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22 pages, 7805 KiB  
Article
Effects of Underwater Lighting Time on the Growth of Vallisneria spinulosa Yan and Its Water Restoration Process
by Mengyi Wei, Jinshan Zhao, Xiaolin Zhou, Fengdan Li, Min Zhao, Xiangyong Zheng, Ye Tang, Chang Yang, Zhenmin Jin and Suqing Wu
Water 2024, 16(24), 3697; https://doi.org/10.3390/w16243697 (registering DOI) - 21 Dec 2024
Abstract
Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan ( [...] Read more.
Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan (V. spinulosa) and its water restoration process. V. spinulosa achieved a higher Fv/Fm (0.64), ETRmax (10.43), chlorophyll content (0.85 mg/g), and removal efficiency of total phosphorus (0.37 × 10−3 g m−3 d−1) and a lower algal abundance with a longer lighting time (18 h every day). However, a higher removal efficiency of NH4+–N and TN was obtained with a shorter lighting time (6–12 h every day). The lighting time showed a significance influence on the microbial community of the V. spinulosa growth system, and the influence was significantly different in different regions. Temperature and electrical conductivity were the main environmental impact factors for the microbial community under different lighting times. The abundances of Proteobacteria, Bacteroidota, and Verrucomicrobia exhibited a great positive correlation with each other and a strong positive correlation with the two factors. In addition, the lighting time had a strongly significant correlation with the physical and chemical characteristics of the water environment (p < 0.001) and a significant correlation with the growth characteristics of V. spinulosa (p < 0.05). Full article
(This article belongs to the Special Issue Ecological Wastewater Treatment and Resource Utilization)
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Figure 1

Figure 1
<p>Mean value of water properties in different treatment groups: (<b>a</b>) EC, (<b>b</b>) T, (<b>c</b>) pH, (<b>d</b>) DO. (V: <span class="html-italic">V. spinulosa</span> without auxiliary light source; LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio; MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio; HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio).</p>
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<p>The difference in removal load of (<b>a</b>) TN, (<b>b</b>) TP, (<b>c</b>) NH<sub>4</sub><sup>+</sup>–N, (<b>d</b>) PO<sub>4</sub><sup>3−</sup>–P, and (<b>e</b>) NO<sub>3</sub><sup>−</sup>–N in each experimental group under different light duration ratios. (V: <span class="html-italic">V. spinulosa</span> without auxiliary light source; LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio; MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio; HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio).</p>
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<p>The changes in (<b>a</b>) Fv/Fm and (<b>b</b>) ETRmax in each experimental group under different light duration ratios. (V: <span class="html-italic">V. spinulosa</span> without auxiliary light source; LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio; MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio; HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio).</p>
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<p>The changes in (<b>a</b>) Chl a + b content and (<b>b</b>) carotenoid content in each experimental group under different light duration ratios (V: <span class="html-italic">V. spinulosa</span> without auxiliary light source; LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio; MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio; HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio).</p>
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<p>The changes in (<b>a</b>) plant height, root length, and (<b>b</b>) biomass in each experimental group under different light duration ratios. (V: <span class="html-italic">V. spinulosa</span> without auxiliary light source; LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio; MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio; HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio).</p>
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<p>CLSM diagram of leaf–biofilm complex in different light duration ratios. (<b>a</b>) LV: <span class="html-italic">V. spinulosa</span> + low light duration ratio, (<b>b</b>) MV: <span class="html-italic">V. spinulosa</span> + medium light duration ratio, and (<b>c</b>) HV: <span class="html-italic">V. spinulosa</span> + high light duration ratio. Red is EPS polysaccharide stained with Texas red, green is protein stained with FITC, and bright blue is DNA stained with DAPI.</p>
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<p>Venn diagram of gate distribution in different samples. (VW: V–Water, LVW: LV–Water, MVW: MV–Water, HVW: HV–Water, LVL: LV–Leaf surface, MVL: MV–Leaf surface, HVL: HV–Leaf surface, VS: V–Sediment, LVS: LV–Sediment, MVS: MV–Sediment, HVS: HV–Sediment).</p>
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<p>Microbial community analysis: (<b>a</b>) the percentage of community abundance at the phylum level; (<b>b</b>) heatmap of bacterial community at the genus level.</p>
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<p>Microbial PLS−DA analysis (gate level).</p>
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<p>(<b>a</b>) LEfSe analysis of microbial abundance in LV, MV, and HV and (<b>b</b>) microbial markers (LDA threshold &gt; 2).</p>
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<p>RDA analysis of microbial community structure and environmental factors.</p>
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<p>Partial least squares path model (PLS–PM) of PSII between water characteristics, water nutrients, <span class="html-italic">V. spinulosa</span> characteristics, and microorganisms. The blue and red lines represent positive and negative paths, respectively, and the solid and dotted lines represent significant and non–significant correlations, respectively. The significance level is represented by an asterisk: *** <span class="html-italic">p</span> ≤ 0.001, ** 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, * 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. The latent variable (red square) is represented by a measurement variable (yellow square). The values are their respective weights.</p>
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14 pages, 1630 KiB  
Article
Insights into Orris (Iris pallida Lam.) In Vivo Acclimatization and Response to Salt Stress via Exogenous Melatonin Application
by Annalisa Meucci, Cristina Ghelardi, Rita Maggini, Fernando Malorgio, Beatrice Pezzarossa, Irene Rosellini and Anna Mensuali
Agriculture 2024, 14(12), 2353; https://doi.org/10.3390/agriculture14122353 (registering DOI) - 21 Dec 2024
Abstract
The loss of agricultural land is one of the main problems facing the global agricultural sector, and it is related to multiple phenomena; one of the main causes is soil salinization, induced both by natural processes and human activities. Among the strategies adopted [...] Read more.
The loss of agricultural land is one of the main problems facing the global agricultural sector, and it is related to multiple phenomena; one of the main causes is soil salinization, induced both by natural processes and human activities. Among the strategies adopted to deal with soil salinization and its mitigation, the cultivation of species able to survive in saline soils seems to be an effective way of making salt-compromised lands usable. Iris pallida is a rustic plant and a species of high economic value that is mostly cultivated for perfume production. Consequently, the application of I. pallida to cover soils not suitable for crops traditionally cultivated for human and livestock nutrition could be considered; therefore, a preliminary test on the capacity of I. pallida to tolerate salinity during the acclimatization phase of micropropagated plants was conducted. Plantlets were treated with exogenous melatonin during the in vitro phase by adding it to the culture medium; therefore, during the acclimatization phase, crescent salt doses (150, 300, and 400 mM) were added to the soil every 14 days, administering melatonin to plants by a spray solution 24 h before each salt addition. At the end of the experiment, biometric measurements, chlorophylls, carotenoids, and macro-element contents were measured, and the relative water content (RWC) was determined in each salt addition. The results showed that orris plants can survive soil salt concentrations of up to 400 mM, and that the 50 µM melatonin spray treatment can protect orris rhizomes from salt side effects. Full article
(This article belongs to the Section Crop Production)
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<p>Root development (cm) monitored during the different steps of the treatment: plants transferring to Magenta<sup>®</sup> vessels with ventilated caps (T0), transferring to perlite (T1), to peat and perlite (T2), and their length at the end of the acclimatization phase (TF). Data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05) and ns indicates no significance among the treatments.</p>
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<p>Leaf development (cm) monitored during the different steps of the treatment: plants transferred to containers with ventilated caps (T0), transferred to perlite (T1), and transferred to peat and perlite (T2), and their length at the end of the acclimatization phase (TF). The data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05) and ns indicates no significance among the treatments.</p>
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<p>Number of roots (<b>a</b>) and new leaves (<b>b</b>) of <span class="html-italic">I. pallida</span> plants treated with 400 mM of salt (Ctr + salt) and with both melatonin and salt and (50–100 µM + salt) compared to control plants (Ctr). Data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), and the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Dry weight (g plant<sub>dw</sub> <sup>−1</sup>) of rhizomes (<b>a</b>) and leaves (<b>b</b>) of <span class="html-italic">I. pallida</span> plants treated with 400 mM of salt (Ctr + salt) and with both melatonin and salt (50–100 µM + salt) compared to control plants (Ctr). The data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), and the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Relative water content (RWC) of leaves of <span class="html-italic">I. pallida</span> plants treated with 400 mM of salt (Ctr + salt) and with both melatonin and salt (50–100 µM + salt) compared to control plants (Ctr). The data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), and the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Total chlorophyll (ChlTOT) and carotenoid content (µg g<sub>fw</sub><sup>−1</sup>) in leaves of <span class="html-italic">I. pallida</span> plants treated with 400 mM of salt (Ctr + salt) and with both melatonin and salt (50–100 µM + salt) compared to control plants (Ctr). The data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), and the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Macro-elements content (Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>, K<sup>+</sup> g kg<sub>dw</sub><sup>−1</sup>) in roots (<b>a</b>), rhizomes (<b>b</b>), and leaves (<b>c</b>) of <span class="html-italic">I. pallida</span> plants treated only with 400 mM of salt and with both melatonin and salt (50–100 µM + salt) compared to control. The data, reported as mean values ± S.E., were subjected to analysis of variance (ANOVA), the different letters indicate significant differences among means (Tukey post-test, <span class="html-italic">p</span> ≤ 0.05) and ns indicates no significance among the treatments.</p>
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18 pages, 2635 KiB  
Article
Investigation of Effects of Cushioning Packaging on the Physiological and Quality Changes in Chinese Olive Fruits During Cold Chain Transportation
by Han Lin, Fanghao Fu, Jinghai Li, Jiahui Liu, Kaiyang Du, Bingxia Zhu, Zhixiong Guo, Tengfei Pan and Wenqin She
Foods 2024, 13(24), 4133; https://doi.org/10.3390/foods13244133 (registering DOI) - 20 Dec 2024
Abstract
To gain a deeper understanding of the mechanisms by which cushioning packaging preserves the quality of Chinese olive fruits during cold chain transportation and extends their shelf life, this study simulated cold chain conditions and investigated the effects of cushioning packaging on the [...] Read more.
