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Search Results (2,272)

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19 pages, 8885 KiB  
Article
Slow-Release Nitrogen Fertilizer Promotes the Bacterial Diversity to Drive Soil Multifunctionality
by Tiantian Meng, Jingjing Shi, Xiangqian Zhang, Guolong Ge, Yuchen Cheng, Meiren Rong, Liyu Chen, Xiaoyu Zhao, Xiaoxiang Wang and Zhanyuan Lu
Agronomy 2024, 14(11), 2712; https://doi.org/10.3390/agronomy14112712 (registering DOI) - 17 Nov 2024
Abstract
The application of slow-release nitrogen fertilizer not only economizes labor input, but also decreases the frequency of use of mechanical intakes, with significant implications in advancing modern intensive agricultural production. Whether slow-release nitrogen fertilizer application can influence the association between microbial diversity and [...] Read more.
The application of slow-release nitrogen fertilizer not only economizes labor input, but also decreases the frequency of use of mechanical intakes, with significant implications in advancing modern intensive agricultural production. Whether slow-release nitrogen fertilizer application can influence the association between microbial diversity and soil multifunctionality remains controversial. This study analyzed the spatial variances of soil environmental factors, soil multifunctionality, and their correlations with bacterial and fungal communities under five nitrogen application rates. The key factors influencing the dominant microbial species and community structures at different spatial locations were determined by the slow-release nitrogen fertilizer application rate, and the driving factors and dominant species of soil multifunctionality were identified. In contrast to the control group, moderate slow-release nitrogen fertilizer application enhanced soil multifunctionality and ameliorated the resilience of microbial diversity loss at diverse spatial locations resulting from irrational nitrogen fertilizer application. The resilience of the fungal community to disturbances caused by fertilization was lower than that of the bacterial community. Bacterial diversity exhibited a significant correlation with soil multifunctionality, and the soil multifunctionality intensity under 240 kg ha−1 treatment increased by 159.01% compared to the CK. The main dominant bacterial communities and the dominant fungal community Ascomycota affected soil multifunctionality through slow-release nitrogen fertilizer application. Structural equation modeling and random forest analysis demonstrated that bacterial community diversity, particularly in bulk soil and the rhizosphere, community composition, and soil nitrogen form are the primary driving factors of soil multifunctionality. Results indicated that the microbial niche alterations induced by slow-release nitrogen fertilizer application positively affect soil multifunctionality. Full article
(This article belongs to the Section Soil and Plant Nutrition)
18 pages, 5263 KiB  
Article
Kiwifruit Vine Decline Syndrome (KVDS) Alters Soil Enzyme Activity and Microbial Community
by Valentino Bergamaschi, Alfonso Vera, Lucia Pirone, José A. Siles, Rubén López-Mondéjar, Laura Luongo, Salvatore Vitale, Massimo Reverberi, Alessandro Infantino and Felipe Bastida
Microorganisms 2024, 12(11), 2347; https://doi.org/10.3390/microorganisms12112347 (registering DOI) - 16 Nov 2024
Viewed by 432
Abstract
Kiwifruit Vine Decline Syndrome (KVDS) has become a major concern in Italy, impacting both plant health and production. This study aims to investigate how KVDS affects soil health indicators and the composition of soil microbial communities by comparing symptomatic and asymptomatic areas in [...] Read more.
Kiwifruit Vine Decline Syndrome (KVDS) has become a major concern in Italy, impacting both plant health and production. This study aims to investigate how KVDS affects soil health indicators and the composition of soil microbial communities by comparing symptomatic and asymptomatic areas in two kiwifruit orchards located in Latium, Italy. Soil samples were collected during both spring and autumn to assess seasonal variations in soil physicochemical properties, enzyme activities, and microbial biomass. The results reveal that KVDS influences several soil properties, including pH, electrical conductivity, and the contents of water-soluble carbon and nitrogen. However, these effects varied between orchards and across different seasons. Additionally, KVDS significantly impacts soil enzyme activities and microbial biomass, as assessed through the phospholipid fatty acid (PLFA) analysis, particularly showing an increase in fungal biomass in symptomatic areas. Metabarcoding further demonstrates that microbial communities differ between symptomatic and asymptomatic soils, exhibiting notable shifts in both diversity and relative abundance. Our findings emphasise the complex interactions between plants, soil, and microbial communities in relation to KVDS. This suggests that the syndrome is multifactorial and likely linked to an imbalance in soil microbial communities at the rhizosphere level, which can negatively affect soil health. Full article
(This article belongs to the Section Environmental Microbiology)
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Figure 1
<p>Sampling layout and orchard conditions. (<b>a</b>) Asymptomatic and (<b>b</b>) symptomatic kiwifruit orchard. Detailed view of kiwifruit trees with designated sampling points around the trunk for (<b>c</b>) asymptomatic and (<b>d</b>) symptomatic trees with the five specific sampling locations around each trunk.</p>
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<p>Scoring scale for disease severity (0–3) for epigeal and hypogeal symptoms in kiwifruit plants. Epigeal symptoms: (<b>b</b>) no symptoms (healthy plant); (<b>d</b>) mild symptoms (plant decline sometimes visible through reduced shoot growth, leaf chlorosis, fewer new shoots, and smaller leaves); (<b>f</b>) severe symptoms (leaf drop, fruit drop, reduced fruit size if present, and overall vine decline); (<b>h</b>) dead plant. Hypogeal symptoms: (<b>a</b>) no symptoms (healthy roots); (<b>c</b>) mild symptoms (reduction of absorbent roots and visible necrosis); (<b>e</b>) severe symptoms (decay of primary roots, near-complete rot of secondary roots, loss of cortical tissue, “rat-tail” appearance, and loss of absorbent roots); (<b>g</b>) dead roots. For root symptoms, images show roots during sampling (<b>left</b>) and after washing (<b>right</b>).</p>
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<p>Bar chart of soil physicochemical properties of Orchards 1 and 2 in Spring and Autumn. (<b>a</b>) pH, (<b>b</b>) SOC: soil organic carbon content, (<b>c</b>) WSC: soil water-soluble C, (<b>d</b>) EC: electrical conductivity, (<b>e</b>) TN: total soil nitrogen content, (<b>f</b>) WSN: soil water-soluble N, and the letters A and S indicate Asymptomatic and Symptomatic, respectively. Different letters (a, b) indicate significant differences based on One-Way ANOVA results at <span class="html-italic">p</span> &lt; 0.05. Error bars represent the standard error of the mean (4 replicates).</p>
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<p>Bar chart of β-glucosidase (μmol PNF g<sup>−1</sup> soil h<sup>−1</sup>) (<b>a</b>), alkaline phosphatase (μmol PNF g<sup>−1</sup> soil h<sup>−1</sup>) (<b>b</b>), urease (μmol NH<sub>4</sub><sup>+</sup> g<sup>−1</sup> soil h<sup>−1</sup>) (<b>c</b>), and basal soil respiration (BSR) (mg CO<sub>2</sub> kg<sup>−1</sup> soil day<sup>−1</sup>) (<b>d</b>) of Orchard 1 and 2 in Spring and Autumn. The letters A and S indicate Asymptomatic and Symptomatic, respectively. Different letters (a, b) indicate significant differences based on One-Way ANOVA results at <span class="html-italic">p</span> &lt; 0.05. Error bars represent the standard error of the mean (4 replicates).</p>
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<p>Bar chart of biomass abundance (nmol g<sup>−1</sup> soil h<sup>−1</sup>) divided into Bacteria (<b>a</b>), Fungi (<b>b</b>), Gram- Total Biomass (<b>c</b>), Fungi/Bacteria ratio (<b>d</b>), of Orchard 1 and 2 in Spring and Autumn. Different letters (a, b) indicate significant differences based on One-Way ANOVA results at <span class="html-italic">p</span> &lt; 0.05. Error bars represent the standard error of the mean (4 replicates).</p>
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<p>Heat map of Spearman’s correlation for soil and physiological parameters. Negative and positive correlations are represented in blue and red, respectively. All correlations are significant at <span class="html-italic">p</span> &lt; 0.05. EC: electrical conductivity, WSC: soil water-soluble C, WSN: soil water-soluble N, Amm: soil ammonium content, Ntotal: total soil nitrogen content, C total: total soil carbon content, SOC: soil organic carbon, CaCO<sub>3</sub>: soil carbonate calcium content, CN: carbon/nitrogen ratio, bG: β-glucosidase activity, alkP: alkaline phosphatase activity, Ure: urease activity, BSR: basal soil respiration, Fun: soil fungal biomass, Bac: soil bacterial biomass, TB: total soil microbial biomass.</p>
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<p>Composition of fungal (<b>a</b>) and bacterial (<b>b</b>) abundance at phylum level in Orchards 1 and 2 in Spring and Autumn.</p>
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<p>NMDS analysis of fungal community (<b>a</b>) and bacterial community (<b>b</b>) from Orchard 1 in Spring (dot) and Autumn (triangle), and Orchard 2 in Spring (square) and Autumn (cross). The asymptomatic and symptomatic samples are shown in red and blue, respectively. For the PerMANOVA test, the significance levels are shown at * <span class="html-italic">p</span> ≤ 0.05, and *** <span class="html-italic">p</span> ≤ 0.001. O×C means orchard and status interaction.</p>
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19 pages, 6417 KiB  
Article
Effects of Rice Root Development and Rhizosphere Soil on Methane Emission in Paddy Fields
by Sheng Guan, Zhijuan Qi, Sirui Li, Sicheng Du and Dan Xu
Plants 2024, 13(22), 3223; https://doi.org/10.3390/plants13223223 (registering DOI) - 16 Nov 2024
Viewed by 161
Abstract
Paddy fields are important anthropogenic emission sources of methane (CH4). However, it is not clear how rice root development and rhizosphere soil properties affect CH4 emissions. Therefore, we selected rice varieties with similar growth periods but different root traits in [...] Read more.
