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Search Results (1,073)

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23 pages, 1096 KiB  
Review
Exploring the Cardiovascular Benefits of Extra Virgin Olive Oil: Insights into Mechanisms and Therapeutic Potential
by Esposito Milena and Mandalà Maurizio
Biomolecules 2025, 15(2), 284; https://doi.org/10.3390/biom15020284 - 14 Feb 2025
Viewed by 166
Abstract
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, driven by complex interactions among genetic, environmental, and lifestyle factors, with diet playing a pivotal role. Extra Virgin Olive Oil (EVOO), a cornerstone of the Mediterranean diet (MedDiet), is a plant-based fat that [...] Read more.
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, driven by complex interactions among genetic, environmental, and lifestyle factors, with diet playing a pivotal role. Extra Virgin Olive Oil (EVOO), a cornerstone of the Mediterranean diet (MedDiet), is a plant-based fat that has garnered attention for its robust cardiovascular benefits, which are attributed to its unique composition of monounsaturated fatty acids (MUFAs), particularly oleic acid (OA); and bioactive polyphenols, such as Hydroxytyrosol (HT) and oleocanthal. These compounds collectively exert antioxidant, anti-inflammatory, vasodilatory, and lipid-modulating effects. Numerous clinical and preclinical studies have demonstrated that EVOO’s properties reduce major modifiable cardiovascular risk factors, including hypertension, dyslipidemia, obesity, and type 2 diabetes. EVOO also promotes endothelial function by increasing nitric oxide (NO) bioavailability, thus favoring vasodilation, lowering blood pressure (BP), and supporting vascular integrity. Furthermore, it modulates biomarkers of cardiovascular health, such as C-reactive protein, low-density lipoprotein (LDL) cholesterol, and NT-proBNP, aligning with improved hemostatic balance and reduced arterial vulnerability. Emerging evidence highlights its interaction with gut microbiota, further augmenting its cardioprotective effects. This review synthesizes current evidence, elucidating EVOO’s multifaceted mechanisms of action and therapeutic potential. Future directions emphasize the need for advanced extraction techniques, nutraceutical formulations, and personalized dietary recommendations to maximize its health benefits. EVOO represents a valuable addition to dietary strategies aimed at reducing the global burden of cardiovascular diseases. Full article
(This article belongs to the Special Issue Feature Papers in the Natural and Bio-Derived Molecules Section)
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<p>Flowchart of the methodological approach followed for the selection/exclusion criteria of the articles.</p>
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<p>Mechanism of action of EVOO compounds. The diagram illustrates the beneficial effects of EVOO on cardiovascular health, highlighting its impact on inflammation, oxidative stress, lipid profile, and vascular function. Oleic acid, HT, and oleocanthal, contribute to reducing inflammatory markers, improving antioxidant defenses, and modulating blood pressure and glucose metabolism. This combination of effects supports cardiovascular protection and metabolic regulation. Nuclear Factor kappa B (NF-κB), Tumor Necrosis Factor-alpha (TNF-α), Cyclooxygenase-1 and -2 (COX1,2), Interleukin-1 (IL-1), Interleukin-6 (IL-6), Matrix Metalloproteinase 9 and 2 (MMP-9, -2), von Willebrand Factor (vWF). Forkhead Box O3 (FOXO3), Nuclear factor erythroid 2-related factor 2 (Nrf2), Catalase (CAT), Thioredoxin Reductase (TrxR), Heme Oxygenase-1 (HO-1), NAD(P)H Quinone Dehydrogenase 1 (NQO1), Paraoxonase 2 (PON2), Glutathione S-transferase (GST), Apolipoprotein A1 (ApoA1), ATP-binding cassette transporter A1 (ABCA1), Cholesteryl Ester Transfer Protein (CETP), Lecithin–Cholesterol Acyltransferase (LCAT), low-density lipoprotein (LDL), oxidized low-density lipoprotein (oxLDL), high-density lipoprotein (HDL), Vascular Cell Adhesion Molecule 1 (VCAM-1), Intercellular Adhesion Molecule 1 (ICAM-1), Monocyte Chemoattractant Protein-1 (MCP-1), L-type Calcium Channels (L-type Ca<sup>2+</sup> channels), Big Potassium Channels (BK channels), Calcium-activated Potassium Channels (Ca<sup>2+</sup> activated K channels), Phosphoinositide 3-Kinase/AKT Pathway (PI3K/AKT), Cyclic Guanosine Monophosphate (cGMP), Asymmetric Dimethylarginine (ADMA), Angiotensin II Receptor Type 1 (AT1R), Sphingosine-1-Phosphate Receptor 2 (S1P2R), Phospholipase C (PLC), and Inositol 1,4,5-Trisphosphate (IP<sub>3</sub>). ↑ = increase; ↓ = decrease.</p>
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28 pages, 19915 KiB  
Article
Comprehensive Analysis of Hormonal Signaling Pathways and Gene Expression in Flesh Segment Development of Chinese Bayberry (Myrica rubra)
by Yihan Fu, Shuwen Zhang, Li Yang, Yu Zong, Yongqiang Li, Xingjiang Qi, Wenrong Chen, Fanglei Liao and Weidong Guo
Plants 2025, 14(4), 571; https://doi.org/10.3390/plants14040571 - 13 Feb 2025
Viewed by 309
Abstract
Chinese bayberry (Myrica rubra or Morella rubra) is a valuable fruit, yet the mechanism of its flesh segment development is not well understood. Using paraffin sectioning, we investigated the flower buds of the ‘Biqi’ and ‘Zaojia’ varieties, revealing that the flesh [...] Read more.
Chinese bayberry (Myrica rubra or Morella rubra) is a valuable fruit, yet the mechanism of its flesh segment development is not well understood. Using paraffin sectioning, we investigated the flower buds of the ‘Biqi’ and ‘Zaojia’ varieties, revealing that the flesh segment development in these Chinese bayberry varieties involved the formation of a primordium outside the ovary wall, the establishment of a simple columnar structure, and the formation of the primary flesh segment. Assessment of endogenous hormone levels indicated the significant reductions in jasmonic acid (JA) and indole-3-acetic acid (IAA) levels at the critical stages of flesh segment development. Correlation analysis highlighted the essential roles of IAA, JA, abscisic acid (ABA), and gibberellins in the flesh segment developmental process, underscoring the complex interactions driven primarily by the IAA, JA, and ABA networks. Gene modules positively correlated with flesh segment development were identified using transcriptome-based weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) were enriched in plant hormone signal transduction pathways, particularly for upregulated genes associated with auxin and JA signaling. Key genes predicted to be involved in flesh segment development included LAX2 and LAX3 (auxin transport), JAZ6 (JA signaling repression), and KAN1 and KAN4 (regulating multiple hormonal signaling pathways). Quantitative real-time polymerase chain reaction (qRT-PCR) validation confirmed that the expression trends for these genes were consistent across both varieties, particularly for CRC, SEP1, SEP3, IAA7, and JAZ6. Immunofluorescence localization studies revealed that auxin was primarily distributed in the central vascular bundle and outer cells of the flesh segment. This uneven auxin distribution might contribute to the unique morphology of flesh segments. Overall, this study provides insights into the hormonal regulation and genetic factors involved in the development of Chinese bayberry flesh segments. Full article
(This article belongs to the Section Plant Development and Morphogenesis)
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<p>Comparisons of (<b>a</b>) bayberry, (<b>b</b>) cherry, and (<b>c</b>) citrus fruit structures. Bayberry has a unique fruit structure where the outer edge of the pericarp is specialized to form flesh segments. These segments are morphologically similar to the juice sacs of citrus.</p>
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<p>Morphological and histological characteristics of bayberry flower buds. The bayberry variety used for the morphological and histological observations was ‘Biqi’. The flower buds had not reached the peak flowering stage during these observations. (<b>a</b>) The longitudinal section of the inflorescence in the bayberry flower buds. (<b>b</b>) Paraffin sections showing the development of bayberry flower buds: 1 represents the pistil primordia of the flower bud, 2 represents the flower bud bracts, 3 represents the bract primordia, 4 represents the pistil, 5 represents the stigma, and 6 represents the ovary.</p>
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<p>Paraffin sections illustrating the development of bayberry flesh segments. For the ‘Biqi’ variety, the first column shows the appearance of flower buds sampled at different time points (scale bar = 2 mm). (<b>A</b>–<b>D</b>) display flower bud sections under a 20× magnification (scale bar = 200 μm), while (<b>A’</b>–<b>D’</b>) provide observations of the red-boxed areas in (<b>A</b>–<b>D</b>) under a 40× magnification (scale bar = 40 μm), with the arrows indicating the protruding structure of the flesh segment primordia or primary flesh segment. For the ‘Zaojia’ variety, the first column shows the appearance of flower buds sampled at different time points (scale bar = 2 mm). (<b>E</b>–<b>H</b>) show flower bud sections under a 20× magnification (scale bar = 200 μm), while (<b>E’</b>–<b>H’</b>) provide observations of the red-boxed areas in (<b>E</b>–<b>H</b>) under a 40× magnification (scale bar = 40 μm), with the arrows indicating the protruding structure of the flesh segment primordia or primary flesh segment. In the first stage of flesh segment development, the ovary structure of the pistil expanded.</p>
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<p>Fluctuations of the endogenous hormone levels in the flower buds of ‘Biqi’ and ‘Zaojia’ during flesh segment development. Samples for Stage I were collected before the initiation of flesh segment development, on 26 December for ‘Biqi’ and 17 November for ‘Zaojia’. Samples for Stage II were collected at the stage of flesh segment primordial cell formation, on 18 February for ‘Biqi’ and 26 December for ‘Zaojia’. Samples for Stage III were collected after the formation of the primary flesh segment, on 9 March for ‘Biqi’ and 18 February for ‘Zaojia’. Significant differences were analyzed using Duncan’s test, with different lowercase letters indicating significant differences (<span class="html-italic">p</span> &lt; 0.05). In both ‘Biqi’ and ‘Zaojia’, the levels of JA, JA-Ile, and IAA were significantly downregulated at the initiation of flesh segment development. In ‘Zaojia’, the level of JA decreased substantially (by approximately 93.83%) after primordium formation. Meanwhile, in ‘Biqi’, the level of iP increased significantly during the subsequent stages of flesh segment development. In contrast, ‘Zaojia’ exhibited an initial decrease in the iP level, followed by a recovery. However, the iP level in ‘Zaojia’ remained lower than that in ‘Biqi’.</p>
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<p>Correlations between flesh segment development stages and endogenous hormone levels. Pearson’s correlation analysis was conducted, and the numerical values in the figure represented correlation coefficients (<span class="html-italic">r</span> values). Positive or negative values indicate the direction of the correlations, while asterisks denote the significance of the correlations (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01). In both (<b>a</b>) ‘Biqi’ and (<b>b</b>) ‘Zaojia’, the degree of flesh segment development was negatively correlated with the levels of IAA, JA, and JA-Ile. Moreover, there were significant correlations among the levels of these three hormones throughout the flesh segment development process.</p>
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<p>Statistics on the number of DEGs before and after flesh segment development. (<b>a</b>) A Venn diagram on the number of DEGs. (<b>b</b>) A bar chart on the number of upregulated and downregulated DEGs.</p>
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<p>WGCNA analysis of genes identified in the transcriptome data on bayberry flesh segment development. (<b>a</b>) Statistics on the number of genes in each module. (<b>b</b>) A heatmap showing the associations between WGCNA co-expression modules and traits related to bayberry flesh segment development. The MEcyan, MEblue, and MEmidnightblue modules were significantly correlated with the development of bayberry flesh segments.</p>
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<p>A heatmap of the core gene expression levels in the biological pathways enriched in (<b>a</b>) ‘Biqi’ and (<b>b</b>) ‘Zaojia’. The identified core genes included genes involved in plant hormone signaling pathways, such as <span class="html-italic">LAX3</span> and <span class="html-italic">IAA7</span>, as well as genes involved in pistil development, including <span class="html-italic">CRC</span>.</p>
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<p>KEGG pathway enrichment analysis of DEGs involved during flesh segment development in (<b>a</b>) ‘Biqi’ and (<b>b</b>) ‘Zaojia’. These plant hormone signaling pathways were highly enriched during the flesh segment development process.</p>
