A Technology Platform for Africa

A Technology Platform for Africa

Creating a common vision of the opportunity: Rationale?

Criteria for relevance/success? Core functions/services? Implementation phases?

ReSAKSS/SAKSS • Policy analysis • Capacity

strengthening

Potted History/Context CGIAR Reform

AU CAADP Planning (-> Implementation)

(NAIPs) Dublin Process

AU (NEPAD, FARA, SROs)

/CGIAR/DP

(G8) New Alliance for FS&N

Country/DPs Private Sector

TPs (CG, AGRA, FARA)

• Roadmap • AU-CGIAR MoU • Science Agenda • G8 Tech. Platform support • Investment Mapping

& Alignment Prototype

(themes, FS, commodities, AEZs, partners, investment, FTE’s, location mapping, bibliography, contextual knowledge)

• CRPs • New commitment

to partnerships • Open access policy

40 African countries (at varying pace)

Global (at varying pace)

3 => 6 => 10 countries (at varying pace)

All SSA Regions and several countries (at varying pace)

• G8 pledges & coordination • National policy reform • Increased private investment • Mutual accountability framework • Focus crops/Yield targets • Technology Platform • Targeted tech. options • Scaled implementation • ICT/Open Data

The Emergence of a Technology Platform (Phase I) NAIPs, CPPs… & other locally-

owned goals/plans

Technology Inventory (structured, open access, knowledgebase (e.g., databases, videos) of technologies and practices; types, benefits, costs, access, sources, service/scaling partners)

Sample Inventory of Technologies (and Practices)

Several existing examples to draw from; varieties, soil fertility, small scale irrigation, etc to be pooled as a core component of the Technology Platform (simple variety example shown)

NAIPs, CPPs… other locally- owned goals/plans


Commodity Prioritization & Productivity Growth Targets Data/tools for prioritizing commodities and setting yield goals

The Emergence of a Technology Platform (Phase I)

G8 New Alliance - Technology Platform National Target Worksheet: Ghanaf(∆nutrem, ∆watrem)

Base year: 2012 Statistics Trials/Fiel Calculated HH Surve Expert/UserCalculated f(∆cal, ∆prot) f(seed sales, share marketed)

Price AreaAv.

YieldAchiev.

Yield

Abs. Yield

Target DIVA GLSS5

Adoption after 10

yearsYield

Increase

National Av. Yield

Level ∆VoP∆Gross return ∆Calorie ∆Protein

Economic Impact

Share to Poor Nutrition

Sustain-ability

Private Sector

contribution OVERALL(P) (A) (Y) (Yp) (Yp) (%) (%) (a10) (∆Y10) (Yt) (∆VoP) (∆GR) (∆Cal) (∆Prot) $/T 1000ha t/ha t/ha % % % % % t/ha $M/year $/ha % Bkcal (1000t) 0.40 0.20 0.15 0.15 0.10 1.00

CerealsMaize 117 991.7 1.70 6.00 253 57 28 57 144.2 4.2 283.90 286.3 54 8,653 230.91 1.75 1.33 5.35 -0.50 1.49 1.84Millet 162 176.6 1.30 2.00 54 28 56 30.2 1.7 10.3 63.6 71 216 6.17 0.06 1.75 0.13 -1.41 0.65 0.25Sorghum 158 252.6 1.30 2.00 54 28 56 30.2 1.7 15.6 61.9 72 340 10.00 0.10 1.77 0.21 -1.04 0.65 0.33Rice (Paddy) 249 181.2 2.40 6.50 171 28 56 95.7 4.7 103.8 572.7 54 1,165 24.97 0.64 1.31 0.72 -0.59 1.35 0.67

Cassava 54 875.0 13.80 48.70 253 36 30 60 61.2 22.2 396.0 452.5 31 8,055 66.51 2.44 0.75 4.91 -0.35 0.70 1.88Cocoyam 122 205.3 6.70 8.00 19 30 60 11.6 7.5 19.5 95.2 26 138 2.40 0.12 0.65 0.08 -0.36 0.33 0.17Yam 122 384.9 15.30 49.00 220 30 60 132.2 35.5 947.4 2461.2 46 7,861 101.19 5.84 1.12 4.79 -0.28 0.60 3.30Sweet potato 416 73.4 8.00 24.00 200 30 60 120.0 17.6 293.1 3993.6 44 648 4.93 1.81 1.08 0.40 -0.29 0.00 0.95Plantain 133 328.0 11 20.00 82 30 60 49.1 16.4 235.2 717.1 26 1,328 14.17 1.45 0.64 0.81 -0.65 0.84 0.82

