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Topic Editors

Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Research Centre for Vegetable and Ornamental Crops, Corso degli Inglesi 508, 18038 Sanremo, Italy
CREA Research Centre for Vegetable and Ornamental Crops, Via dei Fiori 8, 51012 Pescia, Italy

Plant-Soil Interactions, 2nd Volume

Abstract submission deadline
30 September 2025
Manuscript submission deadline
31 December 2025
Viewed by
31231

Topic Information

Dear Colleagues,

Following the successful completion of Volume I of “Plant–Soil Interactions” and the great interest in this research topic, we are pleased to announce the launch of Volume II. Biological fertilizers are substances that contain microorganisms that, when applied to seeds, plant surfaces, or soil, colonize the rhizosphere and promote plant growth by increasing the supply of primary nutrients to the host plant. Research has shown that biofertilizers have different effects in various environments, and even within the same one. A number of scientists have been working on solving this problem, but no perfect solution has yet been found. Despite their satisfactory effects in drier climates, biofertilizers are likely to be better controlled and regulated in all environments in the future. Therefore, it is necessary to enhance knowledge on this subject. The aim of this Special Issue is therefore to promote research surrounding the use of microorganisms in improving plant growth and protection against biotic and abiotic stresses.

Dr. Fernando Monroy
Dr. Domenico Prisa
Topic Editors

Keywords

  • soil ecology
  • rhizosphere
  • mycorrhiza soil-borne pathogens
  • sustainable agriculture

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Agriculture
agriculture
3.3 4.9 2011 19.2 Days CHF 2600 Submit
Agronomy
agronomy
3.3 6.2 2011 17.6 Days CHF 2600 Submit
Crops
crops
- - 2021 22.1 Days CHF 1000 Submit
Diversity
diversity
2.1 3.4 2009 18.3 Days CHF 2100 Submit
Plants
plants
4.0 6.5 2012 18.9 Days CHF 2700 Submit

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Published Papers (18 papers)

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15 pages, 17298 KiB  
Article
Periodicity of Fruit Cracking in Orange Fruit and Integrated Management Intervention
by Xingjian Shi, Mingxia Wen, Zhihao Dong, Jiangzhou Zhang, Anoop Kumar Srivastava, Mohamed G. Moussa and Yueqiang Zhang
Plants 2025, 14(3), 389; https://doi.org/10.3390/plants14030389 - 27 Jan 2025
Viewed by 690
Abstract
Fruit cracking in citrus is one of the most researched constraints in crop management. However, researchers are still clueless even today on how to curtail this important production loss through an integrated management system. Our study introduces a management strategy for fruit cracking [...] Read more.
Fruit cracking in citrus is one of the most researched constraints in crop management. However, researchers are still clueless even today on how to curtail this important production loss through an integrated management system. Our study introduces a management strategy for fruit cracking in citrus by analyzing different production constraints. As many as 70 Bingtang orange (Citrus sinensis L. Osbeck cv. Bingtang) orchards in Xinping County were investigated to determine the intensity and periodicity of fruit cracking. The results indicated that citrus cracking was in a high incidence state during production in the past two years, accounting for 48.2–50.6% of fruit drop following the physiological premature drop period, particularly exacerbating in the year with irregular rainfall (from June to September). Among factors such as soil texture, soil fertility, and orchard management, the soil sand proportion, soil calcium, soil potassium, and soil magnesium content were the main factors contributing to the occurrence of fruit cracking, with contributions of 18.57%, 17.14%, 10.00%, and 8.75%, respectively. Fruit cracking was significantly positively correlated with soil magnesium content (0.802) and significantly negatively correlated with soil calcium (0.8007), potassium (0.7616), and soil sand proportion (0.7826). The integrated management treatment (organic fertilizer to improve soil + foliar nutrient supplementation) showed better control on fruit cracking by 9.34–65.25% and an increase in yield by 4.13–37.49%, respectively, compared to the supplementation of a single element in all orchards with different production and quality traits. Our findings could thus help citrus growers optimize cultivation techniques for quality citrus production under increasingly changing climatic conditions. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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Figure 1

Figure 1
<p>Fruit drop and related causes of Bingtang oranges in 2022 and 2023. (<b>A</b>) Fruit drop, where the blue color represents the 2022 fruit drop number, and the black line represents the 2023 fruit drop number; (<b>B</b>) the dropped fruit composition after the physiological premature drop in 2022; (<b>C</b>) the dropped fruit composition after the physiological premature drop in 2023.</p>
Full article ">Figure 1 Cont.
<p>Fruit drop and related causes of Bingtang oranges in 2022 and 2023. (<b>A</b>) Fruit drop, where the blue color represents the 2022 fruit drop number, and the black line represents the 2023 fruit drop number; (<b>B</b>) the dropped fruit composition after the physiological premature drop in 2022; (<b>C</b>) the dropped fruit composition after the physiological premature drop in 2023.</p>
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<p>Rainfall situation in recent years. (<b>A</b>) Average rainfall from 2019–2023; (<b>B</b>) rainfall in 2022; (<b>C</b>) rainfall in 2023.</p>
Full article ">Figure 2 Cont.
<p>Rainfall situation in recent years. (<b>A</b>) Average rainfall from 2019–2023; (<b>B</b>) rainfall in 2022; (<b>C</b>) rainfall in 2023.</p>
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<p>Number of cracked fruits in orchards in 2022 and 2023.</p>
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<p>The boundary line analysis between different soil trait factors and fruit cracking. The blue triangles represent the number of fruit cracks corresponding to different factors. The red dots indicate the maximum number of fruit cracks that can be generated under different factors.</p>
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<p>The explained cracking fruit gap for limiting factors, expressed as a percentage of the attained maximum cracking fruit in Bingtang orange orchards. The box boundaries indicate upper and lower quartiles, the whisker caps indicate 90th and 10th percentiles, and the points indicate the outliers.</p>
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<p>The effects of different treatments on controlling citrus cracking. Different lowercase letters indicate significant differences among different treatments at 5% level (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>The effects of different treatments on the yield of different citrus orchards. Different lowercase letters indicate significant differences among different treatments at 5% level (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Different soil trait factors identified from the boundary line analysis and their corresponding contribution (proportions) for citrus cracking.</p>
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20 pages, 5506 KiB  
Article
Response of Plant Community Characteristics and Soil Factors to Topographic Variations in Alpine Grasslands
by Qinyang Liang, Jinmei Zhao, Zixin Wang, Xingyi Wang, Dianxia Fu and Xiaogang Li
Plants 2025, 14(1), 63; https://doi.org/10.3390/plants14010063 - 28 Dec 2024
Viewed by 470
Abstract
Topography has an important influence on plant–soil relationships. However, research on plant–soil relationships in alpine grassland at the slope aspect and slope position scales is currently inadequate. In this paper, based on the topographic and geomorphological characteristics of the study area, alpine grassland [...] Read more.
Topography has an important influence on plant–soil relationships. However, research on plant–soil relationships in alpine grassland at the slope aspect and slope position scales is currently inadequate. In this paper, based on the topographic and geomorphological characteristics of the study area, alpine grassland with typical slope aspect and slope position conditions was selected as the research object. Through field investigations and laboratory research to reveal how the characteristics of the alpine grassland plant community and soil factors respond to changes in topography. The results show: Slope aspect and slope position changes significantly affect alpine grassland plant communities and soil properties. In terms of the dominant species in plant communities, the sunny slopes were dominated by Poaceae and the shady slopes were dominated by Polygonaceae. Plant community characterization variables showed a decreasing trend from shady to sunny slopes and bottom to top. The soil factors showed significant differences among the six types of topography (p < 0.05), and the magnitude order in different slope aspects and positions was basically shady slope > sunny slope and bottom > middle and top. Correlation analysis showed that there were good correlations between soil organic carbon (SOC), soil water content (SWC), total nitrogen (TN), pH, and plant community characteristics in alpine grassland. In addition, redundancy analyses (RDA) indicated that the divergence in plant community characteristics was primarily driven by the change difference in SOC along topographic gradients. Our findings may provide a scientific basis for the restoration and utilization of alpine grassland vegetation and the evaluation of the ecological environment in this region. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Sample plots layout map.</p>
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<p>Difference in α biodiversity index in different slope aspects and slope positions. Note: differences between topographies at the 0.05 level are indicated by lowercase letters.</p>
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<p>(<b>a</b>) Biomass characteristics of different topographies. Note: differences between topographies at the 0.05 level are indicated by lowercase letters. (<b>b</b>) Belowground biomass in 0–50 cm soil layers. Note: differences within the same soil depth but different topographies are represented by lowercase letters (<span class="html-italic">p</span> &lt; 0.05). AGB and BGB represent aboveground biomass and belowground biomass, respectively.</p>
Full article ">Figure 3 Cont.
<p>(<b>a</b>) Biomass characteristics of different topographies. Note: differences between topographies at the 0.05 level are indicated by lowercase letters. (<b>b</b>) Belowground biomass in 0–50 cm soil layers. Note: differences within the same soil depth but different topographies are represented by lowercase letters (<span class="html-italic">p</span> &lt; 0.05). AGB and BGB represent aboveground biomass and belowground biomass, respectively.</p>
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<p>Soil water content in different topographies. Note: Differences within the same soil depth but different topographies are represented by lowercase letters (<span class="html-italic">p</span> &lt; 0.05), the same as below.</p>
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<p>(<b>a</b>–<b>c</b>) Soil total nutrient content in different topographies.</p>
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<p>Soil available nutrient content in different topographies.</p>
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<p>Relationship between plant community characteristics and soil factors.</p>
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<p>Plant community characteristics and soil factors RDA ordination diagram. Note: plant community characteristics are indicated by blue solid arrows, and soil environmental factors are indicated by red hollow arrows.</p>
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16 pages, 11337 KiB  
Article
Renewal and Iteration Mechanisms of Aged Tea Trees: Insights from Tea Garden Soil Microbial Communities
by Houqiao Wang, Tianyu Wu, Wenxia Yuan, Lijiao Chen, Hongxu Li, Xiujuan Deng, Chun Wang, Weihao Liu, Wei Huang and Baijuan Wang
Agronomy 2024, 14(12), 2955; https://doi.org/10.3390/agronomy14122955 - 12 Dec 2024
Viewed by 929
Abstract
This study focuses on the renewal and iteration mechanisms of aged tea trees in interactions with their soil microbial communities, aiming to elucidate the impact of the planting age of tea trees on the structure and function of soil microbial communities and how [...] Read more.