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<p>Heatmap analysis of the DEGs upregulated in the plant hormone signaling pathways involved during flesh segment development in ‘Biqi’.</p>
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<p>Heatmap analysis of DEGs that were upregulated in the plant hormone signaling pathways involved during flesh segment development in ‘Zaojia’.</p>
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<p>Relative expression levels of genes related to flesh segment development in ‘Biqi’.</p>
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<p>Relative expression levels of genes related to flesh segment development in ‘Zaojia’.</p>
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<p>Immunofluorescence localization of auxin in the (<b>a</b>) longitudinal and (<b>b</b>) transverse sections of flesh segments. The bayberry variety used for the immunofluorescence localization analysis was ‘Biqi’, and all scale bars were set to 200 μm. In (<b>a</b>), the dashed line indicates a longitudinal section of a single flesh segment, where the auxin fluorescence signals are enriched at the top and side walls of the flesh segment, forming a continuous linear distribution along the contour marked by the dashed line. In (<b>b</b>), the arrow indicates the central vascular bundle within the cross-section of the flesh segment, where the enrichment of auxin fluorescence signals is observed.</p>
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<p>The mechanism of morphological development of flesh segment. (<b>a</b>) Distribution pattern of IAA in flesh segment. The red dots represent IAA, the black dashed box indicates the enriched area of IAA, and the red dashed arrow represents the possible transport direction of IAA. (<b>b</b>) Potential molecular mechanisms underlying the morphological development of flesh segment. IAA is enriched in the outer cell layer of the flesh segment, which may be the reason for the unique morphology of the flesh segment. In addition, IAA is also enriched in the central vascular system, where there may be transport of IAA. It is speculated that there are two possible transport directions: one is that IAA is transported through the vascular system to the top of the flesh segment and then distributed to the outer edge cell layer, and the other is that IAA is transported horizontally within the vascular system and directly distributed to the outer edge cell layer. Molecular pathways for predicting the development of flesh segment morphology based on transcriptome analysis of genes selected through functional analysis and hormone pathway analysis. According to the results, it was found that there is a strong correlation between auxin and jasmonic acid during the development of the flesh segment. It is speculated that the development of the flesh segment may involve the joint regulation of two hormone pathways, and the regulatory network may involve <span class="html-italic">LAX</span>\<span class="html-italic">CRC</span>\<span class="html-italic">SEP</span> as the upstream, <span class="html-italic">IAA7</span> as the downstream auxin regulatory pathway, and <span class="html-italic">JAZ6</span> as the responsive jasmonic acid regulatory pathway.</p>
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29 pages, 2280 KiB  
Article
Geometric Models of Speciation in Minimally Monophyletic Genera Using High-Resolution Phylogenetics
by Richard H. Zander
Plants 2025, 14(4), 530; https://doi.org/10.3390/plants14040530 - 9 Feb 2025
Viewed by 354
Abstract
High-resolution phylogenetics using both morphology and molecular data reveal surfactant-like trait buffering of peripatric descendant species that facilitate resilience for supra-specific entities across geologic time. Regular polygons inscribed in circles model balanced areas of survival of various numbers of new species in one [...] Read more.
High-resolution phylogenetics using both morphology and molecular data reveal surfactant-like trait buffering of peripatric descendant species that facilitate resilience for supra-specific entities across geologic time. Regular polygons inscribed in circles model balanced areas of survival of various numbers of new species in one genus. This model maximizes the peripatric survival of descendant species, with populations partly in allopatric habitats and in sympatric areas. It extends the theory advanced with Willis’s Age and Area hypothesis. Hollow curves of the areas bounded between a series of inscribed regular polygons and their containing circles show a ranked progression governed by similar power laws of other phenomena, including Zipf’s law and a universal meta-law in physics. This model matches best the physics meta-law (law of laws) but is only one of several somewhat different curves generated by somewhat different processes. A rule of four can explain why most genera in vascular plants exhibit a hollow curve of optimally one to five species per genus. It implies a constraint on variation that enhances survival and provides a physics explanation for the monophyletic skeleton of macrogenera. A high-resolution form of ancestor–descendant analysis is compared to traditional phylogenetic analysis to best modeling of the demonstrable results of evolutionary processes. Arguments are advanced for the preservation of scientific concepts of taxa over cladistic clades. Full article
(This article belongs to the Special Issue Evolution of Land Plants)
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<p>Species and traits per species. (<b>A</b>) Numbers of species each of 26 minimally monophyletic groups (microgenera). Genera with more than five species (one ancestor and four descendants) are few, and immediate descendants may have descendants of their own. The dotted line is an Excel regression trendline demonstrating that this is a power rule. (<b>B</b>) Average new traits per species (the novon set) in 26 microgenera. A few genera average many traits per species, explained by serial extinction. Again, the trendline demonstrates that this is a power rule distribution. The number of new traits per species (solid line) is independent of the number of species per genus (dotted line). The comparison of these graphs reveals a self-similarity of the constraint of information across rank hierarchies.</p>
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<p>General evidence for the evolutionary rule of four (optimally four immediate descendants per ancestral species). Heavy lines plot the hollow curve. The dotted line at five species demonstrates a large number of species of one to five species. (<b>A</b>) All vascular plants, with a number of species cut off at 35. (<b>B</b>) Angiosperm genera, <span class="html-italic">X</span>-axis exponential to show the existence of huge genera. (<b>C</b>) Reptiles, implying a similar rule of four in animals. The five-species optimality is potentially explained by constraints on the geometric dispersal of survival information during peripatric speciation.</p>
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<p>Regular polygons inscribed in circles modeling peripatric speciation and balanced competition between descendant species ranked 0 through 8 for a number of polygon sides. The black portion models the maximum habitat coverage of descendant species without inter-competition. Zero is just the ancestral species. One is a conjectural polygon of one side, the descendant balancing the ancestral species. Two is a conjectural polygon of 2 sides, balancing two descendant species. The remainder are actual regular polygons of 3 to 8 sides. Percent of the peripheral area cut off by the inscribed polygon or equivalent is evolutionarily important. Genera with fewer than six immediate descendant species may sustain less internal competition and have better chances of survival in the long term.</p>
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<p>Model of peripatric speciation with increasing number of peripatric descendant species over time. Peripatric descendant species seldom originate beyond four in number, then disperse and eventually become ancestral species themselves. A = ancestral species, D = descendant species. This is a theoretical model of how competition might control numbers of less-than-successful immediate descendant species, which preserves successful traits in the lineage as a whole across geological time scales.</p>
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<p>Hollow curves of power rules with negative exponents. The thick solid line is the area outside the regular polygon as a percent of the inscribed circle. The thin line is Zipf’s law showing polygons ranked by a number of sides as a harmonic series of fractions. The dotted line is Constantin et al.’s (2024) meta-law for a series of operators in physics formulae. These comprise a unit or sheaf of hollow curves, each apparently valid in describing closely associated aspects or contextual views of processes in nature. The physical law or joint cause is not and perhaps cannot be precisely modeled by the curves.</p>
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<p>Evolutionary diagram of a group of moss species from West Indies and adjacent areas showing actual geometric rule-of-four descent with modification. Self-similarity is present at various genus and family levels, with four descendants of satellite genera and of the central ancestor of these genera. Two genera show secondary ancestry. Every ancestral species is supported by being the most generalist among the ingroup and also the most similar of all species to the outgroup (second-order Markov chain). Five species per genus is optimal and explains the hollow curves, and extinction trims away unsuccessful internally competing species of the genera.</p>
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<p>Comparison of analytic methods for determining monophyly. (<b>A</b>) Phylogenetics uses cluster analysis to estimate common ancestry and requires that by the Phylogenetic Classification Principle of Holophyly, all species in a cluster be of the same genus (or the same other rank). For a species to be a member of some phylogenetic genus, it must share the same ancestor as all the other species, that is, given the assumption that cladistically clustered species share the same ancestor, then to share an evolutionarily based name, they must share the same cluster. The poor solution ensuring overall monophyly is to either rename the unclusterable species to the same genus or to name all species as different genera. (<b>B</b>) High-resolution phylogenetics uses ancestor–descendant analysis to discover, among a larger monophyletic group, the internal branching train of minimally monophyletic genera. The key feature is the inheriting, to the descendant species, of the entire set of recent advanced morphological traits (novon 2) of the genus ancestor. This theoretically enables descendant survival peripatrically by species able to survive in two environments, a surfactant metaphorically labeled “soap”. The outgroup is species A1, the ancestor is A2, and the descendant species D1 through D4. For each descendant, “novon 2” is the set of new traits of the ancestor given to each descendant as a redundancy, and “novon 3”, “novon 4”, etc. are the new traits of each descendant.</p>
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<p>Example of the fractal surfactant in the moss family Streptotrichaceae, with estimates of age of origin. Species are represented by a presumed potential or actual ancestor (square on edge) and four peripheral potential or actual descendant species. Thick solid lines indicate ancestor–descendant relationships of actual species that possess the most recent new traits of the ancestor and the new traits of the descendant species; these are represented as a sum in bits (the minimum sequential Bayes posterior probability based on one bit per new trait). The dotted lines reflect evolutionary changes of the immediate ancestron between genera. Names of genera are given. One extinct genus is inserted based on a large (11 bits) evolutionary distance between two genera. Dotted lines are relationships between genera that only approximate the sharing of ancestral new traits with all descendants; bit numbers are new traits of their descendants. Numbers of extinct species may be estimated for genera by four minus numbers of actual descendants.</p>
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14 pages, 3985 KiB  
Article
The Role of Stone Materials, Environmental Factors, and Management Practices in Vascular Plant-Induced Deterioration: Case Studies from Pompeii, Herculaneum, Paestum, and Velia Archaeological Parks (Italy)
by Alessia Cozzolino, Giuliano Bonanomi and Riccardo Motti
Plants 2025, 14(4), 514; https://doi.org/10.3390/plants14040514 - 8 Feb 2025
Viewed by 379
Abstract
The biodeterioration process involves the alteration of stone monuments by living organisms, such as bacteria, algae, fungi, lichens, mosses, ferns, and vascular plants, combined with abiotic factors, resulting in physical and chemical damage to historic buildings. This study aims to investigate the role [...] Read more.
