Mulc lchin ing g for or so soil il rest stor oration ation - - PowerPoint PPT Presentation

Mulc lchin ing g for

• r so

soil il rest stor

• ration

ation an and cr d crop

• p

produ ducti ctivity vity in in agricu icultu ltural ral sy syst stems ms of Bu Burkin ina a Fas aso

03-02-2015

BSc thesis Plant Sciences (YPS-82318) Name: Philippe Belliard (Reg. num.: 931021047060) Supervisors: Georges Félix, Johannes Scholberg Department: Farming Systems Ecology

Con

• ntents

tents

I. Introduction

• II. Materials and Methods
• III. Results
• IV. Conclusion

• I. Intr

trod

• duction

uction

• Soil degradation
• 3 main causes:
• vergrazing,

deforestation , agricultural activities

• >24% of agricultural

land worldwide moderately degraded: >6% severely degraded

• Can lead to

desertification

• ±15% global degraded

area located in Sub- Saharan Africa

• Soil restoration
• Conservation Agriculture: reduced

tillage, crop diversification in space/time, soil cover

• Key role of organic matter: nutrient

cycling, CEC, water infiltration/retention, soil biology

• Mulching: protection against erosion

and run-off, enhanced soil moisture…

www.fao.org www.vega.isara.fr www.treepower.org

• Organic matter amendments
• progressive soil ‘aggradation’
• crop residues, manure

but…

• Residue availability: low productivity,

competing claims → need for alternative sources

• Piliostigma reticulatum
• widespread throughout the Sahel
• common in crop fields
• multipurpose,
• high availability, minimal competing claims

→potential for use as mulch

source: Georges Félix

• WASSA project
• Enhance Piliostigma resource-use efficiency and

management

• Quantify effects of amendment application on crops

and on soil properties

• Analyse community-level trade-offs
• Optimize soil restoration, improve livelihoods

Lahmar et al., 2012

• This thesis
• Effects of Piliostigma mulch on crop growth and yield
• Previous experiments show yield increases due to mulch
• Locally available biomass?

Does Piliostigma-based mulch from in situ vegetation result in increased sorghum and cowpea yield?

• Sorghum vegetative growth
• Sorghum grain and dry straw yield, 1000-grain weight,

harvest index

• Cowpea grain yield, 1000-grain weight
• Sorghum non-destructive vegetative predictors (proxies)
• f grain yield

• II. Mate

aterials ials an and Meth thod

• ds
• Zone of study

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 20 40 60 80 100 120 140 160 180 200 Days of rain Monthly rainfall (mm)

Days of rain Rainfall

• II. Mate

aterials ials an and Meth thod

• ds
• Zone of study

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 20 40 60 80 100 120 140 160 180 200 Days of rain Monthly rainfall (mm)

Days of rain Rainfall

• Experimental setup
• Total available Piliostigma

above-ground biomass (leaf litter)

• control (M0), average mulch

(M1), double mulch (M2)

0% P

M0

100% P

M1

200% P

M2

Total available biomass (P)

source: Marcel Ouédraogo

• Measurements
• Sorghum vegetative growth: plant height,

leaf number. Five biweekly measurements starting at 32 days after sowing (1)

• Sorghum yield:
• in-field sampling
• subsamples
• Cowpea yield:
• on farm
• subsamples

(1) Study conducted by Marcel Ouédraogo

• Proxies: none-destructive

measurements for yield prediction based on: mean plant height, stem diameter and fresh panicle yield per planting hole

III. . Re Result sults

• Sorghum vegetative growth:Average plant height

– M2 > M0 (P<0.005) and M2 > M1 (P≤0.01) at all five measuring dates (Mann-Whitney U-test) – M1 > M0 at all five measuring dates, statistically significant

• nly at 32, 46 and 88 days after sowing (DAS) (P<0.05).

III. . Re Result sults

• Sorghum vegetative growth:Average plant height

– M2 > M0 (P<0.005) and M2 > M1 (P≤0.01) at all five measuring dates (Mann-Whitney U-test) – M1 > M0 at all five measuring dates, statistically significant

• nly at 32, 46 and 88 days after sowing (DAS) (P<0.05).

50 100 150 200 250 300 18 32 46 60 74 88 102

Plant height (cm)

Days after sowing (DAS)

Average plant height over time

M0 M1 M2

• Sorghum vegetative growth:Average leaf number

– M2 > M0 (P<0.005) and M2 > M1 (P<0.005) at all five measuring dates. – M1 > M0 at all five measuring dates, statistically significant

• nly at 32 and 46 DAS (P<0.05).

