acai

Cassava farmers in Tanzania to benefit from new industry partnership with ACAI project

No comments

At a recent meeting in Tanzania, IITA, through the African Cassava Agronomy Initiative (ACAI) and the Tanzania Agricultural Research Institute (TARI-Naliendele) agreed to explore areas of collaboration with the Cassava Starch Tanzania Corporation (CSTC).

Demand for cassava is increasing as more companies are seeking to process the roots into high-value, starch-rich flour. New processing capacity is starting to come online for many companies, such as CSTC. However, one of the main concerns of these ventures is getting a stable supply of cassava.

This new agreement could see CSTC helping to deploy ACAI’s latest tools to secure the cassava supply of smallholder farmers across Tanzania.

ACAI Project coordinator in Tanzania and East Africa, Veronica N.E. Uzokwe explains: “The ACAI project has essentially distilled years of agronomic research on cassava farming into simple-to-use and practical decision support tools that can help farmers achieve significant crop yield and quality improvements.”

Working with thousands of farmers across Tanzania, the ACAI project has been applying advanced agronomic analyses to answer farmers’ questions such as, “When is the best time to plant? When should I harvest? What fertilizer do I use; how much and when?”

Among the various decision support tools created by ACAI, their fertilizer recommendation tool is designed to maximize productivity based on a given fertilizer input. Their scheduled planting guidance offers support to farmers to ensure that harvested roots supplied to starch companies have a high starch content. The economic calculations driving the tools are also of great use to fledgling companies in the cassava food processing industry, looking to maximize profitability.

Cassava farmers in Tanzania to benefit from new industry partnership with ACAI project
Cassava stakeholders with members of CSTC.

ACAI is currently validating the tools with the help of many smallholder farmers, who supported their initial development. To date, development and delivery of the support tools have been carried out by an extensive network of ACAI partner organizations, including Minjingu Fertilizer, FJS starch company, Mennonite Economic Development Associates (MEDA), Cassava: Adding Value for Africa (C:AVA), and Farm Concern International.

Uzokwe said, “We welcome more partners from all levels of the cassava value chain. We believe that CSTC will be able to help us reach more farmers through extension agents. Training these stakeholders will promote food security, generate incomes, and support people’s livelihoods. This aligns with the goals of IITA.”

Mathew de Klerk, CSTC General Manager, said that his company is willing to work with a dynamic organization that has a good track record in agriculture. He also thanked and praised the Tanzanian Government for providing an enabling environment to drive cassava industrialization in Tanzania and East Africa as a whole.

acaiCassava farmers in Tanzania to benefit from new industry partnership with ACAI project
read more

Akilimo Dashboard: ACAI develops a data management system for field activities and validation of agronomy advice tools

No comments

ACAI has developed a dashboard that will be used to curate project activity data and provide a real-time summary of results from field activities as entered by extension agents. The Akilimo Dashboard is a suite of code in R language combined with the Open Data Kit (ODK) data collection tools to form a data processing engine that delivers reports in easy-to-read pdf format, CSV files, and an interactive web interface.

Akilimo Dashboard output plots showing an Extension Agent’s status of events and calendar of activities

Extension agents (EAs) and national research system agronomists provide agronomy advice to cassava growers, monitor validation activities and provide data via mobile phones or tablets using the ODK collect app. Data entered by the EAs are processed daily through the R script and organized as output for interpretation customized to the user’s needs.

The dashboard will help ACAI management in monitoring the activities around the validation of the ACAI decision support tools (DSTs). Coordinators of the activities will be able to check the status and get real-time information on planned and ongoing activities in their respective regions at the click of a button. From this information, the project team and interested parties can view the number and details of the households who have received ACAI recommendation for follow-up and further observations.

EAs working with ACAI on validation activities are compensated through a reward system, based on the amount of work done and data delivered. The EA earns points against which the remuneration is made on a monthly basis. The dashboard will provide a summary of all activities to facilitate payment for the EAs.

