




































 Agricultural Science; Vol. 3, No. 1; 2021 
ISSN 2690-5396   E-ISSN 2690-4799 

https://doi.org/10.30560/as.v3n1p7 

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Prevalence and Distribution of Cassava Bacterial Blight in the Kenyan 
Coast 

A. Livoi1*, A. W. Mwang’ombe1, E.Nyaboga2, D. Kilalo1 & E. Obutho1 
1 Department of plant science and crop protection, University of Nairobi, Nairobi, Kenya 
2 Department of Biochemistry, University of Nairobi, Nairobi, Kenya 
Correspondence: Antony Livoi Musera, Department of plant science and crop protection, University of Nairobi, 
Po Box 30197-00100, Nairobi, Kenya. E-mail: livoiantony@gmail.com 
 
Received: November 11, 2020   Accepted: November 26, 2020   Online Published: February 18, 2021 
 
The research is financed by (Regional universities forum for capacity building in Agriculture: RUFORUM) 
 
Abstract 
Cassava (Manihot esculenta Crantz) is one of the staple food crops grown in Kenya. Diseases remain one of the 
major constraints for cassava production. Apart from other major viral diseaes Cassava mosaic and Cassava brown 
streak, Cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv manihotis and Xanthomonas 
axonopodis pv cassavae are a major constraint in cassava production in Kenya. This study was done to identify 
the prevalence, distribution, and farmers' knowledge of cassava bacterial blight in the coastal region of Kenya. A 
survey was conducted involving 250 farmers who were randomly selected from two regions of Kilifi and Taita 
Taveta counties. Among the 250 farmers interviewed, 61.6 % identified cassava bacterial blight symptoms in their 
farms. The main varieties found growing in the region were Tajirika, Karembo, Kibandameno, and Shibe which 
were all confirmed by farmers as susceptible to cassava bacterial blight. During the survey, plant samples were 
randomly collected in the field. Out of the 70 samples collected, 40 of them were confirmed positive with X.pv 
manihotis and X.pv cassavae which cause cassava bacterial blight. The study concluded that there is a widespread 
of cassava bacterial blight in Kilifi and Taita taveta counties. Kilifi County had the highest incidence of 22% with 
Taita Taveta having the lowest incidence of 13%. Kilifi County had a higher severity of 8% as compared to Taita 
Taveta which had 5% Severity. Therefore there is a need for a proper management program to be deployed in 
managing the disease to enhance cassava production in the region.  
Keywords: Cassava, Survey, Incidence, X. axonopodis pv manihotis, X. axonopodis pv cassavae 
1. Introduction 
Cassava manihotis esculenta is one of the major crops grown and consumed in the sub-Saharan Africa. It provides 
carbohydrates for more than 800 million people in Africa (FAO, 2017). Cassava production quantity in Kenya is 
at 946,076 metrics tones from 61,592 of hectares of land (FAOSTAT 2018). Western Kenya is the leading producer 
of cassava, followed by the coastal regions (MOA 2007; Abong’ et al., 2016). The crop is grown for its tubers 
which provide starch and carbohydrates and leaves which are rich in protein and other minerals like calcium, iron 
and phosphorous. Production of cassava is on the increase as compared to the years back and this is because it has 
potential in adapting to climate change, food security and also an industrial potential to produce starch and feed 
for animals.  
Cassava is faced by challenges both biotic and abiotic challenges. One of the main biotic challenges is Cassava 
bacterial blight, caused by Xanthomonas axonopodis pv. manihotis and Xanthomonas axonopodis pv. cassavae 
(Verdier et al .,1994); (Ogunjobi & Fagade, 2008). The disease is commonly spread through infected planting 
materials (Lozano et al., 1980). Since the pathogen exists in stems in latent form, it is not easy to detect the disease. 
Therefore, farmers have played a major role in disseminating the disease unknowingly by sharing planting 
materials over long distances (Taylor, 2009). In Kenya, the disease was first reported in western region (Mukunya 
et al., 1980). Survey done in 2016 across the country in cassava growing regions indicated that cassava bacterial 
blight exists in all the cassava growing regions (Odongo et al., 2016). This study was conducted to determine the 
prevalence of cassava bacterial blight in two cassava growing regions of Kilifi and Taita Taveta counties in coastal 
Kenya. 



