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Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance
Authors:Gustavo A Lobos  Iván Matus  Alejandra Rodriguez  Sebastián Romero‐Bravo  José Luis Araus  Alejandro del Pozo
Institution:[1]Plant Breeding and Phenomic Center, Faculty of Agricultural Sciences, University of Talca, Talca, Chile; [2]CRI-Quilamapu, Agricultural Research Institute, Chillan, Chile; [3]Plant Physiology Department, Faculty of Biology, University of Barcelona, Barcelona, Spain
Abstract:A collection of 368 advanced lines and cultivars of spring wheat (Triticum aestivum L.) from Chile, Uruguay, and CIMMYT (Centro Internacional de Mejoramiento de Maíz y Trigo), with good agronomic characteristics were evaluated under the Mediterranean conditions of central Chile. Three different water regimes were assayed: severe water stress (SWS, rain fed), mild water stress (MWS; one irrigation around booting), and full irrigation (FI; four irrigations: at tillering, flag leaf appearance, heading, and middle grain filling). Traits evaluated were grain yield (GY), agronomical yield components, days from sowing to heading, carbon isotope discrimination (Δ13C) in kernels, and canopy spectral reflectance. Correlation analyses were performed for 70 spectral reflectance indices (SRI) and the other traits evaluated in the three trials. GY and Δ13C were the traits best correlated with SRI, particularly when these indices were measured during grain filling. However, only GY could be predicted using a single regression, with Normalized Difference Moisture Index (NDMI2: 2,200; 1,100) having the best fit to the data for the three trials. For Δ13C, only individual regressions could be forecast under FI (r2: 0.25–0.37) and MWS (r2: 0.45–0.59) but not under SWS (r2: 0.03–0.09). NIR‐based SRI proved to be better predictors than those that combine visible and NIR wavelengths.
Keywords:Breeding  drought  dry matter index  normalized difference moisture index  vegetative index  water index
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