To gain a deeper understanding of the mechanisms by which cushioning packaging preserves the quality of Chinese olive fruits during cold chain transportation and extends their shelf life, this study simulated cold chain conditions and investigated the effects of cushioning packaging on the physiology, antioxidant capacity, and secondary metabolites of fruits during a 20-day shelf life. The results indicated that the decay rate in cushioning-packaging-treated fruit was 75% lower than that in the unbuffered packaging fruit at day 20 of shelf life. Simultaneously, cushioning packaging treatment mitigated the damage severity of the cell membrane structure and kept the cell membrane permeability at a low level, which was 15.34% lower than that in the unbuffered packaging fruit at day 20 of shelf life. Additionally, cushioning packaging effectively restrained the increases in malondialdehyde (MDA) content and alleviated the decline in chlorophyll and total flavonoid contents. It kept a balance among reactive oxygen species (ROS), antioxidant levels, and antioxidant enzyme activities, thereby reducing mechanical-damage-induced decay rates in Chinese olive fruits during the shelf life. Furthermore, metabolome analysis of Chinese olives during the shelf life was performed comparing those without buffered packaging to those with buffered packaging. The metabolome analysis found that the flavonoid biosynthetic pathway exhibited a higher accumulation of chrysin, neohesperidin, naringenin chalcone, sakuranetin, quercetin, catechin, and naringenin metabolites in cushion-packaging treatment compared to those without cushioning treatment. Furthermore, within the phenylalanine metabolic pathway, the accumulation of phenylalanine, p-coumaraldehyde, p-coumaric acid, coniferin and caffeoyl quinic acid metabolites was significantly higher in buffered-packaging groups compared to those without buffering. Together, these findings suggest that cushioning packaging can effectively sustain the integrity of cell membranes and enhance the shelf-life quality of Chinese olive fruits by regulating the balance of ROS and mitigating oxidative stress during cold chain transportation. Full article
24 pages, 12643 KiB  
Article
Regulatory Mechanism of Exogenous ABA on Gibberellin Signaling and Antioxidant Responses in Rhododendron chrysanthum Pall. Under UV-B Stress
by Wang Yu, Kun Cao, Hongwei Xu and Xiaofu Zhou
Int. J. Mol. Sci. 2024, 25(24), 13651; https://doi.org/10.3390/ijms252413651 (registering DOI) - 20 Dec 2024
Abstract
In the present work, we examined the effects of exogenous abscisic acid (ABA) under ultraviolet B (UV-B) exposure on gibberellin (GA) production, signaling, and antioxidant-related genes in Rhododendron chrysanthum Pall (R. chrysanthum). Using transcriptomics, acetylated proteomics, and widely targeted metabolomics, the [...] Read more.
In the present work, we examined the effects of exogenous abscisic acid (ABA) under ultraviolet B (UV-B) exposure on gibberellin (GA) production, signaling, and antioxidant-related genes in Rhododendron chrysanthum Pall (R. chrysanthum). Using transcriptomics, acetylated proteomics, and widely targeted metabolomics, the effects of UV-B stress on R. chrysanthum and the regulatory effects of exogenous ABA on it were revealed from multiple perspectives. The findings revealed that R. chrysanthum’s antioxidant enzyme genes were differentially expressed by UV-B radiation and were substantially enriched in the glutathione metabolic pathway. Exogenous ABA supplementation boosted plant resistance to UV-B damage and further enhanced the expression of antioxidant enzyme genes. Furthermore, under UV-B stress, glutathione reductase, glutathione peroxidase, and L-ascorbate peroxidase were found to be the primary antioxidant enzymes controlled by exogenous ABA. In addition, gibberellin content was altered due to UV-B and exogenous ABA treatments, with greater effects on GA3 and GA53. The acetylation proteomics study’s outcomes disclosed that the three main oxidative enzymes’ acetylation modifications were dramatically changed during UV-B exposure, which may have an impact on the antioxidant enzymes’ functions and activities. The protective impact of exogenous ABA and gibberellin on R. chrysanthum’s photosynthetic system was further established by measuring the parameters of chlorophyll fluorescence. This research offers a theoretical foundation for the development of breeding highly resistant plant varieties as well as fresh insights into how hormone levels and antioxidant systems are regulated by plants in response to UV-B damage. Full article
(This article belongs to the Special Issue Transcriptional Regulation in Plant Development: 2nd Edition)
25 pages, 1091 KiB  
Article
Effect of Herbicide-Resistant Oil-Degrading Bacteria on Plants in Soil Contaminated with Oil and Herbicides
by Tatyana Korshunova, Elena Kuzina, Svetlana Mukhamatdyarova, Milyausha Iskuzhina, Liliya Kulbaeva and Svetlana Petrova
Plants 2024, 13(24), 3560; https://doi.org/10.3390/plants13243560 - 20 Dec 2024
Abstract
Biological remediation of agricultural soils contaminated with oil is complicated by the presence of residual amounts of chemical plant protection products, in particular, herbicides, which, like oil, negatively affect the soil microbiome and plants. In this work, we studied five strains of bacteria [...] Read more.
Biological remediation of agricultural soils contaminated with oil is complicated by the presence of residual amounts of chemical plant protection products, in particular, herbicides, which, like oil, negatively affect the soil microbiome and plants. In this work, we studied five strains of bacteria of the genera Pseudomonas and Acinetobacter, which exhibited a high degree of oil biodegradation (72–96%). All strains showed resistance to herbicides based on 2,4-D, imazethapyr and tribenuron-methyl, the ability to fix nitrogen, phosphate mobilization, and production of indole-3-acetic acid. The presence of pollutants affected the growth-stimulating properties of bacteria in different ways. The most promising strain P. citronellolis N2 was used alone and together with oat and lupine plants for soil remediation of oil, including herbicide-treated oil-contaminated soil. Combined contamination was more toxic to plants and soil microorganisms. Bacterization stimulated the formation of chlorophyll and suppressed the synthesis of abscisic acid and malonic dialdehyde in plant tissues. The combined use of bacteria and oat plants most effectively reduced the content of hydrocarbons in the soil (including in the presence of herbicides). The results obtained can be used to develop new methods for bioremediation of soils with polychemical pollution. Full article
(This article belongs to the Special Issue Role of Microbial Plant Biostimulants in Abiotic Stress Mitigation)
14 pages, 2107 KiB  
Article
Physiological Responses of Cucumber Seedlings to Combined High-Temperature and High-Humidity Stress at Different Leaf Stages
by Xi’ao Wang, Yupeng Pan, Hanqiang Liu, Huanwen Meng and Zhihui Cheng
Horticulturae 2024, 10(12), 1369; https://doi.org/10.3390/horticulturae10121369 - 20 Dec 2024
Abstract
The growth and development of plants are closely tied to growth stages, such as germination, flower bud differentiation, photosynthesis, water and fertilizer use efficiency, stress resistance, etc. Previous studies on the stress resistance of plants with different leaf stages have primarily focused on [...] Read more.
