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Article

Genetic Uniqueness and Pomological Diversity Among the Apple Accessions Maintained Within the Croatian National Clonal Germplasm Repository

by
Danijel Čiček
1,*,
Almira Konjić
2,
Martina Skendrović Babojelić
3,
Predrag Vujević
1,
Silvio Šimon
4 and
Fuad Gaši
2
1
Croatian Agency for Agriculture and Food, Center of Pomology and Vegetable Crops, Gorice 68b, 10000 Zagreb, Croatia
2
Faculty of Agriculture and Food Sciences, University of Sarajevo, Zmaja od Bosne 8, 71000 Sarajevo, Bosnia and Herzegovina
3
Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia
4
Ministry of Agriculture, Forestry and Fisheries, Ulica Grada Vukovara 78, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(1), 113; https://doi.org/10.3390/agronomy15010113
Submission received: 6 December 2024 / Revised: 1 January 2025 / Accepted: 2 January 2025 / Published: 4 January 2025
(This article belongs to the Section Crop Breeding and Genetics)
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Versions Notes

Abstract

:
In the Croatian apple germplasm, there are, presumably, unique genotypes that have not yet been documented in reference molecular databases. Due to similarities between accessions, incorrect names are often used, which creates a problem in the identification of accessions. Overall, 169 apple accessions and 11 reference cultivars from the largest ex situ apple collection in the Republic of Croatia were investigated within this study. The examined accessions have been genotyped using SSR markers. In order to assess the advantage of a high-resolution marker system, such as SNPs, compared to low-resolution markers, such as SSRs, a subset of 23 unique apple accessions and eight reference cultivars were genotyped using the 480K Affymetrix Axiom SNP array. Results obtained through the use of two marker systems revealed 26 synonyms, 40 duplicates, 13 mislabeling accessions, 45 accessions with confirmed identity (known cultivars), and 45 unique accessions, as well as the true identity of a large number of accessions, currently maintained at the Croatian National Apple Germplasm Bank. In order to investigate the pomological variability of unique apples, a three-year study was carried out on eleven pomological traits. The researched germplasm shows an exceptional diversity of pomological properties. Many of the accessions can be considered unique, and the results of the pomological characterization indicated that this germplasm contains valuable traits of interest for future breeding programs.

1. Introduction

Apple trees are the most prevalent fruit species in temperate climates [1]. While commercial apple cultivation relies on a limited number of widely distributed cultivars, there is a rich diversity of over 10,000 documented apple cultivars globally [1]. This diversity is crucial, as it provides a reservoir of genetic traits that can be used for breeding programs aimed at improving fruit quality and resilience. In recent decades, the conservation and utilization of plant genetic resources have gained significant attention, particularly in the context of sustainable food production [2].
Data on apple morphology and genetic structure provide significant assistance in the maintenance of germplasms and the selection of suitable material for the breeding of premium cultivars [3]. Certain traditional apple cultivars exhibit desirable morphological and pomological properties, as well as better sensory acceptability, compared to commercial cultivars. Additionally, these cultivars have lower requirements for chemical agents during cultivation and contain a higher proportion of biologically active compounds. However, due to similarities between cultivars, incorrect names are often used, which creates a problem in the identification of cultivars.
Croatia boasts a long-standing tradition in fruit production, with traditional apple cultivars playing a vital role [4]. It is believed that within the Croatian apple germplasm, there are unique genotypes that have not yet been documented in reference molecular databases. Additionally, certain traditional genotypes may exhibit superior physical and chemical properties compared to standard cultivars. The study by Jakobek et al. [5] examining the pomological, physical, and chemical properties of traditional apple cultivars from Croatia reports a higher percentage of specific apple polyphenols, dihydrochalcones, in much higher concentrations in traditional cultivars compared to commercial cultivars. Traditional apple cultivars show a diversity of pomological characteristics, and they are rich in polyphenols and have high antioxidant activity, even higher than those found in conventional cultivars [6]. They might represent an important source of bioactive compounds and constitute the basis for further breeding [6]. Polyphenols from traditional apple cultivars have the potential to serve as natural defenses against fungal infections, suggesting the importance of selecting or breeding cultivars with higher polyphenol content to improve resistance to postharvest pathogens, thereby enhancing the quality and safety of stored apples [7]. Dolker et al. [8] studied the phenological and pomological characteristics of seven local apple cultivars of the trans-Himalayan region of Ladakh. Research has shown that domestic apple cultivars possess significant diversity. Unique characteristics such as early flowering and early fruit ripening are interesting for future breeding programs for the development of early ripening cultivars. Understanding the origin of these selected accessions is crucial for future breeding activities, as it can guide the selection of genotypes that are best suited for specific environmental conditions and consumer preferences.
Numerous phenotypic studies have been carried out on European apple germplasm. Namely, pomological properties and fruit quality of the most represented traditional cultivars of apples from the Topusko municipality were investigated by Skendrović Babojelić et al. [9]. The morphological diversity of 30 indigenous apple cultivars in Montenegro was studied by Božović et al. [10]. Morphological characterization of the collection of Spanish apple cultivars was carried out by Arnal et al. [11]. Phenological, morphological, biochemical, and sensory properties of 22 local genotypes of summer apple cultivars in Turkey were investigated by Karatas [12]. A total of 31 local apple cultivars from Italy were analyzed by Cice et al. [13] using agronomic, morphological, and physicochemical properties. The results of the analyzes of the properties of all the mentioned studies showed a high degree of phenotypic diversity for the analyzed properties between the accessions.
In the past decade, Simple Sequence Repeat markers (SSRs) have been widely used for the genetic characterization of apples. These markers have been particularly useful in studying genetic diversity due to their abundance, reproducibility, and polymorphism [14].
SSRs have been used to investigate ex situ collections in New Zealand [15], Spain [16,17,18], Sweden [19], Iran [20], the Netherlands [21], Lithuania [22], Turkey [23], Norway [2], Bosnia and Herzegovina [24,25,26,27,28], and Croatia [29,30,31], revealing genetic relationships, structure, and diversity, as well as detecting mislabeling and redundancies.
However, in the last few years, medium- and high-density markers based on single-nucleotide polymorphisms (SNPs) have emerged, allowing for more detailed genome-wide comparisons and offering higher resolution due to a larger number of markers. The popularity of these markers has increased due to their flexibility as well as cost efficiency [32]. Currently, a few SNP arrays are available for research in apples: the Infinium® IRSC 8 K array [33], the Illumina Infinium® 20 K array [34], 50 K array [35], and the Affymetrix Axiom® 480 K SNP array [36]. These arrays have been used in various genetic analyses of apple cultivars, including the investigation of genetic structures [37], pedigree studies [38,39,40], ploidy detection [41], and genome-wide association studies [42,43,44,45].
SNPs have also been used alongside SSRs in recent investigations to analyze genetic relationships within apple germplasm, revealing finer genetic distinctions that contribute to breeding programs and conservation efforts in Sweden [46], Denmark [47], and Bosnia and Herzegovina [48,49]. In these studies, SNPs have been proven to provide a better overview of relationships and are more effective in detecting genetic structures compared to SSR markers.
Overall, 169 apple accessions and 11 reference cultivars from the largest ex situ apple collection in the Republic of Croatia were investigated within this study. The examined accessions were genotyped using SSR markers. Additionally, the comparative advantages of a high-density marker system (Axiom® Apple 480 K SNP array) for pedigree reconstruction and ploidy assessment were explored. The obtained molecular and pomological data enabled an assessment of the genetic and pomological diversity, as well as the relationships and genetic structure, among the apple accessions maintained within the Croatian National Clonal Apple Germplasm Repository (CNCAGR). Based on the obtained results, homonyms, synonyms, and mislabeled accessions were identified using international SSR and SNP genetic databases. This is the first study in the region to integrate both SSR and SNP genetic markers, along with phenotypic data.

