




































 Agricultural Science; Vol. 2, No. 1; 2020 
ISSN 2690-5396   E-ISSN 2690-4799 

https://doi.org/10.30560/as.v2n1p83 

83                             Published by IDEAS SPREAD 
 

Genetic Variability and Heritability among Sugarcane Genotypes at 
Early Stage of the Advanced Selection for some Agronomic Traits in 

Ferké, Northern Ivory Coast 
YM Béhou1,2 & CB Péné2 

1 Agronomic Sciences and Agricultural Engineering, EDP/INPHB, Yamoussoukro, Ivory Coast  
2 Research and Development Department, SUCAF-CI/SOMDIAA, Ivory Coast  
Correspondence: Crépin B. PÉNÉ, SUCAF-CI/SOMDIAA Group, Research & Development Department, 22 rue 
des Carrossiers, Treichville Zone 3, P.O. Box 1967 Abidjan 01, Ivory Coast. Tel: 225-4783-1916. Email: 
bpene@sucafci.somdiaa.com/cbpene20@yahoo.com 
 
Received: March 15, 2020   Accepted: April 12, 2020   Online Published: April 16, 2020 
 
Abstract 
Selection in sugarcane from true seed was recently implemented in Ivory Coast with the aim to increase the genetic 
variability of crop material used and, therefore, improve significantly sugar yields with a positive impact on the 
competitiveness of the Ivorian sugar industry. The objective of study was to determine the best performing cane 
genotypes among 29 clones tested under sprinkler irrigation, in comparison with a check variety (R579). It was 
carried out on R3-002 commercial sugarcane plantation of Ferké 2 sugar estate, in northern Ivory Coast. The 
experimental design used was a randomized complete block with 30 cane genotypes in three replications. Each 
plot comprised two dual rows of five meters with 0.5 and 1.90 m of inter-row spacing, i.e. 19 m² per plot and about 
600 m² for the whole experiment. Based on sugar yields, four promising genotypes namely RCI12/15, RCI12/19, 
RCI13/121 and RCI13/136 were equivalent to the check variety which performed 15.6 t/ha. They are due to 
undergo the advanced selection stage during the 2020-21 cropping season for three more years for determining the 
first new sugarcane varieties of RCI origin to be tested commercially in Ferké sugar estates. Their yield 
performances ranged from 12.8 to 13.8 t sugar/ha, i.e. from 134.0 to 144.8 t cane/ha compared to 161.3 t/ha for 
the control variety. Although a relatively high level of stem-borer infestation rate recorded, with 15.6% on average 
(almost three times the tolerable threshold value of 5%), reasonable values of sucrose percent obtained with the 
promising genotypes, ranged from 12.7 to 13.9% over both crop cycles, compared with 13.6% for the check. 
Higher heritability values ranging from 61 to 80.5% were observed in traits like sugar yield, sucrose content 
(62.6%), recoverable sucrose (60.6%), fiber content (72%), stem-borer infestation rate (80.5%), number of 
internodes/stalk (67.7%), and flowering rate (79.6%). In contrast, lower and moderate values of heritability were 
observed for Pol juice (59.8%), juice purity (50.5%), cane yield (53%), millable stalk number/ha (29.5%), single 
stalk weight (36.7%), single stalk height (45%), and single stalk diameter (38.7%).  
Keywords: phenotypic correlation, genotypic correlation, coefficient of variation, genetic advance, yield trait, 
juice quality 
1. Introduction 
Sugarcane is a C4 plant grown in tropical and subtropical regions of the world as an important cash crop which 
contributes to approximatively 80% of the world sugar production, greatly exceeding sugar beet as a another source 
of sugar (Dahlquist, 2013). In addition to being a source of sugar, sugarcane is an important bioenergy crop, with 
an energy ratio of ethanol production five times higher than that of maize (Goldemberg, 2008; Waclawovsky et al, 
2010). It is considered by the US Environmental Protection Agency as a feedstock for production of advanced 
biofuel due to its superior contribution to reduce the life cycle greenhouse gas production in the fight against global 
warming and climate change (Altpeter and Karan, 2018). In 2003, the FAO estimated that sugarcane had a 
worldwide gross production value of $81.5 billion (FAO, 2013). It was grown on about 27.1 million ha with a 
world harvest of 1.9 billion metric tons, higher than maize (1.0 billion t), rice (741.0 million t) and wheat (729 
million t) (FAO, 2014). Sugarcane is ranked third in quantity of plant calories in the human diet (Moore and Botha, 
2013). As a result of its very high biomass production, well-established farming, harvesting and processing 
technologies, sugarcane is a leading candidate for bioenergy production and a feedstock for bio-refineries. 
However, productivity improvements in sugarcane have been negligible in the past three decades, and production 