The growth and development of plants are closely tied to growth stages, such as germination, flower bud differentiation, photosynthesis, water and fertilizer use efficiency, stress resistance, etc. Previous studies on the stress resistance of plants with different leaf stages have primarily focused on single-factor environmental conditions. However, there has been a lack of systematic research on the physiology of plant seedlings under combined high-temperature and high-humidity (HH) stress, and the relationship between cucumber growth stages and HH tolerance remains unclear. In this study, we analyzed the phenotype, photosynthetic characteristics, reactive oxygen species content, and antioxidant enzyme activity of cucumber seedlings at 1-, 2-, 3-, and 4-leaf stages under control (25 °C + 80%RH, CK) and HH (42 °C + 95%RH) stress, aiming to clarify the relationship between growth stage and cucumber HH tolerance. The results indicated that the HH tolerance of cucumber seedlings increases with leaf stage. Seedlings at 1-leaf and 2-leaf stages were most sensitive to HH, whereas 4-leaf seedlings showed the greatest tolerance. Under HH stress, the biomass, chlorophyll content, net photosynthetic rate, and photosynthetic electron transfer rate were significantly reduced compared to CK. Simultaneously, there was an increase in reactive oxygen species content and antioxidant enzyme activity. The relative values for dry weight, total chlorophyll content, net photosynthetic rate, Fv/Fm, qP, ETR, and Y (II) in 1-leaf and 2-leaf seedlings were significantly lower, while ROS accumulation and changes in antioxidant enzyme activity were significantly higher compared to 4-leaf seedlings. This lays a foundation for future studies on the growth and physiological response of cucumber plants at different growth stages under varying temperature and humidity combined stresses. Full article
(This article belongs to the Special Issue Biotic and Abiotic Stress Responses of Horticultural Plants)
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Figure 1
<p>Phenotypes of different leaf-stage cucumber seedlings at 8 h after HH stress.</p>
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<p>Relative biomass of different leaf-stage cucumber seedlings 8 h after treatments. (<b>A</b>) Leaf fresh weight; (<b>B</b>) top part fresh weight; (<b>C</b>) root fresh weight; (<b>D</b>) whole-plant fresh weight; (<b>E</b>) leaf dry weight; (<b>F</b>) top part dry weight; (<b>G</b>) root dry weight; (<b>H</b>) whole-plant dry weight. Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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<p>Relative values of photosynthetic pigment content of different leaf-stage cucumber seedlings 6 h after HH stress: (<b>A</b>) chlorophyll a; (<b>B</b>) chlorophyll b; (<b>C</b>) carotenoids; (<b>D</b>) total chlorophyll; (<b>E</b>) total pigment. Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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<p>Relative values of photosynthesis parameters of different leaf-stage cucumber seedlings 6 h after HH stress. (<b>A</b>) Net photosynthesis rate; (<b>B</b>) stomatal conductance; (<b>C</b>) intercellular carbon dioxide concentration; (<b>D</b>) transpiration rate. Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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<p>Relative values of chlorophyll fluorescence parameters in different leaf-stage cucumber seedlings 6 h after HH stress. (<b>A</b>) Fv/Fm; (<b>B</b>) qP; (<b>C</b>) NPQ; (<b>D</b>) ETR; (<b>E</b>) Y(II); (<b>F</b>) Y(NPQ); (<b>G</b>) Y(NO). Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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<p>Relative value of reactive oxygen species content in different leaf-stage cucumber seedlings 6 h after HH stress. (<b>A</b>) O<sub>2</sub><sup>●−</sup> content; (<b>B</b>) H<sub>2</sub>O<sub>2</sub> content. Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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<p>Relative values of antioxidant enzyme activities in different leaf-stage cucumber seedlings 6 h after HH stress. (<b>A</b>) SOD activity. (<b>B</b>) POD activity. (<b>C</b>) CAT activity. Values are means ± SD from three biological replicates, ANOVA and Tukey HSD test, <span class="html-italic">p</span> &lt; 0.05. Different letters on the bars represent significant differences while same letters represent non-significant difference among treatment.</p>
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18 pages, 6673 KiB  
Article
SOS3-3 Enhances the Salt Tolerance of Tomato Plants by Regulating ROS Balance
by Niannian Zhou, Jiahui Huang, Fangling Jiang, Enmei Hu, Xiaoming Song, Rong Zhou and Zhen Wu
Agronomy 2024, 14(12), 3044; https://doi.org/10.3390/agronomy14123044 - 20 Dec 2024
Abstract
Salt stress affects the growth, metabolism, yield, and quality of crops. To adapt to high-salt environments, plants form various regulatory mechanisms. Salt over sensitive (SOS) is the key gene of SOS signal transduction pathway. As a member of the SOS3 subfamily, [...] Read more.
Salt stress affects the growth, metabolism, yield, and quality of crops. To adapt to high-salt environments, plants form various regulatory mechanisms. Salt over sensitive (SOS) is the key gene of SOS signal transduction pathway. As a member of the SOS3 subfamily, the function of SOS3-3 under salt stress has not been reported. To verify the function of SOS3-3 and the morphological and physiological parameters, the expression of genes related to stress were compared between the SOS3-3 overexpressed (OESOS3-3) and silenced tomato (VSOS3-3) at control and 10 days’ NaCl treatment. The results showed that, compared with the control (Ve), the plants of VSOS3-3 were shorter under salt stress, with curled leaves and abscission. The fresh and dry weights, Fv/Fm, total chlorophyll content, antioxidant enzyme activities, and proline content of VSOS3-3 significantly decreased, while the relative conductivity, hydrogen peroxide (H2O2), and Malondialdehyde (MDA) content of VSOS3-3 plants significantly increased compared to that of WT, respectively. Compared to the wild-type (WT), OESOS3-3 plants were less damaged by salt stress, with significantly higher plant height, fresh and dry weights, Fv/Fm, total chlorophyll content, antioxidant enzyme activity, and proline content. However, the relative conductance, H2O2, and MDA content were significantly lower in OESOS3-3 than WT. The expression levels of SOS1, SOS2, LKT1 (ion transport-related gene), APX1 (ROS signaling pathway-related gene), P5CS (osmoregulation-related gene), and ABF4 (ABA signaling pathway-related gene) were significantly lower in VSOS3-3 than Ve, but significantly higher in OESOS3-3 than in WT. These results suggested that SOS3-3 regulate salt tolerance by influencing physiological and biochemical changes and the expression of genes related to stress response. This study revealed the mechanism of SOS family participating in regulating tomato salt tolerance, providing a theoretical basis for improving tomato salt tolerance. Full article
(This article belongs to the Special Issue Crop and Vegetable Physiology under Environmental Stresses)
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Figure 1
<p>Subcellular localization of the SOS3-3 protein of tomato. GFP: green fluorescence; D53-mCherry: nucleus marker (from left, the green, fluorescent channel; mCherry channel; bright channel; compound channel. From top, PR101 empty; connecting the PR101 of SOS3-3).</p>
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<p>Identification of V<span class="html-italic">SOS3-3</span> and OE<span class="html-italic">SOS3-3</span> plants. (<b>A</b>) 1. PCR amplification results of <span class="html-italic">SOS3-3</span> silent fragment of tomato; (<b>B</b>) phenotype of TRV2-<span class="html-italic">PDS</span> report plant; (<b>C</b>) the silencing efficiency of <span class="html-italic">SOS3-3</span> gene, the expression level of <span class="html-italic">SOS3-3</span> in VSOS3-3 plants; (<b>D</b>) 1. PCR amplification results of <span class="html-italic">SOS3-3</span> overexpression fragment; (<b>E</b>) genomic PCR analysis of OE<span class="html-italic">SOS3-3</span> transgenic lines; (<b>F</b>) expression levels of <span class="html-italic">SOS3-3</span> in T<sub>1</sub> generations for OE<span class="html-italic">SOS3-3</span> transgenic lines. M. DL2000 Marker. Data was the mean of three biological repeats ± standard error (SE). Different letters represented significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Growth changes of V<span class="html-italic">SOS3-3</span> and OE<span class="html-italic">SOS3-3</span> under salt stress. (<b>A</b>) Phenotypes of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>B</b>) phenotypes of WT and OE<span class="html-italic">SOS3-3</span> under salt stress; (<b>C</b>) changes in plant height of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>D</b>) changes in plant height of WT and OE<span class="html-italic">SOS3-3</span> under salt stress. Asterisks indicate significant differences between V<span class="html-italic">SOS3-3</span> and Ve as well as WT and <span class="html-italic">OESOS3-3</span>. *, <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, Student’s <span class="html-italic">t</span> test.</p>
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<p>Effects of <span class="html-italic">SOS3-3</span> silencing and overexpression on <span class="html-italic">F<sub>v</sub></span>/<span class="html-italic">F<sub>m</sub></span> and the total chlorophyll content of tomato under salt stress. (<b>A</b>) <span class="html-italic">F<sub>v</sub></span>/<span class="html-italic">F<sub>m</sub></span> of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>B</b>) content of total chlorophyll of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>C</b>) <span class="html-italic">F<sub>v</sub></span>/<span class="html-italic">F<sub>m</sub></span> of WT and OE<span class="html-italic">SOS3-3</span> under salt stress; (<b>D</b>) content of total chlorophyll of WT and OE<span class="html-italic">SOS3-3</span> under salt stress. Asterisks indicate significant differences between V<span class="html-italic">SOS3-3</span> and Ve as well as WT and <span class="html-italic">OESOS3-3</span>. *, <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, Student’s <span class="html-italic">t</span> test.</p>
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<p>Effects of <span class="html-italic">SOS3-3</span> silencing and overexpression on REC, MDA, and Pro content for tomato under salt stress. (<b>A</b>) Relative conductivity of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>B</b>) MDA content of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>C</b>) proline content of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>D</b>) relative conductivity of WT and OE<span class="html-italic">SOS3-3</span> under salt stress; (<b>E</b>) MDA content of WT and OE<span class="html-italic">SOS3-3</span> under salt stress; (<b>F</b>) proline content of WT and OE<span class="html-italic">SOS3-3</span> under salt stress. Asterisks indicate significant differences between V<span class="html-italic">SOS3-3</span> and Ve as well as WT and <span class="html-italic">OESOS3-3</span>. *, <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, Student’s <span class="html-italic">t</span> test.</p>
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<p>Effects of <span class="html-italic">SOS3-3</span> silencing and overexpression on the expression level of <span class="html-italic">P5CS</span>, <span class="html-italic">APX1</span>, and ion transporters (<span class="html-italic">SOS1</span>, <span class="html-italic">SOS2</span>, <span class="html-italic">LKT1</span> and <span class="html-italic">ABF4</span>) in tomato under salt stress. (<b>A</b>) Relative expression of <span class="html-italic">P5CS APX1</span> and <span class="html-italic">SOS1</span>, <span class="html-italic">SOS2</span>, <span class="html-italic">LKT1</span>, and <span class="html-italic">ABF4</span> of Ve and V<span class="html-italic">SOS3-3</span> under salt stress, respectively; (<b>B</b>) relative expression of <span class="html-italic">P5CS APX1</span> and <span class="html-italic">SOS1</span>, <span class="html-italic">SOS2</span>, <span class="html-italic">LKT1</span> and <span class="html-italic">ABF4</span> of WT and OE<span class="html-italic">SOS3-3</span> under salt stress, respectively. Different letters represented significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of V<span class="html-italic">SOS3-3</span> and OE<span class="html-italic">SOS3-3</span> on H<sub>2</sub>O<sub>2</sub> content and antioxidant enzyme activity for tomato under salt stress. (<b>A</b>) H<sub>2</sub>O<sub>2</sub> content and antioxidant enzyme activity of Ve and V<span class="html-italic">SOS3-3</span> under salt stress; (<b>B</b>) H<sub>2</sub>O<sub>2</sub> content and antioxidant enzyme activity of WT and OE<span class="html-italic">SOS3-3</span> under salt stress. Asterisks indicate significant differences between V<span class="html-italic">SOS3-3</span> and Ve as well as WT and <span class="html-italic">OESOS3-3</span>. *, <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, Student’s <span class="html-italic">t</span> test.</p>
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17 pages, 6242 KiB  
Article
Comparative Study on Growth Characteristics and Yield of Colored Rice Varieties
by Yiwen Song, Shaoxia Yang, Aaqil Khan, Hang Zhou, Zhiyuan Sun, Jiashuang Wu, Linchong Ding, Jian Xiong, Wanqi Mei, Naijie Feng and Dianfeng Zheng
Agronomy 2024, 14(12), 3038; https://doi.org/10.3390/agronomy14123038 - 19 Dec 2024
Abstract
In recent years, pigment rice has been the focus of much attention due to its high nutritional value and ornamental value. To gain a better understanding of pigmented rice, we studied the morphological, physiological, and yield characteristics of four varieties, i.e., light green [...] Read more.
