Cover Cropping-Mediated Regulation of Phyllosphere Microbial Health and Rice Yield.

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Learn more: PMC Disclaimer | PMC Copyright Notice J Agric Food Chem . 2026 May 18;74(20):15358–15371. doi: 10.1021/acs.jafc.5c12290 Cover Cropping-Mediated Regulation of Phyllosphere Microbial Health and Rice Yield Dan Wu † , Qiwei An † , Kaifeng Zhou † , Chengcui Yang † , Xingye Yang † , Shunqiang Yang †, ‡, §, ∥, * , Liuxing Xu †, * Author information Article notes Copyright and License information † College of Agronomy and Life Sciences, Zhaotong University, Zhaotong 657000, China ‡ Yunnan Key Laboratory of Gastrodia Elata and Fungal Symbiotic Biology, College of Agronomy and Life Sciences, Zhaotong University, Zhaotong 657000, China § Key Laboratory of Edible Fungi Resources Innovation Utilization and Cultivation, College of Agronomy and Life Sciences, Zhaotong University, Zhaotong 657000, China ∥ Yunnan Key Laboratory of Smart Villages and Agri-Cultural-Tourism Integration, Zhaotong University, Zhaotong 657000, China * Email: ysq6666@163.com . * Email: 20210006@ztu.edu.cn . Received 2025 Sep 15; Accepted 2026 May 11; Revised 2026 May 8; Collection date 2026 May 27. © 2026 The Authors. Published by American Chemical Society This article is licensed under CC-BY-NC-ND 4.0 PMC Copyright notice PMCID: PMC13220304  PMID: 42145272 Abstract Although cover crops are integral to sustainable agriculture, their specific impacts on rice ( Oryza sativa ) disease management and yields remain poorly understood. This 2-year field study (2023–2024) evaluated the effects of winter cover crops [winter fallow, Italian ryegrass ( Lolium multiflorum , IR), and smooth vetch ( Vicia villosa , VV)] on summer rice phyllosphere microbial assembly and yield. Compared to fallow, transpiration rates under VV and IR increased by 31.6% and 25.3%, while net photosynthetic rates increased by 25.0% and 23.9%, respectively ( P < 0.05). Cover crops enriched potentially beneficial taxa (e.g., Pseudomonas and Microbacterium ) and reduced the relative abundance of Erwinia , which is a potential pathogen reservoir. Furthermore, VV and IR enhanced the abundance of functional fungal genera ( Epicoccum , Sporobolomyces , and Rhodotorula ). Compared to fallow, the VV and IR treatments increased the grain yield by 26.77% and 21.26%, respectively. Winter cover cropping with VV and IR is recommended for sustainable, high-yield rice production. Keywords: cover crops, health, phyllosphere microbial communities, rice Introduction With increasing global attention to sustainability and ecological security in agricultural production, cover crops are widely adopted soil management practices that improve productivity and soil health. For example, studies have demonstrated that cover crops contribute to increases in soil organic matter and improvements in soil structure. These changes are accompanied by enhanced water retention and reduced soil erosion. In rice ( Oryza sativa ) production systems, planting forage crops or green manure as cover crops can improve soil physicochemical properties, increase soil organic matter and water-holding capacity, and provide favorable conditions for summer rice growth. Beyond these soil benefits, recent research indicates that cover crops also influence aboveground microbial assembly through plant–soil feedback mechanisms and cover crop–microbiome linkages. However, research investigating how cover crops influence rice photosynthetic performance; phyllosphere physiological, biochemical, and structural traits; and overall plant health through the modulation of phyllosphere microbial communities remains limited, especially considering the unique environmental constraints of the phyllosphere compared with the soil environment. Microbial communities inhabiting the phyllosphere, located on the surface of and within plant leaves, play critical roles in regulating plant nutrition, , stress tolerance, and overall health. Unlike the relatively stable rhizosphere, the phyllosphere is characterized by nutrient limitations, intense UV radiation, and rapid fluctuations in temperature and humidity. , These abiotic factors impose strong selective pressure on microbial colonization. Beneficial bacteria, such as Bacillus , promote plant growth and enhance disease resistance, whereas pathogenic microorganisms, including Xanthomonas and Fusarium , are responsible for leaf spot and ear rot diseases, leading to reductions in crop yield. In addition, phyllosphere fungal communities contribute significantly to plant health, with certain fungi enhancing host stress tolerance by stimulating antioxidant enzyme activities. , Notably, plants are not passively influenced by microorganisms; rather, they regulate the phyllosphere microenvironment through metabolite secretion and physiological processes, thereby affecting the composition and function of microbial communities. This indicates the existence of complex interactions between the plants and microorganisms. For example, under drought stress, plants can modulate phyllosphere microbial composition by adjusting soluble carbohydrate and total phenolic contents, , thereby enhancing their resilience to environmental stressors. Such mechanisms may also operate in rice systems managed with winter cover crops. Empirical studies have demonstrated strong correlations between leaf physiological traits and phyllosphere microbial communities, including photosynthetic parameters, stomatal density, trichome density, and biochemical indicators such as soluble sugars, total phenolics, free amino acids, and vitamin C, which are associated with phyllosphere microbial diversity and composition and collectively influence plant stress tolerance and health status. , Furthermore, cover crops have been shown to indirectly affect phyllosphere microbial community structure and diversity by modifying soil physicochemical properties. Despite these insights, systematic investigations of how belowground management drives phyllosphere microbial dynamics in crop-rotation systems remain limited. Therefore, this study aimed to evaluate how winter cover crops [Italian ryegrass ( Lolium multiflorum , IR) and smooth vetch ( Vicia villosa , VV)] influence rice phyllosphere microbial structure, leaf physiological and biochemical traits, and their association with plant health. This study hypothesized that (1) compared with fallow, cover crops could enhance rice photosynthetic capacity and overall health by improving the leaf microenvironment and regulating phyllosphere microbial communities and (2) changes in phyllosphere nutrients are key factors through which cover crops influence phyllosphere microbial communities. To further reveal microbial dynamics, high-throughput sequencing technology was used to systematically analyze the diversity of phyllosphere bacteria and fungi with the aim of providing a scientific basis for rice health management and sustainable high-yield rice cultivation. Materials and Methods Site Description A 2-year fixed-site cultivation trial was conducted from 2023 to 2024 in Hongnizha Village (27.28°N, 103.60°E: altitude 1989 m), Zhaoyang District, Zhaotong City, Yunnan Province. The local cropping system typically involves a rotation of “winter green manure (or forage/fallow, November to the following April)–summer rice (May–October)–green manure,” with IR and VV as the main winter green manure crops. During the rice-growing season (2023–2024), meteorological conditions were monitored at the experimental site. The results showed that the total rainfall in 2023 and 2024 was 1084 mm (monthly range: 0.8–341.7 mm) and 698 mm (monthly range: 0–232.7 mm), respectively. The average annual temperatures displayed seasonal fluctuations, recorded at 14.4 ± 6.0 °C in 2023 and 14.2 ± 6.4 °C in 2024 ( Figure ). Over the last 30 years, the mean annual temperature and total rainfall were 12.2 °C and 678 mm, respectively. To characterize the baseline soil fertility prior to the experiment, the initial physicochemical properties of the topsoil (0–20 cm) were determined as follows: soil pH, 6.22; organic matter content, 22.14 g kg –1 ; alkali-hydrolyzable nitrogen, 24.05 mg kg –1 ; available phosphorus, 40.17 mg kg –1 ; and available potassium, 55.32 mg kg –1 . 1. Open in a new tab Meteorological data of the experimental site for 2023–2024. Experimental Design and Management A 2-year field experiment was conducted from April 2023 to October 2024 to evaluate the effects of three cover crop treatments (fallow, IR, and VV) under a green manure/fallow–rice rotation system. Cover crops and fallow were grown in November and harvested in April of the following year. Rice was transplanted between late April and early May and harvested in late October, after which cover crops or fallow were re-grown on the same plots. Soil for rice and green manure cultivation was manually tilled to a depth of 20 cm. The experimental plots measured 5 × 8 m, with three replicates per treatment arranged in a randomized complete block design. Adjacent plots were separated by 1 m-wide buffer zones to minimize cross- contamination from treatments. Rice ( Dianheyou 615) was transplanted at a density of 1.38 × 10 5 plants/ha. The seeding rates for IR ( Jiewo , tetraploid annual ryegrass) and VV ( Yunguangzao ) were 30 and 80 kg/ha, respectively. Fertilization and irrigation were managed uniformly across all plots. Specifically, nitrogen (N), phosphorus (P 2 O 5 ), and potassium (K 2 O) were applied at rates of 180, 90, and 120 kg/ha, respectively. Nitrogen fertilizer was applied as urea (46% N) in a split ratio of 5:3:2 at the basal, tillering, and panicle initiation stages, while phosphorus (as calcium superphosphate) and potassium (as potassium chloride) were applied entirely as basal fertilizers. A shallow water layer (3–5 cm) was maintained from transplanting until 1 week before harvest, followed by drainage. Weeds were removed manually at 20 and 40 days after transplanting to avoid confounding effects from herbicide application. No insecticides or fungicides were used during the experiment. Detailed agronomic management practices for rice are summarized in Table . 