The biodeterioration process involves the alteration of stone monuments by living organisms, such as bacteria, algae, fungi, lichens, mosses, ferns, and vascular plants, combined with abiotic factors, resulting in physical and chemical damage to historic buildings. This study aims to investigate the role of the vascular plants affecting four archaeological parks in Campania—Pompeii, Herculaneum, Paestum, and Velia—by analyzing correlations with building materials, exposure, and conservation status. To represent species associations and their coverage percentages at each site, transects of one square meter were employed. The hazard index (HI) was applied to evaluate the impact of the identified biodeteriogens. A total of 117 species were detected across 198 samples collected from the four study sites, with 59 taxa recorded in Pompeii, 56 in Paestum, 41 in Velia, and 36 in Herculaneum. Specifically, Pompeii hosts a predominance of cosmopolitan species (35%) and widely distributed taxa (15%) due to elevated anthropogenic disturbance. Conversely, mediterranean species dominate in Paestum (62%) and Herculaneum (52%), reflecting more stable ecological conditions. Substrate type significantly influences the hazard index, whereas exposure was found to have minimal impact on both the average coverage and the measured hazard index. Future work will focus on developing site-specific conservation strategies that consider substrate properties, vegetation impact, and anthropogenic disturbances to effectively mitigate the biodeterioration risks posed by vascular flora in Italian monumental sites. Full article
(This article belongs to the Special Issue Ethnobotany and Botany in the Euro-Mediterranean Region)
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<p>Number of taxa in the four study sites.</p>
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<p>The chorological spectrum at the four sites.</p>
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<p>Life forms at the four sites (T = therophytes; P = phanerophytes; H = hemicryptophytes; G = geophytes; Ch = chamaephytes).</p>
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<p>Heatmap of relative abundance of different plant species in plant communities at the four different sites. Hierarchical clustering of sites is based on Bray–Curtis, while plant species are ordered according to association index.</p>
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<p>Type of substrates at the four study sites.</p>
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<p>Life forms in the different substrates at the four study sites (P = phanerophytes; Ch = chamaephytes; T = therophytes; H = hemicryptophytes; G = geophytes).</p>
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<p>Vegetation coverage for exposure (<b>a</b>) and substrate (<b>b</b>) parameters. Error bars indicate the standard error of the mean (SEM) for the measured variables.</p>
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<p>The average hazard index (HI) across the different sites (<b>a</b>), substrates (<b>b</b>), and exposures (<b>c</b>). Error bars represent the standard error of the mean (SEM). Bars sharing the same letter are not significantly different according to the Duncan test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Study sites: (<b>A</b>) Pompeii; (<b>B</b>) Herculaneum; (<b>C</b>) Paestum; (<b>D</b>) Velia. Pictures by Alessia Cozzolino.</p>
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33 pages, 6032 KiB  
Article
Effects of Low-Temperature Stress During the Grain-Filling Stage on Carbon–Nitrogen Metabolism and Grain Yield Formation in Rice
by Huimiao Ma, Yan Jia, Weiqiang Wang, Jin Wang, Detang Zou, Jingguo Wang, Weibin Gong, Yiming Han, Yuxiang Dang, Jing Wang, Ziming Wang, Qianru Yuan, Yu Sun, Xiannan Zeng, Shiqi Zhang and Hongwei Zhao
Agronomy 2025, 15(2), 417; https://doi.org/10.3390/agronomy15020417 - 7 Feb 2025
Viewed by 490
Abstract
Interactions between carbon and nitrogen metabolism are essential for balancing source–sink dynamics in plants. Frequent cold stress disrupts these metabolic processes in rice and reduces grain yield. Two rice cultivars (DN428: cold-tolerant; SJ10: cold-sensitive) were subjected to 19 °C low-temperature stress at full-heading [...] Read more.
Interactions between carbon and nitrogen metabolism are essential for balancing source–sink dynamics in plants. Frequent cold stress disrupts these metabolic processes in rice and reduces grain yield. Two rice cultivars (DN428: cold-tolerant; SJ10: cold-sensitive) were subjected to 19 °C low-temperature stress at full-heading for varying lengths of time to analyze the effects on leaf and grain metabolism. The objective was to track carbon–nitrogen flow and identify factors affecting grain yield. Low-temperature stress significantly reduced the activity of nitrate reductase (NR), glutamine synthetase (GS), glutamate synthase (GOGAT), glutamate dehydrogenase (GDH), glutamic oxaloacetic transaminase (GOT), and glutamic pyruvic transaminase (GPT), in functional leaves compared to the control. This reduction decreased nitrogen accumulation, inhibited chlorophyll synthesis, and slowed photosynthesis. To preserve intracellular osmotic balance and lessen the effects of low temperatures, sucrose, fructose, and total soluble sugar levels, as well as sucrose synthase (SS) and sucrose phosphate synthase (SPS) activities, surged in response to low-temperature stress. However, low-temperature stress significantly reduced the activity of adenosine diphosphate glucose pyrophosphorylase (AGPase), granule-bound starch synthase (GBSS), soluble starch synthase (SSS), and starch branching enzyme (SBE). At the same time, low-temperature stress reduced the area of vascular bundles and phloem, making it difficult to transport carbon and nitrogen metabolites to grains on time. The response of grains to low-temperature stress differs from that of leaves, with prolonged low-temperature exposure causing a gradual decrease in carbon and nitrogen metabolism-related enzyme activities and product accumulation within the grains. The insufficient synthesis of starch precursors and carbon skeletons results in significantly lower thousand-grain weight and seed-setting rates, ultimately contributing to grain yield loss. This decline was more pronounced in inferior grains compared to superior grains. Compared to SJ10, DN428 exhibited higher values across various indicators and smaller declines under low-temperature stress, suggesting enhanced cold-tolerance and a greater capacity to maintain grain yield stability. Full article
(This article belongs to the Section Water Use and Irrigation)
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Graphical abstract

Graphical abstract
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<p>The temperature trends from the grain-filling stage to maturity in 2022 and 2023.</p>
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<p>Trends in photosynthesis-related indices in functional leaves of rice under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428. (<b>B</b>) SJ10. Suc represents the sucrose content in functional leaves of rice. N represents the nitrogen accumulation in the functional leaves of rice. CDD represents Cold Degree Day. GDD represents Growing Degree Day. The values are the standardized coefficients, i.e., path coefficients, calculated through ridge regression analysis. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. The black lines represent a positive correlation. The red lines represent a negative correlation. The bold lines represent path coefficients greater than 50%.</p>
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<p>Trends in total soluble sugar content and sucrose metabolism-related enzyme activity in functional leaves of rice under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428. (<b>B</b>) SJ10. CDD represents Cold Degree Day. GDD represents Growing Degree Day. Suc represents the sucrose content in functional leaves of rice. Fru represents the fructose content in functional leaves of rice. TSS represents the total soluble sugar content in functional leaves of rice. SS represents the sucrose synthase activities in functional leaves of rice. SPS represents the sucrose phosphate synthase activities in functional leaves of rice. The values are the standardized coefficients, i.e., path coefficients, calculated through ridge regression analysis. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. NS indicates not significant. The black lines represent a positive correlation. The red lines represent a negative correlation. The dashed lines indicate a non-significant correlation. The bold lines represent path coefficients greater than 50%.</p>
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<p>Trends in sugar content and starch metabolism-related enzyme activity in grains of rice under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428 superior grains. (<b>B</b>) SJ10 superior grains. (<b>C</b>) DN428 inferior grains. (<b>D</b>) SJ10 inferior grains. CDD represents Cold Degree Day. GDD represents Growing Degree Day. Suc represents the sucrose content in grains of rice. Fru represents the fructose content in grains of rice. TSS represents the total soluble sugar content in grains of rice. AM represents amylose content in grains of rice. AP represents amylopectin content in grains of rice. AY represents amylum content in grains of rice. AGPase represents the adenosine diphosphate glucose pyrophosphorylase activities in inferior grains of rice. GBSS represents the granule-bound starch synthase activities in inferior grains of rice. SSS represents the soluble starch synthase activities in grains of rice. SBE represents the starch branching enzyme activities in grains of rice. The values are the standardized coefficients, i.e., path coefficients, calculated through ridge regression analysis. The symbol * indicates significance at <span class="html-italic">p</span> &lt; 0.05. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. NS indicates not significant. The black lines represent a positive correlation. The red lines represent a negative correlation. The dashed lines indicate a non-significant correlation. The bold lines represent path coefficients greater than 50%.</p>
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<p>Trends in nitrogen accumulation and nitrogen metabolism-related enzyme activity in functional leaves of rice under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428. (<b>B</b>) SJ10. CDD represents Cold Degree Day. GDD represents Growing Degree Day. N represents the nitrogen accumulation in the functional leaves of rice. NR represents the nitrate reductase activities in functional leaves of rice. GS represents the glutamine synthetase activities in functional leaves of rice. GOGAT represents the glutamate synthase activities in functional leaves of rice. GDH represents the glutamate dehydrogenase activities in functional leaves of rice. GOT represents the glutamic oxaloacetic transaminase activities in functional leaves of rice. GPT represents the glutamic pyruvic transaminase activities in functional leaves of rice. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. NS indicates not significant. The black lines represent a positive correlation. The red lines represent a negative correlation. The dashed lines indicate a non-significant correlation.</p>
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<p>Trends in nitrogen accumulation and nitrogen metabolism-related enzyme activity in the grains of rice under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428 superior grains. (<b>B</b>) SJ10 superior grains. (<b>C</b>) DN428 inferior grains. (<b>D</b>) SJ10 inferior grains. CDD represents Cold Degree Day. GDD represents Growing Degree Day. N represents the nitrogen accumulation in the grains of rice. GS represents the glutamine synthetase activities in the grains of rice. GOGAT represents the glutamate synthase activities in the grains of rice. GDH represents the glutamate dehydrogenase activities in the grains of rice. GOT represents the glutamic oxaloacetic transaminase activities in the grains of rice. GPT represents the glutamic pyruvic transaminase activities in the grains of rice. The values are the standardized coefficients, i.e., path coefficients, calculated through ridge regression analysis. The symbol * indicates significance at <span class="html-italic">p</span> &lt; 0.05. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. NS indicates not significant. The black lines represent a positive correlation. The red lines represent a negative correlation. The dashed lines indicate a non-significant correlation.</p>
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<p>Trends in yield and its components under low-temperature stress during the grain-filling stage and results of ridge regression analysis. (<b>A</b>) DN428. (<b>B</b>) SJ10. CDD represents Cold Degree Day. PAPN represents the phloem area in the panicle node. PAL represents the phloem area in leaves. VBAPN represents the vascular bundle area in the panicle node. VBAL represents the vascular bundle area in the leaves. DMTR represents the contribution rate of dry matter. PC represents the protein content in grains. SC represents the starch content in grains. CD represents the chalky degree. CR represents the chalky grain rate. TGW represents the thousand-grain weight. EPNPP represents the effective panicle number per plant. SSR represents the seed-setting rate. GNPP represents the grain number per panicle. The values are the standardized coefficients, i.e., path coefficients, calculated through ridge regression analysis. The symbol * indicates significance at <span class="html-italic">p</span> &lt; 0.05. ** indicates significance at <span class="html-italic">p</span> &lt; 0.01. NS indicates not significant. The black lines represent a positive correlation. The red lines represent a negative correlation. The dashed lines indicate a non-significant correlation.</p>
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19 pages, 4424 KiB  
Article
Fatty Acid ABCG Transporter GhSTR1 Mediates Resistance to Verticillium dahliae and Fusarium oxysporum in Cotton
by Guanfu Cheng, Xiuqing Li, W. G. Dilantha Fernando, Shaheen Bibi, Chunyan Liang, Yanqing Bi, Xiaodong Liu and Yue Li
Plants 2025, 14(3), 465; https://doi.org/10.3390/plants14030465 - 5 Feb 2025
Viewed by 349
Abstract
Verticillium wilt and Fusarium wilt cause significant losses in cotton (Gossypium hirsutum) production and have a significant economic impact. This study determined the functional role of GhSTR1, a member of the ABCG subfamily of ATP-binding cassette (ABC) transporters, that mediates [...] Read more.
Verticillium wilt and Fusarium wilt cause significant losses in cotton (Gossypium hirsutum) production and have a significant economic impact. This study determined the functional role of GhSTR1, a member of the ABCG subfamily of ATP-binding cassette (ABC) transporters, that mediates cotton defense responses against various plant pathogens. We identified GhSTR1 as a homolog of STR1 from Medicago truncatula and highlighted its evolutionary conservation and potential role in plant defense mechanisms. Expression profiling revealed that GhSTR1 displays tissue-specific and spatiotemporal dynamics under stress conditions caused by Verticillium dahliae and Fusarium oxysporum. Functional validation using virus-induced gene silencing (VIGS) showed that silencing GhSTR1 improved disease resistance, resulting in milder symptoms, less vascular browning, and reduced fungal growth. Furthermore, the AtSTR1 loss-of-function mutant in Arabidopsis thaliana exhibited similar resistance phenotypes, highlighting the conserved regulatory role of STR1 in pathogen defense. In addition to its role in disease resistance, the mutation of AtSTR1 in Arabidopsis also enhanced the vegetative and reproductive growth of the plant, including increased root length, rosette leaf number, and plant height without compromising drought tolerance. These findings suggest that GhSTR1 mediates a trade-off between defense and growth, offering a potential target for optimizing both traits for crop improvement. This study identifies GhSTR1 as a key regulator of plant–pathogen interactions and growth dynamics, providing a foundation for developing durable strategies to enhance cotton’s resistance and yield under biotic and abiotic stress conditions. Full article
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Figure 1

Figure 1
<p>Cloning, structural analysis, and phylogenetic relationships of <span class="html-italic">GhSTR1.</span> (<b>a</b>) PCR amplification of the <span class="html-italic">GhSTR1</span> gene. The red arrow indicates the target band at the expected size of 2454 bp, confirming the successful cloning of the <span class="html-italic">GhSTR1</span> coding sequence (CDS). (<b>b</b>) Protein domain comparison. SMART-based domain predictions showed that <span class="html-italic">GhSTR1</span>, <span class="html-italic">MtSTR1</span>, and <span class="html-italic">AtSTR1</span> share a conserved AAA ATPase domain (red oval) and transmembrane helices (blue rectangles), which are characteristic features of the ABCG subfamily. (<b>c</b>) The phylogenetic analysis of GhSTR1 was conducted using MEGA11 to study the primary ABC transporter proteins from <span class="html-italic">Carya illinoinensis</span> (pecan), <span class="html-italic">Juglans regia</span> (walnut), <span class="html-italic">Alnus glutinosa</span> (alder), <span class="html-italic">Theobroma cacao</span> (cacao), <span class="html-italic">Citrus x clementina</span> (clementine<span class="html-italic">), Prunus avium</span> (cherry), and <span class="html-italic">Ricinus communis</span> (castor bean). The evolutionary relationships among these major ABC transporter proteins were analyzed using the Neighbor-Joining (NJ) method and the JTT substitution model in MEGA11 software (The red section of the figure illustrates the cotton proteins and their corresponding protein families analyzed in this study). Bootstrap analyses with 1000 replications were performed on the nodes of the phylogenetic tree to evaluate their statistical support. As shown in <a href="#plants-14-00465-f001" class="html-fig">Figure 1</a>c, the statistical support for key nodes confirms the robustness of the inferred evolutionary relationships. The phylogenetic tree indicates that GhSTR1 is closely related to MtSTR1 and AtSTR1, confirming its classification within the ABCG subfamily.</p>
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<p>Transcript levels of <span class="html-italic">GhSTR1</span> under <span class="html-italic">Verticillium dahliae</span> V991 and <span class="html-italic">Fusarium oxysporum</span> St89 stress. (<b>a</b>,<b>c</b>) Relative expression levels of <span class="html-italic">GhSTR1</span> in leaves under stress from <span class="html-italic">V. dahliae</span> V991 and <span class="html-italic">F. oxysporum</span> St89, respectively. (<b>b</b>,<b>d</b>) Relative expression levels of <span class="html-italic">GhSTR1</span> in roots under stress from <span class="html-italic">V. dahliae</span> V991 and <span class="html-italic">F. oxysporum</span> St89, respectively. Data are expressed as the mean ± standard error (<span class="html-italic">n</span> = 3) and normalized to the control group (CK, sterile water treatment). Statistical analysis was conducted using the <span class="html-italic">t</span>-test, with significance indicated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Silencing efficiency of the <span class="html-italic">GhSTR1</span> gene. (<b>a</b>) PCR amplification of the <span class="html-italic">GhSTR1</span> target fragment. (<b>b</b>) Restriction digestion of the TRV vector, confirming successful vector construction. (<b>c</b>) The bleaching phenotype observed in pTRV2::<span class="html-italic">GhCLA1</span>-silenced cotton plants, demonstrating effective gene silencing. (<b>d</b>,<b>e</b>) Relative expression levels of <span class="html-italic">GhCLA1</span> and <span class="html-italic">GhSTR1</span> in pTRV2::<span class="html-italic">00</span> and pTRV2::<span class="html-italic">GhSTR1</span> plants, respectively. Data are presented as the mean ± standard error (<span class="html-italic">n</span> = 3). Statistical significance is indicated as follows: *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of <span class="html-italic">GhSTR1</span> gene silencing in cotton resistance to <span class="html-italic">V. dahliae</span> V991 and <span class="html-italic">F. oxysporum</span> St89. (<b>a</b>,<b>f</b>) Leaves of pTRV2::<span class="html-italic">GhSTR1</span> plants exhibited more severe chlorosis, wilting, and lesions following infection with <span class="html-italic">V. dahliae</span> (V991) and <span class="html-italic">F. oxysporum</span> (St89) compared to WT and pTRV2::<span class="html-italic">00</span> controls, respectively. Scale bar = 2 cm. (<b>b</b>,<b>g</b>) Longitudinal sections of infected stems showed more pronounced vascular browning in pTRV2::<span class="html-italic">GhSTR1</span> plants, indicating greater pathogen invasion. Scale bar = 0.2 cm. (<b>c</b>,<b>h</b>) Disease index analysis at 20 dpi revealed significantly higher indices in pTRV2::<span class="html-italic">GhSTR1</span> plants than WT and pTRV2::<span class="html-italic">00</span> control. (<b>d</b>,<b>i</b>) qRT-PCR analysis showed significantly higher fungal biomass in pTRV2::<span class="html-italic">GhSTR1</span> plants than in the controls. (<b>e</b>,<b>j</b>) Fungal hyphal growth in stem sections (1 cm above the cotyledonary node) cultured on PDA medium was significantly greater in pTRV2::<span class="html-italic">GhSTR1</span> plants than in the controls. Scale bar = 0.2 cm. Each group included ≥30 plants with 3 replicates to ensure result reliability. Data are expressed as the mean ± standard error (<span class="html-italic">n</span> = 3). Statistical significance was assessed using analysis of variance (ANOVA), followed by Duncan’s multiple comparison test. The significance levels are indicated as follows: ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001. Different groups with different letters represent statistically significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Genotypic validation and expression analysis of <span class="html-italic">AtSTR1</span> T-DNA insertion mutant in <span class="html-italic">Arabidopsis thaliana.</span> (<b>a</b>) Schematic representation of <span class="html-italic">AtSTR1</span> gene structure in the SALK_129014 mutant. The promoter is shown as an orange rectangle, the single exon as a yellow rectangle, and the T-DNA insertion site as a blue inverted triangle. (<b>b</b>) Genotyping results for the homozygous SALK_129014 mutant. Homozygous plants lacked amplification with LP/RP primers but showed a T-DNA-specific fragment with LBa1/RP primers. (<b>c</b>) SqRT-PCR showed reduced <span class="html-italic">AtSTR1</span> expression in the <span class="html-italic">Atstr1</span> mutant compared to that in the wild-type plants. <span class="html-italic">Actin2</span> was used as the reference gene for normalization. (<b>d</b>) qRT-PCR confirmed significantly reduced <span class="html-italic">AtSTR1</span> expression in the <span class="html-italic">Atstr1</span> mutant relative to the wild-type plants. Data are presented as mean ± standard error (<span class="html-italic">n</span> = 3), with statistical significance indicated as follows: *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Enhanced resistance of <span class="html-italic">Atstr1</span> mutant to <span class="html-italic">V. dahliae</span> (V991) and <span class="html-italic">F. oxysporum</span> (St89). (<b>a</b>,<b>e</b>) Phenotypic comparison of <span class="html-italic">Arabidopsis thaliana</span> Col-0 wild-type and <span class="html-italic">Atstr1</span> mutant 15 days post-infection (dpi) with <span class="html-italic">V. dahliae</span> (V991) and <span class="html-italic">F. oxysporum</span> (St89), respectively. <span class="html-italic">Atstr1</span> mutant displayed reduced wilting and chlorosis compared to the wild-type plants. Scale bar = 1 cm. (<b>b</b>,<b>f</b>) Stem longitudinal sections 1 cm above the tillering node, showing vascular browning at 15 dpi with V991 and St89. <span class="html-italic">Atstr1</span> mutant exhibited milder vascular browning compared to the wild-type plants. Scale bar = 0.2 cm. (<b>c</b>,<b>g</b>) Disease index values at 15 dpi. <span class="html-italic">Atstr1</span> mutant showed significantly lower disease indices than the wild-type plants for both V991 and St89 infections. (<b>d</b>,<b>h</b>) qRT-PCR analysis of the fungal biomass at 15 dpi. <span class="html-italic">Atstr1</span> mutant exhibited significantly reduced fungal biomass compared to wild-type plants. Data are expressed as mean ± standard error (<span class="html-italic">n</span> = 3). Statistical significance was assessed using analysis of variance (ANOVA), followed by Duncan’s multiple comparison test. Significance levels are indicated as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Groups with different letters represent statistically significant differences at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Growth and development phenotype analysis of <span class="html-italic">Atstr1</span> mutant in <span class="html-italic">Arabidopsis thaliana.</span> (<b>a</b>) Overall developmental state of the wild-type (Col-0) and <span class="html-italic">Atstr1</span> mutant during the 15-day growth stage. Scale bar = 5 cm. (<b>b</b>) Root length measurements during the 15-day growth period. Scale bar = 1 cm. (<b>c</b>) Leaf size of the wild-type and <span class="html-italic">Atstr1</span> mutant during the 15-day growth stage. Scale bar = 2 mm. (<b>d</b>) Rosette leaf diameter during the 15-day growth stage. The average diameter was measured at the widest point of the leaf blade across all rosette leaves of the plant. (<b>e</b>) Rosette leaf number during the 15-day growth stage. (<b>f</b>) Overall developmental state of the wild-type and <span class="html-italic">Atstr1</span> mutant during the 45-day growth stage. Scale bar = 5 cm. (<b>g</b>) Plant height during the 45-day growth stage. (<b>h</b>) Number of bolted branches per plant during the 45-day growth stage. (<b>i</b>) Number of siliques per plant during the 45-day growth stage. Forty plants were analyzed for each treatment. Data are presented as the mean ± standard error (SEM; <span class="html-italic">n</span> = 3). The statistical significance is as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Phenotypic and physiological analysis of <span class="html-italic">Atstr1</span> mutant under drought stress. (<b>a</b>) Phenotypic comparison of <span class="html-italic">Arabidopsis thaliana</span> Col-0 wild-type and <span class="html-italic">Atstr1</span> mutant plants before drought treatment, after 10 days of drought stress, and following 8 days of rehydration. (<b>b</b>) Survival rate analysis of Col-0 and <span class="html-italic">Atstr1</span> mutant plants after drought stress and rehydration. (<b>c</b>) Water loss rate curves comparing Col-0 and <span class="html-italic">Atstr1</span> mutant plants during drought stress. A total of 40 plants were analyzed per treatment. Data are presented as mean ± standard error (SEM; <span class="html-italic">n</span> = 3). Statistical significance is as follows: ns: no significant difference.</p>
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15 pages, 13093 KiB  
Article
Structural Particularities of Gall Neoformations Induced by Monarthropalpus flavus in the Leaves of Buxus sempervirens
by Irina Neta Gostin, Irinel Eugen Popescu and Cristian Felix Blidar
Plants 2025, 14(3), 453; https://doi.org/10.3390/plants14030453 - 4 Feb 2025
Viewed by 849
Abstract
The boxwood leafminer Monarthropalpus flavus (Diptera, Cecidomyiidae) has historically been considered a leafminer, but some researchers suggested it induced galls on Buxus species leaves. The larvae of M. flavus create small blister-like galls on Buxus sempervirens leaves, causing tissue hypertrophy and hyperplasia. Histological [...] Read more.