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2. Materials and Methods 
2.1 Survey of Cassava Bacterial Blight and Sample Collection 
A survey was conducted in two counties along the Kenyan coast. This was Kilifi county and Taita taveta county 
as geographically described below. 
Taita Taveta County  
It is one of the counties in the coastal region known for its tourist attraction sites and wildlife. The county has some 
neighboring counties including Makueni, Tana River, and kitui in its North direction. It borders Kilifi and Kwale 
in its East direction. On the south, the county borders the Republic of Tanzania. As per the census done in 2019 
the county is home to a population of 340,671 people with an area of 17,084 km2. (Kenya county fact sheet, 2011). 
Topographically, the County has three major zones. The upper zone comprises Taita, Mwambirwa, and Sagalla 
hills regions with altitudes ranging between 304 and 2,208 meters above sea level. The lower zone has plains while 
the third zone is the volcanic foothills zone covering the Taveta region. The region has two lakes, Jipe and Challa, 
both found in Taveta. The County is largely dry although Taita hills are wetter. Two rainy seasons are experienced, 
long rains between March and May while the Short rains occur between October and December. The annual mean 
rainfall is estimated at 650 mm. Some of the crops grown in this region include: cassava, sweet potato, vegetables, 
sorghum, millet, green grams, cow pea and macadamia. 
Kilifi County 
It is one of the counties touching the Indian Ocean and known for its best beaches that attract both local and 
international tourists. It hosts a population of around 1,109,735 people as per the census done in the year 2009. It 
has a geographical size of 12,245 km2 according to Kenya's independent electoral and boundaries commission. It 
is quite large and has seven counties including Magarini, Malindi, Ganze, Rabai, Kaloleni, Kilifi South, and Kilifi 
North. 
Crops grown in this region include coconut, cassava, cashew nuts, maize, sweet potatoes, and legumes. The county 
has a warm climate with temperatures ranging from 21oC during the cold month and up to 320c during the hottest 
months. It receives an annual rainfall of 900mm to 1000mm, with long rains experienced in April to June and short 
rain experienced in October to December. (Kenya county fact sheet, 2011). 
Survey Conducting 
A survey was conducted in Kilifi and Taita Taveta counties in July 2018 during short rain seasons by randomly 
administering structured questionnaires to cassava farmers. Purposive random sampling was done whereby 
farmers were selected randomly at an interval of 2km from each farmer for questionnaire administering. A sample 
size of 250 farmers were randomly selected from cassava farmers and interviewed during the survey for the two 
regions. All the questionnaires were brought back to the college, cleaned, and entered. The analysis was done using 
the science statistical package (SPSS). 
Plant samples were collected in cassava fields both symptomatic for cassava bacterial blight and asymptomatic 
samples. Sampling was done on plants along diagonals and the number of samples collected per field depended 
on the variability of symptoms and field size (Trujillo et al., 2014 ). From the two sites of study 70 leaf plant 
samples were collected, 34 plant samples from Taita Taveta, and 36 plant samples from Kilifi County. This was 
done randomly on farms having cassava. They were then stored in brown envelopes and put in a cool box and 
transported to the College of Agriculture and Veterinary Science in the Department of plant science and crop 
protection and stored at – 4 °C.  
2.2 Disease Assessment 
Disease assessment was done using the severity index and incidence index. Incidence was obtained by counting 
symptomatic plants in relation to total number of plants in the field according to the equation of Bansal. 

