




































In ternationa l
Scholars
Journa ls

 

African Journal of Agricultural Marketing ISSN 2375-1061 Vol. 5 (8), pp. 001-012, August, 2017. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s)                                           Author(s) retain the copyright of this article. 
 
 

 

Full Length Research Paper 

 

Farmers’ awareness and application of banana 
Xanthomonas wilt control options: The case of 

Uganda and Kenya 

 
Wellington Jogo1*, Eldad Karamura1, Jerome Kubiriba2, William Tinzaara1, Anne 

Rietveld1, Margaret Onyango3 and Michael Odongo4
 

 
1
Bioversity International, P. O. Box 24384, Kampala, Uganda. 

2
Kawanda Agricultural Research Institute, P. O. Box 7065, Kampala, Uganda. 

3
Kenya Agricultural Research Institute, P. O. Box 523, Kisii, Kenya. 

4
Rural Energy and Food Security Organization, P. O. Box 751-50400 Busia, Kenya. 

 
Accepted 13 April, 2017 

 
Banana is a key staple and cash crop in east and central Africa. However, the recent outbreak of Banana 
Xanthomonas wilt (BXW) has threatened farmers whose livelihoods depend on the crop. Since 2002, stakeholders 
embarked on campaigns to sensitize farmers on the disease and its management. This study evaluated the 
effectiveness of these efforts by examining farmers’ awareness of the disease, control options and their 
application in Uganda and Kenya. Data on BXW distribution and incidence, farmers’ awareness of symptoms, 
mechanisms of spread and control options of the disease and banana production were collected through 
household surveys conducted in 2010. The results indicated that most farmers (> 90%) were aware of the disease 
and its symptoms and more than 50% were aware of the recommended control measures. Farmers obtained 
information on the disease from multiple sources but farmer-to-farmer interaction was the main source suggesting 
the key role rural social networks play in managing the disease. Not all affected farmers were able to apply control 
measures due to cost of intervention, lack of labour and inputs. The study recommends strengthening of linkages 
among stakeholders for better coordination of efforts and participatory development and promotion of farmer-
oriented interventions that address farmer constraints. 

 

Key words: Banana (Musa spp), Xanthomonas wilt, awareness, control measures, households. 

 
INTRODUCTION 

 
Banana (Musa spp) is an important crop in east and 
central Africa. Apart from being a key staple food in the 
region, the crop is an important source of income for 
resource poor farmers (Karamura et al., 1998). Despite 
its importance, the crop has been quickly losing ground 
as a dependable crop due to several biotic and abiotic 
constraints. Until the beginning of the century, the main 
biotic threats (weevils, nematodes, fungal and viral 
diseases) were managed using cultural methods. In this 
way farmers suffered reduced productivity but maintained 
reasonable levels of food and income security. However, 
following the arrival of banana Xanthomonas wilt (BXW)  
 
 
 
*Corresponding  author.  E-mail:  W.Jogo@cgiar.org.  Tel:  +256 
414 286 213. Fax: +256414286949. 

 
 
 

 
(caused by Xanthomonas campestris pv. musacearum) in 
the region, entire crop holdings were wiped out in some 
areas where highly susceptible genotypes were 
dominating the farming systems. Up to the 1960s, the wilt 
was known only in Ethiopia, occurring in both bananas 
and enset. In 2001, the disease was reported in central 
Uganda (Tushemereirwe et al., 2001) and in north Kivu 
Province of DR Congo in 2003 (Ndungo et al., 2006) and 
in Rwanda in 2005 (ISAR, 2007). Between 2002 and 
2006, the disease spread to the major banana growing 
regions of Uganda, western Kenya, and other countries in 
Central Africa, where it reportedly caused 80 to 100% 
crop loss, especially in beer bananas (ABB genome) in 
Uganda and DR Congo (Ndungo et al., 2006). Such 
losses drastically affected food security and incomes for 
the poor and vulnerable farmers.  

All banana cultivars in eastern Africa, including endemic 

file:///C:\Users\user\Documents\REPUBLICATION\AGRICULTURAL%20SCIENCES\AppData\Local\Temp\www.internationalscholarsjournals.org


 
 
 

 

highland cooking and brewing cultivars (AAA-EA), exotic 
brewing, dessert and roasting types (AB, AAA, AAB, 
ABB), and hybrids, are susceptible to the disease. No 
cultivars with BXW resistance have so far been identified. 
Some cultivars, e.g. Pisang awak (ABB) are particularly 
susceptible to insect vector transmission and are believed 
to facilitate the spread of BXW (Tushemereirwe et al., 
2003). The first symptoms of floral infection by BXW 
include discoloration at the tip of the flower and withering 
of the flower bracts. This is followed by drying of the 
rachis, premature drying and rotting of bunches and 
eventually wilting and death of the whole plant. In the 
vegetative phase, the symptoms include yellowing, wilting 
and eventually death of the whole plant. When the 
banana pseudostem is cut, yellow ooze in the real stem 
confirms presence of the disease. This discoloration is 
diagnostic and is observable even where other symptoms 
are not yet manifest.  

