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Bonnardel, B
Pethybridge, S.J
Yu, Z
Roel
Kemerer, A.C
Jasper, J
Hunsche, M
Irvine, L
Dhal, S
Balafoutis, A
Burkhart, S
Feng, L
Hachisuca, A
Pires, P.S
Link, A
Deleon, E
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Authors
R, C
Rumpf, T
B, K
Hunsche, M
Pl, L
Noga, G
Reusch, S
Jasper, J
Link, A
Vollmar, J
Pravia, V
Terra, J.A
Roel
McNeill, D
Bishop-Hurley, G.J
Irvine, L
Freeman, M
Bellenguez, R
Chen, N
Liu, F
Jiang, L
Feng, L
He, Y
Bao, Y
Leufen, G
Noga, G
Hunsche, M
Leufen, G
Noga, G
Hunsche, M
Kemerer, A.C
Albarenque, S.M
Melchiori, R.J
Fountas, S
Kotseridis, Y
Balafoutis, A
Anastasiou, E
Koundouras, S
Kallithraka, S
Kyraleou, M
Gnyp, M.L
Panitzki, M
Reusch, S
Jasper, J
Bolten, A
Bareth, G
Hughes, E.W
Pethybridge, S.J
Salvaggio, C
van Aardt, J
Kikkert, J.R
Pomar, C
Andretta, I
Hauschild, L
Kipper, M
Pires, P.S
Souza, E.G
Bazzi, C
Hachisuca, A
Sobjak, R
Gavioli, A
Betzek, N
Schenatto, K
Mercante, E
Rodrigues, M
Moreira, W
Aikes Junior, J
Souza, E.G
Bazzi, C
Sobjak, R
Hachisuca, A
Gavioli, A
Betzek, N
Schenatto, K
Moreira, W
Mercante, E
Rodrigues, M
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Dhal, S
Louis, J
O'Sullivan, N
Gumero, J
Soetan, M
Kalafatis, S
Lusher, J
Mahanta, S
Bonnardel, B
Bonnardel, B
Bazzi, C.L
Oliveira, W.K
Sobjak, R
Schenatto, K
Souza, E
Hachisuca, A
Franz, F
Weule, M
Hufnagel, E
Claussen, J
Berghaus, A
Burkhart, S
Noack, P
Gerth, S
Psiroukis, V
Fountas, S
Uyar, H
Balafoutis, A
Kasimati, A
Brown, A.J
Deleon, E
Wardle, E
Topics
Modeling and Geo-statistics
Precision A-Z for Practitioners
Spatial Variability in Crop, Soil and Natural Resources
Precision Livestock Management
Precision Crop Protection
Fluorescence Sensing for Precision Crop Management
Proximal Sensing in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Applications of Unmanned Aerial Systems
Precision Dairy and Livestock Management
Decision Support Systems
Small Holders and Precision Agriculture
Precision Agriculture and Global Food Security
Wireless Sensor Networks and Farm Connectivity
Precision Agriculture and Global Food Security
Drone Spraying
Type
Oral
Poster
Year
2010
2014
2016
2018
2022
2024
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Filter results22 paper(s) found.

1. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral Signatures

Early recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370-800... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga

2. Estimating Crop Biomass And Nitrogen Uptake Using Cropspectm, A Newly Developed Active Crop-canopy Reflectance Sensor

  In-season variable rate nitrogen fertilizer application needs efficient determination of the nitrogen nutrition status of crops with high spatial and temporal resolution. A suitable approach to get this information fast and at low cost is proximal sensing of the light that is reflected from the crop canopy. CropSpecTM is an active vehicle mounted crop canopy sensor. Using pulsed laser diodes as light source, the sensor is designed to look at the crop at an oblique... S. Reusch, J. Jasper, A. Link, J. Vollmar

3. Does Pasture Longevity Under Direct Grazing Affect Field-scale Sorghum Yield Spatial Variability In Crop-pasture Rotation Systems?

