Spectral reflectance indices as a selection criterion for yield improvement in wheat

Scope and Methods of Study: Yield in wheat (Triticum aestivum L.) is a complex trait and influenced by many environmental factors, and yield improvement is a daunting task for wheat breeders. Spectral reflectance indices (SRIs) have been used to study different physiological traits in wheat. SRIs have the potential to differentiate genotypes for grain yield. SRIs strongly associated with grain yield can be used to achieve effective genetic gain in wheat under different environments. Three experiments (15 adapted genotypes, 25 and 36 random sister lines derived from two different crosses) under irrigated conditions, and three experiments (each with 30 advanced genotypes) under water limited conditions were conducted in three successive years in Northwest Mexico at the CIMMYT (International Maize and wheat Improvement Center) experimental station. SRIs and different agronomic data were collected for three years, and biomass was harvested for two years. Phenotypic and genetic correlations between SRIs and grain yield, between SRIs and biomass, realized and broad sense heritability, direct and correlated selection responses for grain yield, and SRIs were calculated.Findings and Conclusion: Seven SRIs were calculated, and three near infrared based indices (WI, NWI-1 and NWI-2) showed higher level of genetic and phenotypic correlations with grain yield, yield components and biomass than other SRIs (PRI, RNDVI, GNDVI, and SR) under both irrigated and water limiting environments. Moderate to high realized and broad sense heritability, and selection response were demonstrated by the three NIR based indices. High efficiency of correlated response for yield estimation was demonstrated by the three NIR based indices. The ratio between the correlated response to grain yield based on the three NIR based indices and direct selection response for grain yield was very close to one. The NIR based indices showed very high accuracy in selecting superior genotypes for grain yield under both well-watered and water-limited conditions. These results demonstrated that effective genetic gain in grain yield improvement can be achieved by making selections with the three NIR based indices