Characterization of Novel Rice
Germplasm from West Africa
and Genetic Marker
Associations with Rice
Cooking Quality
Dr. Karim Traore IER, Mali
Dr. Anna McClung USDA Beaumont, TX
Dr. Robert Fjellstrom USDA Beaumont, TX
Consumers Around the World Have Different
Preferences in Rice Cooking Quality

The Japanese people prefer soft and sticky rice with
short grain (japonica types)

In the USA, medium and long grain rice varieties are
preferred

In South America and the Middle East, people prefer firm
and non-sticky rice

Thai people prefer long grain soft and nonsticky

In India, Pakistan, fragrant or scented rice is preferred

In Brazil, people prefer long, slender, and translucent
grain
Consumer Preferences in West
Africa
In West Africa consumers prefer:
 long, slender, intermediate amylose
 Aroma
 Sticky rice to make rice porridge
 Parboiled rice
 Brokens
 Farmers like rice that is slow to digest
giving longer satisfaction
Experiments Conducted
1. Conduct genotypic and phenotypic evaluation of
West African germplasm for agronomic and
quality traits to identify characteristics that can
benefit WA and USA rice breeding programs.
2. Determine genetic marker associations with key
cooking quality traits that can be used in rice
cultivar improvement programs.
Data collected for the Quality tests
Alkali Spreading Value (ASV)- qualitative indicator of starch gelatinization temperature, dispersion
of milled grain in 1.5% KOH solution
Apparent Amylose Content (AA), Soluble Amylose (SA)- indicator of cooked rice texture, using wet
chemistry auto analyzer
Rapid Visco Analyzer (RVA)- determines the viscosity of rice flour pasting subjected to cycles of
heating and cooling
Differential Scanning Calorimetry DSC- quantitative indicator of starch gelatinization temperature,
using DSC 6 analyzer determines the temperature and heat of gelatinization
Cooking Time- time required for 10 milled rice grains to be completely gelatinized
Total and Whole Milling Yield – indicator of crop value, using McGill#2 Mill for 1 min.
Grain dimensions- indicator of crop value, using WinSEEDLE
Crude Protein Content- indicator of nutritional value, using nitrogen gas analyzer LECO 528
Aroma (2-Acetyl-1-pyrroline)-indicator of market value, using gas chromatography
Heading from the Agronomic
Evaluation Field of WA Germplasm
IMP = Improved Africa(6)
Land = Landrace(13)
INT = Interspecific (7)
USA = checks (8)
Heading (days)
120
103
102
100
76
74
80
60
40
20
0
IMP
INT
LOC
USA
Same color =
No differences
Plant Height from the Agronomic
Evaluation Field of WA Germplasm
IMP = Improved Africa(6)
Land = Landrace(13)
INT = Interspecific (7)
USA = checks (8)
Plots: 6 rows of 4.57 m length; spacing
17.78 cm between rows
RCBD, 4 rep.
Height (cm)
180
160
140
120
100
80
60
40
20
0
162
122
IMP
119
105
INT
Land
USA
Same color =
No differences
Grain Yield from the Agronomic Evaluation
of WA Germplasm IMP = Improved Africa(6)
Land = Landrace(13)
INT = Interspecific (7)
USA = checks (8)
Yield (kg/ha)
7000
6200
6000
5000
4342
4579
4000
2586
3000
2000
1000
0
IMP
INT
Land
USA
Same color =
No differences
Grain weight from the Agronomic Evaluation
Field of WA Germplasm
IMP = Improved Africa(6)
Land = Landrace(13)
INT = Interspecific (7)
USA = checks (8)
100 seeds (g)
3
2.59
2.78
IMP
INT
2.37
2.5
2.51
2
1.5
1
.5
0
Land
USA
Same color =
No difference
US variety CCDR and African
improved WAB 56-104
CCDR
7004 kg/ha
74 days
99.25 cm
WAB 56-104
4540 kg/ha
69 days
127 cm
African Landrace Gninni Zeba and
interspecific NERICA 5
Gninni Zeba
3063 kg/ha
105 days
162 cm
NERICA 5
6229 kg/ha
69 days
109 cm
Total and Whole Milling Yield of
Varieties Grown in the USA
Plots: 3 rows of 4.57 m length; spacing 17.78 cm
between rows
RCBD, 4 Rep
% Total Mill-Top 10
Gnanle Gnan-Man (78)
Baldo (77)
Bengal (76.6)
Nerica 2 (76.5)
Mahafin (76.4)
Nerica 5 (76.2)
ZHE733(BMT) (76)
Nerica 1 (76)
Mokossi (76)
Nerica 3 (76)
% Whole Mill-Top 10
Bengal (70)
CPRS (68)
Saber (68)
Nerica 3 (67.7)
Saber (BMT) (67.5)
Cheniere (66.7)
Nerica 4 (66.5)
WAB 638-1 (66.1)
Bakue Danane (66.05)
CCDR (65)
Grain Characteristics like Grain Width and
Total Mill can affect Cooking time
CT
GL
GW
GLWR
GL
NS
GW
0.54**
-0.41**
GLWR
NS
0.76**
-0.89**
TOTAL
0.66**
NS
0.41**
NS
WHOLE
NS
NS
-0.34*
0.34*
1% change in breakage can cause a $100,000 difference in profit for an
average-sized rice mill (Hosney 1998)
TOTAL
NS
Aroma Content 2-AP (ng/g) of
Cultivars grown in the USA
Sierra
1258.83 a
Bakue Danane
1140 ab
Cocote
1102 ab
WAB 638-1
1075.33 b
Jasmine 85
494 c
Nerica 1
444 c
Protein Content (%) of
Cultivars Grown in the USA
+1 SD
protein
9.5
9
8.5
8
7.5
7
6.5
6
5.5
Mean
-1 SD
Observations
Cheniere (9.1)
Jaya (9)
Nerica 2 (9)
ZHE733 (BMT)(9)
ZHE733 (8.8)
IITA 123(a) (8.8)
Bengal (8.7)
BG 90-2 (b) (8.6)
IITA 123 (b) (8.5)
Amylose classes and Waxy gene








