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Keywords = stomata conductance

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18 pages, 2803 KiB  
Article
Photosynthetic Traits of Quercus coccifera Green Fruits: A Comparison with Corresponding Leaves during Mediterranean Summer
by Dimitrios Kalachanis, Christos Chondrogiannis and Yiola Petropoulou
Plants 2024, 13(20), 2867; https://doi.org/10.3390/plants13202867 - 14 Oct 2024
Viewed by 386
Abstract
Fruit photosynthesis occurs in an internal microenvironment seldom encountered by a leaf (hypoxic and extremely CO2-enriched) due to its metabolic and anatomical features. In this study, the anatomical and photosynthetic traits of fully exposed green fruits of Quercus coccifera L. were [...] Read more.
Fruit photosynthesis occurs in an internal microenvironment seldom encountered by a leaf (hypoxic and extremely CO2-enriched) due to its metabolic and anatomical features. In this study, the anatomical and photosynthetic traits of fully exposed green fruits of Quercus coccifera L. were assessed during the period of fruit production (summer) and compared to their leaf counterparts. Our results indicate that leaf photosynthesis, transpiration and stomatal conductance drastically reduced during the summer drought, while they recovered significantly after the autumnal rainfalls. In acorns, gas exchange with the surrounding atmosphere is hindered by the complete absence of stomata; hence, credible CO2 uptake measurements could not be applied in the field. The linear electron transport rates (ETRs) in ambient air were similar in intact leaves and pericarps (i.e., when the physiological internal atmosphere of each tissue is maintained), while the leaf NPQ was significantly higher, indicating enhanced needs for harmless energy dissipation. The ETR measurements performed on leaf and pericarp discs at different CO2/O2 partial pressures in the supplied air mixture revealed that pericarps displayed significantly lower values at ambient gas levels, yet they increased by ~45% under high CO2/O2 ratios (i.e., at gas concentrations simulating the fruit’s interior). Concomitantly, NPQ declined gradually in both tissues as the CO2/O2 ratio increased, yet the decrease was more pronounced in pericarps. Furthermore, net CO2 assimilation rates for both leaf and pericarp segments were low in ambient air and increased almost equally at high CO2, while pericarps exhibited significantly higher respiration. It is suggested that during summer, when leaves suffer from photoinhibition, acorns could contribute to the overall carbon balance, through the re-assimilation of respiratory CO2, thereby reducing the reproductive cost. Full article
(This article belongs to the Section Plant Physiology and Metabolism)
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Figure 1

Figure 1
<p>Fine structure of <span class="html-italic">Q. coccifera</span> leaves (left column) and pericarps (right column), as revealed by scanning electron microscope images (<b>A</b>,<b>B</b>) and light micrographs of cross sections (<b>C</b>,<b>D</b>). Stomata are indicated by arrows in the abaxial leaf surface (<b>A</b>), whereas no stomata could be found in pericarps (<b>B</b>). Samples were collected in August. In <a href="#plants-13-02867-f001" class="html-fig">Figure 1</a>A,B, bars = 20 μm; in <a href="#plants-13-02867-f001" class="html-fig">Figure 1</a>C,D. bars = 50 μm. Ch: chlorenchyma, Cu: cuticle, Ep: epidermis, PP: palisade parenchyma, SP: spongy parenchyma, Sc: sclerenchyma, St: stoma.</p>
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<p>Light (<b>A</b>) and epifluorescence (<b>B</b>) microscope images of pericarp cross sections. Pericarps were collected in August. Bars = 100 μm.</p>
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<p>Fast chlorophyll <span class="html-italic">a</span> fluorescence transients (OJIP) from intact leaves (open green circles) and pericarps (closed red circles) in summer. Transients are given on a logarithmic time scale and are expressed as relative variable fluorescence (V<sub>t</sub>), i.e., after double normalization at the F<sub>0</sub> and F<sub>P</sub> steps. Insert shows the I-P part of the transient on a linear time scale, double normalized at the F<sub>I</sub> and F<sub>P</sub> steps. Each curve is the average of 30 independent transients.</p>
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<p>Light response curves of PSII quantum yield (Φ<sub>PSII</sub>, <b>A</b>), linear electron transport rate (ETR, <b>B</b>) and non-photochemical quenching (NPQ, <b>C</b>) from intact leaves (open green circles) and pericarps (closed red circles) in summer. Values are means ± SD from 6 independent measurements. Asterisks denote statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between leaves and pericarps.</p>
Full article ">Figure 5
<p>Induction curves of electron transport rate (ETR, <b>A</b>) and non-photochemical quenching (NPQ, <b>B</b>) at 200 μmol m<sup>−2</sup> s<sup>−1</sup> from leaf (open green circles) and pericarp (closed red circles) discs under ambient O<sub>2</sub>/CO<sub>2</sub> concentrations. Subsequently, the samples were subjected to mutually varying external partial pressures of the interfering gases, i.e., a gradual CO<sub>2</sub> increase and a concurrent O<sub>2</sub> decrease, plus the reversion to ambient levels. Values are means ± SD from 8 independent measurements.</p>
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<p>Net CO<sub>2</sub> assimilation rate (<span class="html-italic">A</span>) at 200 μmol m<sup>−2</sup> s<sup>−1</sup>, under 400 and 2000 ppm CO<sub>2</sub> in the supplied air mixture, and dark respiration (<span class="html-italic">R</span><sub>d</sub>, at 400 ppm CO<sub>2</sub>) from leaf and pericarp segments in summer. Values are means ± SD from 6 independent measurements. Asterisks denote statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between leaves and pericarps.</p>
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<p>Net CO<sub>2</sub> assimilation (<span class="html-italic">A</span>) and transpiration (T<sub>r</sub>) rates and stomatal conductance (<span class="html-italic">g</span><sub>s</sub>) of leaves attached to the plant in August (green columns) and October (orange columns). PAR at 1420 μmol m<sup>−2</sup> s<sup>−1</sup>. Values are means ± SD from 24 independent measurements. Asterisks denote statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) between summer and autumn for the indicated parameter.</p>
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13 pages, 3445 KiB  
Article
StEPF2 and StEPFL9 Play Opposing Roles in Regulating Stomatal Development and Drought Tolerance in Potato (Solanum tuberosum L.)
by Le Kang, Junke Liu, Hongqing Zhu, Leqin Liao, Muying Ye, Yun Wei, Nairong Liu, Qingbo Ke, Ho Soo Kim, Sang-Soo Kwak and Quanlu Zhou
Int. J. Mol. Sci. 2024, 25(19), 10738; https://doi.org/10.3390/ijms251910738 - 5 Oct 2024
Viewed by 500
Abstract
Stomata are essential for photosynthesis and water-use efficiency in plants. When expressed in transgenic Arabidopsis thaliana plants, the potato (Solanum tuberosum) proteins EPIDERMAL PATTERNING FACTOR 2 (StEPF2) and StEPF-LIKE9 (StEPFL9) play antagonistic roles in regulating stomatal density. Little is known, however, [...] Read more.
Stomata are essential for photosynthesis and water-use efficiency in plants. When expressed in transgenic Arabidopsis thaliana plants, the potato (Solanum tuberosum) proteins EPIDERMAL PATTERNING FACTOR 2 (StEPF2) and StEPF-LIKE9 (StEPFL9) play antagonistic roles in regulating stomatal density. Little is known, however, about how these proteins regulate stomatal development, growth, and response to water deficit in potato. Transgenic potato plants overexpressing StEPF2 (E2 plants) or StEPFL9 (ST plants) were generated, and RT-PCR and Western blot analyses were used to select two lines overexpressing each gene. E2 plants showed reduced stomatal density, whereas ST plants produced excessive stomata. Under well-watered conditions, ST plants displayed vigorous growth with improved leaf gas exchange and also showed increased biomass/yields compared with non-transgenic and E2 plants. E2 plants maintained lower H2O2 content and higher levels of stomatal conductance and photosynthetic capacity than non-transgenic and ST plants, which resulted in higher water-use efficiency and biomass/yields during water restriction. These results suggest that StEPF2 and StEPFL9 functioned in pathways regulating stomatal development. These genes are thus promising candidates for use in future breeding programs aimed at increasing potato water-use efficiency and yield under climate change scenarios. Full article
(This article belongs to the Special Issue Genetic Engineering of Plants for Stress Tolerance)
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Figure 1
<p>Bioinformatics analysis of the StEPF2 and StEPFL9 proteins. Structural models of (<b>A</b>) StEPF2 and (<b>B</b>) StEPFL9. SP: signal peptide; Pro: pro-peptide: Mature: mature peptide. (<b>C</b>) qRT-PCR analysis of <span class="html-italic">StEPF2</span> and <span class="html-italic">StEPFL9</span> expression; the potato gene <span class="html-italic">StEF1α</span> and <span class="html-italic">actin</span> were used as an internal control. (<b>D</b>) Western blot analysis of non-transgenic (NT) and transgenic plants. Data show the mean ± SE. Asterisks indicate significant differences between transgenic and NT lines by Duncan’s multiple range test; *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Phenotypic analyses of stomatal density in transgenic potato plants. (<b>A</b>) Photographs of the mature abaxial leaf epidermis of 3-week-old plants showing stomata. Scale bars: 40 μm. Red dots denote positions of stomatal complexes. (<b>B</b>) Stomatal density of non-transgenic (NT) and transgenic plants. Data show the mean ± SE. Asterisks indicate significant differences between transgenic and NT lines by Duncan’s multiple range test; ns: no significant difference; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Photosynthetic responses of non-transgenic (NT) and transgenic potato plants. (<b>A</b>) <span class="html-italic">Pn-PPFD</span> curve. (<b>B</b>) <span class="html-italic">Pn-Ci</span> curve. (<b>C</b>) <span class="html-italic">Gs-PPFD</span> curve. (<b>D</b>) Water loss from detached leaves of 3-week-old NT and transgenic plants. Data show the mean ± SE. Leaves from the same position on each plant were used in this experiment.</p>
Full article ">Figure 4
<p>Phenotypic analyses of non-transgenic (NT) and transgenic potato plants under short-term drought stress conditions. (<b>A</b>) Appearance of plants before and after drought treatment. (<b>B</b>) <span class="html-italic">Pn</span>, (<b>C</b>) Fv/Fm, and (<b>D</b>) H<sub>2</sub>O<sub>2</sub> content in non-transgenic (NT) and transgenic plants. Leaves from the same position on each plant were used in this experiment. Data show the mean ± SE. Asterisks indicate significant differences between transgenic and NT lines by Duncan’s multiple range test; ns: no significant difference; *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Photosynthetic and chlorophyll fluorescence parameters of transgenic potato plants under long-term drought stress. (<b>A</b>) <span class="html-italic">Pn</span>, (<b>B</b>) <span class="html-italic">Tr</span>, (<b>C</b>) <span class="html-italic">Gs</span>, (<b>D</b>) iWUE, (<b>E</b>) Y(NPQ), and (<b>F</b>) Fv/Fm in non-transgenic (NT) and transgenic plants after 7 or 21 days under well-watered and water-restricted conditions. Leaves from the same position on each plant were used in this experiment. Data show the mean ± SE. Asterisks indicate transgenic and NT lines differed significantly by Duncan’s multiple range test; ns: no significant difference; *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effect of long-term drought treatment on production of NT and transgenic potato plants. (<b>A</b>) Phenotypes of 2-month-old aerial parts of NT, E2, and ST plants under well-watered and water-restricted conditions. (<b>B</b>) Phenotypes of tubers produced by NT and transgenic potato plants after harvest. (<b>C</b>) Daily water consumption of each line during drought treatment. (<b>D</b>) Biomass/tuber yield of NT and transgenic potato plants. Data show the mean ± SE, and each sample (three plants per pot) was replicated five times. Asterisks indicate transgenic and NT lines differed significantly by Duncan’s multiple range test; ns: no significant difference; *: <span class="html-italic">p</span> &lt; 0.05; **: <span class="html-italic">p</span> &lt; 0.01.</p>
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21 pages, 4373 KiB  
Article
Stomata Are Driving the Direction of CO2-Induced Water-Use Efficiency Gain in Selected Tropical Trees in Fiji
by Wuu Kuang Soh, Charilaos Yiotis, Michelle Murray, Sarah Pene, Alivereti Naikatini, Johan A. Dornschneider-Elkink, Joseph D. White, Marika Tuiwawa and Jennifer C. McElwain
Biology 2024, 13(9), 733; https://doi.org/10.3390/biology13090733 - 19 Sep 2024
Viewed by 654
Abstract
Understanding plant physiological response to a rising atmospheric CO2 concentration (ca) is key in predicting Earth system plant–climate feedbacks; however, the effects of long-term rising ca on plant gas-exchange characteristics in the tropics are largely unknown. Studying this [...] Read more.
