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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Plant Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Plant Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-462X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpls.2025.1731515</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Mini Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Morphological and genetic diversity of <italic>Beta maritima</italic> populations across Europe and North Africa: a comprehensive review</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Bertram</surname><given-names>Lisa</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3069209/overview"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
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<contrib contrib-type="author">
<name><surname>Frisch</surname><given-names>Matthias</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
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<aff id="aff1"><label>1</label><institution>Institute of Agronomy and Plant Breeding II, Justus Liebig University</institution>, <city>Giessen</city>,&#xa0;<country country="de">Germany</country></aff>
<aff id="aff2"><label>2</label><institution>KWS SAAT SE &amp; Co. KGaA</institution>, <city>Einbeck</city>,&#xa0;<country country="de">Germany</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Lisa Bertram, <email xlink:href="mailto:lisa.bertram@ag.uni-giessen.de">lisa.bertram@ag.uni-giessen.de</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-15">
<day>15</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1731515</elocation-id>
<history>
<date date-type="received">
<day>24</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>03</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>27</day>
<month>11</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Bertram and Frisch.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Bertram and Frisch</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-15">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<p><italic>Beta vulgaris</italic> ssp. <italic>maritima</italic> (sea beet), the wild ancestor of cultivated beet, represents a key reservoir of adaptive genetic diversity for sugar beet breeding. This review synthesizes research on morphological and genetic variation of <italic>Beta maritima</italic> populations across Europe and North Africa to (1) summarize regional diversity patterns, (2) assess the correspondence between phenotypic traits and genetic structure, and (3) identify knowledge gaps. Morphological studies show wide variation in sea beet. Growth habits range from prostrate to erect. Coastal plants often have thicker leaves and prostrate forms while inland types are adapted for water efficiency. Traits like pigmentation, inflorescence, and root shape also differ, reflecting adaptation to local environments. Bolting and flowering occur early in Mediterranean populations but are delayed in northern regions. Genetic analyses further identify a distinct Atlantic/Mediterranean divide. Mediterranean populations exhibit greater genetic diversity, while Baltic populations show low diversity and high homogeneity, presumably due to recent establishment and founder effects. Comparative findings suggest phenotypic variation often exceeds genetic differentiation and is strongly influenced by environmental factors. This review identifies research gaps among sea beet populations in Mediterranean regions particularly along the southern and eastern coasts of Spain, Italy, Greece, Turkey, and the eastern Mediterranean. As the first comprehensive review focused solely on <italic>Beta maritima in-situ</italic> populations, this work delivers a full account of the regions, traits, and genetic patterns studied to date. It establishes a foundation for future research and is an indispensable resource for advancing breeding, conservation, and scientific understanding of this important wild relative.</p>
</abstract>
<kwd-group>
<kwd><italic>Beta vulgaris</italic> ssp. <italic>maritima</italic></kwd>
<kwd>crop wild relatives</kwd>
<kwd>genetic diversity</kwd>
<kwd>genetic resources</kwd>
<kwd>sea beet</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This research was funded by KWS SAAT SE &amp; Co. KGaA, Einbeck, Germany.</funding-statement>
</funding-group>
<counts>
<fig-count count="2"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="37"/>
<page-count count="10"/>
<word-count count="4706"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Plant Breeding</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p><italic>Beta maritima</italic> (<italic>Beta vulgaris</italic> ssp. m<italic>aritima</italic> (L.) Arcang.; sea beet), the wild ancestor of cultivated beet, is the most widespread taxon within the genus <italic>Beta</italic> (<xref ref-type="bibr" rid="B23">Frese and Ford-Lloyd, 2020</xref>; <xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>). Its origin is traced to the Mediterranean region (<xref ref-type="bibr" rid="B31">Romeiras et&#xa0;al., 2016</xref>). Its distribution covers nearly all Mediterranean coastal countries, several Atlantic islands, and much of the Atlantic coast of Europe (<xref ref-type="bibr" rid="B23">Frese and Ford-Lloyd, 2020</xref>; <xref ref-type="bibr" rid="B36">Veloso et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>). Following the last glacial period, Be<italic>ta maritima</italic> expanded northward, establishing populations along the Atlantic and North Sea coasts (<xref ref-type="bibr" rid="B15">Doney et&#xa0;al., 1990</xref>; <xref ref-type="bibr" rid="B11">Boudry et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B21">Fievet et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B27">Monteiro et&#xa0;al., 2013</xref>). Some populations are large and well-established, while others are small and scattered, reflecting both historical dispersal and recent colonization events (<xref ref-type="bibr" rid="B24">Letschert, 1993</xref>; <xref ref-type="bibr" rid="B16">Driessen, 2003</xref>; <xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B23">Frese and Ford-Lloyd, 2020</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Map showing the general distribution of <italic>Beta maritima</italic> along the seashores within its main distribution area in Europe and Northern Africa (blue: frequent; purple: sparse). The map was generated using GoogleEarthPro. Adapted from <xref ref-type="bibr" rid="B23">Frese and Ford-Lloyd (2020)</xref>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-16-1731515-g001.tif">
