ernst J.R. Sudholter, Louis C.P.M. de Smet and Han Zuilhof; A review of spectroscopic methods and their suitability as analytical techniques for farm testing 31; Lars-Ove Sjaunja; Guidance and automated steering drive resurgence in precision farming 39; S. Berglund and R. Buick; Precision agriculture: the solution to control nutrient emissions? 47; J. Stoorvogel and J. Bouma; Precision agriculture: a Western Australian perspective 57; C. Fowler; Spatial variability in weeds and pests 63; Discrimination between nitrogen deficiency and fungal infection of winter wheat by laser induced fluorescence 65; I. Tartachnyk, I. Rademacher and W. Kuhbauch; Site-specific identification of fungal infection and nitrogen deficiency in wheat crop using remote sensing 73; J. Jacobi and W. Kuhbauch; Use of remote sensing within the optical and thermal spectral ranges in order to detect Septoria tritici on winter wheat 81; Herve Nicolas; Digital infrared thermography for the assessment of leaf pathogens 91; E.-C. Oerke, M. Lindenthal, P. Frohling and U. Steiner; Managing soilborne diseases in Australian field crops using precision agriculture and soil DNA tests 99; J.W. Heap and A.C. McKay; Detection and mapping of Ridolfia segetum Moris patches in sunflower (Helianthus annuus L.) crop using remote sensing techniques 107; J. M. Pena-Barragan, F. Lopez-Granados, M. Jurado-Exposito and L. Garcia-Torres; Weed density prediction with secondary input of DEM information 115; M. Jurado-Exposito, F. Lopez-Granados, J. M. Pena-Barragan and L. Garcia-Torres. Feasibility of a real-time weed detection system using spectral reflectance 123; J. Bossu, Ch. Gee, J.P. Guillemin and F. Truchetet; Site-specific weed control using digital image analysis and georeferenced application maps: On-farm experiences 131; H. Oebel and R. Gerhards; Site specific weed control and spatial distribution of a weed seedbank 139; H. Nordmeyer; Weed identification with chlorophyll fluorescence image analysis 147; H. Nordmeyer, S. Aulich and A. Kluge; The sampling problem in weed control - are currently applied sampling strategies adequate for site-specific weed control? 155; M. Backes, D. Schumacher and L. Plumer; Describing weed patches by shape parameters 163; M. Backes, L. Plumer; Development of an image analysis system for estimation of weed pressure 169; A. Ribeiro, C. Fernandez-Quintanilla, J. Barroso and M.C. Garcia-Alegre; Vision based detection of volunteer potatoes as weeds in sugar beet and cereal fields 175; A.T. Nieuwenhuizen, J.H.W. van den Oever, L. Tang, J.W. Hofstee and J. Muller; Spatial variability in crops 183; Effect of travel speed on characterizing citrus canopy structure with a laser scanner 185; M. Salyani and J. Wei; Crop variability and resulting management effects 193; D. Ehlert and R. Adamek; Vehicle mounted sensors for estimating tiller density and leaf area index (LAI) of winter wheat 201; I.M. Scotford and P.C.H. Miller; Temporal prediction of nitrogen status in wheat under the influence of water deficiency using spectral and thermal information 209; L.K. Christensen, D. Rodriguez, R. Belford, V. Sadras, P. Rampant and P. Fisher; Measuring crop status using multivariate analysis of hyperspectral field reflectance with application to disease severity and plant density 217; A. Larsolle and H. Hamid Muhammed; Analyses of spaceborne hyperspectral and directional CHRIS data to deliver crop status for precision agriculture 227; Silke Begiebing, Heike Bach, Daniel Waldmann and Wolfram Mauser. Wheat yield population response to variable rate N fertilization strategies using active NDVI sensors 235; G.J. Schwab, E.M. Pena-Yewtukhiw, O. Wendroth, L.W. Murdock and T. Stombaugh; In-field assessment of wheat-leaf polyphenolics using the new optical leaf-clip Dualex 243; Z.G. Cerovic, A. Cartelat, Y. Goulas and S. Meyer; Application of hyperspectral canopy reflectance measurement and partial least square regression to predict within-field spatial variation in crop growth and nitrogen status before heading stage of rice 251; Hung. T. Nguyen, Jun Han Kim, Anh T. Nguyen, Jin Chul Shin, Byun-Woo Lee; Optimum waveband selection for determining the nitrogen uptake in winter wheat by active remote sensing 261; S. Reusch; Spatial variability of crop water stress in an olive grove with high-spatial thermal remote sensing imagery 267; G. Sepulcre-Canto, P.J. Zarco-Tejada, J.A. Sobrino, J.C. Jimenez-Munoz and F.J. Villalobos; Laser-induced chlorophyll fluorescence sensing to determine biomass and nitrogen uptake of winter wheat under controlled environment and field conditions 273; C. Bredemeier and U. Schmidhalter; Digital infrared thermography for monitoring canopy health of wheat 281; J.