This study focuses on the renewal and iteration mechanisms of aged tea trees in interactions with their soil microbial communities, aiming to elucidate the impact of the planting age of tea trees on the structure and function of soil microbial communities and how these impacts are linked to the formation of tea quality. By conducting a comparative analysis of the cultivation soil from tea trees with varying planting ages ranging from 30 to 200 years, we employed microbial diversity sequencing, a soil physicochemical property analysis, and tea leaf chemical component detection. We combined these methods with redundancy analysis (RDA) and linear discriminant analysis effect size (LEfSe) to reveal significant correlations between the planting age of tea trees and the soil’s microbial diversity and function. The results indicate that as the planting age of tea trees increases, there are significant changes in the soil’s pH and nutrient content. Concurrently, the components of the tea leaves also change. Most notably, around the 120 years mark of the tea tree planting age, the diversity of the soil microbial community reaches a turning point. Key microbial community analyses revealed shifts in the dominant microbial populations within the soil across the various tea tree planting ages, exemplified by taxa such as Hygrocybe Mycena, Humicola, Bradyrhizobium, and Candidatus Solibacter. These alterations in microbial communities are closely associated with soil nutrient dynamics and the developmental stages of tea trees. These findings not only provide scientific guidance for tea garden management, tea tree cultivation, and tea production but also offer new insights into the impact of tea tree–soil–microbe interactions on tea quality, which is significantly important for enhancing tea quality. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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Figure 1
<p>Tea plants at different planting ages and sampling locations.</p>
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<p>Variations in the soil pH (<b>a</b>), total nitrogen (<b>b</b>), total phosphorus (<b>c</b>), total potassium (<b>d</b>), alkali-hydrolyzable nitrogen (<b>e</b>), available phosphorus (<b>f</b>), available potassium (<b>g</b>), and soil organic matter (<b>h</b>) in tea tree cultivation soil with different planting ages.</p>
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<p>Changes in the water extract (WE) (<b>a</b>), tea polyphenol (TP) (<b>b</b>), amino acid (AA) (<b>c</b>), nitrogen (N) (<b>d</b>), phosphorus (P) (<b>e</b>), and potassium (K) (<b>f</b>) content in tea leaves from tea trees with different planting ages.</p>
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<p>The impact of the tea tree planting age on the alpha diversity of soil fungal and bacterial communities (<b>a</b>,<b>b</b>), and the PCoA showing the distribution of soil fungal and bacterial communities across the different planting ages (<b>c</b>,<b>d</b>); * indicates significant difference, <span class="html-italic">p</span> &lt; 0.05, ** indicates significant difference, <span class="html-italic">p</span> &lt; 0.01, no marking indicates no difference.</p>
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<p>Dendrogram of soil fungal and bacterial community structures, based on the UPGMA method, with (<b>a</b>) for fungi and (<b>b</b>) for bacteria.</p>
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<p>Distribution of the top 10 fungal (<b>a</b>) and bacterial (<b>b</b>) phyla in tea garden soil at different planting ages.</p>
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<p>LEfSe analysis depicting the evolutionary cladogram of the abundance changes of characteristic microbial fungi (<b>a</b>) and bacteria (<b>b</b>) in tea garden soil across the different planting ages.</p>
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<p>Functional analysis of key microbial communities in tea garden soil with different tea tree planting ages, with (<b>a</b>) representing fungi and (<b>b</b>) representing bacteria.</p>
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<p>RDA of the relationship between soil microbial community structure and soil properties, with (<b>a</b>) depicting fungi and (<b>b</b>) depicting bacteria.</p>
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11 pages, 1506 KiB  
Article
Abundance of Human Pathogenic Microorganisms in the Halophyte Salicornia europaea L.: Influence of the Chemical Composition of Shoots and Soils
by Matteo Marangi, Sonia Szymanska, Kai-Uwe Eckhardt, Felix Beske, Gerald Jandl, Katarzyna Hrynkiewicz, Julien Pétillon, Christel Baum and Peter Leinweber
Agronomy 2024, 14(11), 2740; https://doi.org/10.3390/agronomy14112740 - 20 Nov 2024
Viewed by 1064
Abstract
Salicornia europaea L. is a halophilic plant species belonging to Chenopodiaceae, whose shoots are used as a vegetable. Since the shoots can be eaten raw, the objective of the present study was to investigate possible controls on the abundance of human pathogenic microorganisms [...] Read more.
Salicornia europaea L. is a halophilic plant species belonging to Chenopodiaceae, whose shoots are used as a vegetable. Since the shoots can be eaten raw, the objective of the present study was to investigate possible controls on the abundance of human pathogenic microorganisms (HPMOs) in the shoots as a health risk. For this reason, the molecular-chemical composition of shoots, site-specific soil organic matter (bulk and rhizosphere), and soil pH and salinity were analyzed. Plant and soil samples were taken from two test sites with differing salinity levels in France (a young and an old marsh). We hypothesized that the chemical traits of plants and soils could suppress or promote HPMOs and, thus, serve as risk indicators for food quality. The chemical traits of shoots and bulk and rhizosphere soil were measured through thermochemolysis using gas chromatography/mass spectrometry (GC/MS). The densities of cultivable HPMOs (Salmonella enterica, Escherichia coli, and Listeria monocytogenes) were determined in plant shoots, rhizosphere soil, and bulk soil using selective media. Negative correlations between lignin content in the shoots and the abundance of S. enterica, as well as between lignin content in bulk soil and the abundance of E. coli, are explained by the lignin-based rigidity and its protective effect on the cell wall. In the shoot samples, the content of lipids was positively correlated with the abundance of E. coli. The abundance of E. coli, S. enterica, and L. monocytogenes in bulk soil decreased with increasing soil pH, which is linked to increased salinity. Therefore, soil salinity is proposed as a tool to decrease HPMO contamination in S. europaea and ensure its food safety. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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Figure 1
<p>Relative abundance (% peak area) of (<b>a</b>) carbohydrates, (<b>b</b>) lignin, and (<b>c</b>) lipids in shoots, rhizosphere soil, and bulk soil as mean values with standard deviation at an old, mature salt marsh (Old marsh) and a recently (2020) created salt marsh (Young marsh) in France. Different letters indicate significance of differences between samples.</p>
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<p>Correlation between (<b>a</b>) the log (CFU g<sup>−1</sup>) of <span class="html-italic">S. enterica</span> and the lignin (% Peak area) content in shoots of <span class="html-italic">S. europaea</span>; and (<b>b</b>) between the log (CFU g<sup>−1</sup>) of <span class="html-italic">E. coli</span> and the lipid (% Peak area) content in shoots of <span class="html-italic">S. europaea</span>. * means significance level of correlation coefficient is 0.05</p>
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<p>Correlation between the lignin content (% peak area) and the abundance of <span class="html-italic">E. coli</span> log (CFU g<sup>−1</sup>) (<b>a</b>), between the pH and <span class="html-italic">E. coli</span> log (CFU g<sup>−1</sup>) (<b>b</b>), between the pH value and <span class="html-italic">L. monocytogenes</span> log (CFU g<sup>−1</sup>) (<b>c</b>), and between the pH value and <span class="html-italic">S. enterica</span> log (CFU g<sup>−1</sup>) (<b>e</b>), and in the rhizosphere soil, between the colonisation density of <span class="html-italic">L. monocytogenes</span> log (CFU g<sup>−1</sup>) and the pH (<b>d</b>), and visualization of interdependencies between these data in a correlation network graph (<b>f</b>).</p>
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12 pages, 3652 KiB  
Article
Effects of the Radicle Sheath on the Rhizosphere Microbial Community Structure of Seedlings in Early Spring Desert Species Leontice incerta
by Xiaolan Xue and Jannathan Mamut
Agronomy 2024, 14(10), 2444; https://doi.org/10.3390/agronomy14102444 - 21 Oct 2024
Viewed by 739
Abstract
Most research on plant–microbe interactions emphasize the effects of micronutrients on the rhizosphere microbial community structure. However, the influence of seed structures, particularly the radicle sheath, on microbial diversity at the seedling root tips under varying temperatures and humidity has been less explored. [...] Read more.
