Next Article in Journal
Cover Crops as Reservoirs for Young Vine Decline Pathogens
Next Article in Special Issue
Identification, Interaction, Expression, and Function of QTLs on Leaf Numbers with Single-Segment Substitution Lines in Rice
Previous Article in Journal
Effect of Arbuscular Mycorrhizal Fungal Seed Coating on Grain Protein and Mineral Composition of Old and Modern Bread Wheat Genotypes
Previous Article in Special Issue
Mechanism of Early Flowering in a Landrace Naked Barley eam8.l Mutant
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 12
Issue 10
10.3390/agronomy12102423
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Diversity of Polish Oat Cultivars with a Glance at Breeding History and Perspectives

by
Aneta Koroluk
1,
Edyta Paczos-Grzęda
1,*,
Sylwia Sowa
1,
Maja Boczkowska
2,3 and
Joanna Toporowska
1
1
Institute of Plant Genetics, Breeding and Biotechnology, University of Life Sciences in Lublin, 20-950 Lublin, Poland
2
Plant Breeding and Acclimatization Institute, National Research Institute, 05-870 Radzików, Poland
3
Center for Biological Diversity Conservation in Powsin, Polish Academy of Sciences Botanical Garden, 02-973 Warszawa, Poland
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(10), 2423; https://doi.org/10.3390/agronomy12102423
Submission received: 29 August 2022 / Revised: 29 September 2022 / Accepted: 4 October 2022 / Published: 6 October 2022
(This article belongs to the Special Issue Genetics Research and Molecular Breeding of Crops)
Browse Figures
Versions Notes

Abstract

:
During 120 years of Polish breeding of oats (Avena sativa L.), dozens of new varieties have been developed. This study was undertaken to investigate the diversity and population structure of 72 Polish oat cultivars released since 1893. The analysis was based on pedigree data as well as ISSR and REMAP marker polymorphisms. The ancestry of common oat cultivars was traced back to 124 cultivars, breeding lines, and landraces. The five most common progenitors were ‘Markische Landsorte’, ‘selection from Ligowo oat’, ‘Fransk Svarthavre’, ‘Blanche de Siberie’, and ‘selection from Schleswig-Holstein landrace’. We found that at least one of them was present in 78% of analysed objects. The studied cultivars were assigned to four groups according to the period of their breeding (before 1945, 1945–1969, 1970–2000, and after 2000) and six groups according to the breeding company (Strzelce Plant Breeding Company, DANKO Plant Breeding, Station of Plant Breeding in Rogaczewo, Małopolska Plant Breeding Company, Station of Plant Breeding in Borów, and other). A decrease in observed heterozygosity within the groups was observed only in the postwar period (1945–1969). As a result of breeders’ efforts and extensive crosses with foreign materials initiated in 1970 and 1980, new alleles were provided to the oat gene pool. The highest number of new varieties came from the Strzelce and DANKO breeding companies. There were no significant differences between modern cultivars derived from different breeding companies. However, very early breeding centres functioning before 1945 had significantly different materials from the modern ones. The population genetic structure of the studied group of cultivars appeared to be quite simple. It was shown that their genetic makeup consisted of two or three distinct gene pools, depending on the method of polymorphism assessment. The performed research proved that Polish oat breeding using traditional breeding methods—such as selection or intraspecific and interspecific crosses—although focused on improving yield and tolerance to biotic and abiotic stress, did not significantly narrow the oat gene pool and has been releasing cultivars that are competitive in the European market.

1. Introduction

Within the genus Avena L., the self-pollinating allohexaploids A. sativa L. and A. byzantina C. Koch., (2n = 6x = 42)—known as common and red oats, respectively—are the main cultivated oat species [1]. In some regions, the diploid A. strigosa Schreb., called bristle oats, and the tetraploid A. abyssinica Hochst., known as Ethiopian oats, are also cultivated [2,3]. The cultivated forms of marginal importance are the diploid species A. nuda L., A. brevis Rotch., and A. hispanica Ard. [2], along with the tetraploid A. barbata Pott. ex link [4].
Avena sativa L. appeared in cultivation several thousand years later than wheat and barley [5]. Initially, it was a weed that polluted these crops [6]. The importance of oats increased as a result of migration from Southeast Asia toward Northern European regions with a cold and humid climate in the late Bronze Age [7,8]. Non-shattering oat mutants emerged and, as they were less demanding, cold-resistant, and well-adapted, they began to displace wheat, becoming cultivated over time [9]. The area of oat cultivation has continuously declined over the past few decades. This can be partially attributed to the increase in major crops such as maize or wheat. However, in recent years, the demand for oats for human consumption has increased, particularly because of their dietary benefits [10]. Today, the common oat is the seventh most economically important cereal, after maize, wheat, rice, barley, sorghum, and millet [11]. The grain production quantity, after a significant (i.e., almost twofold) drop in the 1980s and 1990s, has been quite stable over the last 20 years (2000–2021), oscillating around 25 million tonnes. Due to low environmental requirements, including cool and wet climates and soils with low fertility, oats are cultivated worldwide [1]. Poland is among the three largest oat-producing countries, after Canada and the Russian Federation. The other important oat suppliers—producing about 1 million tonnes per year—are Spain, Finland, Australia, the United Kingdom, and the United States [11]. Formerly, oats were primarily a fodder cereal; therefore, the basic direction of breeding was to increase the yield and improve the fodder value of grain with a low share of husk and high protein and fat [12]. The introduction of naked oat varieties with a low fibre content increased the attractiveness of growing this species as a fodder plant for monogastric animals [13]. Currently, attempts are being made to create varieties that are resistant to biotic stresses and can easily adapt to abiotic stresses and climate change.
Oat breeding in Poland began in the late 19th century, around the same time as oat breeding in Germany, the United Kingdom, and Sweden [14]. Before the First World War and during the interwar period, seed companies and private breeders were involved in breeding oats. The first Polish varieties of oat were ‘Sobieszyński’, ‘Najwcześniejszy Niemierczański’, and ‘Teodozja’. The oldest printed description of breed cultivars concerns the ‘Sobieszyński’ oat, developed by professor Antoni Sempołowski in Sobieszyn in 1893 [15]. Before the First World War and in the interwar period in Poland, mainly domestic cultivars and landraces were cultivated. During the Second World War, almost all achievements of Polish breeders were lost, and after the war, for many years, the register of oat varieties in Poland was based on prewar entities from the 1920s and German varieties cultivated as indemnity for deeds executed during the war. Additionally, immediately after the war, Polish varieties selected from the German ones were created, i.e., ‘Przebój I’, ‘Przebój II’, and ‘Proporczyk’, selected from ‘Flämingsgold’, ‘Flämingstreu’, and ‘Findling’, respectively. At the end of the 1960s, as in the case of other spring cereals, foreign oat varieties were imported, i.e., ‘Flamingsweiss II’, ‘Diadem’, and ‘Leanda’. Because of the lack of national materials, foreign cultivars and lines were included in the Polish breeding programs. It took over 30 years for Polish oat breeding to recover from the damage caused by the war, and new Polish cultivars did not begin to enter the market until 1977 [16]. From 1979, better and better Polish varieties were entered into the register, among which ‘Dragon’, ‘Komes’, and ‘Markus’ gained the greatest importance in cultivation in the 1980s. The last two decades of the 20th century were marked by numerous successes in oat breeding in Poland. Many very good varieties were developed at the plant breeding stations in Borów, Choryń, Polanowice, Wielopole, and Strzelce. Currently, oat breeding is conducted by three companies at Choryń, Polanowice, and Strzelce.
Plant breeders usually source populations for cultivar development from crosses within regionally adapted germplasm with good agronomic performance. The exchange of lines and cultivars between breeders is common but occurs mainly within certain regions and is rare between continents. As a consequence, European spring oat breeding programs may be reliant on a relatively narrow gene pool for agronomic and quality traits [17]. Over the years of selection, some valuable alleles have been lost, so modern breeding seeks new germplasm in wild ancestors, obsolete cultivars, and landraces [18]. New sources of genes could be useful in the future; therefore, a thorough knowledge of cultivars’ genetic diversity and relatedness is highly important for breeders. Molecular markers are so far the most effective tool widely used to study genetic diversity in the Avena genus. Paczos-Grzęda [19] compared RAPD (randomly amplified polymorphic DNA) and simplified PstIAFLP (amplified fragment length polymorphism) in the diversity evaluation of 19 common oat (A. sativa L.) cultivars registered in Poland in the years 1984–2004. Paczos-Grzęda and Bednarek [20] performed a comparative analysis of hexaploid Avena species (A. sativa L., A. fatua L., and A. sterilis L.) using the REMAP (retrotransposon–microsatellite-amplified polymorphism) and ISSR (inter-simple-sequence repeats) methods, and concluded that both techniques were informative enough to differentiate between the species and generated reliable molecular markers for the diversity assessment. ISSR, RAPD, and AFLP were also used by Boczkowska et al. [21] to evaluate the genetic diversity of 23 primary cultivars of common oat bred in Poland before 1939. Comparative analysis of the three molecular markers’ systems showed that the set of ISSRs was the most efficient, highly reproducible, and had a relatively low cost. Moreover, only ISSR showed a statistically significant correlation with morphological data, prompting the use of this method to analyse a set of Polish oat landraces [22] and compare the diversity of landraces to selected modern and old Polish cultivars [23]. One of the major findings of the research was the undeniable distinctiveness of the gene pools of the old and modern Polish cultivars; however, none of the previous studies covered a wide set of Polish varieties representing almost the entire history of Polish oat breeding; hence, an attempt was made to conduct such an experiment. The genetic analysis of 72 oat cultivars released from 1893 to 2008 was performed based on ISSR and REMAP markers, the usefulness of which was confirmed in the studies cited above. Additionally, the results were enriched with pedigree data. The aims of this study were as follows: to investigate the changes in the gene pool of the Polish oat cultivars over nearly 120 years of breeding through diversity and population structure analysis; to verify the possibility of genetic discontinuities between obsolete and modern Polish cultivars hypothesised by researchers in the previous oat diversity studies; and to determine the effectiveness of ISSR and REMAP markers in assessing the genetic diversity of A. sativa.