Understanding plant physiological response to a rising atmospheric CO2 concentration (ca) is key in predicting Earth system plant–climate feedbacks; however, the effects of long-term rising ca on plant gas-exchange characteristics in the tropics are largely unknown. Studying this long-term trend using herbarium records is challenging due to specimen trait variation. We assessed the impact of a ca rise of ~95 ppm (1927–2015) on the intrinsic water-use efficiency (iWUE) and maximum stomatal conductance (gsmax) of five tropical tree species in Fiji using the isotopic composition and stomatal traits of herbarium leaves. Empirical results were compared with simulated values using models that uniquely incorporated the variation in the empirical gsmax responses and species-specific parameterisation. The magnitude of the empirical iWUE and gsmax response was species-specific, ranging from strong to negligible. Stomatal density was more influential than the pore size in determining the gsmax response to ca. While our simulation results indicated that photosynthesis is the main factor contributing to the iWUE gain, stomata were driving the iWUE trend across the tree species. Generally, a stronger increase in the iWUE was accompanied by a stronger decline in stomatal response. This study demonstrates that the incorporation of variation in the gsmax in simulations is necessary for assessing an individual species’ iWUE response to changing ca. Full article
(This article belongs to the Special Issue Biological Response of Plants to Environmental Changes)
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Figure 1

Figure 1
<p>Ratio of leaf intercellular CO<sub>2</sub> to ambient atmospheric CO<sub>2</sub> (<span class="html-italic">c</span><sub>i</sub>/<span class="html-italic">c</span><sub>a</sub>. (<b>a</b>–<b>e</b>)) and intrinsic water-use efficiency (iWUE, (<b>f</b>–<b>j</b>)) responses to rising atmospheric CO<sub>2</sub>. Lines are the fitted regression. Shaded areas are the 95% confidence interval band.</p>
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<p>Relative sensitivity of traits to the atmospheric CO<sub>2</sub> concentration (<span class="html-italic">c</span><sub>a</sub>) of the combined species. (<b>a</b>) Intrinsic water-use efficiency (∆iWUE). (<b>b</b>) Maximum stomatal conductance (∆<span class="html-italic">g</span><sub>sma<span class="html-italic">x</span></sub>). (<b>c</b>) Stomatal density (∆<span class="html-italic">D</span>). (<b>d</b>) Maximum stomatal pore area (∆<span class="html-italic">a</span><sub>max</sub>). Relative change is calculated as the percentage change to the intercept at 300 ppm c<sub>a</sub>. Lines are the fitted regression. Shaded areas are the 95% confidence interval band.</p>
Full article ">Figure 3
<p>Species maximum stomatal conductance (<span class="html-italic">g</span><sub>smax</sub>, (<b>a</b>–<b>e</b>)), stomatal density (<span class="html-italic">D</span>, (<b>f</b>–<b>j</b>)), and maximum stomatal pore area (<span class="html-italic">a</span><sub>max</sub>, (<b>k</b>–<b>o</b>)) response to the rising atmospheric CO<sub>2</sub> concentration. Lines are the fitted regression. Shaded areas are the 95% confidence interval band.</p>
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<p>Contour plots showing the power law relationship between <span class="html-italic">a</span><sub>max</sub> and <span class="html-italic">D</span> in a logarithmic scale superimposed with the lines of equal <span class="html-italic">g</span><sub>sma<span class="html-italic">x</span></sub>; see Equation (1). (<b>a</b>) Clusters of five tree species in Fiji (<span class="html-italic">n</span> = 209). (<b>b</b>) Clusters of species from Florida (five species, <span class="html-italic">n</span> = 652) and Fiji coloured by location.</p>
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<p>Simulation of species physiological trait responses to rising atmospheric CO<sub>2</sub> concentration (<span class="html-italic">c</span><sub>a</sub>) using the BiomeBGC (BiomeBGC<sup>*</sup>) and empirical–biochemical (EB) models. (<b>a</b>) Dotplot of the simulated intrinsic water-use efficiency responses (ΔiWUE/Δ<span class="html-italic">c</span><sub>a</sub>) compared to the empirical results. (<b>b</b>) Dotplot of the simulated operational stomatal conductance response to the rising <span class="html-italic">c</span><sub>a</sub> (Δ<span class="html-italic">g</span><sub>s</sub>/Δ/Δ<span class="html-italic">c</span><sub>a</sub>). (<b>c</b>) Dotplot of the simulated photosynthesis responses to the rising <span class="html-italic">c</span><sub>a</sub> (Δ<span class="html-italic">A</span>/Δ<span class="html-italic">c</span><sub>a</sub>). Dotplots representing the mean of simulated values and whiskers indicating the 95% confidence interval (CI), calculated based on the quantiles of the output distribution. See <a href="#app1-biology-13-00733" class="html-app">Supplementary Table S3</a> for details.</p>
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18 pages, 3885 KiB  
Article
Triacontanol Reverses Abscisic Acid Effects on Stomatal Regulation in Solanum lycopersicum L. under Drought Stress Conditions
by María Asunción Bravo-Díaz, Emilia Ramos-Zambrano, Tomás Ernesto Juárez-Yáñez, María de Jesús Perea-Flores and Alma Leticia Martínez-Ayala
Horticulturae 2024, 10(9), 985; https://doi.org/10.3390/horticulturae10090985 - 18 Sep 2024
Viewed by 553
Abstract
When applied under abiotic stress conditions, triacontanol (TRIA) is effective in regulating the physicochemical processes in plants through mechanisms of defence such as abscisic acid (ABA) signalling. However, TRIA’s role in relation to ABA and stomatal opening is unclear. Therefore, the objective of [...] Read more.
When applied under abiotic stress conditions, triacontanol (TRIA) is effective in regulating the physicochemical processes in plants through mechanisms of defence such as abscisic acid (ABA) signalling. However, TRIA’s role in relation to ABA and stomatal opening is unclear. Therefore, the objective of this study was to evaluate the effects of TRIA and ABA and their combinations on different variables related to stomatal regulation in Solanum lycopersicum, which is subjected to drought stress, and on the leaf epidermis. The negative effects of stress and responses triggered by ABA were reversed in plants treated with TRIA. TRIA increased stomatal conductance and photosynthetic activity in the early hours, and it was determined that TRIA produced larger stomata than did the other treatments. Moreover, the chloroplasts of plants treated with TRIA were significantly smaller and more numerous than those of the control, which could improve CO2 diffusion efficiency and may be related to the regulation of stomatal opening and photosynthesis. Finally, the abaxial epidermis tests reaffirmed the inhibitory effects of TRIA on ABA on stomatal opening. These results confirm the important role of TRIA in regulating various processes in plants and processes triggered by ABA, such as those related to stomatal regulation. Full article
(This article belongs to the Section Biotic and Abiotic Stress)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Experimental design of treatment application during the cultivation of <span class="html-italic">Solanum lycopersicum</span>. (<b>a</b>) Graphic description of design, in which each color indicates the treatment applied in normal and drought stress in plants. (<b>b</b>) treatments applied during the cultivation of <span class="html-italic">Solanum lycopersicum</span> in two stages of plant growth: 30 d and 45 d after germination.</p>
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<p>Graphic description of treatments applied during cultivation of <span class="html-italic">Solanum lycopersicum</span>. Stages of plant growth and application of treatments at 30 d and 45 d after germination; readings of chlorophyll content, photosystem II efficiency, morphometric characterisation of stomata, and chloroplasts at 60 d after germination.</p>
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<p>Chlorophyll content [SPAD] in plants exposed to two water flows (normal conditions and drought stress) and different treatments (Control, TRIA, ABA, and TRIA + ABA). Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05, in which treatments were the predominant factor.</p>
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<p>Operating efficiency of PSII photochemistry, Fq′/Fm′ (ϕPSII), in plants exposed to drought stress and different treatments: (<b>a</b>) ϕPSII at 9–10 a.m.; (<b>b</b>) ϕPSII at 12–1 p.m.; (<b>c</b>) ϕPSII at 4–5 p.m. Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05, in which water flow was the predominant factor at 9–10 a.m. and 4–5 p.m., while treatments were the predominant factor at 12–1 p.m.</p>
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<p>Stomatal conductance in mmol m<sup>−2</sup> s<sup>−1</sup> in plants exposed to drought stress and different treatments: (<b>a</b>) 6–8 a.m.; (<b>b</b>) 9–10 a.m.; (<b>c</b>) 12–1 p.m.; (<b>d</b>) 4–5 p.m. Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05, in which water flow was the predominant factor at 6–8 a.m., 9–10 a.m., and 12–1 p.m., while treatments were the predominant factor at 4–5 p.m.</p>
Full article ">Figure 6
<p>Morphometric characteristics of stomata from plants exposed to drought stress and different treatments: (<b>a</b>) Micrographs of stomata obtained using an optical microscope. Reference bar: 50 µm. (<b>b</b>) Stomatal density/mm<sup>2</sup> area. (<b>c</b>) Area calculated with the equation <span class="html-italic">A</span> = <span class="html-italic">ab</span><span class="html-italic">π</span>. (<b>d</b>) Stomatal aspect ratio. Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05, in which treatments were the predominant factor in stomatal characteristics.</p>
Full article ">Figure 7
<p>Micrographs and morphometric characteristics of chloroplasts from plants exposed to drought stress and different treatments: (<b>a</b>) Micrographs obtained using a confocal laser scanning microscope, reference bar: 20 µm. (<b>b</b>) Chloroplast size in µm<sup>3</sup>. (<b>c</b>) Chloroplast number per 10,000 µm<sup>3</sup>. Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05, in which the interaction of two factors was predominant in the chloroplast characteristics.</p>
Full article ">Figure 8
<p>Effect of TRIA on stomatal opening under light conditions and its effects together with ABA in epidermal strips. Values represent the mean ± SE of at least three replicates. Different letters indicate significant differences, Fisher’s LSD, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Correlation of results obtained under TRIA application in <span class="html-italic">Solanum lycopersicum</span> plants under drought stress conditions compared to the control. Up arrows indicate an increase, down arrows indicate a decrease, and the symbol = represents no significant differences.</p>
Full article ">
15 pages, 2028 KiB  
Article
Effect of CO2 Elevation on Tomato Gas Exchange, Root Morphology and Water Use Efficiency under Two N-Fertigation Levels
by Manyi Zhang, Wentong Zhao, Chunshuo Liu, Changtong Xu, Guiyu Wei, Bingjing Cui, Jingxiang Hou, Heng Wan, Yiting Chen, Jiarui Zhang and Zhenhua Wei
Plants 2024, 13(17), 2373; https://doi.org/10.3390/plants13172373 - 26 Aug 2024
Viewed by 459
Abstract
Atmospheric elevated CO2 concentration (e[CO2]) decreases plant nitrogen (N) concentration while increasing water use efficiency (WUE), fertigation increases crop nutrition and WUE in crop; yet the interactive effects of e[CO2] coupled with two N-fertigation levels [...] Read more.
