Correlation Between Rhizosphere Soil Properties and Microbial Communities of Different Coffea arabica Cultivars

Abstract

This study investigated the differences in rhizosphere soil properties and their associations with microbial communities across eight Coffea arabica cultivars cultivated under uniform conditions at the Kangping Education and Research Base in Pu’er, Yunnan. We assessed arbuscular mycorrhizal fungi (AMF) colonization and spore density, analyzed soil chemical properties—including pH, organic matter (OM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and slowly available potassium (SK)—and characterized microbial communities via high-throughput sequencing. The findings of this study demonstrate that coffee variety significantly influences the contents of available nutrients (AN, AP, AK) and OM in the rhizosphere soil. Sequencing indicated that Ascomycota dominated the fungal community, Chloroflexi and Proteobacteria were the primary bacterial phyla, and Glomus and Sclerocystis were the predominant AMF genera. Analysis of alpha diversity showed that in the bacterial community, S8 exhibited the highest diversity and richness, while S6 showed the lowest. For the fungal community, S6 had the highest diversity, S2 displayed the highest richness, and S5 showed the lowest values for both diversity and richness. Within the AMF community, S8 demonstrated the highest diversity, S7 exhibited the highest richness, and S6 had the lowest diversity and richness values. Overall, bacterial diversity surpassed fungal diversity. Redundancy analysis identified AK as a common key factor influencing both bacterial and fungal communities. Besides AK, OM and TN were also significant drivers for the fungal and bacterial communities, respectively, while the AMF community was most strongly associated with SK

1. Introduction

Coffea arabica is one of the world’s major coffee species, and its cultivation in China is predominantly concentrated in Yunnan Province. China’s major coffee-growing regions include Yunnan and Hainan provinces, among which Yunnan accounts for over 98% of the nation’s total coffee planting area, output, and agricultural value [1,2]. However, the industry faces significant challenges threatening yield, quality, and sustainable development, including climate change [3,4], expansion of monoculture areas [5], soil degradation [6] and frequent disease outbreaks [7]. To address these challenges, it is essential to shift from a management model dependent on chemical inputs toward a systemic management strategy based on the regulation of rhizosphere microbial ecology. This necessitates a focused attention on the rhizosphere—a critical interface for interactions among plant roots, soil, and microorganisms, which plays a central role in plant health and ecosystem functioning.

The rhizosphere is a critical zone for plant–soil–microbiome interactions, playing vital roles in plant stress response, nutrient acquisition, and shaping the microbial community [8]. Soil physicochemical properties are key indicators of soil quality and fertility [9]. Essential nutrients like nitrogen, phosphorus, and potassium are fundamental for plant growth, with their availability directly influencing soil health and plant performance [10,11]. Soil pH and organic matter are interconnected properties crucially affecting the soil micro-ecology and plant growth [12,13]. Rhizosphere microorganisms, the communities inhabiting root-associated soil [14], are pivotal in material cycles and energy flows between plants and soil [15,16,17]. They significantly impact plant nutrient uptake [18], growth [19], and stress resilience [20]. Plants modify rhizosphere properties (e.g., available P, K, pH) via root exudates and nutrient absorption, thereby influencing microbial community structure [21,22]. Conversely, microbial activities feedback to affect soil properties and plant growth [23,24]. Rhizosphere bacteria contribute to nutrient cycling through nitrogen fixation, organic matter decomposition [25], and mineral weathering [26], while also enhancing plant resistance via induced systemic resistance [27] or antibiotic production [28]. Fungi aid plants by forming mycorrhizal symbioses [29] and accelerating litter decomposition [30]. Arbuscular mycorrhizal fungi (AMF), belonging to the Glomeromycota, form symbiotic associations with most land plants [31]. They extend a hyphal network into the soil, thereby enhancing plant access to water and mineral nutrients (especially phosphorus) [32], enhancing stress tolerance, and promoting growth, while relying on host-derived photosynthates [33,34]. Crucially, the formation and function of the rhizosphere microbiome are not passive processes, but can be actively regulated by the host plant itself [35].