2. Materials and Methods

2.1. Plant Material

In this study, 72 Polish A. sativa cultivars released between 1893 and 2008 were included (Table 1). The old cultivars dated before 1986 were obtained from a Polish gene bank (the National Centre for Plant Genetic Resources, Radzików, Poland). The seeds of the remaining cultivars (42) were kindly supplied by three Polish breeding companies: Strzelce Plant Breeding, Małopolska Plant Breeding, and DANKO Plant Breeding. The cultivars were assigned to four groups according to their breeding time: before 1945, 1946–1969, 1970–1999, and after 2000.

2.2. DNA Extraction and Genotyping

Extraction of total genomic DNA was carried out from several-day-old leaves of 15–20 seedlings of each of the 72 genotypes, according to the CTAB procedure [24]. Molecular analyses were performed using the ISSR method described by Ziętkiewicz et al. [25], with minor modifications as specified by Paczos-Grzęda et al. [26]. For amplification, 36 ISSR primers were used (Table S1). Cultivar genotyping was also carried out according to the REMAP method described by Kalendar et al. [27] and modified by Paczos-Grzęda and Bednarek [20], using the REMAP-LTR primer (555′ CTAGGGCATAATTCCAACA 333′) directed toward 555′ terminal LTR sequence Bare-1 retrotransposon, combined with 16 random ISSR primers (Table S1). The amplification products were separated on 2.5% agarose gels in 1X TBE buffer (89 mM Tris-borate, 2.5 mM EDTA, 0.1% EtBr).

2.3. Molecular Data Mining and Analysis

ISSR and REMAP fragments were converted into binary matrix tables. The matrices were then used to determine the level of primer informativeness measured as polymorphic information content (PIC), which is a relative measure of marker informativeness and depends on the number of alleles of the particular marker, calculated according to the formula described by Roldan-Ruiz et al. [28]; marker index (MI), which provides a convenient estimate of marker utility assessed based on the work of Varshney et al. [29]; and resolving power (RP), which is the coefficient that indicates the discriminatory potential of the markers chosen for the analysis, following the formula of Prevost and Wilkinson [30]. The pedigree of the cultivars was traced back to their ancestors’ cultivars or landraces using data available in Polish GenBank databases (https://bankgenow.edu.pl/en/ accessed on 10 June 2022) and POOL (Pedigrees of Oat Lines) (https://triticeaetoolbox.org/POOL/ accessed on 10 June 2022) [31]. The coefficients of parentage (COPs) were computed from a pedigree in MS Excel 2016 for all pairwise combinations of genotypes, as described by Wang and Lu [32]. Distance matrices were developed for molecular data based on the Gower coefficient [33]. A Mantel test was conducted to verify the association between molecular markers and pedigree. The Ward method of clustering was used, and dendrograms were constructed in XLSTAT Ecology [34]. The relationships between the true distances and the distances predicted using the dendrogram were measured as the cophenetic correlation coefficient (CPCC) [35]. Discrimination analysis (DA) was carried out to identify homogeneous groups [34]. Principal coordinate analysis (PCoA) was also conducted based on distance matrices to visualise the grouping pattern and to provide a graphical representation of the relationships between cultivars [34]. The Generalized Procrustes Analysis (GPA) was used to reduce the scale effects and to obtain a consensus configuration of all of the data [34]. Genotypic variations were assessed across groups created based on breeding time and breeding centre using the analysis of molecular variance (AMOVA) in GenAlEx [36]. The AMOVA procedure in GenAlEx follows the methods of Excoffier et al. [37], estimating the proportion of the variance among populations relative to the total variance. When the data are binary, AMOVA calculates the ΦPT value, which is analogous to Fst [38,39]. A ΦPT value of 0 denotes the minimum level of diversity among subpopulations, while a value of 1 denotes the maximum. The significance of the resulting variance and intergroup genetic distances was tested using 999 random permutations. Nei’s coefficient [40] was calculated to estimate genetic variation within the abovementioned groups of cultivars.
Population structure was estimated using a Bayesian model-based approach implemented in the program STRUCTURE v. 2.3.4 [41]. An admixture model with correlated allele frequencies was employed. The number of clusters (k) was set from 1 to 11, with five independent runs for each k (10,000 burn-ins and 100,000 iterations). The Cluster Markov Packager Across K (CLUMPAK) was used to find optimal alignments of independent runs, and the output was used for cluster visualisation [42]. Cultivars with a membership coefficient lower than 0.8 were identified as admixed.

3. Results

3.1. Pedigree

The ancestry of Polish common oat cultivars was traced back to 124 cultivars, breeding lines, and landraces. The average number of ancestors per cultivar was 10.2, ranging from 1 to 28, and it increased along with the time of breeding, i.e., the oldest and the most recent cultivars were derived from 1.6 and 15.6 ancestors on average, respectively (Figure 1). The five most common progenitors were ‘Markische Landsorte’, ‘selection from Ligowo oat’, ‘Fransk Svarthavre’, ‘Blanche de Siberie’, and ‘selection from Schleswig-Holstein landrace’. We found that at least one of these was present in 78% of analysed cultivars.
Eighteen cultivars were bred before 1945, and these were derived from fourteen ancestors. Six of them were descendants of the German landrace ‘Markische Landsorte’. Only two cultivars in the study represented the period 1945–1969, and both of them had ‘Markische Landsorte’ as a progenitor. Thirty cultivars represented the period lasting for the next 30 years (1970–1999). Of 84 identified ancestors, the most common were ‘selection from Ligowo oat’, ‘Markische Landsorte’, and ‘Fransk Svarthavre’, appearing in the pedigrees of 23, 21, and 20 cultivars, respectively. As many as 22 of the most contemporary cultivars—those that were bred after 2000—were predominantly descendants of ‘selection from Schleswig-Holstein landrace’, ‘Markische Landsorte’, ‘selection from Ligowo oat’, and ‘Fransk Svarthavre’. In total, 81 ancestors were identified for the latest cultivars. The summary of these data can be found in Figure 1.
Descendants of ‘Markische Landsorte’ were the result of the Strzelce Plant Breeding Company breeding programs. Only two cultivars—‘Sławko’(63) and ‘Dukat’(26)—did not have it as an ancestor. Another prevailing progenitor was ‘selection from Ligowo oat’, and only ‘Dukat’(26) and its descendants were not connected with it. ‘Blanche de Siberie’ was present in the pedigree of 14 cultivars bred by the Strzelce Plant Breeding Company. In total, in the breeding of 19 cultivars, 56 progenitors were used. The DANKO Plant Breeding Company mainly used derivatives of ‘selection from Ligowo oat’ and ‘Fransk Svarthavre’ in their programs. Four cultivars had a distinct pedigree, i.e., ‘Deresz’(24), ‘Komes’(40), ‘Ułan’(71), and ‘Zuch’(72). A total of 75 ancestors were identified for 16 cultivars. In this study, nine cultivars bred by the Station of Plant Breeding in Borów were included. In the pedigrees, four primary sources were found, i.e., ‘Markische Landsorte’, ‘Blanche de Siberie’, ‘selection from Ligowo oat’, and ‘Fransk Svarthavre’. Two cultivars had a distinct origin: ‘Borys’(16) and ‘Grajcar’(32). Borys’(16) resulted from crossing (‘Dato’ × ‘Po.3999′) × Pinto, while ‘Grajcar’(32) originated from ‘Komes’ × ‘KR 81-112222′. In total, the cultivars were derived from 55 ancestors. The Małopolska Plant Breeding Company was represented in the study by five cultivars, for which 43 progenitors were identified. Their breeding programs, similarly to the previous ones, were based on materials derived from ‘selection from Ligowo oat’ and ‘Markische Landsorte’. Notably, another distinct source (‘Milton’) was found in three cultivars. It is worth noting that ’Modzurowski’(47) also had a slightly different pedigree; however, it was bred in the earlier period (1945–1969). ‘Milton’ also appeared in the pedigrees of all three cultivars that were bred by the Station of Plant Breeding in Rogaczewo. Furthermore, ‘Markische Landsorte’ and ‘selection from Ligowo oat’ were found among the ancestors of all of them. In total, only 15 progenitors were identified for this set. The data summarising the Polish breeding companies and stations are presented in Figure 2.
Based on COPs, the pairwise dissimilarity coefficient was calculated, and its average value was 0.81. The dissimilarity matrix was used to perform clustering analysis. Clustering of genotypes based on the Gower coefficient resulted in the detection of three major clusters (Figure 3a) with CPCC equal to 0.568. Cluster 1 was the most numerous and consisted of 37 cultivars that had 87 progenitors. Their breeding time was as follows: 23 cultivars were bred in the years 1970–1999, 10 after the year 2000, 5 before 1945 and, finally, 1 in the period 1945–1969. The cultivars in this cluster were derived mainly from ‘Markische Landsorte’ or ‘selection from Ligowo oat’ (37 and 28, respectively). All of the oldest cultivars (bred before 1945) had ‘Markische Landsorte’ and/or ‘Leutewizter Gelb’ in their pedigree, which were also the ancestors of 16 other cultivars from this cluster. Among the later cultivars, only three did not have ‘Markische Landsorte’ as a progenitor, i.e., ‘Sławko’(63), ‘Boruta’(14), and ‘Budrys’(18). The ‘selection from Ligowo oat’ was the progenitor of 28 cultivars in this cluster; however, it did not occur in the pedigrees of the oldest cultivars or in ‘Cekin’(20), ‘Ułan’(71), ‘Przebój II’(55), or ‘Budrys’(18). Cluster 2, composed of only nine cultivars, was the smallest cluster. It contained ‘Dukat’(26), which was bred in 1991, and its descendants that were obtained after 2000. Therefore, all cultivars were descendants of the crossing ‘Fagot × KR 2335/74 L’ maximal in the third generation, and their other ancestry components were quite similar. In total, 33 progenitors were identified for this cluster. Avena sterilis L. was the ancestor of seven cultivars (exceptions: ‘Dukat’(26) and ‘Berdysz’(8)). All of them were bred by the two largest Polish breeding companies, i.e., Strzelce and DANKO (6 and 3, respectively). Cluster 3 had 26 cultivars, with the majority having a simple origin, i.e., a short list of progenitors. Thus, the rest of the old cultivars (before 1945) were grouped there. Among other, more contemporary cultivars (i.e., those bred after 1970), the most common ancestors were ‘selection from Ligowo oat’ and ‘Fransk Svarthavre’.
The results of principal coordinate analysis (PCoA) based on pedigree data are presented on scatterplots of the first two principal coordinates in Figure 3b,c. The first and the second principal coordinates explained 15.6% and 12.8% of the variation, respectively. No significant grouping pattern was found, although the points corresponding to the studied cultivars in two-dimensional space were arranged according to the clusters determined by agglomerative hierarchical clustering. When the breeding centre was indicated, the presence of two groups was noted within the cultivars bred by the DANKO Plant Breeding and Małopolska Plant Breeding companies, as well as within those obtained at the Station of Plant Breeding in Borów (Figure 3c).