Atmospheric elevated CO2 concentration (e[CO2]) decreases plant nitrogen (N) concentration while increasing water use efficiency (WUE), fertigation increases crop nutrition and WUE in crop; yet the interactive effects of e[CO2] coupled with two N-fertigation levels during deficit irrigation on plant gas exchange, root morphology and WUE remain largely elusive. The objective of this study was to explore the physiological and growth responses of ambient [CO2] (a[CO2], 400 ppm) and e[CO2] (800 ppm) tomato plant exposed to two N-fertigation regimes: (1) full irrigation during N-fertigation (FIN); (2) deficit irrigation during N-fertigation (DIN) under two N fertilizer levels (reduced N (N1, 0.5 g pot−1) and adequate N (N2, 1.0 g pot−1). The results indicated that e[CO2] associated with DIN regime induced the lower N2 plant water use (7.28 L plant−1), maintained leaf water potential (−5.07 MPa) and hydraulic conductivity (0.49 mol m−2 s−1 MPa−1), greater tomato growth in terms of leaf area (7152.75 cm2), specific leaf area (223.61 cm2 g−1), stem and total dry matter (19.54 g and 55.48 g). Specific root length and specific root surface area were increased under N1 fertilization, and root tissue density was promoted in both e[CO2] and DIN environments. Moreover, a smaller and denser leaf stomata (4.96 µm2 and 5.37 mm−2) of N1 plant was obtained at e[CO2] integrated with DIN strategy. Meanwhile, this combination would simultaneously reduce stomatal conductance (0.13 mol m−2 s−1) and transpiration rate (1.91 mmol m−2 s−1), enhance leaf ABA concentration (133.05 ng g−1 FW), contributing to an improvement in WUE from stomatal to whole-plant scale under each N level, especially for applying N1 fertilization (125.95 µmol mol−1, 8.41 µmol mmol−1 and 7.15 g L−1). These findings provide valuable information to optimize water and nitrogen fertilizer management and improve plant water use efficiency, responding to the potential resource-limited and CO2-enriched scenario. Full article
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Figure 1
<p>Leaf photosynthetic rate (P<sub>n</sub>) (<b>a</b>), stomatal conductance (g<sub>s</sub>) (<b>b</b>), transpiration rate (T<sub>r</sub>) (<b>c</b>), abscisic acid ([ABA]<sub>leaf</sub>) (<b>d</b>), intrinsic water use efficiency (WUE<sub>i</sub>) (<b>e</b>) and instantaneous water use efficiency (WUE<sub>n</sub>) (<b>f</b>) of tomato plants were affected by [CO<sub>2</sub>] concentration (<span class="html-italic">a</span>[CO<sub>2</sub>] and <span class="html-italic">e</span>[CO<sub>2</sub>]), N-fertigation regime (full irrigation during N-fertigation, FIN; deficit irrigation during N-fertigation, DIN) and N fertilizer level (N1 and N2). Error bars indicate standard error of the mean (n = 4). The results of ANOVA are shown in <a href="#plants-13-02373-t001" class="html-table">Table 1</a>.</p>
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<p>Leaf water potential (Ψ<sub>l</sub>) (<b>a</b>), leaf hydraulic conductivity (K<sub>l</sub>) (<b>b</b>), stomatal aperture (SA) (<b>c</b>) and stomatal density (SD) (<b>d</b>) of tomato plants were affected by [CO<sub>2</sub>] concentration (<span class="html-italic">a</span>[CO<sub>2</sub>] and <span class="html-italic">e</span>[CO<sub>2</sub>]), N-fertigation regime (full irrigation during N-fertigation, FIN; deficit irrigation during N-fertigation, DIN) and N fertilizer level (N1 and N2). Error bars indicate standard error of the mean (n = 4). The results of ANOVA are shown in <a href="#plants-13-02373-t001" class="html-table">Table 1</a>.</p>
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<p>Leaf area (LA) (<b>a</b>) and specific leaf area (SLA) (<b>b</b>) of tomato plants were affected by [CO<sub>2</sub>] concentration (<span class="html-italic">a</span>[CO<sub>2</sub>] and <span class="html-italic">e</span>[CO<sub>2</sub>]), N-fertigation regime (full irrigation during N-fertigation, FIN; deficit irrigation during N-fertigation, DIN) and N fertilizer level (N1 and N2). Error bars indicate standard error of the mean (n = 4). The results of ANOVA are shown in <a href="#plants-13-02373-t003" class="html-table">Table 3</a>. Different letters after the means indicate significant differences among treatments determined by Tukey’s multiple range test at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Leaf dry matter (LDM) (<b>a</b>), stem dry matter (SDM) (<b>b</b>), root dry matter (RDM) (<b>c</b>), total dry matter (TDM) (<b>d</b>), plant water use (PWU) (<b>e</b>) and plant water use efficiency (WUEp) (<b>f</b>) of tomato plants were affected by [CO<sub>2</sub>] concentration (<span class="html-italic">a</span>[CO<sub>2</sub>] and <span class="html-italic">e</span>[CO<sub>2</sub>]), N-fertigation regime (full irrigation during N-fertigation, FIN; deficit irrigation during N-fertigation, DIN) and N fertilizer level (N1 and N2). Error bars indicate standard error of the mean (n = 4). The results of ANOVA are shown in <a href="#plants-13-02373-t003" class="html-table">Table 3</a>.</p>
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<p>PCA diagram of tomato plants was affected by [CO<sub>2</sub>] concentration (<span class="html-italic">a</span>[CO<sub>2</sub>] and <span class="html-italic">e</span>[CO<sub>2</sub>]), N-fertigation regime (full irrigation during N-fertigation, FIN; deficit irrigation during N-fertigation, DIN) and N fertilizer level (N1 and N2). Ultramarine vectors were related to P<sub>n</sub>, g<sub>s</sub>, T<sub>r</sub>, [ABA]<sub>leaf</sub>, WUE<sub>i</sub>, WUE<sub>n</sub>, Ψ<sub>l</sub>, K<sub>l</sub>, SA and SD; amaranth vectors were related to LA, SLA, LDM, SDM and RDM; aurantia vectors were related to RL, RD, RSA, RV, SRL, SRSA, RLD and RTD; red vectors were related to TDM, PWU and WUE<sub>p</sub>.</p>
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17 pages, 3811 KiB  
Article
Comparison of Growth and Metabolomic Profiles of Two Afforestation Cypress Species Cupressus chengiana and Platycladus orientalis Grown at Minjiang Valley in Southwest China
by Zhengqiao Liao, Lijun Zhu, Lei Liu, Jürgen Kreuzwieser, Christiane Werner and Baoguo Du
Metabolites 2024, 14(8), 453; https://doi.org/10.3390/metabo14080453 - 17 Aug 2024
Cited by 1 | Viewed by 484
Abstract
In recent years, afforestation has been conducted in China’s hot and dry valleys. However, there is still a paucity of knowledge regarding the performance of tree species in these semi-arid regions, particularly with regard to interspecies differences. The present study compares the growth [...] Read more.