A simplified diagram of the Akilimo dashboard data management processes

The EA dashboard is presented on the desktop using the R shiny app as the tool’s front end. The dashboard’s outputs include households’ registration details, field events, EA points, recommendations given to farmers and the aggregated data. Further plans include summaries of the DST and trial performance to allow individual feedback to households and EAs participating in the exercises.

The Dashboard is a result of intensive 5-month programming by ACAI’s data scientist Meklit Chernet and data analyst Turry Ouma.  According to Turry, the Akilimo dashboard provides on-demand access to all-important metrics for a coordinator to manage EAs and households under his supervision. The dashboard will highly increase the efficiency of accessing and referencing information about the ACAI field activities. It provides an unbiased view of EAs performance and offers the coordinators a platform for further dialogue and great decision-making. The tool also offers a platform for accountability which increases the performance of the EAs.

“We have aggregated EA data into a single interface thereby increasing efficiency, cost-effectiveness, and speed of generating research data,” says Turry.

The tool is interactive and versatile, it offers the user a dynamic experience through filtering data, interacting with plots to see changes over time. The tool is versatile to be customized to the use of other projects by changing the variables of the significant entries that have an impact on the indicators of the project progress and regular activities in general. ACAI will further develop the dashboard as a standalone application and complemented by a training module to allow new partners to test the ACAI DSTs. Through this process, new valuable data is delivered to further improve the DSTs.

acaiAkilimo Dashboard: ACAI develops a data management system for field activities and validation of agronomy advice tools
read more

ACAI combines machine learning, field trial data and crop models to optimize fertilizer recommendations

No comments

The ACAI site-specific fertilizer recommendation (FR) tool is built to provide optimized and economically beneficial recommendations to cassava growers. The tool considers local soil data, weather conditions, prices of available fertilizers and cassava root produce, planting and harvest dates and the investment capacity of the farmer.

ACAI has been conducting nutrient omission trials (NOT) in Nigeria and Tanzania in collaboration with national research and development partners to find out how cassava responds to nutrients. Results show a large variation in nutrient response indicating the need for site-specific fertilizer recommendations.

In order to provide site-specific recommendations, ACAI is developing an integrated system using machine learning techniques coupled with process-based crop models. The ACAI team is combining the Light Interception and Utilization model (LINTUL), Quantitative Evaluation of the Fertility of Tropical Soils model (QUEFTS), and economic optimizer algorithms to calibrate the recommendations. The mechanism put in place determines the soil nutrient supply capacity, yield potential, nutrient-limited yield and fertilizer rates required to acquire a target yield maximizing net revenue by combining observations from field trials, available GIS data, weather data and farmers’ ability to invest in fertilizer.

Using QUEFTS model, the soil NPK supply was accurately predicted using the observed yield response in the NOTs. At these locations, the relationship between apparent soil nutrient supply and soil properties obtained from GIS layers from the International Soil Reference and Information Centre (ISRIC) was modeled using machine learning techniques. These models, in turn, were used to predict the soil NPK for the entire target intervention area. These soil properties can sufficiently explain the regional level of soil variation. To explain soil variation at short range, however, the GIS layers need to be complemented with a local scale soil fertility indicator.

The use of common local soil fertility indicators, such as local soil name, soil depth/color, cropping history, perception of soil fertility, cropping history, manure/fertilizer use, etc., are not sufficiently generic as their predictive ability depends on the local context. Such indicators are therefore challenging to use in a standardized way. Within ACAI, the current yield was found to be the best generic fertility indicator to adjust the soil nutrient supply at a regional scale to local soil conditions. The resulting FR tool is currently providing site-specific recommendations packaged as an ODK form and can be applied offline in the field on a mobile device. Progress is being made to develop generally accessible versions using IVR, USSD, a mobile app, and printable maps and guides.