3.2. ISSR

In this study, 36 ISSR primers were used to amplify 203 fragments, of which 99.5% were polymorphic. On average, a single ISSR generated 5.72 fragments (range: 1–18). The marker informativeness coefficient values ranged as follows: PIC from 0.05 (sr37) to 0.49 (sr32), with a mean of 0.23; MI from 0.0 (sr37) to 0.49 (sr32), with a mean of 0.18; and RP from 0.11 (sr37) to 23.36 (sr60), with a mean of 5.3 (Table S1).
The Nei’s unbiased genetic diversity (uHe) derived from the ISSR data was 0.256 (Table 2). It was the highest for cultivars bred between 1970 and 1999 (0.236), while it was the lowest for the preceding period (0.106). The most diverse cultivars were derived from the Strzelce Plant Breeding Company (0.241). The cultivars bred by the Małopolska Plant Breeding Company had the lowest variation.
AMOVA determined that the majority of the observed genetic variability was due to variation within groups formed according to breeding time (91%) or among cultivars within breeding companies (93%). The pairwise matrix of the ΦPT groups showed that the longer the time interval between the breeding of two groups, the greater the differences between them (Table 3). It also indicated that there were no significant differences between cultivars from modern breeding companies/stations. However, very early breeding centres functioning before 1945 had significantly different materials from the modern ones (Table 4).
The pairwise Gower similarity ranged from 0.936 (‘Biały Mazur’(9) vs. ‘Sobieszyński’(64)) to 0.64 (‘Płatek’(50) vs. ‘Szakal’(67)). The Ward clustering algorithm reflected three main clusters with CPCCs equal to 0.371 (Figure 4a). The first cluster contained 36 cultivars, of which 64% were bred in the period 1970–1999, 31% after 2000, and 2 cultivars were from the oldest group, i.e., ‘Kanarek Mikulicki’(37) and ‘Podkowa Dłużewski’(51). The second cluster was the smallest one, and it was composed of nine cultivars that were bred after 2000 and two from an earlier period (1970-1999), i.e., ‘Sam’(60) and ‘Sławko’(63). The cultivars that were grouped in this cluster were derived from two major breeding centres, i.e., Strzelce and DANKO. The third cluster contained 25 cultivars, including the majority of the oldest cultivars (before 1945), ‘Modzurowski’(47) and ‘Przebój I’(54) that were bred in the period 1945–1969, and also 7 cultivars obtained later. Discriminant analysis indicated that 58.33% of cultivars were assigned to the same group in the analysis of COP and ISSR.
The first two coordinates of PCoA based on the Gower dissimilarity coefficient explained 22.8% of the variance and indicated the presence of three groups (Figure 4b). On the plot below, an association of time of origin with the first coordinate can be observed. The newest and the oldest cultivars were arranged at opposite ends of the axle (Figure 4c).
The genetic structure of 72 oat cultivars was estimated via model-based Bayesian clustering using the STRUCTURE software. Based on the highest Δk values, k = 2 appeared the most probable (Figure 4d). When considering k = 2, the collection was split into two subgroups containing 21 and 28 cultivars, while 23 were admixed (80% level). The oldest cultivars were placed in the first group or were classified as admixed, i.e., ‘Kanarek Mikulicki’(37), ‘Podkowa Dłużewski’(51), ‘Teodzja’(68), and ‘Udycz Biały’(69). Both cultivars bred in the period 1945–1969 and four from 1970–1999 were also assigned to the first group. ‘Polar’(52), which was bred after 2000, was the only cultivar from that period in this group. The second group was formed of 28 cultivars evenly sourced from the two most recent periods (Figure 4d).

3.3. REMAP

Using 21 REMAP pairs of primers, a total of 178 fragments were obtained, of which 87.1% were polymorphic. On average, a single REMAP reaction yielded 8.48 fragments (range: 2–17). All characteristics of the markers are presented in Table S2. The average value of PIC for REMAP markers was 0.29. The maximum PIC was obtained for the primer pairs r42, r47, and r54 (0.49), while the minimum value was demonstrated by r6 and r11 (0.03). The highest and the lowest MI values were obtained for the same primers as PIC, and the values were 0.49 and 0.0, respectively. The average RP value for REMAP was 9.05, and for each primer pair it ranged from 0.08 to 32.92 (r6 and r59, respectively), with a mean of 5.3 (Table S2).
The Nei’s unbiased genetic diversity (uHe) derived from the REMAPs was slightly higher than that from ISSRs, at 0.308 (Table 2). The group of most recent cultivars were the most diverse (0.289), while cultivars bred between 1945 and 1969 had the lowest diversity coefficient (0.158). The most varied cultivars were bred by the DANKO Plant Breeding Company (0.288) and Strzelce Plant Breeding Company (0.283), while the least diverse ones were bred by the Station of Plant Breeding in Rogaczewo.
The results of AMOVA based on REMAP data were consistent with those obtained for ISSRs and indicated that variability among cultivars within the periods of breeding time was significantly higher than the variation between the breeding periods. Variance among cultivars within breeding companies was also higher than between companies. The pairwise ΦPT of breeding period groups did not support the results of analogous analysis for ISSRs. The difference between the oldest and the newest cultivars was smaller than that between the oldest and those bred in the period 1970–1999 (Table 3). Very small differences were found between contemporary breeding companies/stations. The cultivars derived from historical breeding centres were significantly different from the more modern ones, and this was consistent with the ISSR results (Table 4).
Genetic similarity between samples was calculated based on the Gower coefficient. For REMAP analysis, it was in the range of 0.59–0.88 for the cultivar pairs ‘Borek’(12) vs. ‘Proporczyk’(53) and ‘Boryna’(15) vs. ‘Borys’(16), respectively. Based on the genetic distance matrices, Ward’s cluster analysis was performed (Figure 5a). The cophenetic correlation was 0.437. A dendrogram created based on these results showed the presence of three major clusters with a strong hierarchical structure containing 27, 11, and 34 cultivars. The oldest cultivars (before 1945), with no exception, were grouped in the first cluster. Apart from them, there were also the two cultivars from the period 1945–1969, six bred in the period 1970–1999, and ‘Polar’(52) representing the most modern group. The second cluster was composed of only 11 cultivars, the majority of which were bred after 2000. Two cultivars (‘Kasztan’(39) and ‘Sławko’(63)) of this cluster were obtained earlier, i.e., between the years 1970 and 1999. The third and largest cluster was composed of 34 cultivars, of which 22 were bred in the period 1970–1999 and the remaining 12 came from the most recent period. According to DA, the assignment of cultivars to the groups was identical in as much as 79.17% for REMAP and ISSR analyses, but only in 58.33% when comparing pedigree.
Associations among the 72 oat cultivars revealed by PCoA calculated from REMAP-based Gower dissimilarity estimates are presented in Figure 5b. The first (PCo1) and second (PCo2) principle coordinates accounted for 13.8 and 8.4% of the total variation, respectively. The results were spread across the principal coordinates, and no grouping pattern was found. However, an association of the breeding period with the plot could be noted, as shown in Figure 5c. DA confirmed 68.1% compliance of PCoA with the breeding time.
The STRUCTURE software was also used to determine the REMAP-based genetic structure. The Δ statistical test showed that k = 2 was optimal in this analysis (Figure 5d). At k = 2, 25 and 26 cultivars fell into the two groups, while 21 were marked as putative hybrids (Figure 5e). In general, the participation of the genetic makeup of the first group was higher in the cultivars bred before 1970, while the later ones mostly represented the second group. However, two cultivars from the period 1970–1999 and seven from the most recent period showed similarity with the first group at a level above 80%.

