An Economic Assessment of Banana Genetic Improvement and ...

ASSESSING THE IMPACT OF TECHNOLOGIES IN UGANDA 147
Table 10.6 Definition of technology scenarios and selected research parameters
Technology scenario
Probability of
research success a
(percent)
R&D
time lag b
(years)
Potential yield
loss avoided c
(percent)
Scenario Group 1: Increased adoption of current best practice
1. Improved agronomic and IPM practices for management of weevils n.a. n.a. 40
2. Improved agronomic and IPM practices for management of nematodes n.a. n.a. 30
3. Improved agronomic and IPM practices for management of black Sigatoka n.a. n.a. 30
4. Improved agronomic and IPM practices for management of bacteria wilt n.a. n.a. 30
5. Improved nutrient management: inorganic and organic fertilizers, mulch n.a. n.a. 80
6. Adoption of introduced multipurpose hybrids (such as FHIA17) n.a. n.a. 80
Scenario Group 2: Conventional crop improvement
7. Improved resistance to weevils 63 15 38
8. Improved resistance to nematodes 48 15 29
9. Improved resistance to black Sigatoka 78 15 21
10. Improved resistance to bacteria wilt 18 15 13
Scenario Group 3: Genetic modification
11. Genotype with resistance to weevils 78 12 63
12. Genotype with resistance to nematodes 53 12 63
13. Genotype with resistance to black Sigatoka 68 12 54
14. Genotype with resistance to bacteria wilt 68 12 71
Source: Extracted from expert consultation survey results database.
Notes: These estimates were used in setting upper bounds on losses at the end of the plantation life cycle. IPM denotes integrated pest
management.
a The most likely probability of achieving research success for the specified technology (technologies for Scenario Group I are already
available by definition).
b The most likely lag time in years before research would be successful. In the case of biotechnologies, this value includes time for
regulatory testing and approval processes.
c Indicative of value of potential yield losses that could be avoided if the specific technology were successfully developed and adopted.
More specific assessments of avoided yield losses (expressed as decreases in the unit cost of production) were made for each technology
scenario for each of the six banana production systems over a system-specific plantation life cycle.
the technology innovation might be able to
mitigate. As depicted in Figure 2.3 of Chapter
2, the innovation mitigates but does not
eliminate the negative impacts of biotic constraints
on banana yields. In addition, because
technologies and practices already
exist for the current best practice (Group 1)
scenario, the probability of research success
and R&D time lags are irrelevant.
Experts considered that improved resistance
to black Sigatoka through conventional
breeding and improved resistance to
weevils through transgenic approaches are
the most likely scientific outcomes (78
percent probability of success). They considered
the development of bacteria wilt resistance
through conventional means (18
percent) to be least likely. Banana improvement
through conventional approaches is
expected to take longer (15 years) than
through genetic transformation (12 years),
because of the challenges described in
Chapter 4. Thus, time lags for genetic modification
scenarios are shorter, even allowing