2. Materials and Methods

2.1. Plant Materials

The Croatian National Apple Germplasm Bank is the largest ex situ apple collection in the Republic of Croatia. The collection contains 169 accessions and 11 reference cultivars (Supplementary File S5). The collection plantation is located in Donja Zelina (45°55′12″ N 16°14′42″ E) as part of the experimental orchard of the Croatian Agency for Agriculture and Food, Center of Pomology and Vegetable Crops. The accessions were collected mainly in the continental part of Croatia from private amateur collections and partly from older plantations and homesteads, and to a lesser extent from nurseries (cultivars deleted from the List of Fruit Species Cultivars). The collected genotypes were grafted onto the MM 106 rootstock, and four seedlings per accession were produced and planted in the collection plantation in the period from 2013 to 2017. The collection includes 4 trees per accession, with a spacing of 3.6 × 2.5 m, and no replication methods were applied. The average annual temperature in this area is 10.7 °C with 855.1 mm of total rainfall. The soil on which the collection is planted belongs to the pseudogley soil type, with a pH of 5.89 and humus 1.11%. Maintenance practices include irrigation, fertilization, and pest control. The accessions were registered in the Croatian Plant Genetic Resources Database.

2.2. SSR Genotyping

DNA extractions were performed for each of the young leaf samples using the SBM DNA extraction protocol as described by Edge-Garza et al. [50]. Samples were re-suspended in Tris-HCl buffer and diluted as necessary using sterile distilled water for use in the polymerase chain reaction (PCR) genotyping screen.
DNA reference samples (‘Worcester Pearmain’, ‘M9’, ‘M27’, ‘Michelin’, ‘Fiesta’, and ‘Robusta 5’) were included in the DNA fingerprinting analysis. Twelve (12) microsatellite (SSR) markers from the NIAB EMR genotyping set were used to analyze the apple accessions. These 12 markers have been previously used to create the database, and they were used here in order to compare obtained profiles with the existing ones. Data were generated using an Applied Biosystems 3110 Prism Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). Data were collected and analyzed using the GENESCAN 6.x and GENOTYPER 3.8 (Applied Biosystems, Foster City, CA, USA) software applications. Allele sizes estimated by the software were then rounded to a whole number by the operator and adjusted according to the profiles of included standards. Fingerprints for all samples were compared to the respective databases, which contain fingerprints of over 2000 apple accessions from the National Fruit Collection at Brogdale, Tamar Valley (TV) Collection and Irish Seed Savers Association (ISSA) Collection.

2.3. SNP Genotyping

Leaf samples obtained from the Croatian National Apple Germplasm Bank in 2019 were collected and immediately frozen at −80 °C to preserve the genetic material until further analysis. Genomic DNA was then isolated from these leaf samples using the NucleoSpin Plant II mini kit for DNA extraction from plants (Macherey-Nagel, Dueren, Germany), in accordance with the manufacturer’s protocol. Following DNA extraction, the quality and quantity of the genomic DNA were assessed using standard quality control methods. Subsequently, the samples were genotyped using the Axiom® Apple 480 K SNP array (Thermo Fisher Scientific, Waltham, MA, USA) [36].

2.4. Pomological Characterization

The pomological determination of 48 unique apple accessions, based on the results of SSR analysis, and 11 reference cultivars was carried out at the Croatian Agency for Agriculture and Food, Center of Pomology and Vegetable Crops. The samples were collected in the experimental plantation and transported to the laboratory, where only healthy fruits were separated, and the pomological, physical, and chemical traits (fruit weight, fruit height, fruit width, fruit shape index, length of stalk, width of stalk, fruit hardness, content of soluble solids, total acids, content of soluble solids and total acids ratio, and pH value) of 20 fruits per cultivar were analyzed. The fruit weight was determined by a digital analytical balance (OHAUS Corporation, Parsippany, NJ, USA) and expressed in grams (g). The height (FH) and the width (FW) of the fruit, and the length (LST) and width of the stalk (WST), were measured by a digital caliper (Mitutoyo, Kawasaki-shi, Japan)—expressed in millimeters (mm). The fruit shape index as height/width was calculated from the height and width of the fruit data obtained. Fruit hardness (expressed in kg/cm2) was measured using a fruit hardness tester (TR Turoni, Forli, Italy) with an 11,3 mm probe as an average value from four measurements made at opposite fruit sides at the equatorial fruit zone. The juice from each fruit was extracted with an electric juicer and was used for the determination of soluble solid content (expressed in %) with a refractometer (ATAGO PAL-1, Minato, Tokyo, Japan). Titratable acidity (expressed in percent of malic acid per 100 mL of juice %) and pH value were measured with Titrator EasyPlus (Mettler Toledo, Columbus, OH, USA). The ratio soluble solids/total acids was calculated from data of the content of soluble solids and total acids.