One of the major challenges to improve the accuracy of the FR recommendation is the quality of the price data both for the fertilizers and the cassava roots. ACAI is exploring partnerships with various organizations providing digital market information as well as price mapping to provide meaningful default values.

Next steps include validating the FR tool both functionally, verifying whether the recommendations outperform current practices in the field, and architecturally, evaluating the user-friendliness and how the tool can best fit within the dissemination strategy of development partners.

acaiACAI combines machine learning, field trial data and crop models to optimize fertilizer recommendations
read more

ACAI Extension Agents Trained for Dissemination of the Decision Support Tools

No comments

Africa Cassava Agronomy ACAI conducted a training of trainers for extension agents working with Oyo State Cassava Growers Association (OYSCGA). The training is the first of a series planned to kick off the dissemination of the ACAI decision support tools in Nigeria and later in Tanzania.

Extension agents drawn from 11 local governments across Oyo State in Nigeria were trained on the modalities of conducting dissemination activities and to capture feedback from beneficiaries. The trained EAs are also tasked to conduct step down training in the local governments for their colleagues.

The training was led IITA and ACAI’s senior Agronomist Dr. Stefan Hauser accompanied by IITA colleagues Mr. Saburi Adekunbi, Mr. Thompson Ogunsanmi, Mr. Dada Adeboye, and Ms. Augustina Amaechi.

The trainees were shown practical demonstrations of using tables and maps as the paper-based format of the Best Cassava Planting Practice (BPP) decision support tools. The training also included a guide on applying the recommendations from the tools and using the monitoring and evaluation tools to collect information after dissemination events.

ACAI and OYSCGA agreed on the validation and dissemination activities action plan for 2019 that will be implemented at the grassroots level by the Extension Agents affiliated to the association. The EAs will be expected to run demonstrations of the ACAI tools for farmers and provide recommendations within their operation domains while collecting data on the adoption, use, and feedback from beneficiaries.

OYSCGA Chairman Bashir Adesiyan (in red shirt) leads a discussion during the ACAI ToT

OYSCGA chairman Mr. Bashir Adesiyan expressed his appreciation to ACAI for organizing facilitating the training. ACAI has worked with development partners such as OYSCGA to develop decision tools for extension agents to provide farmers with best agronomic advice for cassava intensification and optimized productivity.

acaiACAI Extension Agents Trained for Dissemination of the Decision Support Tools
read more

ACAI team reflects on progress made in first quarter

No comments

ACAI senior management from left Prof Friday Ekeleme, Dr. Chrisitine Kreye, Dr. Pieter Pypers, and Mr. Godwin Atser

Members of the African Cassava Agronomy Initiative (ACAI) met in Nigeria to discuss and evaluate on the progress made in the first quarter of the year, 2019, across the different components of the project otherwise known as Work Streams.

The meetings, which were convened by the Project Coordinator of ACAI, Dr. Pieter Pypers, 2-6 April; were aimed at creating internal synergy within the ACAI team while at the same time providing insights on the progress made by the Nigerian team.

Specifically, members of the ACAI team took a retrospective assessment of the best planting tool, monitoring and evaluation tools, and intercropping tools. There were also meetings with staff to assess the digital extension plan of the project and the scaling strategy being adopted.

Dr. Pypers also took time to discuss and appreciate the contributions of the project administration team, just as he held discussions with the Ph.D. trainees of the project.

At the end of the meetings, Dr. Pypers said he was satisfied with the progress made in Nigeria especially towards the finalization of the Decision Support Tools and the outreach plan.

ACAI staff who participated in the meetings included, Dr. Christine Kreye, Dr. Stefan Hauser, Prof Friday Ekeleme, Mr. Godwin Atser, Ms. Ezinne Ibe, and several other staff.

Commenced in 2015, ACAI is Africa’s flagship cassava agronomy project aimed at delivering cassava agronomy at scale. In 2018, ACAI and the Cassava Weed Management Project merged into one under the framework of ACAI, a move that enlarged the portfolio of ACAI.