In recent years, afforestation has been conducted in China’s hot and dry valleys. However, there is still a paucity of knowledge regarding the performance of tree species in these semi-arid regions, particularly with regard to interspecies differences. The present study compares the growth and metabolome characteristics of two widely used cypress species, namely Cupressus chengiana and Platycladus orientalis, grown at two sites with distinct climate conditions in the hot and dry Minjiang Valley in southwestern China. The findings indicate that C. chengiana trees exhibit superior growth rates compared to P. orientalis trees at both study sites. In comparison to P. orientalis trees, C. chengiana trees demonstrated a greater tendency to close their stomata in order to prevent water loss at the hotter and drier site, Llianghekou (LHK). Additionally, C. chengiana trees exhibited significantly lower hydrogen peroxide levels than P. orientalis trees, either due to lower production and/or higher scavenging of reactive oxygen species. C. chengiana trees accumulated soluble sugars as well as sugar derivatives, particularly those involved in sucrose and galactose metabolisms under stressful conditions. The species-specific differences were also reflected in metabolites involved in the tricarboxylic acid cycle, nitrogen, and secondary metabolisms. The metabolome profiles of the two species appeared to be influenced by the prevailing climatic conditions. It appeared that the trees at the drier and hotter site, LHK, were capable of efficient nitrogen uptake from the soil despite the low soil nitrogen concentration. This study is the first to compare the growth performance and metabolic profiles of two widely used tree species with high resistance to adverse conditions. In addition to the species-specific differences and adaptations to different sites, the present study also provides insights into potential management strategies to alleviate abiotic stress, particularly with regard to nitrogen nutrients, in the context of climate change. Full article
(This article belongs to the Special Issue Metabolic Responses of Plants to Abiotic Stress)
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Figure 1
<p>Soil water content (<b>a</b>), organic matter (<b>b</b>), organic carbon (<b>c</b>), total nitrogen (<b>d</b>), total phosphorus (<b>e</b>), and nitrogen to phosphorus (N/P) ratio (<b>f</b>) at the field sites of Cuojishan (CJS) and Lianghekou (LHK). Soil parameters were determined at two depths of 0–20 cm (without hatching) and 20–40 cm (hatched bar). Asterisks indicate significant differences between the two sites within the same depth (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01). Different upper-case and lower-case letters indicate significant differences between the two soil depths at CJS and LHK, respectively. Data shown means ± SE (n = 6) on a dry weight basis.</p>
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<p>Tree height (<b>a</b>), diameter at 5 cm above ground (<b>b</b>), leaf hydration (<b>c</b>), δ13C (<b>d</b>), hydrogen peroxide (<b>e</b>) and malondialdehyde contents (<b>f</b>) of <span class="html-italic">Platycladus orientalis</span> (yellow) and <span class="html-italic">Cupressus chengiana</span> (red) at Cuojishan (CJS, right panel, without hatching) and Lianghekou (LHK, left panel, hatched bars). Asterisks indicate significant differences between the two species within the same site (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001). Different upper-case and lower-case letters indicate significant differences between the two sites within the same species, respectively. Data shown means ± SE (n = 6 for <b>c</b>–<b>f</b>, n = 31–38 for <b>a</b>,<b>b</b>) on a dry weight basis.</p>
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<p>Total carbon (C), nitrogen (N), phosphorus (P) contents and their ratios (<b>a</b>–<b>f</b>), soluble sugar (<b>g</b>), amino acid (<b>h</b>), soluble protein (<b>i</b>), and δ15N (<b>j</b>) in leaves of <span class="html-italic">Platycladus orientalis</span> (yellow) and <span class="html-italic">Cupressus chengiana</span> (red) at Cuojishan (CJS, right panel, without hatching) and Lianghekou (LHK, left panel, hatched bars). Asterisks indicate significant differences between the two species within the same site (**, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001). Different upper-case and lower-case letters indicate significant differences between the two sites within the same species, respectively. Data shown means ± SE (n = 6) on a dry weight basis.</p>
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<p>Fold change (log2) of sugars, organic acids, polyols, and other compounds in leaves of <span class="html-italic">Platycladus orientalis</span> and <span class="html-italic">Cupressus chengiana</span> between Lianghekou (LHK) and Cuojishan (CJS) (<b>left panels</b>) and between <span class="html-italic">C. chengiana</span> and <span class="html-italic">P. orientalis</span> at CJS and LHK (<b>right panels</b>). Asterisks indicate significant differences between CJS and LHK within the same species and between the two species within the same site (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001). Data shown means ± SE (n = 6) on a dry weight basis.</p>
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<p>Fold change (log2) of amino acids and other N-compounds and aromatic compounds in leaves of <span class="html-italic">Platycladus orientalis</span> and <span class="html-italic">Cupressus chengiana</span> between Lianghekou (LHK) and Cuojishan (CJS) (<b>left panels</b>) and between <span class="html-italic">C. chengiana</span> and <span class="html-italic">P. orientalis</span> at CJS and LHK (<b>right panels</b>). Asterisks indicate significant differences between CJS and LHK within the same species and between the two species within the same site (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001). Data shown means ± SE (n = 6) on a dry weight basis.</p>
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<p>Clustering of all physiological and metabolic parameters in leaves of <span class="html-italic">Platycladus orientalis</span> (triangle) and <span class="html-italic">Cupressus chengiana</span> (circle) at Cuojishan (CJS) and Lianghekou (LHK). Semi-transparent shadings indicate 95% confidence regions.</p>
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<p>Top 20 parameters of component 1 (upper panel, <b>a</b>) and component 2 (lower panel, <b>b</b>) according to the VIP scores of PLS-DA analysis.</p>
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15 pages, 13437 KiB  
Article
Integrative Analysis of Transcriptomic Profiles and Physiological Responses Provide New Insights into Drought Stress Tolerance in Oil Palm (Elaeis guineensis Jacq.)
by Fernan Santiago Mejía-Alvarado, Arley Fernando Caicedo-Zambrano, David Botero-Rozo, Leonardo Araque, Cristihian Jarri Bayona-Rodríguez, Seyed Mehdi Jazayeri, Carmenza Montoya, Iván Ayala-Díaz, Rodrigo Ruiz-Romero and Hernán Mauricio Romero
Int. J. Mol. Sci. 2024, 25(16), 8761; https://doi.org/10.3390/ijms25168761 - 12 Aug 2024
Cited by 1 | Viewed by 849
Abstract
Oil palm (Elaeis guineensis Jacq.) is a highly productive crop economically significant for food, cosmetics, and biofuels. Abiotic stresses such as low water availability, salt accumulation, and high temperatures severely impact oil palm growth, physiology, and yield by restricting water flux among [...] Read more.
Oil palm (Elaeis guineensis Jacq.) is a highly productive crop economically significant for food, cosmetics, and biofuels. Abiotic stresses such as low water availability, salt accumulation, and high temperatures severely impact oil palm growth, physiology, and yield by restricting water flux among soil, plants, and the environment. While drought stress’s physiological and biochemical effects on oil palm have been extensively studied, the molecular mechanisms underlying drought stress tolerance remain unclear. Under water deficit conditions, this study investigates two commercial E. guineensis cultivars, IRHO 7001 and IRHO 2501. Water deficit adversely affected the physiology of both cultivars, with IRHO 2501 being more severely impacted. After several days of water deficit, there was a 40% reduction in photosynthetic rate (A) for IRHO 7001 and a 58% decrease in IRHO 2501. Further into the drought conditions, there was a 75% reduction in A for IRHO 7001 and a 91% drop in IRHO 2501. Both cultivars reacted to the drought stress conditions by closing stomata and reducing the transpiration rate. Despite these differences, no significant variations were observed between the cultivars in stomatal conductance, transpiration, or instantaneous leaf-level water use efficiency. This indicates that IRHO 7001 is more tolerant to drought stress than IRHO 2501. A differential gene expression and network analysis was conducted to elucidate the differential responses of the cultivars. The DESeq2 algorithm identified 502 differentially expressed genes (DEGs). The gene coexpression network for IRHO 7001 comprised 274 DEGs and 46 predicted HUB genes, whereas IRHO 2501’s network included 249 DEGs and 3 HUB genes. RT-qPCR validation of 15 DEGs confirmed the RNA-Seq data. The transcriptomic profiles and gene coexpression network analysis revealed a set of DEGs and HUB genes associated with regulatory and transcriptional functions. Notably, the zinc finger protein ZAT11 and linoleate 13S-lipoxygenase 2-1 (LOX2.1) were overexpressed in IRHO 2501 but under-expressed in IRHO 7001. Additionally, phytohormone crosstalk was identified as a central component in the response and adaptation of oil palm to drought stress. Full article
(This article belongs to the Special Issue Recent Research in Plant Abiotic Stress)
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<p>Physical appearance of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation for three weeks (drought stress).</p>
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<p>Predawn leaf water potential (Ψleaf) of two oil palm cultivars, Deli × La Mé (IRHO 7001 and IRHO 2501), in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Each box corresponds to the mean ± SD (<span class="html-italic">n</span> = 6).</p>
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<p>Physiological response of two oil palm cultivars, Deli × La Mé, IRHO 7001 (7001) and IRHO 2501 (2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Each box corresponds to the mean ± SD. (<span class="html-italic">n</span> = 6). (<b>A</b>). photosynthetic rate (<span class="html-italic">A</span>), (<b>B</b>). stomatal conductance (<span class="html-italic">gs</span>), (<b>C</b>). transpiration rate (E), and (<b>D</b>). instantaneous leaf-level water use efficiency (WUE).</p>
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<p>DEGs of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. (<b>A</b>) Heatmap of the RNA-Seq samples. A tendency toward red indicates under-expression, while a tendency toward blue indicates overexpression. (<b>B</b>) Unique and shared DEGs between two contrasting oil palm genotypes and drought stress conditions. The color key scale corresponds to the L2FC, tendency to blue correspond to underexpressed genes, while tendency to red indicates overexpressed.</p>
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<p>Gene coexpression networks of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. (<b>A</b>) General; (<b>B</b>) IRHO 7001; and (<b>C</b>) IRHO 2501. The igraph R package was used to construct the general and specific cultivar coexpression networks under drought stress. Each node (sphere or bead-like shape) represents a gene, and groups of nodes highlighted with the same color indicate a module of genes. The black edges represent direct correlations between genes, and the red lines represent inverse correlations. The size of each node is proportional to the mean expression level of the gene represented by the node.</p>
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<p>Relative quantification of 15 genes by RT–qPCR compared against RNA-Seq in two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. Ninety-day-old palms were maintained under field capacity (well-watered) or subjected to water deprivation until the photosynthetic rate of the IRHO 7001 cultivar dropped 40% (40%), which is considered moderate drought stress, or until it dropped 75% (75%), which is considered severe drought stress. Yellow bars indicate the relative expression value obtained by RT-qPCR. Lite blue diamonds indicate the RNA-Seq value. (<b>A</b>) WRKY transcription factor 51; (<b>B</b>) NAC transcription factor NAM-B2-like_ NAM-B2; (<b>C</b>) beta-xylosidase alpha-L-arabinofuranosidase 2-like OsI_08964_ BXL1; (<b>D</b>) Leucine-rich repeat receptor-like serine_ At1g17230; (<b>E</b>) Calcium-binding protein CML42; (<b>F</b>) Ser/threo-protein phosphatase 6 regulatory ankyrin repeat subunit B; (<b>G</b>) Pectinesterase-like; (<b>H</b>) Pentatricopeptide repeat-containing protein_ At5g39980; (<b>I</b>) Multiple C2 and transmembrane domain-containing protein 2-like, (<b>J</b>) Non-specific lipid-transfer protein 2-like; (<b>K</b>) Transcription factor bHLH35-like isoform X1; (<b>L</b>) Mitogen-activated protein kinase kinase kinase 2-like; (<b>M</b>) Bidirectional sugar transporter SWEET14-like; (<b>N</b>) Galactinol synthase 1-like_ GOLS1; and (<b>O</b>) Xyloglucan endotransglucosylase/hydrolase protein 22-like XTH22.</p>
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<p>Phytohormone crosstalk and signal cascades of two oil palm cultivars, Deli × La Mé, (IRHO 7001 and IRHO 2501) in response to water deficit. The numbers indicate the step-by-step signaling cascade response in oil palms under drought stress. Numbers 1 and 2 indicate the stimulus and signal perception. 3 indicates signal transduction. 4, 5, and 6 indicate phytohormone metabolism and TFs activation/ inactivation. 7 and 8 indicate drought stress-induced genes and ROS metabolism balance. Gene expression levels are indicated for each cultivar, where 7001 = IRHO 7001 and 2501 = IRHO 2501. The square color corresponds to the gene expression color scale in the L2FC bar. The question mark indicates no gene expression. Arrows colors indicate flux of water (blue), ABA (green), and ROS (red) from soil or roots to leaves. The figure was partly generated using plant icon adaptations licensed and created by Guillaume Lobet (<a href="https://figshare.com/authors/Plant_Illustrations/3773596" target="_blank">https://figshare.com/authors/Plant_Illustrations/3773596</a> is licensed under CC-BY 4.0 Unported <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a>, accessed on 16 April 2024).</p>
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17 pages, 6630 KiB  
Article
Interpreting Controls of Stomatal Conductance across Different Vegetation Types via Machine Learning
by Runjia Xue, Wenjun Zuo, Zhaowen Zheng, Qin Han, Jingyan Shi, Yao Zhang, Jianxiu Qiu, Sheng Wang, Yan Zhu, Weixing Cao and Xiaohu Zhang
Water 2024, 16(16), 2251; https://doi.org/10.3390/w16162251 - 9 Aug 2024
Viewed by 883
Abstract
Plant stomata regulate transpiration (T) and CO2 assimilation, essential for the water–carbon cycle. Quantifying how environmental factors influence stomatal conductance will provide a scientific basis for understanding the vegetation–atmosphere water–carbon exchange process and water use strategies. Based on eddy covariance [...] Read more.
