Evaluation of rice genotypes for sugarcane borer resistance using phenotypic methods and molecular markers

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Crop Protection
journal homepage: www.elsevier.com/locate/cropro
Evaluation of rice genotypes for sugarcane borer resistance using
phenotypic methods and molecular markers
Jacqueline Barbosa Nascimento a, Jose Alexandre Freitas Barrigossi b, *,
Tereza Cristina de Oliveira Borba b, Jose Francisco da Silva Martins c,
Paulo Marçal Fernandes a, Raquel Neves de Mello b
a Federal University of Goias, Faculty of Agronomy, Campus Samambaia, Rodovia Goiânia/Nova Veneza, Km 0, P.O. Box 131, 74690-900 Goiânia, GO, Brazil
b Embrapa Rice and Beans, Rodovia GO-462, Km 12 e Zona Rural, Santo Antônio de Goias, GO 75375-000, Brazil
c Embrapa Temperate Agriculture, Rod. BR 392, Km 78, 9 Distrito, Pelotas, RS 96010-971, Brazil
a r t i c l e i n f o
Article history:
Received 29 March 2014
Received in revised form
22 September 2014
Accepted 24 September 2014
Available online
Keywords:
Diatraea saccharalis
Insect resistance
Morphological traits
Oryza sativa
SSR markers
a b s t r a c t
This study aimed to observe the response of 34 rice accessions to attack by sugarcane borer (Diatraea
saccharalis Fabr., 1794) and to analyze the genetic diversity of these accessions by microsatellite markers.
Twenty larvae were placed on the leaf sheaths of rice plants. At 30 days after infestation the rice plants at
ground level were taken to the laboratory where the signs of borer attack, external and internal diameter
of the stem and weight of surviving larvae were determined. For the molecular analysis of rice acces-sions,
24 microsatellite markers were used. The results of the morphological traits of the rice plant,
response of the plant to insect attack, development of the sugarcane borer larvae and molecular data,
indicated a genotypic variation. The accessions that most favored larval survival were IAC 47 and Ti Ho
Hung. Larvae with highest weight (0.0986 g and 0.0862 g) and the largest internal diameters of the rice
stem (3.18 mm) were found in land races “Canela de Ferro” (rust colored stem) and all these “Canela de
Ferro” accessions also remained genetically grouped. The most tolerant materials, based on the ability to
produce new tillers after larval infestation were, Chiang an Tsao Pai Ku and IR 40 which remained
morphological and genetically grouped. The results of this study indicate that all the traits and molecular
analyses were able to separate the accessions of rice into different groups in relation to resistance to the
sugarcane borer. These materials can be used as donor sources in breeding for genetic resistance to
sugarcane borers and can be used as donors to amplify the genetic base of Brazilian rice.
© 2014 Elsevier Ltd. All rights reserved.
1. Introduction
Rice stem borers are economically important pests of rice (Oryza
sativa L.) in all rice growing areas in the world (Lv et al., 2008; Selvi
et al., 2002). They have been reported to be among the biotic
stressors affected by climate change (Kisimoto and Dyck, 1976).
Stem borers are a threat to rice production and will likely play an
ever increasing role with the changes in weather factors, precipi-tation
and temperature.
Globally, more than 50 species of stem borers, distributed
among three families of Lepidoptera (Crambidae, Noctuidae and
Pyralidae) and one dipteran (Diopsidae), are pests of rice (Pathak
and Khan, 1994). In South America the main species are the
sugarcane borer, Diatraea saccharalis (Fabricius) and the South
America white borer Rupela albinella (Cramer) (Ferreira and
Martins, 1984; Heinrichs, 1994). In North America, natural in-festations
of D. saccharalis in rice were reported as causing yield
reductions up to 60% (Way et al., 2006). Insecticides are most
commonly used to control rice stem borers, but are toxic to the
biocontrol agents that regulate their populations.
The sugarcane borer is a common insect pest in Central Brazil
where it predominantly occurs in upland rice. The increased level of
sugarcane borer damage to upland rice in recent years has been
primarily observed in the state of Mato Grosso, Brazil. The
increased damage in Mato Grosso is attributed to the expansion of
corn (Zea mays L.) and sugarcane (Saccharum officinarum L.), pri-mary
hosts of the sugarcane borer (Martins et al., 2009). The major
problem in the effective management of this pest is the difficulty in
monitoring to detect the pest before damage occurs. It is most
easily detected only after penetration of the stem and the
* Corresponding author. Tel.: þ 55 62 3533 2121.
E-mail addresses: jose.barrigossi@embrapa.br, jose.barrigossi@gmail.com
(J.A.F. Barrigossi).
http://dx.doi.org/10.1016/j.cropro.2014.09.018
0261-2194/© 2014 Elsevier Ltd. All rights reserved.
Crop Protection 67 (2015) 43e51

44 J.B. Nascimento et al. / Crop Protection 67 (2015) 43e51
production of whiteheads (dead panicles) (Martins et al., 1977,
1978, 1981, 1989a,b). It is also difficult to control with pesticides,
as proper timing of application is difficult. Moreover, no pesticides
are officially registered for control of the sugarcane borer in Bra-zilian
rice (Martins et al., 2009).
Some cultural practices are recommended to reduce the risk of
damage by the sugarcane borer to rice: a) avoid planting rice crops
near fields of sugarcane and corn and other sugarcane borer host
plants, b) avoid excess nitrogen fertilization which increases the
susceptibility of the rice plant, and c) use of cultivars that have
characteristics expressing resistance to the borer (Martins et al.,
1977, 2009) in areas of greatest risk of attack. An important strat-egy
to reduce the potential for sugarcane borer damage to rice is the
development of rice cultivars with genetic resistance and their
integration with other cultural control tactics as suggested above.