2.5. Statistical Analyses

Principal component analysis (PCA) was performed and plotted in R studio [51] using the ‘factoextra’ v 1.0.7. [52], ‘ggplot2’ v 3.5.0 [53], ‘dplyr’ v 1.1.4. [54], ‘gridExtra’ v 2.3 [55], and ‘gt’ v 0.11.1. [56] packages.

2.6. Biostatistical Analyses

2.6.1. SSR Data Analysis

The Jaccard distance matrix for SSR data was computed in R Studio [51] using the ‘philentropy’ v 0.8.0 package [57].
The UPGMA (Unweighted Pair Group Method with Arithmetic Mean) dendrogram, based on Jaccard genetic distances, was constructed using MEGA 6 software v 6.0 (Molecular Evolutionary Genetics Analysis) [58].
Genetic diversity parameters for SSR data including number of alleles (Na), number of effective alleles (Ne), and gene diversity (He) were calculated using computer package SPAGeDi v 1.5 (Spatial Pattern Analysis of Genetic Diversity) [59].
The population structure for the SSR dataset was estimated with STRUCTURE v2.3.4 software [60] (Pritchard et al., 2000). Most probable K value estimation was evaluated using the Structure harvester ver. 0.6.1 application [61]. A bar plot of the results from Bayesian genetic structure analyses was generated using the online software ‘Structure Plot v2.0’ [62].
FCA (Factorial correspondence analysis) was conducted and plotted in R Studio [51] using the following packages: gee v 4.13-27 [63], arules v 1.7-8 [64], combinat v 0.0-8 [65], ade4 v 1.7-22 [66], rgl v 1.3.14 [67], and scatterplot3d v 0.3-44 [68].
AMOVA (Analysis of molecular variance) was conducted in R Studio v 4.3.3 [51] using the ‘polysat’ v 1.7-7 [69], ‘adegenet’ v 2.1.10 [70], and ‘vegan’ v 2.6-8 [71] packages.

2.6.2. SNP Data Analysis

The SNP data for all 31 tested genotypes were analyzed using PLINK 1.9 software [72]. SNPs were pruned for linkage disequilibrium (LD) using the command ‘--indep-pairwise 50 5 0.5’. This involved analyzing SNP pairs within a window of 50, removing one SNP if LD exceeded 0.5, and then shifting the window by five SNPs and repeating the process.
The pruned set of 117 K SNPs served as a basis for calculating identity by descent (IBD). In order to detect first-degree relationships, the ‘PI_HAT’ parameter within the PLINK 1.9 software was used.
The obtained SNP data were compared with SNP profiles from an ongoing pedigree reconstruction study [73,74].
The ploidy level of SNP data was assessed using axiomFP.py software v 1.2 [75].

3. Results and Discussion

3.1. Identifying Redundancies Within the Collection

Among the genotyped 169 apple accessions and 11 reference cultivars, maintained within the CNCAGR collection at Donja Zelina, 55 redundancies in the form of synonyms, duplicates, or mislabeled accessions were detected (Supplementary File S1). Additionally, 13 homonyms (accessions with identical or very similar names but displaying a different SSR profile) were also found. The percentage of redundancies within the CNCAGR collection was around 31%, which is almost double the levels of redundancies reported by Urrestarazu et al. [76] (16%) among and within 14 large European apple collections. Similar or higher redundancy values have been reported for apple collections in the Netherlands [21] (32%), Spain [18] (47%), Italy [77] (34%), and France [78] (34%). Lower redundancy has been reported for Norwegian [2,79] and B&H [24,27] apple germplasm collections.
In order to investigate the genetic relationships, as well as display duplicates, synonyms, and homonyms, among the 180 examined apple accessions and reference cultivars, an UPGMA cluster analysis was performed. The analyses grouped all 180 samples into a dendrogram, with synonyms and duplicates positioning themselves on the same line (Figure 1). The cluster analyses revealed that the genotyped samples formed a number of clusters and subclusters displaying a complex network of relationships. Most notably, the eleven reference cultivars did not group tightly but were present in several different subclusters, which also shows that there is a certain degree of genetic diversity between the reference cultivars used and that they do not derive their origin from just a few parental cultivars used in hybridization, but a larger number of cultivars were used for their creation.
Considering the high level of potential mislabeling, as well as the relatively high number of synonyms and homonyms, there is a clear need for a comparison of obtained genetic profiles against available referent databases. This would enable proper genetic identification and assignment of the preferred name and MUNQ code to collected accessions.

3.1.1. Genetic Identity

Running the obtained SSR profiles against very extensive databases with microsatellite data on more than 2000 apple accessions resulted in a substantial number of matches (Supplementary File S1). Namely, 55 of the 114 non-redundant accessions are already present in the British and Irish collections and have been genotyped with the set of twelve SSR markers.
Molecular analyzes obtained data on duplicates, synonyms, and mislabeled accessions, which are presented in Table 1.
Considering that the CNCAGR collection contains numerous ancient, well-known foreign cultivars, some of which have been used extensively in breeding programs, the dispersion of reference cultivars is quite expected.
To identify redundancies within the collection as well as assess the genetic diversity and structure of apple germplasm currently being conserved in Norway, eight microsatellites were used in the genetic characterization of 181 apple accessions. Overall, 14 cases of synonym or possibly mislabeled accessions were identified, as well as several homonyms and duplicates within and among the analyzed collections [79]. A similar study, conducted in Central Italy on 175 accessions provided by 10 apple collections, mainly local cultivars, some of unknown origin, and well-known modern and ancient cultivars, relied on 19 SSRs [80]. The authors identified 25 duplicates, 9 synonyms, and 9 homonyms. Furthermore, as many as 37 unknown accessions were assigned to well-known local or commercial cultivars. Testolin et al. [81], who studied the genetic diversity of apple germplasm collected in Italy started with 469 molecular profiles, analyzed using 15 SSR markers, and allowed for the identification of the ‘truetotype’ genotypes among those maintained in multiple locations. The set of the remaining 234 accessions was further reduced to 132 unique profiles by removing 102 synonyms—that is, accessions with different names and the same molecular profile. A more recent SNP study from neighboring Bosnia and Herzegovina, conducted among 165 apple accessions from the IGR collection (Institute for Genetic Resources, Banja Luka), revealed 54 unique diploid and 18 unique triploid genotypic profiles [49]. Some of the accessions were obvious cases of mislabeling. For example, four accessions were genotypically identical to the rootstock ‘MM.106’, to which the accessions had presumably been grafted.

