Decision support tool for site specific recommendations to improve cassava agronomy

David Ngome, Pieter Pypers, and Meklit Chernet IITA-Nairobi

Mr Ritu Manzi displays a cassava root harvested from one of the ACAI trial plots on his farm in Butiama, near Bunda, Mwanza Tanzania. Preliminary results have indicated a good cassava response to fertilizer. Photo by IITA.






Africa is the global leader in overall production of cassava, but the continent lags behind in yield averages. The average yield of just below 15 t/ha is dismal being below the global average of 20 t/ha, with some countries such as India reaching 30 t/ha.

The Africa Cassava Agronomy Initiative (ACAI) project seeks to address some of the most pressing agronomy problems within the cassava value chain in sub-Saharan Africa to increase the productivity of the crop and create a knowledge base necessary to sustain cassava agronomy research

ACAI is led by IITA and partners with national agricultural research institutes (NARIs) and development partners in Nigeria and Tanzania. The National Root Crops Research Institute (NRCRI) and the Federal University of Agriculture, Abeokuta (FUNAAB) lead the implementation of the field research in Nigeria and the Agricultural Research Institute (ARI) in Tanzania. ACAI is funded by the Bill & Melinda Gates Foundation and is supported by several international research institutions for specialized research support and capacity building.

The project aims to conduct extensive research to understand cassava nutrient requirements and growth dynamics under different conditions within specific areas of interest. Crop growth models have been adapted and calibrated to simulate responses to nutrients and rainfall regimes and have been integrated into decision support tools to provide tailored recommendations. These tools, when deployed, will assist extension agents in advising farmers on the best practices to achieve higher yields and maximal revenue.

The decision support tools

In December 2017, ACAI marked its second year of activities since inception. In just under 21 months, the project had already moved through key milestones in generating a unique knowledge base on cassava agronomy, developing the initial versions of the decision support tools, and improving the capacity of partners and the NARIs to carry out agronomy research.

ACAI is developing decision support tools for six use cases targeted to improve fertilizer use for improved yield and cassava root quality, enable sufficient and sustainable supply of cassava roots to processing industries, and facilitate improved cassava agronomy advice.

IITA’s Adebowale Adetunji and Rebecca Enesi reading a barcode to record
data from a cassava trial plot at IITA, Ibadan, Nigeria. ACAI is using barcoding
of plants and trial plots for identification and efficient data collection and data
management. Photo by IITA

  1. Site-Specific Fertilizer recommendation tool, targeting extension agents supporting
    commercial cassava growers to maximize returns on investments in fertilizer.
  2. Fertilizer Blending recommendation tool, targeting fertilizer companies to produce better blends suited for cassava.
  3. Intercropping recommendation tool, targeting extension agents supporting smallholder cassava growers to maximize revenue generated in cassava intercropping systems by optimizing plant density and arrangement, and varietal choice.
  4. Best Planting Practices recommendation tool, targeting commercial cassava growers investing in mechanized land preparation to recommend the most profitable tillage regime.
  5. Scheduled Planting recommendation tool, targeting commercial cassava growers to ensure sustained year-round supply of cassava roots to the processing industry.
  6. High Root Starch content recommendation tool, targeting outgrowers supplying roots to starch factories to maximize root starch content.

The project has finalized the prototype (V1) of the decision support tools deployed on desktop, Open Data Kit (ODK), and paper-based recommendations. In 2018, ACAI will be carrying out validation exercises to test the accuracy of the tools and the user experience and gather feedback from primary partners for further improvement.

ACAI NOT trial results

Trials on cassava–maize (Nigeria) and cassava– sweet potato intercropping showed that substantial improvements compared with the local practice can be achieved through a combination of improved and compatible germplasm, optimized crop density and arrangement, and application of fertilizer. In Nigeria, average increases of 4 t/ha of cassava roots and 1.2 m2 of maize cobs were achieved, and profitability of fertilizer use could be achieved by targeting fields based on local knowledge on the history of maize performance.

Trials on scheduled planting and harvesting, and starch measurements across the field trials for the various use cases showed wide variation in starch content and yield, with the month of harvest explaining 35–64% of the variation in starch content, and site-specific conditions (mainly weather) and crop age explaining another 21–36%. Small, negative fertilizer effects on starch content were found, but these only occurred when N and P applications were not balanced and did not outweigh the benefits of fertilizer effects on root yield.

The project has especially combined the use of the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model and the Light Interception and Utilization (LINTUL) model. The QUEFTS model is applied for predicting the yield response to the combined application of nitrogen (N), phosphorus (P), and potassium (K) and identifying the most profitable nutrient regime given prices of available fertilizers, while the LINTUL model is used to predict water-limited yields by considering daily weather data, crop characteristics, and soil physical properties.

The two models are in a complimentary sequence to each other generating data on factors that influence cassava root yield. The data is analyzed to determine the kind and amount of fertilizer to be used so that farmers can get maximum return on investment.

Spatializing water-limited yield in Tanzania

These findings were integrated in the first versions of the decision support tools, in a format that allowed extension agents to provide site-specific and tailored recommendations to candidate farmers participating in a pilot exercise to validate the findings. The aim is to further improve both the content and the format of the recommendations before scaling up the tools planned in 2019.

ACAI has run more than 1400 trials across 940 trial locations in Nigeria and Tanzania with over 9000 yield assessments carried out from the trials. The partnership with the NARIs has linked the project with more than 10,000 cassava growers and extension agents within their system.

Numbers and figures

Sylvia Okafor (right) supervising planting of a farmer-managed trial plot. She is an extension agent working with
ACAI through NRCRI in Nando, Anambra East, Anambra State, Nigeria. Photo by IITA

The decision support tools developed by ACAI will be deployed to extension agents operating within the dissemination networks of the development partners to support cassava growers to improve their yield, access the market, and apply best practices for optimal returns and efficient investment.

Although ACAI is currently validating the tools, the project is already training select individuals as trainers who will help transfer technical knowledge to extension agents, who will in turn disseminate and expand the use of the tool.

ACAI is aiming to create tools that will generate a value of $28 million within the project’s five year tenure. This value is expected to directly impact over 100,000 households in the countries where ACAI operates.

Evidence from first testing of the recommendations has confirmed that profitable yield increases of 20–100% can be obtained by applying the recommendations. The tools also successfully identify when not to invest in intensification options, which in itself is a substantial improvement over current, blanket recommendations.

After completion of the validation exercises, ex ante assessments of the potential impact of the tools will be conducted to aid in further targeting and tailoring.

 

Posted on October 30, 2018 in Managing natural resources

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