<b>Leaf-level carbon isotope discrimination and its relationship with yield components as a tool for cotton phenotyping in unfavorable conditions

  • Giovani Greigh Brito Empresa Brasileira de Pesquisa Agropecuária
  • Nelson Dias Suassuna Empresa Brasileira de Pesquisa Agropecuária
  • Vivianny Nayse Silva Empresa Brasileira de Pesquisa Agropecuária
  • Valdinei Sofiatti Empresa Brasileira de Pesquisa Agropecuária
  • Valdir Diola Empresa Brasileira de Pesquisa Agropecuária
  • Camilo Lelis Morello Empresa Brasileira de Pesquisa Agropecuária

Abstract

The initial goal of this study was to measure the efficiency of carbon isotope discrimination (Δ) in distinguishing between cotton plant genotypes subjected to two water regimes. In addition, ∆ measurements, leaf water potential and gas exchange ratios were monitored. Using Brazilian breeding lines, this study also tested the usability of ∆ as a proxy for selecting high-performing yield components in cotton plants grown in unfavorable conditions, particularly water deficiency. For these experiments, ∆ and yield components were measured and their correlations analyzed. Differences among cotton genotypes for Δ (p < 0.0001) were verified, and it was found that this variable was significantly correlated with gas exchange. There was a significant positive correlation between Δ and seed cotton yield only in the site experiencing severe water deficiency (Santa Helena de Goiás). However, Δ had a significant negative correlation with fiber percentage. Our results indicate that Δ is a suitable tool for cotton phenotyping, and it may be applied in cotton breeding programs that aim to produce high-performing yield components in unfavorable conditions.

 

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Published
2014-07-07
How to Cite
Brito, G. G., Suassuna, N. D., Silva, V. N., Sofiatti, V., Diola, V., & Morello, C. L. (2014). <b&gt;Leaf-level carbon isotope discrimination and its relationship with yield components as a tool for cotton phenotyping in unfavorable conditions. Acta Scientiarum. Agronomy, 36(3), 335-345. https://doi.org/10.4025/actasciagron.v36i3.17986
Section
Crop Production

 

2.0
2019CiteScore
 
 
60th percentile
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2.0
2019CiteScore
 
 
60th percentile
Powered by  Scopus