 
Disease severity was scored using a scale developed by (Wydra & Misikita 1998) where: 1 - No symptom, 2 - 
Angular leaf spots, 3 – Angular leaf spots, blight, wilt, defoliation, and sometimes exudates on stems, petioles or 
leaves, 4 –Blight on leaves, leaf wilt, defoliation, exudates, and tip dieback, and 5 - Blight on leaves, leaf wilt, 
defoliation, exudates, abortive lateral shoot formation, and stunting, complete dieback. Severity was obtained using 
the formula by song, et al. 



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To establish farmers’ knowledge and perceptions on CBB in Coastal Kenya, information such as the source of 
planting material, age of the crop, name(s) of the cultivar(s) grown in the fields, disease management approaches 
used, source of information and the duration for which they have grown the crop were asked during questionnaire 
interview. 
2.3 Isolation of Bacteria from Collected Leaf Samples 
Isolation was done according to (Ogunjobi & Fagade, 2008). Infected plant samples stored at -4 0c were cut into 
small pieces of 2mm2 and washed in sterile distilled water. The pieces were then washed in 3% sodium 
hypochlorite for 3 minutes and triple rinsed in sterile distilled water using the universal bottles. Yeast peptone 
glucose (YPG) broth was prepared containing yeast 1%, peptone 1%, and glucose1%. The cut infected parts were 
placed in universal bottles containing 10ml broth and placed on the rotary shaker at a speed of 100rpm for 48 hours 
at room temperature to allow the bacteria to ooze into the broth. The broth was then serial diluted to 10-6 and then 
from each dilution, a drop of 100µl was spread on plates containing freshly prepared selective media containing 
Yeast1% peptone1%, glucose1% and agar1.5% (YPGA). The plates were then placed in an incubator for 28oc for 
48 hours. 
The bacterial colonies obtained were identified and used for pathogenicity tests on clean symptomless plants 
multiplied through tissue culture technique from tissues culture laboratory in the department of plant science and 
crop protection. After four weeks the symptoms were recorded and photos captured both for the infected plants 
and the control which were not infected. Re-isolation was done using YPGA to fulfill Koch’s postulates. 
2.4 Data Analysis 
Data collected during the survey was cleaned, entered and analyzed using the statistical package for social science 
SPSS. Graphs showing the output of farmer response were developed using an Excel spreadsheet (2016) 
3. Results 
3.1 Incidence and Severity of Cassava Bacteria Blight 
From the survey conducted in the study regions, Kilifi County had the highest incidence of 22% with Taita Taveta 
having the lowest incidence of 13%. Kilifi County had a higher severity of 8% as compared to Taita Taveta which 
had 5% Severity as seen in Figure 1. During the survey, a range of symptoms were observed as captured in Figure2 
with the highest score of symptom remaining at 3 on the disease scale used. Angular leafspot, blighting, water-
soaked lesions were visible but defoliation, bacterial exudates, abortive lateral shoot formation, stunting, and die 
back were not record as per the scale used. The grouping was done for the farms in which plant sampling was done 
as seen in Table 1. There were farms which had 0% incidence and other farms were found in the highest scale 
grouping of 76-100% 
 
Table 1. Showing incidence and severity scale grouping. 

scale 0% scale 1-25% scale26- 50% scale 51-75% Scale 76-100% 

TAITA-TAVETA  
REGION 
incidence 14 10 1 4 4 
severity 16 8 10 1 0 
KILIFI REGION 
incidence 20 9 2 3 2 
severity 15 6 5 6 4 

 
The table above shows how many sampled farms were found in each scale grouping for the two study regions of 
Taita Taveta and Kilifi at the Kenyan coast. 



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Figure 1. Incidence and severity of CBB on average in the two surveyed counties 

   
Figure 2. Showing symptoms on infected plants and clean non infected plants respectively 

 
3.2 Confirmation and Pathogenicity of the Isolates 
The isolated bacteria colonies ranged between whitish, creamish, and yellow with convex shape, shiny and mucoid 
as described by Wydra et al., 1990. Inoculation of the bacterial on the plants after 2 weeks showed blighting around 
the point of inoculation with the control showing no blighting at the point of inoculation as seen in Fig 3 hence 
indicating the pathogenicity of the bacteria. 