Genetically resistant/tolerant cultivars are a key tactic in the
development of a package of Integrated Pest Management (IPM)
practices for managing rice stem borer populations (Ferreira et al.,
2000). Resistant/tolerant cultivars are a user-friendly, economical
and environmentally friendly approach to rice stem borer man-agement.
Limited studies have been conducted to identify sugar-cane
borer resistant cultivars in Brazil and thus there are no
identified donor cultivars in the Brazilian accessions with adequate
resistance to the borers for use in the breeding program. However,
there is potential for their use of some Brazilian highlands mate-rials,
as donors in a program of genetic enhancement of resistance,
especially in the “Canela de Ferro” accessions (landraces) (Martins
et al., 1977) and the line CNAs 9023 (Ferreira et al., 2004). Thus,
there is a need to enhance the levels of genetic resistance of
adapted Brazilian cultivars for use as a component in the IPM
program targeting sugarcane borer in upland rice.
The objective of this study was to identify sources of resistance
to D. saccaralis in the Brazilian rice germplasm collection. The ul-timate
goal of this study is to use selected accessions as donor
parents with the aim to produce rice cultivars with enhanced
resistance to the sugarcane borer, via conventional methods of
plant breeding, and in the future, through the use of molecular
markers using genetic engineering methods.
The information derived from the molecular analyses enables a
better understanding of the genetic inheritance for resistance to
stem borers (Nibouche et al., 2010). Molecular markers have been
used to detect genetic diversity and to assist the management of
plant genetic resources (Coburn et al., 2002; Vanniarajan et al.,
2012). In contrast to morphological traits, molecular markers can
reveal differences among genotypes at the DNA level, providing a
more direct, reliable and efficient tool for germplasm character-ization,
conservation and management (Ram et al., 2007).
The types of molecular markers that are available today include
those based on restriction fragment length polymorphism (RFLP)
(Botstein et al., 1980), random amplified polymorphic DNA (RAPD)
(Williams et al., 1990), amplified fragment length polymorphism
(AFLP) (Blears et al., 1998), and simple-sequence repeats (SSRs) or
microsatellite markers (Giarrocco et al., 2007). Microsatellites and
PCR-based markers are both technically efficient, cost-effective and
commonly used in rice breeding research (Temnykh et al., 2000). In
this study we evaluated the response of 34 rice accessions to in-festations
of the sugarcane borer, D. saccharalis, and used SSR
markers to determine the genetic diversity of these accessions.
2. Materials and methods
2.1. Plant material and DNA extraction
A total of 34 accessions of O. sativa were included in this study
(Table 1). These accessions are maintained at Embrapa Rice and
Beans Center, located in Santo Ant^onio de Goias, Goias (GO), Brazil
(altitude 749 m; 164004300 S; 491501400 W). The rice accessions
selected for this study are elite cultivars that have potential for
being good donors in the breeding program as based on their
resistance or tolerance to species of rice stem borers in Asia and
Brazil (Table 1) or because they are adapted to the upland rice
production conditions where stem borers are increasing in
importance in Brazil.
Genomic DNA from each sample was isolated from young leaf
tissue using the cetyltrimethyl ammonium bromide (CTAB) method
proposed by Doyle and Doyle (1987) with minor modifications by
Brondani et al. (2002). DNA concentrations were estimated by
comparison with known concentrations of l DNA on 1% agarose
gels and the final concentration was 3 ng/mL.
2.2. Microsatellite genotyping
Twenty four microsatellite markers with the fluorescent dyes
HEX, 6-FAM, and NED were used in the experiments and the
microsatellite amplification reactions were performed using the
QIAGEN® 2X Multiplex PCR Kit (Qiagen, CA, USA) in a GeneAmp
9700 Thermal Cycler (Applied Biosystems) with an initial dena-turation
step at 95 C for 15 min, followed by 40 cycles of
denaturation (94 C for 30 s), annealing (57 C for 90 s), and
extension (72 C for 90 s), and a final extension step at 72 C for
10 min. The amplified products were diluted in sterile Milli-Q
H2O and the analyses of the fragments were performed using
GeneScan Analysis 2.1 (Applied Biosystems), and the size of the
alleles was obtained using the GeneMapper 3.5 program (Applied
Biosystems).
2.3. Statistical analyses
Genetic analyses were conducted as based on the molecular
profiles generated from the allele frequencies of polymorphic
loci. The number of private alleles was determined using the
GENETIC DATA ANALYSIS (GDA) software (Lewis and Zaykin,
2002). The number of alleles per locus and the PIC (Poly-morphism
Information Content) were determined by Power-
Marker version 3.23 (Liu and Muse, 2005). The probability of
identity (PI) values and the number of pairs of identical in-dividuals
were calculated using the IDENTITY v.1.0 software
(Wagner and Sefc, 1999).
Genetic distance was estimated using the Rogers coefficient as
modified by Wright (1978) using the NTSYS v.2.02 software (Rohlf,
1998) and then subjected to cluster analysis using the UPGMA
(Unweighted Pair Group Method with Arithmetic Means) algo-rithm.
The data were plotted using a dendrogram for the visuali-zation
of genetic distances. To evaluate the consistency of the
dendrogram obtained by UPGMA, the cophenetic correlation co-efficient
(CCC) was calculated.
2.4. Phenotypic data
Rice accessions were evaluated, under greenhouse conditions,
for levels of phenotypic resistance to the sugarcane borer and
their genetic diversity was determined. The phenotypic response
of rice due to sugarcane borer attack was determined under
greenhouse conditions. Experiments were planted in three times
in 2010 (Jan. 01, March, 11 and July 07). The experimental design
was a randomized block with four replications. A plot consisted
of 10 plants, each of which was infested (on the main stem at the
stage of flag leaf formation) with two neonate larvae of
D. saccharalis per plant.

J.B. Nascimento et al. / Crop Protection 67 (2015) 43e51 45
Table 1
Identification number, common name, origin, institution and level of resistance to rice stem borers of selected rice accessions in the Core Collection of the EMBRAPA Rice and
Beans genebank.