In recent years, pigment rice has been the focus of much attention due to its high nutritional value and ornamental value. To gain a better understanding of pigmented rice, we studied the morphological, physiological, and yield characteristics of four varieties, i.e., light green (LG), deep purple (DP), black-purple (BP), and white rice (WR), as plant material. The field experiment was conducted using a randomized complete block design at Guangdong ocean university research farm during 2023 and 2024. The data of the pigmented rice varieties regarding their morphological, physiological, and antioxidant traits were compared with CK. Leaf area and dry matter accumulation were significantly higher in BP than in the other rice varieties, with BP being the best performer and WR being the worst. The internode length, leaf area, and dry matter accumulation of BP were markedly higher than the rest of the rice varieties. The chlorophyll content of BP was significantly higher. The antioxidant enzyme activities were significantly different among all the varieties. The antioxidant enzyme activities of BP were significantly higher than those of the other rice varieties. Seed yield varied significantly, with BP showing the highest yield. The morphophysiological characteristics of BP and DP suggest that these two varieties can alleviate the response to salinity stress, thereby increasing rice yield. Full article
(This article belongs to the Section Innovative Cropping Systems)
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<p>Hours of sunshine, rainfall, maximum and minimum temperatures, 2023.</p>
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<p>Pictures of rice growing in different varieties of fields (<b>A</b>–<b>D</b>); light green rice, LG (<b>A</b>); purple leaf rice, DP (<b>B</b>); black-purple leaf rice, BP (<b>C</b>); and white rice, WR (<b>D</b>).</p>
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<p>Internode length (<b>A</b>) and plant height (<b>B</b>) of different colored rice varieties at various growth stages. Tillering stage (T1), jointing stage (T2), heading stage (T3), and full heading stage (T4). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Leaf area of inverted second leaf (<b>A</b>) and inverted third leaf (<b>B</b>) of colored rice at different growth stages. Tillering stage (T1), jointing stage (T2), heading stage (T3), and full heading stage (T4). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Leaf fresh weight (<b>A</b>), leaf dry weight (<b>B</b>), stem fresh weight (<b>C</b>), stem dry weight (<b>D</b>), spike fresh weight (<b>E</b>), and spike dry weight (<b>F</b>) of different colored rice varieties in different growth stages. Tillering stage (T1), jointing stage (T2), heading stage (T3), and full heading stage (T4). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Changes in chlorophyll a (<b>A</b>), chlorophyll b (<b>B</b>), total chlorophyll content (<b>C</b>), and carotenoid content (<b>D</b>) in different growth stages of rice varieties with different colors. Tillering stage (T1), jointing stage (T2), heading stage (T3), and full heading stage (T4). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The net photosynthetic rate (Pn) (<b>A</b>), stomatal conductance (Gs) (<b>B</b>), intercellular carbon dioxide concentration (Ci) (<b>C</b>), and transpiration rate (Tr) (<b>D</b>). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Activity of SOD (<b>A</b>), APX (<b>B</b>), CAT (<b>C</b>), and POD (<b>D</b>) in different colored rice varieties. Tillering stage (T1), jointing stage (T2), heading stage (T3), and full heading stage (T4). LG (CK): light green rice, DP: purple leaf rice, BP: black-purple leaf rice, WR: white rice. Different lowercase letters indicate significant differences between treatments by LSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Antioxidant enzyme activity, photosynthetic pigment content, and yield correlation. CAT, CAT activity; APX, APX activity; POD, POD activity; MDA, MDA activity; total chlorophyll, total chlorophyll content; carotenoids, carotenoid content; net photosynthetic rate (Pn); stomatal conductance (Gs); intercellular carbon dioxide concentration (Ci); and transpiration rate (Tr); yield, seed yield. Red marks represent a significant correlation (<span class="html-italic">p</span> &lt; 0.05), while blue marks represent no correlation.</p>
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16 pages, 3374 KiB  
Article
Effect of a Steaming Treatment on the Alpha-Glucosidase Inhibitory Components in the Brown Alga Sargassum fusiforme
by Xinxin Liu, Yipeng Gu, Yihao Zhou, Ruiqi Zhang and Tomoyuki Koyama
Molecules 2024, 29(24), 6000; https://doi.org/10.3390/molecules29246000 - 19 Dec 2024
Abstract
The brown alga Sargassum fusiforme (SF) is historically consumed as a food material in Japan. A steaming process is often required for SF products on the market due to their moderate hardness and astringent taste. This investigation aimed to elucidate the effect of [...] Read more.
The brown alga Sargassum fusiforme (SF) is historically consumed as a food material in Japan. A steaming process is often required for SF products on the market due to their moderate hardness and astringent taste. This investigation aimed to elucidate the effect of steaming on the anti-diabetic activity of SF and its related chemical components. Acetone extracts of SF were prepared after it were steamed for 0, 1, 2, or 4 h (SF-0h, SF-1h, SF-3h, and SF-4h, respectively). Alpha-glucosidase inhibitory profiles of each SF extract were made based on activity-guided separation. The active fractions were collected and NMR was applied for a further chemical composition analysis. Our results suggested that total polyphenol levels decreased drastically after steaming, which resulted in a drop in α-glucosidase inhibitory activity. The fatty acid, pheophytin a, and pyropheophytin a contents were elevated significantly after steaming, which contributed to the majority of the activity of steamed SF (SF-1h). However, prolonging the steaming time did not significantly affect the activity of SF further since the content of free fatty acids in steamed SF (SF-2h and SF-4h) almost did not change with a longer time of steaming. Moreover, palmitic acid, 8-octadecenoic acid, and tetradecanoic acid were identified as the top three important fatty acids for the inhibition of α-glucosidase by steamed SF. Further molecular docking results revealed that these fatty acids could interact with residues of α-glucosidase via hydrogen bonds, salt bridges, and hydrophobic interactions. In conclusion, steaming altered the α-glucosidase inhibitory properties of SF by changing the contents of polyphenols, fatty acids, and chlorophyll derivatives. Full article
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<p>Effect of the extraction solvent on carbohydrate-digesting enzyme inhibition by SF-0h. (<b>A</b>) α-Glucosidase, each extract and acarbose were prepared at 10, 25, 50, 125, and 250 μg mL<sup>−1</sup> for the assay; (<b>B</b>) α-amylase, each extract and acarbose were prepared at 10, 25, 50, 125 and 250 μg mL<sup>−1</sup> for the assay. Values are presented as means (SDs), <span class="html-italic">n</span> = 3. <sup>abcd</sup> <span class="html-italic">p</span> &lt; 0.05, different letters indicate significant differences among different extracts at the same concentration.</p>
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<p>Thin layer chromograph pattern of the acetone extracts of SF (SF-0h, -1h, -2h, and -4h). An ODS plate was developed with methanol and ethyl acetic (85:15, <span class="html-italic">v</span>:<span class="html-italic">v</span>). The developed spots were detected with UV (254 or 365 nm) and with 10% sulfuric acid followed by heating at 220 °C.</p>
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<p>Free fatty acid analysis of the acetone extract of SF. (<b>A</b>) Free fatty acid composition; (<b>B</b>) relative contents of total, unsaturated, and saturated free fatty acids. The free fatty acid content was expressed as the fold of the internal standard pentanoic acid. The total fatty acid content of SF-0h was normalized to 1. Values are presented as means (SDs), <span class="html-italic">n</span> = 3. <sup>abc</sup> <span class="html-italic">p</span> &lt; 0.05, different letters indicate significant differences.</p>
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<p>Effect of steaming on alpha-glucosidase inhibition and the yield of SF. (<b>A</b>) IC<sub>50</sub> of the acetone extract of SF against α-glucosidase. Fresh SF was steamed for 0, 1, 2, or 4 h and extracted with acetone. (<b>B</b>) Yield of the acetone extract (mg) of SF (g). Values are presented as means (SDs), <span class="html-italic">n</span> = 3. <sup>abc</sup> <span class="html-italic">p &lt;</span> 0.05, different letters indicate significant differences.</p>
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<p>Effect of the steaming time on the α-glucosidase inhibitory profile of SF. (<b>A</b>) SF-0h; (<b>B</b>) SF-1h; (<b>C</b>) SF-2h; (<b>D</b>) SF-4h. SF was steamed for 0, 1, 2, or 4 h, and extracted with acetone; each acetone extract of SF was separated on the ODS column. The fractions were collected and applied to the α-glucosidase inhibition assay and developed by TLC on an ODS plate with methanol and ethyl acetic (<span class="html-italic">v</span>:<span class="html-italic">v</span> = 85:15). The spots were detected with 10% sulfuric acid and heated at 220 °C subsequently.</p>
