Abstract
• Soil Nmin variations affect wheat yield, canopy structure, and nitrogen use efficiency. • UAV multispectral derived red-edge spectral indices are good predictors for NUE. • Machine learning models predicted NUE from UAV multispectral images. • Spectral indices and canopy height model outperformed texture features in predicting NUE. Drone remote sensing offers a powerful tool for monitoring vegetation and agricultural systems. However, its effectiveness in assessing the effect of soil mineral nitrogen ( N min ) on crop canopy traits remains inadequately explored. This study investigates the relationship between soil N min variability and canopy characteristics, grain yield, and nitrogen use efficiency (NUE), and explores the potential to predict NUE using drone multispectral images. Multispectral data were collected across growth stages over two growing seasons. The analysis revealed that soil N min significantly affected canopy structure, with low N min inducing a ’blue shift’ of the red-edge spectral position. The multilayer perceptron regression model predicted NUE with high accuracy (R 2 > 0.7) in early growth stages, identifying red-edge spectral indices and canopy height as key predictors. Texture features did not play a significant role in the models for predicting NUE, which remains to be further understood in future research. These findings highlight the capability of UAV remote sensing data, especially the red-edge spectral features, to capture the effects of soil N min on canopy traits. This study provides a proof-of-concept for mapping NUE using UAV images, with the final goal of improving crop nitrogen management and fertilizer use efficiency in agriculture.
Abstract from the paper’s OpenAlex record; open copy licensed cc-by-nc-nd. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 5
Claim · model-written summary
Soil mineral nitrogen significantly affected wheat canopy structure.
- Taxon
- wheat
Triticum aestivumt0 - Treatment
- soil N mine0
- Outcome
- canopy structuree0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“soil N min significantly affected canopy structure, with low N min inducing a ’blue shift’ of the red-edge spectral position.”
t0“wheat”
Claim · model-written summary
Low soil mineral nitrogen induced a blue shift in red-edge spectral position.
- Taxon
- wheatTriticum aestivumt0
- Treatment
- low N mine0
- Outcome
- red-edge spectral positione0
- Direction
- ’blue shift’e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“soil N min significantly affected canopy structure, with low N min inducing a ’blue shift’ of the red-edge spectral position.”
t0“wheat”
Claim · model-written summary
A multilayer perceptron predicted wheat nitrogen use efficiency in early growth stages with R 2 greater than 0.7.
- Taxon
- wheatTriticum aestivumt0
- Outcome
- NUEe0
- Value
- R 2 > 0.7e0
- Qualifier
- early growth stagese0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The multilayer perceptron regression model predicted NUE with high accuracy (R 2 > 0.7) in early growth stages, identifying red-edge spectral indices and canopy height as key predictors.”
t0“wheat”
Claim · model-written summary
Red-edge spectral indices and canopy height were key predictors of nitrogen use efficiency.
- Taxon
- wheatTriticum aestivumt0
- Outcome
- key predictorse0
- Qualifier
- red-edge spectral indices and canopy heighte0
Not reportedComparatorValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“identifying red-edge spectral indices and canopy height as key predictors”
t0“wheat”
Claim · model-written summary
Texture features did not play a significant role in models predicting nitrogen use efficiency.
- Taxon
- wheatTriticum aestivumt0
- Outcome
- predicting NUEe0
- Comparator
- Texture featurese0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Texture features did not play a significant role in the models for predicting NUE”
t0“wheat”