<alt-text content-type="machine-generated">Satellite map of Europe and parts of North Africa, showing coastlines highlighted in two colors. Light blue represents frequent distribution and outlines the Mediterranean region, while magenta lines show sparse distribution and marks parts of Northern Europe.</alt-text>
</graphic></fig>
<p>The broad distribution of <italic>Beta maritima</italic> reflects its evolutionary success and its ecological adaptability. It thrives in highly variable and often harsh coastal habitats, including salt marshes, beaches, and inland ruderal sites (<xref ref-type="bibr" rid="B15">Doney et&#xa0;al., 1990</xref>; <xref ref-type="bibr" rid="B33">Stevanato et&#xa0;al., 2001</xref>). This environmental heterogeneity, combined with strong local selection pressures, drives high morphological variation within and among populations (<xref ref-type="bibr" rid="B34">Toll and Hendriksen, 1982</xref>; <xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>; <xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>). Traits such as growth habit, leaf morphology, and bolting behavior are shaped by adaptation to salinity, drought, and temperature extremes (<xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>; <xref ref-type="bibr" rid="B18">El Manhaly et&#xa0;al., 1996</xref>; <xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>). The species&#x2019; ability to colonize diverse habitats and maintain dynamic, <italic>in-situ</italic> populations preserves adaptive alleles that may be lost in <italic>ex-situ</italic> collections (<xref ref-type="bibr" rid="B10">Bohra et&#xa0;al., 2021</xref>).</p>
<p>Understanding the diversity of wild crop relatives like <italic>Beta maritima</italic> is essential for conservation and breeding efforts. Sea beet populations provide a reservoir of adaptive genetic variation, contributing valuable traits to sugar beet improvement (<xref ref-type="bibr" rid="B22">Frese et&#xa0;al., 1990</xref>; <xref ref-type="bibr" rid="B28">Panella et&#xa0;al., 2020</xref>). Over the past decades, numerous studies have documented the morphological variation among sea beet populations. In parallel to morphological investigations, advances in molecular genetics have enabled deeper insights into the population structure and genetic diversity of <italic>Beta maritima</italic>.</p>
<p>This review provides an overview of current research on the morphological and genetic diversity of <italic>Beta maritima</italic> populations across Europe and North Africa. It aims to (1) summarize regional patterns of morphological and genetic variation, (2) evaluate the relationship between observed phenotypic traits and underlying genetic structure, and (3) identify knowledge gaps and underexplored populations to support the utilization of <italic>Beta maritima</italic> as a genetic reservoir for sustainable sugar beet improvement.</p>
</sec>
<sec id="s2">
<title>Morphological variation</title>
<p>Morphological diversity in <italic>Beta maritima</italic> has been extensively studied, with numerous investigations exploring how geographic and environmental factors shape variation within and among populations (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). Across its native range, sea beet populations exhibit pronounced variability in growth habit, leaf morphology, inflorescence structure, pigmentation, and root traits (<xref ref-type="bibr" rid="B34">Toll and Hendriksen, 1982</xref>; <xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>; <xref ref-type="bibr" rid="B33">Stevanato et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Summary of morphological diversity in <italic>Beta maritima</italic> populations examined across different studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Traits examined</th>
<th valign="middle" align="left">Patterns of variation and key findings</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B34">Toll and Hendriksen, 1982</xref> (Italy)</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left">&#x25aa;&#x2003;High variability in growth habit, leaf size, inflorescence, seedball size, and pigmentation<break/>&#x25aa;&#x2003;Variation in root tapering and side root number<break/>&#x25aa;&#x2003;Greater variation between populations than within<break/>&#x25aa;&#x2003;Morphology strongly linked to environment:<break/>&#x2003;&#x2003;&#x25aa;&#x2003;Dry sites: small plants with thick leaves<break/>&#x2003;&#x2003;&#x25aa;&#x2003;Open habitats: procumbent or prostrate growth</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B15">Doney et&#xa0;al., 1990</xref> (England, Ireland, North Ireland, Wales)</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left">&#x25aa;&#x2003;British Isles sea beets: few leaf hairs, heavy waxy cuticle, very green appearance<break/>&#x25aa;&#x2003;Life cycle variation: annual and perennial forms observed; some populations highly uniform, others highly variable (older, established)<break/>&#x25aa;&#x2003;Greater morphological differences with increasing distance and geographic barriers</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B22">Frese et&#xa0;al., 1990</xref> (Portugal, Spain)</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left">&#x25aa;&#x2003;Growth habit varied: erect types frequent on Iberian Peninsula<break/>&#x25aa;&#x2003;Plant size highly variable; old populations produced large seed quantities<break/>&#x25aa;&#x2003;Despite geographic barriers, little morphological differentiation - spatial separation does not seem to prevent gene flow<break/>&#x25aa;&#x2003;Bay of Aerosa: exceptionally high morphological variability observed; may result from admixture of South and North Atlantic gene pools</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref> (Italy)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>15 morphological characters:</italic> pigmentation, leaf pubescence, bract shape, multigermicity, growth habit, flowering stage (2 periods), lamina (length, width, thickness), petiole (length, width), stem diameter, biomass (fresh weight), plant height</td>
