Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat

Spectral indices as a selection tool in plant breeding could improve genetic gains for different important traits. The objectives of this study were to assess the potential of using spectral reflectance indices (SRI) to estimate genetic variation for in-season biomass production, leaf chlorophyll, and canopy temperature (CT) in wheat (Triticum aestivum L.) under irrigated conditions. Three field experiments, GHIST (15 CIMMYT globally adapted historic genotypes), RILs1 (25 recombinant inbred lines [RILs]), and RILs2 (36 RILs) were conducted under irrigated conditions at the CIMMYT research station in northwest Mexico in three different years. Five SRI were evaluated to differentiate genotypes for biomass production. In general, genotypic variation for all the indices was significant. Near infrared radiation (NIR)–basedindicesgavethehighestlevelsofassociationwithbiomass production and the higher associations were observed at heading and grainfilling, rather than at booting. Overall, NIR-based indices were more consistent and differentiated biomass more effectively compared to the other indices. Indices based on ratio of reflection spectra cor

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