Proceedings :: International Society of Precision Agriculture

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Sanderson, R

Linker, R

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Authors

Linker, R

Payne, A

Walsh, K

Cohen, O

Taylor, J

Shahar, Y

James, P

Blacker, C

Leese, S

Sanderson, R

Kavanagh, R

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

Engineering Technologies and Advances

Geospatial Data

Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture

Type

Oral

Poster

Year

2014

2018

2024

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Filter results3 paper(s) found.
1. Detection Of Fruit In Canopy Night-Time Images: Two Case Studies With Apple And Mango Reliable estimation of the expected yield remains a major challenge in orchards. In a recent work we reported the development of an algorithm for estimating the number of fruits in images of apple trees acquired in natural daylight conditions. In the present work we tested this approach with night-time images of similar apple trees and further adapted this approach to night-time images of mango trees. Working with the apple images required only... R. Linker, A. Payne, K. Walsh, O. Cohen Download paper
2. Experiences in the Development of Commercial Web-Based Data Engines to Support UK Growers Within an Industry-Academic Partnership The lifecycle of Precision Agriculture data begins the moment that the measurement is taken, after which it may pass through each multiple data processes until finally arriving as an output employed back in the production system. This flow can be hindered by the fact that many farm datasets have different spatial resolutions. This makes the process to aggregate or analyse multiple Precision Agriculture layers arduous and time consuming. Precision Decisions Ltd located in Yorkshire,... J. Taylor, Y. Shahar, P. James, C. Blacker, S. Leese, R. Sanderson, R. Kavanagh Download paper
3. 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 Download paper

Filter results3 paper(s) found.

1. Detection Of Fruit In Canopy Night-Time Images: Two Case Studies With Apple And Mango

Reliable estimation of the expected yield remains a major challenge in orchards. In a recent work we reported the development of an algorithm for estimating the number of fruits in images of apple trees acquired in natural daylight conditions. In the present work we tested this approach with night-time images of similar apple trees and further adapted this approach to night-time images of mango trees. Working with the apple images required only... R. Linker, A. Payne, K. Walsh, O. Cohen

Download paper

2. Experiences in the Development of Commercial Web-Based Data Engines to Support UK Growers Within an Industry-Academic Partnership

The lifecycle of Precision Agriculture data begins the moment that the measurement is taken, after which it may pass through each multiple data processes until finally arriving as an output employed back in the production system. This flow can be hindered by the fact that many farm datasets have different spatial resolutions. This makes the process to aggregate or analyse multiple Precision Agriculture layers arduous and time consuming. Precision Decisions Ltd located in Yorkshire,... J. Taylor, Y. Shahar, P. James, C. Blacker, S. Leese, R. Sanderson, R. Kavanagh

Download paper

3. 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

Download paper