The 42 eggplant accessions, which form three main populations from Malaysia (19 genotypes), China (6 genotypes), and Thailand (17 genotypes), were used for this study, as presented in Table 1 and Fig. 1. The accessions were assessed in an open field setting at Ladan 15, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia, between September 2018 and January 2019. The accessions were evaluated according to Musa et al. (2021) and plant maintenance including fertilizer application, pest and disease management, weed control were carried out as recommended by the Department of Agriculture, Malaysia (https://jpn.penang.gov.my/index.php/perkhidmatan/teknologi-tanaman/sayur-sayuran/78-terungsp-424).

Figure 1. 

Some of the eggplant genotypes used in this study.

The eleven sets of growth, yield and yielding data were collected and measured under open field cropping conditions. They yield traits include fruit weight (FW), average fruit weight (AFW), fruit length in cm (FL), fruit width in mm (FD), fruit length/width (FL/W), number of fruits per plant (NF/P), and yield per plant (Y/P). While the growth parameters include number of branches per plant (NBPP), plant height (PH), first harvest (PH), and flowering days to 50% (D50%F). All data measurements and observations were conducted on the same day to minimize variations in the developmental stage of plant growth or environmental conditions.

Using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA), all growth, yield, and yield-related data were subjected to analysis of variance (ANOVA), and means were separated using the least significant difference (LSD) at a 5% level of significance. For every attribute that was tested, the mean and standard deviation were also noted.

A modified cetyl trimethylammonium bromide (CTAB) technique was used to extract genomic DNA from early leaves (3 to 4 weeks old) of the 42 genotypes of eggplant (Doyle and Doyle 1987). From the sequence data that was available in the published literature (Khapte et al. 2018; Pandiyarajet al. 2019), exactly 17 SSR markers were chosen. The details of the 17 polymorphic primers and their sequences are presented in Table 2. PCR was performed in a total volume of 16 μL containing 40 ng template DNA, 0.8 μM concentration of each primer (forward and reverse), 8 μL master mix (2×Power Taq PCR MasterMix), 3.2 μL DNA and 3.2 μL nuclease-free water. PCR amplification for background markers was conducted according Khapte et al. (2018) with slight modification.

The polymorphism information content (PIC) value for each SSR locus was computed using the formula PIC = 1-∑pi², where pi is the frequency of the i^th allele in the set of 42 eggplant genotypes studied (Weir BS 1990). The POPGENE 1.31 program by Yeh et al. (1999) was used to calculate the observed number of alleles, effective number of alleles (Ne), He, Nei’s expected heterozygosity (Nei’s), and Shannon’s information index (I). In all eggplant genotypes investigated, amplified fragments were evaluated for the presence (1) or lack (0) of the corresponding bands. Based on the binary data, cluster analysis was performed using NTSYS-PC version 2.1 and the unweighted pair group method with arithmetic averages (UPGMA). The results are presented as a dendrogram using the Rohlf (2000) approach.

Statistical analysis revealed a highly significant (p ≤ 0.01) difference for the traits under study (Table 3). The mean performance for the morphological and yielding traits are presented in Tables 4, 5. The number of days to attain 50% flowering ranged from 57.33 to 77.67 days, as MV12 and MV19 (57.33 days) had the shortest days to attain 50% flowering, whereas the longest days to 50% flowering (77.67 days) were recorded in MV11, which were not statistically different from MV8 and MV11 (77.33 days). In terms of first harvest, the highest number of days (90 days) was recorded in MV11, whereas MV13 and MV19 produce fruits earlier at 69.67 days. In this study, the number of branches was observed among the varieties in which TV13 recorded the highest (10.22), whereas TV2 and TV3 had the lowest (2.67 and 2.55 respectively). The tallest plant in this trial was observed in TV15 (99.55 cm), whereas the shortest plant was observed in TV17 (59.33 cm). The significant variation in vegetative growth among different types of eggplant showed that there is potential for improving these types in terms of all the characteristics that contribute to the reproductive phase of the plant. The wide range of vegetative growth among the different types of eggplant indicates that there is a promising opportunity to enhance the studied types in all aspects that ultimately support and prepare the plant for reproduction. The presence of a genetic composition combined with the influence of the environment was observed as a possible explanation for this(Sulaiman et al. 2020; Chukwu et al. 2022). The values for fruit diameter ranged from 36.57 cm to 10.00 cm. The TV17 genotype had the highest value, whereas MV9 had the lowest value. In the case of fruit length, the values were between 31.50 and 10.70. The longest fruit (31.50 cm) was from TV2 which is not statistically different from TV12 (30.63 cm), whereas the shorted fruit (10.70) was from MV9 which is not statistically different from TV14 (10.53 cm). The fruit length/diameter ratio ranged from 2.29 to 0.48 cm, and the highest (2.29 cm) was observed in MCV11 followed by TV12 (1.82 cm), whereas the lowest fruit length/diameter (0.48 cm) was recorded in TV17, which was statistically similar to TCV16 (0.50 cm). In terms of fruit weight, the weightiest fruit (303.83 g) was recorded in TV17, whereas TV8 produced fruits with the lowest weight (17.23 g). Significant differences were recorded for average fruit weight. MV18 (269.38 g) produced the weightiest fruits, followed by TV17 (249.00 g), whereas TV8 produced lighter fruits (86.03 g). Significant differences were observed among the varieties in terms of the number of fruits per plant, with values ranging from 41.83 to 20.53 fruits. The highest number of fruits in the individual plant was recorded in TV2 (41.83), which was statistically similar to TV12 (40.63 cm), while the lowest value for this trait was recorded in MV9 (20.37), which was statistically similar to TV14 (20.53 cm). Highly significant yield plant was recorded in MV18 (5.97 kg), followed by TV17 (5.49 kg), whereas TV8 recorded the lowest yield (0.98 kg). Overall, there was a notable variation in yield characteristics among all genotypes, indicating their strong diversity. This discrepancy can be attributed to the distinct origins of each genotype, leading to variation within the population (Musa et al. 2020). Several studies have also been conducted on the variation in characteristics among different types of eggplant. The results of these studies align with the findings of Caguiat and Hautea (2014), which further support the claim made by Naujeer (2009) that increasing yield and improving fruit quality are the primary goals of eggplant breeding programs.