The boxwood leafminer Monarthropalpus flavus (Diptera, Cecidomyiidae) has historically been considered a leafminer, but some researchers suggested it induced galls on Buxus species leaves. The larvae of M. flavus create small blister-like galls on Buxus sempervirens leaves, causing tissue hypertrophy and hyperplasia. Histological examination reveals that M. flavus larvae cause the formation of small blister galls, which involve tissue reorganization in the mesophyll. Unlike typical leafminers, which only disrupt existing tissues, M. flavus induces the appearance of a neo-formed tissue, near the larval chamber. This tissue, originating primarily from spongy parenchyma cells, significantly increases as the leaf thickens. Various histochemical analyses show that the new tissue contains starch, lipids, terpenes, and proteins, providing evidence of reprogramming in the plant’s metabolism. The study concludes that M. flavus induces rudimentary galls, not simply mines, due to the formation of new tissue, whose cells have cytological characteristics distinct from those found in non-galled leaves. However, despite some gall-like features, it does not create new vascular elements, distinguishing it from more complex galls formed by other gall-inducing species. Full article
(This article belongs to the Section Plant Protection and Biotic Interactions)
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Figure 1

Figure 1
<p><span class="html-italic">Monarthropalpus flavus</span> larvae and SEM micrographs of larvae: (<b>A</b>,<b>B</b>) second instar larva, (<b>C</b>) third instar larva with sternal spatula (s), microverrucae (mv), (<b>D</b>) third instar larva with sternal spatula (s), microverrucae (mv), head with antenna (an), mouthparts (mp), (<b>E</b>) third instar larva with microverrucae (mv), head with antenna (an), mouthparts (mp), (<b>F</b>) sternal spatula (s) on third instar larva, (<b>G</b>) terminal part of the third instar larva with anus (a), transversal ridges (tr), microverrucae (mv), microsensilla (ms), (<b>H</b>) terminal part of the third instar larva with microsensilla (ms) and microverrucae (mv), (<b>I</b>) pupa with setae (st), antennal sheath (as), wing sheath (ws), leg sheath (ls). (<b>A</b>,<b>C</b>,<b>I</b>) Scale bar = 500 µm, (<b>B</b>) scale bar = 100 µm, (<b>D</b>,<b>G</b>) scale bar = 50 µm, (<b>E</b>,<b>F</b>,<b>H</b>) scale bar = 20 µm.</p>
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<p>Cross-section through 1st year leaf (<b>A</b>–<b>D</b>) and 2nd year leaf (<b>E</b>–<b>H</b>): (<b>A</b>) lamina between veins, 1st year leaf, (<b>B</b>) detail of midrib, (<b>C</b>) detail of sclerenchyma sheath at the periphery of the leaf blade, (<b>D</b>) detail of palisade parenchyma (pp) and a prismatic crystal of calcium oxalate, (<b>E</b>) lamina between veins, 2nd year leaf, (<b>F</b>) detail of midrib, (<b>G</b>) stomata (st) in the lower epidermis, (<b>H</b>) detail of palisade parenchyma: le—lower epidermis, pp—palisade parenchyma, ph—phloem, scl—sclerenchyma, sp—spongy parenchyma, st—stomata, ue—upper epidermis, xl—xylem, ox—calcium oxalate crystals. (<b>A</b>,<b>B</b>,<b>E</b>,<b>F</b>) Scale bar = 100 µm, (<b>C</b>,<b>D</b>,<b>G</b>,<b>H</b>) scale bar = 50 µm.</p>
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<p>Scanning electron microscopy (SEM) images: (<b>A</b>,<b>B</b>) cross sections through a normal leaf, (<b>C</b>) egg insertion area in the lower epidermis, (<b>D</b>) empty larval chamber (in early stage—white star), (<b>E</b>) larval chamber with 1st instar larva inside (early stage—white star), (<b>F</b>) cross section through leaf with mature gall (near the midrib), (<b>G</b>,<b>H</b>) gall with 3rd instar larva inside, (<b>I</b>) neo-formed tissue in proximity to spongy parenchyma (white arrow), (<b>J</b>) neo-formed tissue near actively feeding larva (white arrow), (<b>K</b>–<b>N</b>) stages of development of neo-formed tissue in gall (white arrows), (<b>O</b>,<b>P</b>) calcium oxalate crystals in the vicinity of gall (red star—simple calcium oxalate crystals, yellow star—compound calcium oxalate crystals): ep—entry point, l—larva, le—lower epidermis, lc—larval chamber, n-f t—neo-formed tissue, pp—palisade parenchyma, scl – sclerenchyma, sp—spongy parenchyma, st—stomata, ue—upper epidermis, vb—vascular bundle. (<b>H</b>) Scale bar = 1 mm, (<b>G</b>) scale bar = 500 µm, (<b>B</b>,<b>D</b>,<b>F</b>,<b>I</b>,<b>J</b>) scale bar = 200 µm, (<b>A</b>,<b>C</b>,<b>E</b>,<b>M</b>) scale bar = 100 µm, (<b>K</b>,<b>L</b>) scale bar = 50 µm, (<b>O</b>) scale bar = 20 µm, (<b>N</b>,<b>P</b>) scale bar = 10 µm.</p>
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<p>Cross-section through gall in first year leaf: (<b>A</b>,<b>B</b>) cross-section through leaves sampled in May: (<b>A</b>) initiation zone of galls (white arrow), (<b>B</b>) area near the gall, in the vicinity of the midrib, (<b>C</b>–<b>G</b>) cross-sections through leaves sampled in August; (<b>C</b>) larval chamber, (<b>D</b>–<b>G</b>) details from the vicinity of the larval chamber showing hyperplasia and hypertrophy of cells originating from the assimilatory tissue, (<b>H</b>) detail from the lower epidermis with modified cells: ct—cuticle, hp—hypertrophied tissue towards palisade parenchyma, hs—hypertrophied tissue towards spongy parenchyma (HTHS), lc—larval chamber, le—lower epidermis, pp—palisade parenchyma, sp—spongy parenchyma. (<b>A</b>–<b>G</b>) Scale bar = 100 µm, (<b>H</b>) scale bar = 50 µm.</p>
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<p>Cross-section through gall in second year leaf: (<b>A</b>) cross-section through mature gall, (<b>B</b>,<b>C</b>) callus-like tissue filling the areas of the leaf where the larva has fed, (<b>D</b>) callus-like cells developed in the vicinity of the midrib, (<b>E</b>) detail of the cells of the callus-like tissue, (<b>F</b>) calcium oxalate crystals observed under polarized light: cl t—callus-like tissue, le—lower epidermis, ox—calcium oxalate crystals, ph—phloem, pp—palisade parenchyma, scl—sclerenchyma, xl—xylem, (<b>A</b>–<b>D</b>) scale bar = 100 µm, (<b>E</b>,<b>F</b>) scale bar = 50 µm.</p>
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<p>Histochemical profiles of the galls: (<b>A</b>,<b>B</b>) starch stained in violet with Lugol’s reagent (white arrows), (<b>C</b>,<b>D</b>) lipids stained in red with Sudan Red (white arrows), (<b>E</b>) terpenes stained in dark blue with NADI reagent, (<b>F</b>,<b>G</b>) lignin stained in purple red with phloroglucinol (white arrows), (<b>H</b>) polysaccharides stained in red with PAS reagent, (<b>I</b>) proteins stained in blue with Coomassie brilliant blue, (<b>J</b>–<b>M</b>) polyphenols stained in blue with toluidine blue and Na<sub>2</sub>CO<sub>3</sub> (white arrows); st—starch, (<b>A</b>,<b>C</b>,<b>E</b>,<b>F</b>,<b>G</b>,<b>I</b>,<b>J</b>) scale bar = 100 µm, (<b>B</b>,<b>D</b>,<b>H</b>,<b>K</b>–<b>M</b>) scale bar = 25 µm.</p>
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28 pages, 1778 KiB  
Review
Chromium Remediation from Tannery Wastewater in Arequipa, Peru: Local Experiences and Prospects for Sustainable Solutions
by Lino F. Morales-Paredes, Pablo A. Garcia-Chevesich, Giuliana Romero-Mariscal, Armando Arenazas-Rodriguez, Juana Ticona-Quea, Teresa R. Tejada-Purizaca, Gary Vanzin and Jonathan O. Sharp
Sustainability 2025, 17(3), 1183; https://doi.org/10.3390/su17031183 - 1 Feb 2025
Viewed by 1049
Abstract
The release of tannery wastewater contributes to chromium (Cr) pollution globally. Herein, we conduct a novel consolidation of research from the Arequipa region of southern Peru that integrates university theses written in Spanish alongside peer-reviewed journal articles. The objective is to provide a [...] Read more.
The release of tannery wastewater contributes to chromium (Cr) pollution globally. Herein, we conduct a novel consolidation of research from the Arequipa region of southern Peru that integrates university theses written in Spanish alongside peer-reviewed journal articles. The objective is to provide a place-based complement to existing research in English scientific journals focused on effective tools for Cr treatment from tannery wastewater. Our consolidation categorized a total of 75 publications (70 theses and five peer-reviewed) into five distinct strategies for Cr treatment: adsorption (twenty-three studies), phytoremediation (eighteen studies), bioremediation (thirteen studies), electrocoagulation (five studies), and other techniques (fifteen studies). This synthesis highlighted potentially promising approaches that could be sustainably tailored to regional resources and waste products. This includes sorptive materials derived from food waste such as native achiote peels (B. orellana) and avocado seeds (P. americana) either used directly or as a feedstock for biochar. Other technologies include phytoremediation using microalgae and resident vascular plants and microbial bioremediation that capitalizes on indigenous bacteria and fungi. Promise was also discerned in studies that incorporated a combination of abiotic and biotic mechanisms tailored toward the region, such as infiltration using selective and bioactive materials, wetlands, solar distillation, iron-based coagulation and flocculation, and bioreactors. These findings provide a sustainable complement to prior global investigations for effective attenuation strategies by adding novel materials and techniques that could be further explored to assess the viability of implementation at pilot and larger scales. These promising technologies and the ability to tailor sustainable treatments toward local resources highlight the opportunity to prioritize the treatment of tannery wastewater to ensure a cleaner environment by informing policy makers, academics, and industry on technologies that could be adopted for implementation in the region. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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<p>View of surface water flow (31 L/s) impaired by RSIP wastewater effluent. This tributary undergoes insufficient treatment and subsequently enters the Chili River. Photo taken in April 2023 by and featuring paper authors.</p>
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<p>Temporal evolution of the number publications (peer-reviewed and theses) related to Cr treatment conducted in the Arequipa Region of southern Peru. Though four publications for 2023 and one for 2024 were identified, a terminus of 2022 was selected to account for a time lapse between thesis completion and availability in online repositories.</p>
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<p>pH values documented at experiments done in Arequipa, showing that, in general, the acidity of treated tannery wastewaters is not constant in all treatment approaches evaluated.</p>
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<p>Synthesis of results of Cr species removal from aqueous solution as a function of pH as compiled from adsorption-based studies herein. This analysis demonstrates that more effective attenuation generally relates to lower pH conditions for CrT (R<sup>2</sup> = 0.99), Cr(VI) (R<sup>2</sup> = 0.50), and Cr(III) (R<sup>2</sup> = 0.99), agreeing with the existing literature.</p>
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17 pages, 9075 KiB  
Article
Involvement of the SIX10 Gene in the Pathogenicity of Fusarium oxysporum Formae Speciales in Strawberries
by Wenbo Yang, Tianling Ma, Dong Liang and Chuanqing Zhang
Int. J. Mol. Sci. 2025, 26(3), 1123; https://doi.org/10.3390/ijms26031123 - 28 Jan 2025
Viewed by 415
Abstract
Strawberries are planted globally as an important crop. Fusarium oxysporum f. sp. fragariae (Fof), a haploid mitosporic, pathogenic fungus with obvious host specificity, is responsible for an economically devastating soil-borne disease seriously threatening strawberry. Fusarium oxysporum is distributed in soils worldwide and causes [...] Read more.