1. Agronomic Management Information. Year First fertilizer date Second fertilizer date Sowing date Harvest date Growth time (day) 2023 4 Jul. 4 Aug. 28 Apr. 22 Oct. 177 2024 7 Jul. 9 Aug. 24 Apr. 29 Oct. 179 Open in a new tab Field Sampling Sampling was conducted at the flowering stage of rice [decimal codes (DC) 64 (2023) and 69 (2024)]. To account for the difference in total growth duration (177 days in 2023 vs 189 days in 2024), sampling dates were adjusted to strictly align with these developmental stages rather than calendar dates, ensuring physiological consistency between years. All samples were collected on clear days with wind speeds below grade 3 between 09:00 and 11:00 to minimize the influence of circadian rhythms and environmental fluctuations on plant physiological status. For each experimental plot (biological replicate), 50 plants were randomly selected, and flag leaves were collected and pooled to form one composite sample per plot to minimize individual variation. Leaves of similar developmental ages were selected to reduce systematic errors arising from leaf age variation. During sampling, photosynthetic parameters were first measured in the field. The collected leaves were then divided into three categories: the first set was used for structural and physiological measurements, with leaves immediately placed in foam boxes containing ice packs and promptly transported to the laboratory for analysis; the second set was used for biochemical analyses, with leaves excised in the field using sterile scissors, immediately wrapped in aluminum foil, kept on dry ice during transport, and then quickly stored at −20 °C upon arrival at the laboratory; and the third set was used for phyllosphere microbial diversity analysis, with leaves collected under aseptic conditions, immediately flash-frozen in liquid nitrogen, kept at low temperature during transport, and subsequently stored at −80 °C for long-term preservation to ensure the stability of nucleic acids and community structure. To avoid edge effects, all sampling and harvesting were conducted in the central rows of each plot. At the maturity stage (DC 92), rice plants from a 2 m 2 area were harvested from each plot. Whole-plant fresh matter yield was determined immediately after harvest, and the plants were subsequently threshed and air-dried to measure the thousand-seed weight and grain yield. Measurement Methods Structural and Physiological Properties The photosynthetic parameters of rice were measured on clear mornings using a portable photosynthesis system (LI-COR, Lincoln, Nebraska, USA). Fully expanded and mature flag leaves were selected for measurements, and the net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO 2 concentration (Ci), and stomatal conductance (Gs) were recorded. All measurements were conducted between 09:00 and 11:00, and the data were recorded after the parameters stabilized. After collection, the leaves were quickly blotted to remove surface moisture, and their fresh weights were recorded. The basal part of each leaf was then fixed with a thread and fully immersed in deionized water at 4 °C, where it was left in the dark for 4–6 h until fully hydrated to maximum turgor. After removal, surface water was blotted off and the saturated weight was recorded. Dry weight was obtained by subsequently oven-drying the samples at 70 °C for 48 h until constant weight was reached. Moisture retention capacity (MRC, %) was calculated as (MRC, %) = (fresh – dry) × 100/(turgid – dry). The stomatal density was determined in the middle region of the leaf. For stomatal density analysis, leaf fragments (approximately 5 × 5 mm) were excised from the middle region of the flag leaves. The samples were mounted on metallic stubs and observed directly under a scanning electron microscope (SEM300, tungsten filament: CIQTEK Co., Ltd., Hefei, China) at 250× magnification. The field of view was determined using the microscope’s software. For each leaf, stomata were counted in nine randomly selected independent fields, and the mean value was calculated. Trichome density was measured in the same sampling region using identical scanning electron microscope settings. Trichomes were counted within a fixed field of view, and their densities were calculated. Leaf wettability was assessed using contact angle measurements (OCA20; Dataphysics, Germany). A 2 μL droplet of deionized water was placed on the leaf surface, and after stabilization (approximately 5 s), side-view images were captured using a contact angle goniometer. Chemical Properties Leaf wax content was determined by rapid chloroform extraction. The extracts were air-dried in a fume hood and subsequently oven-dried at 60 °C until a constant weight was achieved, ensuring complete evaporation of chloroform residues before weighing. Wax content was expressed per unit leaf area. Vitamin C was extracted using 6% trichloroacetic acid, and ascorbic acid content was calculated based on a standard curve. Soluble protein was extracted with phosphate buffer, reacted with Bradford reagent, and measured at 595 nm. Protein concentration was calculated using a standard curve. Free amino acids were extracted with 80% ethanol, reacted with ninhydrin in a boiling water bath, and measured at 570 nm. Inorganic phosphate was extracted with 1 M HCl. Total phenolics were extracted with 80% methanol, followed by reaction with Folin–Ciocalteu reagent and Na 2 CO 3 , and absorbance was measured at 765 nm. Total phenolic content was quantified using a gallic acid standard curve and expressed as milligrams of gallic acid equivalents per gram of fresh weight. Unless otherwise stated, all biochemical contents were calculated based on leaf fresh weight, and each assay was performed with three technical replicates. Microbial Diversity Sequencing Total microbial DNA was extracted from each composite leaf sample (representing one biological replicate per plot) using a commercial kit (E.Z.N.A. Plant DNA Kit, Omega Biotek, Norcross, GA, USA) according to the manufacturer’s instructions. The extraction process included mechanical disruption and chemical lysis to ensure complete cell wall breakage. DNA concentration and purity were assessed using a NanoDrop spectrophotometer and 1% agarose gel electrophoresis to confirm suitability for downstream amplification. Bacterial communities were amplified using PCR targeting the V3–V4 region of the 16S rRNA gene (primers 779 F /1193R), whereas fungal communities were amplified by PCR targeting the ITS1 region (primers ITS1F/ITS2R). PCR reactions were performed in triplicate using TransStart FastPfu DNA Polymerase (TransGen, Beijing, China) on an ABI GeneAmp 9700 cycler. The thermal cycling conditions were as follows: initial denaturation at 95 °C for 3 min, followed by 27 cycles (for bacteria) or 33 cycles (for fungi) of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 45 s, with a final extension at 72 °C for 10 min. Negative controls (sterile water) were included to exclude contamination. Sequencing was performed on an Illumina MiSeq PE300 platform (v3 chemistry; Illumina, San Diego, USA) following standard protocols. Raw sequences were processed using fastp for quality filtering (Phred score ≥ 20) and merged using FLASH. High-quality sequences were clustered into operational taxonomic units (OTUs) at 97% similarity using UPARSE (version 7.0.1090), and chimeric sequences were identified and removed using UCHIME. Taxonomic classification was performed using the RDP Classifier (version 2.11) against the SILVA database (Release 138) for bacteria and the UNITE database (Release 8.0) for fungi, with a confidence threshold of 0.7. To ensure data comparability, the OTU table was rarefied to a depth of 47,198 reads per sample (the minimum sequencing depth obtained) prior to diversity analyses. Raw sequences were deposited in the NMDC database under accession number NMDC10020026. Statistical Analysis Statistical analyses were performed using data from two growing seasons. For rice leaf structural, physiological, and chemical properties, a two-way analysis of variance (ANOVA) was conducted to evaluate the effects of year (as a fixed factor), cover crop treatment (as a fixed factor), and their interaction. Duncan’s posthoc test (SPSS 26.0 for Windows; SPSS Inc., Chicago, IL, USA) was used to compare differences among treatments. For microbial community analysis, beta diversity was visualized using principal coordinate analysis (PCoA) based on Bray–Curtis distances. To statistically confirm community-level differences, permutational multivariate analysis of variance (PERMANOVA) and analysis of similarities (ANOSIM) were performed using the vegan package in R. Pearson’s correlation analysis was conducted to explore potential associations between environmental factors and microbial indices. To explicitly infer the ecological processes governing microbial community assembly (deterministic vs stochastic), a null model analysis was conducted to calculate the normalized shuffle test (NST). This metric was derived on the basis of the Jaccard dissimilarity index with 1000 random permutations. An NST value of <50% implies that deterministic selection dominates community assembly, whereas an NST value of >50% indicates that stochastic processes dominate. Furthermore, the Sloan neutral community model was applied to quantify the contribution of stochastic processes and estimate community dispersal ability (migration rate, m). The model was fitted using nonlinear least-squares regression to determine the relationship between the occurrence frequency of taxa and their mean relative abundance. When constructing the experimental model, the overall mean, treatment factors (year and cover crop), and residuals were comprehensively considered. Results IR and VV Improved the Physiological Characteristics and Phyllosphere Nutrition of Rice Leaves Photosynthetic Performance Annual climatic variations significantly influenced rice physiology. In the drier, potentially higher-solar-radiation year of 2024, rice leaves exhibited significantly higher photosynthetic capacity than in the wetter year of 2023 ( P = 0.007–0.048, F = 4.57–9.73). Specifically, the Tr, Pn, Ci, and Gs in 2024 increased by 20.4% ( P = 0.026, F = 5.98), 15.3% ( P = 0.048, F = 4.57), 26.2% ( P = 0.007, F = 9.73), and 29.9% ( P = 0.024, F = 6.12), respectively, compared with 2023. Regarding treatment effects, both winter cover crops enhanced rice photosynthetic potential relative to fallow ( P = 0.015–0.151, F = 2.15–5.68). Compared with fallow, Tr increased by 31.6% under VV and 25.3% under IR ( P = 0.016, F = 5.56), while Pn increased by 25.0% and 23.9% ( P = 0.015, F = 5.68), respectively. However, no significant differences were observed between the VV and IR groups ( P > 0.05). The interaction between year and cover crop had no significant effect on any photosynthetic parameters ( P > 0.05, Table ). Consistent with photosynthetic traits, the water retention capacity of rice leaves in VV and IR treatments was significantly higher than that in fallow plots ( P < 0.0001, Figure A). 