Journal
PLANT SCIENCE
Volume 295, Issue -, Pages -Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.plantsci.2019.110281
Keywords
Wheat; High temperature; Vernalization; Remote sensing; Stable isotopes; Yield prediction
Categories
Funding
- MINECO, Spanish Government [PCIN-2017-063, AGL2016-76527-R]
- International Center for Advanced Mediterranean Agronomic Studies (CIHEAM)
- Mediterranean Agronomic Institute of Zaragoza (IAMZ)
- Lleida University (UdL)
- ICREA Academia, Autonomous Government of Catalonia, Spain
Ask authors/readers for more resources
This study compares distinct phenotypic approaches to assess wheat performance under different growing temperatures and vernalization needs. A set of 38 (winter and facultative) wheat cultivars were planted in Valladolid (Spain) under irrigation and two contrasting planting dates: normal (late autumn), and late (late winter). The late plating trial exhibited a 1.5 degrees C increase in average crop temperature. Measurements with different remote sensing techniques were performed at heading and grain filling, as well as carbon isotope composition (delta C-13) and nitrogen content analysis. Multispectral and RGB vegetation indices and canopy temperature related better to grain yield (GY) across the whole set of genotypes in the normal compared with the late planting, with indices (such as the RGB indices Hue, a* and the spectral indices NDVI, EVI and CCI) measured at grain filling performing the best. Aerially assessed remote sensing indices only performed better than ground-acquired ones at heading. Nitrogen content and delta C-13 correlated with GY at both planting dates. Correlations within winter and facultative genotypes were much weaker, particularly in the facultative subset. For both planting dates, the best GY prediction models were achieved when combining remote sensing indices with delta C-13 and nitrogen of mature grains. Implications for phenotyping in the context of increasing temperatures are further discussed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available