Organizing committee;Alexandre Escola, Joan R. Rosell, JaumeArno.- Scientific committee; JaumAlexandre Escola, Joan R. Rosell,Jaume Arno.- Editorial;John V. Stafford.-Section 1 Soil and crop proximal sensors.- Comparing the DUALEM and VERIS sensors for mapping soil properties;J. Serrano et al.- Three-layered soil maps based on sensor measurements;K. Piikki etal.- Real time soil sensing for determination of tropical soils pH;F.C.S. Silva, J.P. Molin.- Soil compaction sensor for site-specific tillage: design and assessment;J. Aguera et al.- Microphone sensor for grain yield monitoring;K. Shoji et al.- Improving the determination of plant characteristics by fusion of four different sensors;M. Weis et al.- Three-dimensional sensor for dynamic characterization of soil microrelief;F. Marinello et al.- Crop sensor readings in winter wheat as affected by nitrogen and water supply;R. Gebbers et al.- Rapid estimation of rice canopy LAI using multi-source proximal sensors;L.Q. Zhou et al.- Estimating rice nitrogen status with the Crop Circle multispectral active canopy sensor;Q. Cao et al.- Comparison of crop canopy sensors in sugarcane;L.R. Amaral et al.- Field comparison of ultrasonic and canopy reflectance sensors used to estimate biomass and N-uptake in sugarcane;G. Portz et al.- From theory to practice: using canopy reflectance to determine sidedress N rate in potatoes;F.K. van Evert et al.- The use of a laser scanner for measuring crop properties in three different crops in Central Greece;A. Chatzinikos et al.- The problem is not N deficiency: Active canopy sensors and chlorophyll meters detect P stress in corn and soybean;J.H. Grove, M.M. Navarro.- Development of sensor based detection of crop nitrogen status for utilization in variable rate nitrogen fertilization;J.J. Varco etal.- Portability of leaf chlorophyll empirical estimators obtained at Sentinel-2 spectral resolution;M. Vincini, E. Frazzi.-Section 2 Remote sensing.- Enhancement of micro Unmanned Aerial Vehicles for agricultural aerial sensor systems;J. Geipel et al.- Fieldcopter: unmanned aerial systems for crop monitoring services;T. van der Wal et al.- Aerial thermography for crop stress evaluation a look into the state of the technology;M.Meron et al.- Comparison of methods for field scale mapping of plant water status using aerial thermal imagery;O. Rosenberget al.- Imagery from unmanned aerial vehicles for early site specific weed management;J. Torres-Sanchez et al.- Mapping of vine vigor by UAV and anthocyanin content by a non-destructive fluorescence technique;A. Matese et al.- Predicting optimal soybean harvesting dates with satellite data;J.H. Meng et al.- Monitoring time-series crop leaf area index from higher resolution remotely sensed data;S. Jiao, Y. Qu.- Water status detection in California table grapes: from leaf to airborne;M.M.Alsina et al.-Section 3 Spatial variability and mapping.- Long-term effect of super phosphate fertilizer on accumulation of soil phosphorus on a pasture;J. Serrano et al.- Effect of sampling patterns and interpolation methods on prediction quality of soil variability mapping;H.H. Huang et al.- Spatial variability of drip irrigation in small vine fields of south of France;B. Tisseyre, A. Ducanchez.- A simple method for filtering spatial data;M. Spekken et al.- Spatial variability detection of crop height in a single field by terrestrial laser scanning;D.Hoffmeister et al.- Strip-crop rotations: yield spatial structure for spatially coincident and temporally subsequent corn and soybean production;E.M. Pena-Yewtukhiw, J.H. Grove.- Spatial variability of seed depth placement of maize under no tillage in Alentejo, Portugal;L. Conceicao et al.- Stochastic simulation of maize productivity: spatial and temporal uncertainty;A.R.L.Grifo, J. Marques da Silva.- Spatial and temporal variability of soybean and maize yield after 27 years of no-tillage in Sao Paulo, Brazil;S. Vieira et al.- Investigating geostatistical methods to model within-field yield variability of cranberries;R.Kerry et al.- Within-field zoning using a region growing algorithm guided by geostatistical analysis;L. Zane et al.- Understanding the effects of site-specific fertilization on yield and protein content in durum wheat;F. Morari et al.- Within-field variation in deoxynivalenol (DON) contents in oats;M.Soderstrom, T. Borjesson.-Section 4 Machinery, robotics and precision agriculture technologies.- On-line measurement of animal and bio slurry quality variations with near infrared spectroscopy;B. Stenberg, K. Gustafsson.- Automatic selection of vertical spray pattern in orchard sprayer;M. Tamagnone etal.- Management information system for spatial analysis of tractorimplement draft forces;Z. Tsiropoulos et al.- Using RTK-based GPS guidance for planting and inverting peanuts;G.Vellidis et al.- Hydraulic robot arm controlled by visual servoing;G. Raush et al.- Path planning to minimise distances and recharging instances for a small fleet of vehicles in an arable field;J. Conesa-Munoz et al.-Section 5 Management, data analyses and decision support systems.- Can fluorescence based sensing detect nitrogen variability at early growth stages of maize?;L. Longchamps et al.- Sub-paddock scale spatial variability between the pasture and cropping phases of mixed farming systems in Australia;P. McEntee et al.- The effect of long-term phosphorus and potassium precision fertilization;G.Kulczycki, P. Grocholski.- Theoretical basis for sensor-based in-season nitrogen management;V.I. Adamchuk.- A segmentation approach to delineate zones for differential nitrogen interventions;R.P. de Oliveira et al.- Practicable site-specific estimation of nitrate leaching risk from agricultural cropland;A.Kielhorn et al.