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ARS Home » Southeast Area » Stuttgart, Arkansas » Dale Bumpers National Rice Research Center » Research » Publications at this Location » Publication #269323

Title: 13Carbon isotope discrimination in major C4 weeds of rice-implications for root interference studies

Author
item Gealy, David

Submitted to: Proceedings of Southern Weed Science Society
Publication Type: Abstract Only
Publication Acceptance Date: 1/26/2011
Publication Date: 1/26/2011
Citation: Gealy, D.R. 2011. 13Carbon isotope discrimination in major C4 weeds of rice-implications for root interference studies [abstract]. Proceedings of Southern Weed Science Society. 64:138.

Interpretive Summary:

Technical Abstract: Assessing below ground plant interference in rice has been difficult in the past because separation of intertwined weed and crop roots is nearly impossible. A simple 13C depletion method was previously developed for simultaneous quantification of barnyardgrass and rice roots in flooded fields. This research investigated the feasibility of extending this methodology to other rice weed species. '13C (an expression of 13C:12C ratios) levels in roots and leaves of rice were compared to those of ten weed species grown in monoculture in greenhouse and/or field. C4 species included the tropical grasses, barnyardgrass, bearded sprangletop, Amazon sprangletop, broadleaf signalgrass, fall panicum, and large crabgrass, as well as yellow nutsedge. C3 weed species included red rice, gooseweed, and redstem. Rice root '13C levels averaged ~-28‰ indicating that these roots were highly 13C-depleted. Root '13C levels in the C4 species ranged from -10‰ in yellow nutsedge to -17‰ in bearded sprangletop, indicating that these species were much less 13C-depleted than rice, and were suitable for a 13C discrimination approach to root interactions with rice. '13C values for all species tested were strikingly consistent from year to year and in different environments. Shoots of rice tended to be slightly more 13C-depleted than roots. Corrective mathematical ‘mixing’ equations derived from inputs including the weights, carbon mass, % carbon content, and '13C levels of roots and soil were developed to improve the accuracy of root weight and root '13C levels estimated from soil-contaminated samples.