Technologies for intensification in SW Uganda ... - Foodnet - cgiar

y the African Highlands Initiative. In the more detailed technology tables, we again used first
hand knowledge, but also read documents of NARO (South western highland farming systems
improvement programme, workplan 2001-2003, Technology Development and Transfer Nation-
Wide Survey, and NARO Annual Reports) and held discussions with extension and NGOs to
provide more details on the technologies (e.g. which varieties or species are being tested; which
management options are being developed in tandem.)
Status: This is a subjective measure of the stage of dissemination of a technology in the
southwest. This subjective measure substitutes for a more rigorous (but unattainable) count of
households or mapping of areas using the technology. For the evaluation matrix, this assessment
is generalized for the southwest – a more rigorous but costly method would have been to assess
the spread of technology district by district. There are six possible cases: 1) on station only, 2)
on-farm testing, 3) pilot location, 4) initial dissemination, 5) wide dissemination, and 6) common
option for farmers. The knowledge of the team was the main source of information for this. The
technology tables (Appendix 2) do provide a bit more information about the status.
Soil impact: This captures the impact of the technology on soil fertility and conservation. In
some cases, experimental data could be found to compare across a certain number of treatments.
Where absent, expert opinion was sought. This criterion is most useful when comparing types of
technologies within the same general category, such as alternative technologies for soil
conservation. Comparisons between a soil conservation practice and a soil fertility practice are
not warranted. Moreover, while it is possible to assess crops and varieties on their ability to
provide ground cover or to efficiently use available nutrients, there was insufficient information
on which to do this systematically. So for such types of technologies, we have only noted the
cases where clear evidence suggests a significant impact. For indicator values, we have reduced
this to 5 outcomes: excellent/very good, good, fair, poor/neutral, and negative.
Diversity: This variable examines the impact of the technology on biodiversity at the landscape
level. This mainly involves an assessment of the range of species/varieties/provenances suitable
for the use of the technology in the southwest. Where indirect effects on biodiversity are clear,
these are also considered.
Productivity: An attempt was made to find data on yield effects of technologies. For instance,
these could be the yield-enhancing effects on crops of soil fertility practices, new varieties, pest
management strategies, or even soil conservation methods. We also looked at the livestock sector
and the productivity enhancing capacity of new feed strategies. For wood or fruit production
systems, productivity would be the yield of the tree products. Data were often available from onstation
trials, but little information is available from farmers’ experiences. Using this information,
we were able to assign qualitative rankings (the technology tables retain the quantitative measures
where available). When quantitative data were unavailable, we often were able to assign relative
value based on expert opinion of performance relative to other known technologies (e.g. a new
variety compared against a well known variety). In the evaluation matrix, we use the same 5
impact outcomes: excellent/very good, good, fair, poor/neutral, and negative.
Income: Income depends on a number of factors, the quantity produced, the amount of
production that can be sold and the price received for the quantity sold. Production has been well
covered by the previous criterion so this variable reflected principally the output price (less any
input costs) and the ability of producers to sell their output. Data on prices were easy to establish
as were average yields per crop. These served to provide an indicator of potential gross revenue.
This indeed was the principal driver of the “income” evaluation. But this was conditioned by the
extent of the market, which was assessed through consultations with local traders, extension
26