Strawberries are planted globally as an important crop. Fusarium oxysporum f. sp. fragariae (Fof), a haploid mitosporic, pathogenic fungus with obvious host specificity, is responsible for an economically devastating soil-borne disease seriously threatening strawberry. Fusarium oxysporum is distributed in soils worldwide and causes vascular wilt and root rot disease in over 100 plant species. However, the formae speciales of F. oxysporum commonly have a very narrow host range, often restricted to a single host plant species. We isolated and identified pathogenic F. oxysporum from diseased strawberry samples collected from different provinces in China. Further analysis showed that among the 55 F. oxysporum isolates, only 70.91% belonged to Fof, and the remaining 29.09% were named Fo. The mycelial growth of Fof was faster than that of Fo at 20, 30, and 35 °C. The sporulation ability of Fof was weaker than that of Fo, and Fof presented a significantly higher germination rate under high temperatures. Fof and Fo from strawberry were not pathogenic to tomato or cucumber plants, and Fof showed significantly higher pathogenicity on strawberry than Fo. To explore the pathogenic mechanism of Fof, we knocked out SIX10 in Fof. The mycelial growth rate of ΔFofSIX10 was significantly slower than that of the wild type, but there were no significant differences in spore production. The pathogenicity of ΔFofSIX10 to strawberry was significantly weakened, showing decreased severity of symptoms, indicated by root and crown rot, and wilt. Our research provides a basis for understanding the interaction between F. oxysporum and the host strawberry and the occurrence and management of Fusarium disease on strawberry. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>The Bayesian inference phylogeny method was used to construct a <span class="html-italic">Fusarium oxysporum</span> phylogenetic tree based on the <span class="html-italic">EF-1α</span> gene and ITS sequence. Dimensions: ntax = 63, nchar = 1477; format: data type = dna; outgroup = <span class="html-italic">F. tricinctum</span>; Lset: nst = 2, rates = invgamma; Prset: statefreqpr = dirichlet(1, 1, 1, 1); mcmcp: savebrlens = yes, ngen = 100,000, samplefreq = 100, nchains = 4; sumt: contype = allcompat, burnin = 5000.</p>
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<p>Agarose gel electrophoresis of FofraF/FofraR amplification products.</p>
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<p>Effects of different temperatures on the (<b>A</b>) mycelial growth, (<b>B</b>) sporulation, (<b>C</b>) spore germination, and (<b>D</b>) pathogenicity of Fof and Fo. “ns” means no significant difference, * means <span class="html-italic">p</span> &lt; 0.05, and ** means <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>(<b>A</b>) Pathogenicity of different <span class="html-italic">Fusarium oxysporum</span> specialized forms to different hosts. (<b>B</b>) Effects of different <span class="html-italic">F</span>. <span class="html-italic">oxysporum</span> formae speciales on strawberry plant height. Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05), while the same letter indicates no significant difference. CK is treated with sterile water using the same inoculation method. s-Fo: <span class="html-italic">F. oxysporum</span> from strawberry; Fof: <span class="html-italic">F. oxysporum</span> f. sp. <span class="html-italic">fragariae</span>; Fol: <span class="html-italic">F. oxysporum</span> f. sp. <span class="html-italic">Lycopersici</span>; Fom: <span class="html-italic">F. oxysporum</span> f. sp. <span class="html-italic">Melonis</span>.</p>
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<p>Phylogenetic tree of the Fof isolate with the <span class="html-italic">SIX10</span> gene of other host-specialized isolates.</p>
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<p>Generation and identification of <span class="html-italic">Fof16180</span> deletion mutants by gene replacement. (<b>A</b>) Schematic representation of the <span class="html-italic">Fof16180</span> replacement strategy. (<b>B</b>) PCR verification of the <span class="html-italic">Fof16180</span> deletion mutation.</p>
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<p>(<b>A</b>) Colony morphology of wild-type H6 and <span class="html-italic">ΔFof16180</span> on PDA (a1,b1), conidia (a2,b2), (scale bar: (a2,b2) = 20 µm), CM (a3,b3), MM (a4,b4), and OA (a5,b5). (<b>B</b>) Growth rate differences between H6 and <span class="html-italic">ΔFof16180</span> on different culture media. Bars with the same letters are not statistically different (<span class="html-italic">p</span> &gt; 0.05) according to the least significant difference (LSD) test.</p>
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<p>(<b>A</b>) Sporulation difference analysis of H6 and <span class="html-italic">ΔFof16180</span>. (<b>B</b>) Germination rate difference analysis of H6 and <span class="html-italic">ΔFof16180</span>. Bars with the same letters are not statistically different (<span class="html-italic">p</span> &gt; 0.05) according to the least significant difference (LSD) test.</p>
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<p>(<b>A</b>) Colony morphology of wild-type H6 and <span class="html-italic">ΔFof16180</span> from PDA (a1,b1), Congo red (a6,b6), KCl (a7,b7), SDS (a8,b8), glucose (a9,b9), and NaCl (a10,b10). (<b>B</b>) Growth rate differences between H6 and <span class="html-italic">ΔFof16180</span> on different culture media. Bars with the same letters are not statistically different (<span class="html-italic">p</span> &gt; 0.05) according to the least significant difference (LSD) test.</p>
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<p>Pathogenicity of <span class="html-italic">ΔFof16180</span> and wild-type isolates by root inoculation. (<b>A</b>) Plant phenotype diagram. (<b>B</b>) Pathogenicity difference analysis of H6 and <span class="html-italic">ΔFof16180</span>. Bars with the same letters are not statistically different (<span class="html-italic">p</span> &gt; 0.05) according to the least significant difference (LSD) test.</p>
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<p>Pathogenicity of <span class="html-italic">ΔFof16180</span> and wild-type isolates by crown inoculation. (<b>A</b>) Plant phenotype diagram. (<b>B</b>) Pathogenicity difference analysis of H6 and <span class="html-italic">ΔFof16180</span>. Bars with the same letters are not statistically different (<span class="html-italic">p</span> &gt; 0.05) according to the least significant difference (LSD) test.</p>
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14 pages, 3404 KiB  
Article
Characterization and Identification of Neocosmospora solani and Fusarium oxysporum Causing Root Necrosis and Wilting of Orange Trees in Chile
by María A. Garzón-Nivia, Johanna Mártiz Mártiz, Ernesto A. Moya-Elizondo, Braulio Ruiz, Julio C. Cornejo and Héctor A. Valdés-Gómez
Plants 2025, 14(3), 376; https://doi.org/10.3390/plants14030376 - 26 Jan 2025
Viewed by 431
Abstract
Orange trees (Citrus × sinensis (L.) Osbeck) are the third-most cultivated citrus fruit species in Chile. In recent years, several trees in three orange orchards of ‘Lane late’ and ‘Fukumoto’ cultivars grafted on ‘Robidoux’ trifoliate orange (Poncirus trifoliata (L.) Raf.) have [...] Read more.
Orange trees (Citrus × sinensis (L.) Osbeck) are the third-most cultivated citrus fruit species in Chile. In recent years, several trees in three orange orchards of ‘Lane late’ and ‘Fukumoto’ cultivars grafted on ‘Robidoux’ trifoliate orange (Poncirus trifoliata (L.) Raf.) have shown chlorosis, canopy reduction, wilting, root necrosis, defoliation, and plant death symptoms. This study aims to characterize the morphological symptoms observed in diseased orange trees in central Chile and identify the fungal pathogens that are involved. Isolation and morphological characterization of the pathogens were conducted by using different culture media. A total of 53 isolates were obtained, morphologically characterized and 12 isolates were selected for molecular identification. The isolates were identified using ITS, TEF-1α, and RPB2 regions. Two Fusarium species complexes were identified, Neocosmospora (Fusarium) solani (FSSC) and F. oxysporum (FOSC), based on >99% identity. Pathogenicity tests were conducted on young orange seedlings under greenhouse conditions. Results indicated that two months post inoculation, trifoliate orange seedlings displayed root rot symptoms such as necrosis, vascular discoloration, and wilting. FSSC and FOSC were re-isolated from necrotic seedling roots and identified through a combination of morphological traits and molecular techniques. This is the first detailed report of this disease, attributed to FSSC and FOSC, in orange orchards in Chile. These diagnostic results represent the first step in developing adequate phytosanitary programs for managing this disease. Full article
(This article belongs to the Section Plant Protection and Biotic Interactions)
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<p>Symptomatology of orange trees in orchards in Melipilla, Metropolitan Region, Chile. (<b>A</b>,<b>B</b>) Sparse canopy and yellowing; (<b>C</b>) partial defoliation; (<b>D</b>) fruit persistence in the canopy with wilting leaves and advanced decline stage; (<b>E</b>) chlorosis and epinasty of citrus leaves; (<b>F</b>,<b>G</b>) root rot and vascular wilt.</p>
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<p>Morphological structures of <span class="html-italic">Neocosmospora</span> (<span class="html-italic">Fusarium</span>) <span class="html-italic">solani</span> isolated from orange trees. (<b>A</b>,<b>B</b>) Colonies on PDA after 7 days at 20 °C (view from upper site (<b>A</b>) and down site (<b>B</b>) of the petri dish); (<b>C</b>) aerial conidiophores formed on the surface of carnation leaves; (<b>D</b>–<b>F</b>) areal microconidia organized on mucilaginous false heads; (<b>G</b>,<b>H</b>) macro and microconidia; (<b>I</b>) Chlamydospores.</p>
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<p>Morphological structures observed in <span class="html-italic">F</span>. <span class="html-italic">oxysporum</span> isolated from orange trees. (<b>A</b>,<b>B</b>) Colonies on PDA after 7 days at 20 °C (view from upper site (<b>A</b>) and down site (<b>B</b>) of the petri dish); (<b>C</b>) aerial conidiophores formed on the surface of carnation leaves; (<b>D</b>–<b>F</b>) areal microconidia organized on mucilaginous false heads; (<b>G</b>,<b>H</b>) macro and microconidia; (<b>I</b>) Chlamydospores.</p>
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<p>Phylogenetic tree construction using the Maximum Parsimony method based on a concatenated dataset of <span class="html-italic">TEF-1α</span>, <span class="html-italic">ITS</span>, and <span class="html-italic">RPB2</span> sequences of 47 strains belonging to the <span class="html-italic">Fusarium</span> species complex using MEGA v11. Support for the branches was evaluated using bootstrap analysis of 500 replications. Isolates obtained from orange trees are indicated in bold. The branch lengths were proportional to the distance. <span class="html-italic">Fusicolla aquaeductuum</span> (NRRL 20686) was used as an outgroup.</p>
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<p>Necrosis generated by <span class="html-italic">Fusarium</span> spp. infection in three-month-old Rubidoux rootstock orange seedlings recovered 60 days post-inoculation. Uninoculated control (<b>A</b>), <span class="html-italic">Neocosmospora</span> (<span class="html-italic">Fusarium</span>) <span class="html-italic">solani</span> (<b>B</b>) and <span class="html-italic">F. oxysporum</span> (<b>C</b>).</p>
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16 pages, 1840 KiB  
Review
Function of WAKs in Regulating Cell Wall Development and Responses to Abiotic Stress
by Xiaocui Yao, John Humphries, Kim L. Johnson, Jinhui Chen and Yingxuan Ma
Plants 2025, 14(3), 343; https://doi.org/10.3390/plants14030343 - 23 Jan 2025
Viewed by 679
Abstract
Receptor-like kinases (RLKs) are instrumental in regulating plant cell surface sensing and vascular tissue differentiation. Wall-associated kinases (WAKs) are a unique group of RLKs that have been identified as key cell wall integrity (CWI) sensors. WAK signaling is suggested to be activated during [...] Read more.
