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dc.contributor.authorOloo, Richard D.en_US
dc.contributor.authorMrode, Raphael A.en_US
dc.contributor.authorBennewitz, Jörnen_US
dc.contributor.authorEkine-Dzivenu, Chinyere C.en_US
dc.contributor.authorOjango, Julie M.K.en_US
dc.contributor.authorGebreyohanes, Gebregziabheren_US
dc.contributor.authorOkeyo Mwai, Allyen_US
dc.contributor.authorChagunda, Mizeck G.G.en_US
dc.date.accessioned2023-12-28T08:52:54Zen_US
dc.date.available2023-12-28T08:52:54Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/135974en_US
dc.titlePotential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yielden_US
cg.authorship.typesCGIAR and advanced research instituteen_US
dcterms.abstractIntroduction: Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). While indicators of general resilience have been proposed and evaluated in other regions, their applicability in SSA remains unexplored. This study sought to test the viability of utilizing log-transformed variance (LnVar), autocorrelation (rauto), and skewness (Skew) of deviations in milk yield as indicators of general resilience of dairy cows performing in the tropical environment of Kenya. Methods: Test-day milk yield records of 2,670 first-parity cows performing in three distinct agroecological zones of Kenya were used. To predict expected milk yield, quantile regression was used to model lactation curve for each cow. Subsequently, resilience indicators were defined based on actual and standardized deviations of observed milk yield from the expected milk yield. The genetic parameters of these indicators were estimated, and their associations with longevity and average test-day milk yield were examined. Results: All indicators were heritable except skewness of actual and standardized deviation. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 ± 0.04 and 0.17 ± 0.04, respectively. Auto-correlation of actual (rauto1) and standardized (rauto2) deviations had heritabilities of 0.05 ± 0.03 and 0.07 ± 0.03, respectively. Weak to moderate genetic correlations were observed among resilience indicators. Both rauto and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield. LnVar1 and LnVar2 were genetically associated with better longevity (rg = −0.47 ± 0.26 and −0.49 ± 0.26, respectively). Whereas LnVar1 suggested that resilient animals produce lower average test-day milk yield, LnVar2 revealed a genetic association between resilience and higher average test-day milk yield. Discussion: Log transformed variance of deviations in milk yield holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be employed in defining resilience indicators because the resultant indicator does not inaccurately infer that low-producing animals are inherently resilient. This study offers an opportunity for enhancing the productivity of dairy cattle performing in SSA through selective breeding for resilience to environmental stressors.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceCGIARen_US
dcterms.audienceDonorsen_US
dcterms.audienceScientistsen_US
dcterms.available2023-12-15en_US
dcterms.bibliographicCitationOloo, R.D., Mrode, R., Bennewitz, J., Ekine-Dzivenu, C.C., Ojango, J.M.K., Gebreyohanes, G., Mwai, O.A. and Chagunda, M.G.G. 2023. Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield. Frontiers in Genetics 14:1208158.en_US
dcterms.issued2023-12-15en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.subjectdairyingen_US
dcterms.subjectcattleen_US
dcterms.subjectmilk yielden_US
dcterms.subjectenvironmenten_US
dcterms.subjectresilienceen_US
dcterms.typeJournal Articleen_US
cg.subject.ilriCATTLEen_US
cg.subject.ilriDAIRYINGen_US
cg.subject.ilriENVIRONMENTen_US
cg.subject.ilriRESILIENCEen_US
cg.contributor.affiliationUniversity of Hohenheimen_US
cg.contributor.affiliationInternational Livestock Research Instituteen_US
cg.contributor.affiliationScotland's Rural Collegeen_US
cg.identifier.doihttps://dx.doi.org/10.3389/fgene.2023.1208158en_US
cg.isijournalISI Journalen_US
cg.coverage.regionSub-Saharan Africaen_US
cg.subject.impactAreaPoverty reduction, livelihoods and jobsen_US
cg.creator.identifierRaphael Mrode: 0000-0003-1964-5653en_US
cg.creator.identifierRichard Dooso Oloo: 0000-0002-6004-3729en_US
cg.creator.identifierOjango J.M.K.: 0000-0003-0224-5370en_US
cg.creator.identifierAlly Okeyo Mwai: 0000-0003-2379-7801en_US
cg.creator.identifierGebregziabher Gebreyohanes: 0009-0001-5042-2848en_US
cg.contributor.donorFederal Ministry for Economic Cooperation and Development, Germanyen_US
cg.contributor.donorBill & Melinda Gates Foundationen_US
cg.reviewStatusPeer Reviewen_US
cg.howPublishedFormally Publisheden_US
cg.journalFrontiers in Geneticsen_US
cg.issn1664-8021en_US
cg.subject.actionAreaResilient Agrifood Systemsen_US
cg.contributor.initiativeSustainable Animal Productivityen_US


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