ACAI Weed Scientist, Prof Friday Ekeleme commended the convener of the meeting, Dr. Pypers; and pledged the commitment of the team to redouble efforts to reach the milestones set in the project.

Beginning this year, ACAI intends to provide farmers with better agronomy advice and provide tools that allow farmers to access that information either directly (radio, SMS, USSD, IVR) or indirectly through services by EAs who are equipped with the decision support tools (DSTs). This will, in turn, boost the yield of cassava and put the nation on the path of growth, and raise the standard of living of cassava farmers, while providing more food available to feed African people.

acaiACAI team reflects on progress made in first quarter
read more

ACAI and Cassava Weed Management Project Merge

No comments

Dr Friday Ekeleme gives a presentation on the Cassava Weed Management activities.

The African Cassava Agronomy Initiative (ACAI) project and the Cassava Weed Management Project have merged into a single project. Both projects are funded by the Bill & Melinda Gates Foundation under the Agricultural Development program

ACAI project has been carrying out research to develop tools that will increase the availability of appropriate and affordable technologies to sustainably improve cassava productivity in Nigeria and Tanzania.

CWMP, on the other hand, screened environmentally friendly and safe herbicides and explored agronomic factors including motorized mechanical options for weed control in cassava. After the rigorous and intensive research, the project developed the Six Steps to Cassava Weed Management toolkit that when applied increases the productivity of cassava and reduces the drudgery of hand weeding.

Under the new arrangement, the two projects will operate as ACAI with an expanded mandate to include cassava weed management in the ACAI’s decision support tools.

Project teams from ACAI and CWMP met in Nairobi early February to develop an integration plan and a new implementation plan for 2019 and 2020. Components of the weed management solutions will be incorporated into some of the ACAI decision support tools and then disseminated as a single composite package.

Commenting on the merging of the two projects, IITA Director for Development and Delivery, Dr. Alfred Dixon said the move was in the right direction, adding that it offers the new ACAI team a more diversified and talented team that would transform cassava on the African continent.

“(The two projects) have a common goal, coming together is going to make the team more successful, as they share experiences,” Dr. Dixon said.

The new ACAI team at the integration and implementation planning retreat in Nairobi, Kenya

Last year, CWMP received a 2-year supplementary budget extension to join with ACAI in the dissemination of the technologies they have been developing. The weed management project began in 2014 aiming to generate relevant cassava weed management options to share with cassava farmers to help them improve their cassava production.

Among the knowledge outputs from the project include the Six Steps of Cassava Weed Management toolkit and the ABC of Weed Management in Cassava Production in Nigeria.

ACAI started in 2016 to develop decision support tools that would meet specific agronomic needs of partners actively involved in the cassava value chains in Nigeria and Tanzania. The tools are currently in the validation stage of development and slated for dissemination from 2019.

The ACAI project will be intensifying dissemination and scaling of the technologies developed by both teams.

acaiACAI and Cassava Weed Management Project Merge
read more

IITA scientists develop decision support tools to improve cassava agronomy in Africa

No comments

Scientists under the African Cassava Agronomy Initiative (ACAI) have developed decision support tools (DSTs) which can help farmers with the best recommendations for planting cassava in their fields. The new DSTs were developed to replace the older “blanket” recommendations, which did not consider site-specific conditions and thus often produced poor results. 

ACAI is a five-year project focusing on six use-cases, which reflect the different issues identified by cassava value chain actors as the most pressing problems. Each use-case has a lead scientist, supported by others to research, model, and develop the decision support tools. Fertilizer blending, the first use-case, was brought forward by the fertilizer industry because of the lack of knowledge on how to blend a fertilizer that really serves the requirements of cassava. Although there are standard formulations, they are ineffective for cassava and need to be reformulated to produce the kind of fertilizer that would demonstrate clear yield and income advantages.  