<td valign="middle" align="left">&#x25aa;&#x2003;High variation in lamina length, width, and thickness, petiole length and width, stem diameter, biomass, plant height, flowering (both periods)<break/>&#x25aa;&#x2003;Tendency for decreasing leaf length and width from north to south<break/>&#x25aa;&#x2003;No single trait reflected clear regional pattern<break/>&#x25aa;&#x2003;Significant differences between adjacent populations; coastal populations showed large fluctuations<break/>&#x25aa;&#x2003;Inland vs. maritime groups differed for some characters</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B18">El Manhaly et&#xa0;al., 1996</xref> (Egypt)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>18 morphological characters:</italic> growth habit, leaf (erectness, hairiness, thickness), leaf blade (length, width, pigmentation), petiole (length, width), petiole color, hypocotyl pigmentation, external root color, main color flesh, root shape, flower stern pigmentation, male sterility, multigermicity, bolting tendency<break/><italic>9 evaluators for resistance:</italic> curly top, Rhizoctonia, leaf spot, cyst nematode, root aphid, Rhizomania, virus yellows, root maggot, Aphanomyces</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Variation in growth habit, bolting behavior, leaf shape, roots<break/>&#x25aa;&#x2003;Two main groups identified:<break/>&#x2003;&#x2003;&#x25aa;&#x2003;Delta: prostrate, small thick leaves, no leaf hair<break/>&#x2003;&#x2003;&#x25aa;&#x2003;Luxor/Fayum: segregating for leaf size, growth habit, root swelling, bolting, and red types<break/>&#x25aa;&#x2003;Inland types had longer, narrower petioles and less succulent leaves than coastal types<break/>&#x25aa;&#x2003;Bolting occurred very early, complicating disease resistance scoring<break/>&#x25aa;&#x2003;Moderate curly top resistance found in Fayum/Luxor accessions; root aphid resistance noted in some populations</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B6">Bartsch and Schmidt, 1997</xref> (Italy)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>8 morphological characters:</italic> bigermity, hypocotyl color, leaf (color, pubescence), pollen sterility, seed (cluster weight, emergence), annuality</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Differentiation into three types based on morphological characters<break/>&#x25aa;&#x2003;Evidence of hybridization between wild beets and cultivars found (i.e. supported by bigermous individuals, low proportion of annual individuals [26.5%] among offspring)</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B35">Van Dijk et&#xa0;al., 1997</xref> (Belgium, England, France, Guernsey, Jersey)</th>
</tr>
<tr>
<td valign="top" align="left">vernalization requirements, sensitivity for vernalizing factors, flowering date</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Strong variation in flowering time is linked to latitude and vernalization requirement (mainly determined by a single gene <italic>B/b</italic> and quantitative trait loci)<break/>&#x25aa;&#x2003;Southern populations: high frequency of <italic>B</italic> allele (no vernalization needed); northern populations: strong vernalization requirement<break/>&#x25aa;&#x2003;High heritability (0.33) for flowering time &#x2192; potential for evolutionary change.</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B33">Stevanato et&#xa0;al., 2001</xref> (Italy)</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left">&#x25aa;&#x2003;Significant morphological variability in leaf shape and size; deep green leaves, occasional red streaks<break/>&#x25aa;&#x2003;Variability in the reproductive structure (seed stalks)<break/>&#x25aa;&#x2003;Populations showed resistance to Cercospora and Rhizomania</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B11">Boudry et&#xa0;al., 2002</xref> (Belgium, France, The Channel Islands)</th>
</tr>
<tr>
<td valign="top" align="left">Vernalization requirements, flowering response to cold periods at young seedling stage</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Vernalization requirement increased with latitude; northern plants require more vernalization<break/>&#x25aa;&#x2003;Young seedlings more difficult to vernalize than plants which already developed vegetative rosettes<break/>&#x25aa;&#x2003;Penetrance of the annual habit in <italic>Bb</italic> genotypes was affected by both environmental and genetic factors</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B5">Ascarini et&#xa0;al., 2021</xref> (Portugal)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>11 morphological characters:</italic> number of basel stems, plant height, inflorescence height, distance of the first branch from the basis, number of branches, leaf (length, width), petiole (length, width), stem diameter, average number of glomerulus per branch</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Morphological characterization showed a high quantitative variation among populations<break/>&#x25aa;&#x2003;Plant height and inflorescence height parameters had the highest influence in the separation of populations<break/>&#x25aa;&#x2003;Populations in less exposed sites tend to have bigger and more developed aerial parts; plants closer to the sea or under dry/saline conditions are more prostrate with smaller leaves</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref> (Egypt)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>35 morphological characters:</italic> plant length, stalk (length, diameter), number of branches/stalk, branch length, lower &amp; upper leaf lamina (length, width), lower &amp; upper leaf petiole (length, width), inflorescence bract lamina (length, width), inflorescence bract petiole (length, width), lower &amp; upper glomerule bract lamina (length, width), lower &amp; upper glomerule bract petiole (length, width), lower &amp; upper glomerule (length, width), lower &amp; upper glomerule bract length/glomerule length, inflorescence/branch, number of glomerule/inflorescence, number of flowers/glomerule</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Notable morphological diversity observed within and among populations<break/>&#x25aa;&#x2003;Significant differences in 17 of 35 traits; branch length and inflorescence traits showed highest variability<break/>&#x25aa;&#x2003;Two groups identified:<break/>&#x2003;&#x2003;&#x25aa;&#x2003;<italic>var. glabra:</italic> glabrous, erect, large basal leaves<break/>&#x2003;&#x2003;&#x25aa;&#x2003;<italic>var. pilosa:</italic> hairy, prostrate, smaller basal leaves<break/>&#x25aa;&#x2003;Soil parameters significantly influenced population morphological variability; especially strong correlation to soil organic carbon</td>
</tr>
<tr>
<th valign="middle" colspan="2" align="left"><xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref> (Tunisia)</th>
</tr>
<tr>
<td valign="top" align="left"><italic>23 morphological characters:</italic> growth habit, stem (color, pigmentation, hairiness), leaf (color, pigmentation, curliness, hairiness, shape, blade length, blade width), petiole (color, length, width), cuticle thickness, bract (shape, thickness), inflorescence (color, height), multigermicity, flowering pattern between plants, glomerule diameter, 1000 seed weight</td>