3.1.2. Ploidy Assessment Based on SSRs

The detection of more than two different alleles per locus, on at least one of the twelve analyzed loci, which was taken as an indication of a triploid state, was noted for 33 accessions or 29% of non-redundant genotypes. Although this approach is not a substitute for flow cytometry, a complete correlation between triploids detected with SSRs and flow cytometry has been reported by Pereira-Lorenzo et al. [16]. The percentage of putative triploids is comparable to values reported on Bosnian [24,27] (27%), Spanish, and Portuguese [82] (24%) germplasm but somewhat higher compared to the Turkish one (19%) [83]. A much lower occurrence of triploid in the apple germplasm collection has been reported for Norway [2,79] (12–13%). A higher frequency of triploids within Southern European apple germplasm compared to the Northern one, because of negative selection pressure on genotypes with pollination issues in a Northern climate, has previously been proposed by Kanlić et al. [84].

3.1.3. SSR Polymorphism

After removing all the redundancies, we were left with 114 apple accessions and 11 reference cultivars. The remaining genotypes were used to investigate the genetic diversity of the apple germplasm maintained at the CNCAGR collection, as well as to examine its genetic structure.
In this study, 12 primer pairs amplified 184 distinct alleles, or an average of 15.33 alleles per locus among all 125 apple accessions and reference cultivars (Table 2). Removing the reference cultivars from the analyses resulted in the reduction of only two alleles. The average number of alleles per SSR locus reported here is higher than the values published from two Norwegian apple diversity studies with comparable numbers of apple accessions: 158 unique genotypes (11.9) [79] and 171 accessions (14.3) [2]. A slightly lower value for this parameter has been reported by Marconi et al. [80] (14.6), who investigated 175, mostly Italian, apple accessions provided by 10 apple collections, using 19 SSR markers. In the available literature, higher values, such as 18.5 reported by van Treuren et al. [21], 16.7 by Urrestarazu et al. [18], 16.8 by Liang et al. [77], 19.5 by Lassois et al. [78], up to 23.06 by Urrestarazu et al. [76], and 30.7 by Venison et al. [85] have been reported. However, it is worth noting that these studies examined hundreds and in some cases thousands of apple accessions originating from numerous different countries.
A notable difference between the parameters number of alleles (15.17) and number of effective alleles (6.43) was detected among the genotyped CNCAGR accessions. This large difference generally indicates a high presence of rare alleles within an apple germplasm. Furthermore, a high presence of rare alleles can indicate that a large portion of the investigated germplasm has not been extensively used in breeding programs [2]. On the other hand, the difference between the total number and effective number of alleles among the reference cultivars, most of which are widely used in breeding programs, was minimal (6.33 versus 5.18).
The gene diversity calculated for all loci among the 125 apple accessions was 0.82, ranging between 0.69 for CH01h10 and 0.91 for CH02c11 (Table 2). The calculated value is only slightly lower than the highest reported value of 0.83 [76,77] or identical to values reported by several previous studies on much larger sets of samples, 0.82 [18,78,82].
The stark differences in values for the average number of alleles per SSR locus and gene diversity between the germplasm accessions from the Croatian National Clonal Germplasm Repository and the reference cultivars can be viewed as a consequence of the discrepancy in sample size (114 versus 11 genotypes).

3.1.4. Genetic Structure

In order to examine the underlying genetic structure of the apple germplasm maintained at the CNCAGR collection, a Bayesian analysis was implemented on 114 accessions and 11 reference cultivars. The subsequent ΔK analyses [86] revealed maximum values for K = 2, as well as smaller peaks for K = 4, K = 7, and K = 9 (Figure 2).
The two genetic clusters (GCs) inferred for K = 2 contained 53 (GC1) and 45 (GC2) accessions, respectively, that were assigned with a probability of membership qI > 80% (Supplementary File S2; Figure 3). The remaining 27 genotypes were designated as admixed. All the 11 reference cultivars were assigned to GC1, together with ‘Jonathan’ and numerous old West European, British, and American cultivars (‘Staymanred’, ‘Wagener’, ‘London Pippin’, ‘Belle de Boskoop’, ‘James Grieve’, and ‘Cox’s Orange Pippin’). Another accession that was grouped in GC1 was ‘Lijepocvjetka’, previously reported by Gaši et al. [27] to be a synonym of ‘Yellow Bellflower’. The second genetic cluster was characteristic for its absence of the reference cultivar but also the presence of well-known traditional apple accessions from Bosnia and Herzegovina (‘Senabija’, ‘Budimka’, ‘Bihorka’ ‘Prijedorska zelenika’, and ‘Rozmarinka’), some of which were introduced during the reign of the Ottoman empire over the country [48]. However, it is important to note that GC2 also contained old, foreign cultivars such as ‘White Transparent’, ‘Gruner Stettiner’, ‘Stark Earliest’, ‘Peasgoods’, ‘Mantet’, ‘Kronprinz Rudolf’, ‘Close’, ‘Melba’, ‘Lesans kalvil’, and ‘Adamčica’/’Pomme étoilée’.
In the K = 4 scenario, only 26 of the 125 genotypes were classified into any of the four genetic clusters with a probability of membership above 80% (Figure 3). Furthermore, the GC2 and GC4 were devoid of any accessions, while GC1 contained 13 samples, and GC3 contained 13. The remaining 99 accessions are designated as admixed. Both clusters included reference apple cultivars. A similar situation was noted for K = 7, with only 23 accessions grouped into one of the seven genetic clusters with a probability of membership above 80%. GC1, GC2, GC3, and GC5 were without any accession, while the GC4 contained eight accessions, GC6 contained ten accessions, and GC7 contained five accessions. The remaining 102 accessions were admixed. Clusters GC4 and GC7 included reference apple cultivars. Cluster GC7 was characteristic of the absence of a reference cultivar, but also of the presence of known traditional cultivars of apples from B&H (‘Budimka’, ‘Senabija’ i ‘Bihorka) [24,28]. The K = 9 analyses revealed that only 16 samples were assigned to a cluster with the previously mentioned likelihood probability of belonging above 80%. GC2, GC3, GC4, GC6, GC7, and GC9 were without any accessions, while the GC1 contained five accessions, GC5 contained seven accessions, and GC8 contained four accessions. The remaining 109 accessions are marked as mixed. Clusters GC1 and GC5 included reference apple cultivars. Cluster GC8 was characteristic of the absence of a reference cultivar but also of the presence of known traditional cultivars of apples from B&H (‘Budimka’, ‘Senabija’, and ‘Bihorka’).
Considering the obtained results, it is possible to conclude that the genetic structure within the examined samples is most pronounced for K = 2. In order to further examine the relationship between these two genetic clusters, a factorial correspondence analysis (FCA) was performed. The FCA (Figure 4) displayed a very small separation between the two GCs, which was unsurprising considering that both groups contained numerous old, foreign cultivars from Western Europe and North America. Furthermore, the FCA graph clearly showed that the GC2 was much more heterogeneous than GC1—also unsurprising, considering that this group included accessions introduced from the east during the expansion of the Ottoman empire.
An analysis of molecular variance (AMOVA) carried out on the two GCs revealed that a significant part of the variance (5.8%; p < 0.001) was attributed to differences between GCs, indicating small but significant genetic differentiation between these groups. For comparison, the genetic differentiation among the genetic clusters identified, using a Bayesian genetic structure analysis on the neighboring B&Hs apple germplasm, have ranged from 7.7% to 13% [27,79]. The lower differentiation noted here between the genetic clusters, using both AMOVA and FCA, is in line with the significant introgression of foreign cultivars in the Croatian apple germplasm revealed through the previously presented database matches. Namely, more than 40% of the total number of researched accessions are imported foreign cultivars.