The second use-case centers on site-specific fertilizer recommendations with respect to knowing the type, quantity, method, and timing of application of fertilizer. There is feedback between fertilizer recommendation and the fertilizer blending use cases because soils across Nigeria and Tanzania are different and different soils require different formulations. The fertilizer recommendation DST considers soil properties, climate, planting and harvesting time, target yield, and resource endowment of the farmer. Thus, the fertilizer recommendation will be specific to every field and to every farmer’s capacity to invest in fertilizer. With this DST on fertilizer application, it is possible to optimize the amount of money farmers invest on fertilizers and maximize the revenue from cassava.  

Cassava field for ACAI project.

The intercropping use-case focuses on planting different crops together and particularly investigates what planting density of maize is best to attain high yields without compromising the cassava yield and the best possible use of fertilizer to increase yields and profitability. However, the best planting practices use-case does not exclusively look into methods of increasing yields but has a strong component on reducing the cost of production. This use-case was brought forward by the farmers’ association because one major constraint is the need to invest in tillage at the start of the season when neither yield nor prices are known. By reducing the initial investment to a minimum without compromising cassava root yields, the probability of attaining higher income from cassava will increase.   

The scheduled planting use-case was developed by the cassava processing industry to stabilize the supply of raw roots to factories and processing facilities. Currently, cassava supply peaks in the main harvest season and is too low before and after. The factories, however, need a certain amount of roots every day to use their capacity and to work profitably. Along with high and low supply phases come price fluctuations that can hurt both the processors and the farmers. With methods that would lead to a more uniform distribution of the cassava production across the year, prices would stabilize and factories would process at a lower cost leading to higher income for farmers and potentially lower product costs for consumers.  

The scheduled planting use-case is linked with the high-starch use-case which focuses on attaining the highest possible starch content of cassava. Many processing factories price cassava according to the starch content. This means that cassava with a higher starch content will fetch a higher price per ton. The industry is interested in high starch cassava because the extraction costs decline with higher starch content. Farmers should thus be interested in knowing how to grow cassava to achieve high starch content.  

This is the fourth year of the ACAI project. The first three years concentrated on research and development of the DSTs to help farmers with the best site-specific recommendations. Currently the project is engaging many extension agents to get training on the use of the different DSTs. Together with farmers, extension agents test the DSTs in validation plots to assess if and by which margin the yields and revenue increase when farmers follow the recommendations of the DSTs. After the validation phase, extension agents and farmers who want to use these tools can download the DSTs as apps on smartphones and apply the technology in their fields. The Global Positioning System (GPS) in the phones will read the coordinates of the field and report back to a server, which will make use of all available data to understand the situation of the field.  

In addition, the farmer needs to answer a few questions and the app will make recommendations. Farmers can then follow the recommendation and compare if the recommendation is better than their usual practice and report back if the recommendation produced higher yields and how much. These data are used to reduce the risk of incorrect recommendations and to further fine-tune the DSTs to improve cassava productivity and achieve higher incomes for farmers.

acaiIITA scientists develop decision support tools to improve cassava agronomy in Africa
read more

Modern cassava production turning around fortunes of Kisarawe

No comments

Mr. Petro Kagusi a cassava farmer from Kidete village, Mzenga ward, Kisarawe region, Eastern Tanzania is extremely happy with the new improved farming practices he has learned through the African Cassava Agronomy Initiative (ACAI) project. These include proper spacing, use of improved varieties and use of fertilizers.

“I used to grow my cassava following the traditionally ways – planting randomly, not maximizing space or using any fertilizers. The results were very poor yield, not good at all!” he said speaking to a group of journalists visiting the project’s trial on farmers’ fields in in Kisarawe district, Eastern Tanzania.

“After joining the project and learning of better ways to grow cassava including planting in rows, closer spacing and applying NPK fertilizer, I have been getting very good harvests. As farmers, we should adopt these technologies, so we can increase the crop’s production and attract investors to process cassava,” he said as he showed the media the bricks he had bought to build a new better home for his family.