Starch = amylose + amylopectin (60-80%) of edible weight of cereal.
Starch comprises 90% of the total dry matter of milled rice (Bao et al.
2002). The cooking and eating quality of rice is mainly influenced by the
properties of starch.
Smith et al. (1997): GBSS= wx protein is the product of waxy gene, plays
roles in the synthesis of amylose.
Starch branching enzyme, soluble starch synthase, and starch debranching
enzyme plays major role in the synthesis of amylopectin.
No amylose (waxy): very soft and extremely sticky (0%)
Low amylose: firm, separate, non sticky (10-19%)
Intermediate: (20-24%)
High amylose: extra firm, low solid loss during processing, superior kernel
stability (>24%)
Glucose molecule
Amylose
Amylopectin
Count
Distribution of Waxy Alleles in
WARDA Materials Grown in Africa
14
12
10
8
6
4
2
0
Conv. LG
DXBL
PB/Canning
Soft Cooking
103
105
114
116
118
Waxy allele
122
124
HE
Distribution of the Waxy allele among
the interspecifics Grown in Africa
30
25
21.1
21.7
22.2
22.6
23.5
23.6
24.7
20
15
AA
10
%
5
0
Waxy 124
Waxy 103-105
25.3
26.1
Marker Associations with Cooking
Quality Traits
Cocodrie CCDR: Cypress//L-202/Tebonnet at Louisiana in
1990.
Dixiebelle DXBL: RU8303181/CB801 at Beaumont in 1983
Brown rice was used for DNA extraction using Qiagen
Kit. PCR was used for amplification followed by evaluation for
polymorphisms using ABI sequencer
Diagrammatic Representation of the Waxy Gene
----- (CT)n-- G/TTATAC-
CT repeats
associated with
apparent amylose
content
(CT)10 & (CT)11=
high
(CT)14 & (CT) 20= int
(CT)17 & (ct)18= low
Ayres et al. (1997)
Bergman et al.
(2001)
Exon 1
GT
substitution is
associated with
low amylose
varieties.
-interm. /high
-low amylose
Ayres et al.
(1997)
Adapted from Chen (2004)
Exon 6:
A  C transversion
and substitution
changes a Tyrosine
to Serine
Differences in DNA
sequence of
Rexmont, JODON,
and Toro-2 from
lemont
-intermediate
-High/low
Larkin and Park.
2003
Rexmont= high amylose strong RVA
Lemont= intermediate amylose
Jodon, L202= high amylose, weak RVA
Toro-2= low amylose
Exon 10:
C  T transition
and substitution
changes a Proline
to Serine.
Differences in DNA
sequence of
Rexmont from
Jodon, Toro-2 and
Lemont.
-high amyl.strong
RVA
-others
Larkin and Park
(2003)
CCDR et DXBL ont la même teneur en
Amylose (~26%) mais Diffèrent en RVA
DXBL
Temperature
profile
Peak
Cool
300
105
90
CCDR
RVU
75
200
Hot
60
100
Bkdn=Peak- hot
Stbk= Cool-Peak 0