3.2. Pomological Characterization

In order to investigate the pomological variability of 48 unique apple accessions from the Croatian National Clonal Germplasm Repository at Donja Zelina, a three-year study was carried out on eleven pomological traits (fruit weight—FW, fruit height—FH, fruit width—FW, fruit shape index—FSI, length of stalk—LST, width of stalk—WST, fruit hardness—FH, percentage of soluble solids—PSS, total acids—TAs, PSS and TA ratio—PSM/TA, pH value—pH). Simultaneously, the same analyses were performed on the fruit collected from the 11 reference cultivars, maintained at the same site. The obtained values (Supplementary File S3) were used for a principal component analysis (PCA), conducted in order to investigate the relationships between the 48 unique apple accessions that are not found in the SSR bases, as well as 11 reference cultivars (Figure 5). Overall, there was a substantial overlap between the number of accessions and reference cultivars when it came to the first two main components. Individual accessions were separated into special groups outside the ellipse, which represents a 95% confidence limit for individual group membership. The following unique accessions are separated into a special group (Table 3).
In the biplot, individual properties are shown as vectors, and their direction indicates an increase in the value of genotypes for a particular property located in that direction. The length of the vectors reflects their overall variability as determined by principal component analysis, which means that a longer length indicates a greater degree of variability. The proximity of individual original properties reflects their degree of mutual correlation, which means that the closer the property vectors are, the more correlated the properties are. The aforementioned separation shows that in terms of dominant original properties from this combination of main components, individual members of one and the other group differ starkly. The graph shows that there is a high positive correlation between the weight and width of the fruit. The properties in the analysis of the main components of the maximum value for the characterizing vectors were the weight, height, and width of the fruit and the fruit shape index, and the lowest values were seen in the pH, soluble dry matter ratio, total acids, and soluble dry matter content. Based on the obtained results, the researched germplasm shows an exceptional diversity of pomological properties.
The two first principal components accounted for over 50% of the overall variance. Similar values on accumulative variance have been reported by Gaši et al. [26] (48.86%), who analyzed 18 phenotypic characteristics within the B&H apple germplasm, as well as international reference cultivars. Out of the total of 18 properties, 7 of the first properties were analyzed in more detail through their inherent values and the share that these properties had in the total variance. The individual influence of the original properties through the values of the characteristic vectors on the newly formed properties was also analyzed. The results of the analysis of the main components indicate that within the first main component, which has a higher share of total variance through dominant peculiar vectors, the most significant properties are those affecting the appearance and weight of apple fruit (Table 4).

3.3. Genetic Identity and Pedigree Reconstruction

3.3.1. Comparison of SSR and SNP Marker Systems

In order to assess the advantage of a high-resolution marker system, such as SNPs, compared to low-resolutions markers, such as SSRs, a subset of 23 unique apple accessions and eight reference cultivars were genotyped using the 480K Affymetrix Axiom SNP array (Thermo Fisher Scientific, Waltham, MA, USA) (Supplementary File S4). The randomly chosen, unique CNCAGR accessions and a subset of reference cultivars were limited to 31 because of the extreme disparity in genotyping costs between the microsatellite and the mentioned SNP array.
The possibility to compare the obtained SNP profiles with genotypes in an ongoing pedigree reconstruction study [73,74] enabled additional identification of international synonyms. This comparison revealed the proper identity of 5 of the 24 apple accessions deemed unique according to SSR data. Namely, ‘Prinčevka’ was identical to the French cultivar ‘Conique’, ‘Galetina’ to a modern apple cultivar ‘Enterprise’, ‘Carevka’ to the old German cultivar ‘Oberdiecks Renette’, and ‘Kristalka’ to another old German cultivar ‘Schöner von Nordhausen’, while the identity of ‘Florianer Rosmarin’ was confirmed.
A major advantage of the high-resolution marker system is the ability to use the obtained genomic data to reconstruct extensive pedigree networks [38,40]. This approach, together with the use of the SNP profiles from the aforementioned, ongoing Malus pedigree reconstruction study, revealed that one of the parents of ‘Adamovka petrovka’ was the rootstock M8. The accession ‘Ivanlija’ is an offspring of two German germplasm accessions, ‘Striesselapfel’ and ‘Kleiner_Fleiner_1’. One of the parents of the ‘Rajska’ accession was the German ‘Kasseler Renette’. Furthermore, the pedigree reconstruction of ‘Bijela repica’ accession revealed ‘Weisser Wintertaffetapfel’ as a possible grandparent and other closest relatives as German and Southeastern European cultivars. Similarly, the closest relatives of ‘Klopčenka’ are mostly Southeastern European cultivars but also German, French, and Italian cultivars. This finding indicates a hybridization between apple germplasm introduced from the east during the Ottoman Empire and the one introduced later during the Austro–Hungarian rule of the region. This pattern of introduction was previously proposed by Gaši et al. [24] for the apple germplasm of the neighboring Bosnia and Herzegovina. On the other hand, the closest relatives of ‘Tvrdika’ and ‘Žuta zimska’ are Italian and Southeastern European cultivars. Additionally, an Italian accession was revealed to be the parent of ‘Šiljika’. Some parts of the Croatian territory (Istria, Primorje, part of Dalmatia, and part of the islands) were under the control of the Republic of Venice for several centuries, so it is likely that during that period some Italian cultivars were introduced into this area, which spread over time to the rest of the territory of Croatia. There is another possibility for the question of how Italian cultivars were introduced into the territory of continental Croatia, or more precisely Slavonia, namely that at the end of the 19th century Italians from northeastern Italy immigrated to the territory of Western Slavonia in villages in the vicinity of Pakrac and Lipik, and to a lesser extent to the territory of Nova Gradiška and Požega (the reasons for their arrival are socioeconomic) [87]. Interestingly enough, the ‘Slačica’ accession displayed close relatedness exclusively with Southeastern European cultivars, indicating that, in spite of widespread hybridization, part of the southeastern germplasm remained distinct.

