Robust Phenotyping Strategies for Evaluation of Stem Non-Structural Carbohydrates (NSC) in Rice

Edward Wolfrum, Diane Wang, Parminder Virk, Abdelbagi Ismail, Anthony Greenberg, Susan McCouch

Research output: Contribution to journalArticlepeer-review

29 Scopus Citations

Abstract

Rice plants (Oryza sativa) accumulate excess photoassimilates in the form of non-structural carbohydrates (NSCs) in their stems prior to heading that can later be mobilized to supplement photosynthate production during grain-filling. Despite longstanding interest in stem NSC for rice improvement, the dynamics of NSC accumulation, remobilization, and re-accumulation that have genetic potential for optimization have not been systematically investigated. Here we conducted three pilot experiments to lay the groundwork for large-scale diversity studies on rice stem NSC. We assessed the relationship of stem NSC components with 21 agronomic traits in large-scale, tropical yield trials using 33 breeder-nominated lines, established an appropriate experimental design for future genetic studies using a Bayesian framework to sample sub-datasets from highly replicated greenhouse data using 36 genetically diverse genotypes, and used 434 phenotypically divergent rice stem samples to develop two partial least-squares (PLS) models using near-infrared (NIR) spectra for accurate, rapid prediction of rice stem starch, sucrose, and total non-structural carbohydrates. We find evidence that stem reserves are most critical for short-duration varieties and suggest that pre-heading stem NSC is worthy of further experimentation for breeding early maturing rice.

Original languageAmerican English
Pages (from-to)6125-6138
Number of pages14
JournalJournal of Experimental Botany
Volume67
Issue number21
DOIs
StatePublished - 1 Nov 2016

Bibliographical note

Publisher Copyright:
© 2016 The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

NREL Publication Number

  • NREL/JA-5100-67277

Keywords

  • Near-infrared spectroscopy
  • non-structural carbohydrates
  • Oryza sativa
  • partial least-squares
  • replication
  • yield potential

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