Proceedings

Find matching any: Reset
Bochtis, D
Brodbeck, C.J
Ben Abdallah, F
Hunsche, M
Rozenstein, O
Rodekohr, D
Gahler, A
Bückmann, H
Zekri, S
Add filter to result:
Authors
Goffart, J
Ben Abdallah, F
Fountas, S
Bochtis, D
Sorensen, C
Green, O
J, R
Bartzanas, T
R, C
Rumpf, T
B, K
Hunsche, M
Pl, L
Noga, G
Norwood, S.H
Fulton, J.P
Winstead, A.T
Shaw, J.N
Rodekohr, D
Brodbeck, C.J
Macy, T
Jayasuriya, H.P
Zekri, S
Zaier, R
Al-buasidi, H
Teirab, A
Hamza, N
Leufen, G
Noga, G
Hunsche, M
Leufen, G
Noga, G
Hunsche, M
Rozenstein, O
Haymann, N
Kaplan , G
Tanny, J
Rydahl, P
Boejer, O
Torresen, K
Montull, J.M
Taberner, A
Bückmann, H
Verschwele, A
Stahl, K
Hartschuh, J.M
Gahler, A
Rozenstein, O
Cohen, Y
Alchanatis , V
Behrendt, K
Bonfil, D.J
Eshel, G
Harari, A
Harris, W.E
Klapp, I
Laor, Y
Linker, R
Paz-Kagan, T
Peets, S
Rutter, M.S
Salzer, Y
Lowenberg-DeBoer, J
Topics
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Modeling and Geo-statistics
Engineering Technologies and Advances
Fluorescence Sensing for Precision Crop Management
Proximal Sensing in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
In-Season Nitrogen Management
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Type
Poster
Oral
Year
2012
2010
2014
2018
2022
2024
Home » Authors » Results

Authors

Filter results11 paper(s) found.

1. Spatial-temporal Management Zones For Biomass Moisture

 Biomass 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. 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

3. A Case Study For Variable-rate Seeding Of Corn And Cotton In The Tennessee Valley Of Alabama

      Farmers have recently become more interested in implementing variable-rate seeding of corn and cotton in Alabama due to increasing seed costs and the potential to maximize yields site-specifically due to inherent field variability.  Therefore, an on-farm case study was conducted to evaluate the feasibility of variable-rate seeding for a corn and cotton rotation. ... S.H. Norwood, J.P. Fulton, A.T. Winstead, J.N. Shaw, D. Rodekohr, C.J. Brodbeck, T. Macy

4. Potential Indicators Based On Leaf Flavonoids Content for the Evaluation of Potato Crop Nitrogen Status

Nitrogen (N) fertilization strategies aim to limit environmental pollution by improving potato crop N use efficiency. Such strategies may use indicators for the assessment of in season crop N status (CNS). Leaf polyphenolics (flavonoids) content appears as a valuable indicator of CNS. Because of their absorption features in... J. Goffart, F. Ben abdallah

5. Evaluation Of A Sensor-Based Precision Irrigation System For Efficiency And To Monitor And Control Groundwater Over-Pumping In Oman

Oman is a country with a total area of 309,500 km2. However, cultivable land in Oman is estimated to be less than 2%, which amounts to about 6100 km2. More than 50 percent of the arable lands located in the northern coastal belt of Al Batinah region. The country with average annual rainfall around 100 mm, has limited natural fresh water resources and has been facing the serious problem of sea water intrusion into the scarce groundwater reserves due to undisciplined... H.P. Jayasuriya, S. Zekri, R. Zaier, H. Al-buasidi, A. Teirab, N. Hamza

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. Estimating Cotton Water Requirements Using Sentinel-2

Crop coefficient (Kc)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management.  Spectral modeling of Kc is possible due to the high correlations between Kc and the crop phenologic development and spectral reflectance.  In this study, cotton evapotranspiration was measured in the field using several methods, including eddy covariance, surface renewal, and heat pulse.  Kc was estimated as the ratio between reference evapotranspiration... O. Rozenstein, N. Haymann, G. Kaplan , J. Tanny

9. Economic Potential of IPMwise – a Generic Decision Support System for Integrated Weed Management in 4 Countries

Reducing use and dependency on pesticides in Denmark has been driven by political action plans since the 1980ies, and a series of nationally funded accompanying R&D programs were completed in the period 1989-2006. One result of these programs was a decision support system (DSS) for integrated weed management. The 4th generation (2016) of the agro-biological models and IT-tools in this DSS, named IPMwise. The concept of IPMwise is to systematically exploit that: occurrence... P. Rydahl, O. Boejer, K. Torresen, J.M. Montull, A. Taberner, H. Bückmann, A. Verschwele

10. Evaluation of Fall and Spring Nitrogen Rates Effect on Cereal Rye Forage Crude Protein and Tillering Using NDVI and Canopeo to Make Infield Nitrogen Rate Decisions

Fall applied nitrogen has been used to increase plant tiller and protein in wheat but less research has been done of its effects on cereal rye forage and how NDVI and Canopeo readings can be used to make nitrogen application management decisions. This study took place at the Ohio State University North Central Agricultural Research Station in Fremont, Ohio. The experiment is a randomized complete block split-plot design with four nitrogen rates in the fall (0, 30, 60, and 90 lbs/ac) and in the... K. Stahl, J.M. Hartschuh, A. Gahler

11. Data-driven Agriculture and Sustainable Farming: Friends or Foes?

Sustainability in our food and fiber agriculture systems is inherently knowledge intensive.  It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience.  Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer