Synthetic wheat as a new source of flour quality under drought conditions: Associations with solvent retention capacity.
Synthetic hexaploid lines are proposed as high-potential germplasm for improving bread wheat by introducing new genes (biotic and abiotic stresses) lost during common wheat evolution. A panel of 99 synthetic and common wheat was studied for quality and grain-related traits and drought tolerance unde...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316945 |
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| Summary: | Synthetic hexaploid lines are proposed as high-potential germplasm for improving bread wheat by introducing new genes (biotic and abiotic stresses) lost during common wheat evolution. A panel of 99 synthetic and common wheat was studied for quality and grain-related traits and drought tolerance under two different moisture conditions (water stress and normal) during two growing seasons. Results indicated different variations for most traits suggesting that the synthetic hexaploid wheat-derived lines (SHW-DL) panel contains valuable genes for drought tolerance improvement of wheat. Drought stress reduced morphological traits and production but increased protein (Pro), rapid mix test (RMT), and solvent retention capacity (SRC) traits. Synthetic wheat lines were superior with higher grain yield, glutenin, damaged starch, available pentosane, overall water holding capacity, and gluten strength (glutenin and gliadin strength) compared to common wheat making them more suitable for bread-baking. The results showed that solvent retention capacity had a strong capacity to differentiate the quality of wheat genotypes. Correlation analysis indicated that genetic improvement for high-yielding varieties can be achieved by producing more damaged starch, higher water absorption, hardness, and lower gluten strength, and zeleny (ZEL). Selection of superior genotypes using univariate and multivariate methods will be discussed. |
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| ISSN: | 1932-6203 |