Paddy fields are important anthropogenic emission sources of methane (CH4). However, it is not clear how rice root development and rhizosphere soil properties affect CH4 emissions. Therefore, we selected rice varieties with similar growth periods but different root traits in the local area. We measured CH4 emission fluxes, cumulative CH4 emissions, root dry weight, root length, and the dissolved organic carbon (DOC), microbial biomass carbon (MBC), redox potential (Eh), ammonium nitrogen (NH+ 4–N), and nitrate nitrogen (NO− 3–N) contents in rhizosphere soil. Methanogens and methanotrophs are crucial factors influencing CH4 emissions; thus, their abundance and community composition were also assessed. The result showed that CH4 fluxes of each rice variety reached the peak at tillering stage and jointing-booting stage. The CH4 emissions in tillering stage were the largest in each growth period. CH4 emissions had negative correlations with root length, root dry weight, Eh NO− 3–N, methanotroph abundance, and the pmoA/mcrA ratio, and positive correlations with NH+ 4–N, MBC, DOC, and methanogen abundance. Path analysis confirmed methanogens and methanotrophs as direct influences on CH4 emissions. Root development and rhizosphere soil properties affect CH4 emissions indirectly through these microbes. This study suggests that choosing rice varieties with good root systems and managing the rhizosphere soil can effectively reduce CH4 emissions. Full article
(This article belongs to the Special Issue Plant Root: Anatomy, Structure and Development)
28 pages, 936 KiB  
Review
Processing Tomato and Potato Response to Biostimulant Application in Open Field: An Overview
by Marco Francesco Golin, Vittoria Giannini, Marco Bagarello, Wendy Carolina Vernaza Cartagena, Maria Giordano and Carmelo Maucieri
Agronomy 2024, 14(11), 2699; https://doi.org/10.3390/agronomy14112699 (registering DOI) - 16 Nov 2024
Viewed by 136
Abstract
Biostimulants include a wide array of microorganisms and substances that can exert beneficial effects on plant development and growth, often enhancing nutrient uptake and improving tolerance against abiotic and biotic stress. Depending on their composition and time of application, these products can influence [...] Read more.
Biostimulants include a wide array of microorganisms and substances that can exert beneficial effects on plant development and growth, often enhancing nutrient uptake and improving tolerance against abiotic and biotic stress. Depending on their composition and time of application, these products can influence plant physiology directly as growth regulators or indirectly through environmental condition changes in the rhizosphere, such as nutrient and water availability. This review evaluated 48 case studies from 39 papers to summarize the effects of biostimulant application on fruit and tuber yields and on the quality of processing tomato and potato in open field conditions. For potato, PGPR bacteria were the main studied biostimulant, whereas the low number of studies on processing tomato did not permit us to delineate a trend. The yield and quality were greatly influenced by cultivars and biostimulant composition, application method, period, and dose. For processing tomato, a positive effect of the biostimulant application on the marketable yield was reported in 79% of the case studies, whereas for potato, the effect was reported in only 47%. Few studies, on processing tomato and potato, also reported data for quality parameters with contrasting results. The variability of crop response to biostimulant application in open field conditions highlights the need for more comprehensive studies. Such studies should focus on diverse cultivars, deeply understand the interaction of biostimulant application with agronomic management (e.g., irrigation and fertilization), and evaluate yield and quality parameters. This approach is crucial to fully understand the potential and limitations of biostimulant applications in agriculture, particularly regarding their role in sustainable crop production. Full article
17 pages, 8788 KiB  
Article
Effects of Deep Tillage on Rhizosphere Soil and Microorganisms During Wheat Cultivation
by Junkang Sui, Chenyu Wang, Feifan Hou, Xueting Shang, Qiqi Zhao, Yuxuan Zhang, Yongqiang Hou, Xuewen Hua and Pengfei Chu
Microorganisms 2024, 12(11), 2339; https://doi.org/10.3390/microorganisms12112339 (registering DOI) - 16 Nov 2024
Viewed by 319
Abstract
The production of wheat is fundamentally interconnected with worldwide food security. The practice of deep tillage (DT) cultivation has shown advantages in terms of soil enhancement and the mitigation of diseases and weed abundance. Nevertheless, the specific mechanisms behind these advantages are unclear. [...] Read more.
The production of wheat is fundamentally interconnected with worldwide food security. The practice of deep tillage (DT) cultivation has shown advantages in terms of soil enhancement and the mitigation of diseases and weed abundance. Nevertheless, the specific mechanisms behind these advantages are unclear. Accordingly, we aimed to clarify the influence of DT on rhizosphere soil (RS) microbial communities and its possible contribution to the improvement of soil quality. Soil fertility was evaluated by analyzing several soil characteristics. High-throughput sequencing techniques were utilized to explore the structure and function of rhizosphere microbial communities. Despite lowered fertility levels in the 0–20 cm DT soil layer, significant variations were noted in the microbial composition of the DT wheat rhizosphere, with Acidobacteria and Proteobacteria being the most prominent. Furthermore, the abundance of Bradyrhizobacteria, a nitrogen-fixing bacteria within the Proteobacteria phylum, was significantly increased. A significant increase in glycoside hydrolases within the DT group was observed, in addition to higher abundances of amino acid and carbohydrate metabolism genes in the COG and KEGG databases. Moreover, DT can enhance soil quality and boost crop productivity by modulating soil microorganisms’ carbon and nitrogen fixation capacities. Full article
(This article belongs to the Special Issue Advances in Soil Microbial Ecology, 2nd Edition)
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<p>The α-diversities of deep-tillage cultivation group’s and control group’s wheat rhizosphere soil microbes. (<b>a</b>) for Chao index value, (<b>b</b>) for Simpson index value, (<b>c</b>) for shannon index value.DT and CK: Deep- and non-deep-tillage cultivated wheat rhizosphere soil groups, respectively.</p>
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<p>β-diversities (NMDS and ANOSIM analysis) of DT and CK cultivation wheat rhizosphere soil microbes. (<b>a</b>) for NMDS analysis, (<b>b</b>) for ANOSIM analysis. DT and CK: Deep- and non-deep-tillage cultivated wheat rhizosphere soil groups, respectively.</p>
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<p>Phylum-level compositions (<b>a</b>) and differences (<b>b</b>) and genus-level compositions (<b>c</b>) and differences (<b>d</b>) in the rhizosphere soil (RS) microbiome in various cultivation modes. * represented 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** represented 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** represented <span class="html-italic">p</span> ≤ 0.001. DT and CK: Deep- and non-deep-tillage cultivated wheat RS groups, respectively.</p>
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<p>Gene abundance in microbes of deep- and non-deep-tillage rhizosphere soil. (<b>a</b>) Relative abundance changes in COG genes; (<b>b</b>) KEGG metabolic pathway-related functional genes.</p>
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<p>Carbohydrate enzyme-related genes in DT and CK rhizosphere soil (RS) microbes. (<b>a</b>) Proportion of the carbohydrate enzyme-correlated genes in the RS of both groups; (<b>b</b>) comparison of the difference in carbohydrate enzyme-correlated genes in the RS microbes of both groups. ** represented 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01. DT and CK: Deep- and non-deep-tillage cultivated wheat RS groups, respectively.</p>
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<p>Antibiotic resistance ontology (ARO) composition and abundance. (<b>a</b>) ARO abundance in the rhizosphere soil of deep-tillage cultivated wheat; (<b>b</b>) ARO composition and (<b>c</b>) difference in both groups. * represented 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05, ** represented 0.001 &lt; <span class="html-italic">p</span> ≤ 0.01, *** represented <span class="html-italic">p</span> ≤ 0.001. DT and CK: Deep- and non-deep-tillage cultivated wheat RS groups, respectively.</p>
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16 pages, 3428 KiB  
Article
Regulation of the Rhizosphere Microenvironment by Arbuscular Mycorrhizal Fungi to Mitigate the Effects of Cadmium Contamination on Perennial Ryegrass (Lolium perenne L.)