Another farmer, Maria Mtanga explained that the agronomic practices they had learned under the ACAI project made operations such as weed management and harvesting easier.

Maria Mtanga speaks to members of the press who visited her farm in Kisarawe, Eastern Zone, Tanzania

Maria has been interacting with other farmers sharing the good agronomic practices learnt from the project. She said many of the farmers were willingly to adapt the technology, particularly the use of fertilizer.

“Now we need to make sure the technology (fertilizer) is accessible and available to meet the demand” she said.

Growing new varieties not good enough

Director General of Tanzania Agriculture Research Institute (TARI – one of the project’s important collaborators in the country, Dr Geoffrey Makamilo was also part of the trip.

While briefing the media, Mkamilo explained that cassava was an important crop for the district due to its proximity to Dar es Salaam. However, the cultivation of the crop in the district, like elsewhere in Tanzania, was greatly threatened by pests and diseases and use of poor farming methods.

“Several new improved high-yielding disease resistant cassava varieties have been released by researchers including Korana 1, Kiroba, Cheleko, Kipusa, Kizimbani and Mkumba. However, farmers should understand growing improved seed varieties should go hand with hand with use good agronomy practices including the use of appropriate fertilizer regimes to tap into the yield potential” he said.

“For example, if a farmer grows improved cassava varieties without applying fertilizers, they can harvest up to 10 tons of cassava per hectare, an increase from 6 t/ha from the local varieties. However, by using NPK fertilizer, the farmers, can increase production up to 60 tons of cassava per hectare,” he said,

tools  

David Ngome, ACAI project Communications Officer, added that ACAI had developed a set of decision support tools to guide agriculture extension officers on the use of good agronomic practices to boost the crop’s production.

These   included site-specific fertilizer recommendation tool and Fertilizer blending recommendation tool to maximize returns, scheduled planting recommendation tool to ensure a sustainable year-round supply of cassava to the processing industry and the high starch recommendation tool to ensure optimum starch content in the cassava roots for processing appropriate use of fertilizers, spacing and hedging

“Our fertilizer decision support tool can give very site-specific advice using satellite to locate the farmers’ location and the farmer inputting details such as planting time and variety. It is able to recommend   the amount and type of fertilizer to use and the anticipated increase in yield and income,” he said.

The project had distributed over 400tablets to the extension officers so they can be able to access and use these decision support tools, he added.

The tour engaged journalist from both the newspaper and broadcast including from the national Tanzania Broadcasting Corporation (TBC) and international German broadcaster Deutchewelle.

ACAI has been working closely with farmers and partners to develop and deploy agronomy recommendation tools to intensify cassava farming and increase root and starch yields in Nigeria and Tanzania but will expand to Democratic Republic of Congo, Ghana and Uganda.

acaiModern cassava production turning around fortunes of Kisarawe
read more

Choice Experiment to Understand Farmer Preferences for Technology Adoption

No comments

ACAI is carrying out a choice experiment exercise that is meant to help the project team understand the socioeconomic factors that influence cassava farmers’ readiness to adopt and use the decision support tools that the project is developing.

 

The experiment is a joint initiative between IITA, Tanzania Agricultural Research Institute, TARI, and the University of KU Leuven, Belgium. In the course of September and October, enumerators working with ACAI IITA staff and partners will participate in collecting data at household level from farmers working with ACAI.

Results from the experiment are expected to help the project predict and drive an efficient adoption campaign. The experiment will be looking at farmers’ willingness to intensify cassava farming and the motivation behind the willingness. The participating farmers will be taken through prepared choice experiment to select cassava growing and selling options under different circumstances with varying positive and negative outcomes.

Dr George Sonda from Tanzania Agricultural Research Institute Ukiriguru, shows the choice cards to a cassava farmer in Mkuranga, Tanzania where ACAI performed the test trial of the experiment.