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statistics are reflecting decreased yields globally (FAO, 2014). In all cases, increased sugarcane production is 
linked to expansion of land surface rather than to increases in yield (Jackson, 2005).  
Breeding superior commercial cultivars is crucial for maintaining sugarcane production, which will benefit from 
research in sugarcane genome sequencing and genetic mapping. These research areas focused on understanding 
sugarcane’s genome structure, organization and inheritance patterns. They also help in understanding genetic 
variations within sugarcane populations or germplasms that control important agronomic traits (Yang et al, 2018). 
Usually, the ultimate objective of sugarcane breeding programs is to release varieties which improve the 
profitability of the sugar industry being targeted. That is why breeders need to determine the optimal weightings 
that should be applied to each trait being selected for. A first step towards this involves identifying all traits 
influencing industry stakeholders and determining the relative economic value of variation in each trait, preferably 
in quantitative terms (Wei et al, 2006). As industries change, the economic value of traits may change. In recent 
decades, weightings of some traits have changed in response to developments such as the introduction of 
mechanical harvesting, increased use of sugarcane for energy production and change in agronomic practices. In 
all sugarcane breeding programs worldwide, the key targeted traits are resistance to important local diseases and 
pests, commercially extractable sucrose content, cane yield, acceptable fiber content and ratooning performance. 
In some programs, other traits affecting costs of harvesting or crop management are of importance. 
Sugarcane varieties tend to run out or decline after some years of cultivation in a specific area (Khan et al, 2009). 
To obtain high yield on a sustainable basis, it has been essential to substitute varieties regularly grown with new 
clones. Sugarcane varieties are clonally propagated and therefore are not expected to undergo genetic changes as 
it may occur in a seed propagated crop except for the variety decline over several ratoons due to disease incidence 
and other environmental constraints with therefore a need for replacement (Ali et al, 2017).  
Genetic improvement in cane and sugar yields may be achieved by targeting traits closely associated to them. A 
number of attributes have been proposed as indirect selection criteria for genetic improvement of yields in plant 
breeding programs (Rebettzke et al, 2002). Heritability represents the relative importance of genetic and 
environment factors in the expression of phenotypic and genotypic differences among genotypes within a 
population (Kang et al, 1983; Dagar et al, 2002 cited by Ehib et al, 2015). Consequently, the knowledge of 
heritability related to important traits and the correlations among them are key issues to determine the best selection 
strategy (Hallauer and Miranda, 1988; Falconer, 1989). Genotypic coefficient of variation (GCV) is another 
measure of relative genetic variation of a trait within a population (Ram & Hemaprabha, 1992). Traits exhibiting 
relatively high GCV estimates may respond favorably to selection. Chaudhary (2001) reported high GCV for single 
stalk weight and millable cane number per unit area. Genotype x environment interactions (GxE) are a serious 
concern in breeding programs as they affect selection decisions. When a rank of a genotype changes across 
environments, it requires evaluation of genotypes across environments to determine their real value (Kimbeng et 
al, 2002). Studies in various sugarcane breeding programs have reported significant GxE interactions for cane and 
sugar yields (Parfitt, 200; Kimbeng et al, 2002; Glaz & Kang, 2008). 
The objective of study was to evaluate the variability of thirty sugarcane genotypes through heritability, genetic 
gain and genetic variations of some yield and juice quality traits. 
2. Material and Methods 
2.1 Site Characteristics 
The study was carried out on a Ferké 2 sugarcane field (R3-002) sprinkler irrigated with center pivot (9°16’ N, 
5°22’ W, 325 m a.s.l), in northern Ivory Coast. The prevailing climate is tropical dry with two seasons: one, starting 
from November to April, is dry and the other, from May to October, is wet. The dry season is marked by the 
Saharan trade wind, which blows over mid-November to late January. The rainfall pattern is unimodal and 
focussed on August and September which total amount of rainfall reaches almost half of the average annual rainfall 
(1200 mm) with an average daily temperature of 27 °C. Average maximum and minimum daily air temperatures 
reach 32.5 and 21 °C, respectively.  To meet crop water requirements, the total amount of irrigation water required 
reaches 700 mm/year (Konan et al a-b, 2017; Péné et al, 2012). Both Ferké sugar mill plantations cover around 
15 500 ha with 10 000 ha under irrigation and 3 500 ha of rainfed village plantations, lie mainly on shallow or 
moderately deep soils built up on granites. Main soil units encountered are oxisols and temporally waterlogged 
soils in valley bottoms of Bandama and Lokpoho river basins with a sandy-clay texture. 
2.2 Cane Genotypes Used 
All 29 cane genotypes tested, of Reunion and Ivory Coast origin (RCI), derived from about 8,000 true seeds of 60 
different families (or crosses) provided by eRcane Sugarcane Development Centre of Reunion Island in November 