by Fan Yang, Jinji Han, Ruizhu Lin, Yuan Yin, Xiaoxia Deng, Yueming Li, Jixiang Lin and Jinghong Wang
Microorganisms 2024, 12(11), 2335; https://doi.org/10.3390/microorganisms12112335 (registering DOI) - 15 Nov 2024
Viewed by 281
Abstract
Rhizosphere microorganisms are crucial for enhancing plant stress resistance. Current studies have shown that Arbuscular mycorrhizal fungi (AMF) can facilitate vegetation recovery in heavy metal-contaminated soils through interactions with rhizosphere microbiota. However, the mechanisms by which AMF influences rhizosphere microbiota and plant growth [...] Read more.
Rhizosphere microorganisms are crucial for enhancing plant stress resistance. Current studies have shown that Arbuscular mycorrhizal fungi (AMF) can facilitate vegetation recovery in heavy metal-contaminated soils through interactions with rhizosphere microbiota. However, the mechanisms by which AMF influences rhizosphere microbiota and plant growth under cadmium (Cd) stress remain unclear. In this study, Lolium perenne L. was inoculated with AMF (Rhizophagus irregularis) and grown in soils supplemented with Cd (0 mg kg−1, Cd0; 100 mg kg−1, Cd100). Plant biomass, antioxidant enzyme activities, peroxide content, Cd uptake, and rhizosphere bacterial community composition were evaluated. AMF inoculation reduced Cd influx in aboveground tissues, enhanced nutrient availability in the rhizosphere, and mitigated Cd biotoxicity. Additionally, AMF inoculation improved the scavenging efficiency of reactive oxygen species and alleviated oxidative stress in L. perenne, thereby mitigating biomass reduction. Moreover, AMF treatment increased leaf and root biomass by 342.94% and 41.31%, respectively. Furthermore, under the same Cd concentration, AMF inoculation increased bacterial diversity (as measured by the Shannon index) and reduced bacterial enrichment (as indicated by the ACE index). AMF promoted the enrichment of certain bacterial genera (e.g., Proteobacteria and Actinobacteria) in the Cd100 group. These findings suggest that AMF regulated the composition of the rhizosphere bacterial community and promoted the growth of potentially beneficial microorganisms, thereby enhancing the resistance of L. perenne to Cd stress. Cd contamination in soil severely limits plant growth and threatens ecosystem stability, highlighting the need to understand how AMF and rhizosphere microbes can enhance Cd tolerance in L. perenne. Therefore, inoculating plants with AMF is a promising strategy for enhancing their adaptability to Cd-contaminated soils. Full article
16 pages, 6754 KiB  
Article
The Synergistic Impact of a Novel Plant Growth-Promoting Rhizobacterial Consortium and Ascophyllum nodosum Seaweed Extract on Rhizosphere Microbiome Dynamics and Growth Enhancement in Oryza sativa L. RD79
by Pisit Thamvithayakorn, Cherdchai Phosri, Louisa Robinson-Boyer, Puenisara Limnonthakul, John H. Doonan and Nuttika Suwannasai
Agronomy 2024, 14(11), 2698; https://doi.org/10.3390/agronomy14112698 (registering DOI) - 15 Nov 2024
Viewed by 263
Abstract
This study investigated the combined effects of novel plant growth-promoting rhizobacteria (PGPR)—Agrobacterium pusense NC2, Kosakonia oryzae WN104, and Phytobacter sp. WL65—and Ascophyllum nodosum seaweed extract (ANE) as biostimulants (PGPR-ANE) on rice growth, yield, and rhizosphere bacterial communities using the RD79 cultivar. The [...] Read more.
This study investigated the combined effects of novel plant growth-promoting rhizobacteria (PGPR)—Agrobacterium pusense NC2, Kosakonia oryzae WN104, and Phytobacter sp. WL65—and Ascophyllum nodosum seaweed extract (ANE) as biostimulants (PGPR-ANE) on rice growth, yield, and rhizosphere bacterial communities using the RD79 cultivar. The biostimulants significantly enhanced plant growth, shoot and root length, and seedling vigour; however, seed germination was not affected. In pot experiments, biostimulant application significantly increased the richness and evenness of bacterial communities in the rhizosphere, resulting in improvements in rice growth and yield, with increases in plant height (9.6–17.7%), panicle length (14.3–17.9%), and seeds per panicle (48.0–53.0%). Notably, biostimulant treatments also increased post-harvest soil nutrient levels, with nitrogen increasing by 7.7–19.2%, phosphorus by 43.4–161.4%, and potassium by 16.9–70.4% compared to the control. Principal coordinate analysis revealed distinct differences in bacterial composition between the tillering and harvesting stages, as well as between biostimulant treatments and the control. Beneficial bacterial families, including Xanthobacteraceae, Beijerinckiaceae, Acetobacteraceae, Acidobacteriaceae, and Hyphomicrobiaceae, increased in number from the tillering to harvesting stages, likely contributing to soil health improvements. Conversely, methanogenic bacterial families, such as Methanobacteriaceae and Methanosarcinaceae, decreased in number compared to the control. These findings highlight the dynamic responses of the rhizosphere microbiome to biostimulant treatments and underscore their potential benefits for promoting sustainable and productive agriculture. Full article
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Figure 1
<p>Alpha-diversity analyses of three biostimulant treatments, ANE, PGPR, and PGPR-ANE, along with control, during both tillering (S1) and harvesting (S2) stages using Chao1 (<b>A</b>,<b>B</b>) and Shannon (<b>C</b>,<b>D</b>) indices. (<b>A</b>,<b>C</b>) Analysis of each stage and treatment separately. (<b>B</b>,<b>D</b>) Combined analysis of both stages within each treatment.</p>
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<p>The relative abundances of PGPR-associated and methanogenic bacterial families in rhizosphere soils compared across the three biostimulant treatments, ANE, PGPR, and PGPR-ANE, as well as the control (UI), during both the tillering (S1) and harvesting (S2) stages.</p>
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<p>Comparative microbial community in rice rhizosphere soil across growth stages and treatments. (<b>A</b>) PCoA of microbial communities at tillering and harvesting stages. (<b>B</b>) PCoA of microbial communities by treatment at tillering stage (S1) and harvesting stage (S2). (<b>C</b>,<b>D</b>) LEfSe analysis highlighting differential abundances of taxa across treatments at tillering (S1) and harvesting (S2) stages. (<b>E</b>,<b>F</b>) Venn diagram of shared and unique families at tillering (S1) and harvesting (S2) stages across treatments.</p>
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21 pages, 6767 KiB  
Article
Dynamics of Arbuscular Mycorrhizal Fungi in the Rhizosphere of Medicinal Plants and Their Promotion on the Performance of Astragalus mongholicus
by Wanyi Zhang, Chao He, Yuli Lin, Shenghui Qin, Duo Wang, Chunmiao Li, Min Li, Xiang Sun and Xueli He
Agronomy 2024, 14(11), 2695; https://doi.org/10.3390/agronomy14112695 (registering DOI) - 15 Nov 2024
Viewed by 221
Abstract
Arbuscular mycorrhizal fungi (AMF) act as intermediaries between the root systems of host plants and the surrounding soil, offering various benefits to medicinal plants, such as promoting growth and enhancing quality. However, the host range of AMF in medicinal plants and the characteristics [...] Read more.