3.4. Combined and Comparative Evaluation

A pairwise Mantel test was performed for all combinations of dissimilarity matrices. Statistically significant correlation (r = 0.419, p-value < 0.0001) was observed only for the comparison of the ISSR and REMAP matrices.
For the combined binary matrices obtained from the ISSR and REMAP analyses, agglomerative hierarchical clustering (AHC) was performed using the Ward method. It showed the presence of three main clusters that, as before, were strongly hierarchical inside and contained 19, 18, and 35 cultivars, respectively (Figure 6a). Discriminant analysis showed that the AHC results for the pooled matrices were 77.78% consistent with the clustering derived from the ISSR results and 86.11% consistent with the results derived from REMAP alone. The concordance of the clustering of the combined matrices with the results obtained from the pedigree analysis was 58.33%, which was the same as for each of the molecular analyses separately.
A combination of PCoA results obtained from the pedigree, ISSR, and REMAP data was performed using Generalized Procrustes Analysis (GPA). The proportion of total variance explained by the consensus matrix (Rc) for the dataset was high (0.737), and the permutation test indicated that it was statistically significant (p < 0.05), so the agreement within the dataset was strong. The pedigree data gave slightly less consistent results. The first two PCA dimensions (PC1 and PC2) accounted for 18.97 % of the variance in the consensus matrix (Figure 6b). Based on the biplot of the first two dimensions, the presence of three groups was noted. Moreover, a shift and then a change in breeding direction were found (Figure 6c).
Genetic structure was estimated based on combined genetic data using the model-based Bayesian clustering (Figure 6d). Based on the highest Δk values, k = 3 appeared to be optimal. The oldest cultivars represented the first group, with the small participation of other groups (Figure 6e). From 1970 to 1999, the presence of the genotypes representing the second group was higher, while the recent cultivars belonged to both the second and third groups. This reflected the GPA results presented below.

4. Discussion

The dozens of new oat cultivars have been developed over nearly 120 years of Polish breeding of oats (Avena sativa L.). In this study, an analysis of the diversity and population structure of 72 oat cultivars released since 1893 was carried out. The pedigree data as well as ISSR and REMAP markers were used for the research. The studied set of cultivars was assigned to the four groups according to the period of their breeding (before 1945, 1945–1969, 1970–2000, and after 2000) and six groups where the breeding company by which they were developed was considered (Strzelce Plant Breeding Company, DANKO Plant Breeding, Choryń, Station of Plant Breeding, Rogaczewo, Małopolska Plant Breeding Company, Station of Plant Breeding, Borów, or other). For historical and geographical reasons, European breeding has had a significant impact on the beginnings of oat breeding in Poland. In this research, the ancestry of Polish common oat cultivars was traced back to 124 cultivars, breeding lines, and landraces, allowing us to establish the influence of foreign varieties on the analysed material.
In our studies, we identified the five most common progenitors of Polish cultivars, which were ‘Markische Landsorte’, ‘selection from Ligowo oat’, ‘Fransk Svarthavre’, ‘Blanche de Siberie’, and ‘selection from Schleswig-Holstein landrace’. We found that at least one of these was present in 78% of analysed cultivars. ‘Selection from Markische Landsorte’ became the cultivar ‘Lochows Gelb’, which gave rise to ‘Flaminstreue’—a cultivar from the first German oat breeding lineages described by Bickelman (1989). Bickelmann’s studies on fatuoid oats enabled him to conclude that the German varieties were derived from several genetic lines, three of which are the most numerous. One of them comes from the cross of the landraces ‘Lochows Gelb’ and ‘Oberschlesische Landsorte Weiβ’, which gave rise to ‘Flamingstreue’ and ‘Flamingsgold’. Most of the German breeding materials are descendants of these cultivars. The cross of ‘Probstei Type’ with ‘Lochows Gelb’ gave rise to the ‘Adler’ lineage, to which a series of cultivars can be traced back. The cross of ‘Silber’ with a ‘Fransk Svarthavre’ gave rise to ‘Minor’—the starting point of a third breeding lineage. Another progenitor of Polish cultivars, ‘Selection from Ligowo oat’—a cultivar from Sweden—gave rise to ‘Swedish Select’, followed by the ‘Blanche de Siberie’ (or ‘White Siberie’). This variety, after crossing with ‘Lochows Gelb’, gave the ‘Flamingsgold’ variety (also from the first German lineages). ‘Fransk Svarthavre’ gave rise to the third German lineage. The common Polish cultivars’ progenitor, ‘selection from Schleswig-Holstein landrace’, took part in the formation of a Probsteir-type oat lineage, which may be related to the second most popular pedigree line of German varieties. This confirms that Polish and German obsolete oat cultivars were derived from a small number of closely related landraces, cultivars, or breeding lines.
Comparing the European cultivars with the North American ones, Achleitner et al. [43] found that oat cultivars originating from European breeding programs showed less diversity than cultivars originating from North and South America. However, in Canadian breeding programs, 130 cultivars released from 1930 to 2001 could be traced back to fewer than 10 parental lines [44]. Similarly, most of the USA germplasm utilised for cultivar development before 1970 traced back to only seven landrace varieties introduced from Europe: ‘Kherson’ (‘Sixty Day’), ‘Green Russian’, ‘Victory’, ‘Markton’, ‘White Russian’ (‘White Tartar’), ‘Red Rustproof’, and ‘Winter Turf’ [7]. The higher diversity of American cultivars was probably the effect of the popularity of the hybridisation of A. sativa with A. byzantina. Such hybrids were quite rare, especially in North and Central Europe, because A. byzantina is a winter-type red oat that is well-adapted to the mild winters typical of the Mediterranean basin as well as the United Kingdom.
Concern has often been expressed that modern intensive plant breeding leads to a reduction in the genetic diversity of crops. Such reductions may have consequences, both for the susceptibility of crops to pests and diseases and their ability to respond to climate change [45]. It is therefore necessary to quantify the changes that have occurred in the genetic diversity of major crops. In this study, the diversity and population structure analyses of 72 oat genotypes were performed to investigate the changes in the gene pool of the Polish oat cultivars over nearly 120 years of breeding. For this purpose, ISSR and REMAP molecular marker systems were used. Large-scale DNA sequencing techniques allow for an increase in the number of polymorphisms identified in a single experiment—mainly SNPs and In/Dels. Nevertheless, many breeding companies and scientists still cannot afford sequential analysis, and traditional polymorphism analysis techniques are a widely used and cheap alternative. PCR-based techniques give a direct measure of genetic diversity and identify a high number of polymorphic loci uniformly distributed through the genome. In our study, both the ISSR and REMAP matrices showed a statistically significant correlation, allowing us to obtain complementary results. Similarly, Dziurdziak et al. [46], examining local barley cultivars, found a high correlation between the results obtained with the ISSR method and DArTseq. The DArTseq relies on the analysis of SNPs by restriction digestion within the reduced representation of the genome. Thus, it can be concluded that the ISSR and related REMAP markers belong to the group of highly informative and reliable markers.
In this paper, the effectiveness of ISSR and REMAP markers was determined by the amount of polymorphism, PIC (polymorphic information content) coefficient, marker index (MI), and resolving power (RI). The highest average number of polymorphic fragments as well as PIC, RI, and MI was characterised by REMAP, in contrast to the results of Paczos-Grzęda and Bednarek [20]. The REMAP method identifies polymorphisms resulting from the distribution of microsatellite sequences and retrotransposons; therefore, a greater polymorphism of REMAP markers seems to be justified. The ISSR method, on the other hand, detects variation in the size of the genomic regions between the two adjacent microsatellite sequences used as the primer binding sites [25]. Most of the studies on Avena diversity conducted so far by other authors have been carried out using the ISSR method; however, enriching the results with REMAP polymorphism works in favour of the obtained results, especially since the two methods show a statistically significant correlation. Pedigree analysis is the most misleading method, as it is based on the assumption that parents contribute half of their genome to the progeny and are genetically significantly distinct from one another. Consequently, the differences between genotypes obtained by this method are overestimated.
The genetic diversity of Polish oat cultivars has been analysed in the past using molecular markers such as RAPD and AFLP [19], as well as ISSR [18,20,21,47]. The results obtained in the previous studies indicated differences between old and modern Polish cultivars; however, the diversity within the analysed gene pools was at a low level, which is consistent with the results obtained in this study. Our research indicates that most of the variability is due to the variation within analysed oat groups based on the period of their breeding. The longer the breeding time interval, the greater the differences between the studied gene pools. The distinction of the historical gene pool from that of modern oat cultivars is justified by the destruction of Polish breeding materials during World War II. Historical cultivars from the first half of the 20th century mainly result from selection within landraces. Landraces, usually genetically heterogeneous and adapted to local conditions, are seen as a source of easily accessible genes that provide better resistance to biotic and abiotic stresses [48]. Landraces, in comparison to cultivars, are considered to be much more genetically diverse, as confirmed by the previous results of a genetic diversity analysis within a collection of common oat landraces originating from the same regions [18,22,23]. The total variation of the collection was relatively low in contrast to the internal variation of the studied landraces. Moreover, the level of oat landraces’ internal variation was significantly higher than that found within historical and modern cultivars [23]. In our study, the group of the most recent cultivars was more diverse than most of the compared groups; however, incorporating landraces as well as wild relatives into the modern breeding process would definitely expand the oat gene pool and enrich it with the desired breeding traits. Today, in the modern breeding process—mostly for economic reasons—the exploitation of landraces is replaced by advanced cultivars or breeding lines with a limited genetic makeup. By narrowing the starting material, breeders do not need several backcrossing cycles to eliminate the undesirable traits introduced along with the desirable ones, significantly speeding up the breeding process, but leading to meeting short-term breeding goals.
Currently, attempts are being made to create cultivars that are resistant to new aggressive races of pathogens and easily adapt to abiotic stresses and climate change [13]. This study indicates that historical oat cultivars are genetically distinct from more modern ones and, according to our previous research [49] determining resistance to Puccinia coronata f.sp. avenae in a set of 63 previously uncharacterised oat cultivars, historical varieties could be a valuable source of useful Pc resistance genes discarded during subsequent breeding. A similar role may be played by wild oat progenitors [49,50,51,52,53]; however, all Avena spp. are grouped into three gene pools [54], and successful introgression of genes from diploids or tetraploids belonging to the tertiary gene pool to hexaploid A. sativa is more demanding and requires special techniques [55]. Attention needs to be paid to integrated efforts in the conservation of oat germplasm and the exploration of new sources of desirable alleles. Continuous diversification of breeding materials and gene introgression from more exotic germplasm would broaden the genetic diversity and allow sustainable oat improvements.
Diversity loss is common in modern crops of major species developed by large breeding programs [56]. The performed research proved that Polish oat breeding using traditional breeding methods, although focused on improving traits defined by market needs, did not significantly narrow the oat gene pool and has been releasing cultivars that are competitive in the European market. A further, more detailed analysis extended with morphological and physiological characteristics is crucial for developing long-term strategies that are beneficial to modern oat breeding.