As a result of the severity of the disease, regional 
stakeholders developed a management strategy in 2005 
(Karamura et al., 2006) based on what was known about 
the mode of spread of other similar bacterial wilt diseases 
of banana (e.g. Moko and Blood diseases). Removal of 
male buds is instrumental in preventing possible insect 
and/or bat transmission of the disease. Destruction and 
disposal of infected plants, disinfecting tools used in the 
plantation, avoiding using planting materials from infected 
areas, replacing bananas with other crops and quarantine 
measures are the other recommended practices. These 
cultural practices, if adhered to, should slow but may not 
completely prevent the spread of BXW (Karamura et al., 
2008). Since 2002, intensive campaigns were mounted 
across the region to create awareness on the disease 
and educate farmers about its diagnosis, prevention and 
recommended control practices through posters, 
brochures, newspaper inserts, calendars, radio and 
several other participatory development communication 
approaches. However, little is known about the 
effectiveness of these efforts in raising farmers‟ 
awareness of the disease, control options and their 
application and how these may be influenced by farmers‟ 
agro-ecological and socio-economic context.  

The objective of this study, therefore, was to assess 
farmer-level awareness of BXW, its effect on production, 
control options and their application in the main banana 
cropping systems using data from Uganda and Kenya. 
The results of this study should generate insights that will 
inform policy-makers and stakeholders in the banana 
sector on possible interventions for managing BXW and 
reduce its impacts on food security and incomes of poor 
farmers. 
 
 
METHODOLOGY 
 
This study was carried out in Uganda and Kenya. In Uganda, the 
study targeted the two main banana cropping systems: the „Kayinja‟ 
beer banana (ABB genome) and the East African highland banana 
(EAHB) „Matooke‟ (AAA-EAHB) based systems. The AAA-EAHB 

 
 
 
 

 
types are produced by farm households mainly for food security 
purposes, while the ABB types are largely market-oriented. The 
Kayinja system is located mainly in central Uganda, and is usually a 
mix of bananas and other crops (e.g. coffee, cassava and trees) 
while the EAHB based system is mainly found in the south western 
parts of Uganda, on relatively fertile soils and with low banana pest 
pressure. The EAHB system is more intensively managed (with 
frequent pruning, weeding, de-budding) than the Kayinja system. 
Accordingly, BXW transmission in the EAHB system is mainly 
through farm tools while in the Kayinja system, insects are the main 
mechanism of transmission.  

In Kenya, one district from the western part of the country 
(Ugunja division, Siaya district) where the disease is prevalent and 
banana is a key crop for farm households was selected. In this 
area, the banana production system is dominated by dessert 
bananas including Kivuvu (ABB genome), Sukari Ndiizi (AB 
genome), Cavendish (AAA genome) but also has significant Kayinja 
and EAHB bananas (Mbaka et al., 2009). In general, management 
of banana fields is less intensive in Kenya than in Uganda. In both 
countries, household surveys were conducted in May to September, 
2010 to collect data using a structured questionnaire. A similar 
questionnaire was used in both countries, although minor 
adaptations were made to capture contextual differences. The 
questionnaire solicited data on household socio-economic 
characteristics, BXW distribution and incidence; farmers‟ awareness 
of disease symptoms, mechanisms of spread and control 
measures, banana production, coping mechanisms and livelihoods 
strategies. In Uganda, a multi-stage stratified random sampling 
design was used to select households for the survey. The two main 
banana systems described earlier were the sampling units for the 
first stage.  

A total of ten districts were purposively selected to represent the 
two banana systems in the country, six for the EAHB system 
(Isingiro, Mbarara, Masaka, Bushenyi, Ibanda and Ntungamo) and 
four from the Kayinja system (Kiboga, Mityana, Mubende and 
Mpigi). Occurrence of the disease and period since the disease was 
first observed were also considered in selecting the districts for the 
survey. Within each of the selected districts, communities were 
mobilized to control BXW using three main extension approaches:  
1) farmer field schools, 2) community-based extension and 3) 
traditional top-down extension approach. For example, there were 
over twenty communities who were mobilized using farmer field 
schools in each of the cropping systems, three of which were 
randomly selected for this study. Likewise, three communities were 
randomly selected among those who were mobilized using 
community and traditional approaches in each district. Households 
in each of the selected communities were then stratified according 
to the banana marketing strategy they use: group versus individual. 
To take into account farm size, the households were further 
stratified according to farm size into large (>2 acres) and small 
farms (<2 acres) and twenty households were randomly selected in 
each stratum. The final sample of households interviewed in 
Uganda consisted of 350 households.  

In Kenya, the cropping systems and technology transfer 
approaches used for mobilizing farmers for BXW control were more 
or less similar across the country and hence one district was 
selected for the survey. A total of 52 households were randomly 
sampled from six locations in the district. Descriptive frequencies 
were used to analyse farmers‟ awareness, sources of information, 
application of BXW control measures and coping strategies in the 
two study countries. Comparative statistics (means, frequencies 
and cross tabulations) with statistical tests for significance were 
used in examining differences in various factors across sites and 
cropping systems (t-tests and chi-square tests). The impact of 
disease on banana production and sales was first analyzed by 
comparing the significance of the difference in mean banana 
production and sales before and at the peak of the disease using a 
paired t-test statistic. 