CS= Cool- Hot
0
0
45
3
6
9
Time minutes
12
15
15
Temp oC
400
PCR Primers Used for Molecular
Marker Analysis
21 PCR markers were selected and screened for marker association
study. The markers were either:
-near starch metabolism (like SSS, SBE )
-at a map position with significant effects on starch properties (like
amylose content, or RVA pasting properties
Primers
Annealing
temp.
Sequence
Starch
Map location
metabolism /Chromo.
gene
Loc.
Waxy
55
5’-CTTTGTCTATCTCAAGACAC-3’
5’-TTGCAGATGTTCTTCCTGATG-3’
GBSS
6-8.2
Exon 10
66
5’-GCGGCCATGACGTCTGG-3’
5’-GGCGGCCATGACGTCTGA-3’
GBSS
6-8.2
AB26285
55
5’-CTAGCCATGCTCTCGTACC-3’
5’-CAACTTACTGTGACTGACTTGG-3’
SSSI
6-15.3
Waxy, exon10, and AB26285 showed association with the
amylose and RVA properties.
Single Factor Analysis for the 3 Markers used for
Associations Study
Source
variation
df
AA
SA
IA
PEAK
HOT
COOL
Waxy
2
1.04*
78.00**
60.33
116548.61**
98433.24**
26737.78**
Additive
1
2.08*
155.75**
120.39
232946.49**
196828.50**
52458.07**
Dominant
1
NS
NS
NS
1124.02*
NS
NS
0.04
0.63
0.54
0.80
0.81
0.48
R^2
Exon 10
2
1.18*
76.56**
58.02**
112729.13**
95577.79**
246835.08**
Additive
1
2.35**
153.07**
115.99**
225123.11**
190999.55**
493627.87**
Dominant
1
NS
NS
NS
NS
NS
NS
0.04
0.61
0.52
0.77
0.80
0.79
R^2
AB26285
2
NS
30.41**
24.52**
56690.88**
46866.25**
112115.44**
Additive
1
NS
60.77**
48.92**
112538.50**
93473.63**
223082.71**
Dominant
1
NS
NS
NS
NS
NS
NS
0.01
0.24
0.22
0.38
0.39
0.36
R^2
R^2= Total Phenotypic explanation (%)
Summary and Conclusions

Interspecifics were found interesting for reduced water
rice growing, more studies can elucidate these findings

Nerica 2 had good agronomic and milling characteristics

Bakue Danane, Cocote, WAB 638-1 had strong aroma

Jaya, Nerica 2, BG 90-2, IITA 123 had high level of
Protein
Summary and Conclusions (cont.)



Soluble Amylose (SA) explained more the difference in
RVA profile than the Apparent Amylose (AA).
Different GBSS alleles may produce the same amount of
total amylose but different proportions of soluble and
insoluble amylose.
The Waxy microsatellite and waxy exon 10 SNP markers
are now useful molecular markers for rapid and efficient
identification of cooking quality traits that can be difficult
to separate with only physico-chemical data.
Acknowledgements
I wish to express my sincere
gratitude to:




WARDA
Rockefeller foundation
Texas A&M (Soil and
Crop Sciences)
USDA-ARS Beaumont