5. Conclusions

The performed analysis enabled the investigation of the changes in the gene pool of the oat cultivars over nearly 120 years of breeding in Poland. A decrease in observed heterozygosity within the groups was observed only in the postwar period (1945–1969), and new alleles were provided as a result of extensive crosses with foreign materials. The population genetic structure was quite simple, composed of two or three distinct gene pools, depending on the method of polymorphism assessment. ISSR and REMAP analysis support the statement that currently grown cultivars share a very similar genetic background, although they are derived from different breeding companies and their gene pool is significantly distinct from that of older varieties. This confirms the undeniable distinctiveness of the gene pools of old and modern Polish cultivars hypothesised by researchers in the previous oat diversity studies. The pedigree analysis enabled the identification of the five most common progenitors of Polish cultivars and the establishment of the influence of foreign varieties in the analysed material. Comparative analysis of the methods used in the study showed that the set of REMAPs was the most efficient, and since most of the studies on Avena diversity conducted so far have been carried out using the ISSR method, enriching the results with REMAP polymorphism works in favour of the obtained results—especially since the two methods show a statistically significant correlation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12102423/s1, Table S1: List of ISSR primers used in the study and values of informativeness coefficients: Polymorphic information content (PIC); Marker Index (MI); Resolving Power (RP); Table S2: List of REMAP primers used in the study and values of informativeness coefficients: Polymorphic information content (PIC); Marker Index (MI); Resolving Power (RP).

Author Contributions

Conceptualisation and methodology, A.K., E.P.-G. and S.S.; investigation, A.K. and J.T.; resources E.P.-G.; writing—original draft preparation, A.K.; writing—review and editing, E.P.-G. and S.S.; visualisation, M.B. All authors have read and agreed to the published version of the manuscript.