Most research on plant–microbe interactions emphasize the effects of micronutrients on the rhizosphere microbial community structure. However, the influence of seed structures, particularly the radicle sheath, on microbial diversity at the seedling root tips under varying temperatures and humidity has been less explored. This study conducted controlled indoor experiments in the northern desert of Xinjiang to assess the radicle sheath’s impact on microbial community composition, diversity, and function. The results indicated no significant changes in the Chao1 index for bacteria and fungi, but notable differences were observed in the Shannon and Simpson indices (p < 0.05). Under drought conditions, the radicle sheath significantly reduced bacterial infections without affecting fungi. Genus-level analysis showed an increased abundance of specific dominant bacterial groups when the radicle sheath was retained. NMDS analysis confirmed its significant effect on both bacterial and fungal community structures. LEfSe analysis identified 34 bacterial and 15 fungal biomarkers, highlighting the treatment’s impacts on microbial taxonomic composition. Functional predictions using PICRUSt 2 revealed that the radicle sheath facilitated the conversion of CH4 to CH3OH and various nitrogen cycle processes under drought. Overall, the radicle sheath plays a crucial role in maintaining rhizosphere microbial community stability and enhancing the functions of both bacteria and fungi under drought conditions. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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Figure 1
<p>Study area. Note: The yellow dots in the figure indicate the four collection sites of <span class="html-italic">Leontice incerta</span> seeds.</p>
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<p>Taxonomic composition at the genus level for bacteria (<b>A</b>) and fungi (<b>B</b>) in the young roots of <span class="html-italic">Leontice incerta</span> seedlings. Note: different colors represent different microbial taxa.</p>
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<p>α-diversity indices for rhizosphere bacteria (<b>A</b>) and fungi (<b>B</b>) in the seedlings of <span class="html-italic">Leontice incerta.</span> Note: DTCF: dry treatment removes radicle sheath, DTCL: dry treatment retains radicle sheath, WTCF: wet treatment removes radicle sheath, and WTCL: wet treatment retains radicle sheath. * is the significance value of the post hoc test between the corresponding two groups.</p>
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<p>NMDS analysis of rhizosphere bacterial (<b>A</b>) and fungal (<b>B</b>) communities of <span class="html-italic">Leontice incerta</span> seedlings under different treatments. Note: DTCF: dry treatment removes radicle sheath, DTCL: dry treatment retains radicle sheath, WTCF: wet treatment removes radicle sheath, and WTCL: wet treatment retains radicle sheath.</p>
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<p>Venn analysis of bacterial (<b>A</b>) and fungal (<b>B</b>) communities in the rhizosphere of <span class="html-italic">Leontice incerta</span> seedlings under different treatments based on OUT levels. Note: each ellipse represents a treatment, and the number of shared OTUs between treatments is represented by the number of overlapping parts, while the number of non-overlapping parts represents the number of unique OTUs between treatments. DTCF: dry treatment removes radicle sheath, DTCL: dry treatment retains radicle sheath, WTCF: wet treatment removes radicle sheath, and WTCL: wet treatment retains radicle sheath.</p>
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<p>LEfSe difference analysis diagram of rhizosphere bacteria (<b>A</b>) fungi (<b>B</b>) community in <span class="html-italic">Leontice incerta</span> seedlings. Note: DTCF: dry treatment removes radicle sheath, DTCL: dry treatment retains radicle sheath, WTCF: wet treatment removes radicle sheath, and WTCL: wet treatment retains radicle sheath.</p>
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<p>Functional prediction of rhizosphere bacterial communities in <span class="html-italic">Leontice incerta</span> seedlings. Note: In the Figure, the horizontal axis is the abundance (per million KO/PWY/COG) or count of the functional pathway/classification; the vertical axis is the functional pathway/classification of the second classification level of KEGG/Meta Cyc/COG; and the rightmost axis is the first-level pathway/classification to which the pathway belongs. The average abundance of all selected samples or the count of all selected samples is displayed here. The Meta Cyc Super pathway is not displayed by default.</p>
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<p>C (<b>A</b>) and N (<b>B</b>) cycling of rhizosphere bacteria in the seedlings of <span class="html-italic">Leontice incerta</span>. Note: DTCF: dry treatment removes radicle sheath, DTCL: dry treatment retains radicle sheath, WTCF: wet treatment removes radicle sheath, and WTCL: wet treatment retains radicle sheath.</p>
Full article ">
19 pages, 4009 KiB  
Article
Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure
by Yixuan Chen, Sen Wang, Yuru Li, Wanyu Liu and Zhenchuan Niu
Agriculture 2024, 14(9), 1637; https://doi.org/10.3390/agriculture14091637 - 18 Sep 2024
Viewed by 1172
Abstract
This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C3 and C4 plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 [...] Read more.
This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C3 and C4 plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 were employed for functional predictions. Results showed significant differences between C3 and C4 plants in terms of bacterial community structure. C3 plants exhibited higher abundances of Proteobacteria, Bacteroidetes at the phylum level and Sphingomicrobium at the genus level, compared to C4 plants. Conversely, C4 plants had higher abundances of Actinobacteria and Patescibacteria at the phylum level and Nocardioides at the genus level. LEfSe and function prediction analyses revealed that the rhizosphere soil bacteria in C3 plants exhibited significantly higher enrichment in nitrogen fixation functions (p < 0.05), whereas C4 plants showed a significantly higher relative abundance of bacteria and functions related to organic pollutant degradation (p < 0.05). These findings suggest that the rhizosphere soil bacteria of C3 plants exhibit a stronger response to BTBPE exposure in nitrogen metabolism-related processes, while C4 plants possess superior biodegradation ability compared to C3 plants. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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Figure 1
<p>α-diversity of soil bacteria in the rhizosphere of different treatments. (<b>a</b>) Chao 1. (<b>b</b>) observed_species. (<b>c</b>) Phylogenetic Diversity (PD)_whole_tree. (<b>d</b>) Shannon. Different letters in the same column indicate significant difference (<span class="html-italic">p</span> &lt; 0.05) (CK1, BTBPE-contaminated soil without plant; SI, <span class="html-italic">Setaria italica</span> (L.) Beauv.; ZM, <span class="html-italic">Zea mays</span> L.; AT, <span class="html-italic">Amaranthus tricolor</span> L.; TA, <span class="html-italic">Triticum aestivum</span> L.; GM, <span class="html-italic">Glycine max</span> (L.) Merr.; MS, <span class="html-italic">Medicago sativa</span> L.; LP, <span class="html-italic">Lolium perenne</span> L.).</p>
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<p>Non-metric multidimensional scaling (NMDS) analysis and Partial Least Squares Discriminant Analysis (PLS-DA) of bacterial communities in rhizosphere soil of different treatments. Ellipses are used to compare the similarity of community structure composition between groups. (<b>a</b>) NMDS analysis of different plants. (<b>b</b>) NMDS analysis of C<sub>3</sub> and C<sub>4</sub> plants. (<b>c</b>) Partial Least Squares Discriminant Analysis (PLS-DA) of different plants. (<b>d</b>) Partial Least Squares Discriminant Analysis (PLS-DA) of C<sub>3</sub> and C<sub>4</sub> plants (CK1, BTBPE-contaminated soil without plant; SI, <span class="html-italic">Setaria italica</span> (L.) Beauv.; ZM, <span class="html-italic">Zea mays</span> L.; AT, <span class="html-italic">Amaranthus tricolor</span> L.; TA, <span class="html-italic">Triticum aestivum</span> L.; GM, <span class="html-italic">Glycine max</span> (L.) Merr.; MS, <span class="html-italic">Medicago sativa</span> L.; LP, <span class="html-italic">Lolium perenne</span> L.).</p>
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<p>Composition characteristics of bacterial phylum (<b>a</b>,<b>b</b>) and genus (<b>c</b>,<b>d</b>) in rhizosphere soil of different treatments (CK1 BTBPE-contaminated soil, SI <span class="html-italic">Setaria italica</span> (L.) Beauv., ZM <span class="html-italic">Zea mays</span> L., AT <span class="html-italic">Amaranthus tricolor</span> L., TA <span class="html-italic">Triticum aestivum</span> L., GM <span class="html-italic">Glycine max</span> (L.) Merr., MS <span class="html-italic">Medicago sativa</span> L., LP <span class="html-italic">Lolium perenne</span> L.).</p>
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<p>Evolutionary branch diagram of bacteria in rhizosphere soil of C<sub>3</sub> and C<sub>4</sub> plants based on LEfSe analysis. The circles radiating from the center represent taxonomic levels from phylum to genus (or species). Each small circle at different taxonomic levels represents a classification at that level, with the diameter of the circle proportional to its relative abundance. The coloring principle is as follows: species with no significant difference are uniformly colored to yellow, while biomarkers of the different species are colored according to their respective groups. Red nodes represent microbial groups that are significant in the red group, and the green nodes represent the microbial groups that are significant in the green group. Other circles follow the same color meaning. The species names represented by the English letters in the figure are displayed in the right legend.</p>
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<p>Difference analysis of FAPROTAX function prediction in soil bacterial communities in rhizosphere of C<sub>3</sub> and C<sub>4</sub> plants.</p>
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<p>Difference in functional prediction of PICRUSt 2 in soil bacterial communities in rhizosphere of C<sub>3</sub> and C<sub>4</sub> plants (KEGG level 2).</p>
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16 pages, 4344 KiB  
Article
Characteristics of Grassland Species Diversity and Soil Physicochemical Properties with Elevation Gradient in Burzin Forest Area
by Jiaorong Qian, Mao Ye, Xi Zhang, Miaomiao Li, Weilong Chen, Guoyan Zeng, Jing Che and Yexin Lv
Agriculture 2024, 14(7), 1176; https://doi.org/10.3390/agriculture14071176 - 18 Jul 2024
Cited by 2 | Viewed by 942
Abstract
In order to explore the changes and interrelationships of grassland plant community species diversity and soil physicochemical properties with elevation gradient, this study takes the grassland in the Burzin forest area of Xinjiang as the research object and analyzes the responses of grassland [...] Read more.