Plant stomata regulate transpiration (T) and CO2 assimilation, essential for the water–carbon cycle. Quantifying how environmental factors influence stomatal conductance will provide a scientific basis for understanding the vegetation–atmosphere water–carbon exchange process and water use strategies. Based on eddy covariance and hydro-metrological observations from FLUXNET sites with four plant functional types and using three widely applied methods to estimate ecosystem T from eddy covariance data, namely uWUE, Perez-Priego, and TEA, we quantified the regulation effect of environmental factors on canopy stomatal conductance (Gs). The environmental factors considered here include radiation (net radiation and solar radiation), water (soil moisture, relative air humidity, and vapor pressure deficit), temperature (air temperature), and atmospheric conditions (CO2 concentration and wind speed). Our findings reveal variation in the influence of these factors on Gs across biomes, with air temperature, relative humidity, soil water content, and net radiation being consistently significant. Wind speed had the least influence. Incorporating the leaf area index into a Random Forest model to account for vegetation phenology significantly improved model accuracy (R2 increased from 0.663 to 0.799). These insights enhance our understanding of the primary factors influencing stomatal conductance, contributing to a broader knowledge of vegetation physiology and ecosystem functioning. Full article
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<p>Locations of the study sites.</p>
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<p>Histogram of the importance of <span class="html-italic">G</span><sub>s</sub> characteristics at each site. The y-axis starts at −0.5 because the importance and error bars exceed 0 for some sites, and the negative y indicates that the feature hurts the RF prediction results.</p>
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<p>Histogram of the importance of <span class="html-italic">G</span><sub>s</sub> characteristics at each site. The y-axis starts at −0.5 because the importance and error bars exceed 0 for some sites, and the negative y indicates that the feature hurts the RF prediction results.</p>
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<p>Model accuracy of before (Benchmark) and after adding LAI (LAI). The darker colors in the panels correspond to higher values. (<b>a</b>) presents R<sup>2</sup> results for the training set, while (<b>b</b>) displays R<sup>2</sup> results for the test set. (<b>c</b>) shows RMSE outcomes for the training set, and (<b>d</b>) outlines RMSE results for the test set.</p>
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<p>Histogram of the importance of <span class="html-italic">G</span><sub>s</sub> characteristics at each site (adding LAI). The y-axis starts at −0.5 because the importance and error bars exceed 0 for some sites, and the negative y indicates that the feature hurts the RF prediction results.</p>
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<p>Histogram of the importance of <span class="html-italic">G</span><sub>s</sub> characteristics at each site (adding LAI). The y-axis starts at −0.5 because the importance and error bars exceed 0 for some sites, and the negative y indicates that the feature hurts the RF prediction results.</p>
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13 pages, 1567 KiB  
Article
Escherichia coli Inoculation Decreases the Photosynthetic Performance on Tomato Plants: Clarifying the Impact of Human Commensal Bacteria on Transient Plant Hosts
by Anicia Gomes, Conceição Santos, Lia-Tânia Dinis and Rafael J. Mendes
Horticulturae 2024, 10(7), 758; https://doi.org/10.3390/horticulturae10070758 - 17 Jul 2024
Viewed by 712
Abstract
The commensal/pathogenic Escherichia coli affects humans and animals, being present in diverse environmental niches, possibly surviving due to its adaptation to transient plant hosts like crops, increasing the risk of foodborne diseases. E. coli interaction with the plant host remains unknown, particularly the [...] Read more.
The commensal/pathogenic Escherichia coli affects humans and animals, being present in diverse environmental niches, possibly surviving due to its adaptation to transient plant hosts like crops, increasing the risk of foodborne diseases. E. coli interaction with the plant host remains unknown, particularly the impacts on photosynthesis. We hypothesize that E. coli influences the tomato transient host’s photosynthetic capacity. To validate this hypothesis, we exposed 57-day-old tomato plants (Solanum lycopersicum) to different inoculation conditions, namely, non-inoculated plants (negative control, C−); plants directly injected with E. coli SL6.1 (107 CFU/mL) (positive control, C+); plants irrigated one time with E. coli SL6.1 (107 CFU/mL); and plants chronically irrigated with E. coli SL6.1 (104 CFU/mL). No significant changes were observed in chlorophyll fluorescence, pigments’ contents, morphological aspects, and fruiting in all conditions. However, irrigated plants (chronically and one-time contaminated) had decreased stomatal conductance (gs, 31.07 and 34.42 mol m−2 s−1, respectively, vs. 53.43 and 48.08 mol m−2 s−1 in C− and C+, respectively), transpiration rate (E, 0.32 and 0.35 mol m−2 s−1 in chronically and one-time contaminated conditions vs. 0.57 and 0.48 mol m−2 s−1 in C− and C+, respectively), and a trend of increased intrinsic carboxylation (Ci, 384 and 361 ppm in chronically and one-time irrigated plants vs. 321 and 313 ppm in C− and C+, respectively). The one-time inoculated plants presented more severe effects than the remaining conditions, with lower net photosynthetic rate (PN, 0.93 vs. 3.94–5.96 μmol (CO2) m−2 s−1 in the other conditions), intrinsic water use efficiency (iWUE, 33.1 vs. 74.51–184.40 μmol (CO2)/mmol (H2O) in the chronically irrigated and the control plants), and intrinsic carboxylation efficiency (iCE, 0.003 vs. 0.012–0.022 μmol (CO2)/ppm in the remaining conditions). Our data support that some observed effects are similar to those associated with phytopathogenic bacteria. Lastly, we propose that the decrease in some parameters of gas exchange requires direct contact with the leaf/stomata, and is mainly observed for high concentrations of E. coli. Full article
(This article belongs to the Section Plant Pathology and Disease Management (PPDM))
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<p>Effects of inoculation of <span class="html-italic">Escherichia coli</span> in the (<b>A</b>) minimal fluorescence yield (F<sub>0</sub>); (<b>B</b>) variable fluorescence (F<sub>v</sub>); (<b>C</b>) maximum fluorescence yield of the dark-adapted leaves (F<sub>m</sub>); (<b>D</b>) maximum PSII efficiency (F<sub>v</sub>/F<sub>m</sub>); (<b>E</b>) maximum efficiency of PSII photochemistry (F<sub>v</sub>′/F<sub>m</sub>′); (<b>F</b>) photochemical quenching (qP); (<b>G</b>) effective photochemical efficiency of PSII (Ф<sub>PSII</sub>); and (<b>H</b>) non-photochemical quenching (NPQ). Negative control (C−): plants not inoculated with <span class="html-italic">E. coli</span>; positive control (C+): plants stem-injected with 100 µL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; one-time: inoculation by irrigation with only one aerial irrigation (approximately 20 cm above the soil) with 60 mL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; and chronic: inoculation by chronic irrigation with 60 mL of water containing 10<sup>4</sup> CFU/mL of <span class="html-italic">E. coli</span> once a week until the end of the study. Vertical bars: mean value with standard deviation (<span class="html-italic">n</span> = 5). Different letters mean statistically significant differences, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of the inoculation of <span class="html-italic">Escherichia coli</span> chlorophylls (<b>A</b>–<b>C</b>) and carotenoid contents (<b>D</b>) in tomato plants. Negative control (C−): plants not inoculated with <span class="html-italic">E. coli</span>; positive control (C+): plants stem-injected with 100 µL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; one-time: inoculation by irrigation with only one aerial irrigation (approximately 20 cm above the soil) with 60 mL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; and chronic: inoculation by chronic irrigation with 60 mL of water containing 10<sup>4</sup> CFU/mL of <span class="html-italic">E. coli</span> once a week until the end of the study. Vertical bars: mean value with standard deviation (<span class="html-italic">n</span> = 5). Different letters mean significant differences, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of inoculation of <span class="html-italic">Escherichia coli</span> on (<b>A</b>) stomatal conductance (gs); (<b>B</b>) transpiration rate (E); (<b>C</b>) intercellular CO<sub>2</sub> concentration (Ci); (<b>D</b>) intercellular and atmospheric CO<sub>2</sub> concentration ratio (Ci/Ca); (<b>E</b>) net photosynthetic rate (P<sub>N</sub>); (<b>F</b>) intrinsic water-use efficiency (iWUE); and (<b>G</b>) intrinsic carboxylation efficiency (iCE). Negative control (C−): plants not inoculated with <span class="html-italic">E. coli</span>; positive control (C+): plants stem-injected with 100 µL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; one-time: inoculation by irrigation with only one aerial irrigation (approximately 20 cm above the soil) with 60 mL of 10<sup>7</sup> CFU/mL of <span class="html-italic">E. coli</span>; and chronic: inoculation by chronic irrigation with 60 mL of water containing 10<sup>4</sup> CFU/mL of <span class="html-italic">E. coli</span> once a week until the end of the study. Vertical bars: mean value with standard deviation (<span class="html-italic">n</span> = 5). Different letters mean significant differences, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>PCA biplot of the effects on photosynthetic parameters of one-time and chronic exposure through irrigation, as well as stem inoculation (C+) of plants with <span class="html-italic">Escherichia coli</span> on tomato plants. Loading plot for the first axis, PC1, explained 50.23% of the variance, and the second axis, PC2, explained 30.61%.</p>
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14 pages, 1400 KiB  
Article
Morphological and Anatomical Differentiation of Potamogeton gramineus in Relation to the Presence of Invasive Species Elodea nuttallii: A Case Study from Vlasina Lake, Serbia
by Danijela Nikolić, Dragana Jenačković Gocić, Irena Raca, Miodrag Đorđević, Ana Savić and Marina Jušković
Plants 2024, 13(14), 1937; https://doi.org/10.3390/plants13141937 - 14 Jul 2024
Viewed by 3285
Abstract
Elodea nuttallii represents non-native and highly invasive species in Europe that significantly influence freshwater plant communities by decreasing the diversity of native species. This study aimed to determine whether the morphological and anatomical features of Potamogeton gramineus, a native species in Vlasina [...] Read more.
