Chandra Babu Ranganathan

Prof. Chandra Babu Ranganathan


Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 October 2012 in Rice
Verified
Journal Article
Open access
PDF file
ARAnitha Raman
Anitha Raman
SVSatish Verulkar
Satish Verulkar
NMNimai Mandal
Nimai Mandal
MVMukund Variar
Mukund Variar
VSV Shukla
V Shukla
AKArvind Kumar
Arvind Kumar
Background: Drought is the most severe abiotic stress reducing rice yield in rainfed drought prone ecosystems. Variation in intensity and severity of drought from season to season and place to place requires cultivation of rice varieties with different level of drought tolerance in different areas. Multi environment evaluation of breeding lines helps breeder to identify appropriate genotypes for areas prone to similar level of drought stress. From a set of 129 advanced rice (Oryza sativa L.) breeding lines evaluated under rainfed drought-prone situations at three locations in eastern India from 2005 to 2007, a subset of 39 genotypes that were tested for two or more years was selected to develop a drought yield index (DYI) and mean yield index (MYI) based on yield under irrigated, moderate and severe reproductive-stage drought stress to help breeders select appropriate genotypes for different environments. Results: ARB 8 and IR55419-04 recorded the highest drought yield index (DYI) and are identified as the best drought-tolerant lines. The proposed DYI provides a more effective assessment as it is calculated after accounting for a significant genotype x stress-level interaction across environments. For rainfed areas with variable frequency of drought occurrence, Mean yield index (MYI) along with deviation in performance of genotypes from currently cultivated popular varieties in all situations helps to select genotypes with a superior performance across irrigated, moderate and severe reproductive-stage drought situations. IR74371-70-1-1 and DGI 75 are the two genotypes identified to have shown a superior performance over IR64 and MTU1010 under all situations. Conclusion: For highly drought-prone areas, a combination of DYI with deviation in performance of genotypes under irrigated situations can enable breeders to select genotypes with no reduction in yield under favorable environments compared with currently cultivated varieties. For rainfed areas with variable frequency of drought stress, use of MYI together with deviation in performance of genotypes under different situations as compared to presently cultivated varieties will help breeders to select genotypes with superior performance under all situations.

24 July 2015 in Rice
Verified
Journal Article
Open access
PDF file
SPSilvas J Prince
Silvas J Prince
RBR Beena
R Beena
MICHAEL SELVARAJMICHAEL SELVARAJ
MICHAEL SELVARAJ
SSS Senthivel
S Senthivel
CRChandra Babu Ranganathan
Chandra Babu Ranganathan
Background: Drought stress is a major limitation to rainfed rice production and yield stability. Identifying yield-associated quantitative trait loci (QTLs) that are consistent under drought stress predominant in target production environments, as well as across different genetic backgrounds, will help to develop high-yielding rice cultivars suitable for water-limited environments through marker-assisted breeding (MAB). Considerable progress has been made in mapping QTLs for drought resistance traits in rice; however, few have been successfully used in MAB. Results: Recombinant inbred lines of IR20 × Nootripathu, two indica cultivars adapted to rainfed target populations of environments (TPEs), were evaluated in one and two seasons under managed stress and in a rainfed target drought stress environment, respectively. In the managed stress environment, the severity of the stress meant that measurements could be made only on secondary traits and biomass. In the target environment, the lines experienced varying timings, durations, and intensities of drought stress. The rice recombinant inbred lines exhibited significant genotypic variation for physio-morphological, phenological, and plant production traits under drought. Nine and 24 QTLs for physio-morphological and plant production traits were identified in managed and natural drought stress conditions in the TPEs, respectively. Yield QTLs that were consistent in the target environment over seasons were identified on chromosomes 1, 4, and 6, which could stabilize the productivity in high-yielding rice lines in a water-limited rainfed ecosystem. These yield QTLs also govern highly heritable key secondary traits, such as leaf drying, canopy temperature, panicle harvest index and harvest index. Conclusion: Three QTL regions on chromosome 1 (RM8085), chromosome 4 (I12S), and chromosome 6 (RM6836) harbor significant additive QTLs for various physiological and yield traits under drought stress. The similar chromosomal region on 4 and 6 were found to harbor QTLs for canopy temperature and leaf drying under drought stress conditions. Thus, the identified large effect yield QTLs could be introgressed to develop rice lines with stable yields under varying natural drought stress predominant in TPEs.

1 January 2021 in Field Crops Research
Verified
Journal Article
Open access
AKArvind Kumar
Arvind Kumar
ARAnitha Raman
Anitha Raman
SYShailesh Yadav
Shailesh Yadav
SVS.B. Verulkar
S.B. Verulkar
NMN.P. Mandal
N.P. Mandal
HPH.P. Piepho
H.P. Piepho
• Genetic gain for rice grain yield for International Rice Research Institute drought breeding program was estimated. • Positive trend of 0.68 %, 0.87 %, 1.9 % under irrigated control, moderate and severe drought achieved. • Superiority of new rice varieties over currently grown demonstrated on farmers’ fields. • International Rice Research Institute developed rice varieties can protect farmers from crop losses under drought conditions.

5 February 2011 in Molecular Biotechnology
Verified
Journal Article
Closed access
PDF file
ASArvindkumar Shivaji Salunkhe
Arvindkumar Shivaji Salunkhe
RPR. Poornima
R. Poornima
KPK. Silvas Jebakumar Prince
K. Silvas Jebakumar Prince
PKP. Kanagaraj
P. Kanagaraj
JSJ. Annie Sheeba
J. Annie Sheeba
CRChandra Babu Ranganathan
Chandra Babu Ranganathan

3 December 2009 in Acta Physiologiae Plantarum
Verified
Journal Article
Closed access
PDF file
SGSelvaraj Michael Gomez
Selvaraj Michael Gomez
NBN. Manikanda Boopathi
N. Manikanda Boopathi
SKS. Satheesh Kumar
S. Satheesh Kumar
TRT. Ramasubramanian
T. Ramasubramanian
ZCZhu Chengsong
Zhu Chengsong
CRChandra Babu Ranganathan
Chandra Babu Ranganathan

23 May 2006 in Genetic Resources and Crop Evolution
Verified
Journal Article
Closed access
PDF file
BBB. Kalyana Babu
B. Kalyana Babu
Senthil NatesanSenthil Natesan
Senthil Natesan
SGS. Michael Gomez
S. Michael Gomez
KBK. R. Biji
K. R. Biji
NRN. S. Rajendraprasad
N. S. Rajendraprasad
CRChandra Babu Ranganathan
Chandra Babu Ranganathan