4.5 Article

Multi-Level Determination of Heat Tolerance in Cotton (Gossypium hirsutum L.) under Field Conditions

Journal

CROP SCIENCE
Volume 50, Issue 6, Pages 2553-2564

Publisher

CROP SCIENCE SOC AMER
DOI: 10.2135/cropsci2010.03.0182

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Funding

  1. Cotton Catchment Communities Cooperative Research Corporation
  2. Australian Cotton Research and Development Corporation
  3. University of Sydney
  4. Texas AM University
  5. CSIRO, Plant Industry

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Screening a diverse set of cotton genotypes for heat tolerance may enable identification of superior germplasm for inclusion in future breeding programs. This study used a multilevel approach to assess whether cultivar differences in biochemistry reflected physiology or yield performance under high temperature environments for high yielding genotypes. Membrane integrity and enzyme viability were determined for genotypes Sicot 53, Sicala 45, Sicala V-2, and CSX 99209-376 subjected to high water bath temperatures. The temperature for 50% membrane integrity was lowest for Sicala 45 (temperature [degrees C] at which 50% relative electrical conductivity occurred [T(50)] = 39.3 degrees C) and enzyme viability was highest for Sicot 53 (spectrophotometric absorbance at 530 nm at a specific water bath temperature [Abs(t)] = 1.1) compared with the other genotypes (T(50) = 43.7-44.7 degrees C and Abs(t) = 0.6-0.7), indicating relative heat tolerance was higher for Sicot 53 and lower for Sicala 45. To validate this approach in the field, Sicot 53 and Sicala 45 were evaluated for yield, gas exchange, and fluorescence under high temperature tents. Sicot 53 outperformed Sicala 45 under tents. Yield and fruit retention decreased to a greater extent, photosynthesis and electron transport rate (ETA) were lower and stomatal conductance and transpiration were higher for Sicala 45 compared with Sicot 53 under tents. Electron transport rate, membrane integrity, and enzyme viability were the most rapid and reliable screens for heat tolerance, and the utility of these screens were enhanced by incorporation into a multilevel plant screening model encompassing both laboratory and field based components.

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