Identification
numbera
The neonate D. saccharalis larvae used to infest the rice plants
were obtained from eggs provided by the company Biocontrol®,
Sert~aozinho, SP, Brazil where the borer was reared on an artificial
diet (Vacari et al., 2012). The cards with the eggs of the sugarcane
borer were treated with copper sulfate in the laboratory of
Biocontrol® and shipped to Goias. There they were maintained until
larval emergence in the EMBRAPA Rice and Beans Entomology
laboratory in acrylic type 350 ml germination boxes (Gerbox) (Reis
et al., 2000) containing moistened cotton.
The neonate larvae were placed on the leaf sheaths of rice plants
with a fine camel's hair brush. Thirty days after infestation, the rice
plants were cut at ground level and taken to the laboratory where
the stalks were examined. The following phenotypic data were
recorded: NLL e number of live larvae/stem; IM e individual (one
larva) mass in grams of surviving larvae; ED e external diameter of
the stem; ID e internal diameter of the stem (the diameter was
measured between five and 10 cm from the base of stem); NTP e
number of tillers produced by 30 days after larval infestation; NSA
e number of stems attacked after larval infestation and NLD e
number of stems with no larval damage after larval infestation.
Analyses of variance and the ScotteKnott test (Scott and Knott,
1974) were performed for comparison of means while multivariate
statistics were performed to verify the separation of groups in the
population for resistance to D. saccharalis. A CVA (Canonical Vari-able
Analysis), the matrix of Mahalanobis distance (D2) and Tocher's
grouping method (Cruz and Carneiro, 2006) were calculated using
GENES software (Cruz, 2006). To determine the correlation be-tween
two similarity matrices of morphological traits and molec-ular
data, the Mantel test was performed using PAST software
(Hammer et al., 2001).
Common name Country
of origin
Institution Levels of
resistance
Stem borer species Reference
Introduced lines and cultivars
CNA 0002846 Patnai 6 India IRRI Resistant Chilo suppressalis Pathak and Khush (1975), Ferreira et al. (1979),
Martins (1983)
CNA 0003021 Su yai 20 China IRRI Moderately
resistant
Chilo suppressalis Pathak and Khan (1994), Ferreira et al. (1979),
Martins (1983), Heinrichs et al. (1985)
CNA 0003053 Ti Ho Hung e IRRI Resistant Diatraea saccharalis Martins et al. (1977), Heinrichs et al. (1985),
Ferreira et al. (1979), Martins (1983), Pathak
and Khush (1975)
CNA 0003084 TKM 6 India IRRI Resistant Diatraea saccharalis
Chilo suppressalis
Stem borers
Martins et al. (1977), Martins (1983)
CNA 0003271 IR 42 Philippines IRRI Resistant Chilo suppressalis
Stem borers
Pathak and Khan (1994)
CNA 0004014 IR 13429-109-2.2.1 Philippines IRRI e e e
CNA 0005471 IR 40 Philippines IRRI Resistant Chilo suppressalis,
Scirpophaga incertulas
Heinrichs et al. (1985)
CNA 0005484 Chiang- an-Tsao-Pai Ku China IRRI Resistant Chilo suppressalis
Martins et al. (1977), Heinrichs et al. (1985)
CNA 0005485 C 409 Myanmar IRRI Resistant Chilo suppressalis
Martins et al. (1977), Heinrichs et al. (1985)
Brazilian lines and cultivars
CNA 0002023 IAC 47 Brazil IAC Susceptible Elasmopalpus lignosellus
Martins et al. (1977), Ferreira et al. (2000)
CNA 0006187 Caiapo Brazil EMBRAPA e e e
CNA 0006710 Carajas Brazil EMBRAPA e e e
CNA 0007475 Canastra Brazil EMBRAPA Tolerant Diatraea saccharalis Ferreira et al. (2000)
CNA 0007706 Confiança Brazil EMBRAPA e e e
CNA 0008070 Primavera Brazil EMBRAPA Moderately
resistant
Diatraea saccharalis Lana et al. (2003), Ferreira et al. (2000)
CNA 0008172 Bonança Brazil EMBRAPA Tolerant Diatraea saccharalis Ferreira et al. (2000)
CNA 0008305 Carisma Brazil EMBRAPA e e e
CNA 0008711 Soberana Brazil EMBRAPA e e e
CNA 0010618 IAC 201 Brazil IAC e e e
CNA 0004121 Guarani Brazil EMBRAPA e e e
Land races
CA 220025 Canela de ferro Brazil EMBRAPA e e e
a The number is used in the EMBRAPA Rice and Beans gene bank.

3. Results
3.1. Genetic diversity of rice accessions based on cluster analysis
Atotal of 261 alleles were detected with the set of 24 SSR markers
(Table 2). The average number of alleles per locus was 10.9 ranging
from 4 (RM 171) to 28 (RM 14). Of the total, 92 alleles were private.
The locusRM14 (13 private alleles) (Table 2) and the accessionsTKM
6 (Table 3) (13 private alleles) and IR 42 (Table 3) (9 private alleles)
had the highest number of private alleles. The PIC (Polymorphism
Information Content) ranged from 0.10 (locusRM 171) to 0.87 (locus
OG 106), with an average of 0.63 (Table 2). The PIwas 1.005 1018.
The high degree of polymorphism of microsatellite markers allowed
separation among rice accessions, resulting in rapid and efficient
identification of diversity of the accessions (Table 2).
