Meeting agricultural demands is becoming progressively difficult due to population growth and changing climate. Breeding stress-resilient crops is a viable solution to meet these challenges, as information about genetic variation and their role in stress tolerance is becoming available due to high volume of data generated through advancement in technology. We quantified photosynthesis model parameters using light and CO2 response curves of 11 rice genotypes with varying susceptibility to stress (drought and elevated nighttime temperature). We used model parameters, such as the maximum carboxylation rate (Vcmax), the maximum electron transport rate (Jmax), the maximum gross photosynthesis rate (Pmax), daytime respiration (Rd), quantum yield (phi), and stress on photosystem II (Fv/Fm) as phenotypic traits to screen the genotypes under well watered and drought conditions in a greenhouse study.
Results/Conclusions
Our results show a large variation in model parameters across these genotypes and screened stress tolerant genotypes based on changes in models parameters under well watered and drought conditions. For example Vcmax and Pgmax declined under drought conditions in drought sensitive genotypes (e.g., nipponbare and glaberrima) but showed no changes in drought resistant genotypes (e.g., N22). N22 showed the highest respiration level and 311688 showed the lowest respiration level. Our integrated approach, combining genetic information and photosynthesis modeling, adds a new dimension to genetic data and provides improved information for plant breeders to improve crop yield under stress conditions.