3.3.2. Ploidy Assessment Based on SNPs

As previously mentioned, microsatellite profiles have been widely used in apple accession ploidy assessment [40,76]. However, the most reliable method for determining the ploidy in Malus germplasm entails the use of flow cytometry [88]. There are some downsides with this approach, as it requires sampling of fresh plant tissue during the vegetation period and demands specialized equipment. In apple germplasm studies that rely on SNP arrays, the obtained genomic data can be used to generate B allele frequency (BAF) plots, which indicate the level of ploidy among accessions with a high degree of certainty [41]. For instance, Gilpin et al. [37] determined the triploid state of an accession within Norwegian germplasm labeled as ‘Gravenstein’, using B allele frequency (BAF) plots. The ancient North European cultivar ‘Gravenstein’ is one of the most well-known triploid apples. In a preceding study on the Norwegian apple germplasm, Gaši et al. [79] failed to discover a third allele among eight SSR loci for three of the four apple accessions labeled as ‘Gravenstein’. This could also be due to mislabeling, since only two of the four accessions labeled as ‘Gravenstein’ displayed an identical SSR profile, and one of them displayed the presence of a third allele and was thus deemed a triploid. Nonetheless, it would be useful to compare the results of ploidy assessment based on SSRs and SNPs among the selected subset of CNCAGR accessions and reference cultivars.
Unfortunately, the ploidy assessment protocol proposed by Chagné et al. [41] is only applicable on the medium-density Illumina Infinium® 20K apple SNP array [34]. Thus, a new software axiomFP.py v 1.2 [75] was used in order to diagnose the ploidy level on SNP data obtained from the Axiom® Apple 480 K SNP array (Figure 6). Overall, among the 31 CNCAGR accessions and reference cultivars, both the SSR and SNP data identified the same six genotypes as triploids (Supplementary File S4); therefore, the concordance between these two approaches was 100%.
Additionally, the analyses of international cultivars genotyped on the 480K array resulted in cluster plots which were in complete concordance with known ploidy data such as for diploids ‘Braeburn’, ‘Elstar’, ‘Fuji’, ‘Pinova’, ‘Golden Delicious’, ‘Gala’, and ‘Topaz’, as well as triploid ‘Jonagold’.

4. Conclusions

The results obtained through the use of two marker systems revealed a significant number of synonyms, duplicates, and homonyms, as well as the true identity of a large number of accessions, currently maintained at the Croatian National Apple Germplasm Bank. Nonetheless, many of the accessions can be considered unique, and the results of the pomological characterization indicated that this germplasm contains valuable traits of interest for future breeding programs. The data presented here will ensure a more sustainable future for the CNAGB collection, as well as stimulate the utilization of the Croatian apple germplasm.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15010113/s1, Supplementary File S1: Results table with used loci; Supplementary File S2: Results from the four Bayesian genetic structure analyses; Supplementary File S3: Pomological traits and PC values; Supplementary File S4: Ploidy and pedigree; Supplementary File S5: List of accessions and reference cultivars.

Author Contributions

D.Č., A.K., M.S.B., P.V., S.Š. and F.G.; investigation, D.Č., A.K. and F.G.; resources, P.V., M.S.B. and F.G.; data curation, A.K., D.Č., M.S.B. and F.G.; writing—original draft preparation, D.Č., A.K. and F.G.; writing—review and editing, D.Č., A.K., M.S.B. and F.G.; visualization, A.K.; supervision, S.Š.; project administration, F.G. and M.S.B.; funding acquisition, P.V., M.S.B. and F.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by National Program for Conservation and Sustainable Use of Plant Genetic Resources for Food and Agriculture in Republic of Croatia by Ministry of Agriculture, Forestry and Fisheries (Proc. No. 2016, 2017, 2018/K842018).

