Characterizing natural genetic variation in photosynthetic efficiency across 44 accessions and five subpopulations of oryza sativa

With an ever-growing human population and a finite amount of arable land, the ability to produce higher yields with fewer inputs has become increasingly imperative. Improving photosynthetic efficiency at the leaf level, especially leaf CO2 uptake (Asat) is an approach to not only bettering crop yields, but also optimizing water and nutrient use efficiency. As the world’s second most cultivated crop, improving photosynthesis in Oryza sativa would have positive implications for millions worldwide who are dependent on rice for their economic livelihoods and the majority of their dietary calories. In this study, 44 accessions representing all five rice subpopulations from the larger Rice Diversity Panel 1 (RDP1) were phenotyped for photosynthetic efficiency at the International Rice Research Institute (IRRI) in Los Baños, Philippines. Phenotyping of both physiological and biochemical traits allowed for an in depth understanding of overall photosynthetic activity at the genotype and subpopulation levels. This study found that there are significant differences for individual components of photosynthetic efficiency between the subpopulations of rice. Differences between subpopulations were found at the biochemical level for carboxylation efficiency, maximum rate of carboxylation (Vcmax) maximum electron transport rate (Jmax), and triose-phosphate use (TPU) limitations – among 25 other traits. For example, subpopulation tropical japonica had the highest values for both Vcmax and Jmax, and demonstrated 11.9% and 19% higher rates for both traits respectively when compared with the lowest performing subpopulations. These differences were more pronounced at the accession level when genotypes were compared against the control IR64, confirming a wealth of natural variation that might be exploited to improve photosynthetic efficiency in cultivated rice. Examining existing natural genetic variation allows superior genotypes and traits to be identified, aiding in targeted plant improvement through mapping in the future.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Crop Sciences

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Acevedo-Siaca, Liana G.

Contributors dc:contributor

• Long, Stephen P.

• Photosynthesis
• Plant physiology
• Natural genetic variation
• Rice
• Rice subpopulations

Statement dc:rights

• Copyright 2017 Liana Acevedo-Siaca

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/99257

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/99257