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Climate change-induced biotic and abiotic stresses pose a significant threat to global efforts aimed at nutritional enhancement in wheat. Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), remains a major constraint to wheat production. Wheat improvement programs must now target multiple traits, particularly combining nutritional quality with durable stripe rust resistance. Integrating conventional breeding approaches with spectral vegetation indices and SSR-based genotyping offers an efficient, eco-friendly strategy for accelerating genetic gains. The present study, aimed to characterize high-micronutrient advanced wheat breeding lines developed during (2019-23) along with their parents for stripe rust resistance using both physiological and molecular tools during 2023-24. A total of 21 genotypes—comprising 13 advanced breeding lines and 8 parents—were evaluated in a Randomized Complete Block Design (RCBD) with three replications under both artificial epiphytotic and controlled conditions. Vegetation indices such as NDVI (based on NIR and IR reflectance), chlorophyll content (measured via absorbance at 650 nm and 940 nm), and canopy temperature (assessed via infrared radiation emission) were used as non-invasive indicators of plant health and stress response. Molecular analysis employed 12 SSR markers linked to known Yr resistance genes, among which four were found to be polymorphic but out of these four only Barc 181 ( Yr24 ) and Xgwm 102 ( Yr16 ) confirmed resistance in lines JWBL-3, JWBL-12 and JWBL-13, which also demonstrated high yield potential. Genotypes JWBL-1, JWBL-3, JWBL-4, JWBL-7, JWBL-13, and parental lines HP-25 and HP-45 exhibited lower values for Coefficient of Infection (CI) and Area Under Disease Progress Curve (AUDPC), indicating better resistance levels. These results underscore the potential of combining marker-assisted selection (MAS) with vegetation index-based physiological screening to efficiently identify and advance stripe rust-resistant, nutritionally enhanced wheat genotypes.
Singh et al. (Thu,) studied this question.