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Session 2 intercropping dst

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The Development of the Optimal Intercropping Practices (IC) Decision Support Tool in Nigeria
and Zanzibar, Tanzania – Current progress, including how WS1-3 activities feed into the Decision Support Tool

Published in: Government & Nonprofit
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Session 2 intercropping dst

  1. 1. Development of the Best Intercropping Practices (IC) Decision Support Tool (DST) – V1 www.iita.org | www.cgiar.org | www.acai-project.org
  2. 2. Overview www.iita.org | www.cgiar.org | www.acai-project.org Best Intercropping Practices DSTs: 1. Background and modelling framework (Christine Kreye): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: Decision Tree Models 2. Field activities (Mark Tokula and Haji Saleh): • Field activities: Intercropping Trials • Field trial results 3. Development of the DST (Veronica Uzokwe): • Overview of recommendations • The Decision Support Tool • Next steps and additional data needs
  3. 3. Overview www.iita.org | www.cgiar.org | www.acai-project.org Best Intercropping Practices DSTs: 1. Background and modelling framework (Christine Kreye): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: Decision Tree Models 2. Field activities (Mark Tokula and Haji Saleh): • Field activities: Intercropping Trials • Field trial results 3. Development of the DST (Veronica Uzokwe): • Overview of recommendations • The Decision Support Tool • Next steps and additional data needs
  4. 4. Introduction www.iita.org | www.cgiar.org | www.acai-project.org Best Intercropping Practices DSTs: • Specific purpose: recommend optimal time of planting, crop density and fertilizer application for a maize (NG) / sweet potato (Zanzibar) intercrop to increase overall productivity • Requested by: FCI (TZ) and 2SCALE (NG) • Other partners: SG2000 (NG) • Intended users: Extension Agents (EAs) supporting cassava growers • Expected benefit: Intercrop yield increased by 2 tonnes/ha and cassava yield not affected or increased by 0.5 tonnes/ha realized by 35,100 HHs, with the support of 124 extension agents, on a total area of 17,550 ha, generating a total value of US$3,948,750 • Current version: V1: uses expert knowledge to estimate current crop performance and revenue based on default or user-defined prices of roots and intercrop produce to recommend best planting time, planting density and fertilizer regime for a preferred set of varieties, maximizing overall net revenue or intercrop yield without affecting cassava yield • Approach: Decision tree model based on analysis of field trial data • Input required: Cropping objective (maximize total revenue or maximize cassava yield), prices of intercrop produce (maize cobs (NG) / sweet potato (Zanzibar)) and cassava roots, willingness to invest in fertilizer and knowledge of field history • Interface: Paper-based decision tree, including guidelines for simple calculations to estimate profitability
  5. 5. Learnings from the literature review www.iita.org | www.cgiar.org | www.acai-project.org Learnings for cassava – maize intercropping: Cassava is affected by… maize variety → negative impact on cassava yield minimized with short-duration varieties maize density → negative impact on cassava yield with densities > 50,000 plants ha-1. Fertilizer application increases yield of maize. Insufficient literature to evaluate residual impact on cassava…
  6. 6. Learnings from the literature review www.iita.org | www.cgiar.org | www.acai-project.org Learnings for cassava – sweet potato intercropping: Cassava yield (t/ha) Sweet potato yield (t/ha) LER Moreno & Hart, 1979 Cassava 10,000 + SP 50,000 -42% (9.7/16.8) -40% (6.3/10.5) 1.17 Cassava 10,000 + 2x SP 50,000 -32% (11.5/16.8) -40%, (5.6/10.5, 3.5/4.7) 1.95 Kanpinga, 1995 Cassava short non-branching + SP -35% (9/14) -23% (15/19) 1.4 Cassava semi-erect, tall, high-branching + SP -35% (9/14) -46% (7.5/19) 1.0 Ojore Ijoyah, 2012 Cassava + SP [very low ~ 5 t ha-1 in MC] • High competition between crops, with 30-40% yield loss for both cassava and sweet potato, compared to the monocrops. • Variety is important, indicating that aboveground competition is substantial, not just belowground – both crops are high K feeders – hence, explore ways to minimize light competition → delayed planting of sweet potato. Very limited information available – 3 studies of which 2 useful, without much detail.