-H. Lenthe, E.-C. Oerke and H.-W. Dehne; On-the-go detection of plant parameters by camera vision in rape 289; K.-H. Dammer; Suitability of different crop parameters for the determination of site-specific nitrogen fertilizer demand 297; A. Link, J. Jasper and S. Reusch; Spatial relationships between soil amino sugar nitrogen, soil properties and landscape attributes 303; J.D. Williams, C.R. Crozier, D.A. Crouse, J.G. White, J. Bang, M. Duffera; A comparison of fertilizer strategies for spring barley (Hordeum vulgare L.) based on measured yield response to applied N on morainic soils in SE Norway 311; A. Korsaeth and H. Riley; Discriminating the effect of nitrogen and other environmental stresses on spatial variability of wheat yield in Mediterranean environments 319; R. Casa, F. Pieruccetti, N. Rosati and B. Lo Cascio; Evaluation of mapping and on-line nitrogen fertilizer application strategies in multi-year and multi-location static field trials for increasing nitrogen use efficiency of cereals 327; Th. Ebertseder, U. Schmidhalter, R. Gutser, U. Hege and S. Jungert. Predicting variation in plant N-uptake in three fields using soil organic matter, texture and Near Infrared Reflectance (NIR) spectroscopy 337; J. Wetterlind, B. Stenberg and A. Jonsson; Providing operational nitrogen recommendations to farmers using satellite imagery 345; Anne Blondlot, Philippe Gate and Herve Poilve; Change in spatial variability structure of NDVI readings related to observation scale 353; E.M. Pena-Yewtukhiw, G.J. Schwab, O. Wendroth, L.W. Murdock and T. Stombaugh; Cotton lint quality spatial variability and correlation with soil properties and yield 361; T. A. Gemtos, Ath. Markinos and Th. Nassiou; * Yield and quality; Monitoring wheat protein content on-harvester - Australian experiences 369; James Taylor, Brett Whelan, Lars Thylen, Mikael Gilbertsson and James Hassall; Prediction of within-field yield and protein variability in malting barley using canopy reflectance, thermal stress, and soil electrical conductivity 377; CG. Pettersson, M. Soderstrom and B. Frankow-Lindberg; Evaluation of an on-combine wheat protein analyzer on Montana hard red spring wheat 385; D. Long and T. Rosenthal; Uniform potato quality with site-specific potassium application 393; L. Wijkmark, R. Lindholm and K. Nissen; Evaluation of forage yield map techniques on a mowing-conditioning machine 401; F. Kumhala, M. Kroulik, J. Masek, P. Prochazka and Z. Kviz; Yield determination in a mower conditioner by means of hydraulic pressure measurements 409; K. Wild and S. Ruhland; Spatial variability in soils 415; * Soil variability; Physical background of soil EC mapping: laboratory, theoretical and field studies 417; E. Luck, J. Ruhlmann and U. Spangenberg; Using secondary information sources to improve the within-field soil textural mapping in a layered alluvial soil 425; W.A.U. Vitharana, M. Van Meirvenne and L. Cockx; Spatial and temporal variability of soil properties with respect to relief information 433; H.I. Reuter, K.C. Kersebaum and O. Wendroth. * Soil sensors; Prediction and spatial variability of soil dynamic properties in sugar cane fields of Sao Paulo State - Brazil 441; R.B. Silva, K.P. Lancas and E.E.V. Miranda; An integrated system for mapping soil physical properties on-the-go: the mechanical sensing component 449; V.I. Adamchuk and P.T. Christenson; Development of soil pH and lime requirement maps using on-the-go soil sensors 457; E.D. Lund, V.I. Adamchuk, K.L. Collings, P.E. Drummond and C.D. Christy; Evaluation of the penetration resistance along a transect 465; H. Domsch, J. Boess, D. Ehlert and H.