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 as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 84 Published by IDEAS SPREAD 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 as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 85 Published by IDEAS SPREAD 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. as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 86 Published by IDEAS SPREAD 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. as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 87 Published by IDEAS SPREAD 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 as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 88 Published by IDEAS SPREAD 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, as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 89 Published by IDEAS SPREAD 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 as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 90 Published by IDEAS SPREAD 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 as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 91 Published by IDEAS SPREAD 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. as.ideasspread.org Agricultural Science Vol. 2, No. 1; 2020 92 Published by IDEAS SPREAD 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%). References Ali, A., Khan, S. A., Farid, A., Khan, A., Khan, S M., & Ali, N. (2017). Assessment of sugarcane genotypes for cane yield. Sarhad J Agric., 33(4), 668-73. Chaudhary, R. R. (2001). Genetic variability and heritability in sugarcane. Nepal Agric. Res. J., 4, 56-9. Dagar, P., Pahuja, S. K., Kaian, S. P., & Singh. (2002). Evaluation of phenotypic variability in sugarcane using principal factor analysis. Ind. J. Sugarc. Technol., 17, 95-100. Dahlquist, E. (2013). 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