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

Cluster Analysis of Red Rice based on SSR Markers from Hani's Terraced Fields in Yunnan Province

Authors
Mengli Ma, Yanhong Liu, Tiantao Wang, Bingyue Lu
Corresponding Author
Mengli Ma
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.29How 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. Cluster analysis based on unweighted pair group method with arithmetic mean showed that the similarity coefficients varied from 0.19 to 0.85, all genotypes grouped into two major clusters in the dendrogram at 0.19 similarity. Indica rice clusters including 58 rice landraces as main rice cultivation types in 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
https://doi.org/10.2991/aiea-16.2016.29How 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  - Tiantao Wang
AU  - Bingyue Lu
PY  - 2016/11
DA  - 2016/11
TI  - Cluster Analysis of Red Rice based on SSR Markers 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  - 159
EP  - 162
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.29
DO  - https://doi.org/10.2991/aiea-16.2016.29
ID  - Ma2016/11
ER  -