Receptor-like kinases (RLKs) are instrumental in regulating plant cell surface sensing and vascular tissue differentiation. Wall-associated kinases (WAKs) are a unique group of RLKs that have been identified as key cell wall integrity (CWI) sensors. WAK signaling is suggested to be activated during growth in response to cell expansion or when the cell wall is damaged, for example, during pathogen attack. WAKs are proposed to interact with pectins or pectin fragments that are enriched in primary walls. Secondary walls have low levels of pectins, yet recent studies have shown important functions of WAKs during secondary wall development. Several wak mutants show defects in secondary wall thickening of the xylem vessels and fibers or the development of vascular bundles. This review will discuss the recent advances in our understanding of WAK functions during plant development and responses to abiotic stresses and the regulation of vascular tissue secondary wall development. Full article
(This article belongs to the Special Issue Stress Tolerance and Genetic Improvement in Fiber Crops)
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<p>A model for Arabidopsis and rice WAKs regulating primary and secondary wall signaling in plants. (<b>A</b>) In Arabidopsis, AtWAK1, Glycine-Rich Protein 3 (AtGRP-3), and Kinase-Associated Protein Phosphatase (KAPP) are associated with a multimeric complex of 500 kDa. WAK1 senses pectin fragments of oligogalacturonide (OG) and triggers a defense response that accumulates ROS through activation of NADPH oxidase AtRbohD and MAPK-mediated activation of defense gene expression. Pectin binding activates WAK kinase and the subsequent activation of Mitogen-activated Protein Kinase 3 (MPK3), leading to the regulation of genes involved in cell expansion. MPK6 is either repressed or not activated. AtWAKL4 interacts with and phosphorylates the Cd transporter protein Natural-Resistance-Associated Macrophage Protein 1 (NRAMP1), resulting in enhanced degradation of NRAMP1, which ultimately reduces Cd uptake. (<b>B</b>) AtWAKL14 and AtWAKL8 may interact with cell wall pectin, activating cytoplasmic kinases and downstream signaling pathways to regulate vascular tissue differentiation and SCW development via transcriptional networks, influencing stem and fruit development. (<b>C</b>) In rice, OsWAK11 was found to be capable of binding directly to the BR receptor brassinosteroid insensitive 1 (OsBRI1) and phosphorylate the receptor. OsWAK11 binding is proposed to compete with and prevent binding of the co-receptor Somatic Embryogenesis Receptor-like Kinase 1 (OsSERK1). Inhibition of the kinase Glycogen Synthase Kinase 3 (OsGSK3) allows the accumulation of the transcription factors Brassinazole Resistant 1 (OsBZR1) in a dephosphorylated active form and inhibits its activity. OsWAK11 demonstrated stability under light conditions but underwent degradation under dark conditions, thereby releasing the inhibition of OsBARI activity. OsWAK112 negatively regulates plant salt responses by inhibiting ethylene production, possibly via direct binding with S-adenosyl-L-methionine synthetase (SAMS) 1/2/3 (SAMS1/2/3). (<b>D</b>) OsWAK10 and OsXa4 interact with cell wall pectin, activating cytoplasmic kinases and downstream signaling pathways to regulate vascular tissue differentiation and SCW development via transcriptional networks.</p>
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<p>Summary of expression patterns and biological functions of WAKs involved in secondary wall development in Arabidopsis and rice. Expression profiles of <span class="html-italic">WAKs</span> in shoot meristem, flower, silique, stem, leaf, and root, and transgenic plant phenotypes in Arabidopsis (<b>A</b>) and rice (<b>B</b>). Colored cells indicate tissue expression patterns of WAKs in vascular tissues.</p>
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19 pages, 2455 KiB  
Article
Species Diversity, Biomass Production and Carbon Sequestration Potential in the Protected Area of Uttarakhand, India
by Geetanjali Upadhyay, Lalit M. Tewari, Ashish Tewari, Naveen Chandra Pandey, Sheetal Koranga, Zishan Ahmad Wani, Geeta Tewari and Ravi K. Chaturvedi
Plants 2025, 14(2), 291; https://doi.org/10.3390/plants14020291 - 20 Jan 2025
Viewed by 706
Abstract
Ecosystem functioning and management are primarily concerned with addressing climate change and biodiversity loss, which are closely linked to carbon stock and species diversity. This research aimed to quantify forest understory (shrub and herb) diversity, tree biomass and carbon sequestration in the Binsar [...] Read more.
Ecosystem functioning and management are primarily concerned with addressing climate change and biodiversity loss, which are closely linked to carbon stock and species diversity. This research aimed to quantify forest understory (shrub and herb) diversity, tree biomass and carbon sequestration in the Binsar Wildlife Sanctuary. Using random sampling methods, data were gathered from six distinct forest communities. The study identified 271 vascular plants from 208 genera and 74 families. A notable positive correlation (r2 = 0.085, p < 0.05) was observed between total tree density and total tree basal area (TBA), shrub density (r2 = 0.09), tree diversity (D) (r2 = 0.58), shrub diversity (r2 = 0.81), and tree species richness (SR) (r2 = 0.96). Conversely, a negative correlation was found with the concentration of tree dominance (CD) (r2 = 0.43). The Quercus leucotrichophora, Rhododendron arboreum and Quercus floribunda (QL-RA-QF) community(higher altitudinal zone) exhibited the highest tree biomass (568.8 Mg ha−1), while the (Pinus roxburghii and Quercus leucotrichophora) PR-QL (N) community (lower altitudinal zone) in the north aspect showed the lowest (265.7 Mg ha−1). Carbon sequestration was highest in the Quercus leucotrichophora, Quercus floribunda and Rhododendron arboreum (QL-QF-RA) (higher altitudinal zone) community (7.48 Mg ha−1 yr−1) and lowest in the PR-QL (S) (middle altitudinal zone) community in the south aspect (5.5 Mg ha−1 yr−1). The relationships between carbon stock and various functional parameters such as tree density, total basal area of tree and diversity of tree showed significant positive correlations. The findings of the study revealed significant variations in the structural attributes of trees, shrubs and herbs across different forest stands along altitudinal gradients. This current study’s results highlighted the significance of wildlife sanctuaries, which not only aid in wildlife preservation but also provide compelling evidence supporting forest management practices that promote the planting of multiple vegetation layers in landscape restoration as a means to enhance biodiversity and increase resilience to climate change. Further, comprehending the carbon storage mechanisms of these forests will be critical for developing environmental management strategies aimed at alleviating the impacts of climate change in the years to come. Full article
(This article belongs to the Special Issue Plant Functional Diversity and Nutrient Cycling in Forest Ecosystems)
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<p>Dominant families with number of taxa in Binsar Wildlife Sanctuary.</p>
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<p>Dominant genera in Binsar Wildlife Sanctuary.</p>
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<p>Density (individuals ha<sup>−1</sup>) and total basal area (m<sup>2</sup> h<sup>−2</sup>) of trees in BWLS.</p>
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<p>Correlation of tree density with total basal area of tree; tree diversity; shrub density; shrub diversity; tree species richness and concentration of dominance of trees.</p>
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<p>Correlation of biomass and carbon stock: (<b>A</b>) tree diversity; (<b>B</b>) tree density; (<b>C</b>) total basal area; (<b>D</b>) species richness in the BWLS.</p>
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<p>Principal component analysis (PCA) based on different ecological attributes of six forest communities. Abbreviations used: (RS: rainy season; WS: winter season; SS: summer season; TCSeq: total carbon sequestration; SR: species richness; TCS: total carbon stock).</p>
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<p>Map of the study area.</p>
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22 pages, 11600 KiB  
Article
Comprehensive GC-MS Characterization and Histochemical Assessment of Various Parts of Three Colchicum Species from Bulgarian Flora
by Ivayla Dincheva, Ilian Badjakov, Vasil Georgiev, Ivanka Semerdjieva, Radka Vrancheva, Ivan Ivanov and Atanas Pavlov
Plants 2025, 14(2), 270; https://doi.org/10.3390/plants14020270 - 18 Jan 2025
Viewed by 536
Abstract
This study presents a comprehensive phyto- and histochemical analysis of three Colchicum species: Colchicum autumnale L., the Balkan endemic Colchicum bivonae Guss., and the Bulgarian endemic Colchicum diampolis Delip. et Česchm. Using gas chromatography-mass spectrometry (GC-MS), 66 metabolites were identified, encompassing free amino, [...] Read more.