ACAI is pioneering the choice experiment as a technique that will inform critical and strategic decisions for development of the dissemination strategy. Dr Pieter Pypers, IITA’s senior Agronomist and the ACAI project leader says it is “important to gain an insight into the demographic characteristics of the targeted population in order to package the decision support tool based on the finding.”

Choice experiments are famous for introducing new products in the market with a very high success rate for predicting and estimating customer behavior. ACAI is developing six decision support tools aimed at addressing specific challenges facing cassava grower that will be rolled out in Nigeria and Tanzania before finally being scaled to Ghana, DR Congo and Uganda.

To prepare for the exercise, ACAI project team held a workshop in Dar es Salaam with a team of social economists from the Tanzania Agricultural Research Institute, TARI, to craft the choice card for use in the experiment and to develop the work plan for the exercise.  Leading the workshop was Dr Pypers and IITA’s systems agronomist Dr Veronica NE Uzokwe  who is  also ACAI coordinator for East Africa. Others at the planning workshop included Audrey Vanderghinste from KU Leuven, Dr George Sonda from TARI, Ukiriguru station, Laurent Aswile from Illonga and and Bakari Kidunda from TARI Naliendele research station in Mtwara.

The exercise will start officially on the 26th of September engaging a number of households that ACAI has on the baseline study database.

acaiChoice Experiment to Understand Farmer Preferences for Technology Adoption
read more

ACAI holds Training of Trainiers to kick off DST validation in Tanzania

No comments

ACAI held a training of trainers for the Tanzanian development partners in August to kick off the validation of the ACAI decision support tools in the country.  The training was organized to create a better understanding of the ACAI use cases in Tanzania, the process of effectively evaluating the decision support tools (DSTs) and teaching reliable means of collecting feedback. This was the first step toward the planned capacity building for the project partners to carry out the validation exercises.

IITA’s senior Agronomist and ACAI coordinator for East Africa Dr. Veronica Uzokwe led the training; outlining the project approved standard protocols to be used for site selection, layout of the fields to be monitored during the validation and inputs to be used in the trial fields.

 

The two-day event was held in Mtwara, the southern Zone of Tanzania on the 14th and 15th of August 2018 with 37 people in attendance. Participants drawn from organizations partnering with ACAI in Tanzania including CAVA-II, FJS Starch Development Company, MEDA and MINJINGU Fertilizer received practical training on using the current version of the ACAI DSTs and the methodology of how to train extension agents and farmers to implement the validation exercises.

ACAI is targeting to reach more than 500 farmers in Tanzania for the validation of the DSTs using 40 extension agents pooled from the network of development partners. During the validation, farmers will run a side by side comparative cropping of their normal cassava farming practices against a plot within their fields where ACAI recommendations will be applied based on the tool that is applicable.

The project is running validation trials in the farmer’s fields for the Scheduled Planting Recommendation decision support tool (SPT), Site Specific Fertilizer Recommendation decision support tool (FR) and the Intercropping recommendation decision support tool.

Each of the partners is expected to carry out step down trainings in their respective extension networks and are tasked to monitor the extension agents they will have trained to ensure a successful implementation of the validation process for the DSTs.

Dr Desudedit Peter Mlay from the Tanzania Agricultural Research Institute, TARI, led the discussions that drew a schedule of planned activities starting from the onset of the new planting season in September.

Each partner is responsible to coordinate their extension agent network, to communicate to them the expectations from the project and maintain a close relationship with the farmers under their scope. ACAI has also developed an incentivized trial monitoring and data collection system that encourages spirited involvement of EAs and lead farmers, reward their efforts and appreciate their contribution to the project.

ACAI is carrying out validation exercises to test the version one of the decision support tools that the project has been developing. The validation kicked off in Nigeria early 2018 with similar trainings followed by step-down trainings at state and partner level.

Results and feedback from the validation exercises will be incorporated into further development and improvement of the second version of the decision support tools to improve their prediction and recommendation

acaiACAI holds Training of Trainiers to kick off DST validation in Tanzania
read more