In order to explore the changes and interrelationships of grassland plant community species diversity and soil physicochemical properties with elevation gradient, this study takes the grassland in the Burzin forest area of Xinjiang as the research object and analyzes the responses of grassland species diversity, aboveground biomass, and soil physicochemical properties to the changes of elevation gradient within the altitude range of 1000~2200 m in this area. The results of the study show that: (1) The number of species and aboveground biomass reached the highest levels at elevation gradient III and showed a tendency of increasing and then decreasing with elevation. The Margalef and Shannon–Wiener indices were the largest at elevation III, while the Simpson and Alatalo indices were the largest at elevation I. (2) With the change of elevation, the available nitrogen (AN), available phosphorus (AP), soil electric conductivity (SEC), and soil pH showed a trend of increasing and then decreasing, while soil temperature decreased with elevation. Available potassium and soil water content reached their maximum values at elevation I and elevation IV, respectively. (3) The soil conductivity and diversity index were negatively correlated in elevation gradients I to III. In elevation gradient I~III, soil conductivity was positively correlated with the diversity index and aboveground biomass. Available nitrogen had a significant effect on plant diversity and biomass in elevation gradients IV to VI. (4) Aboveground biomass was significantly positively correlated with the Simpson’s index, while the relationship with the Shannon–Wiener index was less significant, and Margalef’s and Alatalo’s indices were not significant. Soil conductivity and pH significantly affected the Margalef and Simpson indices. Available nitrogen was closely related to the aboveground biomass and Margalef and Alatalo indices. Soil moisture content significantly affected Simpson’s index and the aboveground biomass. This study provides a solid theoretical foundation for the conservation and management of grassland plant community ecosystems along the elevation gradient, and has important reference value for study of the impact of environmental change on species diversity and biodiversity conservation. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Overview map of the study area. The red part of the picture shows Altay Prefecture, and the blue part is Xinjiang Uygur Autonomous Region.</p>
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<p>Species diversity characteristics of grassland plant communities at different elevation gradients. y<sub>m</sub> is the Margale index with the fitted equations for different elevation gradients. y<sub>s−w</sub> is the Shannon–Wiener index with the fitted equations for different elevation gradients. y<sub>s</sub> is the Simpson index with the fitted equations for different elevation gradients. y<sub>a</sub> is the Alatalo index with the fitted equations for different elevation gradients.</p>
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<p>Correlation network analysis of grassland community diversity with aboveground biomass and physical and chemical factors of soil at different elevation gradients. The blue line indicates positive correlation, the red line indicates negative correlation, and the thicker the line, the higher the correlation. AN, soil available nitrogen; AP, soil available phosphorus; AK, soil available potassium; SEC, soil electrical conductivity; pH, soil pH; ST, soil temperature; SM, soil moisture content; ELE, elevation; AGB, aboveground biomass. Margalef, Margalef index; Shannon–Wiener, Shannon–Wiener index; Simpson, Simpson index; Alatalo, Alatalo index. Elevation gradient I, 1000~1200 m; elevation gradient II, 1200~1400 m; elevation gradient III, 1400~1600 m; elevation gradient IV, 1600~1800 m; elevation gradient V, 1800~2000 m; elevation gradient VI, 2000~2200 m.</p>
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<p>Correlation of grassland plant species diversity, aboveground biomass, and soil physicochemical properties. The red line indicates <span class="html-italic">p</span> &lt; 0.01, the green line indicates <span class="html-italic">p</span> &lt; 0.05, and the gray line indicates non-significance. The thickness of the line indicates the magnitude of the r value of the correlation coefficient. The shade of the color represents the correlation between the influencing factors. AN, soil available nitrogen; AP, soil available phosphorus; AK, soil available potassium; SEC, soil electrical conductivity; pH, soil pH; ST, soil temperature; SM, soil moisture content; ELE, elevation; AGB, aboveground biomass. An asterisk indicates the significance level of the correlation coefficient. Specifically: * indicates <span class="html-italic">p</span>-value &lt; 0.05; ** indicates <span class="html-italic">p</span>-value &lt; 0.01; *** indicates <span class="html-italic">p</span>-value &lt; 0.001.</p>
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<p>Predicted contribution of different soil physicochemical properties and aboveground biomass to plant community diversity indices. AN, soil available nitrogen; AP, soil available phosphorus; AK, soil available potassium; SEC, soil electrical conductivity; pH, soil pH; ST, soil temperature; SM, soil moisture content; AGB, aboveground biomass; ELE, elevation.</p>
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19 pages, 3713 KiB  
Article
Fine-Tuning of Arabidopsis thaliana Response to Endophytic Colonization by Gluconacetobacter diazotrophicus PAL5 Revealed by Transcriptomic Analysis
by Fabiano Silva Soares, Ana Lídia Soares Rangel de Souza, Suzane Ariádina de Souza, Luciano de Souza Vespoli, Vitor Batista Pinto, Lucia Matiello, Felipe Rodrigues da Silva, Marcelo Menossi and Gonçalo Apolinário de Souza Filho
Plants 2024, 13(13), 1719; https://doi.org/10.3390/plants13131719 - 21 Jun 2024
Cited by 1 | Viewed by 1464
Abstract
Gluconacetobacter diazotrophicus is a diazotrophic endophytic bacterium that promotes the growth and development of several plant species. However, the molecular mechanisms activated during plant response to this bacterium remain unclear. Here, we used the RNA-seq approach to understand better the effect of G. [...] Read more.
Gluconacetobacter diazotrophicus is a diazotrophic endophytic bacterium that promotes the growth and development of several plant species. However, the molecular mechanisms activated during plant response to this bacterium remain unclear. Here, we used the RNA-seq approach to understand better the effect of G. diazotrophicus PAL5 on the transcriptome of shoot and root tissues of Arabidopsis thaliana. G. diazotrophicus colonized A. thaliana roots and promoted growth, increasing leaf area and biomass. The transcriptomic analysis revealed several differentially expressed genes (DEGs) between inoculated and non-inoculated plants in the shoot and root tissues. A higher number of DEGs were up-regulated in roots compared to shoots. Genes up-regulated in both shoot and root tissues were associated with nitrogen metabolism, production of glucosinolates and flavonoids, receptor kinases, and transcription factors. In contrast, the main groups of down-regulated genes were associated with pathogenesis-related proteins and heat-shock proteins in both shoot and root tissues. Genes encoding enzymes involved in cell wall biogenesis and modification were down-regulated in shoots and up-regulated in roots. In contrast, genes associated with ROS detoxification were up-regulated in shoots and down-regulated in roots. These results highlight the fine-tuning of the transcriptional regulation of A. thaliana in response to colonization by G. diazotrophicus PAL5. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>The growth-promoting effect of <span class="html-italic">Gluconacetobacter diazotrophicus</span> PAL5 on <span class="html-italic">Arabidopsis thaliana</span> at 50 dpi: (<b>a</b>) Morphological effect on rosette growth; (<b>b</b>) Morphological effects on root growth; (<b>c</b>) The fresh and dry weights of shoots (higher) and roots (bottom); (<b>d</b>) Total leaf area. Seven-day-old seedlings were inoculated with <span class="html-italic">G. diazotrophicus</span> strain GD-Kan (1 × 10<sup>6</sup> CFU/mL<sup>−1</sup>). Seedlings treated with water served as a control. The data shown represent the means of 20 biological replicates. Error bars represent the SD. “*” represents statistically significant differences between treatments (ANOVA, Tukey’s test; <span class="html-italic">p</span> &lt; 0.05). Bar = 1 cm.</p>
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<p>Endophytic colonization of <span class="html-italic">A. thaliana</span> plants by <span class="html-italic">G. diazotrophicus</span> PAL5 at 50 dpi: (<b>a</b>) Counting values of <span class="html-italic">G. diazotrophicus</span> PAL5 strain GD-Kan in the leaves and roots of <span class="html-italic">A. thaliana</span> plants; (<b>b</b>) <span class="html-italic">A. thaliana</span> roots inoculated with <span class="html-italic">G. diazotrophicus</span> PAL5 strain GD-F expressing the <span class="html-italic">rfg</span> gene; (<b>c</b>) Control (without inoculation). Bars = 2 µm.</p>
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<p>Overview of <span class="html-italic">Arabidopsis thaliana</span> genes differentially regulated in shoots and roots in response to colonization by <span class="html-italic">Gluconacetobacter diazotrophicus</span> PAL5 at 50 dpi: (<b>a</b>) Venn diagram of genes differentially regulated in response to <span class="html-italic">G. diazotrophicus</span>. In total, 1189 genes were differentially regulated. Overlaps show the number of genes regulated in both tissues; (<b>b</b>) Proportion of genes at different fold change (FC) ranges. The log<sub>2</sub> FC intervals are positive for up-regulated genes and negative for down-regulated genes; (<b>c</b>) Heatmap of differentially expressed genes (DEGs) that were detected in both shoot and root tissues (overlapping group of Venn diagram). Up-regulated (red), down-regulated (blue).</p>
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<p>Identification of differentially expressed genes (DEGs) and its related functional classification of Gene Ontology (GO) terms in the shoot (<b>a</b>) and root (<b>b</b>) tissues of <span class="html-italic">Arabidopsis thaliana</span> inoculated with <span class="html-italic">Gluconacetobacter diazotrophicus</span> PAL5 at 50 dpi. GO terms less than 40 DEGs are shown in <a href="#app1-plants-13-01719" class="html-app">Supplementary Table S2</a>. BP = biological processes; CC = cellular components; MF = molecular functions.</p>
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<p>Differentially expressed genes in the shoots and roots of <span class="html-italic">Arabidopsis thaliana</span> plants inoculated with <span class="html-italic">Gluconacetobacter diazotrophicus</span> PAL5 (at 50 dpi). Each gene is represented as a box; red boxes indicate genes up-regulated, and blue boxes indicate those down-regulated. The regulation of genes is based on log<sub>2</sub> FC (<span class="html-italic">p</span> &lt; 0.05). Squares with the same number indicate genes regulated in both plant tissues. The chart was compiled with the Adobe Illustrator program, using the MapMan functional categories. See <a href="#app1-plants-13-01719" class="html-app">Table S3</a> for details.</p>
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<p>Schematic illustration of the major transcriptional regulation in the shoots and roots of <span class="html-italic">G. diazotrophicus</span>-inoculated <span class="html-italic">A. thaliana</span>. The overlapping region corresponds to common DEGs in the shoots and roots. The upward red arrows show up-regulated DEGs, and the downward blue arrows show down-regulated DEGs.</p>
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11 pages, 44177 KiB  
Communication
Shifting Mountain Tree Line Increases Soil Organic Carbon Stability Regardless of Land Use
by Sofia Sushko, Kristina Ivashchenko, Alexandra Komarova, Anna Yudina, Victoria Makhantseva, Ekaterina Elsukova and Sergey Blagodatsky
Plants 2024, 13(9), 1193; https://doi.org/10.3390/plants13091193 - 25 Apr 2024
Viewed by 1314
Abstract
Climate and land use changes are causing trees line to shift up into mountain meadows. The effect of this vegetation change on the partitioning of soil carbon (C) between the labile particulate organic matter (POM–C) and stable mineral-associated organic matter (MAOM–C) pools is [...] Read more.
