ARTICLES

 

Yield and Multivariate Analysis among Twelve Sugarcane (Saccharum Officinarum L) Genotypes at Mankusa, North Western, Ethiopia

 

 

Mekonnen S.A.; Azene T.F.; Tessema W.M

Debre Markos University Burie Campus, Department of Plant Sciences, Burie, Ethiopia. Orcid id: https://orcid.org/0000-0003-4910-863X

Correspondence

 

 

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ABSTRACT

Smallholders cultivated sugarcane for household consumption, immediate cash, and feeding livestock in Ethiopia. However, its production and productivity are constrained by a lack of improved varieties. Sugarcane germplasm was collected from Districts of West Gojjam, Ethiopia, to evaluate yield and its contributing characters and quantify the phenotypic diversity at Mankusa, Jabitehnan, Ethiopia. The experiment was conducted using a randomised complete block design with three replications for two crop cycles, from April 2020 to March 2023. Data were recorded for the number of tillers, internode length, sellable stalks, plant height, stalk diameter, cane yield and biomass yield from twelve genotypes collected. The data recorded were subjected to analysis of variance, and means were separated using the Duncan Multiple Range Test at a 5% significance level. Variance and multivariate analysis indicated the existence of high phenotypic diversity between genotypes in all quantitative traits studied. Acc 7/20 and Acc 5/20 genotypes produced the highest number of tillers and longest internodes, while Acc 6/20 produced the highest number of sellable stalks. The genotype Acc 4/20 was the longest, and the thickest genotype, which could be elite donors for it respected quality traits through crossing. The highest cane yield was recorded from Acc 4/20 (178.04 t/ha), Acc 7/20 (151.41 t/ha), Acc 8/20 (134.1 t/ha) and Acc 12/20 (132 t/ha), producing 58, 34, 19 and 17% advantageous from the overall genotypes mean, respectively. Cluster analysis grouped the twelve sugarcane genotypes into four clusters, indicating the possibility of broadening the genetic basis by crossing genotypes in the different clusters. It also indicated that a cross between cluster II and III genotypes could create the thickest canes with many sellable stalks. Therefore, genotypes Acc 04/20, Acc 07/20, Acc 8/20 and Acc 12/20 have been recommended and must be evaluated in other sugarcane growing areas to exploit their potential.

Keywords: Cluster Analysis, PCA, Sugarcane, Variability, Yield

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1. INTRODUCTION

Sugarcane is an important crop cultivated in tropical and subtropical climatic regions for chewing, animal feed and sugar production (Ochami & Ochieng, 2020).The most preferred natural sweetener and energy source worldwide. Sugarcane (Saccharum) is a genus characterised by high ploidy levels with chromosome numbers ranging from 2n= 80 to 2n= 130. The high ploidy nature of sugarcane complexes improves practices for the crop as it is highly influenced by changes in the environment and favoured specific adaptations. Globally, sugarcane breeders develop better-adapted and high-yielding varieties to meet the requirements of the smallholder farmers and sugar industry (Govindaraj et al., 2016).

Sugarcane is an important crop widely cultivated for multiple purposes by smallholder farmers in sub-Saharan Africa (SSA), including Ethiopia. It has been cultivated in Ethiopia since the 16^th century and preceded the commercial sector, and commercial sugarcane production has a history of six decades (Esayas et al., 2018). A report by the Central Statistics Agency (CSA, 2019) of Ethiopia showed that 998,749 households grew sugarcane in about 27,826.98 hectares of land with a production of 12,940,81t/year and productivity of 46.5t/ha. However, sugarcane production and productivity under smallholder farming systems are constrained by biotic, abiotic, and socioeconomic factors (Tena et al., 2016). The low yield of sugarcane genotypes and production technologies are the major causes of the hampering of sugarcane yield in Ethiopia. Promising varieties and suitable technologies are solutions to improve growers' cane yield. These constraints can be resolved by evaluating locally collected sugarcane landraces by identifying preferred genes for breeding purposes. Information about genetic diversity is a prerequisite for any breeding program. New avenues and sources of genetic diversity enable breeders to develop cultivars that can tolerate changing environments, diseases, pests and climatic conditions. Sufficient genetic diversity enables species to resist diseases and adapt to new climatic conditions.

