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Overview
www.iita.org | www.cgiar.org | www.acai-project.org
Site-Specific Fertilizer Recommendation and Best Fertilizer Blend DSTs:
1. Background and modelling framework (Guillaume Ezui):
• Introduction
• Learnings from literature
• Learnings from baseline and rapid characterization
• Modelling framework: LINTUL and QUEFTS
2. Field activities (Yemi Olojede and Deusdedit Peter Mlay):
• Field activities: Nutrient Omission Trials
• Field trial results
3. Development of the DST (Meklit Chernet):
• Overview of recommendations for Tanzania
• The Decision Support Tool
• Ongoing validation activities
• Next steps and additional data needs
Overview
www.iita.org | www.cgiar.org | www.acai-project.org
Site-Specific Fertilizer Recommendation and Best Fertilizer Blend DSTs:
1. Background and modelling framework (Guillaume Ezui):
• Introduction
• Learnings from literature
• Learnings from baseline and rapid characterization
• Modelling framework: LINTUL and QUEFTS
2. Field activities (Yemi Olojede and Peter Mlay):
• Field activities: Nutrient Omission Trials
• Field trial results
3. Development of the DST (Meklit Chernet):
• Overview of recommendations for Tanzania
• The Decision Support Tool
• Ongoing validation activities
• Next steps and additional data needs
Introduction
www.iita.org | www.cgiar.org | www.acai-project.org
The Site-Specific Fertilizer Recommendation DST:
• Specific purpose: recommend site-specific fertilizer rates that maximize net return on investment
• Requested by: SG2000 (NG), Notore (NG), Minjingu (TZ)
• Other partners: MEDA (TZ)
• Intended users: Extension agents (EAs) supporting commercial cassava growers
• Expected benefit: Cassava root yield increased by 8 tonnes/ha, realized by 28,200 HHs, with the
support of 215 extension agents, on a total of 14,100 ha, generating a total value
of US$2,185,500
• Current version: V1: implemented at 5x5km, for an investment of maximally 200 $ ha-1 (fixed),
for a fixed set of fertilizers (urea, Minjingu mazao, MOP) at fixed average regional
unit prices, and for a fixed average regional price for cassava produce
• Input required: GPS location and planting date (harvest date is fixed at 10 MAP)
• Interface: ODK form running on a smartphone or tablet, allowing offline use, and serving as
a ‘hybrid’ between research tool and a practicable dissemination tool
Introduction
www.iita.org | www.cgiar.org | www.acai-project.org
The Best Fertilizer Blend DST:
• Specific purpose: identify best-suited fertilizer blends to address nutrient constraints for cassava
production in a target area
• Requested by: Notore (NG), Minjingu (TZ)
• Other partners: -
• Intended users: Fertilizer producers engaged in the cassava value chain
• Expected benefit: 5000 tonnes of new fertilizer blends sold to commercial cassava growers, with a
total value of US$2,500,000
• Current version: V1: implemented at 5x5km, assessing N, P and K requirements for target yield
increases by 5, 10, 15, 20 t ha-1 and closing the yield gap across the cassava-
growing area in the target countries (selected districts and states)
• Input required: Target area (districts or states) and target yield increase
• Interface: R-shiny application (web-based) running on a desktop computer

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Pages from diapo_1.pdf

  • 1. Overview www.iita.org | www.cgiar.org | www.acai-project.org Site-Specific Fertilizer Recommendation and Best Fertilizer Blend DSTs: 1. Background and modelling framework (Guillaume Ezui): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: LINTUL and QUEFTS 2. Field activities (Yemi Olojede and Deusdedit Peter Mlay): • Field activities: Nutrient Omission Trials • Field trial results 3. Development of the DST (Meklit Chernet): • Overview of recommendations for Tanzania • The Decision Support Tool • Ongoing validation activities • Next steps and additional data needs
  • 2. Overview www.iita.org | www.cgiar.org | www.acai-project.org Site-Specific Fertilizer Recommendation and Best Fertilizer Blend DSTs: 1. Background and modelling framework (Guillaume Ezui): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: LINTUL and QUEFTS 2. Field activities (Yemi Olojede and Peter Mlay): • Field activities: Nutrient Omission Trials • Field trial results 3. Development of the DST (Meklit Chernet): • Overview of recommendations for Tanzania • The Decision Support Tool • Ongoing validation activities • Next steps and additional data needs
  • 3. Introduction www.iita.org | www.cgiar.org | www.acai-project.org The Site-Specific Fertilizer Recommendation DST: • Specific purpose: recommend site-specific fertilizer rates that maximize net return on investment • Requested by: SG2000 (NG), Notore (NG), Minjingu (TZ) • Other partners: MEDA (TZ) • Intended users: Extension agents (EAs) supporting commercial cassava growers • Expected benefit: Cassava root yield increased by 8 tonnes/ha, realized by 28,200 HHs, with the support of 215 extension agents, on a total of 14,100 ha, generating a total value of US$2,185,500 • Current version: V1: implemented at 5x5km, for an investment of maximally 200 $ ha-1 (fixed), for a fixed set of fertilizers (urea, Minjingu mazao, MOP) at fixed average regional unit prices, and for a fixed average regional price for cassava produce • Input required: GPS location and planting date (harvest date is fixed at 10 MAP) • Interface: ODK form running on a smartphone or tablet, allowing offline use, and serving as a ‘hybrid’ between research tool and a practicable dissemination tool
  • 4. Introduction www.iita.org | www.cgiar.org | www.acai-project.org The Best Fertilizer Blend DST: • Specific purpose: identify best-suited fertilizer blends to address nutrient constraints for cassava production in a target area • Requested by: Notore (NG), Minjingu (TZ) • Other partners: - • Intended users: Fertilizer producers engaged in the cassava value chain • Expected benefit: 5000 tonnes of new fertilizer blends sold to commercial cassava growers, with a total value of US$2,500,000 • Current version: V1: implemented at 5x5km, assessing N, P and K requirements for target yield increases by 5, 10, 15, 20 t ha-1 and closing the yield gap across the cassava- growing area in the target countries (selected districts and states) • Input required: Target area (districts or states) and target yield increase • Interface: R-shiny application (web-based) running on a desktop computer