2. Effects of Year and Cover Crops on the Photosynthetic Characteristics of Rice . Years and crops Tr (μmol m –2 s –1 ) Pn (μmol m –2 s –1 ) Ci (μmol mol –1 ) Gs (μmol m –2 s –1 ) Years (Y) 2023 10.3 ± 0.60b 20.3 ± 0.70b 259 ± 9.16b 581 ± 35.4b 2024 12.4 ± 0.61a 23.4 ± 1.26a 327 ± 4.16a 755 ± 60.2a Crops (C) Fallow 9.50 ± 0.64b 18.8 ± 0.75b 294 ± 14.1 554 ± 42.6 VV 12.5 ± 0.84a 23.5 ± 1.39a 322 ± 8.33 759 ± 89.3 IR 11.9 ± 0.53a 23.3 ± 1.07a 318 ± 6.77 692 ± 46.1 P Y 0.026 0.048 0.007 0.024 C 0.016 0.015 0.151 0.097 Y × C 0.877 0.618 0.802 0.396 Standard error of the means 0.49 0.79 6.28 39.9 F Y 5.98 4.57 9.73 6.12 C 5.56 5.68 2.15 2.74 Open in a new tab a Note: Different lowercase letters in the same column represent a significant difference between experiment years or crops ( P < .05). VV, Vicia villosa ; IR, Italian ryegrass. 2. Open in a new tab Effects of different cover crops on moisture retention capacity, wax content, vitamin C content, and leaf surface structure of rice: (A) Moisture retention capacity, (B) wax, (C) vitamin C, (D) stomatal density, (E) trichome density, and (F) contact angle. Note: Different lowercase letters indicate significant differences ( P < 0.05). MV, mean value; SEM, standard error of the means. VV, Vicia villosa ; IR, Italian ryegrass. Leaf Chemistry Most biochemical indicators, including leaf wax content ( Figure B, P = 0.255) and vitamin C ( Figure C, P = 0.753), showed no significant differences among the three treatments ( P > 0.05). An exception was the free amino acid content, which varied significantly ( Table , P = 0.034, F = 4.25). Notably, the phyllosphere nutrient levels on the leaf surface were significantly lower than those in the whole leaf ( P = 0–0.006, F = 9.95–150.8). 3. Effects of Cover Crops and Leaf Parts on Phyllospheric Nutrients of Rice . Crops and parts Soluble protein (mg/g FM) Soluble sugar (mg/g FM) Free amino acid (mg/kg FM) Inorganic phosphorus (mg/g FM) Total phenolics (mg/g FM) Crops (C) Fallow 0.83 ± 0.33 14.6 ± 5.67 37.8 ± 14.3b 0.12 ± 0.05 10.6 ± 2.37 VV 0.83 ± 0.32 11.8 ± 3.36 18.3 ± 7.12b 0.10 ± 0.04 14.7 ± 1.77 IR 0.82 ± 0.32 11.1 ± 3.96 131 ± 47.8a 0.10 ± 0.02 12.4 ± 1.42 Parts (P) Whole leaf 1.55 ± 0.01a 21.1 ± 2.52a 113 ± 31.8a 0.19 ± 0.02a 15.8 ± 1.51a Leaf surfaces 0.11 ± 0.002b 3.90 ± 0.57b 11.8 ± 3.51b 0.01 ± 0.001b 9.34 ± 0.53b P C 0.999 0.84 0.034 0.934 0.338 P <0.0001 <0.0001 0.006 <0.0001 0.001 C × P 0.51 0.124 0 0.321 0.853 Standard error of the means 0.17 2.44 19.7 0.02 1.10 F Y 0.001 0.18 4.25 0.07 1.17 P 150.8 44.2 9.95 130.6 16.4 Open in a new tab a Note: Different lowercase letters in the same column represent a significant difference between experiment crops or parts ( P < 0.05). FM, fresh matter; VV, Vicia villosa ; IR, Italian ryegrass. Leaf Structural Traits The different cover crop treatments had no significant effects on stomatal density ( Figure D, P = 0.537 and 0.906) or contact angle ( Figure F, P = 0.487 and 0.401) on the adaxial and abaxial leaf surfaces. However, trichome density on the abaxial surface of leaves under the VV treatment was significantly lower than that under the fallow and IR treatments ( Figure F, P = 0.004). Regardless of treatment, rice leaves exhibited structural heterogeneity between surfaces: stomatal density was significantly higher on the abaxial surface ( P < 0.0001), whereas trichome density was higher on the adaxial surface ( P = 0.002). The contact angles did not differ significantly between the two surfaces ( P = 0.311). Effects of Cover Crops on Rice Phyllosphere Bacterial Diversity Cover cropping altered both the composition and structure of rice phyllosphere bacterial communities ( Figure ). PCoA ( Figure A) showed that principal components 1 and 2 explained 54.94 and 28.04% of variation ( R 2 = 0.5465, P = 0.019), respectively. Although the 95% confidence intervals of the three treatments partially overlapped, the bacterial communities were clearly differentiated at the genus level, with pronounced differences between fallow and cover crop treatments ( P < 0.05). Venn analysis indicated that the three treatments shared 27 species (40.3%), whereas the fallow, VV, and IR treatments had 10 (14.92%), 5 (7.46%), and 5 (7.46%) unique species, respectively ( Figure B). Community composition analysis revealed that Pseudomonas , Pantoea , Erwinia , Microbacterium , and Curtobacterium were the dominant genera, but their relative abundances varied among treatments. VV was enriched with Pseudomonas , whereas IR was dominated by Microbacterium ( Figure C). Notably, Erwinia (7.64%) showed the highest relative abundance under fallow conditions, whereas the other four genera had higher relative abundances under the VV or IR treatments ( Table ). 3. Open in a new tab Effects of cover crops on the phyllosphere bacterial community structure of rice. Note: A, triangles indicate the 95% confidence interval ( R 2 = 0.5465, P = 0.019); B, different colors represent different treatments; C, different colors represent the relative abundance of different microbes; D, the Y -axis represents community dispersal ability; E, the Y -axis represents the normalized shuffle test index; F, points of different colors indicate different species; G, stacked bar chart of transient, intermediate, and persistent species distributions; H, ternary diagram of different components; I, node size indicates species abundance, and different colors represent different species; purple indicates positive correlation, green indicates negative correlation; J, mantel test heatmap; K, effects of environmental factors on microbial communities. Tr, transpiration rate; Pn, net photosynthetic rate; Ci, intercellular CO 2 concentration; Gs, stomatal conductance; MRC, moisture retention capacity; VC, vitamin C; AdSD, adaxial stomatal density; AbSD, abaxial stomatal density; AdT, adaxial trichome density; AbT, abaxial trichome density; AdCA, adaxial contact angle; AbCA, abaxial contact angle; WLSP, whole-leaf soluble protein; LSSP, leaf surface soluble protein; WLSS, whole-leaf soluble sugar; LSSS, leaf surface soluble sugar; WLFAA, whole-leaf free amino acids; LSFAA, leaf surface free amino acids; WLIP, whole-leaf inorganic phosphorus; LSIP, leaf surface inorganic phosphorus; WLTP, whole-leaf total phenolics; LSTP, leaf surface total phenolics. VV, Vicia villosa ; IR, Italian ryegrass. 4. Effects of the Top Ten Bacteria and Fungi in Relative Abundance on Plant Growth or Health. Type Species name Potential ecological function reported in the literature Relative abundance sorting Bacteria Pseudomonas Both plant-growth-promoting rhizobacteria or phytopathogens VV > fallow > IR Pantoea It promotes rice growth, mitigates abiotic stress, and suppresses diseases. Alternatively, excessive production of indole-3-acetic acid disrupts the endogenous hormonal balance in rice, leading to root malformation or growth inhibition. The secretion of cellulases, pectinases, and other enzymes degrades rice cell wall structures, facilitating pathogen invasion. Additionally, virulence gene expression is coordinated through signaling molecules (e.g., AHLs), enhancing pathogenicity VV > fallow > IR Erwinia Causes bacterial foot rot Fallow > VV > IR Microbacterium Promotes rice growth and alleviates cold stress IR > fallow > VV Curtobacterium Alleviates salt stress in rice IR > fallow > VV Frigoribacterium Promotes mineral solubilization, produces hydrolytic enzymes and plant hormones, and induces the expression of rice defense genes Fallow > IR > VV Xanthomonas Interferes with host immunity and induces the expression of susceptibility genes, leading to the occurrence of crop leaf blight VV > fallow > IR Paenibacillus Directly promotes plant growth (e.g., nitrogen fixation, phosphate solubilization, and IAA hormone production) and indirectly suppresses pathogens (e.g., through antimicrobial compounds, extracellular enzymes, and induction of systemic resistance) to enhance crop growth and health Fallow > IR > VV Chryseobacterium Enhances crop growth and health by promoting plant growth (e.g., IAA production, nutrient solubilization, and salt stress tolerance) and suppressing pathogens (e.g., through antimicrobial activity or improvement of the rhizosphere microbiome) Fallow > IR > VV Escherichia-Shigella Potential human pathogens IR > fallow > VV Fungi Epicoccum Inhibits the hyphal growth and appressorium formation of Magnaporthe oryzae in rice leaves and activates plant resistance mechanisms (such as peroxidase and β-1,3-glucanase activities), thereby effectively reducing the disease incidence IR > VV > fallow Sporobolomyces Produces carotenoid pigments with antioxidant or antimicrobial potential VV > fallow > IR Vishniacozyma Promotes plant growth, enhances disease resistance, and inhibits pathogenic fungi with multiple functions Fallow > IR > VV Rhodotorula Promotes animal health by improving antioxidant capacity and lipid metabolism VV > fallow > IR Cladosporium Promotes plant growth Fallow > IR > VV Filobasidium By establishing symbiosis with plants, it improves the plant’s growth environment and enhances its stress resistance Fallow > VV > IR Phaeosphaeria Causes leaf spot and ear rot, leading to crop yield reduction IR > VV > fallow Alternaria Enhances plant stress resistance VV > IR > fallow Sampaiozyma During pathogen infection, multiple extracellular hydrolytic enzymes (including but not limited to cellulases, pectinases, and proteases) are secreted to systematically degrade components of the plant cell wall, dismantling the host’s physical and chemical defense barriers and creating favorable conditions for successful pathogen invasion and subsequent spread Fallow > IR > VV Bullera It has a strong biofilm-forming ability and can enhance the activity of various defense-related enzymes in host tissues VV > IR > fallow Open in a new tab Cover crops altered community assembly processes and dispersal characteristics. Based on the Sloan Neutral Community Model, the estimated migration rate, which serves as a quantitative proxy for community dispersal ability, was lower under cover crop treatments than under fallow conditions. Specifically, the m value ( Figure D) decreased from 0.32 (Fallow) to 0.29 (IR) and 0.22 (VV), suggesting that cover crops imposed stronger dispersal limitations on the phyllosphere community. Consistent with this pattern, the NST analysis (where NST > 50% indicates stochastic dominance) revealed that the proportion of stochastic assembly was significantly higher under VV and IR than under fallow conditions ( P < 0.05, Figure E). The ternary plot ( Figure F) and species persistence analysis ( Figure G) further demonstrated that VV and IR altered niche distribution and