In Ethiopia, the smallholder sugarcane production sector for chewing is under-researched, with no industrial link or support. There is a limited effort to collect and characterise sugarcane varieties locally. However, they have long agricultural values, adaptation, and co-evolution with prevailing pests and diseases across different agroecological regions of the country. They can also serve as a rich source of novel genes desired for farmer's preferred traits. In addition, sugarcane production declined from 30 296 to 27 827 ha and the number of growers reduced from 1,270,627 to 998,749 households (CSA, 2015 and CSA, 2019).

Developing high-yielding and stable varieties requires a continuous supply of new germplasm as a source of desirable genes. One of these germplasm sources is local sugarcane landraces, which could be sources of desirable genes that adapt and coevolve with the country's agroecologies and growing conditions. The addition of desirable genes and knowledge of phenotypic and genetic diversity is crucial in any crop improvement programs and gene introgression. Multivariate analysis allows the estimation of the contribution of variations in different traits to the total variability in a germplasm collection (Karakoy et al., 2013). Cluster and principal component analysis are the major multivariate analysing tools used to provide information for the existing genetic variability and the trend of character association, which help to identify donor genotypes for important sugarcane traits (Karakoy et al., 2013). Cluster analysis (CA) is important in grouping genotypes with multi-desirable characters. Principal component analysis (PCA) is a valuable method of determining the inter-relationship among variables (Brown et al., 2000).

Therefore, this study was initiated to collect and screen the best local sugarcane genotypes cultivated across West Gojjam in Ethiopia. The study's specific objectives were 1) to screen the best sugarcane genotypes for yield and their contributing characteristics and 2) to quantify the genetic diversity of collected sugarcane genotypes for sources of genes to farmers' preferred traits based on cluster and principal component analyses.

 

2. MATERIALS AND METHODS

The study was conducted at Mankusa (10° 70' N 37° 18' E) in the Jabi Tehinan district, which is 397 km away from Addis Ababa during the 2020/21 growing season using irrigation. The experimental site is at 1,917 m above sea level with an average annual rainfall of 1,450 mm and minimum and maximum temperatures of 10 °C and 23 °C, respectively. The soil type is nitosols, with a pH ranging from 5.3 to 6.

Twelve sugarcane genotypes (Acc 1/20, Acc 2/20, Acc 3/20, Acc 4/20, Acc 5/20, Acc 6/20, Acc 7/20, Acc 8/20, Acc 9/20, Acc 10/20, Acc 11/20 and Acc 12/20) were collected in April 2020 across West Gojjam, Ethiopia, from farmers' fields and local markets. The districts and sub-districts were selected based on the long agricultural history and relatively wide areas allocated to sugarcane production. Moreover, purposive sampling was also employed based on information supplied by key informants on the uniqueness and quality of sugarcane types grown in these areas. Sugarcane clones were collected following the methods proposed by Hawkes (1980). Information on the sampled sugarcane germplasm was recorded, and passport data was collected following the Biodiversity International method (Hawkes, 1983).

The collected genotypes were tagged and planted in April 2020 at Mankusa, grown with the supplementary use of irrigation until March 2023. The experiment was a completely randomised block design with three replications. An equal number of two-budded sets was planted using the end-to-end planting method for each genotype. Cultural practices such as tillage operations, fertilisation, moulding, irrigation, weed, pest and disease control were done uniformly to all entries as per the farmers' practice.

