Genetic Diversity and Association of Yield-Related Traits in Taro (<i>Colocasia esculenta</i> (L.) Schott) Sourced from Different Agroecological Origins of Nigeria

Fufa, Tilahun Wondimu; Oselebe, Happiness Ogba; Amadi, Charles Okechukwu; Menamo, Temesgen Matewos; Abtew, Wosene Gebreselassie

doi:https://doi.org/10.1155/2023/8832165

International Journal of Agronomy

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Abstract Introduction Materials and Methods Results Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 8832165 | https://doi.org/10.1155/2023/8832165

Genetic Diversity and Association of Yield-Related Traits in Taro (Colocasia esculenta (L.) Schott) Sourced from Different Agroecological Origins of Nigeria

Tilahun Wondimu Fufa,^1,2Happiness Ogba Oselebe,²Charles Okechukwu Amadi,³Temesgen Matewos Menamo,⁴and Wosene Gebreselassie Abtew⁴

Academic Editor: Maria Serrano

Received05 May 2023

Revised02 Dec 2023

Accepted04 Dec 2023

Published11 Dec 2023

Abstract

Taro’s production is characterized by low productivity due to a lack of sufficient improved cultivars suited to the different growing areas coupled with biotic and abiotic stresses. The first step in plant breeding program is to examine and quantify variations for traits of interest in a given set of genotypes so those variations can be exploited in breeding programmes. One hundred taro accessions were evaluated for 16 quantitative traits in a simple lattice design with the objective of estimating variability and determine and quantify association of characters with yield. Multienvironment trial analysis combined over seasons showed highly significant differences among taro accessions for several traits. Yield per plant showed a strong, positive, and highly significant genotypic correlation with plant height (0.99), leaf area (0.82), corm weight (0.99), and cormel weight (0.99). Genotypic path coefficient analysis showed plant height (1.49), leaf area (0.97), corm weight (0.76), and cormel weight (0.21) exerted a high positive direct effect on yield per plant indicating true relationship between the characters. Accessions EBNFC054, EBNFC045, EBNFC100, EBNFC046, EBNFC032, EBNFC075, EBNFC084, EBNFC057, and EBNFC037 were superior and could be promoted to field evaluation. This assessment of variability and associations can assist breeders to tap the potential of the genotypes for certain traits and identify major traits that could be used as a basis for the selection of superior taro genotypes.

1. Introduction

Taro (Colocasia esculenta (L.) Schott) is one of the world’s most ancient food crops, with a history of more than 2,000 years in cultivation [1]. It originated in south central Asia, while high diversity was reported in Southeast Asia [2]. It is morphologically diverse, with over 10,000 landraces worldwide [3], and about 10 ecotypes have been reported growing in Nigeria [4].

Taro is largely produced and consumed in tropical and subtropical countries [5], and Nigeria is the largest taro producer in the world [6]. Only the skins of the taro corm and the true anatomical roots have not been reported as food; meanwhile, the corms, blades, petioles, and inflorescences are edible. The corm has been reported to have high starch, while the leaf contains high protein [7]. Among tuber crops, taro is perhaps the most widely prepared or processed into more consumable forms [8]. It is a staple food, mainly for resource-poor rural dwellers in south eastern Nigeria [4], and is regularly consumed as a main component or as a soup thickener [5].

As is true for some crops, taro remains an orphan, and so far, no improved variety is available in Nigeria. It is chiefly characterized by low productivity, disease susceptibility and poor eating quality [9]. Specifically, taro yield was estimated at 3.94 t ha⁻¹ in Nigeria in 2021, which was very far below the global average yield of 9.50 t ha⁻¹ [6]. Yield is a complex trait governed by several genes that govern a number of yield components and are also influenced by environmental factors, signifying indirect selection breeding to improve taro yield.

The first step in any plant breeding program is to identify plants that exhibit variation for the traits of interest. Desirable traits combination should be sought among plants in existing populations such as recommended cultivars, breeding lines and landrace [10]. To have a good choice of characters for selection of desirable genotypes, the estimate of heritability, genetic advance, and knowledge of association of component traits with yield is of great importance to plant breeders as it helps them make selection with more precision and accuracy [11]. Heritability estimate can be used to predict gain from selection [12]. Genetic correlation is a measure of the extent to which the same gene, or closely linked genes, cause simultaneous variation in two different traits [13]. Path analysis further permits the partitioning of the correlation coefficients into components of direct and indirect factors of association and provides an effective tool in finding out the direct and indirect contribution of different contributing characters towards yield [14].