Arbuscular mycorrhizal fungi (AMF) act as intermediaries between the root systems of host plants and the surrounding soil, offering various benefits to medicinal plants, such as promoting growth and enhancing quality. However, the host range of AMF in medicinal plants and the characteristics of plant–AMF networks in farmland ecosystems remain insufficiently studied. In the present study, we measured AMF colonization, species diversity, and soil properties of 31 medicinal plants at the Anguo Medicine Planting Base in Northwest China. The medicinal plant–AMF network was subsequently analyzed, and the growth-promoting effects of AMF on Astragalus mongholicus were examined. Spore density, species richness, and total colonization exhibited significant variation across different medicinal plant species. Glomus melanosporum, G. claroideum, and Septoglomus constrictum were the dominant species among 61 AMF species. Soil organic matter, phosphatase, available nitrogen, and glomalin-related soil proteins (GRSPs) were the main factors affecting the AMF composition. Structural equation models and a variation partitioning analysis suggested a highly plant species-specific pattern of AMF distribution patterns, where the host identities explained 61.4% of changes in spore density and 48.2% of AMF colonization. The soil nutrient availability and phosphatase activity also influenced AMF colonization. Our results confirmed glomalin as an important contributor to the soil carbon in farmland for cultivating medicinal plants. The medicinal plant–AMF symbiotic network exhibited highly nested patterns, a low specialized structure, high connectance, and low modularity, which suggested saturated AMF colonization and symbiosis stability provided by redundant plant–AMF associations. Despite the wide host range among medicinal plants, AMF inoculation revealed species-specific effects on the growth performance and active ingredient content levels in A. mongholicus, G. claroideum and Sep. constrictum induced the highest biomass and active ingredient content accumulation in A. mongholicus. These findings advance our understanding of AMF community dynamics in the rhizosphere of medicinal plants and offer valuable insights for optimizing medicinal plant cultivation practices. Full article
(This article belongs to the Section Horticultural and Floricultural Crops)
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Figure 1
<p>Arbuscular mycorrhizal fungal (AMF) colonization in roots of medicinal plants. H = AMF hyphae; V = AMF vesicular. (<b>a</b>) <span class="html-italic">Aristolochia contorta</span>, (<b>b</b>) <span class="html-italic">Atractylodes macrocephala</span>, (<b>c</b>) <span class="html-italic">Sedum sarmentosum</span>, (<b>d</b>) <span class="html-italic">Scutellaria barbata</span>, (<b>e</b>) <span class="html-italic">Mimosa pudica</span>, (<b>f</b>) <span class="html-italic">Hosta plantaginea</span>, (<b>g</b>) <span class="html-italic">Lilium davidii</span>, (<b>h</b>) <span class="html-italic">Linum perenne</span>, (<b>i</b>) <span class="html-italic">Paeonia suffruticosa</span>, (<b>j</b>) <span class="html-italic">Stemona japonica</span>, (<b>k</b>) <span class="html-italic">Rehmannia glutinosa</span>, (<b>l</b>) <span class="html-italic">Angelica dahurica</span>.</p>
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<p>Arbuscular mycorrhizal fungal (AMF) total colonization rate (%) in medicinal plant roots. Different letters above the error bars indicate significant differences.</p>
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<p>Relative abundance (%) of arbuscular mycorrhizal fungal (AMF) genus (<b>a</b>) and species (<b>b</b>) level in rhizosphere soil of medicinal plants.</p>
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<p>Differences in arbuscular mycorrhizal fungal (AMF) spore richness ((<b>a</b>), number of species) and the Simpson index (<b>b</b>) at the family level of medicinal plants. Different letters indicate significant differences.</p>
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<p>The relative contributions of plant species and soil factors were evaluated using a variation partitioning analysis on arbuscular mycorrhizal fungal (AMF) total colonization (<b>a</b>) and spore density (<b>b</b>). Values &lt; 0 are not shown.</p>
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<p>Structural equation model illustrating the causal connections between plant species, arbuscular mycorrhizal fungal (AMF) communities, and soil parameters. The final model fitted the data well, with the maximum likelihood, x<sup>2</sup> = 35.667, df = 13, <span class="html-italic">p</span> = 0.01, RMSEA = 0.138, GFI = 0.918, AIC = 81.667, and CFI = 0.905. Solid lines represent significant pathways, while dashed lines denote nonsignificant ones. The thickness of the solid lines corresponds to the strength of the causal effect, and the numbers adjacent to the arrows show the standardized path coefficients. “e” represents the residual values. TG: total extractable glomalin-related soil protein.</p>
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<p>The bipartite interaction network formed by medicinal plants (lower boxes) and arbuscular mycorrhizal fungal (AMF) spores. The colors of the different lower boxes represent different medicinal plants.</p>
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<p>The impacts of arbuscular mycorrhizal fungi (AMF) on the growth parameters of <span class="html-italic">Astragalus mongholicus</span> seedlings. Growth diagram (<b>a</b>), plant height (<b>b</b>), branch number (<b>c</b>), plant biomass (<b>d</b>), blade number (<b>e</b>), root length (<b>f</b>), Calycosin-7-glucoside (<b>g</b>), and formononetin (<b>h</b>). Different letters above the error bars indicate significant differences. CK, inoculated control; GM, <span class="html-italic">Glomus melanosporum</span>; GC, <span class="html-italic">Glmous. claroideum</span>; SC, <span class="html-italic">Septoglomus constrictum</span>.</p>
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19 pages, 3147 KiB  
Article
Deciphering the Effects of Phosphate Fertiliser on Rhizospheric Bacterial Community Structure and Potato Common Scab
by Shanshan Chen, Jingjing Cao, Pan Zhao, Zhiqin Wang, Xiu Wang, Genhong Liu and Naiqin Zhong
Microorganisms 2024, 12(11), 2322; https://doi.org/10.3390/microorganisms12112322 - 15 Nov 2024
Viewed by 224
Abstract
The prolonged practice of continuous potato cropping, coupled with inadequate field management, disrupts the soil bacterial community equilibrium. Such disturbances compromise the resilience of the soil ecosystem, predisposing it to an increased incidence of potato diseases. However, the effects of the phosphorus fertiliser [...] Read more.
