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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/49968
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | S L Krishnamurthy | en_US |
dc.contributor.author | S K Sharma | en_US |
dc.contributor.author | D K Sharma | en_US |
dc.contributor.author | P C Sharma | en_US |
dc.contributor.author | Y P Singh | en_US |
dc.contributor.author | V K Mishra | en_US |
dc.contributor.author | D Burman | en_US |
dc.contributor.author | B Maji | en_US |
dc.contributor.author | B K Bandyopadhyay | en_US |
dc.contributor.author | S Mandal | en_US |
dc.contributor.author | S K Sarangi | en_US |
dc.contributor.author | R K Gautam | en_US |
dc.date.accessioned | 2021-07-24T16:24:23Z | - |
dc.date.available | 2021-07-24T16:24:23Z | - |
dc.date.issued | 2016-06-01 | - |
dc.identifier.citation | Krishnamurthy, S.L., Sharma, S.K., Sharma, D.K. et al. 2016. Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India, Cereal Research Communication, Vol.44(2):349-360, DOI: https://doi.org/10.1556/0806.43.2015.055., | en_US |
dc.identifier.uri | https://akjournals.com/view/journals/0806/44/2/article-p349.xml | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/49968 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Genotype × environment (G × E) interaction effects are of special interest for identifying the most suitable genotypes with respect to target environments, representative locations and other specific stresses. Twenty-two advanced breeding lines contributed by the national partners of the Salinity Tolerance Breeding Network (STBN) along with four checks were evaluated across 12 different salt affected sites comprising five coastal saline and seven alkaline environments in India. The study was conducted to assess the G × E interaction and stability of advanced breeding lines for yield and yield components using additive main effects and multiplicative interaction (AMMI) model. In the AMMI1 biplot, there were two mega-environments (ME) includes ME-A as CARI, KARAIKAL, TRICHY and NDUAT with winning genotype CSR 2K 262; and ME-B as KARSO, LUCKN, KARSA, GOA, CRRI, DRR, BIHAR and PANVE with winning genotypes CSR 36. Genotypes CSR 2K 262, CSR 27, NDRK 11-4, NDRK 11-3, NDRK 11-2, CSR 2K 255 and PNL 1-1-1-6-7-1 were identified as specifically adapted to favorable locations. The stability and adaptability of AMMI indicated that the best yielding genotypes were CSR 2K 262 for both coastal saline and alkaline environments and CSR 36 for alkaline environment. CARI and PANVEL were found as the most discernible environments for genotypic performance because of the greatest GE interaction. The genotype CSR 36 is specifically adapted to coastal saline environments GOA, KARSO, DRR, CRRI and BIHAR and while genotype CSR 2K 262 adapted to alkaline environments LUCKN, NDUAT, TRICH and KARAI. Use of most adapted lines could be used directly as varieties. Using them as donors for wide or specific adaptability with selection in the target environment offers the best opportunity for widening the genetic base of coastal salinity and alkalinity stress tolerance and development of adapted genotypes. Highly stable genotypes can improve the rice productivity in salt-affected areas and ensure livelihood of the resource poor farming communities. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | AMMI | en_US |
dc.subject | GxE interaction | en_US |
dc.subject | rice | en_US |
dc.subject | salinity | en_US |
dc.subject | alkalinity | en_US |
dc.title | Analysis of Stability and G × E Interaction of Rice Genotypes across Saline and Alkaline Environments in India | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Cereal Research Communications | en_US |
dc.publication.volumeno | 44(2) | en_US |
dc.publication.pagenumber | 349-360 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | DOI: https://doi.org/10.1556/0806.43.2015.055 | en_US |
dc.publication.authorAffiliation | ICAR::Central Soil Salinity Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | International | en_US |
dc.publication.naasrating | 6.81 | en_US |
dc.publication.impactfactor | 0.81 | en_US |
Appears in Collections: | NRM-CSSRI-Publication |
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