Genetic variability studies for tuber yield and yield attributes in Ethiopian released potato (Solanum tuberosum L.) varieties

Experimental materials and sites

The present study was carried out at two locations in the central highlands of Ethiopia, Holetta Research Centre and Adaberga sub-station research fields for a single cropping season (Table 1). The experiment consisted of 20 released varieties and one local potato cultivar (Table S1). The experiment was laid out in a randomized complete block design replicated three times. Analysis of variance for each location and across locations was done using SAS software version 9.3 (SAS Institute, Cary, NC, USA) as per the procedure indicated for the design using a general linear model (GLM) (Gomez & Gomez, 1984).

Data collection and measurement for the traits

Data collection and measurement of yield and agronomic traits (days to 50% flowering, days to physiological maturity, number of leaves per plant, plant height, stem number per hill, average tuber number per hill, average tuber weight, total tuber yield, marketable tuber yield, specific gravity, dry matter content, starch content percentage and total starch yield) were under taken based on the procedures indicated by Lemma, Wassu & Tesfaye (2020).

Statistical methods

For each quantitative attribute, phenotypic and genotypic variability were estimated using variances and coefficient of variations using the procedure suggested by Burton & de Vane (1953).

$$\mathrm{G}\mathrm{e}\mathrm{n}\mathrm{o}\mathrm{t}\mathrm{y}\mathrm{p}\mathrm{i}\mathrm{c}\mathrm{v}\mathrm{a}\mathrm{r}\mathrm{i}\mathrm{a}\mathrm{n}\mathrm{c}\mathrm{e}({\sigma }^2\mathrm{g})={\displaystyle \frac{Mg-Me}{r}}$$where σ²_g = genotypic variance

M_g = mean square of genotype

M_e = mean square of error; r = number of replications; Phenotypic Variance (σ²_p) = σ²_g + σ²_e

where, σ²_g = Genotypic variance; σ²_e = Environmental variance; σ²_p = phenotypic variance

$$\mathrm{P}\mathrm{C}\mathrm{V}=\left(\frac{\sqrt{{\sigma }_{\mathrm{p}}^2}}{\overline{\mathrm{x}}}\right)\times 100$$

$$\mathrm{G}\mathrm{C}\mathrm{V}=\left(\frac{\sqrt{{\sigma }_{\mathrm{g}}^2}}{\overline{\mathrm{x}}}\right)\times 100$$where PCV = Phenotypic coefficient of variation

GCV = Genotypic coefficient of variation

$\overline{\mathrm{x}}$ = population mean of the character being evaluated.

PCV and GCV values were classified as low, moderate, and high according to Sivasubramanian & Menon (1973) as 0 up to 10% = Low, 10 up to 20 = Moderate and above 20 = High.

Estimates of variability components over locations

The computation of genotypic and phenotypic variance across locations considered the expected mean squares from combined analysis of variance and the σ²P, σ²G and H² = phenotypic variance, genotypic variance and heritability in broad sense were determined as indicated in Table 2 as proposed by Jalal & Ahmad (2012). Principal component analysis (PCA) was conducted to reduce the observed agronomic and yield traits as suggested by Amy & Pritts (1991). The study considered the main component of maximum eigenvalue of up to 1.0 to estimate the variability in potato varieties studied.

Phenotypic and genotypic variation

At Holetta, the estimated phenotypic (PCV) and genotypic (GCV) coefficient of variations of specific gravity and total starch yield of the different potato genotypes studied ranged between (0.71% to 35.23% and 0.62% to 34.51%), respectively. At Adaberga the PCV and GCV values of specific gravity and total starch yield ranged between (0.91% to 32.75% and 0.83% to 31.97%), respectively (Table 5). The over locations PCV values range from 0.75% (specific gravity) to 32.22% (total starch yield) while the GCV values ranged from 0.70% (specific gravity) to 30.22% (total starch yield) (Table 6). The results of the phenotypic variance were in general higher than the genotypic variance for all characters studied.

The difference between PCV and GCV was the most pronounced for the traits stem number, average tuber number, average tuber weight, number of leaves per plant, tuber yield. Therefore, we speculated that these traits are substantially influenced by the growing environments.

Estimates of heritability and genetic advance

The estimated values of H² and GAM ranged from 33.52% (average tuber number per hill) to 98.66% (days to 50% flowering) and 1.35% (specific gravity) to 58.26% (total starch yield), respectively (Table 6). All the traits had high heritability values but average tuber number per hill, days to physiological maturity, average tuber weight, and the number of leaves per plant. Highest GAM was recorded for total starch yield, starch content percent, total and marketable tuber yields, plant height, and the number of stems per hill. High heritability coupled with high GAM was recorded from all the traits with high GAM, meaning that a simple breeding method could be employed to advance these traits. Comparatively moderate heritability with low and moderate GAM was recorded for days to physiological maturity, the number of leaves per plant, average tuber number per hill, and average tuber weight per plant, suggesting non-additive gene action in their control: hence complex breeding methods might be recommended improving potato yield through these traits.

