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Behrendt, K
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Authors
Al Amin, A
Lowenberg‑DeBoer, J
Franklin, K
Behrendt, K
Behrendt, K
Takahashi, T
Rutter, M.S
Al Amin, A
Lowenberg-DeBoer, J
Franklin, K.F
Dickin, E
Monaghan, J
Behrendt, K
Maritan, E
Behrendt, K
Lowenberg-DeBoer, J
Morgan, S
Rutter, M.S
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
Behrendt, K
Capper, J
Ford, L
Harris, E.W
Behrendt, K
Michels, M
Topics
Robotics, Guidance and Automation
ISPA Community: Economics
Profitability and Success Stories in Precision Agriculture
Site-Specific Pasture Management
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Precision Dairy and Livestock Management
Meeting
Type
Oral
Year
2022
2024
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Authors

Filter results7 paper(s) found.

1. Economics of Field Size for Autonomous Crop Machines

Field size constrains spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare... A. Al amin, J. Lowenberg‑deboer, K. Franklin, K. Behrendt

2. Determining the Marginal Value of Extra Precision in Precision Grazing Systems – an Ex Ante Analysis of Impacts on System Productivity, Sustainability and Economics

The development of precision livestock farming (PLF) technologies for application in grazing systems is rapidly evolving. PLF technologies that facilitate the spatial and temporal management of variability in landscapes, pastures and animals promise to improve the efficiency, profitability and sustainability of livestock farming. However, such technologies as a complete package do not yet exist in grazing systems and the question of impacts at the farm system level remains unresolved. Other potential... K. Behrendt, T. Takahashi, M.S. Rutter

3. Profitability of Regenerative Cropping with Autonomous Machines: an Ex-ante Assessment of a British Crop-livestock Farm

Farmers, agroecological innovators and research have suggested mixed cropping as a way to promote soil health. Mixing areas of different crops in the same field is another form of precision agriculture's spatial and temporal management. The simplest form of mixed cropping is strip cropping. In conventional mechanized farming use of mixed cropping practices (i.e., strip cropping, pixel cropping) is limited by labour availability, rising wage rates, and management complexity. Regenerative agriculture... A. Al amin, J. Lowenberg-deboer, K.F. Franklin, E. Dickin, J. Monaghan, K. Behrendt

4. A Multi-objective Optimisation Analysis of Virtual Fencing in Precision Grazing

Virtual fencing is a precision livestock farming tool consisting of invisible boundaries created via Global Navigation Satellite Systems (GNSS) and managed remotely and in real time by app-based technology. Grazing livestock are equipped with battery-powered collars capable of delivering audio or vibration cues and possibly electric shocks when approaching or crossing an invisible boundary. Virtual fencing makes precision grazing possible without the need for physical fences. This technology originated... E. Maritan, K. Behrendt, J. Lowenberg-deboer, S. Morgan, M.S. Rutter

5. 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

6. Have Your Steak and Eat It Too: Precision Beef Management to Simultaneously Reduce Ech4 and Increase Profit

Achieving carbon net zero is a clear priority, with beef farmers under significant scrutiny from food system stakeholders. Tools are available to assess greenhouse gas emissions (GHGe), yet adoption is low, and producers are not currently financially incentivised to change management practices. This study used cattle performance data from a commercial beef operation to model the optimal age and weight at slaughter to maximise profit and reduce enteric methane (eCH4) emissions at the... K. Behrendt, J. Capper, L. Ford, E.W. Harris

7. Precision Agriculture Economics, Profitability, Adoption, and Risk Community Meeting

Agenda Update on Community Activities Update on membership Announcement and introduction of incoming Deputy Leader Discussion points GIATE Symposium session Other activities AOB ... K. Behrendt, M. Michels