Climate and land use changes are causing trees line to shift up into mountain meadows. The effect of this vegetation change on the partitioning of soil carbon (C) between the labile particulate organic matter (POM–C) and stable mineral-associated organic matter (MAOM–C) pools is poorly understood. Therefore, we assessed these C pools in a 10 cm topsoil layer along forest–meadow ecotones with different land uses (reserve and pasture) in the Northwest Caucasus of Russia using the size fractionation technique (POM 0.053–2.00 mm, MAOM < 0.053 mm). Potential drivers included the amount of C input from aboveground grass biomass (AGB) and forest litter (litter quantity) and their C/N ratios, aromatic compound content (litter quality), and soil texture. For both land uses, the POM–C pool showed no clear patterns of change along forest–meadow ecotones, while the MAOM–C pool increased steadily from meadow to forest. Regardless of land use, the POM–C/MAOM–C ratio decreased threefold from meadow to forest in line with decreasing grass AGB (R2 = 0.75 and 0.29 for reserve and pasture) and increasing clay content (R2 = 0.63 and 0.36 for reserve and pasture). In pastures, an additional negative relationship was found with respect to plant litter aromaticity (R2 = 0.48). Therefore, shifting the mountain tree line in temperate climates could have a positive effect on conserving soil C stocks by increasing the proportion of stable C pools. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Plant litter input from grass aboveground biomass (AGB) and forest litter along forest–meadow ecotones with different land uses. Mean ± standard error for <span class="html-italic">n</span> = 3; different lowercase letters show significant differences for grass AGB, and capital letters show these differences for total plant litter input (grass AGB + forest litter) for each land use.</p>
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<p>Silt (0.002–0.05 mm) (<b>A</b>) and clay (&lt;0.002 mm) (<b>B</b>) content in topsoil (0–10 cm) along forest–meadow ecotones with different land uses. Mean ± standard error for <span class="html-italic">n</span> = 3; <span class="html-italic">p</span>-value for Kruskal–Wallis test.</p>
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<p>Total C stock in 10 cm topsoil layer (<b>A</b>), its distribution in particulate organic matter (POM–C) (<b>B</b>) and mineral-associated organic matter (MAOM–C) pools (<b>C</b>), and POM–C/MAOM–C ratios (<b>D</b>) along forest–meadow ecotones with different land uses. Mean ± standard error for <span class="html-italic">n</span> = 3; <span class="html-italic">p</span>-value for Kruskal–Wallis test.</p>
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<p>Relationship of topsoil POM–C/MAOM–C ratio (0–10 cm) with grass aboveground biomass (AGB) (<b>A</b>), plant aromaticity index (<b>B</b>), and clay content (<b>C</b>) along forest–meadow ecotones with different land uses (* <span class="html-italic">p</span> ≤ 0.1; ** <span class="html-italic">p</span> ≤ 0.05; *** <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>Scheme of location (<b>A</b>) and general view (<b>B</b>) of the studied reserve and pasture slopes in the Northwest Caucasus of Russia; sampling design (<b>C</b>).</p>
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<p>Soil profiles along studied forest–meadow ecotones with different land uses.</p>
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15 pages, 1902 KiB  
Article
Warming Mitigates the Impacts of Degradation on Nitrogen Allocation between Soil Microbes and Plants in Alpine Meadow
by Zhe Pang, Guoqi Wen, Lili Jiang, Xiaowei Nie, Zongsong Wang, Rui Pang, Wenjing Liu, Meirong Chen, Weiwai Zhao, Li Tang, Biao Zhang, Linfeng Li, Shutong Zhou, Xingliang Xu, Yanbin Hao, Xiaoyong Cui, Shiping Wang and Yanfen Wang
Agronomy 2024, 14(3), 508; https://doi.org/10.3390/agronomy14030508 - 29 Feb 2024
Cited by 2 | Viewed by 1753
Abstract
In alpine meadows, plants and soil microbes typically engage in competition for nitrogen (N) under N-deficient conditions. However, the acquisition and distribution of N among soil microbes and plants under alpine meadow degradation and climate warming induced by global climate change are still [...] Read more.
In alpine meadows, plants and soil microbes typically engage in competition for nitrogen (N) under N-deficient conditions. However, the acquisition and distribution of N among soil microbes and plants under alpine meadow degradation and climate warming induced by global climate change are still uncharacterized. In this study, we isotope labeled inorganic (NH4+-15N, NO3-15N) and organic (glycine-15N) N in both degraded and non-degraded plots by using open-top chambers (OTC) to mimic increasing air temperatures. After 6 h, the 15N contents in soil microbes and plants were measured to investigate the effects of degradation and rising air temperature on N allocations in the ecosystems studied. Results showed that alpine meadow degradation significantly reduced soil microbial N accumulation by 52% compared to those in non-degraded plots. In non-degraded plots, warming significantly lowered the organic N levels of soil microbes by 49%, whereas in degraded ones, it reduced both NH4+-15N and NO3-15N recovery by 80% and 45% on average but increased glycine-15N recovery by 653%. Meanwhile, warming decreased the plant recovery of NH4+-15N and NO3-15N by 75% and 45% but increased the recovery of glycine-15N by 45% in non-degraded plots. Conversely, in degraded plots, warming markedly lowered NH4+-15N recovery by 40% but increased glycine-15N recovery by 114%. Warming mitigates the effects of alpine meadow degradation on nitrogen allocation among soil microbes and plants. In unwarmed plots, degradation significantly elevated the total 15N recovery ratio of soil microbes to plants by 60%. However, in warmed plots, the impact of degradation on this ratio was reduced. The responses of the 15N recovery ratio of soil microbes and plants to rising temperatures were closely related to alpine meadow quality. In non-degraded areas, warming enhanced the recovery ratio for NH4+-15N by 165% but reduced it for glycine-15N by 66%. Conversely, in degraded plots, warming decreased the recovery ratio for NH4+-15N by 66% but increased it for glycine-15N by 232%. This indicates that warming can increase carbon limitation for soil microbes in degraded alpine meadows, and the restoration of degraded alpine meadows should prioritize restoring carbon accumulation. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>The experiment treatments in the warming plot (NMND: non-warming non-degraded; NWD: non-warming degraded; WND: warming non-degraded; WD: warming degraded).</p>
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<p>Total <sup>15</sup>N recovered in microbial biomass (% of added <sup>15</sup>N) for both overall (<b>a</b>,<b>b</b>) and specific N types (NO<sub>3</sub><sup>−</sup>-<sup>15</sup>N, NH<sub>4</sub><sup>+</sup>-<sup>15</sup>N, and glycine-<sup>15</sup>N) (<b>c</b>,<b>d</b>) measured six hours post-<sup>15</sup>N-injection at 0–10 cm soil depth in alpine meadow. Significant differences (<span class="html-italic">p</span> &lt; 0.05) are marked with different letters above bars, comparing no degradation (ND) to degradation (D) in panels a, and no warming (NW) to warming (W) in panels (<b>b</b>–<b>d</b>).</p>
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<p>Total <sup>15</sup>N recovery by plants (% of added 15N) at both community (<b>a</b>) and species level (<b>b</b>) and the recovery from NO<sub>3</sub><sup>−</sup>-<sup>15</sup>N, NH<sub>4</sub><sup>+</sup>-<sup>15</sup>N, and glycine-<sup>15</sup>N at community (<b>c</b>) and species level (<b>d</b>–<b>g</b>), measured six hours post-<sup>15</sup>N-injection at 0–10 cm soil depth in alpine meadow. Significant differences (<span class="html-italic">p</span> &lt; 0.05) are marked with different letters above bars, comparing no warming (NW) to warming (W). D and ND represent degradation and no degradation, respectively.</p>
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<p>Ratios of total <sup>15</sup>N recovery in soil microbials to plants at the community (<b>a</b>) and species level (<b>b</b>) and ratios of total <sup>15</sup>N recovery in soil microbials to plants from NO<sub>3</sub><sup>−</sup>-<sup>15</sup>N, NH<sub>4</sub><sup>+</sup>-<sup>15</sup>N, and glycine-<sup>15</sup>N at community (<b>c</b>) and species level (<b>d</b>–<b>g</b>) six hours post-<sup>15</sup>N-injection at 0–10 cm soil depth in alpine meadow. Significant differences (<span class="html-italic">p</span> &lt; 0.05) are marked with different letters above bars, comparing no warming (NW) to warming (W). D and ND represent degradation and no degradation, respectively.</p>
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18 pages, 9407 KiB  
Article
Effects of Root–Root Interactions on the Physiological Characteristics of Haloxylon ammodendron Seedlings
by Huifang Yang, Suwan Ji, Deyan Wu, Menghao Zhu and Guanghui Lv
Plants 2024, 13(5), 683; https://doi.org/10.3390/plants13050683 - 28 Feb 2024
Cited by 1 | Viewed by 1122
Abstract
The root traits and response strategies of plants play crucial roles in mediating interactions between plant root systems. Current research on the role of root exudates as underground chemical signals mediating these interactions has focused mainly on crops, with less attention given to [...] Read more.
The root traits and response strategies of plants play crucial roles in mediating interactions between plant root systems. Current research on the role of root exudates as underground chemical signals mediating these interactions has focused mainly on crops, with less attention given to desert plants in arid regions. In this study, we focused on the typical desert plant Haloxylon ammodendron and conducted a pot experiment using three root isolation methods (plastic film separation, nylon mesh separation, and no separation). We found that (1) as the degree of isolation increased, plant biomass significantly increased (p < 0.05), while root organic carbon content exhibited the opposite trend; (2) soil electrical conductivity (EC), soil total nitrogen (STN), soil total phosphorus (STP), and soil organic carbon (SOC) were significantly greater in the plastic film and nylon mesh separation treatments than in the no separation treatment (p < 0.05), and the abundance of Proteobacteria and Actinobacteriota was significantly greater in the plastic film separation treatment than in the no separation treatment (p < 0.05); (3) both plastic film and nylon mesh separations increased the secretion of alkaloids derived from tryptophan and phenylalanine in the plant root system compared with that in the no separation treatment; and (4) Pseudomonas, Proteobacteria, sesquiterpenes, triterpenes, and coumarins showed positive correlations, while both pseudomonas and proteobacteria were significantly positively correlated with soil EC, STN, STP, and SOC (p < 0.05). Aurachin D was negatively correlated with Gemmatimonadota and Proteobacteria, and both were significantly correlated with soil pH, EC, STN, STP, and SOC. The present study revealed strong negative interactions between the root systems of H. ammodendron seedlings, in which sesquiterpenoids, triterpenoids, coumarins, and alkaloids released by the roots played an important role in the subterranean competitive relationship. This study provides a deeper understanding of intraspecific interactions in the desert plant H. ammodendron and offers some guidance for future cultivation of this species in the northwestern region of China. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Biomass and root characteristics of <span class="html-italic">H. ammodendron</span> seedlings from different separation methods. Different letters indicate significant differences between treatments (<span class="html-italic">p</span> &lt; 0.05): TB: total biomass; AB: aboveground biomass; UB: underground biomass; FRB: fine root biomass; SRL: specific root length; SRA: specific leaf area; RSR: root-shoot ratio; RC: root organic carbon; RTN: root total nitrogen; RTP: root total phosphorus; D2: no separation group; N: nylon net separation group; P: plastic film separation group.</p>
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<p>Variations in rhizosphere soil physicochemical properties were examined under different separation conditions. Significant differences (<span class="html-italic">p</span> &lt; 0.05) among the different treatments are denoted by different letters, while treatments without letters indicate nonsignificant differences between groups: SOC: soil organic carbon; STN: soil total nitrogen; SAP: soil available phosphorus; STP: soil total phosphorus; EC: electrical conductivity; pH: soil pH; SNN: soil nitrate nitrogen; SAN: soil ammonium nitrogen; D2: no separation treatment; N: nylon net separation treatment; P: plastic film separation treatment.</p>
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<p>Genus-level bacterial community composition and distribution under different isolation methods: (<b>A</b>) A bar chart illustrating the distribution of bacterial taxa in terms of their relative abundance. (<b>B</b>) Principal component analysis (PCA) plot of the bacterial community composition. (<b>C</b>) LEFSe analysis. D2: Nonisolation group; N: Nylon net isolation group; P: Plastic film isolation group.</p>
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<p>Correlations among plant traits and Mantel test results for bacterial and root exudate relationships: C: aboveground plant organic carbon; TN: aboveground plant total nitrogen; TP: aboveground plant total phosphorus. For the meanings of the remaining letters, please refer to <a href="#plants-13-00683-f001" class="html-fig">Figure 1</a>. *: <span class="html-italic">p</span> ≤ 0.05; **: <span class="html-italic">p</span> ≤ 0.01; ***: <span class="html-italic">p</span> ≤ 0.001; ns: insignificant; Spearman correlation.</p>
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<p>Correlation analysis between differential secondary metabolites and differential bacterial groups. The red lines represent positive correlations; the blue lines represent negative correlations. Green boxes represent differential flora and orange represents differential metabolites.</p>
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<p>Correlation analysis between differential bacterial groups, differential secondary metabolites, and soil environmental factors: <b>left</b>: correlation analysis between differential bacterial groups and soil physicochemical properties; <b>right</b>: correlation analysis between differential secondary metabolites and soil physicochemical properties. The meanings of the letters can be found in <a href="#plants-13-00683-f002" class="html-fig">Figure 2</a>. *: <span class="html-italic">p</span> ≤ 0.05; **: <span class="html-italic">p</span> ≤ 0.01; ***: <span class="html-italic">p</span> ≤ 0.001.</p>
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<p>PCA and OPLS-DA of root metabolites in <span class="html-italic">H. ammodendron</span> seedlings under different separation methods. (<b>A</b>): PCA analysis of root secretion <span class="html-italic">H. ammodendron</span> seedlings under different separation treatments. (<b>B</b>): OPLD-DA analysis of root secretions of <span class="html-italic">H. ammodendron</span> seedlings between N and P treatments. (<b>C</b>): OPLD-DA analysis of root secretions of <span class="html-italic">H. ammodendron</span> seedlings between N and D2 treatments. (<b>D</b>): OPLD-DA analysis of root secretions <span class="html-italic">H. ammodendron</span> seedlings between P and D2 treatments.</p>
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13 pages, 1999 KiB  
Article
The Effects of Different Rotations of Beans, Maize, and Cabbage on Soil Moisture and Economic Benefits
by Xiaojuan Wang, Tianle Wang, Lei Wang and Enke Liu
Agronomy 2024, 14(3), 479; https://doi.org/10.3390/agronomy14030479 - 27 Feb 2024
Cited by 1 | Viewed by 1580
Abstract
The article investigates the effects of different cropping rotations on soil moisture and economic benefit. Cabbage–maize–cabbage (CMC), beans–maize–cabbage (BMC), and cabbage–cabbage–cabbage (CCC) treatments were set up to study the effects of different crop rotation combinations on soil water storage, evapotranspiration (ET), water use [...] Read more.