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<p>Identification of the active components of Frac. 43. (<b>A</b>) TLC results for Frac. 43 and the subfractions. (<b>B</b>) α-Glucosidase inhibition by Frac. 43 and its subfractions. Acetone extracts of SF steamed for 0, 1, 2, or 4 h were subjected to the ODS column for separation, and Frac. 43 (appeared at 43 min) of SF-4h was further separated into 4 subfractions (Frac. 43-1, 43-2, 43-3, and 43-4); each fraction was dried and redissolved in an equal volume of 20% DMSO for the subsequent α-glucosidase inhibition assay. Values are presented as means (SDs), <span class="html-italic">n</span> = 3. <sup>abcd</sup> <span class="html-italic">p</span> &lt; 0.05, different letters indicate significant differences.</p>
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<p>Variable importance of free fatty acids by the random forest model. (<b>A</b>) Cumulative error rates of the random forest classification. (<b>B</b>) Top 5 significant features identified by random forest. The accuracy importance measure was computed for each tree and averaged over the forest (150 trees). Percentage increases in the mean squared error (MSE%) of variables were used to estimate the importance of predictors, and the higher the MSE% was, the more important the predictors were. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Conformational and interaction analyses of molecular docking for alpha-glucosidase and fatty acids. (<b>A</b>) Palmitic acid; (<b>B</b>) 8-octadecenoic acid; (<b>C</b>) tetradecanoic acid. The expansion of the highlighted regions shows a close-up view of the binding sites and binding residues. The blue solid line represents a hydrogen bond, the yellow dotted line represents a salt bridge, and the black dotted line represents a hydrophobic interaction.</p>
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21 pages, 12878 KiB  
Article
Exogenous 24-Epibrassinolide Improves Resistance to Leaf Spot Disease Through Antioxidant Regulation and Phenylpropanoid Metabolism in Oats
by Zheng Wang, Kuiju Niu, Guiqin Zhao, Yuehua Zhang, Jikuan Chai and Zeliang Ju
Agronomy 2024, 14(12), 3035; https://doi.org/10.3390/agronomy14123035 - 19 Dec 2024
Abstract
Leaf spot disease has become a significant limitation in oat production. 24-epibrassinolide (EBR), a highly active brassinosteroid, plays a significant role in enhancing plant immunity against various diseases by modulating physiological and molecular responses. However, the exact mechanisms by which exogenous EBR regulates [...] Read more.
Leaf spot disease has become a significant limitation in oat production. 24-epibrassinolide (EBR), a highly active brassinosteroid, plays a significant role in enhancing plant immunity against various diseases by modulating physiological and molecular responses. However, the exact mechanisms by which exogenous EBR regulates plant defense to leaf spot disease are still largely unknown. In this study, we applied various concentrations of EBR (0, 0.01, 0.1, 1, and 10 mg·L−1) to the leaves of oat plants that were inoculated with the Drechslera avenae pathogen. The application of 1 mg·L−1 EBR significantly decreased disease index and increased chlorophyll content under pathogen inoculation while also enhancing antioxidant enzyme (SOD, CAT, and APX) activity and reducing pathogen-induced O2•− production rate and MDA content. Moreover, the enzymes associated with phenylpropanoid metabolism, such as PAL, C4H, and 4CL, were significantly activated by exogenous EBR. Our transcriptomic analyses further revealed that the combination of exogenous EBR and pathogen inoculation upregulated genes involved in signal transduction (BR, ABA, and MAPK), antioxidant enzyme defense systems, and phenylpropanoid and lignin-specific pathways, such as BAS1, APX, GPX, PAL, C4H, 4CL, CCR1, and CAD. Together, these findings reveal that exogenous BR application can improve resistance to Drechslera avenae-induced leaf spot disease in oats by regulating antioxidant defense systems and phenylpropanoid metabolism, which may have the potential to control leaf spot disease in oat production. Full article
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<p>Effects of exogenous EBR on phenotype (<b>a</b>), disease index (<b>b</b>), and chlorophyll content (<b>c</b>) in oat leaves inoculated with a pathogenic fungus, <span class="html-italic">Drechslera avenae</span>. CK indicates the control plants; BR0 indicates the plants treated with pathogen inoculation alone; BR0.01, BR0.1, BR1, and BR10 indicate plants treated with both pathogen inoculation and foliar application of EBR at the concentrations of 0.01, 0.1, 1.0, 10.0 mg·L<sup>−1</sup>, respectively. Data presented are the mean ± SD (n = 3). Different letters indicate significant differences among treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effect of exogenous BR on antioxidant enzyme activity (<b>a</b>–<b>c</b>) and oxidative product content (<b>d</b>–<b>f</b>) in oat leaves inoculated with pathogenic fungus <span class="html-italic">Drechslera avenae</span>. CK indicates the control plants; BR0 indicates the plants treated with pathogen inoculation alone; BR0.01, BR0.1, BR1, and BR10 indicate plants treated with both pathogen inoculation and foliar application of EBR at the concentrations of 0.01, 0.1, 1.0, and 10.0 mg·L<sup>−1</sup>, respectively. Data presented are the mean ± SD (n = 3). Different letters indicate significant differences among treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effect of exogenous EBR on the activity of enzymes (<b>a</b>–<b>c</b>) and the content of related secondary metabolites (<b>d</b>–<b>f</b>) related to phenylpropane metabolism in oat leaves inoculated with a pathogenic fungus, <span class="html-italic">Drechslera avenae</span>. CK indicates the control plants; BR0 indicates the plants treated with pathogen inoculation alone; BR0.01, BR0.1, BR1, and BR10 indicate plants treated with both pathogen inoculation and foliar application of EBR at the concentrations of 0.01, 0.1, 1.0, and 10.0 mg·L<sup>−1</sup>, respectively. Data presented are the mean ± SD (n = 3). Different letters indicate significant differences among treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Principal component analysis (<b>a</b>) and number of DEGs (<b>b</b>) among different comparisons: A, the control group (CK); B, pathogen inoculation group; E, EBR application group; F, the combination of EBR application and pathogen inoculation group.</p>
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<p>GO and KEGG enrichment of DEGs induced by pathogen inoculation and in combination with exogenous EBR application. (<b>a</b>,<b>b</b>) GO enrichment of DEGs in the B-vs-A comparison and F-vs-B comparison, respectively. The 30 most enriched GO terms in the three categories are shown. (<b>c</b>,<b>d</b>) KEGG enrichment of DEGs in the B-vs-A comparison and F-vs-B comparison, respectively. The 20 most enriched KEGG terms are shown. A high <span class="html-italic">p</span>-value is represented by blue, and a low <span class="html-italic">p</span>-value is represented by red.</p>
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<p>DEGs involved in pathogen attack pathways based on Mapman analysis in the F-vs-B comparison.</p>
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<p>Redox-related DEGs among different comparisons. A, control group (CK); B, pathogen inoculation group; E, EBR application group; F, combination of EBR application and pathogen inoculation group.</p>
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<p>DEGs involved in BR signal transduction among the different comparisons. A, control group; B, pathogen inoculation group; E, EBR application group; F, combination of EBR application and pathogen inoculation group.</p>
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<p>Secondary metabolism-related DEGs among different group comparisons. A, control group; B, pathogen inoculation group; E, EBR application group; F, combination of EBR application and pathogen inoculation group.</p>
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<p>Cluster heatmap of DEGs related to phenylpropanoid and lignin pathways. A, control group; B, pathogen inoculation group; E, EBR application group; F, combination of EBR application and pathogen inoculation group.</p>
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<p>Expression levels and FPKM values of 20 randomly selected genes. The different lowercase letters represent significant differences among different treatments.</p>
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17 pages, 2473 KiB  
Article
The Combined Effects of Salt and Nitrogen Addition on the Chlorophyll Fluorescence, Antioxidant System, and Leaf Stoichiometry of Torreya grandis Sexes
by Yang Liu, Danyang Chen, Haochen Zhang and Songheng Jin
Forests 2024, 15(12), 2238; https://doi.org/10.3390/f15122238 - 19 Dec 2024
Abstract
Previous studies have shown that there are significant sexual differences in the physiological responses of Torreya grandis to environmental stress. However, little is known about its sex-specific differences in response to salt stress against the background of nitrogen (N) deposition. In this experiment, [...] Read more.
