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| Filter results12 paper(s) found. |
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1. Spatial-temporal Management Zones For Biomass MoistureBiomass handling operations (harvesting, raking, collection, and transportation) are critical operations within the agricultural production system since they constitute the first link in the biomass supply chain, a fact of substantial importance considering the increasingly involvement of biomass in bio-refinery and bio-energy procedures. Nevertheless, the inherent uncertainty, imposed by the interaction between environmental, biological, and machinery factors, makes the available scheduling... S. Fountas, D. Bochtis, C. Sorensen, O. Green, R. J, T. Bartzanas |
2. 3D Map in the Depth Direction of Field for Precision AgricultureBy a change in eating habits with economic development and the global population growth, we have been faced with the need for increased food production again. In order to solve the food problem in the future, the introduction of agriculture organization is progressing in emerging countries as well as developed countries. However, the occurrence of natural disasters and abnormal weather, which is becoming a worldwide problem at present, is further weakening the crops of farm... H. Umeda, S. Shibusawa, Q. Li, K. Usui, M. Kodaira |
3. Using A Potable Spectroradiometer For In-Situ Measurement Of Soil Properties In A Slope Citrus FieldIn precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for crop and soil management. However, the spatial variability of soil properties is consider to be high cost and time consuming to characterize using traditional soil analysis method. To achieve cost and time reduction, the potential benefits of in-situ measurement of soil spectra have been recognized. ... S. Shibusawa, H. Umeda, K. Usui, M. Kodaira, Q. Li |
4. Site-Specific Variability Of Grape Composition And Wine QualityPrecision Viticulture (PV) is the application of site-specific tools to delineate management zones in vineyards for either targeting inputs or harvesting blocks according to grape maturity status. For the creation of management zones, soil properties, topography, canopy characteristics and grape yield are commonly measured during the growing season. The majority of PV studies in winegrapes have focused on the relation of soil and vine-related spatial data with grape composition... S. Fountas, Y. Kotseridis, A. Balafoutis, E. Anastasiou, S. Koundouras, S. Kallithraka, M. Kyraleou |
5. Proximal Hyperspectral Sensing in Plant BreedingThe use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detection... H. Lilienthal, P. Wilde, E. Schnug |
6. EZZone - An Online Tool for Delineating Management ZonesManagement zones are a pillar of Precision Agriculture research. Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions. The use of Geographic Information Systems for agricultural management is common, especially with management zones. Although many algorithms have been produced in research settings, no online software for management zone delineation exists. This research used a common... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos |
7. Calculating the Water Deficit of Apple Orchard by Means of Spatially Resolved ApproachIn semi-humid climate, spatially resolved analysis of water deficit was carried out in apple orchard (Malus x domestica 'Pinova'). The meteorological data were recorded daily by a weather station. The apparent soil electrical conductivity (ECa) was measured at field capacity, and twenty soil samples in 30 cm were gathered for texture, bulk density, and gravimetric soil water content analyses. Furthermore, ten trees were defoliated in different ECa regions in order to estimate the leaf... N. Tsoulias, D. Paraforos, N. Brandes, S. Fountas, M. Zude-sasse |
8. AI Tools in Agri DSS Pipeline - the Case of Irrigated SugarbeetA general pipeline that can be associated to a DSS includes several steps. Data Collectionn includes Acquisition, extraction, and aggregation of data from previously identified and selected sources. Data Cleaning and preparation make data available for exploratory analysis that make them usable. Data Analysis is then applied to extract meaningful information e.g. by statistical and/or simulation models. Data are successively synthesized and visualized to make them clear to the decision-maker to... G.-. Vitali, C. Ferraz |
9. Optimizing Vineyard Crop Protection: an In-depth Study of Spraying Drone Operational ParametersIn modern agriculture, the precise and efficient application of agrochemicals is essential to ensure crop health and increase productivity while minimizing adverse environmental impacts. While traditional spraying methods have long been the cornerstone of crop protection, the introduction of unmanned aerial vehicles (UAVs), commonly known as drones), has led to a revolutionary era in agriculture. UAVs offer novel opportunities to improve agricultural practices by providing precision, efficiency,... V. Psiroukis, S. Fountas, H. Uyar, A. Balafoutis, A. Kasimati |
10. Large-Scale Sugarcane Yield Prediction Across Regions by Integrating Multi-Source Remote Sensing and Machine LearningSugarcane (Saccharum officinarum L.) is one of the most important agro-industrial crops worldwide, playing a key role in sugar, bioethanol, and renewable energy production. Early and accurate yield estimation during the growing season is essential to support agricultural planning, resource management, and decision-making in the sugar-energy industry under increasing climate variability. However, most yield models are calibrated to single locations and struggle to transfer across regions. The primary... R. Fortes Gallego, F. Serra Burriel, M. Cabrera Dengra, C. Ferraz, A. Do Vale Dondo |
11. Development of a Predictive Machine Learning Model for Pasture Biomass Using Satellite Vegetation Indices and Climate Data in Spanish Dehesa SystemsExtensive livestock systems are fundamental to the ecological, economic, and cultural sustainability of Mediterranean agroecosystems such as the Spanish dehesa. These silvopastoral landscapes support biodiversity, prevent land abandonment, and sustain rural livelihoods, but their productivity is highly dependent on pasture availability. Efficient management therefore requires accurate and timely information on pasture biomass, which is strongly influenced by climatic variability, soil properties,... C. Ferraz, A. Tamayo López, A. Do Vale Dondo |
12. Operational Satellite Weed Detection Across 14,000 Sugarcane Fields: Lessons in Temporal Feature DesignWeed infestations in sugarcane (Saccharum officinarum L.) can reduce yields by 20–60% depending on species composition and management timing, yet operational weed management at scale remains an unsolved challenge. Existing studies typically cover tens of fields; scaling to thousands introduces challenges in processing throughput, ground truth scarcity, and feature design. This work describes the development and operational deployment of a satellite-based weed detection system covering... C. Ferraz, R. Fortes, M. Cabrera Dengra, J. Poli, E. Bernardes Júnior, A. Do Vale Dondo |