<td valign="middle" align="left">&#x25aa;&#x2003;Substantial morphological variability within and between populations<break/>&#x25aa;&#x2003;Traits like glomerule diameter, seed weight, and inflorescence height showed high between-population variability<break/>&#x25aa;&#x2003;Island populations: prostrate habit, red inflorescences<break/>&#x25aa;&#x2003;Mainland populations: erect habit, hairy curly leaves<break/>&#x25aa;&#x2003;Strong phenotypic plasticity; Adaptation to harsh conditions (salinity, heat, drought) evident, i.e. reducing leaf size allows plants to reduce water loss by evapotranspiration</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>The table lists the main traits analyzed, key findings, and principal patterns of variation observed within each study. Countries in brackets indicate the origin of the analyzed populations.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Morphological differentiation is strongly influenced by environmental factors. Traits such as plant size, leaf thickness, and growth form are strongly linked to habitat conditions. Plants in dry or exposed environments tend to be smaller with thicker leaves, while those in open, resource-rich habitats often develop more expansive, procumbent forms (<xref ref-type="bibr" rid="B34">Toll and Hendriksen, 1982</xref>; <xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>). Exposure to stressors like high salinity, drought, or heat further drives adaptive changes, including reduced leaf size and increased cuticle thickness (<xref ref-type="bibr" rid="B7">Ben Mahmoud et&#xa0;al., 2025</xref>). Soil properties, especially organic carbon content, also significantly influence morphological variability (<xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>).</p>
<p>A consistent pattern emerges when comparing inland and coastal populations. Inland types typically have longer, narrower petioles and less succulent leaves, whereas coastal populations display shorter, thicker leaves and a more prostrate growth habit (<xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>; <xref ref-type="bibr" rid="B18">El Manhaly et&#xa0;al., 1996</xref>). Coastal populations are also more likely to bolt and flower early, while inland types often show delayed generative development. These patterns reflect adaptation to contrasting environmental pressures. Coastal habitats favor compact, robust morphology, while inland environments select for traits that enhance water use efficiency and competitive ability (<xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>; <xref ref-type="bibr" rid="B18">El Manhaly et&#xa0;al., 1996</xref>).</p>
<p>The extent to which morphological variation correlates with geography is variable. Some studies report substantial diversity within short coastal stretches (<xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>), while others find only minor divergence across broader regions (<xref ref-type="bibr" rid="B25">Letschert and Frese, 1993</xref>). In the British Isles, morphological variation increases with geographic distance and physical barriers, highlighting the influence of dispersal mechanisms and environmental heterogeneity (<xref ref-type="bibr" rid="B15">Doney et&#xa0;al., 1990</xref>).</p>
<p>A clear distinction is observed between Atlantic and Mediterranean populations. Mediterranean populations generally exhibit greater morphological and genetic diversity, with a wider range of growth forms and adaptive traits, while Atlantic populations, especially those in the Baltic and North Sea regions, are more uniform and often display traits associated with recent colonization and founder effects (<xref ref-type="bibr" rid="B22">Frese et&#xa0;al., 1990</xref>; <xref ref-type="bibr" rid="B30">Richards et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>). This regional contrast is also reflected in the frequency of key adaptive alleles, such as gene <italic>B</italic>, which controls vernalization requirement and flowering time. The <italic>B</italic> allele, which eliminates the need for vernalization and promotes early bolting, is frequent in Mediterranean populations but largely absent in northern populations, contributing to the observed differences in life history strategies (<xref ref-type="bibr" rid="B35">Van Dijk et&#xa0;al., 1997</xref>; <xref ref-type="bibr" rid="B11">Boudry et&#xa0;al., 2002</xref>).</p>
<p>Much of this diversity is attributable to phenotypic plasticity &#x2013; <italic>Beta maritima&#x2019;s</italic> ability to adapt its morphology in response to environmental variation (<xref ref-type="bibr" rid="B29">Ribeiro et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B5">Ascarini et&#xa0;al., 2021</xref>). Nevertheless, genetic control is also evident, as shown by the identification of major genes (e.g. gene <italic>B</italic>) and quantitative trait loci affecting flowering and growth (<xref ref-type="bibr" rid="B35">Van Dijk et&#xa0;al., 1997</xref>; <xref ref-type="bibr" rid="B11">Boudry et&#xa0;al., 2002</xref>). The interplay between plasticity and genetic differentiation complicates the interpretation of regional patterns and underscores the need for integrative approaches.</p>
<p>Beyond basic morphology, few studies also described variation in agronomically relevant traits such as disease resistance and stress tolerance. For example, resistance to important pathogens such as Cercospora leaf spot and Rhizomania has been documented in certain wild populations (<xref ref-type="bibr" rid="B33">Stevanato et&#xa0;al., 2001</xref>). Moderate resistance to curly top virus and root aphid has also been identified in populations from Egypt (<xref ref-type="bibr" rid="B18">El Manhaly et&#xa0;al., 1996</xref>). However, most findings are based on phenotypic screening rather than genetic confirmation. Nevertheless, these findings underscore the value of <italic>Beta maritima</italic> as a genetic resource for breeding programs, offering a reservoir of adaptive traits that can be harnessed to improve stress tolerance and disease resistance in cultivated beets.</p>
</sec>
<sec id="s3">
<title>Genetic diversity</title>
<p>Following extensive research on morphological variation in wild sea beet, recent studies have increasingly focused on genetic diversity and population structure using molecular techniques (see <xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref> for an overview of diversity measures across studies). These genetic analyses have uncovered both broad-scale patterns and distinct regional differences within <italic>Beta maritima</italic> populations. Importantly, genetic differentiation across Europe and North Africa reflects a complex, multi-layered process. Rather than being determined solely by geographic distance, population structure in <italic>Beta maritima</italic> populations is shaped by a combination of historical events, dispersal mechanisms, and environmental heterogeneity.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Overview of diversity measures reported across studies. .</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="left">Study</th>