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2014 and sowed late December 2014. They were pre-selected within families over a period of three years involving 
three consecutive steps starting from one seedling to one stool of tillers and one line of 3 m long per genotype 
without replication. During this process, the genotypes used were pre-selected following ratings based on hybrid 
vigor, tillering ability, ratooning performance and tolerance to endemic diseases like smut, leaf scald, pokkah 
boeng and sugarcane streak mosaic (SCSM). Parents of genotypes investigated, as complex polyploids, were 
commercial varieties of different origins. The heterozygous and polyploidy nature of sugarcane has resulted in 
generations of greater genetic variability. Knowledge on the nature and magnitude of variability present in the 
genetic material is therefore of prime importance for breeders to conduct effective selection programs. Coefficients 
of variation along with heritability as well as genetic advance are very essential to improve any trait of sugarcane 
because this would help in knowing whether or not the desired objective could be achieved from the material to 
be investigated (Tadesse et al, 2014). 
2.3 Experimental Design 
The experiment was carried out from late March 2018 to mid-February 2020 in plant cane and first ratoon, 
following a randomized complete block design (RCBD) with 30 different genotypes, including the check variety 
R579, in 3 replicates. A plot comprised 2 dual rows of 5 m long with narrow and wide spacings of 0.50 m and 1.90 
m. Field managements in terms of sprinkler irrigation, fertilizer and herbicide applications were done according 
to usual practices in commercial plantations.  
2.4 Agronomic Traits Investigated 
Data was collected at harvest from both dual rows for millable stalk number/ha, cane yield, juice quality traits 
(sucrose, purity, and recoverable sucrose), fiber content, and damaged internodes by stem borer (Eldana 
saccharina W). 
At harvest, burned cane fresh production of both dual rows of each plot was weighed separately to determine crop 
yield. Moreover, 50 millable stalks were randomly chosen within every plot and split longitudinally with a machete 
in order to determine the percentage of bored or attacked internodes and cane (%BIN, %BC) by stem borer.  
Thirty millable cane stalks were sampled per plot for sucrose analyses in the laboratory. Prior to sample grinding 
operations in the laboratory for sucrose analyses, each stalk was cut into 3 pieces of almost equal length, while 
separating them in basal, median and top parts. This allowed to randomly reconstitute 3 batches of 10 stalks for a 
better homogenization of the initial field sample by permutation of the pieces so that each reconstituted stalk was 
composed of parts from 3 different cane stalks. Eventually, only one batch of 10 reconstituted stalks over 30 (1/3 
of initial sample) were ground for a series of sucrose analyses to determine the sucrose content (Pol%C), fiber 
content (Fiber %C), juice purity (Purity %C) and recoverable sucrose (SE%C). Equipment used comprised a Jefco 
cutter grinder, a hydraulic press (Pinette Emideceau), a digital refractometer BS-RFM742 and a digital polari-
meter SH-M100. Hoarau (1970) reported on methods used in the determination of required technological 
parameters. The recoverable sucrose was calculated as follows (Hugot, 1999; Péné et al, 2016):  
SE %C = [(0.84 x Pol%C) (1.6 -60/Purity) - (0.05 x Fib %C)] with: 
Purity %C = (Pol juice/Brix) x 100 and Pol juice = Pol factor x Pol read.  
Pol%C = Factor n x Pol juice 
Factor pol, depending on brix value (amount of soluble dry matter in juice measured with a refractometer), was 
provided by Schmidt table relative to a polarimeter for 26 g of glucose. The fiber content and factor n were 
provided by a table, depending on the weight of fiber cake obtained after pressing 500 g of cane pulp resulting 
from the grinding operation of each sample of cane stalks. 
2.5 Phenotypic and Genotypic Coefficients of Variation, Heritability and Genetic Advance 
The phenotypic and genotypic variances for each trait were estimated from the RCBD analysis of variance (Table 
1). The expected mean squares under the assumption of random effects model was computed from linear 
combinations of mean squares were determined as follows (Burton & Davane, 1953 cited by Shitahum et al, 2018): 
Genotypic variance (σ²g) = (MS g – MSe)/r 
Environmental variance (σ²e) = MSe 
Phenotypic variance (σ²p) = σ²g + σ²e 
Where MSg and MSe are mean sum of squares for genotypes and error in the analysis of variance, respectively, 
and r the number of replicates. 



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Genotypic and phenotypic coefficients of variation (GCV, PCV) were computed as follows (Singh & Chaundary, 
1977): 
GCV = σg x100/grand mean 
PCV = σp x100/grand mean 
Broad sense heritability h² = 100 x σ²g / σ²p 
Genetic advance (GA) and genetic advance as percent mean (GAM):  GA = k x h² x σp   and GAM = 100 x GA/X 
With k: standard selection differential at 5 % selection intensity (k = 2.063) and X: grand mean of trait X. 
Phenotypic and genotypic correlation coefficients rp and rg between A and B traits are defined as: 
rp = Covp (A,B)/(σpA x σpB) 
rg = Covg (A,B)/(σgA x σgB) 
where similarly to the phenotypic variance equation, the phenotypic covariance Covp is expressed as: 
Covp = Covg + Cove 
2.6 Statistical Analyses 
The quantitative data recorded in this study was subjected to the analysis of variance using statistical procedures 
described by Gomez & Gomez (1984), with the assistance of R software package version 3.5.1 (Table 1). 
 
Table 1. Analysis of variance calculations in a RCBD involving GxY interactions 

Source of variation Degree of freedom (df) Mean square (MS) Expected mean square (EMS)
Replication (R) y(r-1) MSr
Years (Y) y-1
Genotypes (G) g-1 M1=MSg σ²e + rσ²gy +  ryσ²g

G x Y (g-1) (y-1) M2=MSgy σ²e + rσ²gy + ryσ²g

Error (G x R)  (r-1) (gy-1) M3=MSe σ²e

Total  gyr-1
R: number of replicates; g= number of genotypes; MSr mean square due to replicates; MSg= mean square due to 
genotypes; MSe mean square of error; σ²g, σ²r, σ²y and σ²e stand for variances due to genotypes, replicates, years 
and error, respectively. 
 