Elodea nuttallii represents non-native and highly invasive species in Europe that significantly influence freshwater plant communities by decreasing the diversity of native species. This study aimed to determine whether the morphological and anatomical features of Potamogeton gramineus, a native species in Vlasina Lake, differ between sites where it coexists with E. nuttallii and those where E. nuttallii is not present. Environmental variables such as water depth, temperature, pH, conductivity, saturation, and O2 concentration were included in the analysis. Analyses were conducted on 32 morphological and anatomical features of P. gramineus collected from six sites within Vlasina Lake, comprising three sites where E. nuttallii was present and three sites where it was absent. The datasets containing morphometric and environmental variables underwent analysis using standard univariate techniques (Descriptive, ANOVA), Tukey’s Honest Significant Difference (HSD) test, Student’s t-test, and the Mann–Whitney U test, as well as multivariate statistical methods such as Canonical Discriminant Analysis (CDA). The results show the presence of morphological differentiation among P. gramineus individuals across the analyzed sites. These findings suggest that morphological and anatomical features, such as epidermis, mesophyll, palisade, and aerenchyma tissue thickness in floating leaves, number, length, width, and the surface area of stomata, as well as the width of submersed leaves and stem aerenchyma tissue thickness, effectively differentiate individuals that coexist with E. nuttallii and individuals that growth without its presence. Moreover, they indicate that P. gramineus exhibits a notable ability to modify its morphological traits in response to invasion. Full article
(This article belongs to the Special Issue Plant Invasions across Scales)
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<p>Cross-sections taken in the midrib area of the floating, submersed leaves, and stems of <span class="html-italic">P. graminues</span> from six sites in Vlasina Lake. In sites I, II, and III, the invasive species <span class="html-italic">E. nuttallii</span> was absent, while in sites IV, V, and VI, it was present.</p>
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<p>Results of Canonical Discriminant Analysis (CDA) based on all morphological and anatomical features of <span class="html-italic">Potamogeton gramineus</span> population: (<b>A</b>) scatterplots with canonical scores for each individual in a space defined by the first and second CDA axes; (<b>B</b>) scatterplots with canonical scores for each individual in a space defined by the first and third CDA axes.</p>
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19 pages, 2975 KiB  
Article
Effect of Green Light Replacing Some Red and Blue Light on Cucumis melo under Drought Stress
by Xue Li, Shiwen Zhao, Qianqian Cao, Chun Qiu, Yuanyuan Yang, Guanzhi Zhang, Yongjun Wu and Zhenchao Yang
Int. J. Mol. Sci. 2024, 25(14), 7561; https://doi.org/10.3390/ijms25147561 - 10 Jul 2024
Viewed by 877
Abstract
Light quality not only directly affects the photosynthesis of green plants but also plays an important role in regulating the development and movement of leaf stomata, which is one of the key links for plants to be able to carry out normal growth [...] Read more.
Light quality not only directly affects the photosynthesis of green plants but also plays an important role in regulating the development and movement of leaf stomata, which is one of the key links for plants to be able to carry out normal growth and photosynthesis. By sensing changes in the light environment, plants actively regulate the expansion pressure of defense cells to change stomatal morphology and regulate the rate of CO2 and water vapor exchange inside and outside the leaf. In this study, Cucumis melo was used as a test material to investigate the mitigation effect of different red, blue, and green light treatments on short-term drought and to analyze its drought-resistant mechanism through transcriptome and metabolome analysis, so as to provide theoretical references for the regulation of stomata in the light environment to improve the water use efficiency. The results of the experiment showed that after 9 days of drought treatment, increasing the percentage of green light in the light quality significantly increased the plant height and fresh weight of the treatment compared to the control (no green light added). The addition of green light resulted in a decrease in leaf stomatal conductance and a decrease in reactive oxygen species (ROS) content, malondialdehyde MDA content, and electrolyte osmolality in the leaves of melon seedlings. It indicated that the addition of green light promoted drought tolerance in melon seedlings. Transcriptome and metabolome measurements of the control group (CK) and the addition of green light treatment (T3) showed that the addition of green light treatment not only effectively regulated the synthesis of abscisic acid (ABA) but also significantly regulated the hormonal pathway in the hormones such as jasmonic acid (JA) and salicylic acid (SA). This study provides a new idea to improve plant drought resistance through light quality regulation. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Effect of different treatments on photosynthetic characteristics of melon seedlings. (<b>a</b>) Effect of transpiration rate (E) between treatments; (<b>b</b>) effect of stomatal conductance (gsw) between treatments; (<b>c</b>) effect of intercellular CO<sub>2</sub> (Ci) between treatments; and (<b>d</b>) effect of net photosynthetic rate (Pn) between treatments. Note: in same figure, different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05), and same letters represent insignificant differences (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Effect of different treatments on relative electrolytes, MDA content, and SOD activity in melon seedlings. (<b>a</b>) Relative electrolytic leakage under different treatments measured on 3, 6, and 9 days. (<b>b</b>) MDA content under different treatments at 9 days. (<b>c</b>) SOD content under different treatments at 9 days. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05), while the same letters represent no significant differences (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Effect of different treatments on ROS in melon seedlings. (<b>a</b>) H<sub>2</sub>O<sub>2</sub> content under different treatments at 9 days. (<b>b</b>) DAB staining of melon seedling leaves under each treatment at 9 days. (<b>c</b>) O<sub>2</sub><sup>∙−</sup> content under different treatments at 9 days. (<b>d</b>) NBT staining of melon seedling leaves under each treatment at 9 days. Different letters represent significant differences (<span class="html-italic">p</span> &lt; 0.05), while the same letters represent no significant differences (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>RNA-Seq-based analysis of DEGs in melon seedlings under different treatments. (<b>a</b>) RNA-Seq-based heat map analysis of DEGs under different treatments in melon seedlings. (<b>b</b>) GO functional classification of DEGs in different treatments under drought stress. (<b>c</b>) Classification of KEGG pathways of DEGs in different treatments under drought stress.</p>
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<p>Analysis of plant hormone signal transduction pathways.</p>
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<p>LC-MS-based analysis of differential metabolites in melon seedlings under different treatments. (<b>a</b>) Metabolite pattern diagram for PCA analysis. (<b>b</b>) Classification of KEGG pathways of different treatment differential metabolites under drought. (<b>c</b>) Changes in metabolites related to phytohormone synthesis after different treatments.</p>
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<p>Spectrograms of different treatments.</p>
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13 pages, 2065 KiB  
Article
Estimation of Photosynthetic Induction Is Significantly Affected by Light Environments of Local Leaves and Whole Plants in Oryza Genus
by Zhuang Xiong, Jian Xiao, Jinfang Zhao, Sicheng Liu, Desheng Yang, Dongliang Xiong, Kehui Cui, Shaobing Peng and Jianliang Huang
Plants 2024, 13(12), 1646; https://doi.org/10.3390/plants13121646 - 14 Jun 2024
Viewed by 672
Abstract
Photosynthetic induction and stomatal kinetics are acknowledged as pivotal factors in regulating both plant growth and water use efficiency under fluctuating light conditions. However, the considerable variability in methodologies and light regimes used to assess the dynamics of photosynthesis (A) and [...] Read more.
Photosynthetic induction and stomatal kinetics are acknowledged as pivotal factors in regulating both plant growth and water use efficiency under fluctuating light conditions. However, the considerable variability in methodologies and light regimes used to assess the dynamics of photosynthesis (A) and stomatal conductance (gs) during light induction across studies poses challenges for comparison across species. Moreover, the influence of stomatal morphology on both steady-state and non-steady-state gs remains poorly understood. In this study, we show the strong impact of IRGA Chamber Illumination and Whole Plant Illumination on the photosynthetic induction of two rice species. Our findings reveal that these illuminations significantly enhance photosynthetic induction by modulating both stomatal and biochemical processes. Moreover, we observed that a higher density of smaller stomata plays a critical role in enhancing the stomatal opening and photosynthetic induction to fluctuating light conditions, although it exerts minimal influence on steady-state gs and A under constant light conditions. Therefore, future studies aiming to estimate photosynthetic induction and stomatal kinetics should consider the light environments at both the leaf and whole plant levels. Full article
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<p>Response of photosynthetic rate (<span class="html-italic">A</span>) and stomatal conductance (<span class="html-italic">g</span><sub>s</sub>) to a stepwise increase in irradiance (shade to white) across the two rice genotypes. WPI-ICI, WPS-ICI, WPI-ICS, and WPS-ICS represent measurements conducted under the Whole Plant Illumination and IRGA Chamber Illumination, Whole Plant Shading and IRGA Chamber Illumination, Whole Plant Illumination and IRGA Chamber Shading, and Whole Plant Shading and IRGA Chamber Shading conditions, respectively. The gray area (0–120 s) represents the initial phases at low light conditions for all measurements. The data presented are means (± SD) of all the treatments. The Standard Deviations (SDs) are shown in gray above and below the means for all the treatments.</p>
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<p>Response of intercellular CO<sub>2</sub> concentration (<span class="html-italic">C</span><sub>i</sub>) and intrinsic water use efficiency (<span class="html-italic">WUE</span><sub>i</sub>) to a stepwise increase in irradiance (shade to white) across the two rice genotypes. WPI-ICI, WPS-ICI, WPI-ICS, and WPS-ICS represent the measurements conducted under the Whole Plant Illumination and IRGA Chamber Illumination, Whole Plant Shading and IRGA Chamber Illumination, Whole Plant Illumination and IRGA Chamber Shading, and Whole Plant Shading and IRGA Chamber Shading conditions, respectively. The gray area (0–120 s) represents the initial phases at low light conditions for all measurements. The data presented are means (± SD) of all the treatments. The Standard Deviations (SDs) are shown in gray above and below the means for all the treatments.</p>
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<p>Transient stomatal and biochemical limitation to photosynthesis during light induction across the two rice genotypes. WPI-ICI, WPS-ICI, WPI-ICS, and WPS-ICS represent the measurements conducted under the Whole Plant Illumination and IRGA Chamber Illumination, Whole Plant Shading and IRGA Chamber Illumination, Whole Plant Illumination and IRGA Chamber Shading, and Whole Plant Shading and IRGA Chamber Shading conditions, respectively. The data presented are means (± SD) of the four measurements. The Standard Deviations (SDs) are shown in gray above and below the means for all the treatments.</p>
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<p>Comparison of stomatal morphology and stomatal conductance across the two rice genotypes. The adaxial and abaxial stomatal size and density are presented. <span class="html-italic">g</span><sub>s, steady</sub> is measured at a PPFD of 1500 µmol m<sup>−2</sup> s<sup>−1</sup> and CO<sub>2</sub> concentration of 400 µmol mol<sup>−1</sup>. <span class="html-italic">g</span><sub>s,max</sub> is calculated based on stomatal morphology according to Franks and Beerling (2009) [<a href="#B33-plants-13-01646" class="html-bibr">33</a>]. All the values are means (± SD) of the four measurements. Different letters indicate statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) across the two rice genotypes (<b>A</b>,<b>B</b>). Significance levels are indicated by *** and ns that indicate <span class="html-italic">p</span> &lt; 0.001 and <span class="html-italic">p</span> &gt; 0.05, respectively (<b>C</b>,<b>D</b>).</p>
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15 pages, 1921 KiB  
Article
New Data on Phytochemical and Morphophysiological Characteristics of Platycladus orientalis L. Franco and Thuja occidentalis L. Conifer Trees in Polluted Urban Areas of Kazakhstan
by Nurgul Yerezhepova, Meruyert Kurmanbayeva, Nina Terletskaya, Moldir Zhumagul, Marko Kebert, Milena Rašeta, Yusufjon Gafforov, Roza Jalmakhanbetova and Medeu Razhanov
Forests 2024, 15(5), 790; https://doi.org/10.3390/f15050790 - 30 Apr 2024
Viewed by 1053
Abstract
The adaptive potential of plants in urban environments, responding to factors like air pollution, electromagnetic radiation, and specific microclimates, remains insufficiently understood. Our study focused on two evergreen Cupressaceae family species, Thuja occidentalis L. and Platycladus orientalis L. Franco, which are commonly found [...] Read more.
