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Robin, S.
- Evaluation of Rice Genetic Diversity and Variability in a Population Panel by Principal Component Analysis
Abstract Views :212 |
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Authors
Vishnu Varthini Nachimuthu
1,
S. Robin
2,
D. Sudhakar
3,
M. Raveendran
3,
S. Rajeswari
2,
S. Manonmani
2
Affiliations
1 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu rajisundar93@gmail.com, swamimano@yahoo.co.in, IN
2 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
3 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
1 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu rajisundar93@gmail.com, swamimano@yahoo.co.in, IN
2 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
3 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 7, No 10 (2014), Pagination: 1555-1562Abstract
A population panel of 192 rice genotypes comprising traditional landraces and exotic genotypes from 12 countries was evaluated for 12 agro - morphological traits by principal component analysis for determining the pattern of genetic diversity and relationship among individuals. Twelve quantitative characters i.e. plant height, leaf length, number of productive tillers, panicle length, number of filled grains, spikelet fertility, days to 50% flowering; days to harvest maturity, grain length, grain width, grain length width ratio, and single plant yield were measured. The largest variation was observed for number of productive tillers with Coefficient of Variation (CV) of 28.03% followed by number of filled grains per panicle, single plant yield, leaf length , grain length width ratio. Days to maturity has shown the least variation with the CV of 9.74%. Principal component analysis was utilized to examine the variation and to estimate the relative contribution of various traits for total variability. In the current study, Component 1 had the contribution from the traits such as days to 50% flowering, leaf length, plant height, panicle length, days to maturity and number of filled grains which accounted 28.46% of the total variability. Grain width and grain length width ratio has contributed 16.8% of total variability in component 2. The remaining variability of 14.4%, 11.7% and 9.3% was consolidated in component 3, component 4 and component 5 by various traits such as spikelet fertility, single plant yield, grain length and number of productive tillers. The cumulative variance of 80.56% of total variation among 12 characters was explained by the first five axes. Thus the results of principal component analysis used in the study have revealed the high level of genetic variation and the traits contributing for the variation was identified. Hence this population panel can be utilized for trait improvement in breeding programs for the traits contributing for major variation.Keywords
Genetic Variation, Principal Component Analysis, Rice- Genotypic Variation for Micronutrient Content in Traditional and Improved Rice Lines and its Role in Biofortification Programme
Abstract Views :244 |
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Authors
Vishnu Varthini Nachimuthu
1,
S. Robin
1,
D. Sudhakar
2,
S. Rajeswari
1,
M. Raveendran
2,
K. S. Subramanian
3,
Shalini Tannidi
1,
Balaji Aravindhan Pandian
1
Affiliations
1 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, IN
2 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, IN
3 Department of Nano science and technology, Tamil Nadu Agricultural University, Coimbatore, IN
1 Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, IN
2 Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, IN
3 Department of Nano science and technology, Tamil Nadu Agricultural University, Coimbatore, IN
Source
Indian Journal of Science and Technology, Vol 7, No 9 (2014), Pagination: 1414-1425Abstract
Biofortification is an emerging cost-effective strategy to address global malnutrition especially in developing countries. This strategy involves supplying of micronutrients such as iron and zinc in the staple foods by using conventional plant breeding and biotechnology methods. Initial step in conventional plant breeding is to screen the natural gene reservoir for existing variation. The objective of this study is to estimate iron and zinc in the brown rice of 192 germplasm lines and to define its role in biofortification programme. Substantial variations among 192 lines existed for both iron and zinc content. Iron concentration ranged from 6.6 ìg/g to 16.7 ìg/g and zinc concentration from 7.1 ìg/g to 32.4 ìg/g in brown rice. Iron and zinc concentration were positively correlated implying the chance for concurrent selection for both the micronutrients. Micronutrient-rich genotypes identified in this study opens up the possibilities for the identification of genomic regions or QTLs responsible for mineral uptake and translocation that can be used as donor for developing nutrient enriched varieties.Keywords
Biofortification, Germplasm, Iron, Micronutrient, Variability, Zinc- DBT Propelled National Effort in Creating Mutant Resource for Functional Genomics in Rice
Abstract Views :326 |
PDF Views:102
Authors
S. V. Amitha Mithra
1,
M. K. Kar
2,
T. Mohapatra
1,
S. Robin
3,
N. Sarla
4,
M. Seshashayee
5,
K. Singh
6,
A. K. Singh
7,
N. K. Singh
1,
R. P. Sharma
1
Affiliations
1 ICAR-National Research Centre on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi 110 012, IN
2 ICAR-National Rice Research Institute, Cuttack 753 006, IN
3 Tamil Nadu Agricultural University, Coimbatore 641 003, IN
4 ICAR-Indian Institute Rice Research, Hyderabad 500 030, IN
5 University of Agricultural Sciences, Bengaluru 560 065, IN
6 Punjab Agricultural University, Ludhiana 500 030, IN
7 ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN
1 ICAR-National Research Centre on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi 110 012, IN
2 ICAR-National Rice Research Institute, Cuttack 753 006, IN
3 Tamil Nadu Agricultural University, Coimbatore 641 003, IN
4 ICAR-Indian Institute Rice Research, Hyderabad 500 030, IN
5 University of Agricultural Sciences, Bengaluru 560 065, IN
6 Punjab Agricultural University, Ludhiana 500 030, IN
7 ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN
Source
Current Science, Vol 110, No 4 (2016), Pagination: 543-548Abstract
In 2007, with the help of DBT, a research project to create mutant resources for functional genomics in rice was launched through a national initiative involving ICAR-National Research Centre on Plant Biotechnology, New Delhi; ICAR-Indian Agricultural Research Institute, New Delhi; Tamil Nadu Agricultural University, Coimbatore; ICAR-Indian Institute of Rice Research, Hyderabad; University of Agricultural Sciences, Bangalore and Punjab Agricultural University, Ludhiana. Genetically well-defined material is a prerequisite for functional genomics. Thus, the project aimed to generate EMS mutants in the background of an upland and short duration aus genotype, Nagina22, characterize the mutants and use them in crop improvement. As of now, nearly 85,000 rice M2 mutant populations have been created under the project. Based on field phenotyping, gain and or loss of function mutants for tolerance to herbicide spray, drought, salinity and resistance to rice leaf and panicle blast, sheath blight and high phosphorus (P) use efficiency under low P field have been identified. Notably, the herbicide-tolerant mutant identified is under the process of registration for distribution to public and private rice breeders under appropriate material transfer agreement. Besides this, the project also aims to serve as a 'National Repository of rice EMS mutant resource' for the researchers involved in rice biology and improvement in the country.Keywords
EMS Mutagenesis, Mutant Resources, Nagina22, Rice.References
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