3. Results and Discussion 
3.1 Climatic Conditions Over Plant Cane and First Ratoon Crop 
The total amount of rainfall recorded in plant cane was similar to that in first ratoon, with 1311 and 1303 mm, 
respectively. However, total rainfall during in the hottest period (from April to July) decreased by 51.4% in the 
first ratoon compared to that of plant cane, with 352.7 and 726.2 mm respectively. In contrast, the amount of 
rainfall recorded over the cloudy and per-humid period (from August to October) increased by 59%, with 554.6 
and 880.7 mm respectively in plant cane and first ratoon (Fig 1).  Total crop water deficit over the dry season to 
be met with irrigation water reached 571 and 565 mm, respectively, in plant cane and first ratoon. The average 
daily temperature over the entire crop cycle yields 27.8 and 26.8 °C, respectively. 



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Fig 1a. Climate over plant cane. Fig 1b. Climate over first ratoon crop. 
Figure 1. Prevailing climate on experimental site over both crop cycles in Ferké 2 sugar estate, Ivory Coast 

 
3.2 Multivariate ANALYSES 
It came out from the principal component analysis (Figure 2) that most relevant traits in genotype clustering were 
related to juice quality (recoverable sucrose, sucrose content, purity, fiber content), and some yield components 
like stalk diameter and average stalk diameter. The dendrogram deduced from the hierarchical ascendant 
classification analysis (Figure 3) exhibits six different cluster genotypes, which average agronomic characteristics 
are displayed in Table 2.  

Figure 2a. Correlation circle of agronomic traits 
investigated in 1-2 factor plane. 

Figure 2b. Projection of sugarcane genotypes in 
1-2 factor plane. 

Figure 2. Results of Principal Component Analysis regarding aggregate data of both plant and first ratoon crops 

0.05.010.015.020.025.030.035.0

0.050.0100.0150.0200.0250.0300.0350.0400.0450.0

April2018 Jun Aug Oct Dec Feb
Mean T

empera
ture (°C

)

Rainfal
l (mm)

Months
Rainfall ETo Temp

0.05.010.015.020.025.030.035.0

0.050.0100.0150.0200.0250.0300.0350.0400.0

Mean T
empera

ture (°C
)

Rainfal
l (mm)

Months
Rainfall ETo Temp



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Figure 3. Dendrogram deduced from cluster analysis of all 30 cane genotypes tested in Ferké 2 sugar estate, 

Ivory Coast 
 
Table 2. Mean values of clusters genotypes determined following different agronomic traits investigated in Ferké 
2 sugar estate, Ivory Coast (aggregate of plant cane and first ratoon) 

Agronomic traits Cluster 1 
(n=3) 

Cluster 2 
(n=5)

Cluster 3 
(n=6)

Cluster 4 
(n=9)

Cluster 5 
(n=2) 

Cluster 6 
(n=5)

Pol juice (%) 11.8 16.1 14.0 14.9 16.1 15.5
Purity (%) 77.1 83.8 80.1 82.2 81.9 83.4
Sucrose (Pol%C) 9.3 12.9 11.4 12.0 12.8 12.7
Fiber content (%) 15.6 14.3 13.4 14.1 14.8 13.3
Cane Yield (t/ha) 95.8 108.5 130.7 128.5 133.5 146.8
Recov Sucrose (%) 5.7 8.9 7.5 8.1 8.6 8.7
Sugar Yield (t/ha) 5.5 9.7 9.8 10.4 11.6 12.8
StalkNbx1000 143.9 145.1 132.2 157.6 182.8 148.2
%BIN 27.7 11.9 16.7 15.4 8.5 13.9
Avg Weight (kg) 0.8 1.0 1.1 1.0 0.9 1.2
Avg Diam (mm) 2.3 2.4 2.4 2.4 2.5 2.5
Avg Height (cm) 21.6 21.8 23.4 21.6 19.6 22.7
Nb Internode 20.0 24.0 20.9 21.2 24.4 21.9
Flowering rate (%) 25.3 3.6 12.4 8.3 2.2 6.2

C1: RCI13/119, RCI14/14, RCI14/18; C2: R579, RCI13/121, RCI0/133, RCI13/136, RCI14/130 ; C3 : RCI14/127, 
RCI13/117, RCI13/122, RCI13/126, RCI13/125, RCI13/116 ; C4 : RCI/14/129, RCI13/123, RCI11/115, 
RCI13/137, RCI11/113, RCI14/132, RCI14/131, RCI12/15, RCI14/11; C5: RCI13/124, RCI12/19; C6: RCI11/14, 
RCI13/17, RCI13/12, RCI13/120, RCI13/118 
 
3.3 Phenotypic Correlations Within Agronomic Traits 
All yield and juice quality traits were negatively correlated with stem borer infestations, except for fiber content 
(Table 2), in line of findings reported by different authors (Gravois et al, 1992, Tena et al, 2016, Dumont et al, 
2019).  Fiber content was negatively correlated with yields and juice quality traits like juice sucrose, purity, 