The adaptive potential of plants in urban environments, responding to factors like air pollution, electromagnetic radiation, and specific microclimates, remains insufficiently understood. Our study focused on two evergreen Cupressaceae family species, Thuja occidentalis L. and Platycladus orientalis L. Franco, which are commonly found in Kazakhstan’s urban landscapes. Conducted in Almaty, one of Kazakhstan’s most polluted cities, our comparative analysis examined the anatomical features, photosynthetic activity, and secondary metabolite composition of these conifers. Both species exhibited xeromorphic traits, such as submerged stomata, resin passages, and a prominent leaf cuticle. T. occidentalis displayed higher photosynthetic activity values (quantum yield of photosystem II (YII), electron transport rate (ETR), and quantum yield of non-photochemical quenching (Y(NPQ))) than P. orientalis, while P. orientalis exhibited a higher quantum yield of non-regulated energy dissipation in PSII (Y(NO)) values. Chemical analysis revealed 31 components in T. occidentalis and 33 in P. orientalis, with T. occidentalis containing three times more thujone (16.42% and 5.18%, respectively) and a higher monosaccharide content (17.33% and 6.98%, respectively). T. occidentalis also contained 14.53% steroids, whereas P. orientalis showed no steroid presence. The cytotoxic activity of essential oils was determined by the survival of Artemia salina aquatic crustaceans, whereas tested essential oils from both species exhibited acute lethal toxicity to A. salina aquatic crustaceans across all tested concentrations. The connection between physiological traits, adaptation strategies, and cytotoxic effects offers a comprehensive view of the ecological and pharmacological importance of these two observed conifer species, highlighting their diverse roles in urban environments, as well as their potential medical uses. Full article
(This article belongs to the Section Forest Ecophysiology and Biology)
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<p>Cross section of the three scale-like leaves of <span class="html-italic">T. occidentalis</span>, revealing photosynthetic tissues and vascular bundles. (<b>a</b>) The scale bar represents 20 µm, indicating the magnification level of the image. (<b>b</b>) The scale bar represents 300 µm, indicating the magnification level of the image. This scale range (20–300 µm) allows for a better understanding of the size and structure of the observed anatomical features. The central leaf is rounded, and the two marginals are elongated. (1) The epidermis consists of a single cell layer, with thickened cell walls and a cuticle. The mesophyllum (m) is heterogenous. (2) The adaxial side comprises chlorenchyma with 2–3 cell layers, characterized by small, rounded cells containing numerous chloroplasts. (3) The inner part of the mesophyllum has large parenchymatic cells and intercellulars that are linked to the chlorenchyma with narrow bridges of small chlorenchymatic cells. (4) Surrounding the vascular bundle (VS), the innermost cell layer of the mesophyll consists of a single layer. The vascular bundle consists of (5) xylem (tracheids) in the inner region and (6) phloem (sieve cells) in the outer region. (7) Resin ducts are also evident.</p>
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<p>Cross section of a facial leaves of <span class="html-italic">P. orientalis</span>: e—epidermis; p—palisade mesophyll cell; s—spongy mesophyll cell; v—vein; rc—resin channel. (<b>a</b>) The scale bar represents 100 µm, indicating the magnification level of the image. (<b>b</b>) The scale bar represents 130 µm, indicating the magnification level of the image. This scale range (100–130 µm) allows for a better understanding of the size and structure of the observed anatomical features.</p>
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<p>Cross section of the facial leaves of <span class="html-italic">P. orientalis</span>. Letters in the images indicate the following: h—hypoderm; t—tannin; x—xylem; ph—phloem. (<b>a</b>) The scale bar represents 20 µm, indicating the magnification level of the image. (<b>b</b>) The scale bar represents 100 µm, indicating the magnification level of the image. This scale range (20–100 µm) allows for a better understanding of the size and structure of the observed anatomical features.</p>
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17 pages, 2133 KiB  
Article
Arbuscular Mycorrhizal Fungi Improve the Performance of Tempranillo and Cabernet Sauvignon Facing Water Deficit under Current and Future Climatic Conditions
by Daria Kozikova, Inmaculada Pascual and Nieves Goicoechea
Plants 2024, 13(8), 1155; https://doi.org/10.3390/plants13081155 - 22 Apr 2024
Cited by 1 | Viewed by 1154
Abstract
Climate change (CC) threatens Mediterranean viticulture. Rhizospheric microorganisms may be crucial for the adaptation of plants to CC. Our objective was to assess whether the association of two grapevine varieties with arbuscular mycorrhizal fungi (AMF) increases grapevine’s resilience to environmental conditions that combine [...] Read more.
Climate change (CC) threatens Mediterranean viticulture. Rhizospheric microorganisms may be crucial for the adaptation of plants to CC. Our objective was to assess whether the association of two grapevine varieties with arbuscular mycorrhizal fungi (AMF) increases grapevine’s resilience to environmental conditions that combine elevated atmospheric CO2, increased air temperatures, and water deficit. Tempranillo (T) and Cabernet Sauvignon (CS) plants, grafted onto R110 rootstocks, either inoculated (+M) or not (−M) with AMF, were grown in temperature-gradient greenhouses under two environmental conditions: (i) current conditions (ca. 400 ppm air CO2 concentration plus ambient air temperature, CATA) and (ii) climate change conditions predicted by the year 2100 (700 ppm of CO2 plus ambient air temperature +4 °C, CETE). From veraison to maturity, for plants of each variety, inoculation treatment and environmental conditions were also subjected to two levels of water availability: full irrigation (WW) or drought cycles (D). Therefore, the number of treatments applied to each grapevine variety was eight, resulting from the combination of two inoculation treatments (+M and −M), two environmental conditions (CATA and CETE), and two water availabilities (WW and D). In both grapevine varieties, early drought decreased leaf conductance and transpiration under both CATA and CETE conditions and more markedly in +M plants. Photosynthesis did not decrease very much, so the instantaneous water use efficiency (WUE) increased, especially in drought +M plants under CETE conditions. The increase in WUE coincided with a lower intercellular-to-atmospheric CO2 concentration ratio and reduced plant hydraulic conductance. In the long term, mycorrhization induced changes in the stomatal anatomy under water deficit and CETE conditions: density increased in T and decreased in CS, with smaller stomata in the latter. Although some responses were genotype-dependent, the interaction of the rootstock with AMF appeared to be a key factor in the acclimation of the grapevine to water deficit under both current and future CO2 and temperature conditions. Full article
(This article belongs to the Topic Effects of Climate Change on Viticulture (Grape))
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<p>Evolution of the substrate water content from fruit veraison to maturity. Dashed line, percentage of water in droughted pots; solid line, well-watered control pots (100%).</p>
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<p>(<b>A</b>) Photosynthesis, (<b>B</b>) leaf conductance, (<b>C</b>) transpiration, and (<b>D</b>) intercellular CO<sub>2</sub> concentration on days 7 (white bars) and 14 (black bars) after the onset of drought in Tempranillo (1) and Cabernet Sauvignon (2). Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each gas exchange parameter and grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) on days 7 and 14, respectively, among the different combinations of treatments (non-mycorrhizal, −M; mycorrhizal, +M; well-watered, WW; drought, D; current CO<sub>2</sub> and temperature, CATA; and predicted CETE). Asterisks indicate significant differences (*, <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001) between days 7 and 14. For each variety (T or CS), environmental condition (CATA or CETE), and mycorrhizal inoculation (−M or +M) arrows highlight significant differences between WW and D treatments.</p>
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<p>Effect of water deficit on the instantaneous water use efficiency (<span class="html-italic">WUE</span>) on days 7 (white bars) and 14 (black bars) after the onset of drought in Tempranillo and Cabernet Sauvignon, either inoculated (+M) or not (−M) with AMF and cultivated under current (CATA) or predicted (CETE) environmental conditions. Results are expressed as percentages of the respective WW controls (100%, dashed line). Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) on days 7 or 14, respectively. Asterisks indicate significant differences (*, <span class="html-italic">p</span> ≤ 0.05) between days 7 and 14.</p>
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<p>Effect of water deficit on the ratio between intercellular (Ci) and atmospheric (Ca) CO<sub>2</sub> on days 7 (white bars) and 14 (black bars) after the onset of drought in Tempranillo and Cabernet Sauvignon, either inoculated (+M) or not (−M) with AMF and cultivated under current (CATA) or predicted (CETE) environmental conditions. Results are expressed as percentages of the respective WW controls (100%, dashed line). Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) on days 7 or 14, respectively. Asterisks indicate significant differences (*, <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01) between days 7 and 14.</p>
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<p>Predawn leaf water potential (Ψ<sub>pd</sub>) on days 7 (white bars) and 14 (grey bars) after the onset of drought and at fruit harvest (black bars) in Tempranillo and Cabernet Sauvignon, either inoculated (+M) or not (−M) with AMF, well-watered (WW) or subjected to drought (D), and cultivated under current (CATA) or predicted (CETE) environmental conditions. Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety and day, different letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Effect of water deficit on plant hydraulic conductance (Kh) on days 7 (white bars) and 14 (black bars) after the onset of drought in Tempranillo and Cabernet Sauvignon, either inoculated (+M) or not (−M) with AMF and cultivated under current (CATA) or predicted (CETE) environmental conditions. Results are expressed as percentages of the respective WW controls (100%, dashed line). Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) on days 7 or 14, respectively. Asterisks indicate significant differences**, <span class="html-italic">p</span> ≤ 0.01) between days 7 and 14.</p>
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<p>Effect of water deficit on leaf water content (WC) on days 7 (white bars) and 14 (black bars) after the onset of drought in Tempranillo and Cabernet Sauvignon either inoculated (+M) or not (−M) with AMF and cultivated under either current (CATA) or predicted (CETE) environmental conditions. Results are expressed as percentages of the respective WW controls (100%, dashed line). Bars represent means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) on days 7 or 14, respectively. Asterisks indicate significant differences (**, <span class="html-italic">p</span> ≤ 0.01;) between days 7 and 14.</p>
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<p>Stomatal density in leaves of Tempranillo and Cabernet Sauvignon, either inoculated (+M) or not (−M) with AMF, well-watered (WW) or subjected to drought cycles (D) and cultivated under current (CATA, white bars) or predicted (CETE, black bars) CO<sub>2</sub> concentrations and air temperatures. Data were collected at the fruit harvest. Values are means (<span class="html-italic">n</span> = 4) ± SD. For each grapevine variety, different lowercase and capital letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) under CATA or CETE conditions, respectively. Asterisks indicate significant differences (*, <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001) between CATA and CETE.</p>
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19 pages, 6339 KiB  
Article
Echeveria Leaf Morpho-Anatomical Analysis and Its Implications for Environmental Stress Conditions
by My Khanh Thi Ha Tran, Raisa Aone M. Cabahug-Braza and Yoon-Jung Hwang
Horticulturae 2024, 10(4), 308; https://doi.org/10.3390/horticulturae10040308 - 22 Mar 2024
Viewed by 1486
Abstract
Echeveria, classified in the Crassulaceae family, possesses unique adaptive strategies with xeromorphic features to withstand semi-arid environments. The diversity and ecological adaptation of succulent plants offer valuable insights into addressing climate change challenges. In particular, the epidermis, hypodermis, vascular bundles arrangement, and [...] Read more.