 
 
 

 
In order to obtain robust estimates of the impact of the disease 

on banana production and sales, a combination of propensity score 
matching (PSM) and difference-in-difference or double difference 
(DID) approaches was applied. PSM is used to match affected 
households (the treated group) with non-affected households (the 
control group), based on similarity in observable socio-economic 
characteristics (Barker, 1999). This controls for selection bias 
arising from differences in observable characteristics between the 
two groups. Bias due to unobservable time-invariant characteristics 
(e.g. ability of farmers, inherent quality of natural resources) or 
common trends affecting both groups equally (e.g. prices, weather) 
was addressed by using the DID approach (Barker, 1999; Smale et 
al., 2008; Davis and Nkonya, 2008). Combining the two nets out, 
both observable and unobservable factors that affect the outcome 
variable and in principle produces impact estimates that are more 
plausible than those based on a single difference (either overtime, 
as is the case with the paired t-test statistic highlighted earlier or 
between groups) (Nkonya and Davis, 2008). Because the sample 
size for Kenya was very small, the impact analysis using PSM and 
DID was only done for Uganda. 
 

 

RESULTS AND DISCUSSION 

 

Socio-economic characteristics and importance of 
banana in the study countries 

 

The demographic characteristics of the interviewed 
households in the two countries are summarized in Table  
1. Age of household head averaged in the forties in both 
countries was not significantly different between the two 
sites. Similarly, the average education level of household 
head for the two countries was not significantly different 
with most of the household heads not having gone 
beyond primary education. However, while there was no 
significant difference in the number of years living in the 
area between the two study countries, households in 
Uganda had significantly more farming experience than 
those in Kenya. Results on the importance of bananas in 
farming systems in the two countries are presented in 
Table 2. The results show that mean farm size per 
household was significantly higher in Uganda than in 
Kenya. In both countries, banana was an important food 
and income crop.  

However, the crop was more important in Uganda than 
in Kenya, as evidenced by the fact that more than 70% of 
the interviewed households in Uganda grew banana as 
the main crop compared to only 10% in Kenya. 
Accordingly, households in Uganda allocated a signi-
ficantly higher proportion of their farmland to banana 
production, invested a higher proportion of their income in 
banana production and consumed banana products more 
frequently than their Kenyan counterparts. In Uganda, the 
percentage of households growing banana as the main 
crop and the proportions of farmland under banana and 
household monthly income from banana were 
significantly higher in the EAHB system than in the 
Kayinja system. This confirms the special position of East 
African highland cooking „Matooke‟ bananas in the 
livelihoods (food security and income purposes) of rural 

  
  

 
 

 

households in the country. The difference in importance 
of banana for farmers in the two systems may influence 
their decision to invest in BXW control. 
 
 
Farmer awareness and application of BXW control 
measures 

 

In both countries, more than 70% of the interviewed 
farmers had their farms affected by BXW. All interviewed 
households were aware of the disease and its symptoms. 
In line with findings from previous studies (Ngambeki et 
al., 2006; Bagamba et al., 2006; Muhangi et al., 2006) 
this study found that the three main recommended BXW 
control measures of removing male buds with a forked 
stick; destroying infected plant material (through different 
approaches of cutting of pseudo stem of affected plants; 
cutting down and bury whole mat of diseased plants); and 
disinfecting cutting tools were widely known and applied 
by farmers in Uganda (Table 3). Destroying affected 
plants through cutting of affected pseudo stem; cutting 
and dig down whole mat of affected plants and removal of 
male buds with cutting tools were the most widely known 
and practiced control measures in Kenya. Contrary to the 
results in Uganda, removal of male buds with forked stick 
and disinfecting of farm tools were known and practiced 
by very few farmers in Kenya. The limited application of 
removal of male buds with forked stick by farmers 
supports an earlier finding by Mbaka et al. (2009) that few 
farmers in western Kenya carry out this practice and do it 
not with the intention to control BXW, but to use the male 
bud as a stopper for water containers. 
 

Although the use of cutting tools in de-budding is 
discouraged by researchers and extension practitioners, 
a significant number of farmers in both countries were still 
using cutting tools for de-budding (29 and 39% in Uganda 
and Kenya, respectively). This demonstrates that a 
significant number of farmers were still not aware of the 
potential danger posed by cutting tools in transmitting the 
disease both in-field and across fields. Future awareness 
campaigns need to emphasise on enhancing farmer 
understanding of the rationale behind different practices 
and the motive behind discouraging certain practices 
such as the use of cutting tools. In both countries, putting 
restrictions on movement of plant material (including 
suckers) to contain the spread of disease to disease-free 
areas was less practiced. More than 90% of the farmers 
in both countries used suckers from their own fields or 
from neighbors, thereby increasing the chances of 
spreading the disease across farms through planting 
material. With the exception of a few practices, more 
farmers under the EAHB system were applying BXW 
control measures than under Kayinja system (table 4), as 
the former is more important to the farmers‟ livelihoods 
and therefore farmers are more willing to invest in 
disease control in that system than in the latter.  

A comparison of the percentage  of households  aware 



 
 
 

 
Table 1. Socio-economic characteristics of interviewed households in Uganda and Kenya.  
 