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sucrose percent and recoverable sucrose with coefficients ranging from -0.29 to -0.42. Higher and positive 
correlation coefficients were obtained between sugar yield and juice quality traits, with values ranging from 0.78 
to 0.86. A strong and positive correlation was also observed between yield traits (r=0.80) as well as juice quality 
traits, with coefficients ranging from 0.80 to 0.99. Except for fiber content, juice quality and yield traits were 
negatively correlated to stem borer infestation rate (r= -0.40 to -0.73). The stalk fiber content and single stalk 
weight were, respectively, positively and negatively correlated to stem borer infestation rate (r=0.34, -0.68). 
Moreover, sugarcane flowering rate affected negatively all juice quality and yield traits (r= -0.33 to -0.53). 
3.4 Genotypic Correlations Within Agronomic Traits 
Similarly with phenotypic correlations, all yield and juice quality traits were genotypically correlated negatively 
with stem borer infestations, except for fiber content (Table 2), with values ranging from -0.42 to -0.81. As 
expected, strong and positive correlations were observed not only between juice quality traits but also between 
yield traits, with coefficients ranging from 0.83 to 0.99. Strong and positive correlations were also obtained 
between sugar yield and juice quality attributes like pol juice, purity, sucrose content and recoverable sucrose (r= 
0.79 to 0.89). Similarly to phenotypic correlations previously discussed, juice quality and yield traits were 
negatively correlated to stem borer infestation rate (r= -0.42 to -0.81). The stalk fiber content and single stalk 
weight were, respectively, positively and negatively influenced by stem borer infestation rate (r=0.36, -0.40).  
Moreover, sugarcane flowering rate affected negatively all juice quality and yield traits (r= -0.44 to -0.62). 
3.5 Performance of Cane Genotypes Tested 
Except for stalk number/ha, highly significant differences within genotypes were observed for all agronomic traits 
investigated (Table 3). Significant or highly significant differences within crop cycles were observed for all traits 
except for Pol juice, recoverable sucrose, single stalk weight and the average number of internodes per stalk. In 
contrast, genotype by crop cycle interactions were non-significant except for stem-borer infestation rate, average 
number of internodes per stalk and flowering rate. Based on sugar yields, four genotypes, namely RCI12/15, 
RCI12/19, RCI13/121 and RCI13/136 were equivalent to the check variety R579 which performed 15.6 t/ha. Their 
sugar yields ranged from 12.8 to 13.8 t/ha, while their cane yields from 134.0 to 144.8 t/ha compared with 161.3 
t/ha for the control variety. Although a relatively high level of stem-borer infestation rate recorded, with 15.6% on 
average (almost three times the tolerable threshold value of 5%), reasonable values of sucrose percent obtained 
with the promising genotypes ranged from 12.7 to 13.9% over both crop cycles, compared with 13.6% for the 
check.  
3.6 Phenotypic, Genotypic and Environmental Variance 
Regardless the trait considered, phenotypic variances obtained were higher than the genotypic ones. This shows a 
greater influence of the environment on genetic variations in line of observations made by different authors 
(Tadesse et al, 2014; Ehib et al, 2015). Moreover, except for traits like stalk number/ha, average stalk weight, 
height and diameter, genotypic variances calculated were higher than environmental ones, suggesting significant 
variations among genotypes (Table 4). Greater environmental variance in millable stalk number/ha compared to 
the genotypic variance could be explained by no significant difference observed due to a very lower values of 
genotypic coefficient of variation and heritability obtained, with 7.3 and 29.5% respectively. 
3.7 Genotypic and Phenotypic Coefficients of Variation (GCV, PCV) 
GCV is another measure of relative genetic variation of a trait in a population (Ram and hemaprabha, 1992). Traits 
exhibiting relatively high GCV estimates may respond favorably to selection (Ebid et al, 2015).  Regardless the 
trait considered, the phenotypic coefficient of variation was higher than the genotypic one, suggesting that apparent 
variations were not only due to genetics but also due to environmental influences (Table 4). However, differences 
between PCV and GCV for most traits were small in line of observations made by Ram (2005), indicating high 
prospects for genetic progress through selection under conditions of this study. As stated by Shivasubramanian & 
Menon (1973) cited by Tadesse et al (2014), PCV and GCV values are ranked as low, medium and high, with 0 to 
10 %, 11 to 20% and > 20% respectively. Based on that statement, all PCV and GCV values determined which 
ranged from 5 to 94%, on the one hand, and from 3.5 to 83.9%, on the other hand, ranged from low to high. As 
reported by different authors (Tadesse et al, 2014; Singh et al, 1994, Péné & Béhou, 2019a,b), high GCV and PCV 
indicated that selection might be effective on traits investigated and their expression be relevant to the genotypic 
potential. 
3.8 Heritability and Genetic Advance 
Higher heritability values (Table 4) ranging from 61 to 80.5% were observed in traits like sugar yield, sucrose 
content (62.6%), recoverable sucrose (60.6%), fiber content (72%), stem-borer infestation rate (80.5%), number 



