Wheat genotypic variability in grain yield and carbon isotope discrimination under Mediterranean conditions assessed by spectral reflectance

被引:58
作者
Lobos, Gustavo A. [1 ]
Matus, Ivan [2 ]
Rodriguez, Alejandra [2 ]
Romero-Bravo, Sebastian [1 ]
Luis Araus, Jose [3 ]
del Pozo, Alejandro [1 ]
机构
[1] Univ Talca, Fac Agr Sci, Plant Breeding & Phen Ctr, Talca, Chile
[2] Agr Res Inst, CRI Quilamapu, Chillan, Chile
[3] Univ Barcelona, Fac Biol, Plant Physiol Dept, Barcelona, Spain
关键词
Breeding; drought; dry matter index; normalized difference moisture index; vegetative index; water index; WATER-USE EFFICIENCY; VEGETATION INDEXES; DURUM-WHEAT; INDIRECT SELECTION; WINTER-WHEAT; C-3; CEREALS; CROP YIELD; PLANT; DROUGHT; CHILE;
D O I
10.1111/jipb.12114
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
A collection of 368 advanced lines and cultivars of spring wheat (Triticum aestivum L.) from Chile, Uruguay, and CIMMYT (Centro Internacional de Mejoramiento de Maiz 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 (C-13) 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 C-13 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 C-13, only individual regressions could be forecast under FI (r(2): 0.25-0.37) and MWS (r(2): 0.45-0.59) but not under SWS (r(2): 0.03-0.09). NIR-based SRI proved to be better predictors than those that combine visible and NIR wavelengths.
引用
收藏
页码:470 / 479
页数:10
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