The dendogram (Fig. 1) demonstrated the genetic relationships
among the 34 accessions, including the accessions reported as
resistant to the sugarcane borer and other rice stem borer species
(Table 1). The cluster analysis separated the accessions into five
groups and four accessions were isolated (Fig. 1). The first group
consisted of 22 accessions; Bonança, Carisma, Caiapo, Carajas,
Soberana, IAC 201, IAC 47, Ti Ho Hung, Guarani and 13 “Canelas de
Ferro” accessions (CA 220025, CA 220241, CA 780099, CA 790164,
CA 790167, CA 790216, CA 790217, CA 790309, CA 790367, CA
810055, CA 810064, CA 980007 and CA 980023). The remaining
groups consisted of two accessions each. The second group con-sisted
of Canastra and Confiança; the third consisted of C 409 and
Patnai 6; the fourth group consisted of accessions Chiang an Tsao
Pai Ku and IR 40; and the fifth group consisted of IR 13429-109-
2.2.1 and IR 42. The four isolated accessions were Primavera, Canela
de Ferro (CA 220268), Su Yai 20 and TKM 6.
The average genetic distance of RogerseWright, obtained
among the 34 accessions analyzed, was 0.63 and this value was
used as the cut-off point for identifying similar groups in the
dendrogram. The cophenetic correlation coefficient was high
magnitude (r 0.80) and significant (*P 0.05).
3.2. Phenotypic relationship of rice accessions
3.2.1. Univariate analysis
The phenotypic response of rice accessions to the borer
(D. saccharalis) indicated a genotypic variation (Table 4). There was
a positive correlation between survival (NLL) and the individual
mass (IM) of surviving larvae, external diameter (ED) and internal
Table 2
Number of alleles, polymorphic information content (PIC) and probability of identity
(PI) detected with 24 SSR markers.
Panel SSR marker Interval Allelesa PIC PI
1 RM 204 106e174 12 (5) 0.74 0.12
1 RM 38 236e274 15 (6) 0.79 0.09
1 4653 84e171 13 (6) 0.82 0.07
1 OG 106 187e252 19 (10) 0.87 0.04
1 RM 257 132e190 18 (9) 0.73 0.12
1 RM 103 328e336 5 (1) 0.44 0.36
2 RM 171 323e344 4 (3) 0.10 0.79
2 RM 231 168e192 8 (3) 0.55 0.26
2 RM 287 90e114 9 (4) 0.40 0.37
2 RM 7 166e184 7 (1) 0.51 0.28
2 RM 229 94e130 10 (1) 0.76 0.35
2 OG 44 153e183 8 (1) 0.75 0.14
3 RM 210 134e158 10 (2) 0.77 0.10
3 RM 222 203e227 8 (0) 0.58 0.26
3 RM 14 161e219 28 (13) 0.81 0.08
3 OG 10 94e138 14 (7) 0.72 0.15
3 RM 309 153e171 5 (2) 0.44 0.51
3 RM 253 99e141 11 (4) 0.65 0.20
4 RM 207 110e144 12 (3) 0.72 0.14
4 RM 252 194e262 13 (6) 0.43 0.33
4 RM 248 78e101 10 (0) 0.82 0.79
4 RM 263 153e189 8 (1) 0.72 0.16
4 RM 11 119e146 8 (3) 0.53 0.27
4 RM 55 229e239 6 (1) 0.57 0.25
Average e e 10.9 0.63 e
Combined value e e e e 1.005 1018
a Numbers in parentheses are private alleles.
Table 3
Identification of private alleles detected with 24 microsatellite markers in 34 rice
accessions.
Accessions SSR marker Private alelles
IAC 47 RM 253, RM 257 102, 171
Patnai 6 RM 287, RM 253,
OG 10, RM 204,
OG 106
91, 99, 114, 158, 197
Su Yai 20 RM 257, RM 14 158, 199
Ti Ho Hung RM 207 137
TKM 6 OG 10, RM 11,
RM 204, RM 257,
RM 253, RM 210,
4653, RM 231,
OG 106, RM 38,
RM 171, OG 106,
RM 252
102, 121, 122, 131, 134,
146, 182, 186, 187, 243,
241, 258, 336
IR 42 RM 253, RM 229,
OG10, RM 263,
RM 309, RM 14, RM 55
100,122, 122, 126, 153,
153, 181, 214, 234
IR 13429-109-2.2.1 RM 287, RM 252,
RM 171, RM 103
94, 114, 218, 323, 330
IR 40 4653, RM 287, RM 11 84, 112, 144
Chiang an Tso Pai Ku 4653, OG 10, RM 11,
RM 7, OG 106,
RM 14, RM 252
111, 116, 146, 184, 199,
206, 238
C 409 RM 207, RM 257,
RM 309, RM 14,
RM 231, OG 106
144, 150, 161, 163,
170, 205
Caiapo 4653 99, 150
Carajas 0 0
Canastra RM 207, RM 14, RM 204 110, 168, 172
Confiança OG 44 183
Primavera 0 0
Bonança RM 204 174
Carisma RM 231, RM 14, RM 38 178, 186, 274
Soberana RM 171 327
IAC 201 0 0
Canela de Ferro
(CA 220025)
RM 14, OG 106 189, 207, 248
Canela de Ferro
(CA 220241)
RM 14 219
Canela de Ferro
(CA 220268)
RM 257, RM 14 178, 218
Guarani OG 10, RM 252 113, 196, 248
Canela de Ferro
(CA 780099)
OG 10, RM 257,
OG 106, RM 38
100, 190, 247, 263
Canela de Ferro
(CA 790164)
RM 14,RM 38 216, 242
Canela de Ferro
(CA 790167)
RM 14, OG 106 179, 252
Canela de Ferro
(CA 790216)
RM 38 251
Canela de Ferro
(CA 790217)
0 0
Canela de Ferro
(CA 790309)
0 0
Canela de Ferro
(CA 790367)
RM 257 132
Canela de Ferro
(CA 810055)
RM 204, 4653,
RM 257, OG 106, RM 38
140, 171, 176, 235, 236
Canela de Ferro
(CA 810064)
0 0
Canela de Ferro
(CA 980007)
0 0
Canela de Ferro
(CA 980023)
RM 210, RM 257,
OG 106
140, 162, 218

Fig. 1. Dendrogram obtained by analysis of 34 accessions of rice by 24 SSR loci through genetic distance of RogerseWright. * Isolated accessions.
