Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Genetic Diversity Analysis of Red Rice from Hani's Terraced Fields in Yunnan Province

Authors
Mengli Ma, Yanhong Liu, Hengling Meng, Bingyue Lu
Corresponding Author
Mengli Ma
Available Online November 2016.
DOI
10.2991/aiea-16.2016.28How to use a DOI?
Keywords
Red rice; Hani's terraces fields; Genetic diversity.
Abstract

Genetic diversity is the main source of variability in any crop improvement program. There are abundant rice landraces in Hani's terraces fields in Yunnan, especially red rice resources. A set of 61 red rice landraces were characterized using 78 simple sequence repeat (SSR) markers to study genetic diversity. A total of 499 fragments were amplified, averaging 6.397 alleles per primer pair. The polymorphism information content ranged from 0.115 to 0.836 with an average of 0.593, the gene diversity index was 0.633 and heterozygosity was estimated as 0.165. The results showed that these rice landraces have a rich genetic diversity of Hani's terraces fields in Yunnan.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
10.2991/aiea-16.2016.28How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Mengli Ma
AU  - Yanhong Liu
AU  - Hengling Meng
AU  - Bingyue Lu
PY  - 2016/11
DA  - 2016/11
TI  - Genetic Diversity Analysis of Red Rice from Hani's Terraced Fields in Yunnan Province
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 154
EP  - 158
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.28
DO  - 10.2991/aiea-16.2016.28
ID  - Ma2016/11
ER  -