 Uganda (n=350)  Kenya (n=52) Statistical tests for significance 

Socioeconomic characteristics EAHB system Kayinja system Sample Dessert system t-values (comparison of t-values (comparison 
 (n=172) (n=178) (n=350) (n=52) EAHB and Kayinja) of Uganda and Kenya) 

Age of household head (years) 44 47 46 48 2.02** 1.15 

Education of household head (years) 6 8 7 7 4.55** 1.31 

Years living in area 28 29 28 29 0.25 0.19 

Years in farming 23 25 24 19 1.25 2.21** 

 

     χ 2 
      values 

Gender of household head (%) : Male 49 53 51 65 0.48 1.33 

Female 51 47 49 35   
 
** Significant at 5%. 
 
 

 

of the different control measures with those 
applying them shows that in both countries, not all 
of those who knew the control measures were 
actually applying them. For instance, in Uganda 
82% were aware of the removal of male buds 
using a forked stick as a control measure but only 
67% were practicing this control measure. The 
same trend can be observed for the other control 
measures and also for Kenya. The worst case 
scenario is where farmers were not practicing any 
control measure despite their farms being infected 
with the disease and knowing the control options. 
However, in Uganda only 3% of affected 
households did not apply any control measure 
(26% in Kenya), suggesting that the majority of 
farmers believed the disease could be 
successfully controlled. Limited application of 
practices that farmers were aware of was 
attributed to several constraints (Table 5), 
including high cost of application (e.g. disinfecting 
of farm tools), lack of labour (e.g. cutting down 
and burying whole mat of affected plant) and 
ineffectiveness of control measures. Concerns 

 
 
 

 

raised by some farmers about ineffectiveness of 
some control measures in controlling the disease 
(e.g. debudding with forked stick) could be due to 
incorrect application of such control measures.  

For instance, a study by Muhangi et al. (2006) in 
Uganda found that farmers who de-bud using a 
forked stick or cutting tools did it late (normally 
when fingers have turned upwards). In their study, 
they argued that such incorrect application of the 
control measure could explain the claims by 
farmers that removal of male buds is ineffective in 
controlling the disease. These findings suggest 
the need to go beyond just creating awareness of 
existing control measures but also equip farmers 
with skills on correct application of these 
measures. Most farmers were aware of more than 
one control measure and those controlling the 
disease were mostly applying combinations of 
control measures (Table 3). That explains why the 
percentage of farmers aware or applying the 
different practices add up to more than 100%. 
Whilst most farmers were applying more than one 
control measure, few were deploying the full 

 
 
 

 

package of control measures (using removal of 
male buds with fork stick, destroying infected plant 
material and disinfecting tools simultaneously) 
and as a result few farmers were able to eradicate 
the disease from their farms. The main sources of 
information on BXW control measures are 
presented in Table 6. The results show that 
farmers obtained information on BXW control 
measures from multiple sources. In both 
countries, friends/neighbours and extension were 
the main sources of information for farmers.  

However, the fact that friends/neighbours played 
a key role in disseminating BXW infor-mation, 
demonstrates the importance of social networks 
(such as farmer associations, farmer field schools 
and community-based extension approaches) in 
raising awareness and improving adoption of 
BXW control measures. An interesting contrast 
between the two countries is that while 
researchers played some role in disseminating 
information in Uganda, they played no role in 
Kenya. There is evidence that community-based 
organizations, such as schools, churches and 



  
 
 

 
Table 2. Comparative analysis of the importance of banana in farming systems in the two countries.  

 
 Uganda (n =350)  Kenya (n=52) Statistical tests for significance 

 

Parameter 
EAHB Kayinja 

Sample 
Dessert t-values t-values 

 

system System system (comparison of (comparison of  

 (n=350)  

 

(n=172) (n=178) (n=52) EAHB and Kayinja) Uganda and Kenya) 
 

  
  

Farm size (acres)  
Mean farm size under banana (acres)  
Proportion of farm size allocated to banana (%)  
Proportion of monthly household income from banana (%) 

 
Proportion of household income invested in banana 
production (%) 

 
Mean number of times banana products are consumed 
per week per household 

 
 

6 9 8 4 1.49 1.43* 

2 2 2 0.5 1.21 5.12*** 

63 31 49 14 11.72*** 7.85*** 

43 17 29 27 7.06*** 0.14 

15 14 12 9 0.24 1.22*** 

9 10 7 0.3 0.55 10.89*** 

     χ 
2
  values 

 
Grow banana as (%): Main crop 91 56 73 10 57.23*** 101.14*** 

Secondary crop 9 44 27 90   

Grow banana as (%): Food only 16 31 24 10 18.29*** 49.86*** 

Cash only 1 3 2 2   

Both 83 66 74 89   
 

*, **, *** Significant at 10, 5 and 1% respectively. 
 
 

 

market places also played a role in disseminating 
information on the disease in both countries, albeit 
small. The fact that farmers received information 
from multiple sources, raises concerns about the 
possibility of farmers receiving conflicting 
messages from different sources.  

In their study on BXW in Uganda, Bagamba et 
al. (2006) reported that farmers raised concerns 
over receiving different information from different 
sources. The implication of this finding is that 
there is need for better coordination and 
strengthening of linkages among stakeholders 
(researchers, extension, farmers, media, non- 

 
 
 

 

governmental organisations and community-
based organisations) and build synergies in 
fighting against the disease. 
 

