Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location

The study highlights the promising potential of UAV technology in biomass prediction for wheat at a small plot scale. It suggests that the accuracy of biomass predictions can be significantly improved through optimizing analytical and modelling protocols (i.e., variable selection, algorithm selection, stage-specific model development). Future work should focus on exploring the applicability of these findings under a wider variety of conditions and from a more diverse set of genotypes.

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Publication Details

Journal
Plant Methods
Published
2024-08-20
DOI
https://doi.org/10.1186/s13007-024-01236-w
Citations
11
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
5.05

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article

Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location

Daniel Smith, Scott Chapman, Andries B. Potgieter, Sean Reynolds Massey-Reed et al.
11 citations
Plant Methods
Remote Sensing in Agriculture
5.05
article

Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location

Daniel Smith, Scott Chapman, Andries B. Potgieter, Sean Reynolds Massey-Reed, Qiaomin Chen
article en
11 citations

Abstract

The study highlights the promising potential of UAV technology in biomass prediction for wheat at a small plot scale. It suggests that the accuracy of biomass predictions can be significantly improved through optimizing analytical and modelling protocols (i.e., variable selection, algorithm selection, stage-specific model development). Future work should focus on exploring the applicability of these findings under a wider variety of conditions and from a more diverse set of genotypes.

Plant MethodsVol. 20(1)
The University of Queensland (AU), Agriculture and Food (AU)
Grains Research and Development Corporation
Openalex Percentile: Top 5%
Remote Sensing in Agriculture
5.05
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Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location — Daniel Smith, Scott Chapman, et al. · Plant Methods (2024) | TGRS Research Map | TGRS