  7. 7. Principles of the Best Intercropping Practices Tool www.iita.org | www.cgiar.org | www.acai-project.org 1. Obtain details on current practice 2. Identify alternative options within given constraints 3. Evaluate to what extent the performance of alternative options is location-dependent, based on analysis of multilocational field trial data 4. If so, identify GIS (or other) predictor variables to estimate location-specific effects of interventions on intercrop yield and cassava root yield 5. Convert yield effects to changes in gross revenue based on prices of intercrop produce and cassava roots (default values or user input) 6. Calculate net revenue (subtract cost of fertilizer) 7. Recommend optimal intercrop density, relative time of planting (Zanzibar only) and fertilizer regime (if willing to invest in fertilizer) that maximizes cassava yield or overall net revenue using a decision tree model The IC-DST is developed based on following steps and principles:
  8. 8. Principles of the Best Intercropping Practices Tool www.iita.org | www.cgiar.org | www.acai-project.org What is current practice? – learnings from the RC survey Tanzania (Zanzibar) 38% of cassava is intercropped, of which 45% by sweet potato (45%), planted at the same time (67%) or ± 2 weeks (29%). 0% of farmers apply fertilizer to the sweet potato intercrop, and 62% commercialize at least half of sweet potato produce. Main objective is maximizing land use efficiency. Nigeria 68% of cassava is intercropped, of which 75% by maize, planted 2 weeks earlier (33%) or at the same time (30%). 43% of farmers apply fertilizer to the maize intercrop, and 94% commercialize at least half of the maize produce. Main objective is faster access to food and income. Need picture here!
  9. 9. Tanzania (Zanzibar) Price of sweet potato tubers Nigeria Price of fresh maize cobs Principles of the Best Intercropping Practices Tool www.iita.org | www.cgiar.org | www.acai-project.org What is current practice? – prices of intercrop produce (phone surveys)
  10. 10. Principles of the Best Intercropping Practices Tool www.iita.org | www.cgiar.org | www.acai-project.org What are the alternative options? 2. Optimize the relative time of planting of the intercrop • Reduce competition for light for the cassava crop • Optimal time of planting will depend on the cropping objectives 3. Apply fertilizer • Increased availability of nutrients (reduced belowground competition) • Intercrop as an entry point for fertilizer application to cassava (benefits from residual effects) • Modify the composition of the fertilizer regime to the specific cropping objectives 1. Modify (increase) the crop density: • Optimize land use efficiency • Choose best variety with minimal above- and belowground competition effect
  11. 11. Principles of the Best Intercropping Practices Tool www.iita.org | www.cgiar.org | www.acai-project.org Modelling framework Are the effects of density and fertilizer application dependent on field conditions? Evaluate through multilocational field testing covering target environments Develop decision tree models Can we predict these effects based on expert knowledge?
  12. 12. Overview www.iita.org | www.cgiar.org | www.acai-project.org Best Intercropping Practices DSTs: 1. Background and modelling framework (Christine Kreye): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: Decision Tree Models 2. Field activities (Mark Tokula and Haji Saleh): • Field activities: Intercropping Trials • Field trial results 3. Development of the DST (Veronica Uzokwe): • Overview of recommendations • The Decision Support Tool • Next steps and additional data needs
  13. 13. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Evaluate effects of planting density and fertilizer application on maize (Nigeria): 2 sets of trials based on step-wise intensification: ⇒ CIM-2 (CIM-1); planted in 2016 ⇒ CIM-3, CIM-4 (CIM-5); planted in 2017 based on insights of 2016 CIM-2 CIM-3 CIM-4 ⇒ Fresh cobs are important ⇒ Include effect of maize density on cob quality/size ⇒ CWMP: high cassava density is better ⇒ Basal N (and P) application in CF2/CLMF; 15 kg N/ha
  14. 14. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Sampling frame: maximize representativeness across target AoI Env. %Area #trials #EAs adj. Cum. Ratio 6 19 40 4 0.19 7 14 29 3 0.32 9 11 24 2 0.44 5 11 23 2 0.55 11 8 18 2 0.63 8 8 18 2 0.72 2 8 16 2 0.79 4 7 15 2 0.87 Break off for all clusters below 5% coverage 3 4 8 1 0.90 12 4 7 1 0.94 1 3 7 1 0.97 10 2 5 0 0.99 13 1 2 0 1.00 Environments identified based on clustering exercise using GIS information (climate, soil and vegetation) across the partners’ target area of intervention area for the IC use case:
  15. 15. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Current overview of trials and status of trials - Nigeria • 2016 (CIM-2) trials: 70 trials were used for data analysis • 2017 (CIM-3, CIM-4) trials: 145 trials were planted; 89 trials used for analysis of maize cob harvest Challenges: • Cattle (especially in the SW) • Birds, rodents and monkeys (especially for maize) • Herbicide use at the wrong time (killing the maize) • Weeding
  16. 16. Intercropping Trials Impressions and learnings from the field – NG – some pictures Securing the crops Quality classes of cobs Fertilizer effect Learning new tools www.iita.org | www.cgiar.org | www.acai-project.org
  17. 17. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2016, CIM-2 Cassava Maize Effect of F1: increase in root yield of 4 t/ha + increase of 1.2 cobs/m2 for maize Effect of D: no impact on cassava yield + increase in maize yield Maize intercrop as an entry point to fertilizer application on cassava? Does the maize yield response justify the investment in fertilizer?
