Loading…

Remote sensing techniques and stable isotopes as phenotyping tools to assess wheat yield performance: Effects of growing temperature and vernalization

•High temperature negatively affects wheat yield, particularly in winter genotypes.•Vegetation indices (VI) phenotype better genotypes in normal than in late planting.•Grain δ13C and N content work well as phenotypic traits regardless of planting date.•Combination of VI and isotopes improved yield p...

Full description

Saved in:
Bibliographic Details
Published in:Plant science (Limerick) 2020-06, Vol.295, p.110281-110281, Article 110281
Main Authors: Rezzouk, Fatima Zahra, Gracia-Romero, Adrian, Kefauver, Shawn C., Gutiérrez, Nieves Aparicio, Aranjuelo, Iker, Serret, Maria Dolors, Araus, José Luis
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•High temperature negatively affects wheat yield, particularly in winter genotypes.•Vegetation indices (VI) phenotype better genotypes in normal than in late planting.•Grain δ13C and N content work well as phenotypic traits regardless of planting date.•Combination of VI and isotopes improved yield prediction for both planting dates. 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 °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 (δ13C) 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 δ13C 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 δ13C and nitrogen of mature grains. Implications for phenotyping in the context of increasing temperatures are further discussed.
ISSN:0168-9452
1873-2259
DOI:10.1016/j.plantsci.2019.110281