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Conservation agriculture and drought-tolerant germplasm: Reaping the benefits of climate-smart agriculture technologies in central Mozambique

Published online by Cambridge University Press:  30 September 2015

Christian Thierfelder*
Affiliation:
CIMMYT, P.O. Box MP 163, Mount Pleasant, Harare, Zimbabwe.
Leonard Rusinamhodzi
Affiliation:
CIMMYT, P.O. Box 1041-00621, ICRAF House, United Nations Avenue, Gigiri, Nairobi, Kenya.
Peter Setimela
Affiliation:
CIMMYT, P.O. Box MP 163, Mount Pleasant, Harare, Zimbabwe.
Forbes Walker
Affiliation:
Department of Biosystems Engineering & Soil Science, University of Tennessee Institute of Agriculture, 2506 E.J. Chapman Drive, Knoxville, TN 37996-4531, USA.
Neal S. Eash
Affiliation:
CIMMYT, P.O. Box 1041-00621, ICRAF House, United Nations Avenue, Gigiri, Nairobi, Kenya.
*
* Corresponding author: c.thierfelder@cgiar.org
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Abstract

Conservation agriculture (CA) based on minimum soil disturbance, crop residue retention and crop rotations is considered as a soil and crop management system that could potentially increase soil quality and mitigate the negative effects of climate variability. When CA is combined with drought-tolerant (DT) maize varieties, farmers can reap the benefits of both—genetic improvement and sustainable land management. New initiatives were started in 2007 in Mozambique to test the two climate-smart agriculture technologies on farmers' fields. Long-term trends showed that direct seeded manual CA treatments outyielded conventional tillage treatments in up to 89% of cases on maize and in 90% of cases on legume in direct yield comparisons. Improved DT maize varieties outyielded the traditional control variety by 26–46% (695–1422 kg ha−1) on different tillage treatment, across sites and season. However a direct interaction between tillage treatment and variety performance could not be established. Maize and legume grain yields on CA plots in this long-term dataset did not increase with increased years of practice due to on-site variability between farmer replicates. It was evident from the farmers' choice that, beside taste and good milling quality, farmers in drought-prone environments considered the potential of a variety to mature faster more important than larger potential yields of long season varieties. Population growth, labor shortage to clear new land areas and limited land resources in future will force farmers to change toward more permanent and sustainable cropping systems and CA is a viable option to improve their food security and livelihoods.

Information

Type
Research Papers
Copyright
Copyright © Cambridge University Press 2015 
Figure 0

Figure 1. Geographic location of all experimental sites in central and northern Mozambique.

Figure 1

Table 1. Geographic location of target communities where maize varieties were evaluated under CA.

Figure 2

Figure 2. Rainfall distribution in four target communities of central and northern Mozambique.

Figure 3

Figure 3. (a–e) Average maize grain yield in five target communities (Lamego (a); Malomwe (b); Nhamizhinga (c); Pumbuto (d); Nzewe (e)) in two conservation agriculture and one conventional crop management systems, 2008–2013. Error bars show the standard error of difference (SED) in a particular year; means followed by the same letter above the bar chart are not significantly different at (P ≤ 0.05) probability level.

Figure 4

Table 2. Output of the GLMM procedures for explaining variability in maize grain yields due to tillage, fertilizer, season, site and crop variety under farmer conditions in central Mozambique.

Figure 5

Figure 4. (a-e) Average cowpea and beans grain yield in five target communities (Lamego (a); Malomwe (b); Nhamizhinga (c); Pumbuto (d); Nzewe (e)) in two conservation agriculture and one conventional crop management systems, 2010–2013. Error bars show the standard error of difference (SED) in a particular year; means followed by the same letter above the bar chart are not significantly different at probability level P ≤ 0.05.

Figure 6

Figure 5. Overall varietal performance in two CA and one conventional agriculture cropping system in Mozambique across sites and years, 2010–2014. The error bar shows the standard error of difference (SED) of varieties across cropping systems; means followed by the same letter above the bar chart are not significantly different at (P ≤ 0.05) probability level.

Figure 7

Figure 6. Yield comparison between different management strategies on maize varieties (a) and legume (b) crops in five target communities of Mozambique 2008–2013. Each dot represents a mean CA yield of farmer replicates in a target community in a particular year plotted against a conventional system. Dots above the 1:1 represent a benefit toward CA, dots below the 1:1 line favors the conventional system in the comparison.

Figure 8

Table 3. Output of the GLMM procedures for explaining variability in legume grain yields due to tillage, season and site under farmer conditions in central Mozambique.

Figure 9

Table 4. Maize traits considered important in maize varieties (in percent).

Figure 10

Table 5. Farmer ratings of maize varieties (in percent) according to different traits.