Data was collected from the two central rows for the tillers, sellable stalk, stalk length, internode length, stalk girth, single stalk weight, cane yield, and biomass yield. The quantitative data recorded was subjected to variance analysis using the SAS software (SAS, 2002). Duncan Multiple Range Test comparison method at 5% level of significance was used to separate the treatment means. Clustering of genotypes based on all yield and yield contributing traits was done using the PROC clustering strategy of SAS 9.0, and principal component analysis was computed using statistical analysis software.

 

3. RESULT AND DISCUSSION

3.1. Phenotypic Characterisation

Analysis of variance revealed that the variation among the twelve sugarcane genotypes was significant for all traits studied (Table 1), declaring that the performance of sugarcane genotypes could be significantly affected by environmental conditions. These results coincide with those of Alam et al. (2018), Darika et al. (2021) and Panhwar et al. (2022), who found significant differences among sugarcane genotypes for all the traits examined. This is important for the sugarcane improvement through selection from the diversity of genes attributed to different characters.

 

 

The performances of the genotypes for eight important phenotypic traits over the two ratoon cycles are presented in Table 2. The results showed a wide range of variation in different traits; number of tillers (278 - 644), internode length (5 - 16 cm), number of sellable stalks (166 - 453), single stalk weights (1.04 - 2.21 kg), stalk girth (2.27 - 3.11 cm), stalk length (1.84 - 2.75m), cane yield (64.91 - 178.04 t/ha) and biomass yield (87.85 - 244.70 t/ha). This indicates a wide range of genetic variability for studied characters and highlights the potential for genetic improvement. Arain et al. (2011) also found significant differences among sugarcane genotypes in these traits.

 

 

The genotypes Acc 6/20 and Acc 7/20 produced the highest significant number of tillers compared to the genotypes. The Acc 7/20, Acc 4/20, and Acc 5/20 genotypes had long internodes, with 60%, 40%, and 14.2% lengths higher than the overall genotypes mean (10cm). Those genotypes could be elite donors for internode length and number of tillers in sugarcane (Table 2).

Significant differences were detected for stalk length among tested genotypes. The top four genotypes that exceeded the overall stalk length mean (2.32m) by more than 10% were Acc 4/20(18.5%), Acc 8/20 (15.1%) and Acc 6/20 (11.6%). Genotypes Acc 2/20 (1.84m) and Acc 11/20 (2.05m) recorded the shortest plants with 20.7% and 11.6% less than the overall genotype mean. Significant differences were also detected in the number of sellable stalks. The genotype Acc 6/20 had significantly the highest number of sellable stalks (453), while the accession Acc 1/20 had significantly the lowest sellable stalking numbers. The genotypes Acc 4/20 (3.11cm) and Acc 1/20 (3.07cm) had the highest significant cane thickness and more than 13% advantageous from the overall stalk girth performances of the collected sugarcane genotypes. Acc 6/20 (2.27cm) was recorded significantly as the thinnest sugarcane genotype (Table 2).

Five genotypes (Acc 4/20, Acc 7/20, Acc 8/20, Acc 12/20 and Acc 9/20) yielded up to 62.5% more single stalk weights than overall genotypes mean. The genotype Acc 4/20 (2.21 kg) produced the highest single stalk weights. The highest cane yield-producing genotypes were Acc 4/20 (178.04 t/ha), Acc 7/20 (151.41 t/ha) and Acc 8/20 (134.1 t/ha), with 58, 34 and 19 % more yields than the overall genotype mean. These genotypes also had the highest biomass yield than the overall genotype mean (Table 2). Muhammad et al. (2020), Rao et al. (2022), and Shitahun and Tesfaw (2022) have also reported variability in different yield and yield-related traits of sugarcane. The inherent genetic constitution of the sugarcane genotypes might have resulted in higher and lower cane yields. Ali et al. (2020) and Nishad and Kumar (2020) have also reported higher differences for different yield and yield-related traits among sugarcane genotypes.