The prolonged practice of continuous potato cropping, coupled with inadequate field management, disrupts the soil bacterial community equilibrium. Such disturbances compromise the resilience of the soil ecosystem, predisposing it to an increased incidence of potato diseases. However, the effects of the phosphorus fertiliser application rate on the rhizosphere soil bacterial community composition of potatoes and the occurrence of potato common scab (CS) have not been adequately studied. Here, diseased field soils from Dingxi and Huidong Counties were collected for potting tests, and field tests were conducted in Huidong County for validation. An examination of the relationship between the bacterial community composition in the potato rhizosphere soil and potato CS under different phosphate fertiliser treatments was conducted using 16S rRNA high-throughput sequencing. The results show that a lower phosphorus fertiliser application rate was more conducive to maintaining soil bacterial community diversity under different phosphorus fertiliser treatments in different habitats. In addition, the relative abundance of the txtA gene increased significantly (p < 0.05) with the increase in the phosphate fertiliser application rate. Field trials conducted in Huidong revealed that treatments F1, F2, and F3 had respective CS incidence rates of 28.33%, 46.67%, and 59.44%, while their corresponding disease severity indices were 7.67, 17.33, and 29.44. Further analysis revealed that the relative abundance of antagonistic genera of pathogenic S. scabies decreased significantly (p < 0.05) with increases in the phosphorus fertiliser application rate. In summary, the correlation between potato CS and changes in the bacterial community of rhizosphere soil was used to determine the optimal phosphorus application rate during potato production, which can provide a scientific basis for the management of phosphorus fertiliser in potato farmland. Full article
(This article belongs to the Special Issue Insights into Plant–Soil–Microbe Interactions)
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<p>The Venn diagrams (<b>a</b>–<b>c</b>) illustrate that lower phosphorus fertiliser application rates were beneficial for maintaining bacterial community diversity ((<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF). The graphs show the relative abundances of the bacterial community at the phylum level in the potato rhizosphere under different phosphorus fertiliser application rate conditions ((<b>d</b>) DXG, (<b>e</b>) HDG, and (<b>f</b>) HDF).</p>
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<p>PCA analysis of potato rhizosphere soil bacterial communities under different phosphate fertiliser rates ((<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF).</p>
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<p>Correlation between potato rhizosphere bacterial community and environmental factors with different phosphorus fertiliser application rates ((<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF). Green dots represent bacterial communities.</p>
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<p>Prediction of bacterial community function in potato rhizosphere soil under different phosphorus fertiliser application rates ((<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF).</p>
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<p>The relative abundance of <span class="html-italic">txtA</span> in pathogenic <span class="html-italic">Streptomyces</span> in potatoes under different phosphorus application rates and the incidence of potato CS in HDF. The relative abundances of <span class="html-italic">txtA</span> in (<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF; (<b>d</b>) the incidence of CS disease in HDF; (<b>e</b>) disease severity index in HDF; (<b>f</b>) plant height in DXG; (<b>g</b>) stem diameter in DXG; (<b>h</b>) SPAD in DXG; (<b>i</b>) plant height in HDG; (<b>j</b>) stem diameter in HDG; (<b>k</b>) SPAD in HDG. * Significant at <span class="html-italic">p</span> &lt; 0.05, ** significant at <span class="html-italic">p &lt;</span> 0.01, and *** significant at <span class="html-italic">p &lt;</span> 0.001.</p>
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<p>Phosphate fertiliser application rate effects on the abundance of antagonistic bacteria against <span class="html-italic">S. scabies</span>. (<b>a</b>) A pie chart depicting the distribution of major antagonistic bacterial genera in the potato rhizosphere. Stacked bar charts at the genus level showing the relative abundance of antagonistic bacteria ((<b>b</b>) DXG, (<b>c</b>) HDG, (<b>d</b>) HDF).</p>
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<p>Clustered heat map of relative abundances of the top 30 bacterial species at the species level ((<b>a</b>) DXG, (<b>b</b>) HDG, and (<b>c</b>) HDF). The green boxes mark the antagonistic bacteria and the blue boxes mark the pathogenic bacteria. The chromatograms, from red to blue, indicate a gradual decrease in the abundance of bacterial populations.</p>
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16 pages, 9149 KiB  
Article
Cd-Resistant Plant Growth-Promoting Rhizobacteria Bacillus siamensis R27 Absorbed Cd and Reduced Cd Accumulation in Lettuce (Lactuca sativa L.)
by Shaofang Liu, Yushan Huang, Qinyuan Zheng, Mengting Zhan, Zhihong Hu, Hongjie Ji, Du Zhu and Xia Zhao
Microorganisms 2024, 12(11), 2321; https://doi.org/10.3390/microorganisms12112321 - 15 Nov 2024
Viewed by 254
Abstract
The use of plant growth-promoting rhizobacteria (PGPR) for the bioremediation of heavy metal cadmium (Cd) and for enhancing plant growth in Cd-polluted soil is widely recognized as an effective approach. This study aimed to isolate Cd-resistant bacteria with plant growth-promoting (PGP) traits from [...] Read more.
The use of plant growth-promoting rhizobacteria (PGPR) for the bioremediation of heavy metal cadmium (Cd) and for enhancing plant growth in Cd-polluted soil is widely recognized as an effective approach. This study aimed to isolate Cd-resistant bacteria with plant growth-promoting (PGP) traits from the rhizosphere of vegetables subjected to metal contamination and to investigate the mechanisms associated with Cd adsorption as well as its impact on Cd uptake in lettuce. Six Cd-resistant bacterial strains were isolated from rhizosphere soil, among which the R27 strain exhibited the highest tolerance to Cd (minimum inhibitory concentration of 2000 mg/L) along with PGP traits, including phosphate solubilization (385.11 mg/L), the production of indole-3-acetic acid (IAA) (35.92 mg/L), and siderophore production (3.34 mg/L). Through a range of physiological, biochemical, and molecular assessments, the R27 strain was classified as Bacillus siamensis. This strain demonstrated notable efficiency in removing Cd2+ from the growth medium, achieving an efficacy of 80.1%. This removal was facilitated by cell surface adsorption through functional groups such as O–H, C=O, –CO–NH–, and C–O, alongside intracellular Cd accumulation, as evidenced by SEM, TEM, EDX, and FTIR analyses. Pot culture experiments indicated that R27 significantly promoted lettuce seedling growth and helped plants tolerate Cd stress, with the underlying mechanisms likely involving increased antioxidant activities for scavenging reactive oxygen species (ROS) induced by Cd stress, and reduced Cd2+ levels in lettuce seedlings to mitigate Cd2+ toxicity. These physiological changes were further supported by the down-regulation of genes associated with cadmium transport, including IRT1, Nramp1, HMA2, HMA4, ZIP4, and ZIP12, as well as the significantly reduced root bio-concentration factor (BCF) and translocation factor (TF). In summary, the R27 strain offers considerable potential in the bioremediation of Cd-polluted soils and can serve as a bio-fertilizer to enhance plant growth. Full article
(This article belongs to the Section Plant Microbe Interactions)
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<p>Phylogenetic relationships of 16S rRNA gene sequences of R27 strain.</p>
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<p>The removal effect of R27 on Cd<sup>2+</sup> (<span class="html-italic">n</span> = 3, mean ± standard deviation).</p>
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<p>SEM and TEM images and EDX elemental analysis of R27 strain under non-Cd and Cd stress conditions. (<b>A</b>,<b>B</b>) SEM image and EDX spectrum of R27 under non-Cd stress condition; (<b>C</b>,<b>D</b>) SEM image and EDX spectrum of R27 under Cd stress condition; (<b>E</b>,<b>F</b>) TEM image and EDX spectrum of R27 under non-Cd stress condition; (<b>G</b>,<b>H</b>) TEM image and EDX spectrum of R27 under Cd stress condition. The red arrows indicated the marking selection point for spectrum analysis.</p>
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<p>FTIR analysis diagram.</p>
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<p>Effects of the R27 strain on the growth of lettuce seedlings under non-Cd and Cd stress conditions. (<b>A</b>) Lettuce seedling growth characteristics; (<b>B</b>) the fresh weights of lettuce; (<b>C</b>) the dry weights of lettuce. Blue, red, green, and purple bars represent CK (water only), R27 (R27 inoculation alone), Cd (Cd stress only), and Cd + R27 (Cd stress in combination with R27 inoculation) treatments, respectively. Different letters indicate statistically significant differences between the four treatments (Duncan’s multiple range tests, <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">n</span> = 45, mean ± standard deviation).</p>
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<p>Effects of R27 on the chlorophyll contents of lettuce. Blue, red, green, and purple bars represent CK (water only), R27 (R27 inoculation alone), Cd (Cd stress only), and Cd + R27 (Cd stress in combination with R27 inoculation) treatments, respectively. Different letters indicate statistically significant differences between the four treatments (Duncan’s multiple range tests, <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">n</span> = 6, mean ± standard deviation).</p>
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<p>Effect of R27 strain on Cd content and Cd transport in lettuce. (<b>A</b>) The effects of R27 on the content of Cd; (<b>B</b>) the effects of R27 on the value of BCF and TF. Blue and red represent Cd (only Cd stress) and Cd + R27 (Cd stress + R27 inoculation) treatments. * Statistically significant differences (<span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">t</span>-test, <span class="html-italic">n</span> = 6, mean ± standard deviation).</p>
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<p>Effects of the R27 strain on the expression of genes related to Cd transport. Different letters indicate statistically significant differences between the four treatments (Duncan’s multiple range tests, <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">n</span> = 3, mean ± standard deviation).</p>
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<p>Effects of R27 on antioxidant activities and proline contents. (<b>A</b>) Effects of R27 on antioxidant activities of lettuce. Blue, red, green, and purple bars represent CK (only water), R27 (only R27 inoculation), Cd (only Cd stress), and Cd + R27 (Cd stress + R27 inoculation) treatments, respectively. (<b>B</b>) Effects of R27 on the contents of proline in plants. Different letters indicate statistically significant differences between the four treatments (Duncan’s multiple range tests, <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">n</span> = 6, mean ± standard deviation).</p>
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22 pages, 7222 KiB  
Article
Karst Ecosystem: Moso Bamboo Intercropping Enhances Soil Fertility and Microbial Diversity in the Rhizosphere of Giant Lily (Cardiocrinum giganteum)
by Jie Zhang, Haoyu Wu, Guibin Gao, Yuwen Peng, Yilin Ning, Zhiyuan Huang, Zedong Chen, Xiangyang Xu and Zhizhuang Wu
Forests 2024, 15(11), 2004; https://doi.org/10.3390/f15112004 - 13 Nov 2024
Viewed by 273
Abstract
Intercropping affects soil microbial community structure significantly; however, the effects on understory medicinal plants in karst areas remain unclear. We investigated the effects of four intercropping systems (Moso bamboo, Chinese fir, bamboo-fir mixed forest, and forest gap) on the rhizosphere microbial communities of [...] Read more.
