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dc.contributorSingh, Murarien_US
dc.creatorSarker, Ashutoshen_US
dc.date2015-05-12en_US
dc.date.accessioned2017-06-21T16:17:23Z
dc.date.available2017-06-21T16:17:23Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/MiKalFJ2en_US
dc.identifier.citationAshutosh Sarker, Murari Singh. (12/5/2015). Improving breeding efficiency through application of appropriate experimental designs and analysis models: A case of lentil (Lens culinaris Medikus subsp. culinaris) yield trials. Field Crops Research, 179, pp. 26-34.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/7105
dc.description.abstractLentil (Lens culinaris Medikus subsp. culinaris) is an important staple pulse and rich source of protein, especially to the economically resource-poor consumers of the developing world. Experimental and analytic technology and statistical tools are needed to enhance lentil breeding progress. One of the concerns of field experimentation is to design experiments in suitable block designs and model the data to account for any left-over trend in the field layout and for correlations in the plot errors. Elite breeding lines of lentil developed through conventional breeding methods at ICARDA were evaluated in three contrasting environments in northern Syria and Lebanon during 1999–2005. This study examines the data on seed and straw yields from 226 trials conducted in randomized complete block (RCB) and in square lattice designs. Suitable models incorporating blocking structures, linear trends and spatially correlated plot-errors were fitted to the individual datasets. The results indicated that the spatial analysis model, which accounts for the spatial pattern of the field, was better than the commonly used RCB design model. The spatial analyses gave substantial increases in precision of predicted means for the genotypes. An average efficiency of pairwise genotype means comparison over RCB was 141% for seed yield and 158% for straw yield from the trials conducted in incomplete blocks and where found superior to RCB. It also enhanced estimates of broad sense heritability on mean-basis, with an average of 72% for seed and 70% for straw yield under the superior models, compared to 62 and 55% for RCB model, respectively. The percentage genetic gain due to selection at 10% intensity was 26% for seed and 20% for straw yield based on those models, which were 2–3% higher than those from the RCB model. In general, it is recommended to continue the use of incomplete block designs for variety trials in lentils and use the most suitable spatial pattern for statistical analysis to assist field crop breeders to enhance precision in selection of desirable genotypes. These results are consistent with findings of a number of other variety trials in lentil.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevieren_US
dc.rightsCC-BY-4.0en_US
dc.sourceField Crops Research;179,(2015) Pagination 26,34en_US
dc.subjectincomplete block designen_US
dc.subjectLentilen_US
dc.titleImproving breeding efficiency through application of appropriate experimental designs and analysis models: A case of lentil (Lens culinaris Medikus subsp. culinaris) yield trialsen_US
dc.typeJournal Articleen_US
cg.creator.idSarker, Ashutosh: 0000-0002-9074-4876en_US
cg.creator.idSingh, Murari: 0000-0001-5450-0949en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocefficiencyen_US
cg.subject.agrovocgenetic advanceen_US
cg.subject.agrovocspatial analysisen_US
cg.subject.agrovocheritabilityen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes - GLen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectBiometrics and Statistics Sectionen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionWestern Asiaen_US
cg.coverage.countryLBen_US
cg.coverage.countrySYen_US
cg.contactA.SARKER@CGIAR.ORGen_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.fcr.2015.04.007en_US
dc.identifier.statusOpen accessen_US
mel.project.openhttps://mel.cgiar.org/projects/102en_US
mel.impact-factor3.868en_US


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