The article investigates the effects of different cropping rotations on soil moisture and economic benefit. Cabbage–maize–cabbage (CMC), beans–maize–cabbage (BMC), and cabbage–cabbage–cabbage (CCC) treatments were set up to study the effects of different crop rotation combinations on soil water storage, evapotranspiration (ET), water use efficiency (WUE), and economic benefit. The results showed that the average soil moisture content decreased initially and then increased with crop rotation, whereas it continued to decrease with continuous cabbage cropping as the crop grew. CMC reduced ET, whereas BMC increased ET from the nodulation to maturation stages of cabbage compared with CCC in the third experimental year. WUE of different crops showed that cabbage > maize > beans. The economic benefit of the CMC was higher than the other treatments in the third planting year. Therefore, the best crop rotation combination in this area is cabbage–maize–cabbage. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Precipitation in the experimental site.</p>
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<p>Soil water storage in 0–200 cm in 2018.</p>
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<p>Soil water storage in 0–200 cm in 2019.</p>
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<p>Soil water storage in 0–200 cm in 2020.</p>
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<p>Changes in soil water storage in 0–200 cm soil layers in different growth periods of crops in 2018.</p>
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<p>Changes in soil water storage in 0–200 cm soil layers in different growth periods of crops in 2019.</p>
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<p>Changes in soil water storage in 0–200 cm soil layers in different growth periods of crops in 2020.</p>
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26 pages, 4175 KiB  
Review
Mechanisms and Mitigation Strategies for the Occurrence of Continuous Cropping Obstacles of Legumes in China
by Lei Ma, Shaoying Ma, Guiping Chen, Xu Lu, Qiang Chai and Sheng Li
Agronomy 2024, 14(1), 104; https://doi.org/10.3390/agronomy14010104 - 31 Dec 2023
Cited by 9 | Viewed by 2727
Abstract
Legumes have important nutritional and economic values, but their production faces continuous cropping obstacles that seriously affect their yield formation. In order to reduce the negative impact of the continuous cropping obstacles of legumes, it is necessary to understand the response mechanisms of [...] Read more.
Legumes have important nutritional and economic values, but their production faces continuous cropping obstacles that seriously affect their yield formation. In order to reduce the negative impact of the continuous cropping obstacles of legumes, it is necessary to understand the response mechanisms of legumes to continuous cropping, the causes of continuous cropping obstacles and the measures to alleviate continuous cropping obstacles. This review aimed to identify the current knowledge gap in the field of continuous cropping obstacles of legumes and provide direction and focus for future research. The continuous cropping obstacles of legumes start with soil degradation, leading to oxidative stress in the plants. This triggers the expression of plant-hormone- and signal-molecule-related genes, activating the defense system and causing continuous cropping obstacles. Although there has been progress in researching these challenges in legume crops, many questions remain. We believe that the exploration of molecular mechanisms of legume crops responding to continuous cropping, rhizosphere signal exchange and soil environment repair mechanisms after long-term continuous cropping of soybean, and the excavation of candidate genes and functional loci related to continuous cropping obstacles in legume crops are breakthroughs for proposing effective continuous cropping obstacle management strategies in the future. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Effect of continuous cropping on the growth of legume crops.</p>
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<p>Continuous cropping causes oxidative stress response in legume crops. The solid lines are confirmed by research; the dashed lines are potential mechanisms that require further study. ? indicates that it has not been proven in continuous cropping abstacle of leguminous crops, but there may be an association, and further research is needed in the future.</p>
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<p>Response of the photosynthetic system of legume crops to continuous cropping. The solid lines are confirmed by research; the dashed lines are potential mechanisms that require further study.</p>
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<p>Response of hormone signal transduction of legume crops to continuous cropping obstacles. Solid line: molecular interaction or relation. Dashed line: indirect link or unknown reaction. ? indicates that it has not been proven in continuous cropping abstacle of leguminous crops, but there may be an association, and further research is needed in the future.</p>
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<p>Response of the defense system of legume crops to continuous cropping.</p>
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<p>Soil environment deterioration in continuous cropping system of legume crops.</p>
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<p>Measures to alleviate the continuous cropping obstacles of legume crops. ?: Elements that need to be studied at a later date.</p>
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<p>Mechanisms of legume crops responding to continuous cropping obstacles. The dotted lines are the content that needs to be studied in the future. The arrows following the morphological, physiological and biochemical indicators indicate an increase or decrease in the value of the corresponding indicator, respectively.</p>
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20 pages, 3244 KiB  
Article
What Do Cross-Range Germination, Growth, and Interaction Studies Reveal about the Behaviour of an Expansive Plant Species?
by Krishan Kaushik, Robert W. Pal, Katalin Somfalvi-Tóth, Riyazuddin Riyazuddin, Kinga Rudolf and Tamás Morschhauser
Agriculture 2023, 13(11), 2171; https://doi.org/10.3390/agriculture13112171 - 20 Nov 2023
Viewed by 1624
Abstract
Understanding the invasion potential of any plant species is crucial for early detection in habitat conservation, particularly when observing their expansion within their native region. As a test species, we utilised Allium ursinum L., a dominant clonal species in early spring forest floors. [...] Read more.
