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CROP BREEDING, GENETICS & CYTOLOGY

Spectral Reflectance Indices as a Potential Indirect Selection Criteria for Wheat Yield under Irrigation

^a Department of Plant and Soil Sciences, 368 Ag. Hall, Oklahoma State University, Stillwater, OK 74078, USA
^b International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico, El Batan, Texcoco, Mexico
^c Department of Primary Industries (DPI), Private Bag 260, Horsham, Victoria, Postcode: 3401, DX Number: 216515, Australia
^d Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK 74078, USA

^* Corresponding author (aklatt{at}mail.pss.okstate.edu)

The objectives of this study were to assess the potential of using spectral reflectance indices (SRI) as an indirect selection tool to differentiate spring wheat (Triticum aestivum L.) genotypes for grain yield under irrigated conditions. This paper demonstrates only the first step in using the SRI as indirect selection criteria by reporting genetic variation for SRI among genotypes, the effect of phenology and year on SRI and their interaction with genotypes, and the correlations between SRI and grain yield and yield components of wheat. Three field experiments—15 CIMMYT globally adapted genotypes (GHIST), 25 random F₃–derived lines (RLs1), and 36 random F₃–derived lines (RLs2)—were conducted under irrigated conditions at the CIMMYT research station in northwest Mexico in three different years. Five previously developed SRI (photochemical reflectance index [PRI], water index [WI], red normalized difference vegetation index [RNDVI], green normalized difference vegetation index [GNDVI], simple ratio [SR]) and two newly calculated SRI (normalized water index-1 [NWI-1] and normalized water index-2 [NWI-2]) were evaluated in the experiments. In general, genotypic variation for all the indices was significant. Near infrared radiation (NIR)–based indices (WI, NWI-1, NWI-2) gave the highest levels of association with grain yield during the 3 yr of the study. A clear trend for higher association between grain yield and the NIR-based indices was observed at heading and grainfilling than at booting. Overall, NIR-based indices were more consistent and differentiated grain yield more effectively compared to the other indices. The results demonstrated the potential of using SRI as a tool in breeding programs for selecting for increased genetic gains for yield.

Abbreviations: GHIST, global historic trials • GNDVI, green normalized difference vegetation index • LAI, leaf area index • NIR, near infrared radiation • NWI-1, normalized water index-1 • NWI-2, normalized water index-2 • PRI, photochemical reflectance index • RLs1, random lines-1 • RLs2, random lines-2 • RNDVI, red normalized difference vegetation index • SR, simple ratio • SRI, spectral reflectance indices • VIS, visible wavelength • WI, water index

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