LegumesCowpeas 685 167.0 1.30 3.10 138 82 28 82 113.5 2.8 168.9 1011.8 64 843 57.67 1.04 1.56 0.60 -1.50 1.40 0.73Soybean 250 76.2 1.50 2.30 53 94 28 94 50.1 2.3 14.3 188.0 52 192 21.78 0.09 1.28 0.18 -1.25 0.00 0.13Groundnut 366 353.4 1.5 2.50 67 28 56 37.3 2.1 72.5 205.1 63 819 37.01 0.45 1.54 0.53 -1.86 2.00 0.49

OthersCocoa 3011 160.0 0.4 1.00 150 57 26 52 78.0 0.7 150.3 939.4 18 207 2.00 0.93 0.45 0.25 -3.59 3.72 0.33Pawpaw 330 1.0 45.00 75.00 67 26 52 34.7 60.6 5.0 5148.0 26 4 0.06 0.03 0.65 0.00 -0.97 0.14 0.01Pineapple 276 12.3 50.00 72.00 44 26 52 22.9 61.4 38.8 3151.7 15 37 0.28 0.24 0.36 0.02 -0.91 0.42 0.08Tomato (rainf) 411 30.0 7.50 15.00 100 26 52 52.0 11.4 48.0 1601.2 28 20 0.94 0.30 0.70 0.01 -1.02 1.07 0.21Tomato (irrig) 411 30.0 30.00 65.00 117 26 52 60.7 48.2 224.2 7472.9 28 93 4.37 1.38 0.70 0.06 -1.02 1.07 0.66Garden eggs 283 3.6 8.00 15.00 88 26 52 45.5 11.6 3.7 1030.1 18 3 0.12 0.02 0.45 0.00 -0.94 0.84 0.04Pepper 686 5.4 6.50 32.30 397 26 52 206.4 19.9 49.7 9203.4 37 200 7.75 0.31 0.91 0.13 -2.05 0.74 0.09

Data sources:

Roots and Tubers

NEW ALLIANCE COMMODITY PRIORTIY RATINGS

National Priority Crops

10 YR TARGETS OUTCOME INDICATORS

Share to

Poorest 40%

PRODUCTION BASEBASELINE

ADOPTIONATTAINABLE

YIELD

Commodity/Value Chain Prioritization:

Ghana example

Spreadsheet model: Populated by for each country based on available secondary data sources. Individual NA teams will adapt as needed and validate or replace data sources

Prioritization criteria and weighting

Average and achievable yield of CAADP priority crops under rainfed conditions: Ghana


Average yield

Achievable yield

Performance Yield Targets

(av/achievable) (% over average)*

(Mt / ha) (Mt / ha) (%) (%) Cereals

Maize 1.7 6.0 28.3 253 Millet 1.3 2.0 65.0 54 Sorghum 1.3 2.0 65.0 54 Rice (Paddy) 2.4 6.5 36.9 171

Roots and Tubers Cassava 13.8 48.7 28.3 253 Cocoyam 6.7 8.0 83.8 19 Yam 15.3 49.0 31.2 220 Sweet potato 8.0 24.0 33.3 200 Plantain 11.0 20.0 55.0 82

Legumes Cowpea 1.3 2.6 50.0 100 Groundnut 1.5 2.3 65.2 53 Soybean 1.5 2.5 60.0 67

Others Cashew 0.8 1.8 44.4 125 Cocoa 0.4 1.0 40.0 150 Pawpaw 45.0 75.0 60.0 67 Pineapple 50.0 72.0 69.4 44 Tomato 7.5 15.0 50.0 100 Garden eggs 8.0 15.0 53.3 88 Pepper 6.5 32.3 20.1 397

Source: Ghana MoFA (2010) and Agriculture in Ghana: Facts and Figures (2011)

Potential Focus Commodities/Value Chains


G 8 Investment Countries

Ethiopia Ghana Tanzania Mozambique Burkina

Faso Cote

D'Ivoire

Cereals Maize Millet Sorghum Rice (Paddy) Teff Wheat Roots and Tubers Cassava Potato Sweet potato Yam Legumes Beans Chickpeas Cowpeas Fababean Groundnut Soybean Others Cocoa Coffee Cotton Sugarcane

Investment/Activity Mapping (past, on-going, planned). Opportunities for coordination, collaboration and co-location (alignment, gaps & duplication)





Locate Investments/Activities (Gates, WB, AGRA, AfDB, USAID,…..)

