Abstract
The growth stage best suitable for wheat yield phenotyping has been a hot topic. This study provides a fresh insight into it, from the perspective of spectral correlation between wheat genotype replications. A number of 340 wheat genotypes and their replication were distributed in separate parts (west and east) of an experiment field (2019–2020) in Ashland, Kansas, USA. Unmanned aerial vehicle based hyperspectral images (400–100 nm) of the experiment field were taken over the late growing season, on 29 May 2020, 5 June 2020, and 12 June 2020, respectively. For each narrow spectral band, we calculated a coefficient of determination (R 2) between the reflectance of genotype replications. Results suggest that R 2 is relatively stable within visible spectrum (450–700 nm) and within near-infrared (NIR) spectrum (770–1000 nm), though it tends to be higher for the visible bands. Moreover, while the R 2 of the visible bands decreases across the three dates, it increases for the near-infrared bands. These findings suggest that genetic information is better reflected in visible reflectance than in near-infrared reflectance. Among the three dates, the one when highest intra-genotype spectral correlation over visible spectrum was observed might be the best timing to discriminate yield levels of different genotypes.
Original language | English (US) |
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Pages (from-to) | 1203-1212 |
Number of pages | 10 |
Journal | Remote Sensing Letters |
Volume | 13 |
Issue number | 12 |
DOIs | |
State | Published - Nov 17 2022 |
Bibliographical note
KAUST Repository Item: Exported on 2022-12-01Acknowledgements: The work was supported by the NSF [1238187]; National Institute of Food and Agriculture [2017-67007-25933] This project was supported through the USDA NIFA International Wheat Yield Partnership grant no. 2017-67007-25933/project accession no. 1011391 and based upon work supported by the National Science Foundation under Grant No. (1238187).
ASJC Scopus subject areas
- Earth and Planetary Sciences (miscellaneous)
- Electrical and Electronic Engineering