increased the proportion of persistent taxa. In particular, the proportion of persistent taxa exceeded 98% under IR and VV, whereas transient and intermediate taxa were more prevalent under fallow conditions. Partitioning of beta diversity using Baselga’s framework showed that differences among treatments were primarily driven by species turnover rather than nestedness ( Figure H). The microbial co-occurrence network ( Figure I) and environmental factor analyses ( Figure J,K) showed that bacterial networks under VV and IR were more complex, with higher numbers of nodes and connections and tighter interactions dominated by positive correlations. Mantel test analyses ( Figure J) indicated that photosynthetic parameters and soluble sugars were significantly correlated with phyllosphere bacterial community structure (Mantel’s P < 0.001). A heatmap ( Figure K) revealed that genera such as Serratia and Staphylococcus were positively correlated with photosynthetic and nutrient-related traits under cover cropping. Effects of Cover Crops on Rice Phyllosphere Fungal Diversity The different treatments affected the structure of rice phyllosphere fungal communities. PCoA ( Figure A) showed that cover crops (VV and IR) were clearly separated from fallow within the 95% confidence interval (PC1 = 65.85%, PC2 = 15.89%, R 2 = 0.4428, P = 0.048). OTU sharing and specificity analyses ( Figure B) further supported this result. VV and IR harbored 13 and 20 unique OTUs, respectively, and shared 32 OTUs with the fallow. Differences in the dominant genus compositions were also observed among treatments ( Figure C). Compared with fallow, VV and IR increased the relative abundance of fungi (e.g., Epicoccum , Phaeosphaeria , Alternaria , and Bullera ) and decreased that of low-abundance genera (e.g., Vishniacozyma , Cladosporium , Filobasidium , and Sampaiozyma ). Although the community dispersal ability (assessed using the same method as for bacteria) under IR was higher than that under VV and fallow ( Figure D), the relative proportions of species within the phyllosphere community remained relatively stable across the three treatments ( Figure E). The NST index was significantly higher under fallow than under VV and IR treatments ( Figure F, P < 0.05). Species correlation analysis revealed complex positive and negative relationships and predominantly positive synergistic interactions, with Vishniacozyma , Phaeosphaeria , and Filobasidium occupying key functional positions in the community ( Figure G). Nevertheless, most leaf fungi remained generalist species ( Figure H, 93.33%). Among the multiple environmental factors, Tr and Gs positively affected the relative abundances of Udeniomyces , Alternaria , and Leptosphaerulina ( P < 0.05), whereas Ci, MRC, and Tr negatively affected the relative abundances of Vishniacozyma and Holtermanniella ( P < 0.05) ( Figure I). Further durability analysis ( Figure J) showed that VV (99.95%) and IR (99.85%) increased the proportion of persistent species while reducing the proportions of transient and intermediate species compared to fallow (99.11%). 4. Open in a new tab Effects of cover crops on the phyllosphere fungal community structure of rice. Note: A, triangles indicate the 95% confidence interval ( R 2 = 0.4428, P = 0.048); B, the upper bar chart represents the number of OTUs unique to or shared among different treatments; C, different colors represent the relative abundance of different microbes; D, the Y -axis represents community dispersal ability; E, points of different colors indicate different species; F, the Y -axis represents the normalized shuffle test index; G, node size indicates species abundance, and different colors represent different species; purple indicates positive correlation, green indicates negative correlation; H, niche width scatter plot; I, effects of environmental factors on microbial communities; J, stacked bar chart of transient, intermediate, and persistent species distributions. Tr, transpiration rate; Pn, net photosynthetic rate; Ci, intercellular CO 2 concentration; Gs, stomatal conductance; MRC, moisture retention capacity; VC, vitamin C; AdSD, adaxial stomatal density; AbSD, abaxial stomatal density; AdT, adaxial trichome density; AbT, abaxial trichome density; AdCA, adaxial contact angle; AbCA, abaxial contact angle; WLSP, whole-leaf soluble protein; LSSP, leaf surface soluble protein; WLSS, whole-leaf soluble sugar; LSSS, leaf surface soluble sugar; WLFAA, whole-leaf free amino acids; LSFAA, leaf surface free amino acids; WLIP, whole-leaf inorganic phosphorus; LSIP, leaf surface inorganic phosphorus; WLTP, whole-leaf total phenolics; LSTP, leaf surface total phenolics. VV, Vicia villosa ; IR, Italian ryegrass. Cover Cropping Improved Rice Yield Compared with fallow (26.3 g), thousand-seed weight under VV and IR treatments significantly increased by 7.22 and 5.70%, respectively ( P = 0.001, F = 11.3, Figure A). This enhancement translated into higher productivity: grain yield under VV and IR increased by 26.77 and 21.26%, respectively, relative to the fallow baseline of 3.81 t/ha ( P = 0.023, F = 4.91, Figure B). Similarly, whole-plant fresh matter yield ( P = 0.009, F = 6.65, Figure C) was significantly higher under VV (44.7 t/ha) and IR (42.5 t/ha) treatments than that under fallow (32.9 t/ha). Correlation analyses further revealed specific microbial associations among these traits. Among bacterial taxa ( Figure D), the relative abundance of Pseudomonas tended to be positively correlated with the whole-plant fresh matter yield, whereas Erwinia tended to show negative correlations with both grain and whole-plant fresh matter yields. Within fungal communities ( Figure E), the relative abundances of Epicoccum and Alternaria tended to be positively correlated with the grain yield, while Rhodotorula and Bullera tended to exhibit positive associations with the whole-plant fresh matter yield. 5. Open in a new tab Effects of cover crops on rice yield and correlations with microorganisms: (A) thousand-seed weight, (B) grain yield, (C) whole-plant fresh matter yield, and heatmaps showing the correlations between bacterial (D) or fungal (E) taxa and rice yield traits. Note: Different lowercase letters indicate significant differences ( P < 0.05). GY, grain yield; WFMY, whole-plant fresh matter yield; TW, thousand-seed weight. VV, Vicia villosa ; IR, Italian ryegrass. Discussion Effects of Winter Cover Cropping and Interannual Variation on Photosynthetic Performance and Leaf Traits of Rice Different climatic conditions across years typically influence crop photosynthetic physiology, mainly through the effects of environmental factors such as temperature, light intensity, and precipitation patterns, on photosystem activity and stomatal regulation. Previous studies have demonstrated that adequate water supply and favorable temperature conditions can enhance the photosynthetic potential of rice by improving its light use efficiency and carbon assimilation capacity. However, in this study, despite higher temperature and rainfall during the rice-growing season in 2023 than in 2024, photosynthetic parameters were lower in 2023. This discrepancy suggests that the interannual difference in Pn values likely reflects the variation in sampling stages rather than solely weather conditions alone. This discrepancy may be closely associated with plant developmental stage, as plants sampled in 2023 were at DC64 (halfway anthesis), whereas those in 2024 were at DC69 (complete anthesis), which may account for the observed physiological differences. The heading and flowering stage are recognized as periods during which photosynthetic traits undergo the most dynamic changes. Although soil parameters were not measured in this study, the observed improvement in rice photosynthetic performance under cover cropping treatments may be partially attributed to enhanced soil fertility and microbial activity reported in previous studies. This is another potential explanation for the elevated photosynthetic parameters observed in 2024. Cover cropping also positively affected the photosynthetic performance of rice. In this study, compared with fallow, both VV and IR significantly increased Tr and Pn, indicating that cover crops improved nutrient cycling, thereby creating a more favorable growth environment for rice. The lack of significant differences between VV and IR suggests that different cover crop species may exert functionally redundant effects, improving soil–plant systems through similar ecological processes. With respect to leaf structural traits, cover cropping had no significant effect on stomatal density or contact angle, but the trichome density on the abaxial leaf surface under the VV treatment was significantly lower than that under the fallow and IR treatments. Overall, the stomatal density was significantly higher on the abaxial surface than on the adaxial surface, whereas the trichome density exhibited the opposite pattern. This functional differentiation is closely related to rice leaf adaptations in transpiration regulation and pathogen defense. Regarding chemical composition, nutrient levels on the leaf surface were significantly lower than those within the whole leaf, likely due to microbial uptake and leaching. This discrepancy is expected, as surface nutrients primarily consist of leached metabolites or deposits, representing only a minute fraction of the total nutrient pool stored within the leaf biomass. However, cover crops did not exert significant effects on most chemical traits, indicating that the chemical composition of rice leaves remained relatively stable under short-term cover cropping. Taken together, interannual climatic variability and cover cropping influence photosynthetic performance and structural traits of rice leaves at multiple levels. Annual environmental factors and growth stages primarily drove variations in photosynthetic parameters, whereas cover crops enhanced photosynthetic capacity mainly by improving soil conditions. Crucially, these physiological improvements translated into agronomic benefits, as evidenced by the significant increase in grain yield under VV and IR treatments ( Figure ), confirming that cover cropping effectively optimizes the source–sink relationship in rice production. Cover Crops Reshape Rice Phyllosphere Bacterial Communities In this study, cover crop treatments enriched Pseudomonas (under VV) and Microbacterium (under IR) while reducing the relative abundance of Erwinia ( Figure ). We recognize that the genus Pseudomonas is taxonomically complex, encompassing both plant-growth-promoting rhizobacteria and phytopathogens. Similarly, Erwinia