Many researchers have reported broad-sense heritability and distinguished a number of positive and significant associations of yield and yield attributing characters and their direct and indirect effects in different root and tuber crops. For instance, in taro [15, 16], Tania [15, 17–19], sweet potato [20, 21], and anchote [22, 23], thus, the current study was intended to estimate genetic variability and characters association in taro so as to identify the major traits of importance that could be used as a basis in taro breeding to select superior genotypes.

2. Materials and Methods

2.1. Plant Material

A total of 100 taro accessions were used in this study (Table 1). The accessions were originally collected from five states of Nigeria, i.e., Ebonyi state (21), Anambra (20), Enugu (20), Imo (19), and Abia (20) in 2018. The test collections were comprised of all landraces.

2.2. Description of Site

The field trial was carried out at Ebonyi State University, Department of Crop Production and Landscape Management teaching and experimental field, Abakaliki, Nigeria, during the rainy seasons of 2018 and 2019. The site is situated at 06°4′ N and 08°65′ E at 55.5 metre above sea level. The area receives annual rainfall of 1700 to 2000 mm with 80% to 90% relative humidity. The mean minimum, maximum, and average temperatures were 22°C, 32°C, and 28°C, respectively. The predominant soil is hydromorphic with moderate to reddish brown silty clay subsoil. The site is also good for the production of root crops like cassava and yam among the others.

2.3. Experimental Design and Trial Management

The experiment was laid out using a 10 × 10 simple lattice design with two replicates [24]. Each accession was established in a plot size of 5 m² consisting of one row of 5 m in length. The spacing between rows and plants was 1 m and 0.5 m, respectively [25, 26]. Ten cormels with an average weight of 50 g were used for planting. It was planted on 25^th May, 2018 and 28^th May, 2019. All management practices like weeding and earthing-up were done as recommended during all growth period.

2.4. Data Collection

Data were recorded on 16 quantitative traits from five randomly taken plants. The descriptor, code and description of the characters are presented in Table 2. The traits include number of leaves per plant, plant height (cm), petiole length (cm), leaf length (cm), leaf breadth (cm), leaf area, number of suckers per plant, days to maturity, yield per plant (kg), corm length (cm), corm diameter (cm), cormel diameter (cm), cormel length (cm), corm weight (g), cormel weight (g), and total yield (t ha⁻¹). These data were recorded following a descriptor of taro developed by the International Board for Plant Genetic Resources [27]. Morphological data were recorded at maximum growth stage (120 days after planting), while corm and corm-related traits were recorded at harvest (180 to 220 days after planting).

2.5. Data Analysis

Normality and equal variance test and transformation of data for some characters were done using Minitab software [28]. Descriptive statistics were used to depict variations that emerge from quantitative traits. Quantitative traits were subjected to multienvironment trail analysis (META) based on simple lattice design in order to verify differences among accessions. Phenotypic and genotypic variances and coefficient of variations were estimated as per the procedure suggested by [29]. Broad sense heritability ( was estimated using the formula suggested by [30]. Genetic advance (GA) at selection intensity (K) of 10% was calculated by the formula suggested by [31]. Genetic advance as percentage of mean (GAM) was computed to compare the extent of predicted genetic advance of different characters under selection. Genotypic and phenotypic correlation components between traits were estimated using the equation suggested by [32]. For path analysis, yield per plant was taken as a dependent variable, while others were considered independent variables. Direct and indirect effect of independent variables on yield per plant was estimated using formula suggested by [14]. Correlation analysis was carried out using META R [33], while path analysis was done using Excel.

3. Results

3.1. Variation for Quantitative Traits among Taro Accessions

Multienvironment trial analysis (META) results of 16 quantitative traits are presented in Table 3. META combined over seasons (environment) showed highly significant () differences among the tested accessions for plant height, petiole length, number of suckers per plant, days to maturity, yield per plant, cormel weight, and total yield, while nonsignificant for number of leaves per plant, leaf length, leaf breadth, leaf area, corm length, corm diameter, cormel length, and cormel diameter. META for individual seasons (Table 4) showed a highly significant () differences among the studied accessions for all traits except cormel length which showed significant (), while accessions did not differ statistically significantly for corm diameter.

