Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield

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cg.authorship.typesCGIAR and advanced research instituteen
cg.contributor.affiliationUniversity of Hohenheimen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationScotland's Rural Collegeen
cg.contributor.donorFederal Ministry for Economic Cooperation and Development, Germanyen
cg.contributor.donorBill & Melinda Gates Foundationen
cg.contributor.donorCGIAR Trust Funden
cg.contributor.initiativeSustainable Animal Productivity
cg.coverage.regionSub-Saharan Africa
cg.creator.identifierRichard Dooso Oloo: 0000-0002-6004-3729
cg.creator.identifierRaphael Mrode: 0000-0003-1964-5653
cg.creator.identifierChinyere Ekine-Dzivenu: 0000-0002-8526-435X
cg.creator.identifierOjango J.M.K.: 0000-0003-0224-5370
cg.creator.identifierGebregziabher Gebreyohanes: 0009-0001-5042-2848
cg.creator.identifierAlly Okeyo Mwai: 0000-0003-2379-7801
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.3389/fgene.2023.1208158en
cg.isijournalISI Journalen
cg.issn1664-8021en
cg.journalFrontiers in Geneticsen
cg.reviewStatusPeer Reviewen
cg.subject.actionAreaResilient Agrifood Systems
cg.subject.ilriCATTLEen
cg.subject.ilriDAIRYINGen
cg.subject.ilriENVIRONMENTen
cg.subject.ilriRESILIENCEen
cg.subject.impactAreaPoverty reduction, livelihoods and jobs
cg.volume14en
dc.contributor.authorOloo, Richard Doosoen
dc.contributor.authorMrode, Raphael A.en
dc.contributor.authorBennewitz, Jörnen
dc.contributor.authorEkine-Dzivenu, Chinyere C.en
dc.contributor.authorOjango, Julie M.K.en
dc.contributor.authorGebreyohanes, Gebregziabheren
dc.contributor.authorOkeyo Mwai, Allyen
dc.contributor.authorChagunda, Mizeck G.G.en
dc.date.accessioned2023-12-28T08:52:54Zen
dc.date.available2023-12-28T08:52:54Zen
dc.identifier.urihttps://hdl.handle.net/10568/135974
dc.titlePotential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yielden
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
dcterms.accessRightsOpen Access
dcterms.audienceCGIARen
dcterms.audienceDonorsen
dcterms.audienceScientistsen
dcterms.available2023-12-15
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
dcterms.issued2023-12-15
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherFrontiers Mediaen
dcterms.subjectdairyingen
dcterms.subjectcattleen
dcterms.subjectmilk yielden
dcterms.subjectenvironmenten
dcterms.subjectresilienceen
dcterms.typeJournal Article

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