Proceedings :: International Society of Precision Agriculture

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Bagavathiannan, M

Salzer, Y

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Authors

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

Samborski, S.M

Torres, U

Leszczyńska, R

Bech, A

Bagavathiannan, M

Topics

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

Scouting and Field Data collection with Unmanned Aerial Systems

Type

Oral

Year

2024

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Filter results2 paper(s) found.
1. 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
2. The Relationship Between Vegetation Indices Derived from UAV Imagery and Maturity Class in Potato Breeding Trials In potato breeding, maturity class (MC) is a crucial selection criterion because this is a critical aspect of commercial potato production. Currently, the classification of potato genotypes into MCs is done visually, which is time- and labor-consuming. Unmanned aerial vehicles (UAVs) equipped with sensors can acquire images with high spatial and temporal resolution. The objectives of this study were to 1) establish the relationship between vegetation indices (VIs) derived from UAV imagery at three... S.M. Samborski, U. Torres, R. Leszczyńska, A. Bech, M. Bagavathiannan Download paper

Filter results2 paper(s) found.

1. 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

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2. The Relationship Between Vegetation Indices Derived from UAV Imagery and Maturity Class in Potato Breeding Trials

In potato breeding, maturity class (MC) is a crucial selection criterion because this is a critical aspect of commercial potato production. Currently, the classification of potato genotypes into MCs is done visually, which is time- and labor-consuming. Unmanned aerial vehicles (UAVs) equipped with sensors can acquire images with high spatial and temporal resolution. The objectives of this study were to 1) establish the relationship between vegetation indices (VIs) derived from UAV imagery at three... S.M. Samborski, U. Torres, R. Leszczyńska, A. Bech, M. Bagavathiannan

Download paper