1. Untapped potential of genetic
diversity of cassava in the great
lakes region of Africa
Anthony Pariyo
National Crops Resources Research Institute
P. O. Box, 7084 Kampala, Uganda
P O B K l U d
Chusa Gi é / Veronique Mera Memorial Workshop
Ch Ginés V i M M i lW k h
held at Cali, Colombia, May 12 – 13, 2010

2. Where is Uganda?
Eastern
Africa

3. National Crops Resources Research Institute
NaCRRI,
NaCRRI UGANDA (AFRICA)
Administration block
Old Cassava Molecular lab
New Mol., Biochem &
Biosafety II screen house New TC Lab Pathology lab

4. Presentation outline
Introduction / Background to the study
Materials and Methods
Key findings / discussion
Conclusion
Perspectives: breeding & germplasm conservation
Acknowledgement

5. Introduction

6. Why cassava?
y
Food and Beverage
Paper
P Starch
Wood
CASSAVA Deg.
Deg Plastics
Glue
Textile
Animal Feed
Ethanol

7. Low productivity compared to genetic
potential of 80 – 90 t/ha
Country Productivity /
Yield (t/ha)
Uganda 12.0
Rwanda
R d 6.4
64
Kenya 7.4
Tanzania 9.7
Congo (DRC) 8.1
Nigeria
g 11.2
Brazil 14.0
Colombia 10.8
Viet Nam 16.4
Thailand 22.9
FAOSTAT, 2007

8. Biotic stresses: mainly viral diseases
y
Cassava brown streak disease Cassava Mosaic Disease
(CMD on local landrace
- Ebwanateraka

9. Common whitefly species in E.A. region as
vectors of most viral diseases
Aleurodicus dispersus
(spiralling whitefly)
B. tabaci B. afer

10. CASSAVA MOSAIC DISEASE
1894: First reported (Warburg): Tanzania
1920s: Spreading in Ghana/Nigeria
1930s - Severe epidemic Madagascar
1988 - Epidemic Akwa Ibom Nigeria
1988 - Epidemic Uganda
1992 - Epidemic Cape Verde Islands
1995 - Epidemic Western Kenya
1998 - Epidemic NW Tanzania
2000 - E id i Rwanda
Epidemic R d
2003 - Epidemic Burundi

11. OTHER PATHOGENS/ PESTS
1971 – African root and tuber scale: Cameroon
(Stictococcus vayssierei)
1971 – Cassava green mite*: Uganda
(Mononychellus tanajoa)
1973 – Cassava bacterial blight : Nigeria
blight*:
(Xanthomonas campestris pv manihotis)
1973 – Cassava mealybug*: DRC
(Phenacoccus manihoti)
1992 – Spiralling whitefly*: Nigeria
(Aleurodicus dispersus)

12. COSCA WORKING PAPER 10
(NWEKE et al. 1994)
al
Decade Introduced Abandoned
varieties varieties
1901 10
1901-10 5 0
1911-20 4 0
1921 30
1921-30 5 5
1931-40 20 23
1941 50
1941-50 25 41
1951-60 56 83
1961 70
1961-70 57 118
1971-80 143 110

13. Variation over years in varieties
released to the total
Survey Districts Varieties %
n= R/Total Resistant
Plantings
1990-92
1990 92 21 0/67 0
1994 19 3/69 3
1997 16 3/64 21
2003 21 19/149 32
UGANDA FIELD SURVEYS 1990-2003

14. Cassava yield gap in Africa
Long t
L term yields
i ld
80 Genetic
Yield/ha
70 potential
Ideal pattern of
60 IITA variety genetic gain in yield
Local
50
40
30
Yield gap
20
= 700%
10
0 9 12 15
3
3 6
6 9 12 15 18
18
Ye Year
ar
Source: IITA, computed from FAOStat and IITA data (Dr. A. Dixon, 2008)

15. POTENTIAL THREATS
Cassava horn worm (Erinnyis ello)
Cassava mealybug (Phenacoccus herreni)
Cassava burrowing bug (C t
C b i b Cyrtomenus b i)
bergi
Whiteflies (five species)
Cassava green mottle nepovirus: Pacific
Cassava X potexvirus: Neotropics
p p
Cassava vein mosaic virus: Neotropics
Cassava frogskin ‘virus’: Neotropics

16. Justification
Understanding the amount of genetic
diversity in a crop provides a basis for
selection of genetic materials for further
improvement

17. Study objectives
To estimate genetic diversity of cassava
landraces in the great lakes region of Africa
using SSR markers
To document farmers perspectives on
p p
cassava variety selection in the great lakes
region of Africa

18. Materials and Methods

19. Study scope
y p
Sa p e o g eat a es eg o
Sample of great lakes region
Uganda
Rwanda
W. Kenya
287 farmers / fields
220 villages in Uganda
30 villages in Rwanda
35 villages in W. Kenya
g y
DNA analyses done at BecA, Nairobi hub
466 cassava clones assayed with 5 SSR markers
48 core collection analysed using 26 SSR markers