diameter (ID) of the stem and number of stems attacked (NSA)
(Table 5). This indicates that the larvae were heavier and had
greater survival when feeding on plants with larger stem di-ameters.
The morphological characteristics (large external diam-eter
of the stem and an internal diameter of the stem greater than
2.5 mm) that favor the growth and development of the sugarcane
borer are common in susceptible accessions.
3.2.2. Multivariate analysis
The genetic dissimilarity estimated by the Mahalanobis distance
(D2) (Table 6) indicated that the accessions that were most diver-gent
(dissimilar) (D2 max ¼ 31.00) were accession IAC 47 (accession
ID 1) and Chiang an Tsao Pai Ku (9) while Ti Ho Hung (4) and
“Canela de Ferro” (CA 220241) (21) were the most similar (D2
min ¼ 0.11). With the cluster analysis by Tocher's grouping method,
it was possible to observe four groups (Table 7), with the largest
number (16) of accessions in group I. This group has important
traits for susceptibility to the borer while the third group (Table 7)
consisted of accessions (3 ¼ Su Yai 20; 8 ¼ IR 40; 9 ¼ Chiang an Tsao
Pai Ku; 23 ¼ Guarani) that were more resistant as indicated in
Table 4.
By employment of the canonical variable analysis (CVA) clus-tering
method, it was possible to observe the distribution of ac-cessions
in a two-dimensional graph (Fig. 2). The positions of the
accessions in the graph were apparently distributed into three
groups, two large (group I and II) and one small [group III: Su Yai 20
(3), IR 40 (8), Chiang an Tsao Pai Ku (9)], in which the accessions
within a group were most similar, and two isolated accessions,
“Canela de Ferro” (CA 220268) (22) and Guarani (23), which were
most divergent. The two principal axes accounted for 81.3% of the
total variation (Fig. 2) among the seven characters (Table 4)
describing the 34 rice accessions.
3.3. Correlation between morphological traits and molecular data
The coefficient of correlation between the distance matrices of
morphological traits and molecular data was not significant
(r ¼ 0.82, P ¼ 0.11). Thus, Mantel's test did not reveal a significant
correlation between the morphological traits and molecular data.
However, the separation of groups as expressed in the molecular
(Fig. 1) and phenotypic (Table 7) data are similar. The largest group
(I), formed by the use of the Tocher's method (Table 7), is similar to
the first group in the dendogram as produced with the molecular
data (Fig. 1).
4. Discussion
4.1. Genetic diversity of rice accessions based on cluster analysis
Using 24 polymorphic SSR markers, the total number of alleles
(261) and the average number of alleles detected per locus (10.9)
(Table 2) was higher than the numbers previously described for
O. sativa genotypes (Vijaya et al., 2010; Narasimhulu et al., 2010).
Using 37 SSR markers, Vijaya et al. (2010) found 88 alleles with an
average of 2.37 alleles per locus, while Narasimhulu et al. (2010)
reported 96 alleles with an average of 2.67 alleles per locus. The
PIC value of 0.63 (Table 2) was higher than that previously reported
for genetic diversity assessment in rice germplasm (Brondani et al.,
2006; Giarrocco et al., 2007; Borba et al., 2009b; Pervaiz et al.,
2009). The number of private alleles (92) found in this study
(Table 2) was higher than that reported by Alvarez et al. (2007) and
Borba et al. (2009a). The PI value was low (1.005 1018) (Table 2)
which corresponds to the probability of finding, at random, two
individuals with the same genotype when analyzed by a set of
markers. The analysis of the distribution of number of alleles pre-sent
in the accessions provides an indirect measure of the level of
heterozygosity and diversity present in these accessions (Aitken
et al., 2006). Thus, the higher number of alleles and PIC detected
in our study indicates that the rice accessions analyzed are a good
source of genetic variability to be explored in crosses with rice
germplasm in an effort to increase the allele richness of genebanks.
The cophenetic correlation coefficient (r ¼ 0.82) revealed the
existence of a good fit between the similarity matrix and the
dendrogram (Fig. 1) where we could observe a division of the
groups. According to studies by Li et al. (2010), this genetic diver-gence
in the Embrapa rice germplasm collection could be related to

Table 4
Number of live larvae on the plant (NLL), individual mass (IM) in grams of surviving larvae, external diameter of stem (ED) and internal diameter of stem(ID) in mm, number of
tillers produced (NTP), number of stems attacked (NSA) and number of stems with no larval damage (NLD) after larval infestation on 34 rice accessions evaluated to detect
resistance to Diatraea saccharalis.