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of internodes/stalk (67.7%), and flowering rate (79.6%). In contrast, lower and moderate values of heritability 
were observed for Pol juice (59.8%), Juice purity (50.5%), cane yield (53%), millable stalk number/ha (29.5%), 
single stalk weight (36.7%), single stalk height (45%), and single stalk diameter (38.7%).  This distinction was 
made following heritability scale as stated by Robinson et al (1949) and cited by Tadesse et al, 2014. In line of the 
scale used by Teklu et al (2014), higher values of genetic advance (GAM) were observed for sugar yield (36.2%), 
recoverable sucrose (24.3%), and flowering rate (154%), suggesting that a significant proportion of the total 
variance was heritable and selection of these traits would be effective. Similar values were reported by different 
authors in sugarcane on single stalk weight (Nair et al, 1980; Singh et al, 1994; Ebid et al, 2015). As indicated by 
Vidya et al (2002), knowledge of variability and heritability of characters is essential for identifying those relevant 
to genetic improvement through selection. Moreover, the effectiveness of selection depends not only on heritability 
but also on genetic advance (Butterfield and Nuss, 2002; Shba et al, 2009). Higher levels of genetic advance (GAM) 
observed for cane yield and stem borer infestations were the result of broad sense heritability and high GCV for 
these traits, in line of findings reported by Bakshi (2005). The results suggest the existence of considerable scope 
for sugarcane improvement based on some cane yield components like number of millable stalks/ha, single stalk 
diameter and single stalk weight. Heritability estimates, together with expected genetic gain, are more useful than 
heritability values alone in predicting the effects of selecting best genotypes. Chaudhary (2001) reported high 
heritability and genetic gain for single cane weight followed by number of millable cane in a study of 36 clones, 
indicating substantial scope for cane yield improvement. On the other hand, sucrose content recorded low 
heritability and genetic gain suggesting little scope for improvement in this character (Pandey, 1989). Patel et al 
(2008) also reported high heritability estimates for single cane weight, number of internodes, number of tillers, 
hand refractrometer brix, cane diameter and millable cane height, which were associated with moderate to high 
genetic advance (23-190%). Findings indicated that these characters could be improved through selection. 
 
Table 2. Phenotypic and genotypic correlation matrix of agronomic traits investigated regarding aggregate data of 
both plant and first ratoon crops (respectively below and above diagonal) 

Genotypes PolJ%. Pty% Pol% Fiber% Cane 

Yield 

RSucr. Sug.

Yield

10
3

xNb 

Tillers

%BIN AvWeight AvHeight AvgDiam NbIntern. Flow.% 

Pol juice 1.00 0.92 0.99 -0.37 0.45 0.99 0.85 0.46 -0.81 0.11 0.21 -0.35 0.40 -0.60

Purity 0.91 1.00 0.92 -0.36 0.37 0.95 0.79 0.40 -0.67 0.09 0.00 -0.24 0.29 -0.44

Pol%C 0.99 0.91 1.00 -0.47 0.51 0.99 0.89 0.36 -0.80 0.21 0.19 -0.24 0.36 -0.62

Fiber% -0.31 -0.29 -0.41 1.00 -0.72 -0.48 -0.67 0.58 0.36 -0.82 0.02 -0.75 0.13 0.46

CYield 0.36 0.32 0.42 -0.61 1.00 0.50 0.83 -0.02 -0.42 0.74 0.32 0.37 -0.01 -0.44

RSucrose  0.99 0.94 0.99 -0.42 0.41 1.00 0.89 0.34 -0.78 0.20 0.14 -0.21 0.34 -0.59

SYield 0.83 0.78 0.86 -0.59 0.80 0.86 1.00 0.20 -0.71 0.50 0.29 0.04 0.20 -0.59

SNbx103 0.30 0.26 0.25 0.35 0.08 0.23 0.19 1.00 -0.30 -0.97 -0.37 -0.99 0.17 -0.23

%BIN -0.72 -0.58 -0.73 0.34 -0.40 -0.70 -0.66 -0.18 1.00 -0.40 -0.61 0.09 -0.58 0.68

AvWeight 0.09 0.07 0.17 -0.68 0.53 0.16 0.38 -0.52 -0.30 1.00 0.35 0.80 0.04 -0.40

AvHeight 0.18 0.04 0.18 -0.01 0.32 0.14 0.29 -0.16 -0.48 0.39 1.00 -0.06 0.56 -0.18

AvDiam -0.27 -0.22 -0.18 -0.61 0.20 -0.17 -0.01 -0.74 0.09 0.78 -0.04 1.00 -0.53 0.02

NbInternode 0.35 0.23 0.32 0.11 0.01 0.29 0.19 0.17 -0.50 0.14 0.54 -0.33 1.00 -0.49

Flowering -0.50 -0.33 -0.53 0.42 -0.36 -0.49 -0.49 -0.17 0.62 -0.35 -0.14 -0.44 -0.46 1.00



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Table 3. Mean values of agronomic traits in plant cane and first ratoon (on aggregate) for different 
genotypes tested in Ferké, Ivory Coast (1rst stage of advanced screening) 

Genotypes PolJ% Pty% Pol% Fiber% Cane 

Yield 

RSucr% Sug. 

Yield 

10
3

xNb 

Tillers 

BIN% AvWeight 

(kg) 

AvHeight 

(m) 

AvgDiam 

(mm) 

NbIntern. Flow.% 

R579 16.5ab 85.7ab 13.6ab 12.7hi 161.3a 9.7ab 15.6a 136.7 13.7de 1.3ab 2.5ab 23.5ab 21.2cd 2.0hi 

RCI10/133 15.0ab 83.2ab 12.1ab 14.3cd 140.8ab 8.2ab 11.5bc 150.7 21.0bc 1.1ab 2.5ab 23.1ab 22.0cd 9.7fg 

RCI11/113 12.4ef 77.6de 10.0fg 14.2cd 132.1ab 6.2ef 8.2fg 154.5 19.9bc 1.0ab 2.4ab 21.8ab 21.4cd 15.2cd 

