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Limits of conservation agriculture to overcome low crop yields in sub-Saharan Africa

Abstract

Conservation agriculture (CA) has become a dominant paradigm in scientific and policy thinking about the sustainable intensification of food production in sub-Saharan Africa. Yet claims that CA leads to increasing crop yields in African smallholder farming systems remain controversial. Through a meta-analysis of 933 observations from 16 different countries in sub-Saharan African studies, we show that average yields under CA are only slightly higher than those of conventional tillage systems (3.7% for six major crop species and 4.0% for maize). Larger yield responses for maize result from mulching and crop rotations/intercropping. When CA principles are implemented concomitantly, maize yield increases by 8.4%. The largest yield benefits from CA occur in combination with low rainfall and herbicides. We conclude that although CA may bring soil conservation benefits, it is not a technology for African smallholder farmers to overcome low crop productivity and food insecurity in the short term.

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Fig. 1: Location of the experiments considered in this meta-analysis.
Fig. 2: Effect of CA relative to CT on grain yield for different crop species.
Fig. 3: Effect of CA relative to CT on maize grain yield under different combinations of CA principles.
Fig. 4: Effect of CA relative to CT on crop grain yield in relation to experimental duration.
Fig. 5: Effect of CA relative to CT on crop grain yield as a function of herbicide use in the CA treatment.
Fig. 6: Effect of CA relative to CT on crop grain yield as a function of applied chemical phosphorus fertilizer.
Fig. 7: Effect of CA relative to CT on crop grain yield as a function of average seasonal rainfall at the experimental site.

Data availability

The data used in this study are available from the Dataverse repository at https://doi.org/10.18167/DVN1/DLTQWR.

Code availability

Scripts used in the literature search and statistical analyses are available from the corresponding author on request.

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Acknowledgements

This work was implemented as part of the CGIAR Research Programs on Climate Change, Agriculture and Food Security (CCAFS) and Maize, which are carried out with support from the CGIAR Trust Fund and through bilateral funding agreements. The views expressed in this document cannot be taken to reflect the official opinions of these organizations.

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Contributions

M.C. conceived the project and developed it with A.M.W., R.K and K.N. M.C. and K.N. contributed to the literature research, extracted data from publications and constructed the database. P.L., M.C. and R.K. conducted the analyses. M.C. wrote the manuscript draft and all authors contributed to the interpretation of the results and writing of the final paper.

Corresponding author

Correspondence to Marc Corbeels.

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Extended data

Extended Data Fig. 1 Random-effects model with explanatory covariates.

Results of the random-effects model developed to determine the influence of explanatory covariates on the CA to CT yield ratio.

Extended Data Fig. 2 Effect of CA relative to CT on crop grain yield as a function of soil texture for different regimes of average seasonal rainfall at the experimental site.

a, < 400mm; b, 400–800mm; c) 800–1200m and d) > 1200mm. Values are mean effect sizes and error bars show the 95% CI. The number of observations and total number of studies for each category are shown in parentheses. The mean effect sizes were considered significant if the 95% CI does not include 0. The CA effect on yield is significantly lower on medium-texture soils than on coarse- (P<0.005) and fine-textured soils (P<0.02) under the 800–1200mm rainfall regime, and the effect on coarse-textured soils is significantly higher than on medium- (P<0.05) and fine-textured soils (P<0.01) under the >1200mm rainfall regime, determined via paired Student’s t-tests.

Extended Data Fig. 3 Operational forms of no- and reduced tillage employed by smallholder farmers in sub Saharan Africa.

Different operational forms of no- and reduced tillage employed by smallholder farmers in sub Saharan Africa (source: CIRAD and CIMMYT).

Extended Data Fig. 4 Effect of CA relative to CT on crop grain yield as a function of type of reduced tillage in the CA treatment.

Values are mean effect sizes and error bars show the 95% CI. The number of observations and total number of studies for each category are shown in parentheses. The mean effect sizes were considered significant if the 95% CI does not include 0. The CA effect on yield is significantly higher under no-tillage than under minimum tillage (P<0.005) and basins/permanent beds (P<0.05), determined via paired Student’s t-tests.

Extended Data Fig. 5 Effect of CA relative to CT on crop grain yield as a function of type of field trial.

Values are mean effect sizes and error bars show the 95% CI. The number of observations and total number of studies for each category are shown in parentheses. The mean effect sizes were considered significant if the 95% CI does not include 0. The CA effect on yield is significantly (P<0.05) higher in on-farm trials than on-station trials.

Extended Data Fig. 6 Funnel plot on the marginal deviations from the random-effects model added to the average logarithmic yield ratio for maize (as reference, solid vertical line).

The diagonal lines represent the 95% CI limits around the effect size logratio. Each point represents an observation (n=933), open blue circles from on-farm studies (n=605), open red circles from on-station studies (n=328). Skewness TS is -0.03, P=0.67 (all observations), 0.18, P=0.07 (on-farm observations) and −0.26, P=0.05 (on-station observations).

Extended Data Fig. 7 Boxplots of logarithmic weights by the inverse of variance of the individual observations in the on-farm (n = 605) versus on-station (n = 328) studies.

The inverse variance weight is significantly (P<0.0001) smaller in on-farm studies than in on-station studies (paired Student’s t-test).

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Corbeels, M., Naudin, K., Whitbread, A.M. et al. Limits of conservation agriculture to overcome low crop yields in sub-Saharan Africa. Nat Food 1, 447–454 (2020). https://doi.org/10.1038/s43016-020-0114-x

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