244-17 Cotton Growth and Photosynthetic Acclimation to Phosphorus Nutrition and CO2 Enrichment.
Poster Number 429
See more from this Division: C02 Crop Physiology and MetabolismSee more from this Session: General Crop Physiology & Metabolism: II
Tuesday, October 23, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
Two experiments were conducted in 2011 to study cotton response to varying phosphate (Pi) supply under current and projected atmospheric CO2 concentrations. Cotton (cultivar deltapine 555) plants were grown in six growth chambers with three levels of Pi supply (0.2 (optimum), 0.05 and 0.01 mM) and two levels of CO2 (400 and 800 µmol mol-1) under optimum irrigation environment for 95 days. Several growth and physiological measurements were made during and at the end of both experiments. Irrespective of the CO2 concentrations, Pi deficient plants exhibited highly reduced leaf photosynthesis (Pnet) and were significantly shorter (45-55%) with decreased node numbers (20-25%) accompanied with reduced leaf area (80-90%) and total biomass (75-80%). Reduced rate of stem elongation, leaf area expansion caused primarily due to reduced cell elongation were the main cause of smaller size of the plants. In general, CO2enrichment failed to alleviate the negative effect of Pi deficiency on photosynthesis and reproductive structure (flower, square and boll). However, elevated CO2 stimulated total biomass production mainly due to rapid growth rate and increased leaf area under Pi deficient conditions. Irrespective of the P supply, photosynthetic acclimations of cotton plants to CO2 enriched environments were evident from the reduced quantum yields and carboxylation efficiency of the photosynthetic processes. The results from this study clearly indicated that the amount of available soil Pi will affect cotton growth and development independent of atmospheric CO2 concentration. One of the aspects of the study was to develop numerical relationships of cotton tissue P content with growth and photosynthesis to derive Pi response algorithms in cotton to improve the predictability of cotton crop simulation model GOSSYM.
See more from this Division: C02 Crop Physiology and MetabolismSee more from this Session: General Crop Physiology & Metabolism: II