species are established causal agents of bacterial foot rot in rice rather than primary leaf pathogens. , However, the ecological role of these taxa must be interpreted in the context of host phenotype. In this study, enrichment of Pseudomonas under cover cropping was strictly synchronous with enhanced rice photosynthetic capacity ( Table and Figure ) and yield ( Figure ). Correlation analysis further confirmed that the relative abundance of Pseudomonas tended to be positively associated with whole-plant biomass. This positive host–microbiome association suggests that the Pseudomonas strains enriched here likely functioned as beneficial or commensal partners rather than pathogens. To provide causal evidence for this hypothesis, we isolated representative strains from the phyllosphere ( Table S1 ). The isolated Pseudomonas (e.g., P. psychrotolerans ) and Microbacterium (e.g., M. oleivorans ) strains exhibited indole-3-acetic acid (IAA) production capacity (2.65–3.21 mg L –1 ) and enhanced rice seedling height, maximum root length, and fresh weight compared with uninoculated controls ( P < 0.05). Conversely, the high abundance of Erwinia in fallow plots, which coincided with the poorest physiological performance and lowest yield, suggests that fallow management may maintain higher pathogen reservoir pressure or a greater load of nonbeneficial epiphytes. This was corroborated by our isolation of an Erwinia gerundensis strain, which lacked IAA production (<0.01 mg L –1 ) and failed to promote rice growth ( Table S1 ), even if typical foot rot symptoms were not the primary focus of this leaf-level study. Unlike previous studies that primarily focused on soil or rhizosphere bacterial responses to cover cropping, this study provides direct evidence for the regulatory effect of cover crops on rice phyllosphere microbiota, revealing an “aboveground–belowground linkage.” Specifically, cover crops improve microenvironmental conditions and supply organic substrates, , transmitting beneficial signals to the leaf surface and enriching dominant functional taxa. These findings align with previous reports showing that rye cover reduced Pseudomonas syringae incidence on pumpkin leaves, suggesting that cover crops may have cross-species applicability in modulating phyllosphere microbiomes. Moreover, the elevated abundance of Erwinia under fallow, recognized primarily as a causal agent of bacterial foot rot rather than a foliar pathogen, suggests that the leaf surface serves as an epiphytic reservoir. Consequently, its reduction indicates that cover crops may function through a pathogen dilution effect to alleviate the overall pathogen load within the rice ecosystem. Regardless of cover cropping, rice phyllosphere bacterial communities are dominated by aerobic taxa, indicating strong environmental selection on the leaf surface, with ecological niches strongly influenced by light, humidity, and host exudates. Consistently, redundancy analysis (RDA) further identified leaf physiological traitsspecifically photosynthetic parameters ( Figure S1A ) and soluble nutrients ( Figure S1B and C )as significant drivers shaping the phyllosphere microbial community structure. The clustering of cover crop treatments (VV and IR) along vectors of enhanced physiological traits in the RDA confirmed that cover crops drive microbiome succession primarily by optimizing the host leaf microenvironment ( Figure S1 ). Cover crops not only alter community composition but may also modulate network structure and functional potential by altering microenvironmental conditions, thereby providing a microbial mechanism to enhance host plant health. Notably, this study found that VV and IR reduced the “dispersal” of the bacterial community while significantly increasing the proportion of persistent taxa. The increased randomness under cover cropping can be attributed to enhanced substrate availability and microenvironmental heterogeneity, which expand ecological niches to promote random aggregation while simultaneously reducing migration rates to favor taxon persistence. , This observation aligns with the understanding that the phyllosphere, as an exposed and highly fluctuating environment, naturally favors random community assembly processes driven by nutrient dynamics and plant physiological status. However, this differs from reports in some systems where late-stage communities are more strongly governed by deterministic processes, suggesting that crop type and management practices (such as cover cropping) can significantly alter phyllosphere community assembly trajectories, a hypothesis that requires further verification across crops and management systems. Importantly, the combination of increased randomness and higher proportions of persistent taxa provides a potential mechanism for enriching functionally beneficial bacteria. By improving the leaf microenvironment and substrate availability, cover crops not only enhance the colonization of beneficial taxa but may also facilitate their ecological niche dominance during stochastic assembly, thereby optimizing community functional potential. This finding offers new mechanistic insights into how cover crops can improve plant health and suppress potential pathogens and is consistent with previous observations that cover cropping promotes the enrichment of functional taxa, such as Pseudomonas under VV. , This study demonstrated that differences in rice phyllosphere bacterial communities between fallow and cover crop (VV and IR) treatments were primarily driven by species turnover rather than nestedness, indicating that cover crops reshape community structure through the replacement of dominant taxa rather than through “species loss or subset formation.” This mechanism aligns with the commonly observed pattern in microbial communities: “environmental or management perturbation → replacement of dominant taxa → functional site shifts,” and is supported by multiple ecological and microbial studies across diverse systems, which have found that turnover predominantly contributes to total β-diversity. Considering the replacement patterns of Pseudomonas , Microbacterium , and Erwinia observed in this study ( Figure ), it can be inferred that cover crops selectively enrich beneficial or antagonistic taxa, achieving structural optimization through “replacement” rather than functional reduction through diversity loss. Additionally, co-occurrence network analysis revealed that cover crops enhance network connectivity and density, which is consistent with the general principle that environmental stress reduces network complexity. This suggests that cover crops may alleviate stress and increase resource flux, thereby transforming microbial networks from loose or fragmented configurations to dense, highly synergistic structures. Notably, genera such as Serratia and Staphylococcus were positively correlated with photosynthetic and nutrient-related traits. Although species within these genera act as opportunistic pathogens in some contexts, they also encompass strains with reported plant-growth-promoting capabilities. Given their positive correlation with rice physiological performance and yield in this study, we hypothesize that the specific strains enriched here likely function as commensals or beneficial partners rather than pathogens. However, this inference warrants caution, as 16S rRNA amplicon sequencing cannot distinguish pathogenic strains from nonpathogenic ones. This finding suggests a potential association between cover crop-induced network restructuring and host physiological improvement, although the underlying biological mechanisms warrant further investigation. Although the positive effects of cover crops on soil microbial diversity and function are well documented, this study further demonstrates that such effects can propagate along the “root–stem–leaf” continuum to the phyllosphere, resulting in dominant taxa replacement, increased randomness, and network complexity. These findings align with the integrated perspective that plant traits and resource flux shape phyllosphere microbial communities ,, and extend the scope of ecosystem services provided by cover cropsfrom soil conservation and nutrient management to aboveground health management, including pathogen suppression and enrichment of functional microbiota. In the context of rice production systems, considering the biocontrol potential of phyllosphere microbes against diseases such as rice blast, our results provide both practical and theoretical support for the development of a “cover crop–phyllosphere engineering” strategy. Selective Restructuring and Functional Implications of Rice Phyllosphere Fungi under Cover Crops Unlike the broad taxonomic shifts observed in bacteria, cover crops reshaped the rice phyllosphere fungal community primarily through a specific selective pressure and functional redundancy. Specificity analysis revealed that cover crops not only introduced unique fungal taxa but also reorganized existing communities by optimizing phyllosphere microenvironments. ,, In terms of selectivity, cover crop treatments increased the relative abundance of dominant functional genera such as Epicoccum , Sporobolomyces , and Rhodotorula , while reducing the proportion of low-abundance genera such as Vishniacozyma , Cladosporium , Filobasidium , and Sampaiozyma . This selective assembly is consistent with previous studies that reported that cover crops enrich functional fungi by regulating soil or phyllosphere conditions. Notably, Sampaiozyma was more abundant under fallow conditions and Phaeosphaeria was more abundant under IR treatment, whereas some studies have suggested that these fungi may have negative effects on crop growth, , indicating that different management practices may indirectly influence host health by modulating the relative proportions of specific fungi. Overall, the VV treatment had the most pronounced effect on enriching beneficial fungi, which may be related to its ability to enhance the photosynthetic performance and physiological traits of rice ( Table ). This was further supported by correlation analysis, which revealed that the relative abundances of key functional genera, such as Epicoccum and Alternaria , were positively correlated with grain yield ( Figure ), suggesting a potential role for these fungi in promoting reproductive growth. In addition, Tr, which is related to leaf water content or humidity, positively regulates the relative abundances of Udeniomyces , Alternaria , and Leptosphaerulina , further supporting the hypothesis that cover crops promote the enrichment of functional fungi by improving phyllosphere