20. Farmers interview (287)Germplasm
Collection form doc
form.doc
Data collected
• Major cultivars grown
• Trait selection criteria
• Source of collection
• Genotype category
Ruhango district, Rwanda (Dec 2007)

21. DNA Analyses
Data analyses
Capillary
Leaf sample collection sequencer / ABI3730
(Rwanda 2007)
DNA extraction PCR and quality testing

22. Cultivar characterization in farmers fields
Root quality attributes
R li ib
Plant architecture Flowering potential

23. Stem cuttings collected for field
establishment in Uganda only?
Tororo district, Uganda

24. Key Results

25. Farmers maintain a wide diversity genotypes
(3 – 4) on their fields
thei
No. of No. of No. of No. of plants No. genotype No. genotype
Country Districts villages farmers examined / village / farmer
Rwanda 9 29 30 100 3.4 3.3
Kenya 4 34 35 125 3.7 3.6
Uganda 22 218 222 694 3.2 3.1

26. Differential preference in culinary qualities of
cassava e ists
cassa a exists in great lakes region of Africa
g eat egion Af ica
Cassava V i t selection by farmers based on culinary qualities
C Variety l ti b f b d li liti
40
35
30
25
% of farmers 20 U
Uganda
15
10
5
0 Kenya
1 2 3 4 5 6 Rwanda
Traits
1 = Sweetness, 2 = Brewing, 3 = Chips, 4 = Bread (Flour),
S t B i Chi B d (Fl )
5 = Vegetable and 6 = Boiling

27. Input traits predominate farmer decision
on variety selection
Farmers preference based on plant archtecture and biological
fitness
50
40
% reason for 30 Y
choice 20
10
Uganda
0 Kenya
Y PR
NV EM AV ST Rwanda
Y = Yi ld PR = Pest Resistance, NV = New variety,
Yield, P tR i t N i t
EM = Early Maturity, AV = Availability and ST = Storability

28. Flowering potential of most genotypes is
known by farmers
k b f
Proportion of genotypes with knowledge of flowering by farmers
120
96.9
96 9
100
81.3 82.2
% of genotypes
80
60
f
40
18.7 17.8
20
3.1
0
Rwanda Kenya Uganda
Country
Known potential
Unknown potential

29. Majority of farmers give names to their
varieties
Farmers interest in naming varieties
90
78.3
80 73.2
70
otypes
59.2
60
Names given / adopted
% of geno
50 40.8
40 8
40 Names not given
26.8
30 21.7
20
10
0
Rwanda Kenya Uganda
Country

30. Illustration of allelic frequencies in core
collection and original collection as assayed
by 5 markers with high PIC
SSR Markers assayed
SSRY102 SSRY21 SSRY38 SSRY59 SSRY69 Total
No of alleles in the total
collection 2.0 5.0 5.0 3.0 8.0 23.0
No of alleles in the selected
genotypes 2.0 5.0 4.0 3.0 7.0 21.0
% No. of alleles in the
selected genotypes 100.0 100.0 80.0 100.0 87.5 91.3

31. Highest number of alleles were observed in
Rwandan collection
Locus Number of alleles Total alleles
Kenya
y Rwanda Uganda
g
Total ll l
T t l alleles 98 109 103 121
Mean number of
alleles 3.77 4.19 3.96 4.65

32. Wide genetic structure exists between
Rwandan genotypes and the Ugandan and
Kenyan genotypes
Kenya Rwanda Uganda
Kenya -
Rwanda 0.0783 -
Uganda 0.0396
0 0396 0.0508
0 0508 -

33. Country level cluster shows country level
genetic differentiation
diffe entiation
0.01
Uganda
Kenya
Rwanda

34. Conclusions
G eate genetic diversity exists
Greater ge et c d e s ty e sts in Rwanda t a in
a da than
Uganda and Kenya
Genotypes in Uganda and Kenya are more closely
related than those from Rwanda
Farmers select for output traits more strongly
compared to input traits
Farmers maintain a wide range of genotypes on
their fields each one for a particular purpose

35. Perspectives: plant breeding and
germplasm conservation
• Need for a more comprehensive study to
characterize these genotypes
• Initiate a comprehensive germplasm conservation
plan to minimize genetic erosion
•E h
Enhancement of participatory plant b di by
t f ti i t l t breeding b
the National programs will improve adoption
• A comprehensive analyses of African and Latin
American germplasm to enhance breeding

36. Acknowledgement
g
Hannington Obiero KARI / Kagamega / Kenya
Gervis Gashaka ISAR / Rwanda
Martin Fregene Danforthcenter / USA
Morag Ferguson IITA / IRRI / Kenya
Inosters Njuki IITA / IRRI / Kenya
Cassava Research team Uganda
Ginés - Mera
IDRC Fellowship

37. Ashanti Sana
Thank you
Obrigado
Gracias