Data Availability Statement

The data presented in this study are available upon request from the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. UPGMA cluster analysis based on polymorphisms of SSR data for 169 apple accessions and 11 reference cultivars, maintained at the Croatian National Clonal Apple Germplasm Repository, using Jaccard’s similarity coefficient.
Figure 1. UPGMA cluster analysis based on polymorphisms of SSR data for 169 apple accessions and 11 reference cultivars, maintained at the Croatian National Clonal Apple Germplasm Repository, using Jaccard’s similarity coefficient.
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Figure 2. Plot of delta K values from the structure analyses based on SSR data obtained on 114 apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository. The blue line represents the calculated Delta K values for each K, while the red vertical line indicates the optimal number of clusters (K = 2), corresponding to the highest Delta K value.
Figure 2. Plot of delta K values from the structure analyses based on SSR data obtained on 114 apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository. The blue line represents the calculated Delta K values for each K, while the red vertical line indicates the optimal number of clusters (K = 2), corresponding to the highest Delta K value.
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Figure 3. Bar plot of the results from the four (K = 2, K = 4, K = 7, and K = 9) Bayesian genetic structure analyses of 114 apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository. Different colors help diferentiate between clusters.
Figure 3. Bar plot of the results from the four (K = 2, K = 4, K = 7, and K = 9) Bayesian genetic structure analyses of 114 apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository. Different colors help diferentiate between clusters.
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Figure 4. Factorial correspondence analysis (FCA) of SSR data for two defined genetic clusters calculated using structure [60] (only genotypes with the likelihood of membership to individual GC above 80% are included in the analyses).
Figure 4. Factorial correspondence analysis (FCA) of SSR data for two defined genetic clusters calculated using structure [60] (only genotypes with the likelihood of membership to individual GC above 80% are included in the analyses).
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Figure 5. PCA plot (PC1 and PC2) estimated from the correlation matrix of 11 pomological traits measured during a three-year trial (2021–2023) on 48 unique apple accessions (U) and 11 international, reference cultivars (I), maintained within the Croatian National Clonal Apple Germplasm Repository (fruit weight—FW, fruit height—FH, fruit width—FW, fruit shape index—FSI, length of stalk—LST, width of stalk—WST, fruit hardness—FH, percentage of soluble solids—PSS, total acids—TAs, PSS and TA ratio—PSM/TA, pH value—pH).
Figure 5. PCA plot (PC1 and PC2) estimated from the correlation matrix of 11 pomological traits measured during a three-year trial (2021–2023) on 48 unique apple accessions (U) and 11 international, reference cultivars (I), maintained within the Croatian National Clonal Apple Germplasm Repository (fruit weight—FW, fruit height—FH, fruit width—FW, fruit shape index—FSI, length of stalk—LST, width of stalk—WST, fruit hardness—FH, percentage of soluble solids—PSS, total acids—TAs, PSS and TA ratio—PSM/TA, pH value—pH).
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Figure 6. Plots generated using axiomFP.py: (a) A plot showing three peaks indicating a diploid state of the accession ‘Tvrdika’; (b) a plot showing four peaks indicating a triploid state of the accession ‘Orahovačka’.
Figure 6. Plots generated using axiomFP.py: (a) A plot showing three peaks indicating a diploid state of the accession ‘Tvrdika’; (b) a plot showing four peaks indicating a triploid state of the accession ‘Orahovačka’.
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Table 1. List of duplicates, synonyms, and mislabeled accessions.
Table 1. List of duplicates, synonyms, and mislabeled accessions.
Accession NameIdentification ResultMethod of Identification
Duplicates‘Bijela zimska rebrača’‘Leathercoat Russet’SSR
‘Bisera’‘Mantet’SSR
‘Carska reneta’‘Bloody Butcher’SSR
‘Cox’s Orange 1’‘Leathercoat Russet’SSR
‘Crvena caklenka’‘Jonatan’SSR
‘Crvena kožara’‘Crveni Boskop’SSR
‘Crvena zimska’‘Jonatan’SSR
‘Crvenka’‘Danciška rebrača’SSR
‘Dulibe velika’‘Bietigheimer’, ‘San Giovanni’SSR
‘Francuska kožara’‘Crveni Boskop’SSR
‘Gospojinska’‘Grafenštajn’SSR
‘Imperica’‘Jonathan’SSR
‘Jakobovka’‘Bietigheimer’, ‘San Giovanni’SSR
‘Ječmenika 151’‘Mantet’SSR
‘Jesenska žuta 103’‘Peasgood’SSR
‘Kanada B’‘Kanada’SSR
‘Kraljevčica kasna’‘Grafenštajn’SSR
‘Lojzendorf’‘Roter Herbstkalvill’SSR
‘Mađarica’‘Calville des Femmes’SSR
‘Mirišljava Budići’‘Danziger Kantapfel’SSR
‘Parkerov peping’‘Leathercoat Russet’SSR
‘Petrovača žuta’‘Bjeličnik’SSR
‘Prsnika’‘Lijepocvjetka’SSR
‘Rebrača Brinje’‘London peping’SSR
‘Slatka srčika’‘Crveni Boskop’SSR
‘Slavonska srčika’‘Crveni Boskop’SSR
‘Slavonska srčika Veić’‘Zeleni štetinec’SSR
‘Slavonska srčika-Milić’‘Zeleni štetinec’SSR
‘Slovenka’‘Carević Rudolf’SSR
‘Srčika 1’‘Zeleni štetinec’SSR
‘Srčika 2’‘Zeleni štetinec’SSR
‘Stara šara’‘Bietigheimer’, ‘San Giovanni’SSR
‘Starkova’‘Starkova najranija’SSR
‘Svijetla musulja’‘Leathercoat Russet’SSR
‘Šampanjka B’‘Šampanjka’SSR
‘Šarulja’‘Baumanova reneta’SSR
‘Winston’‘Leathercoat Russet’SSR
‘Zelenika 35’‘Krupnara’SSR
‘Zelenika 109’‘Krupnara’SSR
‘Žuta jesenska’‘Bloody Butcher’SSR
Synonyms‘Bijela ribnjača’‘Batulenka’, ‘Turkova’SSR
‘Car Aleksandar’‘Kardinal’SSR