microenvironments (e.g., humidity and substrate availability). Cover crop treatments significantly reduced the NST index of fungi, indicating decreased community randomness and enhanced selective assembly. This finding aligns with recent studies showing that “plant traits and environmental factors drive phyllosphere microbial assembly through selective processes.” , Although community dispersal under IR was higher than under VV or fallow conditions, the stability of species diversity within the community suggests that cover crops primarily select and enrich key functional genera rather than reshaping the community through frequent immigration and emigration, similar to the effects of cover crops on soil fungi. Among various fungi, Vishniacozyma , Phaeosphaeria , and Filobasidium occupied key functional positions, consistent with previous reports that “core species in phyllosphere fungal networks maintain ecosystem functional stability.” In this study, the majority of phyllosphere fungi were generalist species (93.33%, based on niche breadth), indicating high resource-use flexibility in the rice phyllosphere, which contribute to ecosystem stability. By stabilizing phyllosphere microenvironments and resource availability, cover crops improve the colonization of key functional fungi, potentially enhancing community function and host health. , Moreover, this study revealed a link between increased persistence of phyllosphere fungi and selective assembly mechanisms, which has rarely been reported in existing studies on cover crops. Collectively, our results suggest that environmental factors, including leaf water status, nutrient availability, and photosynthetic parameters, modulate microbial niche selection, linking the host physiological status to community assembly mechanisms. By reducing community randomness and reinforcing selective assembly, cover crops promote synergistic interactions within microbial networks, thereby enhancing the phyllosphere community stability and ecosystem resilience. It is important to acknowledge that the functional roles of the microbial taxa identified in microbiome studies are often inferred on the basis of amplicon sequencing and phenotypic associations. Given the dual nature of genera such as Pseudomonas (containing both pathogens and beneficials), sequencing data alone cannot definitively assign causality. However, the integration of agronomic data provides robust phenotypic support for our inferences. Rice plants under cover crop treatments exhibited a healthy host phenotype (higher yield and photosynthetic rates), which strongly supports the hypothesis that the cover crop-restructured microbiome functions beneficially. Crucially, our supplementary culture-dependent assays ( Table S1 ) successfully bridge this gap, moving from ecological correlations to the elucidation of causal mechanisms. By isolating these specific strains and verifying their growth-promoting traits, we confirmed that the specific taxa enriched by cover crops actively contribute to plant health. In conclusion, this study elucidates a cover crop–phyllosphere–yield cascade. Winter cover cropping with IR and VV significantly improved rice yields not only by enhancing photosynthetic capacity and optimizing leaf water status but also by selectively restructuring the phyllosphere microbial community. Crucially, these microbial shifts translate into functional outcomes: the enrichment of potentially beneficial genera (e.g., Pseudomonas ) and the suppression of pathogen reservoirs (e.g., Erwinia ) likely contribute to enhanced pathogen suppression and physiological efficiency. This functional optimization of the phyllosphere microbiome, coupled with improved photosynthetic capacity, ultimately underpins the observed stability in the rice yield. Therefore, adopting Vicia villosa or Italian ryegrass is recommended as a strategy to maximize both productivity and ecosystem health in sustainable rice systems. Supplementary Material jf5c12290_si_001.pdf (574.6KB, pdf) Acknowledgments This work was supported by the Research on Evaluation and Innovative Utilization of Gastrodia elata Germplasm Resources (FWCY-ZNT2024026), the Project for Reserve Talents of Young and Middle-aged Academic and Technical Leaders (202305AC160057), Xingzhao Talent Support Program (2023), and the Special Basic Cooperative Research Programs of Yunnan Provincial Undergraduate Universities Association (202501BA070001-002). Sequestration data for microorganisms were stored in NMDC ( https://nmdc.cn/ ) with BioProject accession number NMDC10020026. The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jafc.5c12290 . Effects of inoculation with different bacterial strains on the growth and physiological indices of rice (Table S1) and redundancy analysis of environmental factors and rice phyllosphere microbial community structures (Figure S1) ( PDF ) The authors declare no competing financial interest. References Seitz V. A., McGivern B. B., Borton M. A., Chaparro J. M., Schipanski M. E., Prenni J. E., Wrighton K. C.. Cover crop root exudates impact soil microbiome functional trajectories in agricultural soils. Microbiome. 2024;12(1):183. doi: 10.1186/s40168-024-01886-x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Vukicevich E., Lowery T., Bowen P., Úrbez-Torres J. R., Hart M.. Cover crops to increase soil microbial diversity and mitigate decline in perennial agriculture. A review. Agron. Sustainable Dev. 2016;36(3):48. doi: 10.1007/s13593-016-0385-7. [ DOI ] [ Google Scholar ] Xu L., Tang G., Tian J., Wang X., Zhang J.. Effects of no-tillage sowing on soil properties and forage wheat and Italian ryegrass yields in winter fallow paddy fields. PeerJ. 2021;9:e10573. doi: 10.7717/peerj.10573. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Nascimento G., Catala-Forner M., Villegas D., Ferre O., Tomàs N., Cantero-Martínez C.. Enhancing soil organic carbon and structure in Mediterranean rice systems through cover cropping. Soil Tillage Res. 2026;255:106777. doi: 10.1016/j.still.2025.106777. [ DOI ] [ Google Scholar ] Yue Q., Sun J., Hillier J., Sheng J., Guo Z., Zhu P., Cheng K., Pan G., Li Y., Wang X.. Green manure rotation and application increase rice yield and soil carbon in the Yangtze River valley of China. Pedosphere. 2023;33(4):589–599. doi: 10.1016/j.pedsph.2022.11.009. [ DOI ] [ Google Scholar ] Cao M., Xiang Y., He H., Cheng J., Song Y., Jin C., Xin G., He C.. Italian ryegrass (Lolium multiflorum L.)-rice (Oryza sativa L.) rotation promotes the nitrogen cycle in the rice rhizosphere through dominant ammonia-oxidizing bacteria. Appl. Soil Ecol. 2024;193:105121. doi: 10.1016/j.apsoil.2023.105121. [ DOI ] [ Google Scholar ] Maglione R., Ciotola M., Cadieux M., Toussaint V., Laforest M., Kembel S. W.. Winter rye cover cropping changes squash (Cucurbita pepo) phyllosphere microbiota and reduces Pseudomonas syringae symptoms. Phytob. J. 2022;6(1):3–12. doi: 10.1094/PBIOMES-04-21-0029-R. [ DOI ] [ Google Scholar ] Lindow S. E., Brandl M. T.. Microbiology of the Phyllosphere. Appl. Environ. Microbiol. 2003;69(4):1875–1883. doi: 10.1128/AEM.69.4.1875-1883.2003. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Thomas G., Kay W. T., Fones H. N.. Life on a leaf: the epiphyte to pathogen continuum and interplay in the phyllosphere. BMC Biol. 2024;22(1):168. doi: 10.1186/s12915-024-01967-1. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Luo K., Zhao G., Chen M., Tian X.. Effects of maize resistance and leaf chemical substances on the structure of phyllosphere fungal communities. Front. Plant Sci. 2023;14:1241055. doi: 10.3389/fpls.2023.1241055. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Danso Ofori A., Su W., Zheng T., Datsomor O., Titriku J. K., Xiang X., Kandhro A. G., Ahmed M. I., Mawuli E. W., Awuah R. T., Zheng A.. Roles of phyllosphere microbes in rice health and productivity. Plants. 2024;13(23):3268. doi: 10.3390/plants13233268. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Qian Y., Jin Y., Han X., Malik K., Li C., Yu B.. Effects of grazing and leaf spot disease on the structure and diversity of phyllosphere microbiome communities in Leymus chinensis . Plants. 2024;13(15):2128. doi: 10.3390/plants13152128. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Knoll D., Schreiber L.. Plant-microbe interactions: wetting of ivy (Hedera helix L.) leaf surfaces in relation to colonization by epiphytic microorganisms. Microb. Ecol. 2000;40(1):33–42. doi: 10.1007/s002480000012. [ DOI ] [ PubMed ] [ Google Scholar ] Singh S., Shyu D. J. H.. Perspective on utilization of Bacillus species as plant probiotics for different crops in adverse conditions. AIMS Microbiol. 2024;10(1):220–238. doi: 10.3934/microbiol.2024011. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Zhao Y., Laborda P., Han S. W., Liu F.. Editorial: Pathogenic mechanism and biocontrol of Xanthomonas on plants. Front. Cell Infect. Microbiol. 2023;13:1270750. doi: 10.3389/fcimb.2023.1270750. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Singh H., Kaur H., Hunjan M. S., Sharma S.. Unveiling toxigenic Fusarium species causing maize ear rot: insights into fumonisin production potential. Front. Plant Sci. 2025;16:1516644. doi: 10.3389/fpls.2025.1516644. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Yang H., Liu J., Ma M., Tan Z., Zhang K., Sun R., Zhan X., Cui D.. Leaf development and its interaction with phyllospheric microorganisms: impacts on plant stress responses. Plant Stress. 2025;16:100843. doi: 10.1016/j.stress.2025.100843. [ DOI ] [ Google Scholar ] Zong J., Zhang Z., Huang P., Yang Y.. Arbuscular mycorrhizal fungi alleviates salt stress in Xanthoceras sorbifolium through improved osmotic tolerance, antioxidant activity, and photosynthesis. Front. Microbiol. 2023;14:1138771. doi: 10.3389/fmicb.2023.1138771. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Schäfer M., Pacheco A. R., Kunzler R., Bortfeld-Miller M., Field C. M., Vayena E., Hatzimanikatis V., Vorholt J. A.. Metabolic interaction models recapitulate leaf microbiota ecology. Science. 2023;381(6653):eadf5121. doi: 10.1126/science.adf5121. [ DOI ] [ PubMed ] [ Google Scholar ] Sharma A., Das N., Pandey P., Shukla P.. Plant-microbiome responses under drought stress and their metabolite-mediated interactions towards enhanced crop resilience. Curr. Plant Biol. 2025;43:100513. doi: 10.1016/j.cpb.2025.100513. [ DOI ] [ Google Scholar ] Li M., Hong L., Ye W., Wang Z., Shen H.. Phyllosphere bacterial and fungal communities vary with host species identity, plant traits and seasonality in a subtropical forest. Environ. Microbiome. 