-J. Wuttig; Comparison of geoelectrical methods for soil mapping 473; R. Gebbers and E. Luck; Mobile TDR for geo-referenced measurement of soil water content and electrical conductivity 481; Anton Thomsen, Per Drosher and Flemming Steffensen; Bulk density maps as affected by implementation of a depth control system during on-line measurement of soil compaction 487; Abdul Mounem Mouazen and Herman Ramon; A real-time multi-spectral soil sensor: predictability of soil moisture and organic matter content in a small field 495; S. Shibusawa, K. Ehara, T. Okayama, H. Umeda and S. Hirako; Obtaining 'useful' high-resolution soil data from proximally-sensed electrical conductivity/resistivity (PSEC/R) surveys 503; Alex. B. McBratney, Budiman Minasny and Brett M. Whelan; Field measurements of soil pH and lime requirement using an on-the-go soil pH and lime requirement measurement system 511; R.A. Viscarra Rossel, M. Gilbertson, L. Thylen, O. Hansen, S. McVey and A.B. McBratney; On-the-go sensor for measurement of dry bulk density referring to soil compaction 521; Abdul Mounem Mouazen, Josse De Baerdemaeker and Herman Ramon; Site-specific soil properties prediction using hyperspectral signatures of topsoil coverage and underground image by real-time soil spectrophotometer 529; S.K. Roy, S. Shibusawa and T. Okayama; Topsoil mapping using hyperspectral airborne data and multivariate regression modeling 537; Thomas Selige, Urs Schmidhalter. Technology for precision agriculture 547; * Image analysis; Ground truth evaluation of 3D computer vision on non-rigid biological structures 549; M. Nielsen, H.J. Andersen, D.C. Slaughter and E. Granum; Measuring distribution accuracy of fertiliser using image analysis 557; A. Rydberg and G. Lundin; * Communication; ISOBUS compatible implements in the project AGRIX 565; T. Oksanen, P. Suomi, A. Visala and H. Haapala; Wireless sensor networks for precise Phytophthora decision support 573; D. Goense, J. Thelen and K. Langendoen; * Guidance, autosteer and robotics; Economics of Lightbar and Auto-Guidance GPS Navigation Technologies 581; T. Griffin, D. Lambert and J. Lowenberg-DeBoer; Agricultural robots: an economic feasibility study 589; S.M. Pedersen, S. Fountas, H. Have and B.S. Blackmore; A two-stage route planning system for autonomous agricultural vehicles 597; S. Vougioukas, S. Blackmore, J. Nielsen and S. Fountas; A test facility for evaluating dynamic GPS accuracy 605; Timothy Stombaugh, John Cole, Scott Shearer, Benjamin Koostra; Investigation of the accuracy of a machine vision based robotic micro-spray system 613; H.T. Sogaard and I. Lund; Robotic agriculture - the future of agricultural mechanisation? 621; Simon Blackmore, Bill Stout, Maohua Wang and Boris Runov; Development and test of an autonomous Christmas tree weeder 629; Henrik Have, Jon Nielsen, Simon Blackmore and Frans Theilby; Sensor-actuator integration in a commercial tractor for safe teleoperation and autonomous navigation 637; M.C. Garcia-Alegre, L. Garcia-Perez, A. Ribeiro, D. Guinea; Tractor-implement dynamic trajectory model for automated navigation applications 645; L. Feng, Y. He and Q. Zhang. * Variable rate application; Variable rate application Testing the viability of existing ground spread fertiliser spreaders to perform variable rate fertilisation 655; H. Lawrence, I. Yule, J. Jones and M. Hedley; Variable rate granular fertilization of citrus groves: spreader performance with single-tree prescription zones 665; A. Schumann, W. Miller, Q. Zaman, K. Hostler, S. Buchanon, G. Perkins and S. Cugati; Design of a seeder to achieve highly uniform sowing patterns 675; H.W. Griepentrog, P.T. Skou, J.F. Soriano and B.S. Blackmore; Variable dose rate application of herbicides using optical sensors 683; U.R. Antuniassi, M.S. Nery and C.A.S. Queiroz; Dynamic modeling of variable-rate granular applicator hydraulic flow control valve 691; S.A. Cugati, W.M. Miller and J.K. Schueller; Spatial analysis and mapping 699; Effect of interpolation methods and filtering on the quality of yieldmaps 701; P.O. Noack, T. Muhr and M. Demmel; Maximum likelihood variograms for efficient prediction in precision agriculture 707; R. Kerry and M.A. Oliver; Improving prediction of soil properties in precision agriculture by co-kriging with properties that are easily measured 715; R. Kerry and M.A. Oliver; Multivariate geostatistics for assessing and predicting soil compaction 723; M. Carrara, A. Castrignano, A. Comparetti, P. Febo and S. Orlando; Spatial relation between NDVI and grain yield: impact of spatial resolution and measurement device 731; O. Wendroth, A. Giebel, E. Pena-Yewtukhiw, K.C. Kersebaum, G.J. Schwab, H.I. Reuter, L.W. Murdock and T.S. Stombaugh; Yield mapping based on robust fitting paraboloid cones in butterfly and elliptic neighborhoods 741; M. Bachmaier and H. Auernhammer; Spatial variability of the Illinois soil nitrogen test: implications for soil sampling 751; Matias L. Ruffo, German A. Bollero and Donald G. Bullock. Management 759; * Soil- and crop modelling; How spatial and