Funding

The calculations were performed at the Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw (ICM UW), within the framework of Computational Grant No. G72–19.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Stevens, E.J.; Armstrong, K.W.; Bezar, H.J.; Griffin, W.B.; Hampton, J.G. Fodder oats an overview. In Fodder Oats: A World Overview; Suttie, J.M., Reynolds, S.G., Eds.; Agriculture Organization of the United Nations: Rome, Italy, 2004; pp. 1–9. [Google Scholar]
  2. Baum, B.R. Oats: Wild and Cultivated: A Monograph of the Genus Avena L. (Poaceae); Monograph; Supply and Service Canada: Ottawa, ON, Canada, 1977. [Google Scholar]
  3. Leggett, J.M. Classification and Speciation in Avena. In Oat Science and Technology; Marshall, H.G., Sorrells, M.E., Eds.; Agronomy Monograph; American Society of Agronomy, Crop Science Society of America: Madison, WI, USA, 1992; pp. 29–52. ISBN 978-0-89118-225-2. [Google Scholar]
  4. Zeller, F.J. Nutzung des genetischen Potentials der Avena-Wildarten zur Verbesserung des Saathafers (Avena sativa L.). J. Appl. Bot. 1998, 72, 180–185. [Google Scholar]
  5. Zohary, D.; Hopf, M. Domestication of Plants in the Old World, 2nd ed.; Clarendon Press: Oxford, UK, 1993. [Google Scholar]
  6. Budzyński, W.; Szemplińska, W. Owies (Oat). In Szczegółowa Uprawa Roślin (Detaild Plant Cultivation); Jasińska, Z., Kotecki, W., Eds.; Agricultural Academy: Wrocław, Poland, 2003; pp. 239–258. [Google Scholar]
  7. Coffman, F.A. Oat History, Identification and Classification; US Department of Agriculture: Washington, DC, USA, 1977; Volume 1516.
  8. Murphy, J.P.; Hoffman, L.A. The Origin, History, and Production of Oat. In Oat Science and Technology; Marshall, H.G., Sorrells, M.E., Eds.; American Society of Agronomy: Madison, WI, USA, 1992; p. 27. [Google Scholar]
  9. Leggett, J.M.; Thomas, H. Oat evolution and cytogenetics. In The Oat Crop; Welch, W., Ed.; Chapman & Hall: London, UK, 1995; p. 121. [Google Scholar]
  10. Andersson, A.; Börjesdotter, D. Effects of environment and variety on content and molecular weight of b-glucan in oats. J. Cereal Sci. 2011, 54, 122–128. [Google Scholar] [CrossRef]
  11. FAOSTAT Database. Food and Agriculture Organization of the United Nations. Available online: www.fao.org (accessed on 21 July 2022).
  12. Boczkowska, M.; Podyma, W.; Łapiński, B. Oat. In Genetic and Genomic Resources for Grain Cereals Improvement; Singh, M., Upadhyaya, H.D., Eds.; Elsevier: Amsterdam, The Netherlands, 2016; pp. 159–225. ISBN 9780128020005. [Google Scholar]
  13. Gorash, A.; Armonienė, R.; Mitchell Fetch, J.; Liatukas, Ž.; Danytė, V. Aspects in oat breeding: Nutrition quality, nakedness and disease resistance, challenges and perspectives. Ann. Appl. Biol. 2017, 171, 281–302. [Google Scholar] [CrossRef]
  14. Spiss, L. History of oat breeding in Poland. Biul. Inst. Hod. Aklim. Roślin 2003, 229, 7–11. [Google Scholar]
  15. Arseniuk, E.; Krzymuski, J.; Martyniak, J. History of Breeding and Seed Production in Poland in the 20th Century; IHAR Radzików: Radzików, Poland, 2003; ISBN 83-88518-53-4. [Google Scholar]
  16. Świerczewski, A.; Mazaraki, M. Oat breeding. In Biology and Agrotechnology of Oats; Mazurek, J., Wojcieska, U., Mazurek, J., Król, M., Eds.; IUNG: Pulawy, Poland, 1993; pp. 129–161. [Google Scholar]
  17. Montilla-Bascón, G.; Sánchez-Martín, J.; Rispail, N.; Rubiales, D.; Mur, L.; Langdon, T.; Griffiths, I.; Howarth, C.; Prats, E. Genetic Diversity and Population Structure Among Oat Cultivars and Landraces. Plant Mol. Biol. Report. 2013, 31, 1305–1314. [Google Scholar] [CrossRef] [Green Version]
  18. Boczkowska, M.; Łapiński, B.; Kordulasińska, I.; Dostatny, D.F.; Czembor, J.H. Promoting the Use of Common Oat Genetic Resources through Diversity Analysis and Core Collection Construction. PLoS ONE 2016, 11, e0167855. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Paczos-Grzęda, E. Pedigree, RAPD and simplified AFLP-based assessment of genetic relationships among Avena sativa L. cultivars. Euphytica 2004, 138, 13–22. [Google Scholar] [CrossRef]
  20. Paczos-Grzęda, E.; Bednarek, P.T. Comparative analysis of hexaploid Avena species using REMAP and ISSR methods. Turk. J. Botany 2014, 38, 1103–1111. [Google Scholar] [CrossRef]
  21. Boczkowska, M.; Nowosielski, J.; Nowosielska, D.; Podyma, W. Assessing genetic diversity in 23 early Polish oat cultivars based on molecular and morphological studies. Genet. Resour. Crop Evol. 2014, 61, 927–941. [Google Scholar] [CrossRef] [Green Version]
  22. Boczkowska, M.; Tarczyk, E. Genetic diversity among Polish landraces of common oat (Avena sativa L.). Genet. Resour. Crop Evol. 2013, 60, 2157–2169. [Google Scholar] [CrossRef] [Green Version]
  23. Boczkowska, M.; Onyśk, A. Unused genetic resources: A case study of Polish common oat germplasm. Ann. Appl. Biol. 2016, 169, 155–165. [Google Scholar] [CrossRef]
  24. Doyle, J.J.; Doyle, J.L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 1987, 19, 11–15. [Google Scholar]
  25. Ziętkiewicz, E.; Rafalski, A.; Labuda, D. Genome Fingerprinting by Simple Sequence Repeat (SSR)-Anchored Polymerase Chain Reaction Amplification. Genomics 1994, 20, 176–183. [Google Scholar] [CrossRef]
  26. Paczos-Grzeda, E.; Bednarek, P.T.; Koroluk, A.; Nita, Z.; Banaszak, Z.; Bichonski, A.; Chmiel, M.; Gradzielewska, A.; Nowaczyk, K.; Szolkowska, A.; et al. Genetic similarity assessment among selected naked oat cultivars and breeding lines using ISSR markers. Not. Bot. Horti Agrobot. Cluj Napoca 2014, 42, 66–72. [Google Scholar] [CrossRef] [Green Version]
  27. Kalendar, R.; Grob, T.; Regina, M.; Suoniemi, A.; Schulman, A. IRAP and REMAP: Two new retrotransposon-based DNA fingerprinting techniques. Theor. Appl. Genet. 1999, 98, 704–711. [Google Scholar] [CrossRef]
  28. Roldán-Ruiz, I.; Calsyn, E.; Gilliland, T.J.; Coll, R.; Van Eijk, M.J.T.; De Loose, M. Estimating genetic conformity between related ryegrass (Lolium) varieties. 2. AFLP characterization. Mol. Breed. 2000, 6, 593–602. [Google Scholar] [CrossRef]
  29. Varshney, R.K.; Chabane, K.; Hendre, P.S.; Aggarwal, R.K.; Graner, A. Comparative assessment of EST-SSR, EST-SNP and AFLP markers for evaluation of genetic diversity and conservation of genetic resources using wild, cultivated and elite barleys. Plant Sci. 2007, 173, 638–649. [Google Scholar] [CrossRef] [Green Version]
  30. Prevost, A.; Wilkinson, M.J. A new system of comparing PCR primers applied to ISSR fingerprinting of potato cultivars. TAG Theor. Appl. Genet. 1999, 98, 107–112. [Google Scholar] [CrossRef]
  31. Tinker, N.A.; Deyl, J.K. A Curated Internet Database of Oat Pedigrees. Crop Sci. 2005, 45, 2269–2272. [Google Scholar] [CrossRef]
  32. Wang, S.; Lu, Z. Genetic diversity among parental lines of Indica hybrid rice (Oryza sativa L.) in China based on coefficient of parentage. Plant Breed. 2006, 125, 606–612. [Google Scholar] [CrossRef]
  33. Gower, J.C. A General Coefficient of Similarity and Some of Its Properties. Biometrics 1971, 27, 857. [Google Scholar] [CrossRef]
  34. Addinsoft XLSTAT 2019.4.1 Statistical and Data Analysis Solution; Addinsoft, NY, USA, 2019. Available online: https//www.xlstat.com (accessed on 10 June 2022).
  35. Farris, J.S. On the Cophenetic Correlation Coefficient. Syst. Zool. 1969, 18, 279. [Google Scholar] [CrossRef] [Green Version]
  36. Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef] [PubMed]
  37. Excoffier, L.; Smouse, P.E.; Quattro, J.M. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data. Genetics 1992, 131, 479–491. [Google Scholar] [CrossRef]
  38. Wright, S. The Interpretation of Population Structure by F-Statistics with Special Regard to Systems of Mating. Evolution 1965, 19, 395. [Google Scholar] [CrossRef]
  39. Wright, S. Isolation by distance. Genetics 1943, 28, 114–138. [Google Scholar] [CrossRef] [PubMed]
  40. Lynch, M.; Milligan, B.G. Analysis of population genetic structure with RAPD markers. Mol. Ecol. 1994, 3, 91–99. [Google Scholar] [CrossRef] [PubMed]
  41. Hubisz, M.J.; Falush, D.; Stephens, M.; Pritchard, J.K. Inferring weak population structure with the assistance of sample group information. Mol. Ecol. Resour. 2009, 9, 1322–1332. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Kopelman, N.M.; Mayzel, J.; Jakobsson, M.; Rosenberg, N.A.; Mayrose, I. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 2015, 15, 1179–1191. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Achleitner, A.; Tinker, N.A.; Zechner, E.; Buerstmayr, H. Genetic diversity among oat varieties of worldwide origin and associations of AFLP markers with quantitative traits. Theor. Appl. Genet. 2008, 117, 1041–1053. [Google Scholar] [CrossRef] [PubMed]
  44. Fu, Y.; Peterson, G.W.; Scoles, G.; Rossnagel, B.; Schoen, D.J.; Richards, K.W. Allelic Diversity Changes in 96 Canadian Oat Cultivars Released from 1886 to 2001. Crop Sci. 2003, 43, 1989–1995. [Google Scholar] [CrossRef] [Green Version]
  45. Clunies-Ross, T. Mangolds, manure and mixtures: The importance of crop diversity on British farms. Ecologist 1995, 25, 181–187. [Google Scholar]
  46. Dziurdziak, J.; Gryziak, G.; Groszyk, J.; Podyma, W.; Boczkowska, M. DArTseq Genotypic and Phenotypic Diversity of Barley Landraces Originating from Different Countries. Agronomy 2021, 11, 2330. [Google Scholar] [CrossRef]
  47. Boczkowska, M.; Harasimiuk, M.; Onyśk, A. Studies on genetic variation within old Polish cultivars of common oat. Cereal Res. Commun. 2015, 43, 12–21. [Google Scholar] [CrossRef]