Investment Locations and Contextual Variables (live link into Funder and HarvestChoice database)

Report Alignment by Agroecosystem (AES)




Technology Evaluation Data and tools for what if scenarios of technology use by type, location, and human capacity to drive models and analysis



MANAGEMENT

• Planting window • Planting density • Irrigation • Inorganic fertilizer • Organic manure • Tillage • Residue

CULTIVAR

• Phenology • Max # of kernels • Kernel filling rate

*DSSAT Cropping System Model Ver. 4.0.2.000 May 21, 2009; 16:32:33 *RUN 1 : RAINFED LOW NITROGEN MODEL : MZCER040 - MAIZE EXPERIMENT : UFGA8201 MZ NIT X IRR, GAINESVILLE 2N*3I TREATMENT 1 : RAINFED LOW NITROGEN CROP : MAIZE CULTIVAR : McCurdy 84aa ECOTYPE :IB0002 STARTING DATE : FEB 25 1982 PLANTING DATE : FEB 26 1982 PLANTS/m2 : 7.2 ROW SPACING : 61.cm WEATHER : UFGA 1982 SOIL : IBMZ910014 TEXTURE : - Millhopper Fine Sand SOIL INITIAL C : DEPTH:180cm EXTR. H2O:160.9mm NO3: 2.5kg/ha NH4: 12.9kg/ha WATER BALANCE : IRRIGATE ON REPORTED DATE(S) IRRIGATION : 13 mm IN 1 APPLICATIONS NITROGEN BAL. : SOIL-N & N-UPTAKE SIMULATION; NO N-FIXATION N-FERTILIZER : 116 kg/ha IN 3 APPLICATIONS RESIDUE/MANURE : INITIAL : 1000 kg/ha ; 0 kg/ha IN 0 APPLICATIONS ENVIRONM. OPT. : DAYL= 0.00 SRAD= 0.00 TMAX= 0.00 TMIN= 0.00 RAIN= 0.00 CO2 = R330.00 DEW = 0.00 WIND= 0.00 SIMULATION OPT : WATER :Y NITROGEN:Y N-FIX:N PHOSPH :N PESTS :N PHOTO :C ET :R INFIL:S HYDROL :R SOM :G MANAGEMENT OPT : PLANTING:R IRRIG :R FERT :R RESIDUE:N HARVEST:M WTH:M *SUMMARY OF SOIL AND GENETIC INPUT PARAMETERS SOIL LOWER UPPER SAT EXTR INIT ROOT BULK pH NO3 NH4 ORG DEPTH LIMIT LIMIT SW SW SW DIST DENS C cm cm3/cm3 cm3/cm3 cm3/cm3 g/cm3 ugN/g ugN/g % ------------------------------------------------------------------------------- 0- 5 0.026 0.096 0.230 0.070 0.086 1.00 1.30 7.00 0.10 0.50 2.00 5- 15 0.025 0.086 0.230 0.061 0.086 1.00 1.30 7.00 0.10 0.50 1.00 15- 30 0.025 0.086 0.230 0.061 0.086 0.70 1.40 7.00 0.10 0.50 1.00 30- 45 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50 45- 60 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50 60- 90 0.028 0.090 0.230 0.062 0.076 0.05 1.45 7.00 0.10 0.60 0.10 90-120 0.028 0.090 0.230 0.062 0.076 0.03 1.45 7.00 0.10 0.50 0.10 120-150 0.029 0.130 0.230 0.101 0.130 0.00 1.45 7.00 0.10 0.50 0.04 150-180 0.070 0.258 0.360 0.188 0.258 0.00 1.20 7.00 0.10 0.50 0.24 TOT-180 6.2 22.2 45.3 16.1 21.4 <--cm - kg/ha--> 2.5 12.9 87080 SOIL ALBEDO : 0.18 EVAPORATION LIMIT : 2.00 MIN. FACTOR : 1.00 RUNOFF CURVE # :60.00 DRAINAGE RATE : 0.65 FERT. FACTOR : 0.80 MAIZE CULTIVAR :IB0035-McCurdy 84aa ECOTYPE :IB0002 P1 : 265.00 P2 : 0.3000 P5 : 920.00 G2 : 990.00 G3 : 8.500 PHINT : 39.000 *SIMULATED CROP AND SOIL STATUS AT MAIN DEVELOPMENT STAGES RUN NO. 1 RAINFED LOW NITROGEN CROP GROWTH BIOMASS CROP N STRESS DATE AGE STAGE kg/ha LAI kg/ha % H2O N ------ --- ---------- ----- ----- --- --- ---- ---- 25 FEB 0 Start Sim 0 0.00 0 0.0 0.00 0.00 26 FEB 0 Sowing 0 0.00 0 0.0 0.00 0.00 27 FEB 1 Germinate 0 0.00 0 0.0 0.00 0.00 9 MAR 11 Emergence 29 0.00 1 4.4 0.00 0.00 27 MAR 29 End Juveni 251 0.43 4 1.6 0.00 0.09 1 APR 34 Floral Ini 304 0.44 4 1.5 0.00 0.50