• Sorghum vegetative growth:Average leaf number

– M2 > M0 (P<0.005) and M2 > M1 (P<0.005) at all five measuring dates. – M1 > M0 at all five measuring dates, statistically significant

• nly at 32 and 46 DAS (P<0.05).

2 4 6 8 10 12 14 16 18 32 46 60 74 88 102

Number of leaves Days after sowing

Average number of leaves per plant over time

M0 M1 M2

• Sorghum grain yield

– M2 > M0 by 49% and M2 > M1 by 33% (P<0.005) (paired t-test) – M1>M0 by 12% (P<0.05)

• Sorghum straw yield

– Numerically M2 > M1 > M0 but no significant differences

Different letters indicate significant differences with lower case letters referring to mean separation for grain yields while upper case letters refer to mean separation for straw yields (P<0,05).

• Sorghum 1000-grain weight

– M2 > M1 (P<0.05) – M2 ~ M0 but not significant – M1 ~ M0 but not significant

Treatment Difference M0 M1 M2 M1-M0 M2-M1 M2-M0 Sorghum 1000 grain weight Average 22,69ab 22,02a 23,70b

• 0,68

*1,68 1,00 Std Error 0,87 0,85 0,82 0,61 0,80 0,65 P-value

• 0,150

0,037 0,085 Harvest index Average 0,265a 0,252a 0,291a

• 0,014

0,039 0,021 Std Error 0,025 0,026 0,020 0,023 0,041 0,030 P-value

• 0,245

0,200 0,247

• Sorghum harvest index

– M2 ~ M1 – M2 ~ M0 – M1 ~ M0 No significant differences

Means followed by the same letter are not statistically different * indicates significant differences at a significance level α=0,05

• Cowpea grain yield

– M2 > M0 by 86% (P<0.05) – M2 > M1 by 51% (P<0.05) – M1 > M0 by 23% (P<0.05)

Different letters indicate significant differences (P<0.05)

• Cowpea 1000-grain weight

– M0 ~ M1 ~ M2 – No significant differences – decreasing tendency due to mulch

Treatment Difference M0 M1 M2 M1-M0 M2-M1 M2-M0 Cowpea 1000 grain weight Average 143.3a 140.0a 139.8a

• 3.333
• 0.167
• 3.500

Std Error 6.3 5.1 4.2 2.591 1.493 3.253 P-value

• 0.125

0.456 0.185

Means followed by the same letter are not statistically different

• Sorghum panicle yield proxies:

average height per planting hole

– Linear model: R2

adj = 0,66

– Quadratic model: R2

adj = 0,73

y = 0.0003x - 0.0305 R² = 0.6613 y = 1E-06x2 - 0.0003x + 0.018 R² = 0.7336

• 0.02

0.02 0.04 0.06 0.08 0.1 50 100 150 200 250 300 350 Average fresh panicle weight (kg) Average height (cm)

Correlation height/panicle weight

Linear Polynomial

• Sorghum panicle yield proxies: average

stem diameter per planting hole

– Linear model: R2

adj = 0,57

– Quadratic model: R2

adj = 0,59

y = 0.0359x - 0.017 R² = 0.5733 y = 0.0149x2 + 0.0022x + 0.0004 R² = 0.5939

• 0.01

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.5 1 1.5 2 2.5 Average fresh panicle weight (kg) Average stem diameter (cm)

Correlation stem diameter/panicle weight

Linear Polynomial

IV. . Con

• nclusi

lusion

• ns
• Clear positive effects on crop growth and yield of Piliostigma mulch at rates

corresponding to in situ on-farm availability

• Significant increases of:

– Sorghum vegetative growth: plant height and number of leaves – Sorghum grain yield – Cowpea grain yield

• Sorghum straw yield: evident increase due to mulch application, but differences

not significant.

• Sorghum and cowpea 1000-grain weight: results inconclusive, showing tendencies

but no clear effect of mulching treatments

• Sorghum harvest index: seemed unaffected by mulching, no clear and/or

consistent trend.

• No adequate yield proxies found in vegetative measurements for sorghum
• Further research :

– monitor medium to long-term effects of mulching with Piliostigma – crop-shrub intercropping system designs – assessment of the feasibility and implications of using native woody shrubs at the community-scale.

Than ank you for your at atten tention tion!

Ques estions tions?