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

Highlights

• Increasing cocoa yields per unit area is a means to meet growing demand, secure food security& reduce pressure on forest.

• We quantified cocoa yield gap by comparing water-limited, attainable yield in high- & low-input systems with farmer yields.

• Considerable yield gaps on all cocoa farms but water-limited yield gaps were much larger than in high- and low-input systems.

• Relative yield gaps are substantial, and driven mostly by management practices, cocoa tree density & black pod control.

• Improved agronomic practices offer opportunities to substantially increase production of present-day cocoa plantations.

Abstract

CONTEXT

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(Y_E), iii. attainable yield in low-input systems(Y_F)) 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 (YG_W) were very large with a mean absolute gap of 4577 kg/ha representing 86% of Yw. Attainable yield gap in high-input (YG_E) was lower with mean absolute gap of 1930 kg/ha representing 73% of Y_E. The yield gap in low-input (YG_F) was even lower with mean absolute gap of 469 kg/ha representing 42% of Y_F. Mixed-effects models showed that, absolute YG_W 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 YG_W. These same factors and cocoa planting density explained 28% of variability in absolute YG_E. Regardless of climate, absolute YG_F and relative YG_W, YG_E and YG_F were reduced by increasing cocoa planting density and application of fungicide against black pod. The models explained 25% of the variability in absolute YG_F, and 33%, 33% and 25% in relative YG_W, YG_E and YG_F respectively.

In conclusion, climate determined absolute YG_W in Ghana whilst absolute YG_E were determined by both climate and management. In contrast, absolute YG_F and relative YG_W, YG_E and YG_F 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.