Crop yield spatial variability is usually related to terrain attributes and soil properties. In pasture systems, soil properties are affected by animal grazing. However, soil and terrain attributes relation with crop yield variability has not been assessed in crop-pasture rotations.... V. Pravia, J.A. Terra, Roel

4. A Preliminary Evaluation Of Proximity Loggers To Detect Oestrus Behaviour In Grazing Dairy Cows

... D. Mcneill, G.J. Bishop-hurley, L. Irvine, M. Freeman, R. Bellenguez

5. Diagnosis Of Sclerotinia Infected Oilseed Rape (Brassica Napus L) Using Hyperspectral Imaging And Chemomtrics

 Abstract: Brassica napus L leaf diseases could cause seriously reduction in crop yield and quality. Early diagnosis of Brassica napus L leaf diseases plays a vital role in Brassica napus L growth. To explore an effective methodology for diagnosis of Sclerotinia infected Brassica napus L plants, healthy Brassica napus L leaves and Brassica napus L leaves infected by Sclerotinia were prepared in a controlled circumstance. A visible/short-wave near infrared hyperspectral... N. Chen, F. Liu, L. Jiang, L. Feng, Y. He, Y. Bao

6. Suitability Of Fluorescence Sensors To Estimate The Susceptibility Degree Of Spring Barley To Powdery Mildew And Leaf Rust

The overall role of precision agriculture is not restricted to those systems for in-field and in-season sensing of the impact of stresses. Much more, its contribution comprises the prevention of stresses, amongst others by supporting the selection of appropriate and stress-tolerant genotypes in breeding programs. In this context, the development, selection and use of cultivars which are tolerant to pathogens establish an essential tool for a more sustainable and environmental-friendly... G. Leufen, G. Noga, M. Hunsche

7. Selection Of Fluorescence Indices For The Proximal Sensing Of Single And Multiple Stresses In Sugar Beet

The use of fluorescence indices for sensing the impact of abiotic and biotic stresses in agricultural crops is well documented in the literature. Pigment fluorescence gives a precise picture about the plant physiology and its changes following the occurrence of stresses. In general, alterations in such optical signals is caused either by the stress-induced accumulation of one or more fluorophores, or the degradation of specific molecules like chlorophyll. Unfortunately, many stresses... G. Leufen, G. Noga, M. Hunsche

8. Unmanned Aerial System To Determine Nitrogen Status In Maize

Maize field production shows spatial variability during vegetative crop growth that could be used to prescribe nitrogen variable rates. The use of portable sensors mounted on high-clearance applicators is well documented, however new UAS vehicle equipped with high resolution digital cameras could be used to determine crop spatial variability with the advantage of survey extensive field areas. To our knowledge, comparisons between vegetation indices obtained by a modified digital camera and... A.C. Kemerer, S.M. Albarenque, R.J. Melchiori

9. Site-Specific Variability Of Grape Composition And Wine Quality

Precision 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

10. Comparison Between Tractor-based and UAV-based Spectrometer Measurements in Winter Wheat

In-season variable rate nitrogen fertilizer application needs a fast and efficient determination of nitrogen status in crops. Common sensor-based monitoring of nitrogen status mainly relies on tractor mounted active or passive sensors. Over the last few years, researchers tested different sensors and indicated the potential of in-season monitoring of nitrogen status by unmanned aerial vehicles (UAVs) in various crops. However, the UAV-platforms and the available sensors are not yet accepted to... M. Gnyp, M. Panitzki, S. Reusch, J. Jasper, A. Bolten, G. Bareth

11. Snap Bean Flowering Detection from UAS Imaging Spectroscopy

Sclerotinia sclerotiorum (white mold) is a fungus that infects the flowers of snap beans and causes a reduction in the number of pods, and subsequent yields, due to premature pod abscission. Snap bean fields typically are treated with prophylactic fungicide applications to control white mold, once 10% of the plants have at least one flower. The holistic goal of this research is to develop spatially-explicit white mold risk models, based on inputs from remote sensing systems aboard unmanned... E.W. Hughes, S.J. Pethybridge, C. Salvaggio, J. Van aardt, J.R. Kikkert

12. Environmental Impacts of Precision Feeding Programs Applied in Brazilian Pig Production

This study was undertaken to evaluate the effect that switching from conventional to precision feeding systems during the growing-finishing phase would have on the potential environmental impact of Brazilian pig production. Standard life-cycle assessment procedures were used, with a cradle-to-farm gate boundary. The inputs and outputs of each interface of the life cycle were organized in a model. Grain production was independently characterized in the Central-West and South regions of Brazil,... C. Pomar, I. Andretta, L. Hauschild, M. Kipper, P.S. Pires