Previous studies have shown that there are significant sexual differences in the physiological responses of Torreya grandis to environmental stress. However, little is known about its sex-specific differences in response to salt stress against the background of nitrogen (N) deposition. In this experiment, two-year-old male and female T. grandis seedlings were used as experimental materials and exposed to moderate salt conditions and different N levels to study the effects of nitrogen addition and salt stress on the chlorophyll content, chlorophyll fluorescence parameters, antioxidant system, and leaf stoichiometry of T. grandis seedlings. With the increase in nitrogen content, the contents of proline, malondialdehyde, superoxide anion, and H2O2 in the leaves of T. grandis seedlings under salt conditions gradually increased. The contents of these four metabolites in the leaves of male T. grandis seedlings were almost all higher than those of the female ones. Compared with the control group, the contents of enzymatic and non-enzymatic antioxidants increased under N addition treatments, especially for the low and moderate N addition groups. The results showed that moderate concentrations of N addition can mitigate the damage caused by salt, while high concentrations of nitrogen do not. Under conditions of salt and nitrogen addition, female T. grandis seedlings outperformed male ones, as evidenced by their higher photosynthetic pigment content, enhanced antioxidant enzyme activity, reduced accumulation of intracellular cytotoxic metabolites, and higher carbon and nitrogen content in their leaves compared to those of male seedlings. The findings of this research will contribute to our understanding and offer a theoretical foundation for the cultivation of T. grandis seedlings in environments with nitrogen deposition and salinization. Full article
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<p>Contents of photosynthetic pigments ((<b>A</b>), Chl a; (<b>B</b>), Chl b; (<b>C</b>), total chlorophyll; and (<b>D</b>), carotenoid) in the leaves of female and male <span class="html-italic">T. grandis</span>: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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<p>Common dynamic chlorophyll fluorescence parameters of <span class="html-italic">T. grandis</span> seedlings. (<b>A</b>), male; (<b>B</b>), female. ABS/RC, DIo/RC, TRo/RC, ETo/RC, and PIabs represent the energy absorbed by a single PSII reaction center, the energy dissipated by a single PSII reaction center, the energy absorbed by a single PSII reaction center for the reduction of primary quinone receptors, the energy captured by a single reaction center for electron transfer, and the leaf surface performance index based on absorbed light energy, respectively. Assuming that all parameters of the control are 1, the ratios of the other treatments to the control are plotted.</p>
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<p>Antioxidant enzyme activities ((<b>A</b>), APX; (<b>B</b>), CAT; (<b>C</b>), POD; (<b>D</b>), SOD) in the leaves of male and female <span class="html-italic">T. grandis</span> seedlings: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added); and SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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<p>Contents of glutathione (GSH; (<b>A</b>)), starch (<b>B</b>), soluble protein (<b>C</b>), and proline (PRO; (<b>D</b>)) in the leaves of <span class="html-italic">T. grandis</span> seedlings: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; and SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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<p>H<sub>2</sub>O<sub>2</sub> (<b>A</b>) and malondialdehyde (MDA; (<b>B</b>)) content in the leaves of <span class="html-italic">T. grandis</span> seedlings: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; and SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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<p>Carbon (<b>A</b>), nitrogen (<b>B</b>), and phosphorus (<b>C</b>) content in the leaves of <span class="html-italic">T. grandis</span> seedlings after treatments: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; and SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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<p>Carbon (C)/nitrogen (N) (<b>A</b>), C/phosphorus (P) (<b>B</b>), and N:P (<b>C</b>) ratios of the leaves of <span class="html-italic">T. grandis</span> seedlings after treatments: CK, moderate N, N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup>; SLN, low N, ≈0, N added at the level of 2 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; SMN, moderate N, a total of N added at the level of 20 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added; and SHN, high N, a total of N added at the level of 60 kg N ha<sup>−1</sup> year<sup>−1</sup> and 100 mmol NaCl added. Different uppercase letters indicate a significant difference between genders at <span class="html-italic">p</span> &lt; 0.05, and different lowercase letters indicate a significant difference under treatments of salt and nitrogen additions at <span class="html-italic">p</span> &lt; 0.05, according to Tukey’s test.</p>
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32 pages, 4266 KiB  
Article
Revitalizing Soybean Plants in Saline, Cd-Polluted Soil Using Si-NPs, Biochar, and PGPR
by Khadiga Alharbi, Emad M. Hafez, Nevien Elhawat, Alaa El-Dein Omara, Emadelden Rashwan, Hossam H. Mohamed, Tarek Alshaal and Samir I. Gadow
Plants 2024, 13(24), 3550; https://doi.org/10.3390/plants13243550 - 19 Dec 2024
Abstract
Excessive irrigation of saline-alkaline soils with Cd-contaminated wastewater has resulted in deterioration of both soil and plant quality. To an investigate this, a study was conducted to explore the effects of biochar (applied at 10 t ha−1), PGPRs (Bradyrhizobium japonicum [...] Read more.
Excessive irrigation of saline-alkaline soils with Cd-contaminated wastewater has resulted in deterioration of both soil and plant quality. To an investigate this, a study was conducted to explore the effects of biochar (applied at 10 t ha−1), PGPRs (Bradyrhizobium japonicum (USDA 110) + Trichoderma harzianum at 1:1 ratio), and Si-NPs (25 mg L−1) on soybean plants grown in saline-alkali soil irrigated with wastewater. The results showed that the trio-combination of biochar with PGPRs, (as soil amendments) and Si-NPs (as foliar spraying), was more effective than individual or coupled applications in reducing Cd bioavailability in the soil, minimizing its absorption, translocation and bioconcentration in soybean tissues. The trio-combination reduced Cd bioavailability in the soil by 39.1% and Cd accumulation in plant roots, shoots, and seeds by 61.0%, 69.3%, and 61.1%, respectively. Physiological improvements in soybean plants were also observed, including 197.8% increase in root growth, 209.3% increase in chlorophyll content, and 297.4% increase in carotenoid levels. The trio-combination significantly improved soil physicochemical characteristics, enhanced soil microbial indicators and boosted soil enzymes activity, which in turn facilitated nutrient uptake and increased antioxidant enzymes activity. These positive outcomes enhanced photosynthesis, improved productivity and increased seed nutritional value. Overall, the trio-combination of biochar with PGPRs and Si-NPs are considered a reliable approach not only for revitalizing soybean growth but also for immobilizing Cd and improving soil health under wastewater irrigation. Full article
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<p>(<b>A</b>) EC (dS m<sup>−1</sup>), (<b>B</b>) soil Cd content (mg kg<sup>−1</sup>), (<b>C</b>) Na content (mg L<sup>−1</sup>), (<b>D</b>) K content (mg L<sup>−1</sup>) and (<b>E</b>) ESP, in soil grown with soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) pH, (<b>B</b>) urease (µg TPF g<sup>−1</sup> dry soil 24 h<sup>−1</sup>), (<b>C</b>) dehydrogenase (µg TPF g<sup>−1</sup> dry soil 24 h<sup>−1</sup>) and (<b>D</b>) alkaline-phosphatase (mg phenol g<sup>−1</sup> dry soil 24 h<sup>−1</sup>) in soil grown with soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) soil CO<sub>2</sub> evolution (mg CO<sub>2</sub> 100 g<sup>−1</sup> soil 24 h<sup>−1</sup>) and (<b>B</b>) microbial biomass carbon (SMBc; mg g<sup>−1</sup> Soil) in soil grown with soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) Cd content in roots (µg g<sup>−1</sup>), (<b>B</b>) Cd content in shoots (µg g<sup>−1</sup>), (<b>C</b>) Cd content in seeds (µg g<sup>−1</sup>), (<b>D</b>) Bioconcentration factor (BCF), (<b>E</b>) bioaccumulation coefficient (BAC) and (<b>F</b>) translocation factor (TF) in soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) nodules dry weight (mg plant<sup>−1</sup>), (<b>B</b>) root length (cm), (<b>C</b>) chlorophyll a (mg g<sup>−1</sup> FW), (<b>D</b>) chlorophyll b (mg g<sup>−1</sup> FW), and (<b>E</b>) carotenoids (mg g<sup>−1</sup> FW) in soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Na and K contents in leaves of soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Antioxidant enzymes activity such as catalase (CAT; H<sub>2</sub>O<sub>2</sub> g<sup>−1</sup> FW min<sup>−1</sup>), superoxide dismutase (SOD; µM tetraguaiacol g<sup>−1</sup> FW min<sup>−1</sup>) and peroxidase (POX; µmol H<sub>2</sub>O<sub>2</sub> g<sup>−1</sup> FW min<sup>−1</sup>) in leaves of soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Oxidative stress indicators such as (<b>A</b>) lipid peroxidation (MDA; nmol g<sup>−1</sup> FW), (<b>B</b>) hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>; µmol g<sup>−1</sup> FW) and (<b>C</b>) membrane leakage (ML;%) in leaves of soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Yield and related traits such as (<b>A</b>) number of pods plant<sup>−1</sup>, (<b>B</b>) 100-seed weight (g) and (<b>C</b>) seed yield (kg ha<sup>−1</sup>) of soybean (<span class="html-italic">Glycine max</span> L.), irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar at rate of 10 t ha<sup>−1</sup>, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Nutritional value such as N, P and K of soybean seeds (<span class="html-italic">Glycine max</span> L.) irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK). Different letters on bars are significant based on the Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>PCA of individual response variables determined in soybean (<span class="html-italic">Glycine max</span> L.) irrigated with wastewater Cd-polluted and treated with single, coupled and trio-combination of biochar, PGPR at rate of (1:1) and Si-NPs (25 mg L<sup>−1</sup>) compared to untreated plants (control; CK).</p>
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26 pages, 7665 KiB  
Article
Photosynthetic and Physiological Characteristics of Three Common Halophytes and Their Relationship with Biomass Under Salt Stress Conditions in Northwest China
by Xi Zhang, Tao Lin, Hailiang Xu, Guaikui Gao and Haitao Dou
Appl. Sci. 2024, 14(24), 11890; https://doi.org/10.3390/app142411890 - 19 Dec 2024
Abstract
Three different types of common halophytes (Haloxylon ammodendron, Tamarix chinensis, and Phragmites australis) in northwest China were used in this study. A field experiment approach was adopted, involving five solutions with different salt concentrations (0, 150, 200, 250, and 300 [...] Read more.