 

Impact of BXW on farm production, income 
and household coping strategies 
 

Impact on banana production and sales 

 

To ascertain the impact of BXW on banana 
production and incomes at household level, 
farmers were asked to provide estimates of their 

 
 
 

 

banana harvest and sales levels per month (a 
monthly time step was thought to be shorter and 
easier recall period for farmers than a year) before 
and at the peak of BXW. The impact of the 
disease on banana production and sales was first 
analyzed by testing the significance of the mean 
monthly banana harvest and sales per household 
before and at the peak of BXW attack in each 
country using a paired t-test. The results, which 
are presented in Table 7, show that in both 
countries banana harvest and sales levels fell 
drastically at the peak of BXW attack. In Uganda, 
average monthly banana harvest levels per 



 
 
 

 
Table 3. Farmer awareness and application of BXW control measures in Uganda and Kenya.  

 
  Uganda (n=350) Kenya (n=52) 

 

 
Practice Percentage of Percentage  of Percentage of Percentage of 

 

 

households households households households 
 

  
 

  aware currently applying aware currently applying 
 

 Cut down affected pseudo stem of affected plant 74 65 57 41 
 

 Cut down and dig up the whole mat of affected plants 59 41 45 39 
 

 Bury plant remains 49 32 6 2 
 

 Burn plant remains 23 8 4 - 
 

 Heap affected plant remains and leave on ground 35 29 10 6 
 

 Left on ground but not heaped or buried 13 11 6 4 
 

 Remove male buds of affected plant with fork stick 82 67 12 8 
 

 Remove male buds with cutting tools 41 29 45 39 
 

 After cutting, clean tools (JIK/fire) 77 64 4 4 
 

 Treat with concoction 21 16 8 6 
 

 Do not sell or move any fruits, leaves, or suckers outside a disease area 18 14 4 - 
 

 
 

 
Table 4. Proportion of farmers (%) applying control measures by banana cropping system.  

 
  Uganda (n=350)  Kenya (n=52) 

 

 Practice Kayinja system EAHB system χ 2 Dessert  

  
 

  (n=178) (n=172)  system 
 

 Cut down affected pseudo stem of affected plant 80 53 37.31*** 41 
 

 Cut down and dig up the whole mat of affected plant 30 53 14.31*** 39 
 

 Bury plant remains 7 58 88.62*** 2 
 

 Burn plant remains 11 5 5.4** - 
 

 Heap affected plant remains and leave on ground 36 22 9.32*** 6 
 

 Left on ground but not heaped or buried 2 6 11.21*** 4 
 

 Remove male buds of affected plant with fork stick 65 69 2.31 8 
 

 Remove male buds with cutting tools 25 35 4.29** 39 
 

 After cutting, clean tools (JIK/fire) 58 70 6.67** 4 
 

 Do not sell or move any fruits, leaves, or suckers outside a disease area 11 20 5.27** - 
 

 
 

 

household dropped by 57%, while sales fell by 
67% at the peak of BXW infection. Similarly, in 

 
 

 

Kenya, farmers experienced an average of 77% 
reduction in pre-infection banana harvest levels 

 
 

 

while sales fell by 80%. Comparing the production 
impacts in the two countries, we observe that the 



  
 
 

 
Table 5. Farmer constraints to application of different BXW control measures (% of farmers reporting) in Uganda.  

 
   Practice application constraints (% of farmers)  

 

 Practice  Lack of labour (or Technology does not  
 

 

Expensive technology is labour work (ineffective in Spreads BXW 
 

  
 

   intensive) controlling BXW)  
 

 Cut down affected pseudo stem of affected plant 17 17 11 - 
 

 Cut down and dig up the whole mat of affected plants 15 31 2 - 
 

 Bury plant remains 20 22 10 - 
 

 Burn plant remains 17 29 14 - 
 

 Heap affected plant remains and leave on ground 12 16 12 - 
 

 Left on ground but not heaped or buried - 18 9  
 

 Remove male buds of affected plant with fork stick 2 17 9  
 

 Remove male buds with cutting tools - 5 - 16 
 

 After cutting, clean tools (JIK/fire) 33 13 13 - 
 

 Treat with concoction 10 17 2  
 

 Do not sell or move any fruits, leaves, or suckers outside a disease area  7 7.  
 

 Destroy all infected plants until disease has gone away - 11 - - 
 

 
 

 

disease had more severe effects on banana 
production in Kenya than in Uganda presumably 
because farmers in Kenya had less farming 
experience (Table 1) and accordingly possessed 
less experience in managing agricultural risks 
associated with pests and diseases than their 
Ugandan counterparts. This result could also be 
attributed to the fact that farmers in Kenya put less 
effort and invest less resources in managing the 
disease, as banana is grown largely as a 
secondary crop. Also, as results in Table 3 show, 
de-budding with cutting tools still had wider 
application among farmers in Kenya (with only 4% 
farmers disinfecting the used cutting tools) which 
could have exacerbated the disease and 
associated impacts.  