    
Figure 3. Showing Xanthomonas axonopodis pv. manihotis colonies isolated from plants collected in the field, 

infected plant showing symptoms and control plant showing no symptoms at the point of infection 
 
3.3 Distribution of CBB in Coastal Kenya 
Among the 70 plant samples collected from different farms in the field, Isolation was done and 40 samples showed 
bacteria characteristic to Xanthomonas axonopodis pv cassavae and Xanthomonas axonopodis pv manihotis. Of 
the 40 samples, 21 samples were from Taita Taveta and 19 samples were from Kilifi. The colonies obtained were 
mucoid, cream to whitish, circular, shiny and convex as described by Wydra et al., 1990. A distribution map was 

0

5

10

15

20

25

30

KILIFI COUNTY TAITA TAVETA

INCIDENCE SAVERITY



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developed using ARCH GIS software and the incidence was grouped into four classes of 1-25%, 26-50%, 51-75% 
and 75-100%(Odongo et al., 2019). The geographical coordinates used to develop the map were taken using GPS 
tools at the point of sample collection in the field.   

 
Figure 4. Distribution Map for CBB in Kilifi and Taita Taveta showing incidence levels in different places 

 
3.4 Farmers’ Knowledge and Awareness of CBB 
During the survey a representative population of 250 farmers were interviewed, among them, 50.8% of the farmers 
were interviewed from Kilifi while 49.2% of the farmers were interviewed from Taita Taveta. Among the 
interviewed farmers, 61.6% of them had once interacted with symptoms characteristic to cassava bacterial blight 
as seen in the photos used during the survey. Farmers experiencing CBB every season in their farms were 43,6%. 
Only 17.2% of the farmers reported having never seen CBB symptoms in their farms. Other farmers, 39.2% were 
not in a position to tell if they have once seen CBB in theirs farms since some were new in farming, others had 
only planted one season.  
On resistance and susceptibility of the available varieties, 38% of the farmers reported Kibandameno variety as 
highly affected by the disease followed by Tajirika reported by 13.2% of the farmers. All the mentioned variety 
Shibe, Girikacha, and Kaleso were confirmed as susceptible to CBB by the interviewed farmers. There is no single 
farmer who reported a resistant variety in both the regions. Most farmers that is 80% of the interviewed, don’t 
manage cassava bacterial, although they do intercropping with a major reason to maximize on their limited land 
space.  

 



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Figure 5. Graph A showing the seasonality existence of CBB. Graph B showing how farmers manage CBB. 

Graph C showing Varieties susceptible to CBB. Graph D showing the year in which farmers first interacted with 
CBB. 