temporal variability can affect fertilization trial results 761; A. Castrignano, G. Buttafuoco, M. Pisante and A.V. Vonella; A potential role of permanent soil variables and field topography to reveal scale dependence and the temporal persistence of soil water content spatial patterns 769; H. Bourennane, B. Nicoullaud, A. Couturier, B. Mary, G. Richard and D. King; Predicting dynamics of Chenopodium album in a four year crop rotation using site-specific weed control 779; D. Dicke, R. Gerhards and W. Kuhbauch; Time series analysis of high spatial resolution SPOT images for wheat growth monitoring 787; Jean-Philippe Denux, Anne Jacquin, Michel Gay, Ignacio Tourino and Veronique Cheret; Long term simulation of soil/crop interactions to estimate management zones and consequences for site specific nitrogen management considering water protection 795; K.C. Kersebaum, H.I. Reuter, K. Lorenz and O. Wendroth; Using sensor information on drought stress for a site specific calibration of a wheat simulation model 803; U. Bottcher and H. Kage; * Site-specific management and decision support systems; Combining soil-landscape and spatial-temporal variability of yield information to delineate site-specific management zones 811; Y. Miao, D.J. Mulla and P.C. Robert; Topographical data for delineation of agricultural management zones 819; Petter Pilesjo, Lars Thylen and Andreas Persson; Optimum N management using site-specific management zones 827; R. Khosla, D. Inman and D.G. Westfall; Early season grain yield prediction using remote sensing and site-specific management zones 835; D. Inman, R. Khosla, M. Lefsky and D.G. Westfall; A method to combine yield and quality maps to aid decision-making 843; T. Chosa, M. Omine and H. Hosokawa; Multiple variable rate input application: a decision framework 849; B.C. English, R.K. Roberts and J. Larson; Extending Site-Specific Crop Management from individual fields to an entire farm 857; M.J. Florin, A.B. McBratney and B.M. Whelan. Local response to nitrogen inputs: advancing SSCM within Australia 865; B.M. Whelan and J.A. Taylor; FARMSTAR: an efficient decision support tool for near real time crop management from satellite images 873; B. Coquil and Jean Paul Bordes; Precision viticulture 881; Whole-of-vineyard experimentation: an improved basis for knowledge generation and decision making 883; R.G.V. Bramley, D.M. Lanyon and K. Panten; Generating benefits from Precision Viticulture through selective harvesting 891; R.G.V. Bramley, A.P.B. Proffitt, C.J. Hinze, B. Pearse and R.P. Hamilton; Obtaining grape yield maps and analysis of within-field variability in Raimat (Spain) 899; J. Arno, X. Bordes, M. Ribes-Dasi, R. Blanco, J.R. Rosell and J. Esteve; A comparison of the spatial variability of vineyard yield in European and Australian production systems 907; James Taylor, Bruno Tisseyre, Rob Bramley and Angela Reid; Combination of heterogeneous data sets in Precision Viticulture 915; J-N. Paoli, B. Tisseyre, O. Strauss, J-M. Roger and S. Guillaume; Vine parcel detection in aerial images combining textural and structural approaches 923; G. Rabatel, C. Debain and M. Deshayes; Delineation of vine fields by segmentation of high resolution remote sensed images 933; F. Michelet, J.P. Da Costa, C. Germain, O. Lavialle and G. Grenier; Precision irrigation 941; The potential contribution of precision irrigation to water conservation 943; S.A. Al-Kufaishi, B.S. Blackmore and H. Sourell; Farm-scale testing of site-specific irrigation and nitrogen fertilization for cotton production in the Southern High Plains of Texas, USA 951; J.D. Booker, K.F. Bronson, J.W. Keeling, J.P. Bordovsky, E. Segarra and Margarita Velandia-Parra; Optimal water storage location and management zone delineation under variable subsurface drip irrigation 959; Carl R. Dillon, Sayed Saghaian, Juma Salim and Murali Kanakasabai. Economic and environmental effects of precision agriculture 967; Precision agriculture improves efficiency of nitrogen use and minimises its leaching at within-field to farm scales 969; M.T.F. Wong, S. Asseng and H. Zhang; A key indicator for the assessment of spatially variable phosphorus fertilisation 977; Mats Soderstrom, Anna Nyberg, Christoffer Anderson and Borje Linden; Evaluating the benefits from precision agriculture: the economics of meeting traceability requirements and environmental targets 985; Tihomir Ancev, Brett Whelan and Alex McBratney; Keyword index 995; Keyword index 1001.