Three different types of common halophytes (Haloxylon ammodendron, Tamarix chinensis, and Phragmites australis) in northwest China were used in this study. A field experiment approach was adopted, involving five solutions with different salt concentrations (0, 150, 200, 250, and 300 mmol·L−1) for salt stress treatment. The changes in photosynthetic characteristics and physiological characteristics of three different types of halophytes and their relationship with biomass were measured and analyzed. The results showed that (1) with the increase in salt concentration, the plant height, stem diameter, and biomass of three halophytes showed a downward trend. (2) The chlorophyll a, chlorophyll b, and total chlorophyll contents of Haloxylon ammodendron and Tamarix chinensis first increased and then decreased with the increase in salt concentration. Phragmites australis showed a decreasing trend. The malondialdehyde content of three halophytes showed a clear increasing trend. (3) Under different salt concentrations, the diurnal changes in the net photosynthetic rate, transpiration rate, stomatal conductance, and water use efficiency of three different types of halophytes all showed an “M” trend. The diurnal variation in intercellular carbon dioxide concentration showed a “W” trend. (4) With the increase in salt concentration, the daily average values of the net photosynthetic rate, transpiration rate, and stomatal conductance of three different types of halophytes showed a downward trend. The daily average value of intercellular carbon dioxide concentration showed a “V”-shaped trend of first decreasing and then increasing. The daily average value of water use efficiency showed a “single peak” trend of first increasing and then decreasing. Haloxylon ammodendron and Phragmites australis were mainly limited by stomata at a salt concentration of 0~200 mmol·L−1 and were mainly limited by non-stomata at a salt concentration of 250~300 mmol·L−1. Tamarix chinensis is mainly limited by stomata at a salt concentration of 0~250 mmol·L−1 and is mainly limited by non-stomata at a salt concentration of 300 mmol·L−1. Compared with Haloxylon ammodendron and Phragmites australis, Tamarix chinensis has better water use efficiency, salt tolerance, and adaptability. (5) Meteorological factors, growth morphological factors, physiological factors, photosynthetic factors, and salt concentration have higher explanatory degrees, which have significant effects on the biomass of halophytes. Among them, salt concentration and growth morphological factors have direct core driving effects on the biomass of three different types of halophytes, while meteorological factors, photosynthetic factors, and physiological factors have different effects due to the differences in and complexity of halophytes. This study can provide a theoretical basis for further revealing the adaptation mechanism of different halophytes to salt stress. Full article
(This article belongs to the Special Issue Recent Advances in Halophytes Plants)
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<p>Overview of the study area. (<b>a</b>) Geographical location of the study area; (<b>b</b>) topography of the study area.</p>
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<p>Daily variation in meteorological factors in the study area.</p>
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<p>Effects of different salt concentration treatments on the growth of halophytes. (<b>a</b>) Plant height. (<b>b</b>) Stem diameter. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05). A total of 375 samples. Same as below.</p>
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<p>Effect of different salt concentration treatments on the physiology of halophytes. (<b>a</b>) Contents of chlorophyll a and chlorophyll b. (<b>b</b>) Contents of total chlorophyll and malondialdehyde. The error bar above the graph represents the standard error. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Characteristics of daily changes in Pn of halophytes under different salt concentration treatments. (<b>a</b>) Ha. (<b>b</b>) Tc. (<b>c</b>) Pa. (<b>d</b>) Daily average of net photosynthetic rate. The error bar above the graph represents the standard error. The same below. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Characteristics of daily changes in Tr of halophytes under different salt concentration treatments. (<b>a</b>) Ha. (<b>b</b>) Tc. (<b>c</b>) Pa. (<b>d</b>) Daily average of transpiration rate. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Characteristics of daily changes in Gs of halophytes under different salt concentration treatments. (<b>a</b>) Ha. (<b>b</b>) Tc. (<b>c</b>) Pa. (<b>d</b>) Daily average of stomatal conductance. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Characteristics of daily changes in Ci of halophytes under different salt concentration treatments. (<b>a</b>) Ha. (<b>b</b>) Tc. (<b>c</b>) Pa. (<b>d</b>) Daily average of intercellular carbon dioxide concentration. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Characteristics of daily changes in Wue of halophytes under different salt concentration treatments. (<b>a</b>) Ha. (<b>b</b>) Tc. (<b>c</b>) Pa. (<b>d</b>) Daily average of water use efficiency. Different lowercase letters in the graphs indicate significant differences under different salt concentration treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of different salt concentration treatments on biomass of halophytes. The error bar above the graph represents the standard error.</p>
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<p>Relationship between different ecological factors and biomass of halophytes. (<b>a</b>) RDA ordination plot of ecological factors versus halophytes biomass; (<b>b</b>) degree of explanation of halophyte biomass by each ecological factor; “ACO2” is atmospheric carbon dioxide concentration. “Tr” is transpiration rate. “TChl” is total chlorophyll. “Wue” is water use efficiency. “Rh” is relative humidity. “Gs” is stomatal conductance. “Pn” is net photosynthetic rate. “Ta” is atmospheric temperature. “Cb” is chlorophyll b. “D” is stem diameter. “Ci” is intercellular carbon dioxide concentration. “Ca” is chlorophyll a. “MDA” is malondialdehyde. “H” is plant height. “Sc” is salt concentration. “TB” is total biomass. * represents <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Structural equation modeling of different ecological factors and biomass of halophytes. (<b>a</b>) Structural equation modeling of different ecological factors with Ha biomass; (<b>b</b>) structural equation modeling of different ecological factors with Tc biomass; (<b>c</b>) structural equation modeling of different ecological factors with Pa biomass; (<b>d</b>) direct and indirect effects of different ecological factors on Ha biomass; (<b>e</b>) direct and indirect effects of different ecological factors on Tc biomass; (<b>f</b>) direct and indirect effects of different ecological factors on Pa biomass; blue arrows in the figure represent positive correlations, and orange arrows represent negative correlations. A solid line indicates a significant effect, and a dashed line indicates a non-significant effect. The numbers next to the arrows are standardized path coefficients, which reflect the magnitude of the effect between the variables. The width of the arrows is proportional to the standardized path coefficient. * represents <span class="html-italic">p</span> &lt; 0.05. ** represents <span class="html-italic">p</span> &lt; 0.01. *** represents <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Average survival rate of 12 different plants from 2021 to 2023.</p>
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<p>Comparison of ecological restoration effect before and after. (<b>a</b>) Before ecological restoration; (<b>b</b>) after ecological restoration.</p>
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23 pages, 7833 KiB  
Article
Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning
by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu and Yuxuan Feng
Agriculture 2024, 14(12), 2326; https://doi.org/10.3390/agriculture14122326 - 19 Dec 2024
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Abstract
This study accurately inverts key growth parameters of rice, including Leaf Area Index (LAI), chlorophyll content (SPAD) value, and height, by integrating multisource remote sensing data (including MODIS and ERA5 imagery) and deep learning models. Dehui City in Jilin Province, China, was selected [...] Read more.
