| Title |
Field level evaluation of rice introgression lines for heat tolerance and validation of markers linked to spikelet fertility
|
|---|---|
| Published in |
Physiology and Molecular Biology of Plants, April 2016
|
| DOI | 10.1007/s12298-016-0350-6 |
| Pubmed ID | |
| Authors |
V. Vishnu Prasanth, Kumari Ramana Basava, M. Suchandranath Babu, Venkata Tripura V.G.N., S. J. S. Rama Devi, S. K. Mangrauthia, S. R. Voleti, N. Sarla |
| Abstract |
Rice lines derived from wild species and mutants can serve as a good resource for favorable alleles for heat tolerance. In all, 48 stable lines including 17 KMR3/O. rufipogon introgression lines (KMR3 ILs), 15 Swarna/O. nivara ILs (Swarna ILs) along with their parents, Nagina 22 (N22) and its 4 EMS induced mutants and 7 varieties were evaluated for heat tolerance under irrigated conditions under field in two seasons, wet season 2012 using poly cover house method and dry season 2013 using late sown method. Spikelet fertility (SF), yield per plant (YP) and heat susceptibility index (HSI) for these two traits were considered as criteria to assess heat tolerance compared to control. Four KMR3 ILs and eight Swarna ILs were identified as heat tolerant based on SF and YP and their HSIs in both wet and dry seasons. S-65 and S-70 showed low SF and high YP consistently in response to heat in both seasons. We provide evidence that SF alone may not be the best criterion to assess heat tolerance and including YP is important as lines with low SF but high YP and vice versa were identified under heat stress. Out of 49 SSR markers linked to spikelet fertility, 18 were validated for five traits. RM229 in wet season and RM430 and RM210 in dry season were significantly associated with both SF and its HSI under heat stress. RM430 was also significantly associated with both YP and its HSI in dry season. Thirty two candidate genes were identified close to nine markers associated with traits under heat stress. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 25% |
| Student > Ph. D. Student | 3 | 15% |
| Student > Doctoral Student | 1 | 5% |
| Student > Master | 1 | 5% |
| Student > Postgraduate | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 9 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 45% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Business, Management and Accounting | 1 | 5% |
| Unknown | 8 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2016.
All research outputs
#15,380,359
of 22,881,154 outputs
Outputs from Physiology and Molecular Biology of Plants
#134
of 413 outputs
Outputs of similar age
#179,394
of 299,088 outputs
Outputs of similar age from Physiology and Molecular Biology of Plants
#3
of 8 outputs
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