2022;17(1):29. doi: 10.1186/s40793-022-00423-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Tang G., Xu L., Wang X., Zhang J.. Effects of leaf morphological and chemical properties on the population sizes of epiphytes. Microb. Ecol. 2023;85(1):157–167. doi: 10.1007/s00248-022-01963-4. [ DOI ] [ PubMed ] [ Google Scholar ]; b Yang S., Zhang Y., Liu S., Lang Q., Bao L., Yang C., Xu L.. Effects of cropland and cultivars on phyllosphere bacterial communities in forage crops in Southwest China. Grassland Sci. 2025;71(4):164–178. doi: 10.1111/grs.70008. [ DOI ] [ Google Scholar ] Xu L., Chen C., He C., Abd El Tawab A. M., Liu Q., Jiang H.. Effects of irrigation and nitrogen management on phyllosphere microbial communities of silage maize. PeerJ. 2025;13:e19663. doi: 10.7717/peerj.19663. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Ni Y., Sun Z., Huang X., Huang C., Guo Y.. Variations of cuticular wax in mulberry trees and their effects on gas exchange and post-harvest water loss. Acta Physiol. Plantarum. 2015;37(6):112. doi: 10.1007/s11738-015-1856-1. [ DOI ] [ Google Scholar ] Bi H., Kovalchuk N., Langridge P., Tricker P. J., Lopato S., Borisjuk N.. The impact of drought on wheat leaf cuticle properties. BMC Plant Biol. 2017;17(1):85. doi: 10.1186/s12870-017-1033-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Bewick T. A., Shilling D. G., Querns R.. Evaluation of epicuticular wax removal from whole leaves with chloroform. Weed Technol. 1993;7(3):706–716. doi: 10.1017/S0890037X00037581. [ DOI ] [ Google Scholar ] Stevens R., Buret M., Garchery C., Carretero Y., Causse M.. Technique for rapid, small-scale analysis of vitamin c levels in fruit and application to a tomato mutant collection. J. Agric. Food Chem. 2006;54(17):6159–6165. doi: 10.1021/jf061241e. [ DOI ] [ PubMed ] [ Google Scholar ] Bradford M. M.. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 1976;72(1):248–254. doi: 10.1016/0003-2697(76)90527-3. [ DOI ] [ PubMed ] [ Google Scholar ] Wang W.. Improving the method for determining the total dissociative amino acid in fresh plant tissue. J. Beijing Agric. College. 1998;9:1–13. [ Google Scholar ] Hande P. A., Mondal S., Badigannavar A. M., D’Souza S. F.. Genetic variability of phytic acid phosphorus and inorganic phosphorus in cultivated groundnut (Arachis hypogaea L.) Plant Genetic Resour. 2013;11(3):190–195. doi: 10.1017/S1479262113000130. [ DOI ] [ Google Scholar ] Yoo K. M., Lee K. W., Park J. B., Lee H. J., Hwang I. K.. Variation in major antioxidants and total antioxidant activity of yuzu (Citrus junos Sieb ex Tanaka) during maturation and between cultivars. J. Agric. Food Chem. 2004;52(19):5907–5913. doi: 10.1021/jf0498158. [ DOI ] [ PubMed ] [ Google Scholar ] Guo M., Wu F., Hao G., Qi Q., Li R., Li N., Wei L., Chai T.. Bacillus subtilis improves immunity and disease resistance in rabbits. Front. Immunol. 2017;8:354. doi: 10.3389/fimmu.2017.00354. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Li X., Tian J., Zhang Q., Jiang Y., Wu Z., Yu Z.. Effects of mixing red clover with alfalfa at different ratios on dynamics of proteolysis and protease activities during ensiling. J. Dairy Sci. 2018;101(10):8954–8964. doi: 10.3168/jds.2018-14763. [ DOI ] [ PubMed ] [ Google Scholar ] Baselga A.. Partitioning the turnover and nestedness components of beta diversity. Global Ecol. Biogeogr. 2010;19(1):134–143. doi: 10.1111/j.1466-8238.2009.00490.x. [ DOI ] [ Google Scholar ] a Caine R. S., Yin X., Sloan J., Harrison E. L., Mohammed U., Fulton T., Biswal A. K., Dionora J., Chater C. C., Coe R. A.. et al. Rice with reduced stomatal density conserves water and has improved drought tolerance under future climate conditions. New Phytol. 2019;221(1):371–384. doi: 10.1111/nph.15344. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Zhang J., Chen X., Song Y., Gong Z.. Integrative regulatory mechanisms of stomatal movements under changing climate. J. Integr. Agric. 2024;66(3):368–393. doi: 10.1111/jipb.13611. [ DOI ] [ PubMed ] [ Google Scholar ] Gu J., Zhou Z., Li Z., Chen Y., Wang Z., Zhang H., Yang J.. Photosynthetic Properties and Potentials for Improvement of Photosynthesis in Pale Green Leaf Rice under High Light Conditions. Front. Plant Sci. 2017;8:1082. doi: 10.3389/fpls.2017.01082. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Honda S., Ohkubo S., San N. S., Nakkasame A., Tomisawa K., Katsura K., Ookawa T., Nagano A. J., Adachi S.. Maintaining higher leaf photosynthesis after heading stage could promote biomass accumulation in rice. Sci. Rep. 2021;11(1):7579. doi: 10.1038/s41598-021-86983-9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Cai S., Zhang W., Wang B., Wang H., Guo Q., Dai Y., Gong L., Shi H.. Effects of sediment content, flooding, and drainage process on rice growth and leaf physiology of early rice during heading–flowering stage. Agronomy. 2025;15(2):334. doi: 10.3390/agronomy15020334. [ DOI ] [ Google Scholar ] Jiang Y., Zhang J., Manuel D. B., Op de Beeck M., Shahbaz M., Chen Y., Deng X., Xu Z., Li J., Liu Z.. Rotation cropping and organic fertilizer jointly promote soil health and crop production. J. Environ. Manage. 2022;315:115190. doi: 10.1016/j.jenvman.2022.115190. [ DOI ] [ PubMed ] [ Google Scholar ] Lizcano Toledo R., Lerda C., Moretti B., Miniotti E., Santoro V., Fernandez-Ondoño E., Martin M., Said-Pullicino D., Romani M., Celi L.. Cover Crops Increase N and P Cycling and Rice Productivity in Temperate Cropping Systems. Agronomy. 2022;12(9):2193. doi: 10.3390/agronomy12092193. [ DOI ] [ Google Scholar ] a Meddya S., Meshram S., Sarkar D., S R., Datta R., Singh S., Avinash G., Kumar Kondeti A., Savani A. K., Thulasinathan T.. Plant stomata: an unrealized possibility in plant defense against invading pathogens and stress tolerance. Plants. 2023;12(19):3380. doi: 10.3390/plants12193380. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Gahir S., Bharath P., Raghavendra A. S.. Stomatal closure sets in motion long-term strategies of plant defense against microbial pathogens. Front. Plant Sci. 2021;12:761952. doi: 10.3389/fpls.2021.761952. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Perreault R., Laforest-Lapointe I.. Plant-microbe interactions in the phyllosphere: facing challenges of the anthropocene. ISME J. 2022;16(2):339–345. doi: 10.1038/s41396-021-01109-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Xu N., Zhao Q., Zhang Z., Zhang Q., Wang Y., Qin G., Ke M., Qiu D., Peijnenburg W., Lu T., Qian H.. Phyllosphere microorganisms: sources, drivers, and their interactions with plant hosts. J. Agric. Food Chem. 2022;70(16):4860–4870. doi: 10.1021/acs.jafc.2c01113. [ DOI ] [ PubMed ] [ Google Scholar ] Sultana R., Jashim A. I. I., Islam S. M. N., Rahman M. H., Haque M. M.. Bacterial endophyte Pseudomonas mosselii PR5 improves growth, nutrient accumulation, and yield of rice (Oryza sativa L.) through various application methods. BMC Plant Biol. 2024;24(1):1030. doi: 10.1186/s12870-024-05649-6. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Liu H., Qiu H., Zhao W., Cui Z., Ibrahim M., Jin G., Li B., Zhu B., Xie G.. Genome sequence of the plant pathogen Pseudomonas syringae pv. panici LMG 2367. J. Bacteriol. 2012;194(20):5693–5694. doi: 10.1128/JB.01267-12. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Wang W., Zhai Y., Cao L., Tan H., Zhang R.. Endophytic bacterial and fungal microbiota in sprouts, roots and stems of rice (Oryza sativa L.) Microbiol. Res. 2016;188–189:1–8. doi: 10.1016/j.micres.2016.04.009. [ DOI ] [ PubMed ] [ Google Scholar ] Xue Y., Hu M., Chen S., Hu A., Li S., Han H., Lu G., Zeng L., Zhou J.. Enterobacter asburiae and Pantoea ananatis causing rice bacterial blight in China. Plant Dis. 2021;105(8):2078–2088. doi: 10.1094/PDIS-10-20-2292-RE. [ DOI ] [ PubMed ] [ Google Scholar ] Li G., Chen X., Qin W., Chen J., Leng K., Sun L., Liu M., Wu M., Fan J., Xu C., Liu J.. Characteristics of the microbial communities regulate soil multi-functionality under different cover crop amendments in Ultisol. J. Integr. Agric. 2024;23(6):2099–2111. doi: 10.1016/j.jia.2023.11.050. [ DOI ] [ Google Scholar ] Qi G., Chen S., Ke L., Ma G., Zhao X.. Cover crops restore declining soil properties and suppress bacterial wilt by regulating rhizosphere bacterial communities and improving soil nutrient contents. Microbiol. Res. 2020;238:126505. doi: 10.1016/j.micres.2020.126505. [ DOI ] [ PubMed ] [ Google Scholar ] Yuan Q. S., Gao Y., Wang L., Wang X., Wang L., Ran J., Ou X., Wang Y., Xiao C., Jiang W.. et al. Pathogen-driven Pseudomonas reshaped the phyllosphere microbiome in combination with Pseudostellaria heterophylla foliar disease resistance via the release of volatile organic compounds. Environ. Microbiome. 2024;19(1):61. doi: 10.1186/s40793-024-00603-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Ghosh D., Shi Y., Zimmermann I. M., Sturzebecher T., Holzhauser K., von Bergen M., Kaster A. K., Spielvogel S., Dippold M. A., Muller J. A., Jehmlich N.. Cover crop monocultures and mixtures enhance bacterial abundance and functionality in the maize root zone. ISME Commun. 2024;4(1):ycae132. doi: 10.1093/ismeco/ycae132. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Sahu K. P., Patel A., Kumar M., Sheoran N., Mehta S., Reddy B., Eke P., Prabhakaran N., Kumar A.. Integrated metabarcoding and culturomic-based microbiome profiling of rice phyllosphere reveal diverse and functional bacterial communities for blast disease suppression. Front. Microbiol. 2021;12:780458. doi: 10.3389/fmicb.2021.780458. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Chen W., Gao Y., Yang J., Fan F., Zhang W., Li J., Zhou C., Shi G., Tong F., Fan G.. Taxonomical and functional bacterial community selection in the rhizosphere of the rice genotypes with different nitrogen use efficiencies. Plant Soil. 2022;470(1–2):111–125. doi: 10.1007/s11104-021-05170-x. [ DOI ] [ Google Scholar ] Lan G., Wei Y., Zhang X., Wu Z., Ji K., Xu H., Chen B., He F.. Assembly and maintenance of phyllosphere microbial diversity during rubber tree leaf senescence. Commun. Biol. 2024;7(1):1192. doi: 10.1038/s42003-024-06907-x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Li Y., Wang J., Pan J., Zhang R., Zhou B., Niu S.. Divergent assembly processes of phyllosphere and rhizosphere microbial communities along environmental gradient. Plant, Cell Environ. 2025;48(2):1380–1392. doi: 10.1111/pce.15224. [ DOI ] [ PubMed ] [ Google Scholar ] a Powell J. R., Karunaratne S., Campbell C. D., Yao H., Robinson L., Singh B. K.. Deterministic processes vary during community assembly for ecologically dissimilar taxa. Nat. Commun. 2015;6:8444. doi: 10.1038/ncomms9444. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Harris M. A., Kemler M., Slippers B., Jamison-Daniels S.