3.2. Cluster Analysis

Cluster analysis isolates genotypes into clusters, which have demonstrated closer similarities and dissimilarities between clusters. Cluster analysis revealed that the twelve sugarcane genotypes were grouped into four clusters based on the tillers, internode length, sellable stalks, stalk length, cane girth, single stalk weights, cane yield and biomass yield. Alemu et al. (2022) also classified twenty-two sugarcane genotypes into four clusters. Seven genotypes (Acc 2/20, Acc 3/20, Acc 4/20, Acc 8/20, Acc 10/20, Acc 11/20 and Acc 12/20) were grouped into cluster I (58.33%), two genotypes (Acc 1/20 and Acc 9/20) in cluster II (16.67%), two genotypes (Acc 6/20 and Acc 7/20) in cluster III (16.67%) and one genotype (Acc 1/20) in cluster IV (8.33%) (Figure 1). This indicates the presence of high genetic variability among genotypes and the possibility to broaden the genetic basis through the crossing of genotypes in the different clusters.

 

 

Genotypes in cluster I are characterised by average performances regarding the number of tillers and sellable stalks, whereas genotypes in cluster III had the highest number of tillers and sellable stalks. Genotypes grouped in cluster II had the lowest number of tillers and sellable stalks but were the thickest canes. The average rates for the number of tillers (640), internode length (13.5cm), sellable stalk count (396), stalk length (2.43m), cane yield (141.02 t/ha) and cane yield (193.03 t/ha) were the highest in cluster III(Table 3). In this group, Acc 6/20 and Acc 7/20 were superior in their yield and yield-related traits and might be taken into account as a potential to further the breeding program. The cluster analysis indicated the existence of genetic variability among the tested genotypes and showed the possibility of increasing the genetic basis through the crossing of genotypes in the different clusters. For example, genotypes in cluster II are characterised by thicker canes but have a low number of sellable stalks, whereas genotypes in cluster III have the highest number of sellable stalks. A cross made between selected genotypes in those clusters could possibly create the thickest canes with a high number of sellable stalks. Ajmal et al. (2013) argued that cluster analysis makes the isolation procedure simple by considering genotypes recorded higher values yield attributes traits and grouped in a single cluster.

 

 

3.3. Principal Component Analysis

A principal component analysis (PCA) was carried out to describe and better understand the sources of variance among sugarcane genotypes. Four principal components (PC1 to PC4) were extracted from the original data and accounted for 96% of the total variation. Muhammad et al. (2018) also reported 85.7% of the total variation in the tested breeding material from the first four principal components. The first principal component had high positive component loading from cane yield, biomass, stalk height and internode length. The second principal component had high positive component loading from stalk girth and single stalk weight and negative component loading from stalk count and the number of tillers, indicating the existence of a positive and negative correlation between the components and the character (Table 4). The characters with a high positive or negative loading contributed more to the genetic diversity, and they became important in representing the clusters.

 

 

4. CONCLUSIONS AND RECOMMENDATIONS

The variances and multivariate analysis confirmed the existence of significant variability among studied genotypes for the number of internodes, cane length, stalk girth, single stalk weight, stalk count and cane yield. The highest cane yield was recorded from Acc 4/20 (178.04 t/ha), Acc 7/20 (151.41 t/ha), Acc 8/20 (134.1 t/ha) and Acc 12/20 (132 t/ha), producing 58, 34, 19 and 17% advantageous from the overall genotypes mean, respectively. Cluster analysis grouped the twelve sugarcane genotypes into four clusters, indicating the possibility of broadening the genetic basis by crossing genotypes in the different clusters.

Therefore, genotypes Acc 04/20, Acc 07/20, Acc 8/20 and Acc 12/20 had been recommended and must be evaluated in other sugarcane growing areas to exploit their potential.

 

ACKNOWLEDGEMENT

The authors are grateful for the financial grant from Debre Markos University.

 

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Correspondence:
S.A. Mekonnen
Email: Shitahun_alemu@dmu.edu.et