RCI11/114 12.8de 77.2ef 10.5ef 12.9gh 137.6ab 6.6de 9.0ef 122.3 20.3bc 1.2ab 2.5ab 23.6ab 21.7cd 10.7ef 

RCI11/115 14.0ab 79.9ab 11.2cd 14.5bc 122.4bc 7.3bc 9.0ef 158.8 22.1bc 0.9bc 2.2de 20.8bc 21.7cd 0.0i 

RCI12/15 17.3a 86.8a 13.9ab 14.1cd 134.0ab 9.9a 13.1ab 154.8 9.5hi 0.9bc 2.3bc 21.0bc 20.6de 12.ef0 

RCI12/19 17.0ab 84.6ab 13.6ab 14.5bc 144.8ab 9.5ab 13.8ab 180.2 4.7k 0.9ab 2.6ab 19.2e 26.0ab 3.3hg 

RCI13/116 12.3fg 77.6de 10.0fg 13.8de 116.2bc 6.3ef 7.3gh 130.5 18.8bc 1.2ab 2.3ab 24.2ab 21.3cd 9.7ef 

RCI13/117 16.2ab 83.4ab 13.1ab 14.2cd 107.4cd 9.0ab 9.7bc 148.7 13.4ef 0.9bc 2.2cd 21.4cd 22.6cd 3.8gh 

RCI13/118 14.1ab 81.1ab 11.4bc 13.4fg 136.3ab 7.6ab 10.4bc 135.7 17.5bc 1.1ab 2.1ef 24.1ab 18.7h 6.5ef 

RCI13/119 11.8gh 78.0cd 9.2hi 15.7ab 97.1fg 5.7fg 5.5ij 160.8 37.3a 0.7c 2.1f 20.3cd 20.6de 32.0a 

RCI13/12 15.5abc 82.9ab 12.2ab 15.3ab 131.5ab 8.2ab 10.7bc 141.7 12.8fg 1.0ab 2.8a 20.9bc 21.9cd 27.4ab 

RCI13/120 15.0abc 82.7ab 12.3ab 12.9gh 125.9bc 8.4ab 10.6bc 139.5 13.7de 0.9ab 2.3bc 22.7ab 19.2fg 13.8de 

RCI13/121 16.1abc 84.8ab 13.1ab 13.6ef 144.6ab 9.2ab 13.3ab 149.7 10.5hi 1.0ab 2.8a 20.6bc 24.7bc 0.0i 

RCI13/122 16.9ab 84.4ab 13.4ab 14.9ab 115.5bc 9.3ab 10.8bc 142.3 16.2cd 1.1ab 2.5ab 21.5ab 23.4cd 4.3gh 

RCI13/123 14.5abc 83.8ab 11.7ab 14.1cd 118.9bc 8.0ab 9.6cd 163.3 15.3cd 1ab 2.2cd 22.1ab 21.1cd 8.2ef 

RCI13/124 15.1abc 79.2bc 12.0ab 15.1ab 122.1bc 7.7ab 9.4de 185.3 12.4fg 0.9bc 2.4ab 20.0de 22.9cd 1.0hi 

RCI13/125 14.0bc 79.2bc 11.1cd 14.7bc 102.9de 7.1cd 7.4fg 135.0 8.9ij 1.2ab 2.7ab 22.5ab 27.2a 1.5hi 

RCI13/126 16.3ab 85.1ab 13.3ab 13.8de 114.4bc 9.3ab 10.7bc 145.0 5.8jk 1.1ab 2.4ab 22.8ab 24.2bc 0.8i 

RCI13/136 15.4abc 83.6ab 12.7ab 12.7hi 146.9ab 8.8ab 12.8ab 152.7 12.3fg 1.3a 2.4ab 23.9ab 21.0cd 7.7ef 

RCI13/137 14.5abc 82.6ab 11.6ab 14.3cd 128.7ab 7.8ab 10.1bc 157.7 16.0cd 1.1ab 2.4ab 22.1ab 22.2cd 15.9cd 

RCI13/17 14.3abc 79.3bc 11.9ab 12.4i 136.9ab 7.8b 10.5bc 123.5 17.1bc 1.3a 2.5ab 25.0a 22.7cd 6.3ef 

RCI14/11 17.1ab 85.4ab 14.1a 12.9gh 137.7ab 10.0a 13.7ab 146.7 11.5gh 1.2ab 2.6ab 22.9ab 21.6cd 10.8ef 

RCI14/127 17.1ab 86.8a 13.9ab 13.8de 102.4de 9.9a 10.2bc 154.7 15.1cd 0.9bc 2.3cd 20.6bc 22.5cd 7.7ef 

RCI14/129 15.2abc 80.1ab 12.2ab 14.4cd 133.0ab 8.0ab 10.6bc 165.2 14.1de 1.0ab 2.5ab 22.0ab 20.2ef 3.0gh 

RCI14/130 13.1cd 77.6de 10.6de 13.9cd 149.5ab 6.6de 10.0bc 152.7 14.6cd 1.1ab 2.5ab 22.1ab 21.1cd 7.1ef 

RCI14/131 15.6abc 82.2ab 12.5ab 14.0cd 131.2ab 8.5ab 11.1bc 152.5 12.7fg 1.1ab 2.6ab 20.8bc 22.4cd 4.8fg 