The seventeen SSR markers used demonstrated successful amplification (Table 6). However, all primers were polymorphic and amplified between two and four alleles, resulting in a total of 43 alleles across all markers. This equated to an average of 2.53 alleles per SSR marker. The most common allele had an average frequency of 0.53, ranging from 0.33 to 0.83. The average number of effective alleles (Ne) was 2.31, which was slightly lower than the total number of alleles (Na) at 2.53. The range for Ne was 1.36 to 3.79. The SSR marker is valuable for assessing genetic variation in eggplant. In this study, the average PIC value was 0.45, ranging from 0.29 to 0.68. This value was higher than the average PIC value of 0.401 reported by Vilanova et al. (2012), but lower than the value of 0.83 reported by Datta et al. (2021). A PIC value above 0.5 suggest locus with high levels of polymorphism. The classification of a PIC value into low polymorphic, moderate polymorphic, and high polymorphic loci has been established by several studies (Nunome et al. 2009; Kalia et al. 2011; Ge et al. 2013; Gramazio et al. 2019). In this study, the average PIC value was determined to be 0.45, indicating a moderate level of polymorphism in the loci. It is worth noting that the measurement of genetic diversity in eggplants varies across different literature sources. The expected gene heterozygosity (He) for each pair of primers ranged from 0.28 to 0.74, with an average value of 0.54. This study is comparable to the findings of Hurtado et al. (2012), who conducted a study on genetic diversity in Sri Lankan accessions and reported a high diversity value of He = 0.54. Similarly, our research revealed values of Shannon ’s information index ranging from 0.45 to 1.36, with an average of 0.84. This finding aligns with the results reported by Datta et al. (2021), who also observed a Shannon’s index value of 0.85. However, our result was higher than the value reported by Ge et al. (2013), where the Shannon index value was 0.570. These variations in diversity measures may be attributed to differences in the materials studied, analytical approaches employed, and types of markers used (This et al. 2004).

The seventeen SSR markers were selected based on the Euclidean distances between the 42 eggplant genotypes to create a UPGMA dendrogram, as shown in Table 7 and Fig. 2. The dendrogram classified 42 eggplant genotypes into five main groups with a similarity coefficient of 4.24, which was the best fit for convenient discussion, implying that eggplant genotypes have a high level of variation. Group I had the largest number and consisted of 46 genotypes. Malaysian varieties had the largest number (MV1, MV5, MV14, MV15, MC16, MV18 and MV19), followed by Thailand varieties (TV5, TV2, TV6, TV12 and TV13), while Chines varieties had four varieties (CV2, CV3, CV5 and CV6). Group II consisted of five genotypes: four from Malaysia (MV2, MV4, MV9 and MV14) and one from Thailand (TV11). Group III had the second largest number and consisted of 10 genotypes. Thailand varieties had the largest number with seven genotypes (TV1, TV4, TV8, TV10, TV15, TV16 and TV17), followed by Chinese varieties (CV1 and CV4), while Malaysia had one variety (MV7). Another group (Group IV) includes four Malaysian varieties (MV3, MV8, MV9 and MV10) and one Thailand variety (TV7). Meanwhile, cluster V had six genotypes, viz are MV6, MV12, MV13, and MV17 from Malaysia and TV3 and TV14 from Thailand. Several studies have employed SSR markers to investigate the genetic diversity of eggplant. Nunome et al. (2003), Stagel et al. (2008), Demir et al. (2010), and Datta et al. (2021) have reported on this topic. These studies used accessions from various countries, either a shared ancestry or similar morphological traits among these accessions. In contrast, the accessions exhibited significant spatial separation, implying variations in agronomical characteristics or diverse origins. The presence of accessions from distinct clusters and different geographic sources genetic exchange among plant breeders located in various regions. The dissimilarities observed among the accessions may be attributed to prolonged exposure to distinct environmental conditions (Datta et al. 2021).

Figure 2. 

The genetic relationship among the 42 eggplant accessions based on seventeen SSR markers was determined using the unweighted pair group method with arithmetic mean (UPGMA) at a 4.24 similarity coefficient using SAHN clustering on the UPGMA method.