• Data collection in terms of scientific designs should not be an afterthought. Time should be put aside to develop experimental designs and protocols for all interventions.
  • This will be key in measuring and comparing the impact of all innovations
  • Data collection is key to quantify the effect of the interventions that Milkit project is promoting. It can either be positive or negative.
  • This includes farmers perceptions and beliefs
  • All technology innovations should use a participatory technology development to foster ownership of the innovations.
  • All interventions need to have mechanisms of evaluation. Even trainings.
  • Capacity building and sensitization should be considered at all levels in the dairy value chain (farmers, extension officers, transporters etc) for proper diffusion of technologies.
  • There is need to go back to villages with results from FEAST and Techfit tools to share findings and get village specific innovations options that can be promoted by Milkit.

  • Techfit to be done on the feed in all villages of Tanzania together with mr Bwana to avoid respondent fatigue in the villages.
  • Need to get budget costs of sponsoring master’s students and see how much it costs and identify students to add to man power.
  • There is need to involve all partners in the value chain especially extension officers to assist in implementation of the on farm interventions to avoid project staff being overwhelmed.
  • Consider getting a research assistant if students are not easy to be identified.
  • Morogoro to start drafting a protocol for pasture establishment
  • Need to sit down with ben and discuss the experimental situation in Tz to see how data can be harvested and get some information to publish.
  • Quantitative data could include number of animal remaining in at farm or amount of days feed sustains animals in the dry season or plant productivity of the forage established on demo plots in Mbwade.