Understanding the invasion potential of any plant species is crucial for early detection in habitat conservation, particularly when observing their expansion within their native region. As a test species, we utilised Allium ursinum L., a dominant clonal species in early spring forest floors. We compared the species’ germination capacity in native (Hungarian) and non-native (North American) soils, its seedling growth, and competing performances with two co-occurring dominant species, Melica uniflora Retz. and Carex pilosa Scop., in ten soil types and three soil compositions, respectively. Additionally, the competitive interactions of A. ursinum with Convallaria majalis L., a species already introduced in North America, were assessed under three moisture conditions. The results revealed that A. ursinum exhibited enhanced germination in non-native soils, while its shoot growth was most vigorous in control soil. When grown in soils with different co-dominant species, A. ursinum seedlings exhibited varying growth rates, significantly influenced by solar radiation intensity. A. ursinum shoots displayed superior growth in soil collected from C. pilosa stands compared to soil originating from its own stands. Notably, A. ursinum effectively competed against C. majalis in moderate soil moisture conditions. Furthermore, increasing sand content improved the competitive ability of A. ursinum against C. pilosa and M. uniflora. Based on our findings, A. ursinum possesses an invasion potential for particular North American habitats. However, the extent of its potential is dependent upon soil and climatic conditions. Under medium moisture regime, A. ursinum might outcompete the already established C. majalis from its habitats. Additionally, it can potentially displace native species with comparable ecological characteristics, such as C. pilosa and M. uniflora, especially in loose soils. Similar cross-range seed germination, growth, and paired competition experiments with potential competitor species are highly recommended as these can not only elucidate its native range expansion but also various growth scenarios for its agricultural cultivation. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Comparative germination profile of significantly different <span class="html-italic">A. ursinum</span> seeds germination in non-native U.S. soils (in green) against the native Hungarian <span class="html-italic">A. ursinum</span> soils (in brown). Error bar represent the standard error in dataset.</p>
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<p>The mean growth rate of <span class="html-italic">A. ursinum</span> shoots for 21 weeks across different soil types. Legend: AU = <span class="html-italic">A. ursinum</span>; CP = <span class="html-italic">C. pilosa</span>; MU = <span class="html-italic">M. uniflora</span>.</p>
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<p>Duncan post hoc test for growth rate and soil origin type showing which soil origin had a similar effect on <span class="html-italic">A. ursinum</span> growth rate in response to total solar radiation, y-axis: quantile-normalised values of growth rate (order of magnitude similar to the values of the sum of solar radiation. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; CP—<span class="html-italic">C. pilosa</span>; MU—<span class="html-italic">M. uniflora</span>; CNT—Control; 1/2/3—site name. Different letters (a, b, c, d, e) above the symbols refer to significant differences (<span class="html-italic">p</span> &lt; 0.05) between the effect of soil origins on growth rates.</p>
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<p>Cross categories box-plots of R.I.I. (Relative Interaction Index) values based on shoots (Total Leaf Area) and roots (Numbers of Roots) of <span class="html-italic">A. ursinum</span> and <span class="html-italic">C. majalis</span> in three moisture categories. The values above the zeroth fainted dotted line are positive R.I.I. values signifying facilitation, while below this are negative R.I.I. values indicating competition. Both seasons’ mean (2017–2018) regenerated plants were harvested by the following spring season. ‘x’ indicates the mean R.I.I. values in all the box plots. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; CM—<span class="html-italic">C. majalis</span>; reg.—regenerated.</p>
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<p>Cross categories box-plots of R.I.I. (Relative Interaction Index) values based on shoots (Total Leaf Area) and roots (Numbers of Roots) of <span class="html-italic">A. ursinum</span> and <span class="html-italic">C. pilosa</span> in three sand categories. Values above the zeroth fainted dotted line are positive R.I.I. values signifying facilitation, while below this are negative R.I.I. values indicating competition. ‘Wet state’, denoted with number 1, is water-saturated soils, and ‘both seasons’ means regenerated plants were harvested by the next spring season (2017–2018). ‘x’ indicates the mean R.I.I. values in all the box plots. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; CP—<span class="html-italic">C. pilosa</span>; reg.—regenerated.</p>
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<p>Cross categories box-plots of R.I.I. (Relative Interaction Index) values based on shoots (Total Leaf Area) and roots (Numbers of Roots) of <span class="html-italic">A. ursinum</span> and <span class="html-italic">M. uniflora</span> in three sand categories. Values above the zeroth fainted dotted line are positive R.I.I. values signifying facilitation, while below this are negative R.I.I. values indicating competition. ‘Wet state’, denoted with number 1, is water-saturated soils, and ‘both seasons’ means regenerated plants were harvested by the next spring season (2017–2018). ‘x’ indicates the mean R.I.I. values in all the box plots. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; MU—<span class="html-italic">M. uniflora</span>; reg.—regenerated.</p>
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<p>Cross categories box-plots of R.I.I. (Relative Interaction Index) values based on shoots (Total Leaf Area) and roots (Numbers of Roots) of <span class="html-italic">A. ursinum</span> and <span class="html-italic">C. pilosa</span> in three sand categories. Values above the zeroth fainted dotted line are positive R.I.I. values signifying facilitation, while below this are negative R.I.I. values indicating competition. ‘Moist state’, denoted with number 2, is moderately water-saturated soils. ‘x’ indicates the mean R.I.I. values in all the box plots. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; CP—<span class="html-italic">C. pilosa</span>.</p>
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<p>Cross categories box-plots of R.I.I. (Relative Interaction Index) values based on shoots (Total Leaf Area) and roots (Numbers of Roots) of <span class="html-italic">A. ursinum</span> and <span class="html-italic">M. uniflora</span> in three sand categories. Values above the zeroth fainted dotted line are positive R.I.I. values signifying facilitation, while below this are negative R.I.I. values indicating competition. ‘Moist state’, denoted with number 2, is moderately water-saturated soils. ‘x’ indicates the mean R.I.I. values in all the box plots. Abbreviations: AU—<span class="html-italic">A. ursinum</span>; MU—<span class="html-italic">M. uniflora</span>.</p>
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19 pages, 4573 KiB  
Article
Effect of Enhanced Organic Material Addition during Reductive Soil Disinfestation on Disease Resistance, Yield Increase, and Microbial Community in Flue-Cured Tobacco
by Chaosheng Luo, Huiqiong Ding, Yuanyuan Li, Taiqin Liu and Yan Dong
Agronomy 2023, 13(10), 2458; https://doi.org/10.3390/agronomy13102458 - 22 Sep 2023
Cited by 2 | Viewed by 1625
Abstract
The addition of organic materials is pivotal for the efficacy of reductive soil disinfestation (RSD). However, data on the influence of varying amounts of organic matter during RSD on soil-borne disease mitigation, yield increase, and rhizosphere microecological health in the current flue-cured tobacco [...] Read more.
The addition of organic materials is pivotal for the efficacy of reductive soil disinfestation (RSD). However, data on the influence of varying amounts of organic matter during RSD on soil-borne disease mitigation, yield increase, and rhizosphere microecological health in the current flue-cured tobacco season remain limited. This study analyzed various organic material addition rates (CK, G0.8, G1.0, and G1.2) at two experimental sites (K and Y). The results indicated that increasing the application of organic material improved the soil physicochemical properties (pH, AN, AP, AK, OM, and C/N), mitigated the severity of black shank and Fusarium root rot, and amplified the tobacco yield. The K/YG1.2 treatment significantly reduced the Shannon and Sobs fungal indices across both sites, and enhanced the relative abundance of the bacteria Actinobacteria, Chloroflexi, Firmicutes, and Acidobacteriota, while decreasing the relative abundance of Ascomycota. The bacterial genera were predominantly represented by Sphingomonas and Bacillus, whereas the fungal genera were represented by Saitozyma, Mortierella, and Fusarium. The addition of organic materials during RSD substantially decreased the relative abundance of Mortierella and Fusarium. Using FUNGGuild and Tax4Fun to evaluate the application of adding organic matter during the RSD process, we identified that rhizosphere fungi in high application rates of flue-cured tobacco were primarily saprophytic or pathogenic saprophytes, which were mainly involved in the metabolism, environmental information processing, genetic information processing, and cellular processes. The results of the two experimental sites indicate that applying 15 t·ha−1 (K/YG1.2) of solid residues such as vegetables during RSD emerges as the optimal choice. This strategy is highly effective in guaranteeing the sterilization and pest control effect of the RSD process, facilitating the reconstruction of microbial community diversity, lowering pathogen abundance, managing soil-borne diseases that are prevalent in the current flue-cured tobacco season, and leading to an increase in tobacco yield. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Daily average temperature and monthly cumulative precipitation during the planting season at two experimental sites.</p>
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<p>Effect of adding organic materials on the occurrence of soil-borne diseases in flue−cured tobacco and the yield of tobacco leaves. (<b>A</b>) Disease index of two diseases and (<b>B</b>) tobacco leaf yield of in the K and Y experimental sites. Different uppercase (lowercase) letters at the same experimental site represent significant differences among treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Microbial diversity and richness indices of rhizosphere soil in flue-cured tobacco.</p>
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<p>Distribution of OTU abundance of fungi and bacteria in the rhizosphere soil of flue-cured tobacco ((<b>A</b>): fungi at the K site; (<b>B</b>): fungi at the Y site; (<b>C</b>): bacteria at the K site; (<b>D</b>): bacteria at the Y site).</p>
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<p>PCoA analysis of fungi and bacteria in the rhizosphere soil of flue−cured tobacco ((<b>A</b>): K site fungi; (<b>B</b>): Y site fungi; (<b>C</b>): K site bacteria; (<b>D</b>): Y site bacteria).</p>
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<p>Community abundance profiling of rhizosphere soil in flue-cured tobacco at the phylum and genus levels ((<b>A</b>): fungi phylum; (<b>B</b>): bacteria phylum; (<b>C</b>): fungi genus; (<b>D</b>): bacteria genus).</p>
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<p>Relative abundance of pathogenic bacteria in the rhizosphere soil of flue-cured tobacco ((<b>A</b>): <span class="html-italic">Phytophthora nicotianae</span>; (<b>B</b>): <span class="html-italic">Fusarium</span> spp.). Different uppercase (lowercase) letters at the same experimental site represent significant differences among treatments at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>LEfSe multi-level species discriminant analysis of microbial differences in the rhizosphere soil of flue-cured tobacco ((<b>A</b>): fungi; (<b>B</b>): bacteria).</p>
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<p>Correlation analysis between dominant microbial genera and environmental factors in the rhizosphere soil of flue−cured tobacco ((<b>A</b>): fungi; (<b>B</b>): bacteria). * <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>Prediction and analysis of microbial community functions in the rhizosphere soil of flue-cured tobacco ((<b>A</b>): fungi; (<b>B</b>): bacteria).</p>
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<p>RDA analysis of microorganisms and environmental factors in the rhizosphere soil of flue−cured tobacco.</p>
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18 pages, 1048 KiB  
Review
Microbial Biofertilisers in Plant Production and Resistance: A Review
by Domenico Prisa, Roberto Fresco and Damiano Spagnuolo
Agriculture 2023, 13(9), 1666; https://doi.org/10.3390/agriculture13091666 - 24 Aug 2023
Cited by 7 | Viewed by 6989
Abstract
In sustainable agriculture, plant nutrients are the most important elements. Biofertilisers introduce microorganisms that improve the nutrient status of plants and increase their accessibility to crops. To meet the demands of a growing population, it is necessary to produce healthy crops using the [...] Read more.
In sustainable agriculture, plant nutrients are the most important elements. Biofertilisers introduce microorganisms that improve the nutrient status of plants and increase their accessibility to crops. To meet the demands of a growing population, it is necessary to produce healthy crops using the right type of fertilisers to provide them with all the key nutrients they need. However, the increasing dependence on chemical fertilisers is destroying the environment and negatively affecting human health. Therefore, it is believed that the use of microbes as bioinoculants, used together with chemical fertilisers, is the best strategy to increase plant growth and soil fertility. In sustainable agriculture, these microbes bring significant benefits to crops. In addition to colonising plant systems (epiphytes, endophytes and rhizospheres), beneficial microbes play a key role in the uptake of nutrients from surrounding ecosystems. Microorganisms, especially fungi, also play a protective function in plants, enhancing the responses of defence systems, and play a key role in situations related to soil iron deficiency or phosphorous solubilisation. Plant-associated microbes can thus promote plant growth regardless of natural and extreme conditions. The most frequently used strategies for growth-promoting microorganisms are nitrogen fixation, the production of growth hormones, siderophores, HCN, various hydrolytic enzymes and the solubilisation of potassium, zinc and phosphorous. Research on biofertilisers has been extensive and available, demonstrating how these microbes can provide crops with sufficient nutrients to increase yields. This review examines in detail the direct and indirect mechanisms of PGPR action and their interactions in plant growth and resistance. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Increased vegetative growth and flowering in <span class="html-italic">Astrophytum capricorne</span> (<b>A</b>) and <span class="html-italic">Astrophytum myriostigma</span> (<b>B</b>) in plants supplemented with rhizobacteria on biochar substrate [<a href="#B21-agriculture-13-01666" class="html-bibr">21</a>].</p>
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<p>PGPB promotes plant growth through the production of siderophores, increasing iron availability and producing hormones such as auxins, gibberellins and cytokinin that modulate the hormone balance of the host plant. The direct mechanisms include biological nitrogen fixation (BNF) via the activity of the nitrogenase enzyme complex, the solubilization of inorganic phosphate in the soil, and the production of siderophores. The indirect mechanisms are attributed to PGPB’s occupation of niches and the production of substances that repel phytopathogens and nematodes [<a href="#B21-agriculture-13-01666" class="html-bibr">21</a>].</p>
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30 pages, 5171 KiB  
Article
Influence of Mulching on Replantation Disease in Sour Cherry Orchard
by Krzysztof Rutkowski and Grzegorz P. Łysiak
Agriculture 2023, 13(8), 1587; https://doi.org/10.3390/agriculture13081587 - 9 Aug 2023
Cited by 1 | Viewed by 1317
Abstract
Increasingly, in orchards around the world that are planted one after another, disturbances are observed, and these issues with growth and development are called replantation disease. It is manifested mainly by poor tree growth after planting and poor ripening. One way to reduce [...] Read more.