The results obtained from DID impact analysis 
(Table8) show that during the period before BXW, 
affected households harvested significantly more 
than the non-affected households. However, at 

 
 

 

the peak of BXW, affected households suffered a 
significantly higher percentage reduction in 
average harvest (63%), although their harvest 
levels remained slightly higher than those of non-
affected households. Even though there is a 
general downward trend in banana harvest during 
the two periods for both groups (presumably due 
to other factors), it is clear that the disease had 
large impacts on affected households. The 
difference-in-difference estimate is -22.66, which 
shows that average banana harvest among 
affected households was 22.66% lower than that 
of their non-affected counterparts. This is a sign of 
increasing difference between the two groups. 
The same trend is observed for banana sales. The 
reduction in banana production and sales due to 
disease infection adversely affect household food 
security and income. In turn, the loss in banana 
income adversely affects other household 
livelihood aspects into which income from banana 

 
 

 

is invested, such as home care (school fees,  
health) and investments into household 
infrastructure and productive assets.  

The study also analysed the change in banana 
harvest and sales levels before and at peak of 
BXW by years, since the disease was observed in 
the two countries and the results are presented in 
Table 9. In Uganda, the number of years since the 
disease was observed on farm ranged from 0 to 9, 
with an average of 4.5 years and therefore the 
study compared percentage change in harvest 
and sales below and above this average. The 
disease was a recent phenomenon on most farms 
in Kenya, with the number of years since the 
disease was observed on farm ranging from 0 to 3 
years with an average of 1.3 and we similarly 
compared the percentage change below and 
above this average. The results show that in both 
countries, banana harvest and sales reductions 
were much more severe on farms that had been 



 
 
 

 
Table 6. Farmer sources of information (% of farmers) on BXW control measures known in Uganda and Kenya.  

 
    Uganda (n=350)     Kenya (n=52)   

 

 
Practice Friends/ Radio/  

School/  Friends/ Radio/  
School/ Traders/ 

 

 

Extension Researcher Extension market  

  
neighbors TV church neighbors TV church  

     place  

           
 

 Cut down affected pseudo stem of affected plant 36 28 40 1 8 27 6 17 2 2 
 

 Cut down and dig up the whole mat of affected plant 24 20 35 - 5 23 2 19 4 4 
 

 Bury plant remains 17 11 28 - 4 - - - - - 
 

 Burn plant remains 11 9 11 - 3 - - - - - 
 

 Heap affected plant remains and leave on ground 14 11 20 1 4  2 2 - - 
 

 Left on ground but not heaped or buried 5 3 7 - 1 4 - 4 - 2 
 

 Remove male buds of affected plant with fork stick 33 26 48 1 9 2 - 2 - - 
 

 Remove male buds with cutting tools 13 9 19 - 2 21 2 13 4 4 
 

 After cutting, clean tools (JIK/fire) 28 22 46 1 9 2 - 2 - - 
 

 Do not sell or move any fruits, leaves, or suckers outside a disease area 5 3 7 - 2 - - - - - 
 

 
 

 
Table 7. Comparison of banana harvest and sales before and after BXW attack among affected households in Uganda and Kenya.  

 
   Uganda (n=350)   Kenya (n=52)  

 Parameter Before At peak t-test Percentage Before At peak of t-test Percentage 
  BXW of BXW statistic change (%) BXW BXW statistic change (%) 

 Mean banana harvested per month (bunches/household) 78.44 30.50 8.82*** -57.13 31.71 7.36 2.61** -76.82 

 Mean banana sold per month (bunches/household) 59.53 17.13 7.07*** -67.37 23.91 4.77 2.39** -79.57 
 

**, *** Significant at 5 and 1% respectively. 
 
 

 

affected by the disease for a much longer time 
than those recently affected.  

In order to assess the potential recovery from 
application of control measures, this study 
compared banana harvest levels at the peak of 
disease and in the current period (the period the 
survey was conducted). The results show evi-
dence of production recovery from the disease 
through application of control measures. In both 
countries, farmers applying control measures 
recovered more than 50% of their production 

 
 
 

 

losses, and those applying the full package of 
control measures recorded close to 80% 
production recovery. However, as highlighted 
earlier, few farmers (14 and 0% in Uganda and 
Kenya, respectively) were applying the full 
package of control methods. 
 

 

Farmer strategies to cope with BXW 

 

Besides applying control measures to reduce 

 
 
 

 

their losses, farmers are also using various coping 
strategies to „live with the disease‟. Such 
strategies represent a response by way of altering 
livelihood strategies to deal with the disease. 
These strategies range from those related to 
disease management, processing and marketing 
and consumption. Affected house-holds in both 
countries coped with the disease using multiple 
strategies (Table 10). However, the most widely 
used strategy was switching from banana to other 
crops. For instance, in Uganda, a previous work 



  
 
 

 
Table 8. DID estimate of the effect of BXW using matched sample for Uganda.  

 

Parameter BXW infection status 
Before BXW At the peak of Current Difference between 

 

(B) BXW (A) period (C) periods (A-B)  

  
  

 
Banana harvested 
(bunches/month) 

 
 
 

Banana sales 
(bunches/month) 

  
Affected households 80.89 30.32 47.31 -50.57 

Non-affected household 56.77 28.86 34.51 -27.91 

Difference between groups 24.12 1.46 12.80 -22.66 

Affected households 61.30 17.80 26.73 -43.5 

Non-affected households 33.13 13.92 14.56 -19.21 

Difference between groups 28.17 3.88 12.17 -24.29  
 

 

 
Table 9. Percentage change in banana harvest and sales before and after BXW by years since disease has been observed for Uganda and 
Kenya.  
 