‘Carevka’‘Oberdikova reneta’SSR/SNP
‘Crvena djevojačka’‘Framboise’, ‘Malinovača’SSR
‘Div jabuka’‘Calville des Femmes’, ‘Mađarica’SSR
‘Gospojinka B’‘Bloody Butcher’SSR
‘Funtača’‘Bramley’s Seedling’SSR
‘Irmgard’‘Horneburger Pfannkuchen’SSR
‘Kablarka’‘Galloway Pippin’SSR
‘Kamenica’‘Jacquin’, ‘Muškatnica’SSR
‘Kristalka’‘Schoner von Nordhausen’SSR/SNP
‘Krvavka’‘Danziger Kantapfel’SSR
‘Lopatičanka’‘Molleskov’SSR
‘Lovrenčovka’‘Grafenštajn’SSR
‘Lubeničarka’‘Bloody Ploughman’SSR
‘Meglena’‘Dugata’SSR/SNP
‘Pisanika ranka’‘Close’SSR
‘Prinčevka’‘Conique’SSR/SNP
‘Siva jesenska’‘Learthercoat Russet’SSR
‘Slatka’‘Klanferica’SSR
‘Umačka’‘Kinrei’SSR
‘Vrtna’‘Signe Tillisch’SSR
‘Zeleni štetinec’‘Srčika’SSR
‘Zelenika’‘Rhode Island Greening’SSR
‘Žuta Brinje’‘Blajnhajmska reneta’SSR
‘Željeznjača’Majdofija’SSR
Mislabeling of accessions‘Blatnjača’‘MM 106’SSR/SNP
‘Galetina’‘Enterprise’SSR/SNP
‘Grofova’‘Mutsu’SSR
‘Harbertova reneta ‘‘Annie Elizabeth’SSR
‘Ječmenika’‘Julyred’SSR
‘Kasler reneta’‘Harbertova reneta’SSR
‘Kraljevača’‘Prima’SSR
‘Krivopeteljka’‘Bobovec’SSR
‘Ljetni špincl’‘Mollie’s Delicious’SSR
‘Slična Božićnici’‘Idared’SSR
‘Šarlamovski’‘Budimka’SSR
‘Zelenika 77’‘MM 106’SSR
‘Žrnovnička jabuka’‘Mašanka’SSR
Table 2. Number of detected alleles, number of effective alleles, and gene diversity calculated for 114 nonredundant apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository.
Table 2. Number of detected alleles, number of effective alleles, and gene diversity calculated for 114 nonredundant apple accessions and 11 reference cultivars, maintained within the Croatian National Clonal Apple Germplasm Repository.
All (n = 125)Accessions (n = 114) Reference (n = 11)
LocusNo. of AllelesNo. of Effective AllelesGene Diversity HeNo. of AllelesNo. of Effective AllelesGene Diversity HeNo. of AllelesNo. of Effective AllelesGene Diversity He
CH04c07187.980.87187.760.8778.10.88
CH01h10113.280.69113.230.6943.480.72
CH01h01156.670.85156.880.8564.830.80
Hi02c07114.490.78114.560.7853.820.74
CH01f02268.30.88258.550.8876.690.85
CH01f03b134.680.79134.540.7886.70.85
GD12144.330.77144.340.7743.630.73
GD147166.590.85166.90.8663.440.71
CH04e05174.340.77174.460.7872.830.65
CH02d08167.30.86157.20.8678.280.88
CH02c111610.60.911610.930.9195.440.82
CH02c09117.610.87117.80.8764.90.80
Mean15.336.350.8215.176.430.836.335.180.79
Table 3. Unique accessions that were separated from the reference varieties into a special group.
Table 3. Unique accessions that were separated from the reference varieties into a special group.
Accession NameGroup
‘Adamčica’1
‘Adamovka petrovka’2
‘Blatnjača’5
‘Carevka’6
‘Cigančica’7
‘Crvena ribnjača’8
‘Čebulka’9
‘Čelenika ljetna’10
‘Dogaja’11
‘Galetina’16
‘Golubica’17
‘Grinštantin’18
‘Hrapava zvonasta’19
‘Hrapavka rana’20
‘Ivanlija’21
‘Kristalka’25
‘Križara’26
‘Ljetni mošancelj’28
‘Muškotelka’31
‘Prijedorska zelenika’33
‘Prinčevka’34
‘Rožmarinka’36
‘Senabija’39
‘Slačica’40
‘Slavonska srčika-Karolina’41
‘Slavonska srčika-Podravina’42
‘Slična Božićnici’43
‘Šiljika’44
‘Špička’45
‘Braeburn’49
Table 4. Eigenvalues, eigenvectors, and accumulated variance associated with the eleven principal components (PCs) estimated from the correlation matrix of 11 pomological traits measured during a three-year trial (2021–2023) on 48 unique apple accessions (U) and 11 international reference cultivars (I), maintained within the Croatian National Clonal Apple Germplasm Repository.
Table 4. Eigenvalues, eigenvectors, and accumulated variance associated with the eleven principal components (PCs) estimated from the correlation matrix of 11 pomological traits measured during a three-year trial (2021–2023) on 48 unique apple accessions (U) and 11 international reference cultivars (I), maintained within the Croatian National Clonal Apple Germplasm Repository.
PC1PC2PC3PC4PC5PC6PC7
FWG−0.44−0.190.18−0.24−0.18−0.060.11
FL−0.37−0.380.05−0.290.190.030.05
FW−0.43−0.130.29−0.2−0.25−0.050.13
FSI0.02−0.41−0.34−0.210.670.15−0.1
LST−0.16−0.28−0.510.08−0.44−0.18−0.53
WST−0.110.410.39−0.320.250.07−0.61
FH0.040.33−0.31−0.490.06−0.710.1
PSM0.120.21−0.33−0.54−0.290.590.15
TA−0.380.31−0.250.12−0.020.29−0.12
PTR0.41−0.230.16−0.28−0.190.020.19
pH0.35−0.290.24−0.19−0.210.01−0.47
Eigen value3.932.061.491.320.880.60.45
Component variance (%)35.7318.7513.5413.038.025.464.05
Cumulative variance (%)35.7354.4768.0180.0488.0693.5297.57
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Čiček, D.; Konjić, A.; Skendrović Babojelić, M.; Vujević, P.; Šimon, S.; Gaši, F. Genetic Uniqueness and Pomological Diversity Among the Apple Accessions Maintained Within the Croatian National Clonal Germplasm Repository. Agronomy 2025, 15, 113. https://doi.org/10.3390/agronomy15010113

AMA Style

Čiček D, Konjić A, Skendrović Babojelić M, Vujević P, Šimon S, Gaši F. Genetic Uniqueness and Pomological Diversity Among the Apple Accessions Maintained Within the Croatian National Clonal Germplasm Repository. Agronomy. 2025; 15(1):113. https://doi.org/10.3390/agronomy15010113

Chicago/Turabian Style

Čiček, Danijel, Almira Konjić, Martina Skendrović Babojelić, Predrag Vujević, Silvio Šimon, and Fuad Gaši. 2025. "Genetic Uniqueness and Pomological Diversity Among the Apple Accessions Maintained Within the Croatian National Clonal Germplasm Repository" Agronomy 15, no. 1: 113. https://doi.org/10.3390/agronomy15010113

APA Style

Čiček, D., Konjić, A., Skendrović Babojelić, M., Vujević, P., Šimon, S., & Gaši, F. (2025). Genetic Uniqueness and Pomological Diversity Among the Apple Accessions Maintained Within the Croatian National Clonal Germplasm Repository. Agronomy, 15(1), 113. https://doi.org/10.3390/agronomy15010113

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