<th valign="middle" colspan="12" align="left">Country</th>
<th valign="middle" rowspan="2" align="left">Number and type of genetic marker</th>
<th valign="middle" rowspan="2" align="left">N<sub>A</sub><break/></th>
<th valign="middle" rowspan="2" align="left">A<sub>R</sub><break/></th>
<th valign="middle" rowspan="2" align="left">N<sub>P</sub><break/></th>
<th valign="middle" rowspan="2" align="left">H'<break/></th>
<th valign="middle" rowspan="2" align="left">H<sub>O</sub><break/></th>
<th valign="middle" rowspan="2" align="left">H<sub>E</sub><break/></th>
<th valign="middle" rowspan="2" align="left">F<sub>IT</sub><break/></th>
<th valign="middle" rowspan="2" align="left">F<sub>ST</sub><break/></th>
<th valign="middle" rowspan="2" align="left">F<sub>IS</sub><break/></th>
</tr>
<tr>
<th valign="middle" align="left">SE</th>
<th valign="middle" align="left">DK</th>
<th valign="middle" align="left">DE</th>
<th valign="middle" align="left">IE</th>
<th valign="middle" align="left">NL</th>
<th valign="middle" align="left">GG</th>
<th valign="middle" align="left">JE</th>
<th valign="middle" align="left">FR</th>
<th valign="middle" align="left">PT</th>
<th valign="middle" align="left">ES</th>
<th valign="middle" align="left">IT</th>
<th valign="middle" align="left">MA</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B14">Desplanque et&#xa0;al., 1999</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">5 RFLP &amp; 1 microsatellite</td>
<td valign="middle" align="left">3 &#x2013; 26</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.508 &#x2013; 0.796</td>
<td valign="middle" align="left">0.609 &#x2013; 0.900</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.020 &#x2013; 0.204</td>
<td valign="middle" align="left">0.085* &#x2013; 0.318**</td>
</tr>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B17">Driessen et&#xa0;al., 2001</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">75 RAPD-PCR fragment loci</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">8.1 &#x2013; 27.0</td>
<td valign="middle" align="left">0.046 &#x2013; 0.144</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B16">Driessen, 2003</xref></td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">78 RAPD-PCR fragment loci &amp; 1 AFLP</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">6.4 &#x2013; 34.6</td>
<td valign="middle" align="left">0.038 &#x2013; 0.182</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref></td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">8 SSR</td>
<td valign="middle" align="left">1 &#x2013; 8</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.040 &#x2013; 1.000</td>
<td valign="middle" align="left">0.040 &#x2013; 0.810</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">(0.310***)</td>
<td valign="middle" align="left">-0.800* &#x2013; 0.530<sup>NS</sup></td>
</tr>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B21">Fievet et&#xa0;al., 2007</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">7 micro- &amp; 4 minisatellites</td>
<td valign="middle" align="left">3.85 &#x2013; 7.14</td>
<td valign="middle" align="left">3.350 &#x2013; 5.580</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.410 &#x2013; 0.600</td>
<td valign="middle" align="left">0.086*** &#x2013; 0.207*** (0.151***)</td>
<td valign="middle" align="left">0.015<sup>NS</sup> &#x2013; 0.119*** (0.089***)</td>
<td valign="middle" align="left">-0.012<sup>NS</sup> &#x2013; 0.100*** (0.068***)</td>
</tr>
<tr>
<td valign="middle" align="left" style=""><xref ref-type="bibr" rid="B20">F&#xe9;nart et&#xa0;al., 2008</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">5 micro-, 4 minisatellites &amp; 1 PCR-RFLP</td>
<td valign="middle" align="left">1 &#x2013; 6</td>
<td valign="middle" align="left">1.000 &#x2013; 5.410</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.000 &#x2013; 0.880</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.147***</td>
<td valign="middle" align="left">-0.441<sup>NS</sup> &#x2013; 0.439***</td>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B26">Leys et&#xa0;al., 2014</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">8 micro- &amp; 4 minisatellite</td>
<td valign="middle" align="left">3 &#x2013; 56</td>
<td valign="middle" align="left">3.650 &#x2013; 12.043</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.418 &#x2013; 0.831</td>
<td valign="middle" align="left">0.132* &#x2013; 0.223*</td>
<td valign="middle" align="left">0.126* &#x2013; 0.177*</td>
<td valign="middle" align="left">0.007<sup>NS</sup> &#x2013; 0.087*</td>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B30">Richards et&#xa0;al., 2014</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">13 SSR</td>
<td valign="middle" align="left">3 &#x2013; 31</td>
<td valign="middle" align="left">2.020 &#x2013; 6.320</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.290 &#x2013; 0.690</td>
<td valign="middle" align="left">0.400 &#x2013; 0.690</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">(0.140)</td>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B29">Ribeiro et&#xa0;al., 2016</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">6 SSR</td>
<td valign="middle" align="left">3 &#x2013; 15</td>
<td valign="middle" align="left">7.670 &#x2013; 10.170</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.480 &#x2013; 0.906</td>
<td valign="middle" align="left">0.300 &#x2013; 0.900</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.019 &#x2013; 0.121 (0.052)</td>
<td valign="middle" align="left"/>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B5">Ascarini et&#xa0;al., 2021</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">8 SSR</td>
<td valign="middle" align="left">22 &#x2013; 38</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.856 &#x2013; 1.381</td>
<td valign="middle" align="left">0.400 &#x2013; 0.650</td>
<td valign="middle" align="left">0.575 &#x2013; 0.787</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">-0.423 &#x2013; 0.622 (0.186)</td>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B36">Veloso et&#xa0;al., 2021</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">6 SSR</td>
<td valign="middle" align="left">7 &#x2013; 25</td>