OUTPUT Phenology

flowering, grain/seed/tuber, maturity

Yield component grain/seed/tuber, biomass, LAI

Growth grain/seed/tuber, biomass, LAI

Soil nitrogen balance, water balance,

carbon balance

0

1

2

3

4

5

6

7

8

9

10

0 50 100 150 200

Yield(t/ha)

Fertilizer (kg[N]/ha)

Supplementing limited empirical data by assessing potential yield responses for specific locations and technologies

OPV, ---

100% 200%300%

100%

200%300%

% Diff. Yie 100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

100%

200%300%

% Diff. Yie

131% 116%73%66%6%0%

Variation in potential yields and in the efficacy of different technology packages by region Helps assess more realistic local yield targets (higher or lower than national target), as well as informing identification of region-specific technology and input use recommendations and packages

Maize DrylandRiceDrylandWetland

0%

10%20%30%

0%

10%20%

% Diff. Yield 0%

10%20%

% Diff. Yield

0%

20%40%

% Diff. Yield

10%

5%4%0%

Comparing the likely effectiveness of specific technologies sub-nationally

Administrative unit or AEZ-based disaggregation of potential technology impacts




Technology Evaluation Data and tools for what if scenarios of technology use by type, location, and human capacity to drive models and analysis


Technology use and effectiveness Status and trends of the uptake, effectiveness and sustainability of specific technologies/practices


Evidence of improved varietal adoption*

Adoption (percent of planted area)

Ethiopia Ghana Tanzania Mozambique Burkina Faso

Cote D'Ivoire

Cereals Maize 57 72 54

Rice (Paddy) 42 92 Roots and Tubers Cassava 36 30 19 20 Legumes Cowpeas 82 31 11 10 Soybean 94 79 100

Source: DIVA (in publication)

Note: Based on secondary data and expert consultation in countries by CG centers

Economically important improved varieties in Ghana: Maize

Variety Release year Adoption (% area)

Obatanpa 1992 26

Etubi 2007 11

Mamaba (GH 110) 1996 11

Okomasa 1988 5

Dorke-SR 1992 3

Kawandzie 1984 1

All MVs ( national ) 57

Source: Diffusion of Improved Crop Varieties in Africa. The Effectiveness of Crop Improvement Programs in Sub-Saharan Africa from the Perspectives of Varietal Output and Adoption: The Case of Cassava, Cowpea, Maize, and Soybean. Objective 1 Technical Report Arega D. Alene and Jonas Mwalughali IITA, PO Box 30258, Lilongwe, Malawi. July 2012.

CRP Projects & Scientists

Investment/Activity Mapping (past, on-going, planned). Opportunities for coordination, collaboration and co-location (alignment, gaps & duplication).

• Open Access Policies*

• Growing role of ICTs & Remote Sensing

• Infrastructure • Hosting



Technology Evaluation Data and tools for what if scenarios (e.g., CA with CC) by type, location, and local capacity to drive models and analysis

Commodity Prioritization & Productivity Growth Targets Data/tools for prioritizing commodities and setting yield goals National

Productivity Teams

Gov agencies & scientists

Universities Private Sector R&D Partners

Scaling Partners

Technology use and effectiveness Status and trends of the uptake, effectiveness and sustainability of specific technologies/practices

Productivity Progress & Performance Dashboard Data and tools for what if scenarios of technology use by type, location, and human capacity to drive models and analysis

SRO’s (regional priorities, Spillover, capacity building..