Principal component analysis

The principal component (PC) analysis was used to combine the observed traits into four main components that have eigenvalues above 1.0 and was able to explain the tested variability at 87.53% (Table 7). PC1 with the eigenvalue 5.7 explained 47.53% of the total variance, PC2 with the eigenvalue 2.1 contributed to 17.73% of the total variance, PC3 with the eigenvalue of 1.6 contributed to 13.57% of the total variance and PC4 with the eigenvalue 1.0 contributed to 8.70% among the 20 potato varieties and one local cultivar. The first principal component is strongly positively correlated with plant height, total tuber yield and total starch yield. The cumulative variance of 87.53% by the first four axes indicated that total tuber yield, total starch yield ton per hectare, and plant height contributed to the larger share of the observed variations among potato varieties and could effectively be used for selection. Other phenotypes, such as the number of “days to 50% flowering”, “average tuber number per hill”, and “marketable tuber yield ton per hectare” were also important, as they negatively affect the yield (Table 7).

Phenotypic and genotypic variation

The range of PCV and GCV variability for most of the characters were high, indicating the presence of sufficient scope for selection and improvement in these characters, including tuber yield t ha⁻¹. Similarly, maximum PCV and GCV values were reported by Abraham (2013) and Fekadu, Petros & Zelleke (2013) and Singh (2008) for tuber yield and other yield-related traits. These results agreed with Tripura et al. (2016), who reported high PCV and GCV values for tuber yield and additional yield-related traits as average tuber weight, tuber number, tuber breadth, and tuber yield in potato. Low PCV and GCV values were recorded for some tuber quality traits viz., specific gravity and dry matter content which is due to the fact that most tuber quality traits like tuber specific gravity and dry matter content are less influenced by environments (Singh et al., 2006). Likewise, Chepkoech et al. (2018) reported moderate PCV values and low GCV values in plant height, stem number, tuber number, and tuber weight traits. Low to moderate PCV and GCV values were also reported for tuber length (mm), single tuber weight (g), plant height (cm), branch number, lateral leaflet, and the number of tubers per plant.

Estimates of heritability and genetic advance

In the present study, heritability estimates were high for most of the studied traits as categorized (Low <30%; Moderate 30–60%; High >60%) by Robinson, Comstock & Harvey (1949) and Johnson, Robinson & Comstock (1955). The presence of high heritability in most traits indicates a lower environmental influence. Similar results were reported by Panja et al. (2016). Johnson, Robinson & Comstock (1955) categorized GAM values as Low (0–10), Moderate (10–20), and High (≥20). In the present study, results of analysis of GAM of all the studied traits had high to moderate values except specific gravity and days to physiological maturity that exhibited low GAM (1.35 and 3.83), respectively.

High value of H² and GAM indicated the existence of genetic variation in potato varieties which could be an opportunity for further improvement of potato. Similarly, Tripura et al. (2016) reported high heritability values coupled with high genetic advance for an average tuber weight plant⁻¹, single tuber weight, and tuber breadth. Similar reports for total tuber yield (kg per plot) were reported by Rangare & Rangare (2017) and Panigrahi et al. (2017). Likewise, Ozturk & Yildirim (2014) published moderate to high heritability for plant height, leaf width, leaf length, single tuber weight, plant yield, and starch content in potato. Low H² and GA values were reported by Fekadu, Petros & Zelleke (2013) for days to emergence, days to flowering, days to maturity, stem number, tuber yield, number of tubers, harvest index, medium tuber percentage, and biomass yield in potato.

Principal component analysis

The results of principal component analysis (PCA) for the studied traits are presented in Table 7. In the present study, the first three traits (plant height, total tuber yield and total starch yield) explained 47.53% of the variation. The result indicated that the cumulative variance of 87.53% was explained by the first four axes (Table 7). Afuape, Okocha & Nijoku (2011) reported a cumulative variance of 76.00% for the first three axes in evaluating twenty-one sweet potato genotypes. Koussao et al. (2014) identified four principal components, which accounted for 67.22% of the total variation among the accessions. Placide et al. (2015) also used PCA to study the fifty-four sweet potato genotypes and found that the first seven PCs explain the cumulative variance of 77.83%. Rahanjeng & Rahayuningsih (2017) reported 79% of variability using sixty-two sweet potato accessions. In our study the first four principal components explained 87.53% of the variability. This value is within the range mentioned in earlier studies.