Intercropping affects soil microbial community structure significantly; however, the effects on understory medicinal plants in karst areas remain unclear. We investigated the effects of four intercropping systems (Moso bamboo, Chinese fir, bamboo-fir mixed forest, and forest gap) on the rhizosphere microbial communities of giant lily (Cardiocrinum giganteum), an economically important medicinal plant in China. We assessed the intercropping impact on rhizosphere microbial diversity, composition, and co-occurrence networks and identified key soil properties driving the changes. Bacterial and fungal diversity were assessed by 16S rRNA and ITS gene sequencing, respectively; soil physicochemical properties and enzyme activities were measured. Moso bamboo system had the highest fungal diversity, with relatively high bacterial diversity. It promoted a distinct microbial community structure with significant Actinobacteria and saprotrophic fungi enrichment. Soil organic carbon, total nitrogen, and available potassium were the most influential drivers of microbial community structure. Co-occurrence network analysis revealed that the microbial network in the Moso bamboo system was the most complex and highly interconnected, with a higher proportion of positive interactions and a greater number of keystone taxa. Thus, integrating Moso bamboo into intercropping systems can enhance soil fertility, microbial diversity, and ecological interactions in the giant lily rhizosphere in karst forests. Full article
(This article belongs to the Special Issue Ecological Research in Bamboo Forests)
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<p>Soil physicochemical properties in the giant lily rhizosphere under different intercropping systems: (<b>a</b>) total organic carbon (TOC), (<b>b</b>) total nitrogen (TN), (<b>c</b>) total phosphorus (TP), (<b>d</b>) available nitrogen (AN), (<b>e</b>) available phosphorus (AP), (<b>f</b>) available potassium (AK), (<b>g</b>) pH, (<b>h</b>) β-D-glucosidase (BDG), (<b>i</b>) acid phosphatase (ACP), (<b>j</b>) N-acetyl-β-D-glucosaminidase (NAG), and (<b>k</b>) leucine aminopeptidase (LAP). Error bars represent standard deviations (n = 5). Different lowercase letters indicate significant differences among systems (LSD post hoc test, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Amplicon Sequence Variant (ASV) richness of (<b>a</b>) bacteria and (<b>b</b>) fungi in the giant lily rhizosphere under different intercropping systems; blue circles indicate shared taxa across systems; grey circles indicate non-shared ASVs; black bars indicate the number of shared taxa.</p>
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<p>Alpha diversity indices of (<b>a</b>–<b>c</b>) bacterial and (<b>d</b>–<b>f</b>) fungal communities in the giant lily rhizosphere under different intercropping systems. Lowercase letters indicate significant differences among systems (<span class="html-italic">p</span> = 0.05).</p>
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<p>Principal coordinate analysis (PCoA) and analysis of similarities (ANOSIM) tests of (<b>a</b>,<b>b</b>) bacterial and (<b>c</b>,<b>d</b>) fungal communities in the giant lily rhizosphere under different intercropping systems.</p>
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<p>Composition and linear discriminant analysis effect size (LEfSe) analysis of bacterial and fungal communities in the giant lily rhizosphere under different intercropping systems. (<b>a</b>,<b>b</b>) Relative abundance at the phylum level; (<b>c</b>,<b>d</b>) LEfSe results (phylum to genus level).</p>
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<p>Redundancy analysis (RDA) of (<b>a</b>) bacterial and (<b>b</b>) fungal communities in the giant lily rhizosphere under different intercropping systems.</p>
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<p>Functional predictions and correlations with dominant phyla for (<b>a</b>) bacterial functional annotation of prokaryotic taxa (FAPROTAX) and (<b>b</b>) fungal functional guilds (FUNGuild) in the giant lily rhizosphere under different intercropping systems. (<b>c</b>) Correlation analysis between dominant functional groups and dominant bacterial phyla. Asterisks indicate significance levels: * (0.01&lt; <span class="html-italic">p</span> ≤ 0.05), ** (0.001&lt; <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>Co-occurrence networks of bacterial and fungal communities in the giant lily rhizosphere under different intercropping systems: (<b>a</b>,<b>e</b>) bamboo–giant lily, (<b>b</b>,<b>f</b>) Chinese fir–giant lily, (<b>c</b>,<b>g</b>) Moso bamboo–giant lily, and (<b>d</b>,<b>h</b>) forest gap–giant lily intercropping.</p>
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<p>Co-occurrence networks of bacterial and fungal communities in the giant lily rhizosphere under different intercropping systems: (<b>a</b>,<b>e</b>) bamboo–giant lily, (<b>b</b>,<b>f</b>) Chinese fir–giant lily, (<b>c</b>,<b>g</b>) Moso bamboo–giant lily, and (<b>d</b>,<b>h</b>) forest gap–giant lily intercropping.</p>
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14 pages, 4381 KiB  
Article
Enhancing Photosynthetic Carbon Transport in Rice Plant Optimizes Rhizosphere Bacterial Community in Saline Soil
by Weiwei Zhang, Shunying Yang, Tianqi Wei and Yanhua Su
Int. J. Mol. Sci. 2024, 25(22), 12184; https://doi.org/10.3390/ijms252212184 - 13 Nov 2024
Viewed by 247
Abstract
Saline soils exert persistent salt stress on plants that inhibits their ability to carry out photosynthesis and leads to photosynthetic carbon (C) scarcity in plant roots and the rhizosphere. However, it remains unclear how a rhizosphere environment is shaped by photosynthetic C partitioning [...] Read more.
