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Understanding residue management, soil moisture and maize yield interactions under CA: Initial
evidences from SIMLESA
Isaiah NyagumboGlobal Conservation Agriculture Program
+Team SIMLESA Malawi & Mozambique
1. Introduction
CA and residue cover provision• Provision of permanent residue cover is one of the three principles
upon which Conservation Agriculture is hinged.
• Competition between using residues as cattle feed or leaving it for soil cover provision remains a lively discussion point among CA researchers (Valbuena et al 2012); Baudron, et al., 2014)
• It is recommended farmers provide permanent residue cover and use at least 30% residue cover or 2-3t/ha by time of planting.
• In Malawi the low numbers of livestock make the use of residues for soil cover a relatively easy undertaking.
• In Mozambique despite the low livestock numbers, termites pose a serious threat to residues left in fields especially during the dry winter months.
Crop-livestock competition and implication for CA-based intensification
(Data from Adoption Pathways)
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Av CMP-cum.soil loss (kg/ha)
MR-avg-cum.soil loss (kg/ha)
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Total rainfall = 774 mmTotal Erosivity = 9647 J/m2
Total rainfall = 481 mmTotal Erosivity = 9694 J/m2
Total rainfall = 957 mmTotal Erosivity = 13 919 J/m2
Cumulative soil loss (kg/ha) at Hatcliffe, Har-are
Is Soil Cover important with regards to land degradation?
soil loss target= 3.5t/ha/yr
Source: Nyagumbo (2011), WCCA, Brisbane paper
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Rainfall (mm)
Av CMP-cum.runoff(mm)
Av-MR-cum.runoff(mm)
Error bars denote +/- SE of mean
Effects of CA and Conventional Mouldboard Ploughing on cumulative runoff in 3 consecutive seasons at Hatcliffe
Total seasonal run-off amounted to 7.4,16 and 8.1 % of seasonal rainfall for CMP compared to 0.5, 0.8 and 0.6 % for CA over the 3 seasons
Total rainfall 774 mm Total rainfall 481 mm Total rainfall 956 mm
How SIMLESA seeks to contribute to SI
Develop productive, resilient & sustainable CA based maize-legume intensification systems across the major agro-ecologies in 5 ESA countries
CA as a set of technologies to • To increase maize and legume
productivity by 30%– through improved maize, legume varieties,
forages and associated management practices, – with adoption enabled and motivated through the
development of markets and value chains• To reduce downside yield risks by 30% • To benefit at about 650,000 farm
households (until 2020)
Sustainable Intensification
Sustainability•Conserve the natural resource base (Godfray et al., 2010; Pretty et al., 2011; Tilman et al., 2011)
•Ecologically and technically sound eg soil quality degradation through erosion, fertility decline
•Socially and Culturally acceptable ( Do the technologies fit local farming systems?)
•Economically viable (does it make economic sense?)
Intensification•Increased yield or outputs per unit area/inputs (Enhance productivity)•Diversification from maize for diet diversification and improved incomes•Integration of crops & livestock•Improved resilience to market shocks and climate risks •Improved efficiency per unit input eg water, labour, capital, inputs
Improved food security and livelihoods
30% yield risk reduction+ 30% productivity increase among 650000 farms by 2023
Obj 1: Enhanced the understanding of CA-based intensification options for maize-legume production systems, value
chains and impact pathways
Obj 2: Adaptation of productive, CA-based intensification options for sustainable smallholder maize-legume production systems
Obj 3: Increased range of maize, legume and fodder/forage varieties available for smallholders
Typologies & farmscale
studies
Objective 4: Outscaling & Innovation Systems
•Variety preferences•Value chains•Markets
CA meta-analysis
Varieties for CA
Smart sequencing seed road map; business models
Integration
intensification
impact
SIMLESA-2: 2014-18
Which countries did we target?
Major maize growing agro-ecologies across 5 core countries:•Ethiopia•Kenya•Tanzania •Malawi•Mozambique
Plus lean activities in 3 spillover countries
•Botswana•Rwanda•Uganda
SIMLESA strategy
Community awareness meetings
Farmer consultations and agreement on treatmentsIdentification of 6 host farmers per community
On-station trials:
Exploratory on-farm trials establishment and monitoring:
Outscaling activities through IPs and partnerships
Farmer field days
2. Study Objectives
This study sought to
• Understand and compare residue management practices on SIMLESA on-farm sites in Malawi and Mozambique
• Evaluate residue and nitrogen application rates effects on maize yields.