<td valign="middle" align="left">2.333 &#x2013; 10.167</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.044 &#x2013; 0.783</td>
<td valign="middle" align="left">0.074 &#x2013; 0.789</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.000 &#x2013; 0.277</td>
<td valign="middle" align="left">-0.041 &#x2013; 0.287</td>
</tr>
<tr>
<td valign="middle" align="left"><xref ref-type="bibr" rid="B8">Bertram et&#xa0;al., 2025a</xref></td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">X</td>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style=""/>
<td valign="middle" align="left" style="">16,201 SNPs</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left">0.099 &#x2013; 0.167</td>
<td valign="middle" align="left">0.430 &#x2013; 0.780</td>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Countries from which populations were examined, SE, Sweden; DK, Denmark; DE, Germany; IE, Ireland; NL, The Netherlands; GG, Guernsey; JE, Jersey; FR, France; PT, Portugal; ES, Spain; IT, Italy; MA, Morocco. Diversity measures include N<sub>A</sub>, number of alleles per locus; A<sub>R</sub>, allelic richness; N<sub>P</sub>, polymorphic fragments (%); H&#x2032;, Shannon Index; H<sub>O</sub>, observed heterozygosity; H<sub>E</sub>, expected heterozygosity; and F-statistics (F<sub>IT</sub>; F<sub>ST</sub>; F<sub>IS</sub>). Ranges of minimum and maximum values are shown; mean values are provided in brackets where available. Significance levels; if specified in the original studies: * = p &lt; 0.05; ** = p &lt; 0.01; *** = p &lt; 0.001; NS, non-significant.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>A key pattern of variation, the Atlantic&#x2013;Mediterranean divide, originates from glacial history. Mediterranean regions acted as refugia during the last glacial period, preserving high allelic richness and heterozygosity. Northern populations on the other hand were recolonized more recently, resulting in reduced diversity and greater genetic uniformity within these populations (<xref ref-type="bibr" rid="B17">Driessen et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B16">Driessen, 2003</xref>; <xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>). Comparative studies confirm that Mediterranean populations hold more alleles and show stronger substructure, whereas Northern Atlantic and Baltic groups exhibit high gene flow and low differentiation (<xref ref-type="bibr" rid="B14">Desplanque et&#xa0;al., 1999</xref>; <xref ref-type="bibr" rid="B26">Leys et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B30">Richards et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B36">Veloso et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B8">Bertram et&#xa0;al., 2025a</xref>).</p>
<p>Specifically Baltic and North Sea populations exhibit genetic homogeneity and low polymorphism, reflecting founder effects and bottlenecks associated with recent colonization and seed dispersal via ocean currents (<xref ref-type="bibr" rid="B17">Driessen et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B16">Driessen, 2003</xref>). Danish and Swedish populations show high gene flow and no internal structure, consistent with wind pollination and long-distance dispersal (<xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B8">Bertram et&#xa0;al., 2025a</xref>). These northern groups remain distinct from Mediterranean and Atlantic populations, reflecting their restricted genetic base and recent origin.</p>
<p>Different dispersal mechanisms also influence population structure. Coastal populations showed strong geographic clustering shaped by marine currents (<xref ref-type="bibr" rid="B26">Leys et&#xa0;al., 2014</xref>). Inland ruderal populations exhibit more complex genetic structures due to admixture and human activities, such as soil and plant movement and habitat modification (<xref ref-type="bibr" rid="B24">Letschert, 1993</xref>; <xref ref-type="bibr" rid="B26">Leys et&#xa0;al., 2014</xref>). These actions introduce and mix genetically distinct individuals, increasing gene flow and hybridization, and disrupting clear geographic genetic patterns. Nuclear genes, spread by both pollen and seeds, enable broader gene flow and genetic mixing across regions. In contrast, mitochondrial genes, dispersed only through seeds, are more restricted in their movement, resulting in stronger spatial genetic structuring (<xref ref-type="bibr" rid="B20">F&#xe9;nart et&#xa0;al., 2008</xref>). For example, along the French Atlantic and Channel coasts, an asymmetric gene flow shaped by marine currents and differences in nuclear versus cytoplasmic dispersal was observed (<xref ref-type="bibr" rid="B21">Fievet et&#xa0;al., 2007</xref>). This demonstrates how the mode of gene transmission shapes genetic patterns in wild plant populations.</p>
<p>Within these broader patterns, distinct regional variations introduce additional complexity. Admixture signals, such as clustering between French Atlantic and Corsican individuals, highlight ongoing connectivity despite distance (<xref ref-type="bibr" rid="B30">Richards et&#xa0;al., 2014</xref>). Similar dynamics occur in Iberian and Macaronesian systems, where marine currents and isolation create admixture gradients. Northern groups are more differentiated, while southern and insular populations form mixing zones (<xref ref-type="bibr" rid="B36">Veloso et&#xa0;al., 2021</xref>).</p>
<p>Environmental heterogeneity also plays a role in genetic differentiation of populations. For instance, the presence of mixed ploidy levels in Portuguese <italic>Beta</italic> taxa (<xref ref-type="bibr" rid="B13">Castro et&#xa0;al., 2013</xref>) and the high genetic diversity found in salt marsh populations (<xref ref-type="bibr" rid="B29">Ribeiro et&#xa0;al., 2016</xref>) point to a strong adaptive potential linked to diverse habitats. Such habitat heterogeneity creates a mosaic of selective pressures, fostering local adaptation and maintaining genetic variation. Additionally, the pronounced variability observed in Madeira and Porto Santo demonstrates that environmental selection can sometimes override the effects of geographic distance, leading to distinct population characteristics even within relatively small regions (<xref ref-type="bibr" rid="B5">Ascarini et&#xa0;al., 2021</xref>).</p>
