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dc.contributor.authorAsante, Paulina A.en_US
dc.contributor.authorRahn, Ericen_US
dc.contributor.authorZuidema, Pieteren_US
dc.contributor.authorRozendaal, Danae M.A.en_US
dc.contributor.authorvan der Baan, Maris E.G.en_US
dc.contributor.authorLäderach, Peteren_US
dc.contributor.authorAsare, Richarden_US
dc.contributor.authorCryer, Nicholasen_US
dc.contributor.authorAnten, Niels P.R.en_US
dc.date.accessioned2022-08-03T08:33:05Zen_US
dc.date.available2022-08-03T08:33:05Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/120413en_US
dc.titleThe cocoa yield gap in Ghana: A quantification and an analysis of factors that could narrow the gapen_US
cg.authorship.typesCGIAR and advanced research instituteen_US
dcterms.abstractCONTEXT: Global cocoa production is largely concentrated in West Africa where over 70% of cocoa is produced. Here, cocoa farming is largely a rain-fed, low-input system with low average yields, which are expected to decline with climate change. With increasing demand, there is a need to evaluate opportunities to increase production whilst avoiding deforestation and expansion to croplands. Thus, it is important to know how much additional cocoa can be produced on existing farmland, and what factors determine this potential for increased yield. OBJECTIVE: The objective was to quantify the cocoa yield gap in Ghana and identify the factors that can contribute to narrowing the gap. METHODS: We calculated the cocoa yield gap as the difference between potential yield (i. water-limited potential (Yw) quantified using a crop model, ii. attainable yield in high-input systems(YE), iii. attainable yield in lowinput systems(YF)) and actual farmer yield. Both absolute and relative yield gaps were calculated. We then related each yield gap (absolute & relative) as a function of environment and management variables using mixedeffects models. RESULTS AND CONCLUSIONS: There were considerable yield gaps on all cocoa farms. Maximum water-limited yield gaps (YGW) were very large with a mean absolute gap of 4577 kg/ha representing 86% of Yw. Attainable yield gap in high-input (YGE) was lower with mean absolute gap of 1930 kg/ha representing 73% of YE. The yield gap in low-input (YGF) was even lower with mean absolute gap of 469 kg/ha representing 42% of YF. Mixedeffects models showed that, absolute YGW were larger at sites with higher precipitation in the minor wet and minimum temperature in the minor dry season explaining 22% of the variability in YGW. These same factors and cocoa planting density explained 28% of variability in absolute YGE. Regardless of climate, absolute YGF and relative YGW, YGE and YGF were reduced by increasing cocoa planting density and application of fungicide against black pod. The models explained 25% of the variability in absolute YGF, and 33%, 33% and 25% in relative YGW, YGE and YGF respectively. In conclusion, climate determined absolute YGW in Ghana whilst absolute YGE were determined by both climate and management. In contrast, absolute YGF and relative YGW, YGE and YGF can be reduced by agronomic management practices. SIGNIFICANCE: Our study is one of the first to quantify cocoa yield gaps in West Africa and shows that these can be closed by improved agronomic practices.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceScientistsen_US
dcterms.bibliographicCitationAsante, P.A.; Rahn, E.; Zuidema, P.; Rozendaal, D.M.A.; van der Baan, M.E.G.; Läderach, P.; Asare, R.; Cryer, N.; Anten, N.P.R. (2022) The cocoa yield gap in Ghana: A quantification and an analysis of factors that could narrow the gap. Agricultural Systems 201:103473. 13 p. ISSN: 0308-521Xen_US
dcterms.extent13 p.en_US
dcterms.issued2022-08en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherElsevier BVen_US
dcterms.subjectcrop yielden_US
dcterms.subjectyield gapen_US
dcterms.subjectagricultural practicesen_US
dcterms.subjectrendimiento de cultivosen_US
dcterms.subjectdiferencias de rendimientoen_US
dcterms.subjectprácticas agrícolasen_US
dcterms.typeJournal Articleen_US
cg.contributor.affiliationWageningen University & Researchen_US
cg.contributor.affiliationInternational Center for Tropical Agricultureen_US
cg.contributor.affiliationInternational Institute of Tropical Agricultureen_US
cg.contributor.affiliationMondelēz UK R&D Ltd.en_US
cg.identifier.doihttps://doi.org/10.1016/j.agsy.2022.103473en_US
cg.isijournalISI Journalen_US
cg.coverage.regionAfricaen_US
cg.coverage.regionWestern Africaen_US
cg.coverage.countryGhanaen_US
cg.subject.alliancebiovciatCACAOen_US
cg.subject.alliancebiovciatMODELINGen_US
cg.subject.alliancebiovciatSMALLHOLDER FARMERSen_US
cg.subject.alliancebiovciatTREE CROPSen_US
cg.coverage.iso3166-alpha2GHen_US
cg.subject.impactAreaClimate adaptation and mitigationen_US
cg.subject.sdgSDG 13 - Climate actionen_US
cg.creator.identifierEric Rahn: 0000-0001-6280-7430en_US
cg.creator.identifierPeter Läderach: 0000-0001-8708-6318en_US
cg.creator.identifierRichard Asare: 0000-0001-6798-7821en_US
cg.contributor.donorNorwegian Agency for Development Cooperationen_US
cg.reviewStatusPeer Reviewen_US
cg.journalAgricultural Systemsen_US
cg.issn0308-521Xen_US
cg.volume201en_US


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