Increasingly, in orchards around the world that are planted one after another, disturbances are observed, and these issues with growth and development are called replantation disease. It is manifested mainly by poor tree growth after planting and poor ripening. One way to reduce replantation disease is to improve soil fertility after many years of fruit tree cultivation. The aim of the work was to evaluate the growth and yield of cherries after replantation and to compare this with a site where fruit trees had not grown before. The trees were planted at two sites: after the replantation of the cherry orchard (OR1) and in a site where fruit trees had not been cultivated before (OR2). Two combinations were used in each orchard: boiler without mulching (C), mulch—after planting mulching with a substrate after growing mushrooms (M). The trees at the site after replantation grew and bore less fruit than in the position where fruit trees had not grown before. The disease also affected some of the quality characteristics of the fruit. This resulted in an increase in fruit weight and a darker color (L*) and a higher value of hue fruit color. Mulching, which is often recommended in orchards planted after previous cultivation, did not provide the expected improvement. It did not significantly affect tree growth and yield. Only an effect on the content of components in the soil was observed, but it affected the condition of the trees. In addition, we analyzed how experimental combinations responded to climatic conditions by calculating the correlations between the SAT (sum of active temperatures) and the stages of tree development. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Diagram of an experimental system, where each rectangle represents an experimental plot. OR1—site 1 (after replantation), OR2—site 2 (before planting, only agricultural crops were grown), C—control, M—with compost mulch after mushroom (<span class="html-italic">Agaricus bisporus</span>) production.</p>
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<p>Temperature profiles corresponding to the 2 weeks before and after full flowering in the years 2008–2016.</p>
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<p>The effect of mulching on soil reaction and mineral content in the arable layer 0–20 cm.</p>
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<p>The effect of mulching on the pH of the substrate and the content of minerals in the subarable layer 21–40 cm.</p>
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<p>The general yielding average of all treatments of cherry trees over the years. <sup>1</sup> means that the same letters are not significantly different at α = 0.05 (Duncan’s test).</p>
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<p>The weight of 100 sour cherries in the years 2008–2016. <sup>1</sup> means that the same letters are not significantly different at α = 0.05 (Duncan’s test).</p>
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<p>Firmness of the fruits. <sup>1</sup> means that the same letters are not significantly different at α = 0.05 (Duncan’s test).</p>
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<p>The general average of all treatments total soluble solids (TSS) content in the years 2008–2016. <sup>1</sup> means that the same letters are not significantly different at α = 0.05 (Duncan’s test).</p>
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<p>Influence of year on titratable acidity of sour cherry (% malic acid). <sup>1</sup> means that the same letters are not significantly different at α = 0.05 (Duncan’s test).</p>
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17 pages, 2158 KiB  
Article
Growth and Physiological Characteristics of Sour Jujube Seedlings in Different Substrate Formulations
by Ying Zhu, Yanjun Duan, Zhiguo Liu, Mengjun Liu and Ping Liu
Agronomy 2023, 13(7), 1797; https://doi.org/10.3390/agronomy13071797 - 5 Jul 2023
Cited by 3 | Viewed by 1502
Abstract
The raising of container seedlings with light substrates has become an important method of seedling raising, without delaying the seedling period. In order to reduce reliance on non-renewable peat and to promote the reuse of organic waste, this study compared the growth of [...] Read more.
The raising of container seedlings with light substrates has become an important method of seedling raising, without delaying the seedling period. In order to reduce reliance on non-renewable peat and to promote the reuse of organic waste, this study compared the growth of sour jujube seedlings in different substrate formulations (i.e., different proportions of vermicompost instead of peat), using a semi-subterranean placement of root control bags, and explored the application of vermicompost in the raising of sour jujube seedlings. The results showed that there were significant differences in the growth and the physiological and photosynthetic characteristics of sour jujube seedlings treated with different substrates, among which substrates A2 (peat: vermicompost: vermiculite: garden soil = 0.5:0.5:1:1) and A3 (peat: vermiculite: garden soil = 1:2:1) were suitable for sour jujube seedling raising. The seedling height, the seedling ground diameter, the number of secondary branches, the length of the longest secondary branch, the total fresh weight, the aboveground fresh weight, the total root length, the root projection area, and the root surface area were all significantly greater than those of jujube seedlings grown on other substrates. Especially in A3, vermicompost can replace peat as the nursery substrate for sour jujube seedlings, removing dependence on non-renewable peat resources, reducing costs, and providing more prospects for application. The suitable substrate conditions for sour jujube seedlings were as follows: soil porosity 44.0–54.0%, electric conductivity (EC) value 0.2 mS/cm, organic matter 40.39~54.05 g·kg−1, total nitrogen and total phosphorus of 1.67~1.91 g·kg−1 and 0.95~1.20 g·kg−1, respectively, alkali-hydrolyzed nitrogen 139.75~154.69 mg·kg−1, and available phosphorus 137~224 mg·kg−1. Full article
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
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<p>Location of the study site. The green dot in the figure is the test sites for this study. It was located in the Third Experimental Farm of Hebei Agricultural University in Lian Chi District, Baoding City, Hebei Province, China, with longitude 115°21′–115°30′ E and latitude 38°49′–38°56′ N.</p>
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<p>Enzyme activity of different substrates: (<b>a</b>) urease activity (URE, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>b</b>) sucrase activity (SC, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>c</b>) acid phosphatase activity (ACP, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>d</b>) alkaline phosphatase (ALP, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); and (<b>e</b>) catalase activity (CAT, mg·g<sup>−1</sup>·20·min<sup>−1</sup>). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 3).</p>
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<p>Enzyme activity of different substrates: (<b>a</b>) urease activity (URE, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>b</b>) sucrase activity (SC, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>c</b>) acid phosphatase activity (ACP, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); (<b>d</b>) alkaline phosphatase (ALP, mg·g<sup>−1</sup>·24·h<sup>−1</sup>); and (<b>e</b>) catalase activity (CAT, mg·g<sup>−1</sup>·20·min<sup>−1</sup>). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 3).</p>
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<p>Growth characteristics of sour jujube seedlings with different mixed substrates: (<b>a</b>) height (H, cm), (<b>b</b>) stem diameter (D, mm), (<b>c</b>) secondary branch number (SBN/number), and (<b>d</b>) maximum secondary branch length (MSBL/cm). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 10).</p>
Full article ">Figure 3 Cont.
<p>Growth characteristics of sour jujube seedlings with different mixed substrates: (<b>a</b>) height (H, cm), (<b>b</b>) stem diameter (D, mm), (<b>c</b>) secondary branch number (SBN/number), and (<b>d</b>) maximum secondary branch length (MSBL/cm). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 10).</p>
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<p>Photosynthetic parameters of sour jujube seedlings under different substrates: (<b>a</b>) net photosynthetic rate (μmol·m<sup>−2</sup>·s<sup>−1</sup>), (<b>b</b>) stomatal conductance (mmol·m<sup>−2</sup>·s<sup>−1</sup>), (<b>c</b>) intercellular CO<sub>2</sub> concentration (μmol·mol<sup>−1</sup>), and (<b>d</b>) transpiration rate (mmol·m<sup>−2</sup>·s<sup>−1</sup>). A<sub>0</sub> (Peat: vermiculite = 2:1), A<sub>1</sub> (peat: vermicompost: vermiculite: garden soil = 0.75:0.25:1:1), A<sub>2</sub> (peat: vermicompost: vermiculite: garden soil = 0.5:0.5:1:1), A<sub>3</sub> (vermicompost: vermiculite: garden soil = 1:2:1), and A<sub>4</sub> (vermicompost: vermiculite: decomposed sheep manure = 1:2:1). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 5).</p>
Full article ">Figure 4 Cont.
<p>Photosynthetic parameters of sour jujube seedlings under different substrates: (<b>a</b>) net photosynthetic rate (μmol·m<sup>−2</sup>·s<sup>−1</sup>), (<b>b</b>) stomatal conductance (mmol·m<sup>−2</sup>·s<sup>−1</sup>), (<b>c</b>) intercellular CO<sub>2</sub> concentration (μmol·mol<sup>−1</sup>), and (<b>d</b>) transpiration rate (mmol·m<sup>−2</sup>·s<sup>−1</sup>). A<sub>0</sub> (Peat: vermiculite = 2:1), A<sub>1</sub> (peat: vermicompost: vermiculite: garden soil = 0.75:0.25:1:1), A<sub>2</sub> (peat: vermicompost: vermiculite: garden soil = 0.5:0.5:1:1), A<sub>3</sub> (vermicompost: vermiculite: garden soil = 1:2:1), and A<sub>4</sub> (vermicompost: vermiculite: decomposed sheep manure = 1:2:1). Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 5).</p>
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<p>Effects of different vermicompost substrates on aboveground, underground, and total fresh weight of sour jujube seedlings (mean ± SE, <span class="html-italic">n</span> = 10). Note: WFW—total fresh weight; AFW—aboveground fresh weight; UFW—underground fresh weight. Significant differences between treatments are indicated by different lowercase letters (Duncan’s test; <span class="html-italic">p</span> &lt; 0.05; mean ± SD, <span class="html-italic">n</span> = 10).</p>
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