   Uganda (n=350)  Kenya (n=52)  

 

   < 4.5 years 4.5 to 9 years  <1.3 years > 1.3 since  
 

 Parameter  since BXW was since BXW was t-test since BXW was BXW was first t-test 
 

   first observed first observed statistic first observed observed on statistic 
 

   on farm on farm  on farm farm  
 

 Banana harvest  per month 
-58.81 -73.66 3.46** -51.53 -63.89 0.60  

 
(bunches/household)   

        
 

 Banana  sales  per month 
-64.56 -79.54 2.53** -48.70 -86.94 2.16*  

 
(bunches/household) 

 
 

        
 

 
*, **, Significant at 10 and 5% respectively. 
 
 

 

by Karamura (2006) showed that acreage under banana 
declined, as affected farmers moved to crops that were 
considered safer than banana, with maize and cassava 
being the main crops increasing in acreage. Accordingly, 
the change in crop production system is accompanied 
with re-allocation of farm resources such as labour, 
equipment and other farm inputs. Other disease 
management strategies used to cope with the disease 
include raring livestock, use of concoctions, fallowing of 
banana fields and abandoning infected fields completely.  

The results in Table 10 further show that most farmers 
in Kenya coped with the disease mainly through disease 
management strategies (growing other crops, rearing 
livestock, use of concoctions, fallowing and field 
abandonment) and less farmers used strategies related 
to adjusting their marketing and consumption decisions. 
In contrast, a significant proportion of farmers in Uganda 
coped with the disease through changing their 
consumption patterns by reducing the number of banana-
based meals taken (31%) or consuming more of other 
food products (26%). This result supports evidence 
shown by Karamura (2006) that affected households 
have reduced consumption of banana products and 
consumption of other food types such as posho (maize 
meal) has increased (in line with increased importance 
and production of maize as stated earlier). These results 

 
 
 

 

illustrate that BXW has had profound effects on the 
livelihoods of banana-dependent communities by causing 
significant production and income losses and changing 
cropping and consumption patterns and processing and 
marketing decisions of affected communities. 
 

 

CONCLUSIONS AND POLICY IMPLICATIONS 

 

The importance of bananas as a food security crop in 
central and east Africa is increasingly threatened by 
BXW. A lot of progress has been made in raising farmers‟ 
awareness of the disease and available control options 
following its outbreak in the region. Friends/neighbours, 
researchers, extension, media and non-governmental 
organizations (NGOs) and community-based organiza-
tions (CBOs) played a key role in disseminating infor-
mation on the disease and its management to farmers. 
Farmer-to-farmer interaction has been by far the most 
widely used dissemination channel for information on the 
disease and control options, reflecting the importance of 
rural social networks in raising awareness and enhancing 
adoption of improved banana management technologies. 
This draws policy makers‟ and development agents‟ 
attention to exploit these social networks through 
participatory approaches, such as farmer groups, farmer 



 
 
 

 
Table 10. Percentage of farmers using different BXW coping strategies in Uganda and Kenya.  

 
 

Coping strategies 
Uganda Kenya 

 

 
(n=350) (n=52)  

  
 

 Disease management   
 

 Growing other crops 32 28.3 
 

 Raring livestock 8.3 7.5 
 

 Use of concoctions 9.7 13.2 
 

 Cut down entire field and rest for some time (fallowing) 8.9 18.9 
 

 Abandoning the infected field completely 11.1 15.1 
 

 Processing and marketing   
 

 Use other raw materials to make beer 0.9 1.9 
 

 Making cassava and potato chips or other products (instead of banana crisps) 1.4 11.3 
 

 Stop selling banana products 12.6 7.5 
 

 Selling other crop products - 9.4 
 

 Consumption   
 

 Purchasing of banana from the market 11.1 3.8 
 

 Reduction of number of banana-based meals 31.4 9.4 
 

 Consumption of other food types 26.3 13.2 
 

 
 

 

field schools and community extension groups for more 
effective farmer learning and adoption of BXW control 
measures. In addition, the multiplicity of the information 
sources suggest the need to strengthen linkages and 
synergies among all stakeholders (farmers, researchers, 
extension, farmers, media and NGOs, CBOs, policy-
makers, NARS) to ensure that farmers do not receive 
conflicting messages from different sources and foster 
better coordination and complimentarity of efforts in 
managing the disease.  

The results of this study showed that costs of control 
measures, lack of labour (or convenience of application) 
and effectiveness of control measure are key constraints 
to farmer application of control measures. While a more 
rigorous analysis of the factors influencing farmers‟ 
decisions on adoption of BXW control measures will be 
presented in a follow up paper, these preliminary results 
already suggest the need to strengthen farmer-
researcher-extension linkages and adoption of a 
participatory farmer-oriented (demand-driven) technology 
development approach, to take into account indigenous 
knowledge and match technologies to farmer‟s socio-
economic circumstances. This ensures that effective 
technologies are developed and are readily adopted by 
farmers. Furthermore, there is need to go beyond 
awareness raising and educate farmers on the correct 
application of the recommended control measures, 
something that can be addressed through stronger 
researcher-extension-farmer linkages and more effective 
farmer-to-farmer knowledge sharing and experiential 
learning through group approaches such as farmer field 
schools. 

