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<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
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<journal-title>Frontiers in Plant Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Plant Sci.</abbrev-journal-title>
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<issn pub-type="epub">1664-462X</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="doi">10.3389/fpls.2025.1729054</article-id>
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<subj-group subj-group-type="heading">
<subject>Editorial</subject>
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</article-categories>
<title-group>
<article-title>Editorial: Plant-based solutions for sustainable agriculture and environmental remediation</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Santos</surname><given-names>Carla S.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<name><surname>Zarafshar</surname><given-names>Mehrdad</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Nunes da Silva</surname><given-names>Marta</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
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<aff id="aff1"><label>1</label><institution>Universidade Cat&#xf3;lica Portuguesa, CBQF &#x2013; Centro de Biotecnologia e Qu&#xed;mica Fina &#x2013; Laborat&#xf3;rio Associado, Escola Superior de Biotecnologia</institution>, <city>Porto</city>, <country country="pt">Portugal</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Forestry and Wood Technology, Faculty of Technology, Linnaeus University</institution>, <city>V&#xe4;xj&#xf6;</city>, <country country="se">Sweden</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Marta Nunes da Silva, <email xlink:href="mailto:mansilva@ucp.pt">mansilva@ucp.pt</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-11-20">
<day>20</day>
<month>11</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1729054</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Santos, Zarafshar and Nunes da Silva.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Santos, Zarafshar and Nunes da Silva</copyright-holder>
<license>
<ali:license_ref start_date="2025-11-20">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>
<kwd-group>
<kwd>nutrient cycling</kwd>
<kwd>mulching</kwd>
<kwd>grassland degradation</kwd>
<kwd>phytoremediation</kwd>
<kwd>deep learning - artificial intelligence</kwd>
<kwd>phytochemical profile</kwd>
<kwd>glyphosate</kwd>
<kwd>weed management</kwd>
</kwd-group>
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<institution>Funda&#xe7;&#xe3;o para a Ci&#xea;ncia e a Tecnologia</institution>
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<award-id rid="sp1">10.54499/2022.06252.PTDC, 2022.01903.CEECIND/CP1745/CT0002 , 2023.06124.CEECIND/CP2855/CT0008</award-id>
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<ref-count count="8"/>
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<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Plant Biotechnology</meta-value>
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<notes notes-type="frontiers-research-topic">
<p>Editorial on the Research Topic <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/research-topics/67204">Plant-based solutions for sustainable agriculture and environmental remediation</ext-link>
</p>
</notes>
</front>
<body>
<p>The escalating global challenges of climate change, environmental degradation, and food insecurity call for urgent, transformative approaches to agriculture and ecosystem management. With the world population projected to exceed 9 billion by 2050, pressure on finite natural resources continues to intensify, exacerbating soil degradation, biodiversity loss, and pollution (<xref ref-type="bibr" rid="B2">Cobourn and Ignaciuk, 2025</xref>). To sustain long-term productivity and ecological function in forest plantations, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1566140">Fan et&#xa0;al.</ext-link> emphasize the importance of age-specific nutrient management. Their findings reveal a shift from nitrogen limitation and high phosphorus resorption efficiency in young stands to phosphorus limitation and elevated nitrogen resorption efficiency in older stands (&gt;100 years). Stable and high leaf C:N:P ratios indicate low nutrient use efficiency, while seed nutrient composition in mature stands, characterized by higher crude fat and protein, highlights the need for long-term strategies that prioritize nutrient cycling efficiency. In arid orchard systems, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1633540">Li et&#xa0;al.</ext-link> demonstrate that mulching practices, particularly plastic film (FM) and straw mulching (SM), significantly enhance pear yield and fruit quality. Field treatments resulted in significantly higher fruit yield and quality traits, such as sugar/acid ratio and organic acid composition. Mulching further enhanced soil nutrient availability (including NH<sub>4</sub><sup>+</sup>-N, K, Ca, Fe, Mn, Cu, and Zn) and enriched rhizosphere microbial communities, including beneficial bacteria like Proteobacteria, Acidobacteria, Gemmatimonadetes, and Firmicutes, underscoring its role in promoting soil health and agroecosystem resilience.</p>
<p>However, assessing soil quality and ecosystem health remains challenging due to complex interactions among biophysical, socio-economic, and technological factors operating across scales (<xref ref-type="bibr" rid="B1">Bond et&#xa0;al., 2024</xref>). To address this, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1594772">Zhang et&#xa0;al.</ext-link> introduce a geo-coding and abrupt analysis-based (GAAB) method to diagnose grassland degradation via the Living Status of Vegetation (LSV), a composite index integrating cover, height, biomass, and species diversity. Applied to subalpine meadows, GAAB revealed uneven degradation thresholds and asynchronous shifts in community structure and function, including a species transition from <italic>Dactylis glomerata</italic> in healthy meadows to <italic>Potentilla lineata</italic> in degraded zones, potentially enabling tailored restoration strategies based on degradation severity.</p>