Source of variation Mean square
NLL IM ED ID NTP NSA NLD
Blocks 95.20 0.0025 0.305 0.175 9.51 25.49 34.74
Accessions 40.63ns 0.0026ns 7.801** 2.153** 49.48** 10.05ns 52.60**
Residue 30.19 0.0018 1.374 0.881 8.89 6.91 15.39
Average 6.18 0.05 5.04 2.47 3.25 5.31 7.71
CV (%) 88.87 79.00 23.26 37.96 91.83 49.54 50.91
Accessionsa Average
1- IAC 47 10.37 a 0.0710 a 5.82 a 2.51 a 0.62 c 5.9 a 4.50 c
2- Patnai 6 7.62 a 0.0331a 4.25 c 2.26 b 5.00 b 5.2 a 9.75 b
3- Su Yai 20 2.50 a 0.0391 a 2.96 d 1.30 c 6.50 b 4.7 a 11.75 a
4- Ti Ho Hung 10.25 a 0.0689 a 5.35 b 2.82 a 1.75 c 7.4 a 4.25 c
5- TKM 6 9.37 a 0.0522 a 4.63 c 2.39 b 4.50 b 6.1 a 8.37 b
6- IR 42 5.00 a 0.0540 a 5.06 b 2.36 b 5.40 b 6.7 a 8.62 b
7- IR 13429-109-2.2.1 7.75 a 0.0448 a 4.76 b 2.26 b 5.00 b 6.7 a 8.25 b
8- IR 40 3.00 a 0.0674 a 3.78 c 1.67 c 10.50 a 6.0 a 14.50 a
9- Chiang an Tso Pai Ku 4.87a 0.0248 a 2.97 d 1.35 c 11.37 a 7.4 a 12.75 a
10- C 409 4.75 a 0.0537 a 4.80 b 2.24 b 5.50 b 3.6 a 11.37 a
11- Caiapo 6.87a 0.0385 a 4.89 b 2.67 a 1.87 c 3.9 a 8.00 b
12- Carajas 6.25 a 0.0547 a 4.27 c 2.25 b 2.62 c 6.1 a 6.50 c
13- Canastra 4.25 a 0.0463 a 5.13 b 2.46 a 4.62 b 3.5 a 11.12 a
14- Confiança 6.50 a 0.0369 a 5.49 b 2.53 a 2.62 c 3.7 a 8.75 b
15- Primavera 3.12 a 0.0301 a 4.35 c 2.11 b 3.12 c 5.5 a 7.62 c
16- Bonança 2.00 a 0.0163 a 4.96 b 2.33 b 2.50 c 3.0 a 9.50 b
17- Carisma 5.62 a 0.0434 a 4.90 b 2.39 b 4.12 b 5.2 a 8.87 b
18- Soberana 4.12 a 0.0883 a 3.78 c 1.78 c 4.25 b 5.1 a 9.12 b
19- IAC 201 3.00 a 0.0535 a 3.88 c 2.05 b 1.12 c 5.2 a 5.12 c
20- Canela de Ferro (CA220025) 5.12 a 0.0356 a 6.03 a 2.93 a 1.87 c 4.9 a 6.87 c
21- Canela de Ferro (CA220241) 9.25 a 0.0572 a 5.40 b 2.82 a 1.62 c 6.9 a 4.62 c
22- Canela de Ferro (CA220268) 6.50 a 0.0451 a 6.15 a 2.37 b 3.75 c 5.1 a 8.12 b
23- Guarani 2.87 a 0.0396 a 2.88 d 1.48 c 1.75 c 4.6 a 6.37 c
31- Canela de Ferro (CA810055) 5.50 a 0.0487 a 5.23 b 2.55 a 2.25 c 3.6 a 8.62 b
33- Canela de Ferro (CA980007) 6.62 a 0.0520 a 6.11 a 3.18 a 2.75 c 4.4 a 8.00 b
34- Canela de Ferro (CA980023) 6.62 a 0.0738 a 5.35 b 3.04 a 1.87 c 5.5 a 6.00 c
a Numbers 1e34, preceding the accession number refer to arbitrary numbers used to identify the accessions evaluated in this study.
the geographic origin of the accessions as they were received from
rice breeding programs in Asia (International Rice Research Insti-tute)
and from Brazilian institutions, IAC (Instituto Agronomico de
Campinas) and Embrapa- Rice and Beans Center.
4.2. Phenotypic relationship of rice accessions
Resistance of rice to the sugarcane borer has been reported by
several authors in the Philippines, Brazil, China and the USA
(Patanakamjorn and Pathak, 1967; Martins et al., 1977, 1981,
1989a,b,c; Rubia-Sanchez et al., 1998; Zhu et al., 2002; Way et al.,
2006). These authors considered the diameter of the rice stem as an
important quantitative trait for resistance. They observed that least
attacked plants had the smallest stem diameters and numbers of
live larvae. A stem with narrowgalleries becomes a physical barrier
that restricts the movement and feeding of the stem borer, which
characterizes resistance, in the form of antixenosis (Patanakamjorn
and Pathak, 1967; Lara, 1991). Our results agree with those of
Ntanos and Koutroubas (2000) and Hosseini et al. (2011).
The accessions that had more tillers and a larger number of
undamaged stems were IR 40 and Chiang Tsao Pai Ku. The data
show that accessions with high tillering capability after infestation
have a distinct capability to recover from the damage caused by the
stem borer. According to Martins et al. (1981), rice resistance to
sugarcane borers is associated with tillering of the plant after
infestation, a characteristic of tolerant genotypes.
Table 5
Correlation coefficients between the characteristics analyzed in 34 rice accessions
for resistance to Diatraea saccharalis.a
Charactersb NLL IM ED ID NTP NSA NLD
NLL 1 0.456** 0.597** 0.631** 0.395* 0.453** 0.589**
IM e 1 0.404* 0.449** 0.322ns 0.241ns 0.448**
ED e e 1 0.929** 0.599** 0.072ns 0.552**
ID e e e 1 0.677** 0.039ns 0.651**
NTE e e e e 1 0.197ns 0.886**
NSA e e e e e 1 0.257ns
NLD e e e e e e 1
a * and ** ¼ limits of 1 and 5% probability. ns ¼ non-significant values.
b Characters evaluated: number of live larvae (NLL); individual mass of larvae in g
(IM); external diameter of the stem in mm (ED); internal diameter of the stem in
mm (ID); number of tillers produced after infestation (NTP); number of stems
attacked (NSA); number of stems with no larval damage (NLD).

