Genetic Analysis of Indirect Selection for Winter Wheat Grain Yield Using Spectral Reflectance Indices

Increased biomass production could be an important criterion for future grain yield improvement in wheat (Triticum aestivum L.). Quick assessment of genetic variations for biomass production may become a useful tool for wheat breeders. The potential of using canopy spectral reflectance indices (SRI) to assess genetic variation for biomass production in winter wheat was evaluated. Three experiments were conducted for 2 yr (2003-2004 and 2004-2005) at Oklahoma State University, Stillwater, OK. The first experiment consisted of 25 winter wheat cultivars, and the other two experiments contained two sets of 25 F4:6 and F4:7 recombinant inbred lines from two crosses developed by breeding programs in the great plains of the United States of America. Three groups of SRI (vegetation-based, pigment-based, and water-based) were tested for their ability to assess biomass production at three growth stages (booting, heading, and grainfilling). The water index and the normalized water indices gave stronger genetic correlations (P < 0.01) and linear relationship for biomass production compared with the vegetation-based and pigment-based indices. The strong association of water-based indices with biomass was related to the canopy water content of the genotypes. Canopy water content was significantly (P < 0.05) correlated with biomass production. A strong positive association (P < 0.05) of grain yield and dry biomass was observed at the heading and grainfilling stages. Our study demonstrated the potential of using water-based SRI as a breeding tool to estimate genetic variability and identify genotypes with higher biomass production, and could eventually help to achieve higher grain yield in winter wheat. Key words: Wheat; biomass; grain yield; spectral reflectance index

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Heritability, correlated response, and indirect selection involving spectral reflectance indices and grain yield in wheat

Australian Journal of Agricultural Research ◽

10.1071/ar06270 ◽

2007 ◽

Vol 58 (5) ◽

pp. 432 ◽

Cited By ~ 15

Author(s):

M. A. Babar ◽

M. van Ginkel ◽

M. P. Reynolds ◽

B. Prasad ◽

A. R. Klatt

Keyword(s):

Grain Yield ◽

Spectral Reflectance ◽

Genetic Correlations ◽

Grain Filling ◽

Indirect Selection ◽

The Other ◽

Correlated Response ◽

Response To Selection ◽

Selection For ◽

Reflectance Indices

The objectives of this study were to assess the potential of using spectral reflectance indices (SRIs) as an indirect selection tool for grain yield in wheat under irrigated conditions. This paper demonstrates the genetic correlation between grain yield and SRIs, heritability and expected response to selection for grain yield and SRIs, correlated response to selection for grain yield estimated from SRIs, and efficiency of indirect selection for grain yield using SRIs in different spring wheat populations. Four field experiments, GHIST (15 CIMMYT globally adapted genotypes), RLs1 (25 random F3-derived families), RLs2 (36 random F3-derived families), and RLs3 (64 random F5-derived families) were conducted under irrigated conditions at the CIMMYT research station in north-west Mexico in 3 different years. Spectral reflectance was measured at 3 growth stages (booting, heading, and grain filling) and 7 SRIs were calculated using average values of spectral reflectance at heading and grain filling. Five previously developed SRIs (PRI, WI, RNDVI, GNDVI, SR), and 2 newly calculated SRIs (NWI-1 and NWI-2) were evaluated in the experiments. In general, the within- and between-year genetic correlations between grain yield and SRIs were significant. Three NIR-based indices (WI, NWI-1, and NWI-2) showed higher genetic correlations (0.73–0.92) with grain yield than the other indices (0.35–0.67), and these observations were consistent in all populations. Broad-sense heritability estimates for all indices were in general moderate to high (0.60–0.80), and higher than grain yield (0.45–0.70). The realised heritability for the 3 NIR-based indices was higher than for the other indices and for grain yield itself. Expected response to selection for all indices was moderate to high (0.54–0.85). The correlated response for grain yield estimated from the 3 NIR-based indices (0.59–0.64) was much higher than the correlated response for grain yield estimated from the other indices (0.31–0.46), and the efficiency of indirect selection for these 3 NIR-based indices was 90–96% of the efficiency of direct selection for grain yield. These results demonstrate the potential for using the 3 NIR-based SRI tools in breeding programs for selecting for increased genetic gains for yield.

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