Saline soils exert persistent salt stress on plants that inhibits their ability to carry out photosynthesis and leads to photosynthetic carbon (C) scarcity in plant roots and the rhizosphere. However, it remains unclear how a rhizosphere environment is shaped by photosynthetic C partitioning under saline conditions. Given that sucrose is the primary form of photosynthetic C transport, we, respectively, created sucrose transport distorted (STD) and enhanced (STE) rice lines through targeted mutation and overexpression of the sucrose transporter gene OsSUT5. This approach allowed us to investigate different scenarios of photosynthate partitioning to the rhizosphere. Compared to the non-saline soil, we found a significant decrease in soil dissolved organic carbon (DOC) in the rhizosphere, associated with a reduction in bacterial diversity when rice plants were grown under moderate saline conditions. These phenomena were sharpened with STD plants but were largely alleviated in the rhizosphere of STE plants, in which the rhizosphere DOC, and the diversity and abundances of dominant bacterial phyla were measured at comparable levels to the wildtype plants under non-saline conditions. The complexity of bacteria showed a greater level in the rhizosphere of STE plants grown under saline conditions. Several salt-tolerant genera, such as Halobacteroidaceae and Zixibacteria, were found to colonize the rhizosphere of STE plants that could contribute to improved rice growth under persistent saline stresses, due to an increase in C deposition. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>Different soil DOC levels affect bacterial abundance and α-diversity. (<b>a</b>) Soil (DOC) dissolved organic carbon level of WT plants under control or saline conditions; (<b>b</b>) telative abundance of bacterial phyla (<b>a</b>) and alpha diversity analyses, as well as Shannon (<b>c</b>) in rhizosphere and bulk bacteria of WT rice plants. One-way ANOVA; *: <span class="html-italic">p</span> ≤ 0.05; ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>Rhizosphere bacterial community response to different carbon allocation and deposition conditions. Net photosynthetic rate (<b>a</b>), stomatal conductance (<b>b</b>), leaf sucrose content (<b>c</b>), root sucrose content (<b>d</b>), and soil dissolved organic carbon (DOC, (<b>e</b>)) of WT, STD, and STE under control or NaCl treatment. Relative abundance of bacterial phyla (<b>f</b>) and alpha diversity analysis as well as Shannon (<b>g</b>) in rhizosphere and bulk bacteria of STD or STE rice plants. The principal coordinate analysis (PCoA) shows microbial community dissimilarity (Bray−Curtis distance) among rhizosphere samples from the three different sucrose transporting circumstances under control ((<b>h</b>), R<sup>2</sup> = 0.6329, <span class="html-italic">p</span> = 0.001) or salt stress ((<b>i</b>), R<sup>2</sup> = 0.6883, <span class="html-italic">p</span> = 0.001). One-way ANOVA; *: <span class="html-italic">p</span> ≤ 0.05; **: <span class="html-italic">p</span> ≤ 0.01; ***: <span class="html-italic">p</span> ≤ 0.001; ****: <span class="html-italic">p</span> ≤ 0.0001; ns: <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>Carbon deposition conditions affect bacterial enrichments. Volcano plots show enrichment and depletion patterns in rhizosphere microbes between STD and STE under control (<b>a</b>) or NaCl treatments (<b>b</b>).</p>
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<p>Community change in differential abundance analysis (DAA). Dot plot showing the abundance of enriched and depleted rhizosphere ASVs of control (<b>a</b>) and NaCl (<b>b</b>) treatment across native, STD, and STE groups. Color intensity corresponds to the relative abundance of specific ASVs. F/P: functional/pathogen microbes, G/S: generalist/specialist, Un: unclassified.</p>
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<p>Enhanced carbon deposition positively contributes to bacterial network interactions. Visualization of constructed networks in STD and STE under control (<b>a</b>,<b>b</b>) and NaCl treatment (<b>c</b>,<b>d</b>). Different modules are shown in different colors.</p>
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<p>Differential bacteria correlate to environmental correlations and the sucrose transport engineering model. (<b>a</b>) Top 10 most abundant taxa in the DAA analyses and their environmental preferences (e.g., positive or negative). (<b>b</b>) PLS-PM of the drivers of sucrose content. Defense enzyme activities include CAT, SOD, and POD activities. Soil available nutrient included soil NH<sub>4</sub><sup>+</sup>−N, AK, and AP. Each oblong box represents a latent variable, which was chosen according to the correlations among these indicators. Path coefficients were calculated after 1000 bootstraps. The black and red lines represent positive and negative effects, respectively. The full and dashed lines indicate the significant correlations (<span class="html-italic">p</span> &lt; 0.05) and no correlations (<span class="html-italic">p</span> &gt; 0.05), respectively. (<b>c</b>) Model of sucrose transporting affects the rhizosphere micro-ecosystem and bacterial community. DOC: dissolved organic carbon; NH<sub>4</sub><sup>+</sup>−N and NO<sub>3</sub><sup>−</sup>−N: available nitrogen content; AK: available potassium content; AP: available phosphorus content. Significance level: **: <span class="html-italic">p</span> ≤ 0.01; ***: <span class="html-italic">p</span> ≤ 0.001.</p>
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18 pages, 5510 KiB  
Article
Metabolomic Analysis of Specific Metabolites in Codonopsis pilosula Soil Under Different Stubble Conditions
by Fengbin Xu, Daiyu Qiu, Yurong Hu, Xianxian Chen, Zhonghu Li and Qian Li
Molecules 2024, 29(22), 5333; https://doi.org/10.3390/molecules29225333 - 13 Nov 2024
Viewed by 300
Abstract
To investigate the soil-specific metabolites of Codonopsis pilosula under different stubble management practices, this study analyzed differentially abundant metabolites in the rhizosphere soils of rotational (DS) and continuous (LS) cropping systems via liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based metabolomic approaches. The results revealed that [...] Read more.
To investigate the soil-specific metabolites of Codonopsis pilosula under different stubble management practices, this study analyzed differentially abundant metabolites in the rhizosphere soils of rotational (DS) and continuous (LS) cropping systems via liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based metabolomic approaches. The results revealed that 66 metabolites, including amino acids and their derivatives, nucleic acids, alcohols, organic acids, amines, fatty acids, purines, and sugars, were significantly different (p < 0.05) between the DS and LS groups. Under continuous cropping, the levels of amines, fatty acids, organic acids, and sugars in the rhizosphere soil were significantly greater (p < 0.05) than those under rotational cropping, whereas the levels of amino acids and their derivatives, nucleic acids, and purines and pyrimidines were significantly lower (p < 0.05). KEGG pathway enrichment analysis revealed that these differentially abundant metabolites were enriched in metabolic pathways such as amino acid metabolism (e.g., alanine, aspartate, and glutamate metabolism), carbon metabolism, the cAMP signaling pathway, ABC transporter proteins, phenylalanine metabolism, and the biosynthesis of plant secondary metabolites. These metabolic pathways were involved in osmoregulation, energy supply, and resilience in plants. In conclusion, inter-root soil metabolites in rotational and continuous cropping of Codonopsis pilosula were able to influence soil physicochemical properties and microbial populations by participating in various biological processes. Full article
(This article belongs to the Special Issue Analytical Chemistry in Agriculture Application: 2nd Edition)
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<p>Multivariate analysis of the interroot soil metabolomic data of Radix et Rhizoma ginseng via LC–MS. (<b>a</b>,<b>b</b>): Principal component analysis (PCA) of the metabolomes of six continuous soil samples, six rotational crop samples, and quality control (QC) samples in positive (+) and negative (−) ion modes. (<b>c</b>,<b>d</b>): Partial least squares discriminant analysis (PLS-DA) in positive (+) and negative (−) ion modes, respectively. (<b>e</b>,<b>f</b>): Results of the permutation test for the PLS-DA model in positive (+) and negative (−) ion modes, respectively.</p>
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<p>(<b>a</b>) Top 10 compounds with significantly upregulated differentially abundant metabolites. (<b>b</b>) Top 10 compounds with significantly downregulated differentially abundant metabolites. (<b>c</b>) Z-score plot. (<b>d</b>) Base peak chromatogram of typical soil samples in positive ion mode. (<b>e</b>) Base peak chromatogram of typical soil samples in negative ion mode. When <span class="html-italic">p</span> value &lt; 0.05 and <span class="html-italic">p</span> value &gt; 0.01, it is displayed as *; when <span class="html-italic">p</span> value &lt; 0.01 and <span class="html-italic">p</span> value &gt; 0.001, it is displayed as **.</p>
