Show simple item record

The cocoa yield gap in Ghana: a quantification and an analysis of factors that could narrow the gap

dc.contributor.authorAsante, P.A.
dc.contributor.authorRahn, E.
dc.contributor.authorZuidema, P.A.
dc.contributor.authorRozendaal, D.M.A.
dc.contributor.authorvan der Baan, M.E.G.
dc.contributor.authorLaderach, P.
dc.contributor.authorAsare, R.
dc.contributor.authorCryer, N.
dc.contributor.authorAnten, N.P.R.
dc.date.accessioned2022-09-14T09:34:21Z
dc.date.available2022-09-14T09:34:21Z
dc.date.issued2022-08
dc.identifier.citationAsante, P.A., Rahn, E., Zuidema, P.A., Rozendaal, D.M.A., van der Baan, M.E.G., Läderach, P., ... & 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, 1-13.
dc.identifier.issn0308-521X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7744
dc.description.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 low-input 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 mixed-effects 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. Mixed-effects 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.
dc.description.sponsorshipNorwegian Agency for Development Cooperation
dc.format.extent1-13
dc.language.isoen
dc.subjectCocoa
dc.subjectTheobroma Cacao
dc.subjectYields
dc.subjectSpacing
dc.subjectGhana
dc.titleThe cocoa yield gap in Ghana: a quantification and an analysis of factors that could narrow the gap
dc.typeJournal Article
cg.contributor.affiliationWageningen University and Research Centre
cg.contributor.affiliationInternational Center for Tropical Agriculture
cg.contributor.affiliationAlliance of Bioversity International and CIAT
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationMondelez UK R&D Ltd
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryGhana
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeNatural Resource Management
cg.identifier.bibtexciteidASANTE:2022
cg.isijournalISI Journal
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectAgronomy
cg.iitasubjectBiodiversity
cg.iitasubjectClimate Change
cg.iitasubjectCocoa
cg.iitasubjectDisease Control
cg.iitasubjectFarming Systems
cg.iitasubjectLivelihoods
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.journalAgricultural Systems
cg.notesOpen Access Article; Published online: 28 Jul 2022
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1016/j.agsy.2022.103473
cg.iitaauthor.identifierRichard Asare: 0000-0001-6798-7821
cg.futureupdate.requiredNo
cg.identifier.issue103473
cg.identifier.volume201


Files in this item

Thumbnail
Name:
U22ArtAsanteCocoaInthomNodev.pdf
Size:
4.747Mb
Format:
PDF
Description:
Journal Article
View/Open

This item appears in the following Collection(s)

Show simple item record