3.2. Performance of Genotypes

The estimate of range and pooled mean performance of accessions for total yield and yield related traits are presented in Table 3. Yield performance of taro accessions ranged from 1.25 t ha⁻¹ to 18.03 t ha⁻¹ with a pooled mean of 10.08 t ha⁻¹. Sixty percent of the total accessions gave yield above pooled mean yield (10.08 t ha⁻¹). Based on 10% selection intensity, the first ten top high yielders were EBNFC051, followed by EBNFC054, EBNFC045, EBNFC100, EBNFC046, EBNFC032, EBNFC075, EBNFC084, EBNFC057, and EBNFC037. From the top yielder’s five accessions (i.e., EBNFC051, EBNFC054, EBNFC045, EBNFC046, and EBNFC057) were collected from Enugu state, two (EBNFC084 and EBNFC100) from Abia, two (EBNFC 032 and EBNFC037) from Anambra, and one (EBNFC075) from Imo state (Table 1).

Number of leaves per plant ranged from 7.40 to 12.40 with pooled mean of 9.63. Plant height ranged from 35 cm to 110 cm with a mean of 75.28 cm. Petiole length ranged from 16.67 cm to 69.00 cm with mean of 31.82 cm. Leaf length ranged from 5.00 cm to 72.00 cm with a mean of 47.31 cm. Leaf breadth ranged from 16.50 cm to 56.40 cm with a mean of 35.86 cm. Number of suckers per plant ranged from one to 14.40 with a mean of 7.76. Days to maturity ranged from 178 to 213 days with a mean of 197 days. Yield per plant ranged from 0.05 kg to 1.16 kg with a mean of 0.67 kg. Corm length ranged from 2.26 cm to 9.36 cm with a mean of 6.70 cm. Corm diameter ranged from 2.62 cm to 11.06 cm with a mean of 6.74 cm. Cormel length ranged from 3.40 cm to 8.38 cm with a mean of 5.78 cm while cormel diameter ranged from 2.45 cm to 5.95 cm with a mean of 3.71 cm. Corm weight ranged from 0.04 kg to 0.39 kg with a mean of 0.17 kg. Cormel weight ranged from 16.21 g to 84.30 g with a mean of 39.71 g.

3.3. Estimation of Variability

Genotypic and phenotypic variance of all traits studied among taro accessions are presented in Table 5. Genotypic and phenotypic variance ranged from 0.001 to 56.79 and 0.001 to 80.39, respectively. High phenotypic variance values were noted for plant height (80.39), cormel weight (45.83), leaf length (31.11) petiole length (18.42), and days to maturity (41.98). Whereas, high genotypic variance value 56.79, 25.73, 21.84, and 20.31 were noted for plant height, days to maturity, leaf length, and cormel weight, respectively. The lowest genotypic and phenotypic variance were noted for leaf area, yield per plant and corm weight.

Phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values for all traits studied among taro accessions are presented in Table 3. A high percentage of PCV was observed for leaf area (80.67%), followed by corm weight (58.82%), total yield (28.25%), yield per plant (21.11%), and number of suckers per plant (20.66%). Moderate PCV was noted for cormel weight (17.05%), corm diameter (15.56%), petiole length (13.49%), corm length (12.58%), plant height (11.91%), leaf length (11.835%), and leaf breadth (10.663%). The remaining traits showed low PCV. Likewise, a high percentage of GCV were observed for leaf area (76.923%), followed by corm weight (58.824%), total yield (24.118%), and yield per plant (21.108%). Moderate percentage of GCV was noted for the number of suckers per plant (16.950%), yield per plant (14.925%), corm diameter (14.613%), corm length (11.268%), and plant height (10.011%), while other traits showed a low percentage of GCV.

3.4. Estimation of Heritability and Genetic Advance

The estimate of broad-sense heritability for all traits studied among taro accessions is presented in Table 5. Very high heritability values were noted for the number of leaves per plant (87%), corm length (81%), corm diameter (88%), corm weight (89%), and cormel diameter (80%). Moderate high heritability were noted for plant height (71%), leaf length (70%), leaf area (75%), number of suckers per plant (67%), days to maturity (61%), yield per plant (66%), cormel length (65%), and total yield (73%), while petiole length (55%), and cormel weight (44%) were showed moderate heritability.