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<p>(<b>a</b>) Top 10 compounds with significantly upregulated differentially abundant metabolites. (<b>b</b>) Top 10 compounds with significantly downregulated differentially abundant metabolites. (<b>c</b>) Z-score plot. (<b>d</b>) Base peak chromatogram of typical soil samples in positive ion mode. (<b>e</b>) Base peak chromatogram of typical soil samples in negative ion mode. When <span class="html-italic">p</span> value &lt; 0.05 and <span class="html-italic">p</span> value &gt; 0.01, it is displayed as *; when <span class="html-italic">p</span> value &lt; 0.01 and <span class="html-italic">p</span> value &gt; 0.001, it is displayed as **.</p>
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<p>(<b>a</b>) Top 10 compounds with significantly upregulated differentially abundant metabolites. (<b>b</b>) Top 10 compounds with significantly downregulated differentially abundant metabolites. (<b>c</b>) Z-score plot. (<b>d</b>) Base peak chromatogram of typical soil samples in positive ion mode. (<b>e</b>) Base peak chromatogram of typical soil samples in negative ion mode. When <span class="html-italic">p</span> value &lt; 0.05 and <span class="html-italic">p</span> value &gt; 0.01, it is displayed as *; when <span class="html-italic">p</span> value &lt; 0.01 and <span class="html-italic">p</span> value &gt; 0.001, it is displayed as **.</p>
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<p>Heatmap of cluster analysis of differentially abundant metabolites in two interrooted soil samples of <span class="html-italic">Codonopsis pilosula</span> (rotational cropping (DS) and continuous cropping (LS)).</p>
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<p>Metabolite–metabolite correlation analysis. Positive correlations are shown in red; negative correlations are shown in blue.</p>
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<p>Top 30 enriched KEGG pathways from differentially accumulated metabolites (DAMs) identified between DS and LS.</p>
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6 pages, 1267 KiB  
Proceeding Paper
Characterization of Potential Chalky Soil Bacteria Isolated from Rhizosphere of Acacia spp. Growing in Abardae, Maekel Region of Eritrea
by Zekarias A. Asfha, Yulia Kocharovskaya, Nataliya E. Suzina, Tatiana N. Abashina, Valentina N. Polivtseva, Yanina Delegan and Inna P. Solyanikova
Eng. Proc. 2024, 67(1), 76; https://doi.org/10.3390/engproc2024067076 - 12 Nov 2024
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Abstract
The current study was carried out to characterize chalky soil bacteria obtained from the rhizosphere of Acacia species growing in Abardae, Maekel Region of Eritrea. This study collected three chalky soil samples from the rhizosphere of Acacia ethibica, Acacia origena, and [...] Read more.
The current study was carried out to characterize chalky soil bacteria obtained from the rhizosphere of Acacia species growing in Abardae, Maekel Region of Eritrea. This study collected three chalky soil samples from the rhizosphere of Acacia ethibica, Acacia origena, and non-rhizospheric soil. The samples contained 1.42 × 1010, 5.35 × 109, and 5.68 × 107 cfu/g of culturable bacteria, respectively. A total of 80 bacterial strains were isolated, with ten selected for further study based on their distinct morphology. The researchers examined the cell morphology and the antimicrobial and plant growth-promoting activity of the chosen bacterial isolates. The study’s findings identified that the aerial mycelium of the strain EAE-1 displayed a unique and previously unreported arrangement of hyphae-bearing spores. The antimicrobial test results also showed that bacterial strains EAE-1, EAE-3, EAE-14, EAE-15, EAE-40, and EAO-24 displayed a wide range of antimicrobial activity against the examined phytopathogens. Furthermore, the seed germination result showed that the majority of bacterial strains had a positive effect on wheat growth, with strains EAE-40 and EAO-17 particularly enhancing maize growth. To sum up, the substantial capabilities of these strains position them as promising candidates for biotechnological applications. This study also represents the preliminary analysis of the microbial composition of Eritrean soil. Full article
(This article belongs to the Proceedings of The 3rd International Electronic Conference on Processes)
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<p>The microscopy cell morphology of bacterial isolate EAE-1. Scale bar is 10 µm.</p>
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<p>Growth promotion effect of bacterial isolates on the germination rate, shoot length, root length, and fresh weight of wheat (<b>a</b>) and maize (<b>b</b>). The error bars represent the least significant difference among. treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Growth promotion effect of bacterial isolates on the germination rate, shoot length, root length, and fresh weight of wheat (<b>a</b>) and maize (<b>b</b>). The error bars represent the least significant difference among. treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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Article
Atractylodes macrocephala Root Rot Affects Microbial Communities in Various Root-Associated Niches
by Huiyan Fan, Jiayi Han, Xiujuan Li, Jingzhi Zhou, Limei Zhao, Yiling Ying and Guoyin Kai
Agronomy 2024, 14(11), 2662; https://doi.org/10.3390/agronomy14112662 - 12 Nov 2024
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Abstract
Atractylodes macrocephala, a perennial herb widely used in traditional Chinese medicine, is highly prone to root rot, which significantly reduces its yield and quality. This study compared the physicochemical properties of soil from healthy and diseased A. macrocephala plants and analyzed the [...] Read more.
Atractylodes macrocephala, a perennial herb widely used in traditional Chinese medicine, is highly prone to root rot, which significantly reduces its yield and quality. This study compared the physicochemical properties of soil from healthy and diseased A. macrocephala plants and analyzed the microbial diversity in the endophytic, rhizosphere, and root zone soils. The results showed that the diseased plants had higher levels of available potassium and electrical conductivity in the rhizosphere, both positively correlated with the severity of root rot, while soil pH was negatively correlated. The diversity and richness of endophytic bacterial and fungal communities were significantly reduced in diseased plants. Additionally, root rot led to major changes in the rhizosphere microbial community, with an increased abundance of Proteobacteria and Ascomycota, and a decrease in Firmicutes, Bacteroidetes, Actinobacteria, and Basidiomycota. Fusarium oxysporum, Fusarium solani, and Fusarium fujikuroi were identified as key pathogens associated with root rot. This study enhances our understanding of the microbial interactions in soils affected by root rot, offering a foundation for developing soil improvement and biological control strategies to mitigate this disease in A. macrocephala cultivation. Full article
(This article belongs to the Special Issue Molecular Advances in Crop Protection and Agrobiotechnology)
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<p>Beta diversity analysis. (<b>A</b>): (a) Principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity matrices illustrating the effects of compartment niches and root rot disease on bacterial community structure in the endosphere, rhizosphere, and bulk soil microbiomes. (b): Venn diagram displaying the shared and unique OTUs in endosphere bacterial microbiomes. (<b>B</b>): (a) Principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity matrices illustrating the effects of compartment niches and root rot disease on fungal community structure in the endosphere, rhizosphere, and bulk soil microbiomes. (b): Venn diagram displaying the shared and unique OTUs in endosphere fungal microbiomes.</p>
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<p>Relative abundance of different phyla/genera in different samples. (<b>A</b>): (a) Relative abundance of bacterial phyla; (b) relative abundance of bacterial genera. (<b>B</b>): (a) Relative abundance of fungal phyla; (b) relative abundance of fungal genera.</p>
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<p>Kruskal–Wallis H test analysis of bacteria (<b>A</b>) and fungi (<b>B</b>) in the endosphere, rhizosphere, and bulk soil at the genus level. * <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.</p>
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<p>(<b>A</b>): Redundancy analysis (RDA) of the dominant bacterial genera, soil physicochemical properties, and rhizosphere. (<b>B</b>): RDA of the dominant fungal genera, soil physicochemical properties, and rhizosphere. OM: organic matter; AN: alkali-hydrolyzable nitrogen; AP: available phosphorus; AK: available potassium; EC: electric conductivity; H = healthy; M = moderately diseased; S = severely diseased; RS = rhizosphere.</p>
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<p>Isolation of three different potential pathogens (<span class="html-italic">Fusarium solani</span>, <span class="html-italic">Fusarium fujikuroi</span>, and <span class="html-italic">Fusarium oxysporum</span>) from diseased rhizomes. (<b>A</b>) Colony morphology, (<b>B</b>) Conidial morphology. Scale bar = 20 μm.</p>
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