<p>Beyond their role as soil health indicators, plants are pivotal agents in soil restoration due to their adaptive capacity and biochemical versatility. For example, phytoremediation, using plants to extract, degrade, or immobilize pollutants, has shown efficacy in mitigating contaminants across soil and aquatic systems (<xref ref-type="bibr" rid="B4">Ran&#x111;elovi&#x107; et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B5">Sahoo et&#xa0;al., 2025</xref>). Advances in artificial intelligence, including deep learning and process modelling, can further enhance plant-based monitoring of environmental health, ecological restoration, and sustainable agriculture (<xref ref-type="bibr" rid="B8">Yeasmin et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B7">Wu et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B3">Dong et&#xa0;al., 2024</xref>). In this context, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1550302">Guo et&#xa0;al.</ext-link> introduce Bio-DANN, an integrated framework that couples process based biogeochemical simulation with deep learning for dynamic pollutant monitoring and ecological restoration in agricultural waste systems. Bio-DANN mechanistically simulates plant mediated absorption, transformation, and degradation of contaminants, while ingesting environmental sensor streams (e.g., soil moisture and temperature) to train attention-based neural networks. By fusing phytoremediation processes with data driven inference, Bio-DANN delivers accurate predictions of pollutant concentrations and restoration trajectories, outperforming prior approaches in real time monitoring and multidimensional ecological assessment.</p>
<p>Concurrently, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1635867">Nazari et&#xa0;al.</ext-link> highlight the value of integrating molecular and environmental data to guide sustainable cultivation and conservation. ITS-based phylogenetic analysis of Iranian Papaver species revealed complex evolutionary relationships and introgression, while phytochemical profiles, dominated by phenolics, flavonoids, and alkaloids, correlated more strongly with environmental variables (e.g., humidity, elevation) than genetic distance. Among the genotypes evaluated, <italic>P. hybridum</italic> exhibited the highest antioxidant activity, while <italic>P. macrostomum</italic> and <italic>P. dubium</italic> showed higher flavonoid and anthocyanin levels, underscoring their pharmaceutical potential. Valorizing locally adapted underutilized crops and crop wild relatives has proven effective in sustaining key ecosystem services and promoting more sustainable agrifood chains, in part because these species often require fewer chemical inputs (<xref ref-type="bibr" rid="B6">Silva et&#xa0;al., 2025</xref>). Their inclusion in diversified cropping systems can therefore help reduce pesticide dependency, a global concern associated with biodiversity loss, declining water quality, harm to non-target organisms, and the spread of resistant pest populations. Beyond pests, weeds remain a major challenge because they compete with crops for nutrients, water, and light, frequently driving additional fertilizer use to offset yield losses. Addressing weed competition, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fpls.2025.1516963">Li et&#xa0;al.</ext-link> investigated targeted mutations in the EPSPS gene, which encodes a key enzyme of the shikimate pathway, to enhance glyphosate resistance in <italic>Nicotiana tabacum</italic>, allowing for lower application frequency and dosage, and potentially reducing environmental contamination and herbicide runoff. In addition, transgenic lines showed improved oxidative stress resilience, which could support plant survival in degraded or polluted soils, thus contributing to agroecosystem stability.</p>
<p>Collectively, this Research Topic illustrates how plant-based solutions can deliver measurable gains in productivity, resilience, and environmental quality, particularly when deployed as integrated systems rather than isolated interventions. From nutrient cycling in ancient forest stands to microbial modulation in arid orchards, from phytochemical diversity in underutilized species to AI-enhanced pollutant monitoring, the evidence is clear: plant-based solutions thrive when embedded in systems thinking, supported by robust data, and aligned with ecological principles. Effective implementation will depend on participatory codesign of resilient landscapes with farmers, foresters, and local communities, in which biodiversity is valued, external inputs reduced, and ecosystem services quantified and incentivized. As such, the path forward demands not only innovation but integration, where transdisciplinary research converges to embed evidence-based insights into holistic, system-oriented decision-making frameworks.</p>
</body>
<back>
<sec id="s1" sec-type="author-contributions">
<title>Author contributions</title>
<p>CS: Formal Analysis, Funding acquisition, Validation, Writing &#x2013; review &amp; editing. MZ: Formal Analysis, Validation, Writing &#x2013; review &amp; editing. MNS: Conceptualization, Data curation, Writing &#x2013; original draft.</p></sec>
<sec id="s2" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p></sec>
<sec id="s3" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that Generative AI was used in the creation of this manuscript. Generative AI tools were used solely for language editing to refine grammar and improve clarity.</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="s4" 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 and reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/38545"> James Lloyd</ext-link>, Stellenbosch University, South Africa</p></fn>
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