Genetic advance as percentage of mean (GAM %) values for all traits is presented in Table 3. Genetic advance as percentage of mean ranged from 3.53% to 129.31%. Most studied traits had relatively high genetic advance (>10%). Traits with high GAM include leaf area (129.31%), total yield (36.13%), corm weight (22.48%), corm diameter (24.08%), yield per plant (18.52%), corm length (17.72%), plant height (14.77%), leaf length (14.58%), cormel weight (13.26%), leaf breadth (13.18%), petiole length (12.93%), cormel diameter (12.29%), and cormel length (11.27%). The lowest genetic advances (<10%) were noted for the number of leaves per plant (9.20%) and days to maturity (3.53%).

3.5. Relationships among Quantitative Traits

Phenotypic correlation () and genotypic correlation () estimates of all traits studied among taro populations are presented in Table 6. Yield per plant had showed a strong, positive, and highly significant genotypic correlation with plant height (0.99), petiole length (0.99), leaf length (0.85), leaf breadth (0.92), leaf area (0.82), corm length (0.71), corm diameter (0.91), corm weight (0.99), and cormel weight (0.99). Cormel diameter (0.49) and cormel length (0.69) showed a moderate, positive, and highly significant genotypic correlation with yield per plant. Likewise, yield per plant had strong, positive and highly significant phenotypic correlation with plant height (0.72), while petiole length (0.51), leaf length (0.53), leaf breadth (0.54), leaf area (0.51), corm length (0.40), corm diameter (0.56), number of cormels per plant (0.37), cormel diameter (0.34), cormel length (0.47), corm weight (0.68), and cormel weight (0.61) had showed a moderate positive and highly significant phenotypic correlation with yield per plant. But yield per plant showed a moderate, negative, and highly significant correlation with number of leaves per plant ( = 0.64 and = 0.48), respectively.

3.6. Path Coefficient Analysis

The path analysis result at the genotypic level is presented in Table 7. Plant height (1.49) exerted a high positive and direct effect on yield per plant. The indirect effects of plant height on yield per plant via leaf area (0.93), corm weight (0.53), cormel weight (0.21), corm length (0.08), cormel length (0.07), and cormel diameter (0.02) were positive. Leaf area (0.97) exerted a high positive and direct effect on yield per plant. The indirect effects of leaf area on yield per plant via plant height (1.43), corm weight (0.35), and cormel weight (0.21) were positive. Corm weight (0.74) exhibited a high positive and direct effect on yield per plant. Positive and indirect effects were also found via plant height (1.12), leaf area (0.46), corm length (0.07), cormel diameter (0.05), cormel length (0.02), corm weight (0.73), and number of leaves per plant (0.13) on yield per plant.

Cormel weight (0.21) exhibited a positive and direct effect on yield per plant. Positive and indirect effects were also exerted through plant height (1.48), leaf area (0.96), corm length (0.09), cormel diameter (0.02), cormel length (0.04), cormel weight (0.21), and number of leaves per plant (0.09) on yield per plant. However, corm length (0.12) exhibited low positive and direct effect on yield per plant. Positive and indirect effects on yield per plant were also found via leaf area (0.47), corm weight (0.41), cormel weight (0.16), cormel length (0.06), and number of leaves per plant (0.03) on yield per plant. Cormel diameter (0.05) showed a low positive and direct effect on yield per plant. A positive and indirect effect was also found via leaf area (0.35), corm weight (0.25), cormel weight (0.21), cormel diameter (0.66), and number of leaves per plant (0.07) on yield per plant. Cormel length (0.08) exhibited a low positive and direct effect on yield per plant. Positive and indirect effects also found through plant height (1.37), leaf area (0.90), corm weight (0.39), cormel weight (0.06), and number of leaves per plant (0.08) on yield per plant.

4. Discussion

4.1. Variability in Quantitative Traits

META combined over seasons in the current study showed highly significant () differences among the tested accessions for most traits (Table 3). These significant variations among tested taro accessions for the characters showed the existence of variability to have an effective selection. The variation observed for measured quantitative traits in this study were in agreement with the earlier findings of some researchers [34, 35] who had reported high variability for same traits among 14 taro genotypes studied in India.

PCV and GCV values are considered as high if they are ≥20%, medium 10–20%, and low ≤10% [36]. The present study showed higher PCV than GCV estimates for all characters (Table 5) indicating existence of variability among accessions for the characters studied. Besides, PCV and GCV in this study were close to one another for most characters indicating the environmental effects are small. Higher genotypic variances and coefficients of variation for most of the characters than their corresponding environmental variances are also indicative of the existence of variation at the genotypic level. The present work is in line with the work [34] that reported higher PCV than GCV among 14 taro genotypes studied in Ethiopia [37] and India [38].