 
4. Discussion 
The study shows that cassava bacterial blight caused by Xanthomonas axonopodis pv manihotis and Xanthomonas 
axonopodis pv cassavae is widely distributed in the coastal region of Kenya both in Taita Taveta and Kilifi counties 
visited during the study. This confirms work done by (Odongo et al., 2016; Chege et al., 2017) on the distribution 
of Cassava bacterial blight disease in Kenya. Their work similarly reported the presence of cassava bacterial blight 
in major cassava growing regions of Kenya. All the varieties grown both in Kilifi and Taita Taveta County are 
susceptible to cassava bacterial blight as referred to the response from the farmers who grow the varieties. An 
indication that there is no resistant variety for cassava bacterial blight in the region and no landrace variety has 
been identified by farmers in the region to show resistance to CBB, this confirms work done on evaluation of 
resistance of cassava cultivars in Kenya on CBB. (Mbaringong et al .,2017).  
Most of the interviewed farmers reported having seen the disease even before 2016 which was more than 3 years 
back from the year of study. This confirms that CBB has been in existence in the region for quite some time and 
it is not a new disease in the region hence proving work done on distribution of CBB in Kenya(Odongo et al., 
2016) 
Most of the farmers reported to have experienced CBB in their farms every season they plant cassava. This 
indicates that they could be starting their crop with infected planting materials or they don’t do proper farm hygiene 
to remove crop debris from the previous crops to reduce the inoculum. This demonstrates the gap that exists among 
farmers in awareness and management of CBB as indicated in the study where by 80% of them who don’t manage 
CBB. 
5. Conclusion 
The study proved the existence and distribution of cassava bacterial blight in all the study areas of Kilifi and Taita 
Taveta. Varieties grown in this region: Kibandameno, Tajirika, Girikacha, Shibe and kaleso which are both local 
varieties and improved varieties have shown to be susceptible to cassava bacterial blight. Therefore there is need 
to address the issue through developing plant resistant varieties. Farmers in this region are poor at managing the 
disease therefore need for developing an integrated management practice program and good communication 
system to disseminate information to farmers through extension officers. There is also an urgent need for a program 
on clean planting material so that as cassava farming uptake is increasing, farmers can access and use healthy 
planting materials for establishing the new crop. Unless such mitigation measures are put in place, the spread of 
the disease is likely to increase as cassava is being advocated for as a food security crop and climate smart crop. 



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Due to inadequate planting materials and poor seed system in cassava farming, farmers keep exchanging and 
sharing the materials which are infected hence contributed to the risk of spreading the disease in the region. 
Acknowledgments 
The authors would like to appreciate the Regional universities forum for capacity building in Agriculture 
(RUFORUM) for supporting this work under the CARP project. 
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This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 
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    /HRV (Za stvaranje Adobe PDF dokumenata najpogodnijih za visokokvalitetni ispis prije tiskanja koristite ove postavke.  Stvoreni PDF dokumenti mogu se otvoriti Acrobat i Adobe Reader 5.0 i kasnijim verzijama.)
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    /NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken die zijn geoptimaliseerd voor prepress-afdrukken van hoge kwaliteit. De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.)
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    /ENU (Use these settings to create Adobe PDF documents best suited for high-quality prepress printing.  Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.)
  >>
  /Namespace [
    (Adobe)
    (Common)
    (1.0)
  ]
  /OtherNamespaces [
    <<
      /AsReaderSpreads false
      /CropImagesToFrames true
      /ErrorControl /WarnAndContinue
      /FlattenerIgnoreSpreadOverrides false
      /IncludeGuidesGrids false
      /IncludeNonPrinting false
      /IncludeSlug false
      /Namespace [
        (Adobe)
        (InDesign)
        (4.0)
      ]
      /OmitPlacedBitmaps false
      /OmitPlacedEPS false
      /OmitPlacedPDF false
      /SimulateOverprint /Legacy
    >>
    <<
      /AddBleedMarks false
      /AddColorBars false
      /AddCropMarks false
      /AddPageInfo false
      /AddRegMarks false
      /ConvertColors /ConvertToCMYK
      /DestinationProfileName ()
      /DestinationProfileSelector /DocumentCMYK
      /Downsample16BitImages true
      /FlattenerPreset <<
        /PresetSelector /MediumResolution
      >>
      /FormElements false
      /GenerateStructure false
      /IncludeBookmarks false
      /IncludeHyperlinks false
      /IncludeInteractive false
      /IncludeLayers false
      /IncludeProfiles false
      /MultimediaHandling /UseObjectSettings
      /Namespace [
        (Adobe)
        (CreativeSuite)
        (2.0)
      ]
      /PDFXOutputIntentProfileSelector /DocumentCMYK
      /PreserveEditing true
      /UntaggedCMYKHandling /LeaveUntagged
      /UntaggedRGBHandling /UseDocumentProfile
      /UseDocumentBleed false
    >>
  ]
>> setdistillerparams
<<
  /HWResolution [2400 2400]
  /PageSize [612.000 792.000]
>> setpagedevice