Table 6
Dissimilarity, based on the Mahalanobis distance (D2), between pairs of accessions of rice for the seven characters measured: number of live larvae (NLL); individual mass of larvae in g (IM); external diameter of the stem (ED) and
internal diameter of the stem in mm (ID); number of tillers produced after infestation (NTP); number of stems attacked (NSA); number of stems with no larval damage (NLD).
a 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
1 9.9 23.2 2.8 6.3 7.9 6.7 26.3 31.0 7.7 5.0 7.6 6.5 2.5 9.5 7.1 5.9 12.7 10.2 2.1 2.6 2.3 16.7 1.8 0.9 1.3 0.9 0.8 1.1 1.5 3.4 1.9 1.9 4.2
2 4.6 5.2 0.6 2.7 1.2 7.4 7.8 1.6 1.9 1.3 1.7 4.0 1.8 2.8 1.0 2.9 3.7 5.8 4.8 9.1 4.3 9.3 8.8 9.3 7.5 6.7 6.3 6.6 2.9 5.4 4.9 3.9
3 16.7 7.5 7.1 7.0 2.5 2.8 5.3 10.2 6.1 6.6 13.1 4.7 7.6 6.5 2.7 6.5 16.4 16.0 19.1 3.5 21.5 21.6 23.5 19.2 18.0 18.1 18.1 10.5 15.4 16.3 13.1
4 2.5 4.0 2.9 19.1 21.2 6.4 3.0 2.8 5.4 3.7 5.2 6.3 3.1 8.3 5.5 2.2 0.1 5.7 11.0 2.2 2.0 1.2 2.3 1.5 1.0 1.0 3.3 0.9 1.7 0.9
5 2.0 0.6 9.5 10.9 1.8 1.4 1.0 1.7 2.8 2.3 3.3 0.7 3.5 3.9 3.9 2.4 6.6 6.1 5.9 5.4 5.9 4.8 3.7 3.5 3.9 2.0 2.9 2.9 2.0
6 0.5 7.0 9.0 2.7 4.6 1.8 2.4 4.4 1.4 3.5 0.9 3.6 4.3 3.7 3.6 5.4 7.4 8.1 6.5 7.5 6.0 4.3 4.0 3.9 3.6 2.9 4.3 3.6
7 8.1 9.2 2.1 2.7 1.2 1.8 3.1 1.4 2.9 0.4 3.6 4.0 3.3 2.6 5.3 6.6 7.2 5.9 6.4 5.3 3.8 3.4 3.5 2.6 2.6 3.3 2.9
8 1.9 7.3 15.1 9.5 8.8 16.6 8.1 12.2 8.7 4.9 12.1 19.3 18.9 20.2 10.3 25.0 23.5 27.2 22.4 19.5 20.0 20.5 14.3 17.4 18.9 16.2
9 10.8 16.9 10.5 12.2 20.0 8.6 14.2 10.6 7.9 13.0 22.2 20.7 24.9 10.1 30.5 29.0 30.5 27.3 24.2 23.7 23.6 17.8 20.9 22.5 19.1
10 2.3 2.6 0.2 2.2 2.6 1.6 1.0 2.2 4.5 4.8 5.8 5.7 5.7 7.5 6.7 9.1 5.4 4.9 5.4 6.0 1.4 4.6 3.9 4.4
11 1.8 1.7 1.4 3.1 1.9 1.5 5.1 3.3 2.8 2.4 6.4 5.7 4.1 4.2 4.3 2.9 3.5 3.2 3.4 0.7 2.7 1.7 1.6
12 2.5 4.1 0.8 2.9 0.9 2.1 1.0 4.2 2.6 8.3 3.0 6.0 6.3 6.2 5.3 4.9 4.4 4.2 2.5 2.9 4.0 1.6
13 1.4 2.3 1.0 0.7 3.1 4.4 3.3 4.7 4.5 6.3 6.5 5.5 7.5 4.1 3.9 4.1 4.6 0.8 3.4 2.7 3.6
14 4.4 1.6 1.8 7.2 6.2 1.2 2.9 2.0 9.8 3.9 2.8 3.7 1.5 1.7 1.8 2.2 0.4 2.0 0.9 3.2
15 1.7 0.9 2.6 1.4 4.3 4.4 7.8 2.9 8.9 8.5 8.5 6.8 6.4 5.7 5.2 3.1 4.1 5.2 3.7
16 1.3 4.8 3.5 2.8 5.1 4.9 5.2 7.6 6.7 7.5 4.4 5.1 4.8 4.6 1.2 3.9 3.4 4.4
17 2.9 2.9 2.5 2.6 4.6 5.3 5.9 5.0 5.8 3.9 3.2 3.0 3.1 1.2 2.2 2.4 2.2
18 2.6 9.3 8.2 11.8 2.7 10.1 10.8 12.9 9.7 8.9 9.4 9.7 4.8 7.3 8.6 5.5
19 6.3 5.0 11.3 1.4 7.4 8.8 8.3 7.2 7.7 7.1 6.5 4.0 5.0 6.6 3.1
20 1.5 1.9 11.7 3.3 1.8 1.8 1.0 1.1 0.6 0.4 1.7 0.7 0.6 2.5
21 4.9 10.3 2.3 1.9 1.0 1.9 1.4 0.7 0.7 2.7 0.6 1.3 0.8
22 16.9 6.0 3.3 4.9 2.7 1.9 2.3 2.5 3.5 2.9 2.3 6.8
23 13.7 15.6 15.3 13.1 13.6 13.2 12.6 7.0 10.6 11.8 7.6
24 0.6 1.2 0.9 1.5 1.7 2.2 3.3 1.8 2.0 1.8
25 0.9 0.4 0.4 0.6 1.1 2.9 1.0 1.0 2.2
26 1.0 1.3 0.8 0.8 3.9 1.2 1.6 2.2
27 0.5 0.6 0.9 1.6 0.8 0.5 2.0
28 0.2 0.6 2.0 0.5 0.7 2.2
29 0.1 2.1 0.2 0.5 1.7
30 2.5 0.2 0.8 1.8
31 1.8 1.1 2.0
32 0.7 1.0
33 1.6
D2 max ¼ 31.00 (Accessions 1 (IAC 47) and 9 (Chiang Tsao Pai Ku ¼ most dissimilar; D2 min ¼ 0.11 (Accessions 4 (Ti Ho Hung) and 21 (“Canela de Ferro” [CA 220241]) ¼ most similar. See Table 4 for the names of the cultivars
1e34.