<p>Overall, geographic distance alone is an unreliable proxy for genetic differentiation. Population structure results from glacial history, dispersal mechanisms, and ecological selection.</p>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>Research on sea beet populations has progressed from early morphological studies to increasingly sophisticated genetic analyses. Initial work focused on phenotypic traits to infer diversity and adaptation, revealing substantial variation shaped by geography, environment, and local selection pressures. With the advancement of molecular techniques, research has shifted toward examining genetic diversity and population structure, offering deeper insights into evolutionary processes and genetic diversity (<xref ref-type="bibr" rid="B14">Desplanque et&#xa0;al., 1999</xref>; <xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B26">Leys et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B8">Bertram et&#xa0;al., 2025a</xref>).</p>
<p>A key observation is that phenotypic variation in sea beet populations often exceeds genetic differentiation and is strongly influenced by environmental conditions (<xref ref-type="bibr" rid="B29">Ribeiro et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B5">Ascarini et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B1">Abdelhameed et&#xa0;al., 2024</xref>). The species&#x2019; outcrossing mating system, along with high pollen and seed dispersal, promotes gene flow and hence genetic mixing among populations. At the same time, the high phenotypic plasticity of <italic>Beta maritima</italic> enables individuals to respond flexibly to strong environmental gradients across their range. This plasticity complicates the interpretation of morphological data, especially when environmental variation is pronounced. As a result, morphological traits may not reliably reflect underlying genetic relationships. While some studies have identified major genes, such as the <italic>B</italic> gene for vernalization requirement, comprehensive integration of phenotypic and genetic data remains limited. Notably, there are successful examples of wild alleles being introgressed into cultivated beet, such as the <italic>Rz2</italic> gene for Rhizomania resistance (<xref ref-type="bibr" rid="B12">Capistrano-Gossmann et&#xa0;al., 2017</xref>). However, most research has focused on either morphological or genetic variation in isolation, so the extent to which genetic architecture explains morphological patterns is only partially examined. Agronomic traits, especially disease and pest resistances, have been evaluated only minimally across sea beet populations. This gap, likely also due to the difficulty of evaluating such traits in wild material directly (<xref ref-type="bibr" rid="B9">Bertram et&#xa0;al., 2025b</xref>), highlights the need for further studies to systematically assess and characterize this diversity.</p>
<p>Comparative studies have consistently identified two distinct genetic groups among sea beet populations &#x2013; one from the Atlantic and one from the Mediterranean region, with the latter generally exhibit greater genetic and morphological diversity (<xref ref-type="bibr" rid="B14">Desplanque et&#xa0;al., 1999</xref>; <xref ref-type="bibr" rid="B30">Richards et&#xa0;al., 2014</xref>). This divide has been further confirmed by sequence analyses of 239 sea beet <italic>ex-situ</italic> accessions from germplasm banks (<xref ref-type="bibr" rid="B32">Sandell et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B19">Felkel et&#xa0;al., 2023</xref>). This division reflects the influence of both historical events and evolutionary processes on population structure. During the last glacial period, Mediterranean regions acted as refugia and preserved high ancestral diversity. In contrast, post-glacial recolonization toward the north caused genetic bottlenecks and reduced allelic richness in northern populations (<xref ref-type="bibr" rid="B17">Driessen et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B16">Driessen, 2003</xref>; <xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>).</p>
<p>Nevertheless, this does not mean that northern populations lack valuable alleles for breeding. For example, <xref ref-type="bibr" rid="B12">Capistrano-Gossmann et&#xa0;al. (2017)</xref> identified the <italic>Rz2</italic> resistance gene to Rhizomania, which is of major importance for breeding, in a Danish sea beet population. Other studies have also reported unique alleles and polymorphisms in northern Atlantic populations (<xref ref-type="bibr" rid="B2">Andersen et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B8">Bertram et&#xa0;al., 2025a</xref>). While it remains unclear which of these alleles hold practical value for breeding, the implications are significant. This highlights the importance of <italic>in-situ</italic> conservation, specifically of genetically unique micro-populations, to preserve unique genetic variants. It also underscores the need for broad sampling and comprehensive testing to fully uncover useful genetic diversity across all regions. Genomic tools, including high-density SNP arrays and whole-genome sequencing, can aid with the identification of candidate alleles for introgression and the systematic assessment of genetic resources (<xref ref-type="bibr" rid="B4">Andrello et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B19">Felkel et&#xa0;al., 2023</xref>).</p>
<p>Mediterranean populations, with their high diversity and high amount of unique alleles, surely represent valuable sources for crop improvement. Especially their ability to thrive even under challenging conditions, such as drought or high salinity, makes them especially valuable for breeding programs aiming to develop more resilient cultivars. However, despite evidence of rich diversity, Mediterranean sea beet populations remain notably underrepresented, especially in genetic studies (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>). Notable gaps exist along the southern and eastern coasts of Spain, the Italian coastline and Sardinia, all of Greece, the western coast of Turkey, and other eastern Mediterranean regions. Although genebank accessions sampled from these areas confirm the historical presence of <italic>Beta maritima</italic> (<xref ref-type="bibr" rid="B3">Andrello et&#xa0;al., 2016</xref>), many of these populations have not been genetically characterized. <xref ref-type="bibr" rid="B37">Zucchini et&#xa0;al. (2024)</xref> also noted discrepancies between the presence of <italic>in-situ</italic> populations and the original collection sites of <italic>ex-situ</italic> accessions. One possible reason for this is the ongoing decline of natural habitats, which threatens the survival of sea beet populations (<xref ref-type="bibr" rid="B15">Doney et&#xa0;al., 1990</xref>; <xref ref-type="bibr" rid="B33">Stevanato et&#xa0;al., 2001</xref>). However, this does not fully explain the lack of data, as recent studies still report widespread occurrences, for example along the Italian coast (<xref ref-type="bibr" rid="B37">Zucchini et&#xa0;al., 2024</xref>). This highlights a significant research gap. Although Mediterranean populations are known to exist and contribute substantial diversity, they remain largely uncharacterized. Future research should prioritize these regions to better capture the full spectrum of sea beet diversity and its breeding potential.