  48. Villa, T.C.C.; Maxted, N.; Scholten, M.; Ford-Lloyd, B. Defining and identifying crop landraces. Plant Genet. Resour. 2005, 3, 373–384. [Google Scholar] [CrossRef] [Green Version]
  49. Sowa, S.; Paczos-Grzęda, E. A study of crown rust resistance in historical and modern oat cultivars representing 120 years of Polish oat breeding. Euphytica 2020, 216, 1–10. [Google Scholar] [CrossRef]
  50. Okoń, S.M.; Ociepa, T.; Paczos-Grzęda, E.; Ladizinsky, G. Evaluation of resistance to Blumeria graminis (DC.) f. sp. avenae, in Avena murphyi and A. magna genotypes. Crop Prot. 2018, 106, 177–181. [Google Scholar] [CrossRef]
  51. Paczos-Grzęda, E.; Sowa, S.; Koroluk, A.; Langdon, T. Characteristics of resistance to Puccinia coronata f. sp. avenae in Avena fatua. Plant Dis. 2018, 102, 2616–2624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Paczos-Grzęda, E.; Sowa, S.; Boczkowska, M.; Langdon, T. Detached Leaf Assays for Resistance to Crown Rust Reveal Diversity Within Populations of Avena sterilis. Plant Dis. 2019, 103, 832–840. [Google Scholar] [CrossRef]
  53. Sowa, S.; Paczos-Grzęda, E.; Koroluk, A.; Okoń, S.; Ostrowska, A.; Ociepa, T.; Chrząstek, M.; Kowalczyk, K. Resistance to Puccinia coronata f. sp. avenae in Avena magna, A. murphyi, and A. insularis. Plant Dis. 2016, 100, 1184–1191. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Harlan, J.R.; de Wet, J.M.J. Toward a rational classification of cultivated plants. Taxon 1971, 20, 509–517. [Google Scholar] [CrossRef]
  55. Aung, T.; Chong, J.; Leggett, M. The Transfer of Crown Rust Resistance Pc94 from a Wild Diploid to Cultivated Hexaploid Oat. In Proceedings of the 9th International European and Mediterranean Cereal Rust and Powdery Mildews Conference, Lunteren, The Netherlands, 2–6 September 1996; Kema, G.H.J., Niks, R.E., Daamen, R.A., Eds.; Wageningen, European and Mediterranean Cereal Rust Foundation: Lunteren, The Netherlands, 1996; pp. 167–171. [Google Scholar]
  56. Maxted, N.; Dulloo, M.E.; Ford-Lloyd, B.V. Enhancing Crop Genepool Use: Capturing Wild Relative and Landrace Diversity for Crop Improvement; CABI: Boston, MA, USA, 2016. [Google Scholar]
Agronomy 12 02423 g001 550
Figure 1. Description of four periods of breeding, including the number of cultivars, number of ancestors, and the mean number of ancestors per cultivar. The range of the number of single cultivar progenitors is also shown.
Figure 1. Description of four periods of breeding, including the number of cultivars, number of ancestors, and the mean number of ancestors per cultivar. The range of the number of single cultivar progenitors is also shown.
Agronomy 12 02423 g001
Agronomy 12 02423 g002 550
Figure 2. A summary of the breeding centres’ activity.
Figure 2. A summary of the breeding centres’ activity.
Agronomy 12 02423 g002
Agronomy 12 02423 g003 550
Figure 3. Pedigree: (a) A dendrogram of the results of the Ward method of clustering based on the COP. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter–cultivar distances measured using the COP. The colours of the points correspond to the groups marked on the dendrogram ((a,b) each number represents a single cultivar and is consistent with the numbers in Table 1). (c) PCoA plot with the indication of the breeding centre, excluding the group of ‘Others’. The two distinct groups are framed by a dashed line.
Figure 3. Pedigree: (a) A dendrogram of the results of the Ward method of clustering based on the COP. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter–cultivar distances measured using the COP. The colours of the points correspond to the groups marked on the dendrogram ((a,b) each number represents a single cultivar and is consistent with the numbers in Table 1). (c) PCoA plot with the indication of the breeding centre, excluding the group of ‘Others’. The two distinct groups are framed by a dashed line.
Agronomy 12 02423 g003
Agronomy 12 02423 g004 550
Figure 4. ISSR: (a) A dendrogram of the Ward method clustering results based on the Gower dissimilarity coefficient. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter-cultivar distances measured using the Gower dissimilarity coefficient. The colours of the points correspond to the groups marked on the dendrogram. (c) PCoA plot with the indication of the breeding time. (d) Estimated number of clusters obtained for K values from 1 to 11 using ISSR data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 2 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the two subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. (a,b,e—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Figure 4. ISSR: (a) A dendrogram of the Ward method clustering results based on the Gower dissimilarity coefficient. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter-cultivar distances measured using the Gower dissimilarity coefficient. The colours of the points correspond to the groups marked on the dendrogram. (c) PCoA plot with the indication of the breeding time. (d) Estimated number of clusters obtained for K values from 1 to 11 using ISSR data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 2 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the two subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. (a,b,e—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Agronomy 12 02423 g004
Agronomy 12 02423 g005 550
Figure 5. REMAP: (a) Results of the Ward method clustering based on the Gower dissimilarity coefficient. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter-cultivar distances measured using the Gower dissimilarity coefficient. The colours of the points correspond to the groups marked on the dendrogram. (c) PCoA plot with the indication of the breeding time. (d) Estimated numbers of clusters obtained for K values from 1 to 11 using ISSR data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 2 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the two subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. ((a,b,e)—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Figure 5. REMAP: (a) Results of the Ward method clustering based on the Gower dissimilarity coefficient. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) PCoA of the inter-cultivar distances measured using the Gower dissimilarity coefficient. The colours of the points correspond to the groups marked on the dendrogram. (c) PCoA plot with the indication of the breeding time. (d) Estimated numbers of clusters obtained for K values from 1 to 11 using ISSR data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 2 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the two subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. ((a,b,e)—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Agronomy 12 02423 g005
Agronomy 12 02423 g006 550
Figure 6. Combined results: (a) Results of the Ward method clustering based on the Gower dissimilarity coefficient for ISSR and REMAP. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) Scatterplot of GPA results for ISSR, REMAP, and pedigree data. (c) GPA plot with the indication of the breeding time. (d) Estimated number of clusters obtained for K values from 1 to 11 using ISSR and REMAP data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 3 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the three subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. ((a,b,e)—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Figure 6. Combined results: (a) Results of the Ward method clustering based on the Gower dissimilarity coefficient for ISSR and REMAP. The vertical dashed line indicates the optimal number of clusters based on entropy, which measures how elements are distributed or assigned in each cluster. Low entropy corresponds to better clustering. (b) Scatterplot of GPA results for ISSR, REMAP, and pedigree data. (c) GPA plot with the indication of the breeding time. (d) Estimated number of clusters obtained for K values from 1 to 11 using ISSR and REMAP data based on ΔK. (e) Inferred population structure using the model-based program STRUCTURE. Plots were generated based on the Q-matrix consensus permuted across 5 replications for K = 3 using the CLUMPAK software. Each cultivar is represented by a single vertical line, which is partitioned into segments proportional to the estimated membership in the three subpopulations. The likelihood of assignment to a given cluster is on the vertical axis. ((a,b,e)—Each number represents a single cultivar and is consistent with the numbers in Table 1).
Agronomy 12 02423 g006
Table
Table 1. Names, breeding company, pedigree, and information about time of presence in the National Register of Varieties of common oat cultivars.
Table 1. Names, breeding company, pedigree, and information about time of presence in the National Register of Varieties of common oat cultivars.
No.Cultivar NameBreeding CompanyPedigreeAccession NumberDonor IdentifierThe Year of Entry and Removal from the National Register of VarietiesGroup According to the Breeding Time
1AktStrzelce Plant BreedingAdam × Adamo Strzelce1997/20071970–1999
2Antoniński BiałySandomiersko-Wielkopolska Plant Breeding in AntoninySelection of SobieszyńskiPL51622NCPGR1928/-Before 1945
3Antoniński ŻółtySandomiersko-Wielkopolska Plant Breeding in AntoninySelection of Von Lochow GelbPL51465NCPGR1928/-Before 1945
4ArabDANKO Plant Breeding, ChoryńBorys × Jawor-DANKO2004/2014After 2000
5BachmatDANKO Plant Breeding, ChoryńDula × Komes-DANKO2001/2007After 2000
6BajkaStrzelce Plant BreedingKR 8543 × [(Random × KR 316) × Perona]-Strzelce1997/20071970–1999