4.2. Heritability and Genetic Advance in Quantitative Traits

Estimate of genetic advance is more useful as a selection tool when considered jointly with high genotypic coefficients of variation and high heritability values [39]. In this study, high heritability values with high genetic advance as a percentage of the mean (>10%) were observed for corm weight and leaf area indicating these characters are principally under genetic control (due to the high additive gene effect) and selection for these traits can be achieved through their phenotypic performance. For traits with a high heritability value but a moderate value of genetic advance (such as corm length) careful selection is needed. Similarly, characters with high heritability values but a low value of genetic advance (i.e., number of leaves per plant) may be governed by nonadditive gene action or a high genotype by environmental interaction and used for the development of hybrid varieties. Lower heritability values and GAM (%) implies most of the variations for these traits were environmental, and such traits require more management practice than selection to improve the traits performance. Similar work was reported by many researchers on different crop plants [15, 22, 34, 37–42].

4.3. Associations in Quantitative Traits

In the present study, most traits had a higher genotypic correlation coefficient than phenotypic correlation indicating the association among characters was largely due to genetic variance and the reverse is because of environmental variance [43]. Besides, most characters showed a positive correlation both at the genotypic and phenotypic level with yield per plant. The positive and significant association might be due to the effect of genes, a result of the presence of strong coupling linkage between their genes, or the character may be the result of pleiotropic genes that could control these characters in the same direction [44]. Yet again, from this finding some characters showed negative and significant association among each other. Such negative correlation might be because of the fact that different genes or pleiotropic genes that have dominance on the character may control the character in different direction [44]. Yield per plant was positively and significantly () correlated with most traits indicating these traits are useful for indirectly selecting high-yielding varieties, as selection for yield per se is not effective because of the complex nature of the trait. The present finding is in line with the work [45] that reported a similar scenario.

4.4. Direct Effects of Characters on Yield

Plant height, leaf area, corm weight, and cormel weight exerted a positive direct effect on yield per plant. These characters also observed a strong, positive, and highly significant genotypic correlation with yield per plant. The high correlation coefficient of these characters with yield per plant was largely due to the direct effect. As the direct effect and genotypic correlation between the two traits are positive, it indicates a true relationship. The cause and effect relationships are the products of interacting characters influencing each other [11]. In line with this finding, many researchers reported the same among taro [45, 46] and Tania [15, 45, 46].

5. Conclusion

This study assessed the phenotypic variability of 100 taro accessions collected from five states of Nigeria. The analysis of variance revealed the existence of phenotypic variability among the studied accessions. High genotypic coefficient of variation, heritability, and genetic advance were observed for leaf area, corm diameter, plant height and corm weight. The result of the genotypic correlation coefficient as proved by path analysis also showed plant height, leaf area, corm, and cormel weight have a positive and significant direct effect on yield per plant. Thus, it can be concluded that these characters exert a high positive direct effect on yield t at the genotypic level and hold the highest merits to be selected in breeding programs towards improving yield in taro. The presence of morphological variation between genotypes will give opportunity for studying the accessions at the molecular level and searching of functional alleles that could be used in marker-assisted selection.

Data Availability

The data used to support the findings of this study are available from the corresponding and first authors.

Conflicts of Interest

The authors declare that they no conflicts of interest.

Acknowledgments

This research was funded by the European Union Commission through the MoBreed Project (Intra-Africa Academic Mobility Scheme). We are thankful to all farmers and agriculture extension services in five states of Nigeria. We also thank Ebonyi State University for valuable assistance during accessions collection and field experimentation. Tilahun Wondimu, from the Oromia Agricultural Research Institute, Ethiopia, is a scholar of the “Intra-Africa Academic Mobility Scheme” under the project grant number 2016–2988 on “Enhancing training and research mobility for novel crops breeding in Africa (MoBreed)” funded by the Education, Audiovisual, and Culture Executive Agency (EACEA) of the European Commission. The project provided a scholarship for academic training and research mobility and a research grant to the first author to complete a PhD degree at Ebonyi State University (Nigeria).

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Copyright © 2023 Tilahun Wondimu Fufa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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