  18. 18. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2016, CIM-2
  19. 19. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2016, CIM-2 Yield ~ Treatment + (Fertilizer | field) Fixed effects: Estimate Std.Error df t value Pr(>|t|) F1 15.1302 0.9861 65.2300 15.344 < 2e-16 F2 1.6083 0.8787 54.9100 1.830 0.072633 D -2.1444 0.6029 164.7700 -3.557 0.000491 D F1 F2
  20. 20. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2017; CIM-3 and CIM-4 Yield ~ Treatment + MaizeVariety + (Fertilizer | field) All marketable cobs – effect of fertilizer at high maize density ⇒ rel. high variability in response ⇒ target high planting density ⇒ good management (army worm/rodent/bird control) before applying fertilizer ⇒ Need to look at site specific fertilizer rates
  21. 21. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2017; CIM-3 and CIM-4 Yield ~ Treatment + MaizeVariety + (Fertilizer | field) Large Cobs – effect of fertilizer at high maize density ⇒need to look at site specific fertilizer rates ⇒relatively safe response of > 0.3 cobs per m2
  22. 22. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2017; CIM-3 and CIM-4 Yield ~ Treatment + MaizeVariety + (Fertilizer | field) All marketable cobs Large Cobs D F1/CF2 (C)LMFLM D F1/CF2 (C)LMFLM
  23. 23. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results – Nigeria: 2017; CIM-3 and CIM-4 We adjusted the F2 treatment to include a basal fertilizer application. How does it compare to F1 ? All treatments significantly different from D, except LM. D F1 CF2 LM LMF CLMF Yield ~ Treatment + MaizeVariety + (Fertilizer | field) All marketable cobs Large Cobs D F1 CF2 LM LMF CLMF After cassava harvest, the effect of CF2/CLMF on root yield will be evaluated.
  24. 24. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Evaluate effects of planting density, planting time and fertilizer application on sweet potato (Zanzibar):
  25. 25. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Current overview of trials and status of trials - Zanzibar Region clusters CIS-3 CIS-4 Harvested (SP only) Unguja 7 1 73 66 Pemba 3 1 25 22 Total 10 2 98 88 CIS-3 = on-station trials; CIS-4 = on-farm trials Out of 98 on-farm trials established: 86 = good quality, 8 = intermediate, and 3 = poor (lost) Note: sweet potato crop lost in 2016 – only useful data from 2017.
  26. 26. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Impressions and learnings from the field – Zanzibar – some pictures
  27. 27. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results - Zanzibar monocrop monocrop NPK1 monocrop NPK0 On-station trials on Unguja and Pemba
  28. 28. Intercropping Trials www.iita.org | www.cgiar.org | www.acai-project.org Results - Zanzibar On-farm trials with 80 farmers across Unguja and Pemba Between-district variance accounts for 60% of total variance (related to differences in planting time + rainfall) Treatment effects are consistent (within district). Between-farmer variance = 12% of total variance. Analysis of Variance Table Pr(>F) Treatment < 2.2e-16 *** district < 2.2e-16 *** Treatment:district < 2.2e-16 ***
  29. 29. Overview www.iita.org | www.cgiar.org | www.acai-project.org Best Intercropping Practices DSTs: 1. Background and modelling framework (Christine Kreye): • Introduction • Learnings from literature • Learnings from baseline and rapid characterization • Modelling framework: Decision Tree Models 2. Field activities (Mark Tokula and Haji Saleh): • Field activities: Intercropping Trials • Field trial results 3. Development of the DST (Veronica Uzokwe): • Overview of recommendations • The Decision Support Tool • Next steps and additional data needs
  30. 30. How are these results fed into the DST? www.iita.org | www.cgiar.org | www.acai-project.org Nigeria: 1. Cassava appears unaffected by intensification in maize → base V1 on responses of maize. 2. Lessons from the first set of trial (CIM-2) for maize • Farmers value fresh maize cobs for the market • Evaluate responses by cob size • Large cobs fetch highest prices; base decisions on this fraction • Use trials of 2017 (CIM-3 and CIM-4) for V1 development 3. Response to higher planting density of maize is not site-specific (for the selected maize variety) and high density can be a blanket recommendation for total marketable cobs. 4. The height of maize (without fertilizer application) at tasselling can be used as indicator for the response to fertilizer. 5. The maize fertilizer regime (F1) is preferred in all situations (over F2). 6. Planting at the same time as cassava (only +/- a couple of days). 7. Use maize that matures within 90 - 95 days. 8. Maize cob prices and fertilizer availability and cost will drive the decision-making in the DST.