7Bartek Udycki‘Udycz’ CompanyAntoniński Żółty × ZnajdaPI285552USDABefore 1939 /1972Before 1945
8BerdyszDANKO Plant Breeding, Choryń(Dukat × SV87598) × Bajka-DANKO2008/2018After 2000
9Biały MazurMałopolska Plant Breeding in Skrzeszowice—KleszczyńscyLocal variety × Biały OrzełPL51466NCPGR1928/1973Before 1945
10Biały OrzełSveriges Ustadesforenigs Institution, SvalofVon Lochow Gelb × SiegerPL51467NCPGRBefore the war/-Before 1945
11BohunDANKO Plant Breeding, ChoryńLP 8675 × STH 110/86-DANKO2002/2012After 2000
12BorekStation of Plant Breeding, Borów(Selma × Avoine Grise D’hiver) × Udycz ŻółtyPL50043NCPGR1981/19891970–1999
13BorowiakStation of Plant Breeding, BorówGóral × Santor-MPB1998/20101970–1999
14BorutaStation of Plant Breeding, Borów[Rodney ABDHCR × (Astor × Flamingsweiss II)] × DulaPL50113NCPGR1982/19911970–1999
15BorynaStation of Plant Breeding, Borów[Rodney ABDHCR × (Astor × Flamingsweiss II)] × Dula-MPB1990/19991970–1999
16BorysStation of Plant Breeding, Borów(Dato × Po.39) × Pinto-MPB1991/19991970–1999
17BretonDANKO Plant Breeding, ChoryńSzakal × Expander-DANKO2007/2017After 2000
18BudrysDANKO Plant Breeding, ChoryńAdamo × CHD 792-DANKO2001/2005After 2000
19CackoStrzelce Plant BreedingAdam × Adamo-Strzelce2000/2010After 2000
20CekinStation of Plant Breeding, BorówPOB-W-2010/93 × Zlatak-MPB1999/20101970–1999
21CelerStation of Plant Breeding, BorówGóral × KR-KOR-MPB2000/2010After 2000
22ChwatStrzelce Plant BreedingDukat × (Flamingsnova × Swan)-Strzelce2000/2010After 2000
23CwałDANKO Plant Breeding, ChoryńBorys × Jawor-DANKO2001/2011After 2000
24DereszDANKO Plant Breeding, ChoryńMaro × MGH 978.2-DANKO2000/2010After 2000
25DragonStation of Plant Breeding, RogaczewoMGH 6374 × DiademPL50117NCPGR1982/20041970–1999
26DukatStrzelce Plant BreedingFagot × KR 2335/74 L.-Strzelce1991/20061970–1999
27FarysMałopolska Plant Breeding,
Polanowice		(Biały Mazur × Astor) × Cebeco 7511-MPB1989/19991970–1999
28FurmanDANKO Plant Breeding, ChoryńKwant × Jawor-DANKO2006/2016After 2000
29GermanStrzelce Plant BreedingSamanta × Alfred-Strzelce1991/20071970–1999
30GniadyDANKO Plant Breeding, ChoryńNoirine × Tropicale-DANKO2007/2017After 2000
31GóralStrzelce Plant BreedingBorek × Brutus-Strzelce1988/20071970–1999
32GrajcarStation of Plant Breeding, BorówKomes × KR 81-1122-MPB1997/20101970–1999
33HetmanDANKO Plant Breeding, ChoryńJawor × Semundo 212.1-DANKO1999/20071970–1999
34JagiełłoJ.Turnau in MikulicachSelection of Rychlik MikulickiPL51507NCPGRBefore 1939/Before 1945
35JaworDANKO Plant Breeding, ChoryńMGH0894.4 × (Mana × Leanda)-DANKO1994/20071970–1999
36Jubileuszowy WięcławickiBuszczyński and the sonsSelection of Antoniński ŻółtyPL52020NCPGRBefore 1939/Before 1945
37Kanarek MikulickiJ.Turnau in MikuliceSelection of JagiełłoPL51510NCPGR1923/-Before 1945
38KarolStrzelce Plant BreedingSTH 171 × Brutus-Strzelce1989/19961970–1999
39KasztanStation of Plant Breeding, BorówDawid × CHD 1685/84 or 83-MPB1999/20101970–1999
40KomesDANKO Plant Breeding, ChoryńMGH 61649 × Jaycce-DANKO1985/19991970–1999
41KoneserStrzelce Plant BreedingSzakal × (Jawor × Dukat)-Strzelce2007/2017After 2000
42KościeleckiBuszczyński and the sonsselection of Marczak WłosciańskiPL51933NCPGR1923/-Before 1945
43KrezusStrzelce Plant BreedingGóral × [(Flamingsnova × Swan mut.) × Dukat)]-Strzelce2005/2015After 2000
44KwantStrzelce Plant BreedingAlfred × Dula-Strzelce1992/20101970–1999
45LachStation of Plant Breeding,
Aleksandrówka		Vigor × Flamande de BlanchePL50122NCPGR1980/19871970–1999
46MarkusStation of Plant Breeding, RogaczewoAstor × PendekPL50118NCPGR1979/19881970–1999
47ModzurowskiKraków Plant BreedingSun II × Biały MazurPL51319NCPGR1969-19721945–1969
48Niemierczański NajwcześniejszyBuszczyński and the sonsSelection of Włościański z Podola PL51084NCPGR1893/-Before 1945
49PegazMałopolska Plant Breeding,
Polanowice		Auswuchsfester × BordeweissPL51217NCPGR1977/19811970–1999
50PłatekStrzelce Plant Breeding(Flamindsgold × Pendek) × LeandaPL50731NCPGR1986/19931970–1999
51Podkowa DłużewskiDłużew, Mińsko-Mazowiecki district-PL51227NCPGR1929/-Before 1945
52PolarStrzelce Plant Breeding(Ago × Ramiro) × (Płatek × Swan mut) × Caesar-Strzelce2002/2012After 2000
53ProporczykNational Plant Breeding InstitutionsSelection of FindlingPL51229NCPGRBefore 1939/-Before 1945
54Przeboj INational Plant Breeding InstitutionsSelection of FlamingsgoldPL52070NCPGR1962/-1945–1969
55Przeboj IIStation of Plants Selection in Jeżowo-Gola, Gostyń district Selection of FlamingstreuePL51924NCPGR1974/-1945–1969
56Puławski ŚredniorychłyState Research Institute of Rural Husbandry in PuławySelection of Pfiffelbacher GelbPL50406NCPGR1928/-Before 1945
57RajtarDANKO Plant Breeding, ChoryńRamiro × Jawor-DANKO2004/2014After 2000
58RumakStation of Plant Breeding, RogaczewoMGH 6374 × Flamingsweiss IIPL50120NCPGR1981/19871970–1999
59Rychlik OberekMałopolska Plant Breeding in Skrzeszowice (Kleszczyńscy brothers)Rychlik Podgórski × DogoldPL51233NCPGRBefore 1939/-Before 1945
60SamStrzelce Plant Breeding(Flamingsnova × Swan mut) × {[Alfred × (Garland × C2)] × Swan mut.}-Strzelce1999/20101970–1999
61SantorStrzelce Plant BreedingBorek × Brutus-Strzelce1989/19991970–1999
62SkrzatMałopolska Plant Breeding,
Polanowice		Komes × Maris Tabard-MPB1996/20041970–1999
63SławkoStrzelce Plant BreedingMustang × Swan mut.-Strzelce1993/20101970–1999
64SobieszyńskiAgricultural Experimental Station in SobieszynSelection of Rychlik LubelskiPL51261NCPGR1923/-Before 1945
65SprinterStrzelce Plant Breeding(Flamingsnova × Swan mut.) × Dukat-Strzelce2000/2010After 2000
66StoperStrzelce Plant Breeding(Flamingsnova × Swan mut.) × Dukat-Strzelce2003/2013After 2000
67SzakalStrzelce Plant Breeding(Flamingsnova × Swan mut.) × Dukat-Strzelce2000/2010After 2000
68Teodozjabreeded in Łęki by M.Rożański/Czarnecki, Kutnowski districtSelection of Scottish oatPL50976NCPGR1923/-Before 1945
69Udycz BiałyUdycz’ company in KwasówKanarek Mikulicki × SiegerPL51051NCPGR1925/-Before 1945
70Udycz ŻółtyUdycz’ company in KwasówPflugs Gelb × Von Lochow GelbPL51050NCPGRBefore 1939/1976Before 1945
71UłanDANKO Plant Breeding, ChoryńWIR 1714 × DiademPL51449NCPGR1985/19901970–1999
72ZuchDANKO Plant Breeding, ChoryńVusch × Szakal-DANKO2008/2018After 2000
Table
Table 2. Summary statistics of diversity within groups created based on breeding time and breeding company.
Table 2. Summary statistics of diversity within groups created based on breeding time and breeding company.
ISSRREMAP
No. of Fragments% Polymorphic FragmentsNo. of Private FragmentsuHeSENo. of Fragments% Polymorphic FragmentsNo. of Private FragmentsuHeSE
Total20399.51%-0.2560.01217887.08%-0.3080.012
Breeding timeBefore 194517065.02%40.1920.01415566.29%20.2360.015
1945–196911919.21%10.1060.01512628.65%00.1580.019
1970–200018985.22%130.2360.01317388.20%110.2860.014
After 200017072.41%10.2240.01416081.46%20.2890.014
Breeding companyStrzelce Plant Breeding Company17979.31%50.2410.01416380.90%50.2830.015
DANKO Plant Breeding, Choryń16767.49%20.2140.01415879.78%30.2880.015
Station of Plant Breeding, Rogaczewo13338.92%00.1730.01613546.63%00.2110.018
Małopolska Plant Breeding Company14141.38%20.1550.01514155.06%00.2350.018
Station of Plant Breeding, Borów15554.19%00.1880.01515064.61%40.2440.016
Other17267.98%40.1980.01315567.42%40.2390.015
Table
Table 3. Results of the analysis of molecular variance (AMOVA). Pairwise ΦPT values for groupings according to breeding time (p < 0.001) of ISSRs (above diagonal) and REMAPs (below diagonal).
Table 3. Results of the analysis of molecular variance (AMOVA). Pairwise ΦPT values for groupings according to breeding time (p < 0.001) of ISSRs (above diagonal) and REMAPs (below diagonal).
before 19451945–19691970–2000after 2000
before 1945xns0.0910.131
1945–1969nsx0.1100.141
1970–20000.116nsx0.047
after 20000.109ns0.021x
ns—Not significant.
Table
Table 4. Results of the analysis of molecular variance (AMOVA). Pairwise ΦPT values for groupings according to the breeding company (p < 0.001) of ISSRs (above diagonal) and REMAPs (below diagonal).
Table 4. Results of the analysis of molecular variance (AMOVA). Pairwise ΦPT values for groupings according to the breeding company (p < 0.001) of ISSRs (above diagonal) and REMAPs (below diagonal).
OtherStrzelce Plant Breeding CompanyDANKO Plant Breeding, ChoryńStation of Plant Breeding, RogaczewoMałopolska Plant Breeding CompanyStation of Plant Breeding, Borów
Otherx0.1170.1310.1140.0930.108
Strzelce Plant Breeding Company0.104xnsnsnsns
DANKO Plant Breeding, Choryń0.1240.020xnsnsns
Station of Plant Breeding, Rogaczewo0.123nsnsxnsns
Małopolska Plant Breeding Company0.102nsnsnsxns
Station of Plant Breeding, Borów0.1660.043nsnsnsx
ns—Not significant.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Koroluk, A.; Paczos-Grzęda, E.; Sowa, S.; Boczkowska, M.; Toporowska, J. Diversity of Polish Oat Cultivars with a Glance at Breeding History and Perspectives. Agronomy 2022, 12, 2423. https://doi.org/10.3390/agronomy12102423

AMA Style

Koroluk A, Paczos-Grzęda E, Sowa S, Boczkowska M, Toporowska J. Diversity of Polish Oat Cultivars with a Glance at Breeding History and Perspectives. Agronomy. 2022; 12(10):2423. https://doi.org/10.3390/agronomy12102423

Chicago/Turabian Style

Koroluk, Aneta, Edyta Paczos-Grzęda, Sylwia Sowa, Maja Boczkowska, and Joanna Toporowska. 2022. "Diversity of Polish Oat Cultivars with a Glance at Breeding History and Perspectives" Agronomy 12, no. 10: 2423. https://doi.org/10.3390/agronomy12102423

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop