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dc.contributorPattanashetti, Santoshen_US
dc.contributorGowda, M. V. C.en_US
dc.contributorNadaf, Hajisaheb L.en_US
dc.contributorChandran, P.en_US
dc.contributorAshalatha, KV.en_US
dc.contributorNaidu, Gopalakrishna K.en_US
dc.creatorMotagi, Babu Nen_US
dc.date.accessioned2019-06-04T22:25:14Z
dc.date.available2019-06-04T22:25:14Z
dc.identifierhttp://oar.icrisat.org/9234/1/Yield%20loss-foliar%20disaeses-%20modelling%20in%20groundnut-47th%20APRES%20meeting%20July%202015.pdfen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/rRvCJjbSen_US
dc.identifier.citationBabu N Motagi, Santosh Pattanashetti, M. V. C. Gowda, Hajisaheb L. Nadaf, P. Chandran, KV. Ashalatha, Gopalakrishna K. Naidu. (14/7/2015). Yield loss Modeling for late Leafspot and Rust in Groundnut.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10030
dc.description.abstractLate leaf spot and rust diseases occur together and cause considerable yield loss in groundnut. Cultivation of resistant varieties is the best strategy to stabilize productivity under disease epidemics. Several varieties resistant or moderately resistant to LLS and rust have been developed in groundnut, but most of them differ in yield loss even at the same level of disease due to complex interrelationships between disease and yield loss. Crop loss models have been employed to gain insight into these relations and to plan sound breeding strategies. In the present study, different empirical models were tested for their explanatory value for yield loss among 10 groundnut genotypes with varying level of resistance to late !eafspot and/or rust. Towards yield loss modeling, disease severity at different growth stages and physiological traits viz., leaf area index (LAI), harvest index (HI), healthy leaf area duration (HAD), crop and pod growth rates(CGR and PGR) and partitioning coefficient (PC) were considered as independent variables, while yield loss as dependent variable in regression models. Single pOint models based on disease did not explain the variation in loss completely, but revealed pOd fill ing as the critical stage in determining yield loss. Multiple point models using disease at different stages marginally improved the explanatory value; Inclusion of physiological traits in stepwise regression models improved the R2 considerably, revealing their relevance to yield loss. Yield loss varied significantly among the genotypes resistant to both LLS and rust (9-17%), moderately resistant to LLS or rust (18-26%) and susceptible to LLS and rust (30-42%). Resistant genotype, GPBD-4 had high yield potential with minimum yield reduction due to Its high partitioning efficiency and pod growth rate. Though highly susceptible, TAG-24 showed tolerance by early cessation of vegetative growth and efficient translocation of photosynthates to pOds leading to high harvest index.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.rightsCC-BY-NC-4.0en_US
dc.subjectpests and diseaseen_US
dc.subjectgroundnuten_US
dc.subjectyield lossen_US
dc.subjectleafspoten_US
dc.subjectGroundnuten_US
dc.titleYield loss Modeling for late Leafspot and Rust in Groundnuten_US
dc.typeConference Paperen_US
dcterms.available2015-07-14en_US
cg.subject.agrovocplant breedingen_US
cg.subject.agrovocrust diseasesen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerUniversity of Agricultural Sciences Dharwad - UASD Dharwaden_US
cg.contributor.crpCGIAR Research Program on Grain Legumes - GLen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.coverage.regionGlobalen_US
cg.contactB.N.Motagi@cgiar.orgen_US
dc.identifier.statusOpen accessen_US


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