13. AgDataBox: Web Platform of Data Integration, Software, and Methodologies for Digital Agriculture

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. Digital agriculture enables the flow of information... E.G. Souza, C. Bazzi, A. Hachisuca, R. Sobjak, A. Gavioli, N. Betzek, K. Schenatto, E. Mercante, M. Rodrigues, W. Moreira

14. Web Application for Automatic Creation of Thematic Maps and Management Zones - AgDataBox-Fast Track

Agriculture is challenging to produce more profitably, with the world population expected to reach some 10 billion people by 2050. Such a challenge can be achieved by adopting precision agriculture and digital agriculture (Agriculture 4.0). Digital agriculture (DA) has become a reality with the availability of cheaper and more powerful sensors, actuators and microprocessors, high-bandwidth cellular communication, cloud communication, and Big Data. DA enables information to flow from used agricultural... J. Aikes junior, E.G. Souza, C. Bazzi, R. Sobjak, A. Hachisuca, A. Gavioli, N. Betzek, K. Schenatto, W. Moreira, E. Mercante, M. Rodrigues

15. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

16. An IoT-based Smart Real Time Sensing and Control of Heavy Metals to Ensure Optimal Growth of Plants in an Aquaponic Set-up

The concentration of heavy metals that needs to be maintained in aquaponic environments for habitable growth of plants has been a cause of concern for many decades now as it is not possible to eliminate them completely in a commercial set-up. Our goal is to design a cost-effective real-time smart sensing and actuation system in order to control the concentration of heavy metals in aquaponic solutions. Our solution consists of sensing the nutrient concentrations in the aquaponic solution, namely... S. Dhal, J. Louis, N. O'sullivan, J. Gumero, M. Soetan, S. Kalafatis, J. Lusher, S. Mahanta

17. Farmer Charlie - Low Cost Data Analytics for Farmers Accessible in the Field

Farmer Charlie, a spin-off of AB5 Consulting Ltd, is based on an affordable business model including five elements: a data analytics platform, an agribusiness ecosystem app, capable of connecting with local third-party apps; weather and in field sensors; wi-fi Internet connectivity; and power to the field and farms via solar panels, where necessary. Farmer Charlie brings information to farmers in their own fields, in an easy plug and play solution, affordable to the farmers and addressing their... B. Bonnardel

18. Farmer Charlie - Low Cost Smart Local Data Available to Remote Farmers

Farmer Charlie brings connectivity and information to farmers, who receive tailored agronomic data to improve their agricultural practice. Farmer Charlie is based on on-site sensors through which soil data can be detected, gathered, and processed by a dedicated server. Broadband communication allows farmers to receive real-time, localised information on tablet or mobile phone. Farmer Charlie is a low-cost solution, it can be adapted to various crops and to detect soil humidity, pH, temperature,... B. Bonnardel

19. AgDataBox-IoT - Managing IoT Data and Devices on Precision Agriculture

The increasing global population has resulted in a substantial demand for nourishment, which has prompted the agricultural sector to investigate ways to improve efficiency. Precision agriculture (PA) uses advanced technologies such as the Internet of Things (IoT) and sensor networks to collect and analyze field information. Although the advantages are numerous, the available data storage, management, and analysis resources are limited. Therefore, creating and providing a user-friendly web application... C.L. Bazzi, W.K. Oliveira, R. Sobjak, K. Schenatto, E. Souza, A. Hachisuca, F. Franz

20. X-ray Imaging in Breeding and Harvesting Processes

The application of X-ray technology has a long tradition in different medical and technical fields. Compared to other sensor systems, its advantages lie in the capability to reveal structures within objects non-destructively. The analysis of X-ray images with image processing methods is applied for quality control, the detection of foreign objects or damages and other anomalies (e.g. in organs or bones). Until recently, the application of X-ray was mainly constrained to stationary applications... M. Weule, E. Hufnagel, J. Claussen, A. Berghaus, S. Burkhart, P. Noack, S. Gerth

21. Optimizing Vineyard Crop Protection: an In-depth Study of Spraying Drone Operational Parameters

In 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

22. Crop and Water Monitoring Networks with Low-cost, Internet of Things Technology

Making meaningful changes in agroecosystems often requires the ability to monitor many environmental parameters to accurately identify potential areas for improvement in water quality and crop production. Increasingly, research questions are requiring larger and larger monitoring networks to draw applicable insights for both researchers and producers. However, acquiring enough sensors to address a particular research question is often cost-prohibitive, making it harder to draw meaningful conclusions... A.J. Brown, E. Deleon, E. Wardle