Echeveria, classified in the Crassulaceae family, possesses unique adaptive strategies with xeromorphic features to withstand semi-arid environments. The diversity and ecological adaptation of succulent plants offer valuable insights into addressing climate change challenges. In particular, the epidermis, hypodermis, vascular bundles arrangement, and stomata characteristics are commonly used to investigate light, humidity, temperature, and water availability adaptations. While leaf anatomical analysis is a common approach, limited studies have been conducted on Echeveria, especially among cultivars. To understand how succulents cope with environmental stress, leaf morpho-anatomical features were analyzed using the free-hand sectioning method with methanol fixation of fifteen Echeveria cultivars. The finding revealed a robust correlation between epidermis and hypodermis size (r = 0.362–0.729), and a positive association between leaf thickness and the epidermis (r = 0.362–0.536), suggesting implications for water storage. Most cultivars displayed a 3D vascular arrangement, with minor vascular bundles surrounding the main vascular bundle at the center, along with small stomata size, and low stomata frequency in the adaxial surface. Moreover, these cultivars grown under controlled conditions maintain their xeromorphic characteristics with the presence of epicuticular wax and thick and fully expanded small leaves. Likewise, the features of cultivars ultimately suggest that these succulents are tolerant to high temperatures and limited water supply. This study provides a fundamental understanding of Echeveria plants’ leaf anatomy and the correlation of their leaf structures toward environmental stress. Likewise, the methods and results of this study will serve as a benchmark for other research in related species. Full article
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Figure 1

Figure 1
<p>Fifteen (15) <span class="html-italic">Echeveria</span> cultivars subjected to leaf anatomical evaluation: (<b>a</b>) <span class="html-italic">E</span>. ‘Benbadis’; (<b>b</b>) <span class="html-italic">E</span>. ‘Brave’; (<b>c</b>) <span class="html-italic">E. colorata</span> E. Walther; (<b>d</b>) <span class="html-italic">E</span>. ‘Cubic Frost’; (<b>e</b>) <span class="html-italic">E</span>. ‘Dark Ice’; (<b>f</b>) <span class="html-italic">E</span>. ‘Doterang’; (<b>g</b>) <span class="html-italic">E</span>. ‘Fire Pillar’; (<b>h</b>) <span class="html-italic">E</span>. ‘Glam Pink’; (<b>i</b>) <span class="html-italic">E</span>. ‘Loy’; (<b>j</b>) <span class="html-italic">E</span>. ‘Milk Rose’; (<b>k</b>) <span class="html-italic">E</span>. ‘Peerless’; (<b>l</b>) <span class="html-italic">E</span>. ‘Silhouette’; (<b>m</b>) <span class="html-italic">E</span>. ‘Snow Bunny’; (<b>n</b>) <span class="html-italic">E</span>. ‘Tippy’; and (<b>o</b>) <span class="html-italic">E</span>. ‘Viyant’.</p>
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<p>Leaf anatomical cross-sections of the epidermis (white arrow) and hypodermis layer (dark arrow) of <span class="html-italic">Echeveria</span> cultivars fixed in methanol observed under light microscope: (<b>a</b>) <span class="html-italic">E</span>. ‘Benbadis’; (<b>b</b>) <span class="html-italic">E</span>. ‘Brave’; (<b>c</b>) <span class="html-italic">E. colorata</span> E. Walther; (<b>d</b>) <span class="html-italic">E</span>. ‘Cubic Frost’; (<b>e</b>) <span class="html-italic">E</span>. ‘Dark Ice’; (<b>f</b>) <span class="html-italic">E</span>. ‘Doterang’; (<b>g</b>) <span class="html-italic">E</span>. ‘Fire Pillar’; (<b>h</b>) <span class="html-italic">E</span>. ‘Glam Pink’; (<b>i</b>) <span class="html-italic">E</span>. ‘Loy’; (<b>j</b>) <span class="html-italic">E</span>. ‘Milk Rose’; (<b>k</b>) <span class="html-italic">E</span>. ‘Peerless’; (<b>l</b>) <span class="html-italic">E</span>. ‘Silhouette’; (<b>m</b>) <span class="html-italic">E</span>. ‘Snow Bunny’; (<b>n</b>) <span class="html-italic">E</span>. ‘Tippy’; and (<b>o</b>) <span class="html-italic">E</span>. ‘Viyant’. (100× magnification, scale bar = 50 µm).</p>
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<p>Observation periclinal and anticlinal walls of epidermis cells of <span class="html-italic">Echeveria</span> cultivars were observed using a light microscope (LM): (<b>a</b>) <span class="html-italic">E.</span> ‘Benbadis’; (<b>b</b>) <span class="html-italic">E.</span> ‘Brave’; (<b>c</b>) <span class="html-italic">E. colorata</span> E. Walther; (<b>d</b>) <span class="html-italic">E.</span> ‘Cubic Frost’; (<b>e</b>) <span class="html-italic">E.</span> ‘Dark Ice’; (<b>f</b>) <span class="html-italic">E.</span> ‘Doterang’; (<b>g</b>) <span class="html-italic">E.</span> ‘Fire Pillar’; (<b>h</b>) <span class="html-italic">E.</span> ‘Glam Pink’; (<b>i</b>) <span class="html-italic">E.</span> ‘Loy’ (<b>j</b>) <span class="html-italic">E.</span> ‘Milk Rose’; (<b>k</b>) <span class="html-italic">E.</span> ‘Peerless’; (<b>l</b>) <span class="html-italic">E.</span> ‘Silhouette’; (<b>m</b>) <span class="html-italic">E.</span> ‘Snow Bunny’; (<b>n</b>). <span class="html-italic">E.</span> ‘Tippy’; and (<b>o</b>) <span class="html-italic">E.</span> ‘Viyant’ (100× magnification, scale bar = 50 µm).</p>
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<p>Stomatal evaluation of <span class="html-italic">E</span>. ‘Brave’ shows an anisocytic stomatal type comprising three subsidiary cells (800× magnification, scale bar = 10 µm).</p>
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<p>Transverse section of <span class="html-italic">Echeveria</span> cultivars observed under stereomicroscope showing a 2D vascular bundle with main vascular (Main VB) in the center, and a 3D vascular bundle arrangement with main vascular (Main VB) in the middle of the leaves and minor vascular (Minor VB) surrounding (<b>A</b>) <span class="html-italic">E</span>. ‘Benbadis’; (<b>B</b>) <span class="html-italic">E</span>. ‘Brave’; (<b>C</b>) <span class="html-italic">E. colorata</span> E. Walther; (<b>D</b>) <span class="html-italic">E</span>. ‘Cubic Frost’; (<b>E</b>) <span class="html-italic">E</span>. ‘Dark Ice’; (<b>F</b>) <span class="html-italic">E</span>. ‘Doterang’; (<b>G</b>) <span class="html-italic">E</span>. ‘Fire Pillar’; (<b>H</b>) <span class="html-italic">E</span>. ‘Glam Pink’; (<b>I</b>) <span class="html-italic">E</span>. ‘Loy’; (<b>J</b>) <span class="html-italic">E</span>. ‘Milk Rose’; (<b>K</b>) <span class="html-italic">E</span>. ‘Peerless’; (<b>L</b>) <span class="html-italic">E</span>. ‘Silhouette’; (<b>M</b>) <span class="html-italic">E</span>. ‘Snow Bunny’; (<b>N</b>) <span class="html-italic">E</span>. ‘Tippy’; and (<b>O</b>) <span class="html-italic">E</span>. ‘Viyant’ (0.67× magnification, scale bar = 100 µm).</p>
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<p>Diagram of the types of vascularization patterns: (<b>a</b>) 2D type, showing the linear formation of minor vascular bundles (small circles) and the main vascular bundle (big circle) in the center; and the (<b>b</b>) 3D type, exhibiting minor vascular bundles surrounding the edges and the main vascular bundle at the center, while the (<b>c</b>) main vascular bundle is determined to be a collateral type indicating that both the xylem and phloem are adjacent with each other.</p>
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<p>The transverse section from <span class="html-italic">E</span>. ‘Loy’ shows the collateral vascular bundle as the xylem (XY) is surrounded by the phloem (PH) and parenchyma cells (PC) (200× magnification, 20 μm).</p>
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