 
 

 

Finally, our study also showed that BXW has led to 
significant production and income losses among banana-
dependent farmers, threatening their food security and 
incomes. The disease has caused far-reaching impacts 
on their livelihoods by inducing changes in farm 
production systems and consumption patterns and spill-
over effects of the income losses on other downstream 
non-farm household livelihood aspects that depend on 
farm incomes. However, the study demonstrated that in 
the short term, farmers are able to recover their 
production through application of the recommended 
cultural control practices. That being the case though, 
given the evidence that the disease is resurging in some 
areas where it had been successfully controlled, 
developing cultivars with resistance to the disease seems 
to be the most effective long-term solution to the 
epidemic. 
 
 

ACKNOWLEDGEMENTS 
 
The authors are thankful to the McKnight Foundation for 
providing financial support for this research through a 
grant support to the project “Strengthening partnerships 
along value chains to manage Xanthomonas Wilt of 
bananas in East Africa.” 
 
 
REFERENCES 
 
Bagamba F, Kikulwe E, Tushemereirwe WK, Ngambeki D, Muhangi J, 

Kagezi GH, Ramaga PE, Eden-Green S (2006). Awareness of 
banana bacterial wilt in Uganda: farmers‟ perspective. Afr. Crop Sci. 
J., 14(2): 157-164. 



 
 
 

 
Barker J (1999). Evaluating the Poverty Impact of Projects: A Handbook 

for practitioners. LCSPR/PRMPO. The World Bank.  
Davis K, Nkonya E (2008). Developing a methodology for assessing the 

impact of farmer field schools in East Africa. Proceedings of the 24th 
Annual Meeting of the Association for International Agricultural and 
Extension Education (AIAEE), 93–99. College Station, Texas. 
Association for International Agricultural and Extension Education.  

ISAR (2007). Sustainable agricultural productivity for improved food 
security and livelihoods, proceedings of the national conference on 
agricultural research outputs. 25-27 March, 2007. Serena Hotel, 
Kigali, Rwanda.  

Karamura E, Frison E, Karamura DA, Sharrock S (1998). Banana 
production systems in eastern and southern Africa In: Picq C, Foure 
E and Frison E (eds) (1998). Bananas and food security. INIBAP, 
Montpellier, pp. 401-412.  

Karamura EB (2006). Assessing the Impact of the Banana Bacterial 
Wilt, Xanthomonas campestris pv. musacearum (BXW) on Household 
Livelihoods in East Africa: Final technical Report Project R8437 
(ZA0661) to DFID. Crop Protection Programme.  

Karamura EB, Osiru M, Blomme G, Lusty C, Picq C (eds). 2006. 
Developing a regional Strategy to address the outbreak of Banana 
Xanthomonas wilt in East and Central Africa. Proceedings of the 
Banana Xanthomonas wilt regional preparedness and strategy 
development workshop held in Kampala, Uganda. 14-18 February 
2005. INIBAP, Montipellier, France.  

Karamura EB, Turyagyenda FL, Tinzaara W, Blomme G, Ssekiwoko F, 
Eden-Green SJ, Molina A, Markham R (2008). Xanthomonas wilt of 
bananas in East and Central Africa: Diagnostic and Management 
Guide. Bioversity International, Uganda.  

Mbaka JN, Nakato VG, Auma J, Odero B (2009). Status of banana 
Xanthomonas wilt in western Kenya and factors enhancing its spread. 
Afr. Crop Sci. Confer. Proc., 9: 673-676. 

  
  

 
 

 
Muhangi J, Nankinga C, Tushemereirwe WK, Rutherford M, Ragama P, 

Nowakunda K, Abeyasekera S (2006). Impact of awareness 
campaigns for banana bacterial wilt control in Uganda. Afr. Crop Sci. 
J., 14 (2): 175-183.  

Ndungo V, Eden-Green S, Blomme G, Crozier J, Smith JJ (2006). 
Presence of banana xanthomonas wilt (Xanthomonas campestris pv. 
Musacearum) in the Democratic Republic of Congo (DRC). Plant 
Pathol., 55: 294. 

Ngambeki DS, Tushemereirwe WK, Okaasai O (2006). Awareness of 
banana bacterial wilt control in Uganda: community leaders 
perspective. Afr. Crop Sci. J., 14(2): 165-173.  

Nkonya E, Davis K (2008). The statistical challenges of attributing 
impacts of demand driven advisory service programs and farmer field 
schools in Africa. Paper presented at the workshop on: Rethinking 
Impact: understanding the complexity of Poverty and Change, 
Colombia, March 26-29, 2008.  

Smale M, Diakite L, Sidibe A, Grum M, Jones H (2008). An econometric 
analysis of the impact of farmer participation in diversity field fora in 
Mali. Unpublished manuscript, International Food Policy Research 
Institute, Washington D.C.  

Tushemereirwe WK, Kangire A, Smith J, Nakyanzi M, Kataama D, 
Musiitwa, C (2001). An outbreak of banana bacterial wilt in Mukono 
district: A new and devastating disease. National Banana 
Programme. Kawanda Agricultural Research Organisation.  

Tushemereirwe WK, Kangire A, Smith J, Ssekiwoko F, Nakyanzi M, 
Kataama D, Musiitwa C (2003). An outbreak of banana bacterial wilt 
in Uganda. Infomusa, 12: 6-8. 



 