AgMIP GAEZ Farming Systems

Assessment AfSIS

LSMS

CRSPs

CIMSANS

………… IBM ASTI

DIVA Agribenchmark ReSAKSS/SAKSS AGRODEP


Some Technology Platform Attributes

• Initial focus on structured documentation of technologies and practices, assessing potential in local production contexts, & actual uptake and effectiveness in sustainable productivity growth. Reach back into R&D over time

• Many TP components already exist, potential partners (public and private) willing to participate and good indication of donor support. Country experiments / SRO consolidation

• Importance of CGIAR and CAADP investments using common taxonomy/ coding/ ontologies of investment themes, agroecological zones, commodities, partners, etc…

• Build common taxonomies into all investment planning/reporting

• Scope and reliability (hence utility) of data and services will grow over time in response to use/ feedback/ learning

Some Questions/Challenges

• Process for improving existing concept note? e.g., broadening participation in shaping technical and institutional context and setting out overall scope of ambition while taking a realistic phased approach to implementation

• How to integrate strengths and potential roles of both national and regional capacities?

A critical Technology Platform service will be ready access to on-line, interoperable suites of “best bet” and promising practices both maintained and providing benefit to NA partners (government agencies, private sector, CGIAR, SROs/NARs, AGRA, NGOs, farmer organizations, etc)

Organizing and Sharing Knowledge on the Existence, Accessibility,

Performance, and Sourcing of Innovations (Technologies & Practices)

What yields can specific technologies and technology packages achieve?

Can we tune yield targets and

technology packages to different sub-national (e.g. agrecosystem) contexts?

This section describes the application of cropping systems data and modeling tools to help augment national empirical data and inform national technical discussions about specific geographic and technology targeting design and implementation choices

Technology & Innovation Commitments New Alliance communique (May 18, 2012) called for enabling actions to take innovation to scale by;

• Determining 10 year targets for sustainable yields and adoption of new technologies that will increase food security, resilience, and nutrition outcomes

• Launching a Technology Platform to assess availability of and share knowledge about improved technologies and practices

• Identifying current constraints to adoption

• Launching a technology scaling initiative with AGRA

• Share data with G8 and African partners and launch ICT innovation challenge

Questions to be Addressed - 1

• Which CAADP commodities/value chains to focus on?

• What 10 year yield targets are achievable? • What existing technologies are available to

achieve yield targets? • How best to tune yield targets and technologies

to different sub-national conditions (e.g. major agroecosystems)?

Questions to be Addressed - 2

• What policies, strategies, and services are needed to deliver the most appropriate technologies at scale and increase the probability of their sustainable adoption?

• How best to facilitate cross-country learning and knowledge spillover (e.g. “Virtual” Technology Platform facilitated by technical support partners – FARA, CGIAR and AGRA)?

Which CAADP commodities/value chains to focus on?

Commodity/Value Chain Prioritization

• Goal: To identify 3-4 focus commodities/value chains for each country from within CAADP priorities (typically 8-13 commodities)

• Method: Spreadsheet prioritization model developed (HarvestChoice/IFPRI) for refinement and validation with individual NA country teams

• Criteria: Commodity prioritization derived as overall ranking based on user-defined weighting of the following criteria: – Size of sub-sector 2010 (National Value of Production - FAOSTAT) – Projected demand growth 2010-2030 (National demand growth – IFPRI

IMPACT/Global Projections) – Exploitable yield gap (Current national yields vs Best bet technology performance

with best farmers * Expected national adoption within 10 years with NA focus & investments – Published trials/Expert opinion/Household data)

– Share of benefits to poor (Share of bottom 40% of households who (a) produce & (b) consume the commodity – HarvestChoice HH survey collection )

– Nutrition outcomes (Increased in national calorie and protein availability if exploitable yield gap closed by expected amount in 10 year horizon – ∆Production * Calorie of protein per unit of production – Published coefficients)

– NR sustainability (increased extraction of net (a) total nutrients (NPK) and (b) water consumption based on 10 year production increase – HarvestChoice data and Published coefficients)

– Attractiveness to the private sector (input market potential: adoption of improved seeds, output market potential: share of output marketed – Published data, CGIAR, AGRA-PASS, HarvestChoice HH survey data collection)

A Technology Platform for Africa

Education

ha tha tha

mt ha mt ha

varying pace3

practices types

videos oftechnologies

implementation ictopen

y yp yp

yield goalsthe emergence