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Lee, S
Leszczyńska, R
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Authors
Swe, K.M
Kim, Y
Jeong, D
Lee, S
Chung, S
Kabir, M.S
Samborski, S.M
Szatylowicz, J
Gnatowski, T
Leszczyńska, R
Thornton, M
Walsh, O
Samborski, S.M
Torres, U
Leszczyńska, R
Bech, A
Bagavathiannan, M
Topics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
On Farm Experimentation with Site-Specific Technologies
Scouting and Field Data collection with Unmanned Aerial Systems
Type
Oral
Year
2018
2022
2024
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Filter results3 paper(s) found.

1. Sensor Comparison for Yield Monitoring Systems of Small-Sized Potato Harvesters

Yield monitoring of potato in real time during harvesting would be useful for farmers, providing instant yield and income information. In the study, potentials of candidate sensors were evaluated with different yield measurement techniques for yield monitoring system of small-sized potato harvesters. Mass-based (i.e., load cell) and volume-based (i.e., CCD camera) sensors were selected and tested under laboratory conditions. For mass-based sensing, an impact plate instrumented with load cells... K.M. Swe, Y. Kim, D. Jeong, S. Lee, S. Chung, M.S. Kabir

2. Use of Remotely Measured Potato Canopy Characteristics As Indirect Yield Estimators

Prediction of potato yield before harvest is important for making agronomic and marketing decisions. Active optical sensors (AOS) are rarely used together with other hand-held instruments for monitoring potato growth, including yield prediction. The aim of the research was to determine the relationship between manually and remotely measured potato crop characteristics throughout the growing season and yield in commercial potato fields. Objective was also to identify crop characteristics that most... S.M. Samborski, J. Szatylowicz, T. Gnatowski, R. Leszczyńska, M. Thornton, O. Walsh

3. 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