This study presents a comprehensive phyto- and histochemical analysis of three Colchicum species: Colchicum autumnale L., the Balkan endemic Colchicum bivonae Guss., and the Bulgarian endemic Colchicum diampolis Delip. et Česchm. Using gas chromatography-mass spectrometry (GC-MS), 66 metabolites were identified, encompassing free amino, organic, phenolic, and fatty acids, sugars, and alkaloids, which were distributed among various plant parts. Organ-specific metabolic patterns revealed that corms and seeds are particularly rich in alkaloids, supporting their roles in chemical defense and survival during dormancy. Conversely, flowers, leaves, and capsules were enriched with energy-related and phenolic compounds, playing critical roles in reproduction and stress tolerance. Histochemical investigations localized alkaloids predominantly in the endosperm of seeds, parenchyma of corms, and vascular bundles of flowers. Notably, the endemic C. bivonae and C. diampolis displayed unique chemical profiles. Moderate acetylcholinesterase inhibitory activity (AChE) was observed across various plant organs. Statistical analyses demonstrated significant interspecies and organ-specific chemical differentiation, with certain metabolites serving as key markers. These findings enhance our understanding of the chemical composition, organ specialization, and potential as a source of new biomolecules in these Colchicum species. They underscore the ecological and pharmacological importance of endemic taxa and provide a framework for future research into their sustainable utilization and potential bioactivities. Full article
(This article belongs to the Section Phytochemistry)
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<p>Morphological features of seeds, corms, and flowers (perianth leaves) of <span class="html-italic">Colchicum autumnale</span> viewed with Stereo Microscope Motic DM 143 (<b>A</b>–<b>F</b>) and light microscope Motic DMA (<b>G</b>–<b>I</b>; (<b>G</b>) ×10; (<b>H</b>,<b>I</b>); ×40); (<b>A</b>)—general view of seeds; (<b>B</b>)—non treated seeds; (<b>C</b>)—treated seeds; (<b>D</b>)—non treated corm, Control; (<b>E</b>,<b>F</b>)—treated corm; (<b>G</b>)—perianth leaves, Control; (<b>H</b>,<b>I</b>)—treatment perianth leaves; En—endosperm; Sp—spermoderm; Col. En—colored endosperm; C. Corm—cortex of corm; P.t—parenchyma tissue; Col. V.b—colored Vascular bundles; Col. P.t—colored parenchyma tissue E—epidermis; V.b—Vascular bundles; Scale bar = 100 μm.</p>
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<p>Morphological features of seeds, corm, and flowers (perianth leaves) of <span class="html-italic">Colchicum bivonae</span> viewed with Stereo Microscope Motic DM 143 (<b>A</b>–<b>F</b>) and light microscope Motic DMA ((<b>F</b>) ×10, (<b>G</b>) ×40); (<b>A</b>)—general view of seeds; (<b>B</b>)—non-treated seeds, Control; (<b>C</b>)—treated seeds; (<b>D</b>)—non-treated corm, Control; (<b>E</b>)—treated corm; (<b>F</b>)—perianth leaves, Control; (<b>G</b>)—treated perianth leaves; En—endosperm; Sp—spermoderm; Col. En—colored endosperm; C. Corm—cortex of corm; P.t—parenchyma tissue; Col. P.t—colored parenchyma tissue E—epidermis; V.b—Vascular bundles; Scale bar = 100 μm.</p>
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<p>Morphological features of seeds and corm of <span class="html-italic">Colchicum diampolis</span> viewed with Stereo Microscope Motic DM 143 (<b>A</b>–<b>E</b>); (<b>A</b>)—general view of seeds; (<b>B</b>)—non-treated seeds, Control; (<b>C</b>)—treated seeds; (<b>D</b>)—non-treated corm, Control; (<b>E</b>)—treated corm; En—endosperm; Sp—spermoderm; Col. En—colored endosperm; C. Corm—cortex of corm; P.t—parenchyma tissue; Col. P.t—colored parenchyma tissue; Scale bar = 100 μm.</p>
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<p>Heatmap of 25 most significant (ANOVA) GC/MS identified metabolites in different <span class="html-italic">Colchicum autumnale</span> organs: corms (red); capsules (green); flowers (dark blue); leaves (light blue); and seeds (pink).</p>
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<p>PLS-DA score plot (<b>A</b>) and variable importance analysis (VIP) (<b>B</b>) of top 10 GC/MS identified metabolites in different <span class="html-italic">Colchicum autumnale</span> organs.</p>
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<p>Heatmap of 25 most significant (ANOVA) GC/MS identified metabolites in different <span class="html-italic">Colchicum bivonae</span> organs: corms (red); capsules (green); flowers (dark blue); leaves (light blue); and seeds (pink).</p>
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<p>PLS-DA score plot (<b>A</b>) and variable importance analysis (VIP) (<b>B</b>) of top 10 GC/MS identified metabolites in different <span class="html-italic">Colchicum bivonae</span> organs.</p>
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<p>Heatmap of 25 most significant (ANOVA) GC/MS identified metabolites in different <span class="html-italic">Colchicum diampolis</span> organs: corms (red); capsules (green); flowers (dark blue); leaves (light blue); and seeds (pink).</p>
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<p>PLS-DA score plot (<b>A</b>) and variable importance analysis (VIP) (<b>B</b>) of top 10 GC/MS identified metabolites in different <span class="html-italic">Colchicum diampolis</span> organs.</p>
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<p>K-mean clustering (2 clusters) of different organs: corms (red); capsules (green); flowers (dark blue); leaves (light blue); and seeds (pink) of <span class="html-italic">Colchicum autumnale</span> (<b>A</b>), <span class="html-italic">Colchicum bivonae</span> (<b>B</b>), and <span class="html-italic">Colchicum diampolis</span> (<b>C</b>) plants.</p>
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<p>Heatmap of 25 most significant (ANOVA, <span class="html-italic">p</span> = 0.05) metabolites (<b>A</b>) and hierarchical clustering dendrogram of all metabolites (<b>B</b>) identified by GC/MS in corms of <span class="html-italic">Colchicum autumnale</span> (CA), <span class="html-italic">Colchicum bivonae</span> (CB), and <span class="html-italic">Colchicum diampolis</span> (CD). The clustering was performed by using the Ward method with Euclidean distance.</p>
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<p>PLS-DA score plot (<b>A</b>) and variable importance analysis (VIP) (<b>B</b>) of top 10 GC/MS identified metabolites in corms of <span class="html-italic">Colchicum autumnale</span> (CA), <span class="html-italic">Colchicum bivonae</span> (CB), and <span class="html-italic">Colchicum diampolis</span> (CD).</p>
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<p>Correlation analysis showing compounds correlated with acetylcholinesterase inhibitory activities of alkaloid extracts from <span class="html-italic">Colchicum autumnale</span>, <span class="html-italic">Colchicum bivonae,</span> and <span class="html-italic">Colchicum diampolis</span> corms.</p>
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40 pages, 2452 KiB  
Review
Groundbreaking Technologies and the Biocontrol of Fungal Vascular Plant Pathogens
by Carmen Gómez-Lama Cabanás and Jesús Mercado-Blanco
J. Fungi 2025, 11(1), 77; https://doi.org/10.3390/jof11010077 - 18 Jan 2025
Viewed by 929
Abstract
This review delves into innovative technologies to improve the control of vascular fungal plant pathogens. It also briefly summarizes traditional biocontrol approaches to manage them, addressing their limitations and emphasizing the need to develop more sustainable and precise solutions. Powerful tools such as [...] Read more.
This review delves into innovative technologies to improve the control of vascular fungal plant pathogens. It also briefly summarizes traditional biocontrol approaches to manage them, addressing their limitations and emphasizing the need to develop more sustainable and precise solutions. Powerful tools such as next-generation sequencing, meta-omics, and microbiome engineering allow for the targeted manipulation of microbial communities to enhance pathogen suppression. Microbiome-based approaches include the design of synthetic microbial consortia and the transplant of entire or customized soil/plant microbiomes, potentially offering more resilient and adaptable biocontrol strategies. Nanotechnology has also advanced significantly, providing methods for the targeted delivery of biological control agents (BCAs) or compounds derived from them through different nanoparticles (NPs), including bacteriogenic, mycogenic, phytogenic, phycogenic, and debris-derived ones acting as carriers. The use of biodegradable polymeric and non-polymeric eco-friendly NPs, which enable the controlled release of antifungal agents while minimizing environmental impact, is also explored. Furthermore, artificial intelligence and machine learning can revolutionize crop protection through early disease detection, the prediction of disease outbreaks, and precision in BCA treatments. Other technologies such as genome editing, RNA interference (RNAi), and functional peptides can enhance BCA efficacy against pathogenic fungi. Altogether, these technologies provide a comprehensive framework for sustainable and precise management of fungal vascular diseases, redefining pathogen biocontrol in modern agriculture. Full article
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Figure 1

Figure 1
<p>Word cloud showing the most relevant terms extracted from the titles of the articles consulted to produce this review. The frequency each term appears in the titles is visually emphasized in the cloud by their size. The figure was generated using the free online ChatGPT (<a href="https://chatgpt.com/" target="_blank">https://chatgpt.com/</a>, accessed on 12 December 2024).</p>
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<p>Two examples of fungal vascular diseases affecting highly relevant crops. (<b>A</b>) Banana orchard in Tenerife island affected by Fusarium wilt (<span class="html-italic">Fusarium oxysporum</span> f. sp. <span class="html-italic">cubense</span>) (photo credit Javier López Cepero); (<b>B</b>) Olive trees in Southern Spain showing Verticillium wilt (<span class="html-italic">Verticillium dahliae</span>) symptoms (photo credit Jesús Mercado-Blanco).</p>
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<p>A graphical overview of the cutting-edge technologies mentioned in this review and aimed at improving biocontrol strategies for vascular fungal diseases. The figure was created using icons and templates from the free online BioRender (<a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>, accessed on 12 December 2024), except for the digital twins and microbiome transplant images, which were generated with the free online version of ChatGPT (<a href="https://chatgpt.com/" target="_blank">https://chatgpt.com/</a>, accessed on 12 December 2024). The acronyms used are defined as follows: biological control agent (BCA), artificial intelligence (AI), and RNA interference (RNAi).</p>
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12 pages, 2730 KiB  
Article
Variations and Coordination of Leaflet and Petiole Functional Traits Within Compound Leaves in Three Hardwood Species
by Xiaohui Guo, Jinshan Zhang, Jiacun Gu, Zhongyue Li and Yan Wang
Forests 2025, 16(1), 139; https://doi.org/10.3390/f16010139 - 14 Jan 2025
Viewed by 480
Abstract
Leaf morphology and anatomy traits are key determinants for plant performance; however, their roles within compound leaves—comprising both leaflets and petioles—remain insufficiently studied. This study examined the anatomy, morphology, and biomass allocation of leaflets and petioles in three temperate species (Fraxinus mandshurica [...] Read more.
Leaf morphology and anatomy traits are key determinants for plant performance; however, their roles within compound leaves—comprising both leaflets and petioles—remain insufficiently studied. This study examined the anatomy, morphology, and biomass allocation of leaflets and petioles in three temperate species (Fraxinus mandshurica Rupr., Juglans mandshurica Maxim., and Phellodendron amurense Rupr.). The results showed pronounced anatomical variations within the whole leaf. Specifically, as phyllotaxy increased, the number of conduits significantly increased in petioles but showed less variation. Within the same growth position, the number of conduits was highest in the petiole, followed by the petiolule, main vein, and minor veins. In the terminal leaf vascular network, thinner conduits of minor veins may result in a lower hydraulic efficiency but a higher resistance to embolism. Biomass allocation favored leaflets over petioles in all three examined species. Additionally, the specific leaf area slightly increased with an increase in the degree of phyllotaxy. These findings underscore the trade-offs of efficiency and safety in vascular tissues, as well as the expanding leaf and investment between the leaflet and petiole. Full article
(This article belongs to the Special Issue Water Relations in Tree Physiology)
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Figure 1

Figure 1
<p>Phyllotaxy in compound leaves, including (<b>A</b>) schematic diagram of a single complete compound leaf. Phyllotaxy is the mode of arrangement of individual leaflets along the petiole; (<b>B</b>) single leaflet dissected from complete compound leaf; (<b>C</b>) typical anatomical traits of petiole, petiolule, and main and minor veins of <span class="html-italic">Fraxinus mandshurica</span>. Specifically, C1, C2, C3, C4, C5, C6, and C7, C8 represent the detailed anatomical structures of the minor vein, main vein, petiolule, and petiole under 4 and 40 magnifies, respectively.</p>
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<p>Diameter and number of conduit in the minor vein (<b>A</b>,<b>B</b>), main vein (<b>C</b>,<b>D</b>), petiolule (<b>E</b>,<b>F</b>), and petiole (<b>G</b>,<b>H</b>) along phyllotaxy in <span class="html-italic">Fraxinus mandshurica</span> (FM), <span class="html-italic">Juglans mandshurica</span> (JM), and <span class="html-italic">Phellodendron amurense</span> (PA), respectively. The error bars represent ±1 SE. Different lower-case letters with the same color for each trait category indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) among phyllotaxy within species according to Fisher’s LSD test.</p>
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<p>Palisade tissue thickness (<b>A</b>), spongy tissue thickness (<b>B</b>), ratio of palisade tissue thickness to spongy tissue thickness (<b>C</b>), cell tense ratio (<b>D</b>), spongy ratio (<b>E</b>), and leaflet thickness (<b>F</b>) along phyllotaxy in <span class="html-italic">Fraxinus mandshurica</span> (FM), <span class="html-italic">Juglans mandshurica</span> (JM), and <span class="html-italic">Phellodendron amurense</span> (PA), respectively. The error bars represent ±1 SE. Different lower-case letters with same color for each trait category indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) among phyllotaxy within species according to Fisher’s LSD test.</p>
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<p>Relative share of biomass (<b>A</b>) and leaflet area (<b>B</b>) along phyllotaxy within compound leaf in <span class="html-italic">Fraxinus mandshurica</span> (FM), <span class="html-italic">Juglans mandshurica</span> (JM), and <span class="html-italic">Phellodendron amurense</span> (PA), respectively. P: petiole; T: terminal leaflet; L<span class="html-italic">i</span>: the <span class="html-italic">i</span>th leaflet along the phyllotaxy.</p>
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<p>Specific leaf area (SLA) of individual leaflets along phyllotaxy in <span class="html-italic">Fraxinus mandshurica</span> (FM), <span class="html-italic">Juglans mandshurica</span> (JM), and <span class="html-italic">Phellodendron amurense</span> (PA), respectively. The error bars represent ±1 SE. Different lower-case letters with same color indicate significant differences (<span class="html-italic">p</span> &lt; 0.05) among phyllotaxy within species according to Fisher’s LSD test.</p>
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