From africa-rising-wiki
Jump to: navigation, search

Africa RISING ESA Project Partners Meeting
3 June 2021
Virtual via Ms TEAMS
[edit | edit source]


  1. A. Kimaro, ICRAF
  2. B. Zemadim, ICRISAT
  3. C. Azzarri, IFPRI
  4. C. Thierfelder, CIMMYT
  5. D. Mgalla, IITA
  6. E. Swai, TARI-Hombolo
  7. F. Kizito, IITA
  8. F. Muthoni, IITA
  9. G. Fischer, IITA
  10. I. Dominick, WorldVeg
  11. I. Hoeschle-Zeledon, IITA
  12. J. Groot, WUR
  13. J. Kihara, Bioversity-CIAT
  14. J. Manda, IITA
  15. J. Odhong, IITA
  16. L. Claessens, IITA
  17. M. Bekunda, IITA
  18. M. Mutenje, IITA (consultant)
  19. P. Okori, ICRISAT
  20. R. Chikowo, MSU


  • Ex-ante impact assessment of Africa RISING seed and fertilizer technologies in Tanzania with trade-off analysis model for multi-dimensional impact assessment- Dr. Lieven Claessens (IITA)
  • Understanding the potential contributions of ISFM to various sustainable intensification impact domains - Dr. Job Kihara (CIAT)

File:JR 3June ESAPPT.pptx - Dr. Job Kihara (CIAT)

  • Download presentation from link in the title above.


  • Irmgard. How can the difference in adoption of ISFM components between farmers in Babati and K/K be explained? Which are the components that the low adopters do adopt?
  • Job. Well, Irmgard, for the difference in adoption of the ISFM components, it is something that we have considered by looking at various components, and how the intensity of the ISFM influence multiple indicators. For example, in Babati, we presented those farmers with one component and their percentage ( those who are practicing ISFM and the practiced technology). In the writeup, we specified rates in portion, e.g., 65% of one ISFM group are all intercropping. We have those types of tendencies explained in the text and the presentation of the figures and the ISFM components.
  • Irmgard. Okay, may you explain why are Babati farmers adopting more components than Kongwa and Kiteto farmers?
  • Job. Well, because Babati is a high-potential environment, they already have adopted improved varieties. Therefore, penetration of improved varieties is very high in Babati, and many of the farmers in the area, at least 75% > of the farmers practice intercropping. For Kongwa and Kiteto, the situation can be fascinated by the nature of the environment and may not be high penetration of improved varieties. It can probabilistically explain the different uses of ISFM components.
  • Irmgard. So, from the farmer, the need for these ISFM components would be high in Kongwa Kiteteo than Babati?.
  • Job. I think so. But for the scaling perceptive, there might be less information going in Kongwa Kiteto relatively to Babati. In Babati, we would expect to see farmers practicing five components, but, in this case, we have farmers with only two or three components. I still feel there should be a push to make farmers go to four to five. But Yes, Kongwa Kiteto will be essential to make interventions on including these practices.
  • Job. I was shocked to find 0% components from 22% of farmers, any comments from someone in Kongwa Kiteto?
  • Antony. To add up, the low adoption in Kongwa Kiteto can be because the ISFM components that go viral within the short period in this area is the water aspect, and depending on the technology, for example, the tied ridges has been a need in this area, for other technology like Chororo; the planting phasing goes very fast. Therefore, the easier of implementing the technology that captures water, farmers are quickly picking up. It can be one of the ISFM components that can bring up many things, but to what extent has that been captured and under which technology? is something we can look at the data set that Job has.
  • Shitindi. In addition to Dr. Job and Antony, the other factors can be access to the market. Babati has more access to the market of the ISFM technologies, primarily for the Legumes (pigeon pea) than farmers in Kongwa Kiteto. Since this has something to do with the financial muscles, and there are investments, the rate of the reinvestments with the ISFM has something to do with the adoption rate.
  • Irmgard. Thanks, Shitindi, but do you mean input or output market?
  • Shitindi. I mean output market, Irmgard.
  • Swai. To contribute to Shitindi, Antony & Job’s comments on the issue of adaption, adoption is complicated because some of the ISFM technologies, like tied ridges, require massive labor. Hence the rate of adaptation cannot be similar when we compare the nature of labor requirements. Technologies such as mechanization are labor-saving. Currently, there is another survey going on where Kongwa is a part of it. The Kongwa Kiteto team may note that the current level of intensification, maize and pigeon pea component is becoming common like Babati. If we refer to the adoption level of ISFM using pigeon pea in Kongwa Kiteto, we can note the variations. The soil water technology is labor-intensive on one side, and mechanization technology is imperative for many farmers to pick up the technology.
  • Carlo. Job, how can the differences in yields computed among AR farmers be attributed to the AR project and not other intervening/confounding factors?
  • Job. It is unclear if it applies in this case but will use in the survey we are conducting. We have tried to categorize our intervention farmers and farmers whom we did not have an intervention with (the control farmers), and we have records of the list of all our farmers and use the data to set the proportion of the farmers that we will interact with and farmers how are not part of us from the project site to show the difference between those who have interacted with the AR project vs. those who have not. On the other hand, we want to access the initial farmers with the project and identify farmers who had been/ not been considered to see if there will be attributions that can be done. We are doing this with Julius Manda
  • Shitindi. Job, from the presentation, most of the domains are presented by the number of the ISFM components adopted by the farmers, but labor requirements also increase with the number of components adopted. We may establish the label of combinations of these components that people can see the most rewarding in terms of labor investment?
  • Job. I will consider that as something that we can interact with the data set and see how we can enrich our publication with what you have contributed to us.

File:June 3 Seminar presentations Lieven 3June ESAPPT.pptx - Dr. Lieven Claesse (IITA)

  • Download presentation from link in the title above.


  • Carlo. Lieven, why did you conduct the study using the LSMS data that expand across full of Tanzania and not TARBES data? while the information is essentially the same, beside, data were collected among farmers in AR districts with and w/out AR technologies!
  • Lieven. In general, it is ambitious, and it’s the assumption that we had to take. Since the big goal is upscaling, I thought it was a nice try to bring this to the national scaling with all the uncertain things, and there was an assumption we had to make. But I would be happy to exercise with the TARBES data. However, TARBES data is still limited to those two study areas (Babati & Kongwa Kiteto) right?. .
  • Mateete. Yes, Lieven. It is essential for AR project before you go wide nationally. So, if the TARBES data are used to do the second analysis, I think it would be interesting for the project. Because scaling out even within Babati, we work in fewer areas than the full descriptions or even in Kongwa Kiteto. So, the TARBES data would work out okay.
  • Carlo. Lieven, why is this study called ex-ante impact assessment? It looks like scenario modeling to me.
  • Lieven. I don’t know the entail difference Carlo, but we did scenarios regarding the realist yields. For the impact assessment, we refer to the actual adaption rates or predictive adoption rates.
  • Comment. Mateete. There is a need to put all the presentations together and stragetical plan on how we could produce a project legacy docuement from the PPT slides presented. It can be of interest, so there is a need to look at the presentations again and discuss further.