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

Mulc lchin ing g for or so soil il rest stor oration ation an and cr d crop op produ ducti ctivity vity in in agricu icultu ltural ral sy syst stems ms of aso Bu Burkin ina a Fas 03-02-2015 BSc thesis Plant Sciences (YPS-82318) Name: Philippe Belliard (Reg. num.: 931021047060) Supervisors: Georges Félix, Johannes Scholberg Department: Farming Systems Ecology

tents Con ontents I. Introduction II. Materials and Methods III. Results IV. Conclusion

I. Intr trod oduction uction • Soil degradation - 3 main causes: overgrazing, 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 www.vega.isara.fr infiltration/retention, soil biology - Mulching: protection against erosion and run-off, enhanced soil moisture … www.treepower.org www.fao.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) of grain yield

II. Mate aterials ials an and Meth thod ods • Zone of study 200 16.0 180 14.0 Days of rain 160 Monthly rainfall (mm) Rainfall 12.0 140 Days of rain 10.0 120 100 8.0 80 6.0 60 4.0 40 2.0 20 0 0.0

II. Mate aterials ials an and Meth thod ods • Zone of study 200 16.0 180 14.0 Days of rain 160 Monthly rainfall (mm) Rainfall 12.0 140 Days of rain 10.0 120 100 8.0 80 6.0 60 4.0 40 2.0 20 0 0.0

• Experimental setup Total available biomass ( P) - Total available Piliostigma above-ground biomass (leaf litter) - control (M0), average mulch (M1), double mulch (M2) 0% P 100% P 200% P M0 M1 M2 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

sults III. . Re Result • 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 only at 32, 46 and 88 days after sowing (DAS) (P<0.05).

sults III. . Re Result Average plant height over time 300 • Sorghum vegetative growth:Average plant height M0 250 – M2 > M0 (P<0.005) and M2 > M1 (P≤0.01) at all five M1 measuring dates (Mann-Whitney U-test) M2 200 – M1 > M0 at all five measuring dates, statistically significant Plant height (cm) only at 32, 46 and 88 days after sowing (DAS) (P<0.05). 150 100 50 0 18 32 46 60 74 88 102 Days after sowing (DAS)

• 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 only at 32 and 46 DAS (P<0.05).

• Sorghum vegetative growth:Average leaf number Average number of leaves per plant over time – M2 > M0 (P<0.005) and M2 > M1 (P<0.005) at all five 16 measuring dates. M0 14 – M1 > M0 at all five measuring dates, statistically significant M1 12 M2 only at 32 and 46 DAS (P<0.05). Number of leaves 10 8 6 4 2 0 18 32 46 60 74 88 102 Days after sowing

• 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 • Sorghum harvest index – M2 > M1 (P<0.05) – M2 ~ M1 – M2 ~ M0 but not significant – M2 ~ M0 – M1 ~ M0 but not significant – M1 ~ M0 No significant differences 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 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: R 2 adj = 0,66 – Quadratic model: R 2 adj = 0,73 Correlation height/panicle weight 0.1 Linear y = 0.0003x - 0.0305 0.08 R² = 0.6613 Average fresh panicle weight (kg) Polynomial 0.06 y = 1E-06x 2 - 0.0003x + 0.018 R² = 0.7336 0.04 0.02 0 0 50 100 150 200 250 300 350 -0.02 Average height (cm)

• Sorghum panicle yield proxies: average stem diameter per planting hole – Linear model: R 2 adj = 0,57 – Quadratic model: R 2 adj = 0,59 Correlation stem diameter/panicle weight 0.09 Linear 0.08 Average fresh panicle weight (kg) y = 0.0359x - 0.017 R² = 0.5733 0.07 Polynomial 0.06 y = 0.0149x 2 + 0.0022x + 0.0004 R² = 0.5939 0.05 0.04 0.03 0.02 0.01 0 0 0.5 1 1.5 2 2.5 -0.01 Average stem diameter (cm)

ons IV. . Con onclusi lusion • 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.

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