- Yield variability linked to climate uncertainty and nitrogen fertilization;B. Dumont et al.- Variable rate application of side-dress nitrogen on cotton in Georgia, USA;V. Liakos etal.- Improving yield advisory models for precision agriculture with special regards to soil compaction in maize production;A.Nyeki et al.- A model-driven decision support system for vineyard water status management: a time dependent sensitivity analysis;A. Guaus et al.- Prediction of spatial variability of water status in a rain fed vineyard in Spain;I.Urretavizcaya et al.- A field information collecting system based on a wireless sensor network;X. Deng et al.- Site-specific land management of cereal crops based on management zone delineation by proximal soil sensing;G. Halcro et al.- A comparison of bivariate classification and segmentation approaches to delineating and interpreting grain yield-protein management units;J.A. Taylor et al.- Using profile soil electrical conductivity survey data to predict wheat establishment rates in the United Kingdom;S. Griffin, J. Hollis.- Geostatistical methods as auxiliary tools in field plot experimentation;J. Goaszewski etal.- Prediction of non-linear time-variant dynamic crop model using bayesian methods;M. Mansouri et al.-Section 6 Precision crop protection.- Gall mite inspection on dormant black currant buds using machine vision;M.R. Nielsen et al.- Assembly of a model for grapevine powdery mildew in a decision support system and search for evaluation criteria;G.Garin et al.- Advances in pesticide dose adjustment in tree crops;S. Planas et al.- Weed-crop discrimination using LiDAR measurements;D. Andujar et al.- Simulation of the effects of weed decision threshold, detection and treatment resolution on the errors in spraying decisions and on herbicide savings;C. SanMartin et al.- Crop and weed species recognition based on hyperspectral sensing and active learning;D. Moshou et al.- Effect of historical agronomic practices and proximity of infected plots on spatial patterns of broomrape in tomato crops;I. Roei et al.- Spray nozzle characterization using high speed imaging techniques;S. Vulgarakis Minov et al.- Site-specific disease management: a preliminary case with Orange Spotting in oil palm;S. Selvaraja et al.- Mapping redheaded cockchafer infestations in pastures are PA tools up to the job?;A. Cosbyet al.- Risk assessment of grapevine leafroll disease for developing future site-specific disease spread control tactics and strategies;T. Sokolsky et al.-Section 7 Advances in precision fructiculture/ viticulture/ oliviculture and horticulture in general.- Electronic characterization of the phenological stages of grapevine using a LIDAR sensor;M.Rinaldi et al.- Grape quality assessment by airborne remote sensing over three years;I. Bonilla et al.- Multispectral imagery acquired from a UAV to assess the spatial variability of a Tempranillo vineyard;C. Rey et al.- A simplified index to assess the opportunity for selective wine grape harvesting from vigour maps;A. Monso et al.- Using laser scanner to map pruning wood in vineyards;A. Tagarakis et al.- Agronomic significance of the zones defined within vineyards early in the season using NDVI and fruit load information;L.G. Santesteban et al.- Grape physiology, composition and sensory characteristics in a selective harvest winegrape vineyard;D.R. Smart et al.- Temporal evolution of within-season vineyard canopy response from a proximal sensing system;J.A. Taylor et al.- Automated determination of plum tree canopy cover with two different measurement techniques;J. Selbeck, F. Pforte.- Application of variable rate fertilizer in a commercial apple orchard;V. Liakoset al.- Obtaining yield maps in orchards by tracking machine behavior;A.F. Colaco et al.- Determination of field capacity and yield mapping in olive harvesting using remote data acquisition;J. Aguera-Vega et al.-Section 8 Advances in precision irrigation.- Scheduling vineyard irrigation based on mapping leaf water potential from airborne thermal imagery;J. Bellvert etal.- Assessment of drip irrigation sub-units using airborne thermal imagery acquired with an Unmanned Aerial Vehicle (UAV);M.A. Jimenez-Bello et al.- A soil moisture sensor-based variable rate irrigation scheduling system;G. Vellidis et al.- The potential of CWSI based on thermal imagery for in-season irrigation management in potato fields;R. Rud et al.- Variable rate irrigation and nitrogen fertilization of maize across landscape positions;R. Ferguson et al.- Response of alfalfa to precision fertigation in Saudi Arabia;K.A. Al-Gaadi et al.- Fusion of data from multiple soil sensors for the delineation of water holding capacity zones;A.M. Mouazen et al.-Section 9 Economics, practical adoption and emerging issues.- Precision agriculture and agro-environmental policy;J. Schieffer,C. Dillon.- Heuristic optimization for variable rate nitrogen and seeding decisions;C.R. Dillon.- Dispelling misperceptions regarding variable rate application;C.R. Dillon, Y. Kusunose.- Precision analysis of the effect of ephemeral gully erosion on vine vigour using NDVI images;J.A. Martinez-Casasnovas et al.- A survey of future farm automation a descriptive analysis of survey responses;C. Kester et al.- Service engineering in the domain of precision farming;S. Klingner et al.- A survey of wireless sensor technologies applied to precision agriculture;J.M. Barcelo-Ordinas et al.- Standardisation in precision agriculture through INSPIRE;P. Korduan, R. Bill.- Keyword index.- Author index.
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Precision agriculture ’13 von John V. Stafford - mit der ISBN: 9789086867783
Precision Agriculture; B; Life Sciences; Plant Science; Biomedical and Life Sciences, Online-Buchhandlung
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