RCI14/132 15.6abc 84.7ab 12.8ab 13.5ef 128.0ab 8.9ab 11.4bc 154.2 14.1de 1.1ab 2.4ab 22.1ab 20.0ef 7.6ef 

RCI14/14 11.3h 73.5f 9.0i 15.0ab 90.8g 5.2g 4.8j 130.8 24.2b 0.9ab 2.5ab 22.9ab 18.9gh 22.8bc 

RCI14/18 12.5ef 78.9ab 9.7gh 16.0a 99.5ef 6.1ef 6.2hi 140.0 21.6bc 0.9bc 2.5ab 21.7ab 20.6de 21.0bc 

Mean 14.8 81.8 12.0 14.0 126.3 8.0 10.2 148.9 15.6 1.0 2.4 22.1 21.8 9.2 

SD 2.2 4.9 1.9 1.7 23.7 1.7 3.1 38.5 7.6 0.2 0.3 2.4 2.7 11.5 

CV(%) 15.1 6.0 15.7 11.9 18.8 21.6 30.6 26.0 48.6 23.6 11.2 11.0 12.0 125.0 

Replications Ns Ns Ns Ns ** Ns Ns *** ** * Ns Ns ** Ns 

Genotypes *** *** *** *** *** *** *** Ns *** *** *** *** *** *** 

Crop cycles Ns *** *** *** * Ns ** *** *** Ns *** *** Ns *** 

Genotypes x 

Cycles 

Ns Ns Ns Ns Ns Ns Ns Ns *** Ns Ns Ns *** *** 

SNb: millable stalk number/ha; BIN: bored internode; AvWeight: average stalk weight; AvHeight: average stalk 
height; Ns: non-significant. 
*, **,***: significant at 5, 1 and 0.1% levels of probability. 
 
 
 
 
 
 



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Table 4. Variability and heritability among sugarcane genotypes tested as plant crop and first ratoon (aggregate 
data) in Ferké, Ivory Coast 

Variability Mean 
Variance 

Coef. of variation 

(%) h² (%) GA GAM (%) 

σ²p σ²e σ²g PCV GCV 

Juice sucrose% 14.8 4.0 1.6 2.4 13.5 10.4 59.8 2.5 16.7

Purity% 81.8 16.7 8.2 8.4 5.0 3.5 50.5 4.2 5.2

Sucrose% 12.0 2.8 1.0 1.7 13.9 11.0 62.6 2.1 18.0

Fiber content% 14.0 1.0 0.3 0.7 7.1 6.0 72.1 1.5 10.6

Cane yield (t/ha) 123.3 426.6 200.6 226.0 16.7 12.2 53.0 22.6 18.3

Recov. sucrose% 8.0 2.4 1.0 1.5 19.4 15.1 60.6 1.9 24.3

Sugar yield (t/ha) 10.2 8.1 3.0 5.1 27.8 22.1 63.0 3.7 36.2

Stalk number/ha 148.9 396.0 279.0 117.0 13.4 7.3 29.5 12.1 8.1

Bored internode  15.6 43.8 8.5 35.3 42.6 38.2 80.5 11.0 10.7

Avg weight (kg) 1.0 0.0 0.0 0.0 19.3 11.7 36.7 0.1 14.6

Avg height (m) 2.4 0.05 0.0 0.0 9.0 6.0 45.1 0.2 8.4

Avg diameter (mm) 22.1 3.3 2.0 1.3 8.2 5.1 38.7 1.4 6.5

Nb Internodes 21.8 4.6 1.5 3.1 9.8 8.0 67.7 3.0 13.7

Flowering rate% 9.2 75.1 15.3 59.8 94.0 83.9 79.6 14.2 154.4

PCV: phenotypic CV (%); GCV: genotypic CV (%); h²: broad sense heritability; GA: genetic advance; GAM: 
genetic advance as percent of mean (%) 
 
4. Conclusions 
Based on sugar yields, four promising genotypes namely RCI12/15, RCI12/19, RCI13/121 and RCI13/136 were 
equivalent to the check variety R579 which performed 15.6 t/ha. They are due to undergo the advanced selection 
stage during the 2020-21 cropping season for three more years for determining the first new sugarcane varieties 
of RCI origin to be tested commercially in Ferké sugar estates. Their yield performances ranged from 12.8 to 13.8 
t sugar /ha, i.e. from 134.0 to 144.8 t cane/ha compared with 161.3 t/ha for the control variety. Although a relatively 
high level of stem-borer infestation rate recorded with 15.6% on average (almost three times the tolerable threshold 
value of 5%), reasonable values of sucrose percent obtained with the promising genotypes, ranged from 12.7 to 
13.9% over both crop cycles, compared with 13.6% for the check. Higher heritability values ranging from 61 to 
80.5% were observed in traits like sugar yield, sucrose content (62.6%), recoverable sucrose (60.6%), fiber content 
(72%), stem-borer infestation rate (80.5%), number of internodes/stalk (67.7%), and flowering rate (79.6%). In 
contrast, lower and moderate values of heritability were observed for Pol juice (59.8%), Juice purity (50.5%), cane 
yield (53%), millable stalk number/ha (29.5%), single stalk weight (36.7%), single stalk height (45%), and single 
stalk diameter (38.7%). 

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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