• Explore linkages between residue management, soil moisture and maize yield in CA
3. Methods
How was this done?1. Physical assessments of residue application rates
on on-farm trial sites in different agro-ecologies of Malawi and Mozambique and % cover estimation using photo comparison method (Shelton and Jasa, 1995) at the on-set of the cropping season.
2. Analysis of seasonal maize yields from residue*nitrogen on-station trial at Chitala, Malawi from 3 seasons: 2011/2, 2012/13 and 2013/14.
4. Some key findings
Residue management practices
What is the amount of residue leftin the field?
Established relationship between maize residue rates and estimated % cover using data from, Malawi and
Mozambique
Residue cover application is a challenge in termite prone and crop-livestock environments (eg Mw vs Mz)
Residue application well above 3t/ha in environments with no livestock, but well below recommendations in livestock and termite infested environments!
Mitundu mchinji kasungu Salima Balaka Ntcheu Manica SussundengaMalawi-Mid-altitude Malawi-lowlands Mozambique-Central
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(t/h
a)Residue cover application is a challenge in termite prone and
crop-livestock environments (eg Mw vs Mz)Dec 2014
Residue /yield relationships by agro-ecology in Malawi
• R
•Could simply be higher biomass higher yield scenario or Indeed•Increased residues result in higher yields ( weed suppression, moisture conservation etc)
Residue-yield relationships in different mid-alt districts, Malawi
•Well drained soil•Medium to heavy texture•Low incidence of pests and leaf diseases=> Residue increase pays
•Well drained soil•Medium to heavy texture•high incidence of pests and leaf diseases=> Yield loss penalties for using residues
•Poor drainage•Coarse texture •high incidence of pests and leaf diseases=> Yield loss penalties for using residues
Do on-station trial results suggest otherwise.....?
18-Nov 18-Dec 17-Jan 16-Feb 18-Mar 17-Apr0
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643.4 mm
771.4 mm
2011/12 2012/13 2013/14
Time
Daily
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ve ra
infa
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Cummulative rainfall at Chitala, Malawi over 3 seasons 2011/12 to 2013/14
APSIM model suggests residues contribute to some significant N-lock up (>10%)
N-lock-up
Maize grain yields over 3 seasons under different residue and N rates at Chitala, Malawi
N.B. Significant yield increases from CA only observed in the third season!
Residue and N rates effects on maize yields over two seasons at Chitala,
Malawi
•N applications significant right from the beginning!•Some N-lock up apparent in no N situations when residue rates increase from 0 to 2t/ha reduces with time!
Optimum yields seem to feature at 4-5 t/ha irrespective of N fert rate!
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f(x) = − 120.369318181818 x² + 1119.48863636364 x + 5950.04545454545R² = 0.952014888733051
f(x) = − 42.3579545454545 x² + 397.365909090909 x + 5879.73636363636R² = 0.669510045837806f(x) = − 95.4034090909091 x² + 906.356818181818 x + 4506.97272727273R² = 0.953351002088398
f(x) = − 39.3125 x² + 461.375 x + 2619.5R² = 0.80742719510821
0 Polynomial (0) 30 Polynomial (30)
Residue application rate (t/ha)
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ze g
rain
yie
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g/ha
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Optimum residue rate?
How is CA and residues impacting on soil
moisture.....?
Measured soil moisture effects in lowlands and Mid-altitude areas of
Malawi in Feb 2013
N.B CA techniques consistently portray higher moisture status!
Residues effectively enhance water infiltration and minimize run-off!
N.B Pictures taken from Ntcheu 2012!
...and similar effects in Mozambique(Angonia, March 2012)
5. Lessons learnt
Key Emerging lessons• There are major differences in farmers capacity to apply
recommended residues rates in different agro-ecologies, attributed mostly to livestock densities and termite activity in Southern Africa and dependent on local agro-ecological conditions hence
– Farmers in Mozambique have residue cover levels below the recommended 3t/ha while those in Malawi are way above this threshold after 3 seasons of CA!
– Low rainfall areas also suffer more difficulties in meeting recommended residue application rates eg Balaka
.........Key Emerging lessonsApparently farmers site residue application/ importation
as one of the most labour demanding tasks in CA
• Results suggest increased residue application rates may be beneficial to yields on well drained soils but counterproductive in waterlogged conditions , in the presence of maize leaf diseases and pests.
• Optimum application rates however could lie between 4-5 t/ha ( still to be verified further).
• Advantage of CA in soil moisture improvement is apparent.
Acknowledgements• NARS (Mozambique, Malawi)• ACIAR • CIMMYT • QAAFI
• Farmers
Thank you!!