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Geographic distribution of <italic>Beta maritima</italic> populations sampled within the studies covered by this literature review. Locations are based either on GPS coordinates provided in the original publications or inferred from maps therein. Populations are color-coded by study. Only <italic>Beta maritima</italic> populations are shown. P = total number of sea beet populations (locations) sampled, N = number of individuals per sampled population. Type of study: M = morphological: G = genetical characterization. Countries from which populations were evaluated with each study are indicated: SE, Sweden; DK, Denmark; DE, Germany; BE, Belgium; IE, Ireland; NL, The Netherlands; GG, Guernsey; JE, Jersey; FR, France; PT, Portugal; ES, Spain; IT, Italy; MA, Morocco; TN, Tunesia; EG, Egypt. The map was generated using GoogleEarthPro.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-16-1731515-g002.tif">
<alt-text content-type="machine-generated">Map of Europe and North Africa with colored markers indicating study sites. Below, a table lists studies with number of populations studied and corresponding sample size. Crosses in columns under country codes show study presence in those countries.</alt-text>
</graphic></fig>
<p>Despite recent progress, the value of many genetic studies on sea beet populations is limited by small sample sizes and a narrow set of genetic markers, restricting insights into the full genetic architecture of these populations (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>). While these studies provide useful estimates of heterozygosity and allelic richness in specific regions, they offer only a partial view of overall diversity. The work by <xref ref-type="bibr" rid="B8">Bertram et&#xa0;al. (2025a)</xref> represents a major advancement, applying high-density SNP genotyping across large and diverse populations. This approach enables a more comprehensive analysis of genetic variation, population substructure, and mapping potential, setting a new benchmark for future research. However, while genome-wide SNP data represent a significant improvement over single-marker approaches, SNP panels are often developed based on cultivated material and may suffer from ascertainment bias (<xref ref-type="bibr" rid="B4">Andrello et&#xa0;al., 2017</xref>), potentially underrepresenting rare or novel alleles in wild populations. To fully capture the genetic diversity in <italic>Beta maritima</italic> populations and detect also structural variants such as insertions and deletions (<xref ref-type="bibr" rid="B19">Felkel et&#xa0;al., 2023</xref>), whole-genome sequencing would be preferable. Sequencing technologies are becoming increasingly accessible and are likely to become the method of choice for future diversity studies.</p>
<p>Ultimately, the value of sea beet for crop improvement depends not only on the presence of genetic diversity but also on the ability to identify and utilize alleles conferring desirable traits. A key challenge remains: How to evaluate breeding potential without extensive, resource-intensive testing? First studies have begun to tackle this question. <xref ref-type="bibr" rid="B12">Capistrano-Gossmann et&#xa0;al. (2017)</xref> demonstrated an approach to identify resistance genes directly within sea beet populations without time-consuming material development. Building on this, <xref ref-type="bibr" rid="B9">Bertram et&#xa0;al. (2025b)</xref> used simulation studies to design suitable development schemes for evaluating even complex traits like yield.</p>
<p>Looking forward, addressing current knowledge gaps through integrated genomic, phenotypic, and environmental research is essential to fully harness the potential of <italic>Beta maritima</italic> for sugar beet improvement. Combining morphological, genomic, climatic, and soil data will provide a more comprehensive understanding. Genome-wide scans and landscape genomics can reveal adaptive variants and clarify the environmental drivers of genetic differentiation. Additionally, systematic phenotyping for stress and disease traits, together with the integration of <italic>ex-situ</italic> and <italic>in-situ</italic> datasets, will help resolve inconsistencies and maximize the utility of wild genetic resources for both breeding and conservation.</p>
<p>In summary, sea beet populations exhibit remarkable morphological and genetic diversity shaped by geography, environment, and dispersal dynamics. The transition from morphological to genetic characterization has greatly enhanced our understanding of wild sea beet diversity. Nevertheless, significant gaps remain, particularly in the underexplored Mediterranean populations and in translating genetic variation into breeding value to unlock the full value of <italic>Beta maritima</italic> populations for resilient and sustainable crop development.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="author-contributions">
<title>Author contributions</title>
<p>LB: Conceptualization, Data curation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. MF: Writing &#x2013; review &amp; editing.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>We would like to thank Uwe Fischer for his helpful suggestions and comments, and for his valuable encouragement throughout the writing process.</p>
</ack>
<sec id="s7" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>Author LB was employed by KWS SAAT SE &amp; Co. KGaA.</p>
<p>The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The authors declare that this study received funding from KWS SAAT SE &amp; Co. KGaA. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.</p></sec>
<sec id="s8" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s9" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
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<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1913653">Mahesh Rao</ext-link>, Indian Council of Agricultural Research, India</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2206046">Dali Liu</ext-link>, Heilongjiang University, China</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2766750">Santosh Kumar</ext-link>, Indian Agricultural Research Institute (Jharkhand), India</p></fn>
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