-L., Witfeld F., Botha M., Begerow D., Brachmann A., Greve M.. Deterministic processes have limited impacts on foliar fungal endophyte communities along a savanna-forest successional gradient. Fungal Ecol. 2023;64:101249. doi: 10.1016/j.funeco.2023.101249. [ DOI ] [ Google Scholar ] Sahu K. P., Kumar A., Sakthivel K., Reddy B., Kumar M., Patel A., Sheoran N., Gopalakrishnan S., Prakash G., Rathour R., Gautam R. K.. Deciphering core phyllomicrobiome assemblage on rice genotypes grown in contrasting agroclimatic zones: implications for phyllomicrobiome engineering against blast disease. Environ. Microbiome. 2022;17(1):28. doi: 10.1186/s40793-022-00421-5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Ochieng B., Wu H., Zhou Y., Meng F., Xu J., Zhang L., Kimirei I. A., Wang J.. Beta diversity patterns and driving mechanisms of stream bacteria and fungi on Mt. Kilimanjaro. Ecol. Inf. 2024;82:102747. doi: 10.1016/j.ecoinf.2024.102747. [ DOI ] [ Google Scholar ] a Gao C., Xu L., Montoya L., Madera M., Hollingsworth J., Chen L., Purdom E., Singan V., Vogel J., Hutmacher R. B.. et al. Co-occurrence networks reveal more complexity than community composition in resistance and resilience of microbial communities. Nat. Commun. 2022;13(1):3867. doi: 10.1038/s41467-022-31343-y. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Liu J., Sun X., Zuo Y., Hu Q., He X.. Plant species shape the bacterial communities on the phyllosphere in a hyper-arid desert. Microbiol. Res. 2023;269:127314. doi: 10.1016/j.micres.2023.127314. [ DOI ] [ PubMed ] [ Google Scholar ] Mehlferber E. C., Debray R., Conover A. E., Sherman J. K., Kaulbach G., Reed R., McCue K. F., Ferrel J. E., Khanna R., Koskella B.. Phyllosphere microbial associations improve plant reproductive success. Front. Plant Sci. 2023;14:1273330. doi: 10.3389/fpls.2023.1273330. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Santoyo G.. How plants recruit their microbiome? New insights into beneficial interactions. J. Adv. Res. 2022;40:45–58. doi: 10.1016/j.jare.2021.11.020. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Kong Z., Li T., Glick B. R., Liu H.. Priority effects of inoculation timing of plant growth-promoting microbial inoculants: role, mechanisms and perspectives. Plant Soil. 2025;513:1675–1687. doi: 10.1007/s11104-025-07291-z. [ DOI ] [ Google Scholar ] Tang G., Fan Y., Li X., Tian R., Tang R., Xu L., Zhang J.. Effects of leaf properties on the counts of microbes on the leaf surfaces of wheat, rye and triticale. FEMS Microbiol. Ecol. 2023;99(4):fiad024. doi: 10.1093/femsec/fiad024. [ DOI ] [ PubMed ] [ Google Scholar ] Liu C.-Y., Wang Y.-y., Chen X.-y., Tan H., Jin X.-m., Lu Q., He S.-b., Long M.-X.. Cover cropping increases soil fungal-bacterial community diversity and network complexity in apple orchards on the Loess Plateau, China. Front. Environ. Sci. 2022;10:916288. doi: 10.3389/fenvs.2022.916288. [ DOI ] [ Google Scholar ] Yin Y., Wang Y. F., Cui H. L., Zhou R., Li L., Duan G. L., Zhu Y. G.. Distinctive structure and assembly of phyllosphere microbial communities between wild and cultivated rice. Microbiol. Spectrum. 2023;11(1):e04371–04322. doi: 10.1128/spectrum.04371-22. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Ye, G. ; Wang, H. ; Li, T. ; Wang, F. ; Xu, B. . Responses of phyllosphere microbiota and plant health to application of bordeaux mixture. 2023. 10.21203/rs.3.rs-3649527/v1. [ DOI ] [ PMC free article ] [ PubMed ] Soliman S. A., Abdelhameed R. E., Metwally R. A.. In vivo and In vitro evaluation of the antifungal activity of the PGPR Bacillus amyloliquefaciens RaSh1 (MZ945930) against Alternaria alternata with growth promotion influences on Capsicum annuum L. plants. Microb. Cell Fact. 2023;22(1):70. doi: 10.1186/s12934-023-02080-8. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Wang D., Wan Y., Liu D., Wang N., Wu J., Gu Q., Wu H., Gao X., Wang Y.. Immune-enriched phyllosphere microbiome in rice panicle exhibits protective effects against rice blast and rice false smut diseases. iMeta. 2024;3(4):e223. doi: 10.1002/imt2.223. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Long J., Luo W., Xie J., Yuan Y., Wang J., Kang L., Li Y., Zhang Z., Hong M.. Environmental factors influencing phyllosphere bacterial communities in giant pandas’ staple food bamboos. Front. Microbiol. 2021;12:748141. doi: 10.3389/fmicb.2021.748141. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Lajoie G., Dariel L.. How useful are plant traits in explaining variation in phyllosphere microbial abundance and composition across hosts? Environ. Microbiol. 2025;27(6):e70123. doi: 10.1111/1462-2920.70123. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Cloutier M. L., Murrell E., Barbercheck M., Kaye J., Finney D., Garcia-Gonzalez I., Bruns M. A.. Fungal community shifts in soils with varied cover crop treatments and edaphic properties. Sci. Rep. 2020;10(1):6198. doi: 10.1038/s41598-020-63173-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Zhang G., Shi L., Liu C., Mao R., Xia B., Huang Z., Wei X., Wu L., Zheng Y., Wei G.. et al. Modules in robust but low-efficiency phyllosphere fungal networks drive saponin accumulation in leaves of different Panax species. Environ. Microbiome. 2023;18(1):57. doi: 10.1186/s40793-023-00516-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Doni F., Suhaimi N. S. M., Irawan B., Mohamed Z., Mispan M. S.. Associations of Pantoea with rice plants: as friends or foes? Agriculture. 2021;11(12):1278. doi: 10.3390/agriculture11121278. [ DOI ] [ Google Scholar ] Lv L., Luo J., Ahmed T., Zaki H. E. M., Tian Y., Shahid M. S., Chen J., Li B.. Beneficial effect and potential risk of Pantoea on rice production. Plants. 2022;11(19):2608. doi: 10.3390/plants11192608. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Shi F., Zhu S., Li H., Zhang B., Liu J., Song F.. Further enhancement of cold tolerance in rice seedlings by Piriformospora indica collaborating with plant growth-promoting bacteria: Evidence from the antioxidant defense, osmoregulation, photosynthesis, and related genes. Plant Stress. 2024;14:100656. doi: 10.1016/j.stress.2024.100656. [ DOI ] [ Google Scholar ] Vimal S. R., Patel V. K., Singh J. S.. Plant growth promoting Curtobacterium albidum strain SRV4: An agriculturally important microbe to alleviate salinity stress in paddy plants. Ecol. Indic. 2019;105:553–562. doi: 10.1016/j.ecolind.2018.05.014. [ DOI ] [ Google Scholar ] Patel A., Sahu K. P., Mehta S., Javed M., Balamurugan A., Ashajyothi M., Sheoran N., Ganesan P., Kundu A., Gopalakrishnan S.. et al. New insights on endophytic Microbacterium-assisted blast disease suppression and growth promotion in rice: revelation by polyphasic functional characterization and transcriptomics. Microorganisms. 2023;11(2):362. doi: 10.3390/microorganisms11020362. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Grady E. N., MacDonald J., Liu L., Richman A., Yuan Z. C.. Current knowledge and perspectives of Paenibacillus: a review. Microb. Cell Fact. 2016;15(1):203. doi: 10.1186/s12934-016-0603-7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] a Bhise K. K., Bhagwat P. K., Dandge P. B.. Synergistic effect of Chryseobacterium gleum sp. SUK with ACC deaminase activity in alleviation of salt stress and plant growth promotion in Triticum aestivum L. 3 Biotech. 2017;7(2):105. doi: 10.1007/s13205-017-0739-0. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]; b Jung H., Lee D., Lee S., Kong H. J., Park J., Seo Y. S.. Comparative genomic analysis of Chryseobacterium species: deep insights into plant-growth-promoting and halotolerant capacities. Microb. Genomics. 2023;9(10):1108. doi: 10.1099/mgen.0.001108. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Liang Z., Hao Y., Yang L., Yuan P., Kang W., Liang T., Gu B., Dong B.. The potential of Klebsiella and Escherichia-Shigella and amino acids metabolism to monitor patients with postmenopausal osteoporosis in northwest China. BMC Microbiol. 2023;23(1):199. doi: 10.1186/s12866-023-02927-5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Sena A. P., Chaibub A., Côrtes M., Silva G., Silva-Lobo V., Prabhu A., Filippi M., Araújo L.. Increased enzymatic activity in rice leaf blast suppression by crude extract of Epicoccum sp. Trop. Plant Pathol. 2013;38(5):387–397. doi: 10.1590/S1982-56762013005000028. [ DOI ] [ Google Scholar ] Manimala M., Murugesan R.. Characterization of carotenoid pigment production from yeast Sporobolomyces sp. and their application in food products. J. Pharm. Phytochem. 2018;7(15):2818–2821. [ Google Scholar ] Liu S., Cai D., Chai C., Hui F.. et al. Five new epiphytic species of Vishniacozyma (Bulleribasidiaceae, Tremellales) from China. MycoKeys. 2025;113:321–336. doi: 10.3897/mycokeys.113.140598. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Lu X., Ma H., Liu Y., Chen M., Dang J., Su X., Zhao Y., Wang K., Yang G., Zhang G.. et al. Rhodotorula yeast culture improved the antioxidant capacity, lipid metabolism, and immunity of sheep livers. Vet. Sci. 2025;12(4):314. doi: 10.3390/vetsci12040314. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Li Z. T., Janisiewicz W. J., Liu Z., Callahan A. M., Evans B. E., Jurick W. M., Dardick C.. Exposure in vitro to an environmentally isolated strain TC09 of Cladosporium sphaerospermum triggers plant growth promotion, early flowering, and fruit yield increase. Front. Plant Sci. 2019;9:1959. doi: 10.3389/fpls.2018.01959. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Cai S., Lv W., Zhu H., Zhang D., Fu Z., Zhang H., Xu S.. Effect of nitrogen application rate on soil fungi community structure in a rice-fish mutualistic system. Sci. Rep. 2019;9(1):16188. doi: 10.1038/s41598-019-52602-x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Luo W., Ping X., Zhou J., Gao S., Huang X., Song S., Xu J., He W.. Alternaria alternata JTF001 metabolites recruit beneficial microorganisms to reduce the parasitism of orobanche aegyptiaca in tomato. Biology. 2025;14(2):116. doi: 10.3390/biology14020116. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Yu X., Zhang K., Liu J., Zhao Z., Guo B., Wang X., Xiang W., Zhao J.. Identification and evaluation of an endophytic antagonistic yeast for the control of gray mold (Botrytis cinerea) in apple and mechanisms of action. Food Microbiol. 2024;123:104583. doi: 10.1016/j.fm.2024.104583. [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials jf5c12290_si_001.pdf (574.6KB, pdf) Data Availability Statement Sequestration data for microorganisms were stored in NMDC ( https://nmdc.cn/ ) with BioProject accession number NMDC10020026. 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