This study accurately inverts key growth parameters of rice, including Leaf Area Index (LAI), chlorophyll content (SPAD) value, and height, by integrating multisource remote sensing data (including MODIS and ERA5 imagery) and deep learning models. Dehui City in Jilin Province, China, was selected as the case study area, where multidimensional data including vegetation indices, ecological function parameters, and environmental variables were collected, covering seven key growth stages of rice. Data analysis and parameter prediction were conducted using a variety of machine learning and deep learning models including Partial Least Squares (PLSs), Support Vector Machine (SVM), Random Forest (RF), and Long Short-Term Memory Networks (LSTM), among which the LSTM model demonstrated superior performance, particularly at multiple critical time points. The results show that the LSTM performed best in inverting the three parameters, with the LAI inversion accuracy on 21 August reaching a coefficient of determination (R2) of 0.72, root mean square error (RMSE) of 0.34, and mean absolute error (MAE) of 0.27. The SPAD inversion accuracy on the same date achieved an R2 of 0.69, RMSE of 1.45, and MAE of 1.16. The height inversion accuracy on 25 July reached an R2 of 0.74, RMSE of 2.30, and MAE of 2.08. This study not only verifies the effectiveness of combining multisource data and advanced algorithms but also provides a scientific basis for the precision management and decision-making of rice cultivation. Full article
(This article belongs to the Section Digital Agriculture)
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<p>Map of the study area of Dehui City, Jilin Province, showing rice distribution and sampling points.</p>
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<p>Integrated framework for inverting key growth parameters of rice using multisource data and machine learning/deep learning models.</p>
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<p>Correlation between selected key variables and field-measured LAI on 6 July. Note: one asterisk (*), double asterisk (**), and threefold asterisks (***) indicate a correlation coefficient (r) with statistically significance levels of <span class="html-italic">p</span>-value &lt; 0.05, 0.01, and 0.001, respectively.</p>
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<p>Standardized SHAP values for features influencing LAI, SPAD, and height predictions across different dates.</p>
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<p>Comparison of R<sup>2</sup>, RMSE, and MAE for LAI, SPAD, and height predictions using different variable combinations across three growth stages. (<b>a</b>–<b>c</b>) represent the R<sup>2</sup> values for different variable combinations on 6 July, 25 July, and 21 August, respectively. (<b>d</b>–<b>f</b>) represent the RMSE for different variable combinations on 6 July, 25 July, and 21 August, respectively. (<b>g</b>–<b>i</b>) represent the MAE for different variable combinations on 6 July, 25 July, and 21 August, respectively.</p>
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<p>Spatial inversion maps of LAI, SPAD, and height across three key growth stages (6 July, 25 July, and 21 August). (<b>a</b>–<b>c</b>) are the spatial inversion maps of LAI at the three key growth stages. (<b>d</b>–<b>f</b>) are the spatial inversion maps of SPAD at the three key growth stages. (<b>g</b>–<b>i</b>) are the spatial inversion maps of height at the three key growth stages.</p>
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<p>Accuracy evaluation of predicted and measured LAI, SPAD, and height using the LSTM model at three key growth stages. (<b>a</b>–<b>c</b>) are accuracy evaluation of LAI for three periods. (<b>d</b>–<b>f</b>) are accuracy evaluation of SPAD for three periods. (<b>g</b>–<b>i</b>) are accuracy evaluation of Height for three periods.</p>
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19 pages, 5730 KiB  
Article
Enhancing Urban Sustainability: How Spatial and Height Variability of Roadside Plants Improves Pollution Capture for Greener Cities
by Robert Popek, Anamika Roy, Mamun Mandal, Arkadiusz Przybysz, Katarzyna Drążkiewicz, Patrycja Romanowska and Abhijit Sarkar
Sustainability 2024, 16(24), 11131; https://doi.org/10.3390/su162411131 - 19 Dec 2024
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Abstract
Air pollution, particularly particulate matter (PM), poses a significant threat to urban environments and public health. This study aims to explore the impact of small-scale spatial and height variations on the ability of different roadside tree species: Tilia cordata Mill., Platanus × hispanica [...] Read more.
Air pollution, particularly particulate matter (PM), poses a significant threat to urban environments and public health. This study aims to explore the impact of small-scale spatial and height variations on the ability of different roadside tree species: Tilia cordata Mill., Platanus × hispanica Mill. ex Münchh., and Sorbus intermedia (Ehrh.) Pers., to accumulate PM, providing insights for enhancing urban sustainability. Conducted along a high-traffic road in Warsaw, Poland, the research examines PM accumulation at varying heights and locations within tree canopies while also evaluating the influence of PM on photosynthetic efficiency. Results indicate substantial differences in PM accumulation between tree species and height ranges, with S. intermedia accumulating the highest PM levels. PM accumulation was greatest near the roadside and at lower canopy heights (1–1.5 m), while higher canopies and areas distant from the road showed reduced PM concentrations. T. cordata exhibited the highest PM accumulation on the side facing traffic, averaging 12% at 1–1.5 m height, while the interior recorded 5% at 2–2.5 m height. In S. intermedia, the roadside crown contributed the highest accumulation (14%) at 1–1.5 m height and only 6% on the side facing departing traffic at 2–2.5 m height. P. hispanica displayed higher efficiency in PM accumulation, reaching 11% at the roadside (1–1.5 m) and 7% at the top of the crown (3–3.5 m). Additionally, PM accumulation negatively impacted photosynthetic efficiency and chlorophyll content, with the highest PM levels correlating with reduced plant vitality. PCA analysis showed a stronger association between leaf-deposited PM and total chlorophyll content and that the presence of accumulated PM may significantly influence the chlorophyll content of the plants. These findings provide valuable guidance for urban planners in strategically planting roadside vegetation to maximize air quality improvement, offering a cost-effective and sustainable approach to mitigate urban pollution. Full article
(This article belongs to the Special Issue Advances in Ecosystem Services and Urban Sustainability, 2nd Edition)
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Figure 1

Figure 1
<p>(<b>a</b>) Europe. (<b>b</b>) Poland with Warsaw. (<b>c</b>) Satellite view of the sampling site—Aleja Jana Rodowicza “Anody” street in the Ursynów district of Warsaw, and (<b>d</b>) 360° view of the study site. Satellite and 360°view of the study site obtained from Google Maps (available online: <a href="https://maps.google.com" target="_blank">https://maps.google.com</a>). Investigated species—(<b>e</b>) <span class="html-italic">Tilia cordata Mill.</span>, (<b>f</b>) <span class="html-italic">Platanus</span> × <span class="html-italic">hispanica Mill. Ex</span> Münchh., (<b>g</b>) <span class="html-italic">Sorbus intermedia</span> (Ehrh.) Pers. (<b>h</b>) The precise image shows a wind rose plot and a scale, and (<b>i</b>) air mass back trajectories of the study area during the study period.</p>
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<p>The flowchart of the research methodology.</p>
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<p>The concentrations of PM<sub>10</sub>, PM<sub>2.5</sub>, and PM<sub>1</sub> in air in different sampling sites and height.</p>
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<p>Total amount of PM, <sub>S</sub>PM, <sub>W</sub>PM, and different PM fractions accumulation by investigated species. Data are presented as mean ± SE. Different letters indicate significant differences.</p>
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<p>Total amount of different PM fractions accumulation by investigated species.</p>
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<p>(<b>a</b>) Amount of leaf-surface wax (µg cm<sup>−2</sup>) in investigated plant species. Data are presented as mean ± SE. Different letters indicate significant differences. (<b>b</b>) Relationship between the epicuticular wax amount in leaves and accumulation of wax PM (<sub>W</sub>PM) in the leaves of the investigated species.</p>
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<p>Amount of Fv/Fm, PI, and total chlorophyll amount in investigated plant species. Data are presented as mean ± SE. Different letters indicate significant differences.</p>
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<p>Principal component analysis (PCA) of particulate matter (PM) in the air and plant responses of investigated three species in different canopy sites. TC-R-1: <span class="html-italic">Tilia cordata</span> roadside at 1–1.5 m, TC-PS-1: <span class="html-italic">T. cordata</span> pavement side at 1–1.5 m, TC-AC-1: <span class="html-italic">T. cordata</span> approaching car side at 1–1.5 m, TC-DC-1: <span class="html-italic">T. cordata</span> departing car side at 1–1.5 m, TC-I-1: <span class="html-italic">T. cordata</span> inside at 1–1.5 m, TC-R-2: <span class="html-italic">T. cordata</span> roadside at 2–2.5 m, TC-PS-2: <span class="html-italic">T. cordata</span> pavement side at 2–2.5 m, TC-AC-2: <span class="html-italic">T. cordata</span> approaching car side at 2–2.5 m, TC-DC-2: <span class="html-italic">T. cordata</span> departing car side at 2–2.5 m, TC-I-2: <span class="html-italic">T. cordata</span> inside at 2–2.5 m, TC-T-3: <span class="html-italic">T. cordata</span> top at 3–3.5 m, SI-R-1: <span class="html-italic">Sorbus intermedia</span> roadside at 1–1.5 m, SI-PS-1: <span class="html-italic">S. intermedia</span> pavement side at 1–1.5 m, SI-AC-1: <span class="html-italic">S. intermedia</span> approaching car side at 1–1.5 m, SI-DC-1: <span class="html-italic">S. intermedia</span> departing car side at 1–1.5 m, SI-I-1: <span class="html-italic">S. intermedia</span> inside at 1–1.5 m, SI-R-2: <span class="html-italic">S. intermedia</span> roadside at 2–2.5 m, SI-PS-2: <span class="html-italic">S. intermedia</span> pavement side at 2–2.5 m, SI-AC-2: <span class="html-italic">S. intermedia</span> approaching car side at 2–2.5 m, SI-DC-2: <span class="html-italic">S. intermedia</span> departing car side at 2–2.5 m, SI-I-2: <span class="html-italic">S. intermedia</span> inside at 2–2.5 m, SI-T-3: <span class="html-italic">S. intermedia</span> top at 3–3.5 m, PH-R-1: <span class="html-italic">Platanus</span> × <span class="html-italic">hispanica</span> roadside at 1–1.5 m, PH-PS-1: <span class="html-italic">P. hispanica</span> pavement side at 1–1.5 m, PH-AC-1: <span class="html-italic">P. hispanica</span> approaching car side at 1–1.5 m, PH-DC-1: <span class="html-italic">P. hispanica</span> departing car side at 1–1.5 m, PH-I-1: <span class="html-italic">P. hispanica</span> inside at 1–1.5 m, PH-R-2: <span class="html-italic">P. hispanica</span> roadside at 2–2.5 m, PH-PS-2: <span class="html-italic">P. hispanica</span> pavement side at 2–2.5 m, PH-AC-2: <span class="html-italic">P. hispanica</span> approaching car side at 2–2.5 m, PH-DC-2: <span class="html-italic">P. hispanica</span> departing car side at 2–2.5 m, PH-I-2: <span class="html-italic">P. hispanica</span> inside at 2–2.5 m, PH-T-3: <span class="html-italic">P. hispanica</span> top at 3–3.5 m.</p>
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