Su yai 20, IR40 and Chian an Tsao Pai Ku exhibited resistance to
D. saccharalis as based on the number of live larvae (NLL), individual
mass weight of larvae (IM), internal diameter of the stem (ID),
number of tillers produced (NTP) and number of tillers with no
larval damage (NLD) (Table 4). Suyai 20 has been reported to have
moderate resistance to Chilo suppressalis (Walker) (Lepidoptera:
Crambidae) in Asia; IR40 with resistance to C. suppressalis and the
yellow stem borer, Scirpophaga incertulas (Walker) (Lepidoptera:
Pyralidae), in Asia; and Chiang an Tsao Pai Ku with resistance to
C. suppressalis in Asia and D. saccharalis in Brazil and the USA
(Heinrichs et al., 1985). These cultivars were classified in pheno-typic
group III by Tocher's grouping method (Table 7) and were
separated according to the dispersion of scores based on the CVA
clustering method on seven phenotypic characters of rice resis-tance
to D. saccharalis (Fig. 2).
Selvi et al. (2002) observed that the accession TKM 6 proved to
be moderately resistant to the yellow stem borer S. incertulas
(Walker). This classification was confirmed in Selvi's studies with
RAPD markers. According to Khan et al. (1991) and Pathak and Khan
(1994), the resistance of TKM 6 is related to physical and chemical
factors that interfere in the development of the striped stem borer,
C. suppressalis. In our study the accession TKM 6 was moderately
resistant and genetically separate from groups of accessions most
attacked by the sugarcane borer.
The accession IAC 47 was the most susceptible to attack by
D. saccharalis larvae as based on NLL, IM, NTP and NLD (Table 4).
This cultivar has an internal stem diameter greater than 2.5 mm, a
morphological characteristic which is favorable to the growth and
development of D. saccharalis. The classification of IAC 47 as sus-ceptible
to D. saccharalis has been reported by other authors
(Martins et al., 1977, 1989a,b; Khan et al., 1991). Accessions like Ti
Ho Hung and the 13 “Canelas de Ferro” accessions occurred in the
same group as cultivar IAC 47, according to the multivariate
analysis of phenotypic and molecular data. Only one accession of
“Canela de Ferro” (CA 220268) was not associated in the group in
the phenotypic and molecular analysis. CA 220268 was the only
“Canela de Ferro” accession characterized by an internal diameter
of the stem less than 2.5 mm (2.37 mm). There has only been one
study where the Brazilian rice accessions have been evaluated for
resistance to the sugarcane borer. Under natural conditions in the
field Ferreira et al. (2000) observed that cultivars Bonança, Pri-mavera
and Carisma were more tolerant to D. saccharalis than
other cultivars as based on the low level of plant damage and the
high amount of grain production. However, more in depth studies
are needed to better understand the levels and mechanisms of
resistance involved in these rice accessions to the sugarcane
borers.
4.3. Correlation between morphological traits and molecular data
Through the evaluations using the SSR markers and morpho-logical
data we were able to differentiate the most divergent ac-cessions.
It was observed that therewas a correspondence between
the groups formed through clustering methods, under both aspects
analyzed (phenotypic and molecular analyses). However, the
Mantel's test did not reveal a significant correlation between the
phenotypic (morphological traits) as shown in Table 4 and the
molecular data (Fig. 1). In this case, different strategies for the
development of new molecular markers in rice, such as Single
Nucleotide Polymorphisms (SNPs), can be used to identify specific
loci on the rice genome associated with D. saccharalis resistance.
In conclusion, the multivariate analysis was successful in sepa-rating
accessions into groups in relation to resistance to
D. saccharalis. The results indicate that morphological traits and
markers are useful for diversity analysis. According to the
morphological traits, different groups were identified in relation to
resistance to D. saccharalis. The molecular analysis of rice acces-sions
identified the genetic diversity of these materials which can
be exploited in the breeding program by using these accessions as
donor sources to amplify the genetic bases of genetic resistance of
Brazilian upland rice varieties to the sugarcane borer.
Acknowledgments
The authors thank CAPES (Coordination of Improvement of
Higher Education Personnel) for the scholarship granted to the first
author and to Dr E. A. Heinrichs, MS Kyle Koch and Reynard
Odenheimer for the helpful suggestions in reviewing the manu-script.
We are grateful to our co-workers Edmar Cardoso da Silva,
Edson Djalma and Jose Francisco Arruda e Silva for their constant
support. This research was financed by Brazilian Agricultural
Research Corporation e Embrapa (Project: 02090300300030).
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