  31. 31. How are these results fed into the DST? www.iita.org | www.cgiar.org | www.acai-project.org Zanzibar: Sweet potato 1. Sweet potato suffers somewhat from cassava, yield losses of 5 – 15% (higher in high-yielding fields), less than observed in other studies. 2. Delayed planting of sweet potato causes yield reductions of 0 – 45%. → Time of planting is crucial for sweet potato (sweet potato crop was completely lost in 2016). → Delayed planting of sweet potato is only an option if cassava is planted early. 3. Increasing density is not advantageous for sweet potato (but has advantages for weed control). → Recommended density = 10,000-20,000 vines/ha in intercrop. 4. Effects of density and relative planting time are not site-specific. → Recommendations will mainly be driven by cropping objectives and sweet potato tuber prices Cassava 1. Impact of sweet potato on cassava yield will be evaluated after harvest Q2 2018. 2. Negative impact on cassava root yield is expected (based on field observations), but could be alleviated to some extent by fertilizer application and delayed planting of sweet potato. 3. Profitability will likely mostly depend on price ratio of cassava roots over sweet potato tubers.
  32. 32. Packaging in a tool for field use www.iita.org | www.cgiar.org | www.acai-project.org How to make this framework available for quick and easy use? IC-DST packaged as a simple paper-based decision tree with inputs: 1. Variety recommendation: • erect cassava • early maturing maize (90-95 days) 2. High planting densities • cassava (12,500 plants ha-1) • maize (40,000 plants ha-1) 3. Fertilizer regime: • target the maize crop • cassava benefits as well 4. Fertilizer recommendation: • site-specific • use farmers’ experience with their maize crop (plant height at tasselling) 5. Profitability of fertilizer application: • based on expected additional large maize cobs • look-up table [cost of fertilizer x price of large cobs] • formula for easy calculation Note: IC-DST for Zanzibar will be developed after first cassava yields are available, based on the same principles
  33. 33. Packaging in a tool for field use www.iita.org | www.cgiar.org | www.acai-project.org How to make this framework available for quick and easy use? IC-DST packaged as a simple paper-based decision tree with inputs: 1. Variety recommendation: • erect cassava • early maturing maize (90-95 days) 2. High planting densities • cassava (12,500 plants ha-1) • maize (40,000 plants ha-1) 3. Fertilizer regime: • target the maize crop • cassava benefits as well 4. Fertilizer recommendation: • site-specific • use farmers’ experience with their maize crop (plant height at tasselling) 5. Profitability of fertilizer application: • based on expected additional large maize cobs • look-up table [cost of fertilizer x price of large cobs] • formula for easy calculation Note: IC-DST for Zanzibar will be developed after first cassava yields are available, based on the same principles
  34. 34. Next steps www.iita.org | www.cgiar.org | www.acai-project.org 1. Validation exercises (in collaboration with EAs of dev. partners requesting the DST) Technical evaluation: • How accurate are predictions? • How good is farmers ‘ experience with their maize crop to make it a good indicator ? • Can they be improved by use of GIS layers? • Is maize always a good indicator for the performance of both crops? Gather feedback what functionality is needed and how to interface with the end-user? • Is a paper based decision tree appreciated? • Do farmers want a decision tree for grain yield as well? • Are large cobs a good enough indicator? • Do farmers prefer decision making based on the cassava crop? 2. Extend beyond current functionality • Test options to derive site-specific fertilizer rates • Introduce QUEFTS for maize? • Additional varieties – principles for testing? V1 is a ‘hybrid’ between a research tool and the intended ‘app’
  35. 35. Questions and discussion www.iita.org | www.cgiar.org | www.acai-project.org Questions?

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