Advances in molecular biology have accelerated research into plant–rhizosphere interactions. Studies report varietal differences in root exudates and soil enzyme activities influencing soil microbial communities [36,37]. Furthermore, beneficial microorganisms such as Trichoderma [38], Bacillus [39], and Actinomycetes [40] have been identified in the coffee rhizosphere. However, current research on coffee remains constrained within specific paradigms. Relevant studies typically focus on a single microbial group—for example, analyzing arbuscular mycorrhizal fungi and associated fungal communities under different management practices [41], or isolating specific biocontrol agents such as Trichoderma [38] or Actinomycetes [40]—or on a single environmental driver, such as assessing the response of bacterial communities to altitudinal gradients [42]. Consequently, there is a clear lack of systematic research that simultaneously investigates how multiple commercially important Coffea arabica cultivars shape the physicochemical environment of the rhizosphere and the integrated structure of bacterial, fungal, and arbuscular mycorrhizal fungal communities. This gap can be attributed to methodological evolution. Early culture-dependent methods [39,40] possess inherent limitations in capturing microbial community complexity, while the application of high-throughput sequencing technology for holistic microbiome analysis in coffee rhizosphere research has only recently been developed [41,42]. To elucidate the correlations and differences in rhizosphere soil physicochemical properties and microbial communities among different Coffea arabica cultivars, it is essential to conduct multi-cultivar, replicated field comparisons under uniform conditions. Nevertheless, studies adhering to such a rigorous design remain notably scarce.

To address this knowledge gap, the objectives of this study were as follows: (1) to examine the differences in arbuscular mycorrhizal fungi (AMF) colonization and spore density among different cultivars; (2) to assess the variations in rhizosphere soil properties and microbial diversity; and (3) to analyze the influence of soil properties on microbial community structure. To achieve these objectives, soil chemical analysis and high-throughput sequencing techniques were integrated within a uniformly designed field experiment.

2. Materials and Methods

2.1. Site Description

This study was conducted at the Kangping Education and Research Base (22.57° N, 101.48° E; 990.70 m asl) in Jiangcheng County, Pu’er, China. The region has a subtropical mountainous monsoon humid climate with distinct dry/wet seasons. According to the Administrative Divisions Dictionary of the People’s Republic of China (Yunnan Province Volume), the mean annual climate figures are 18.10 °C for temperature, 2212.00 mm for precipitation, and 1359.50 mm for evaporation. The soil is lateritic red soil derived from sandstone and shale. All sampled coffee plants were 5-year-old, visually robust, and exhibited uniform growth vigor, with comparable height and canopy size and no visible disease or pest damage. All agronomic practices, including fertilization, irrigation, and pruning, were consistent across the plantation. For this experiment, fine roots and rhizosphere soils were collected from eight Coffea arabica cultivars (S1: 132, S2: 370, S3: 363, S4: 366, S5: 011, S6: 39x, S7: 316, S8: 036). These cultivars represent the predominant commercial varieties extensively cultivated in the Pu’er region in recent years and encompass key genetic lines, including the Catuai series (316, yellow Catuai; 011, Catuai 140), the Sarchimor series (370, 363, 39X, 366), Castillo (036), and a yellow-fruited variant selection of MEXICO-9 (132).

2.2. Sampling

Sampling was conducted on 24 September 2023, during the late rainy season to capture a relatively stable rhizosphere microbial community. Soil and root samples were collected at a distance of 15 cm from the coffee plant base—targeting the rhizosphere zone with higher fine root density—and at a depth of 10–30 cm to encompass the main soil volume occupied by absorbing roots. To avoid overlap between the rhizosphere zones of adjacent plants, sampled coffee plants were spaced at least 3 m apart both within and between rows. Sampling points (15 cm from the plant base) were oriented away from neighboring plants to ensure that the collected rhizosphere soil originated exclusively from the target cultivar. A five-point sampling method was applied per cultivar. Samples from the five points were thoroughly mixed to form one composite replicate. Three biological replicates were prepared for each of the eight coffee cultivars, resulting in a total of 120 sampled plants (8 cultivars × 5 plants per composite sample × 3 replicates), i.e., 15 individual plants per cultivar. Before sampling, surface debris was removed. Soil within the target depth was then excavated using a small shovel. Roots were gently shaken to dislodge adhering soil, which was defined as the rhizosphere soil. Both the rhizosphere soil and the corresponding roots were separately placed into pre-labeled zip-lock bags. All samples were immediately stored in an icebox and transported to the laboratory.

2.3. Determination of AMF Colonization in Coffee Roots and Spore Density in Rhizosphere Soil

The root AMF colonization rate was determined using a modified lactic acid–glycerol method according to Phillips and Hayman (1970).

AMF colonization (%) = (number of colonized root segments/total number of root segments examined) × 100%

Spore isolation was performed using the wet-sieving and decanting technique described by Gerdemann and Nicolson (1963), followed by observation and counting under a stereomicroscope.

Spore density (spores/g) = Total number of spores counted/Dry weight of soil sample (g)

2.4. Determination of Rhizosphere Soil Physicochemical Properties of Different Coffee Cultivars

Soil physicochemical properties were determined according to standard methods described by Bao (2000) [43]. Specifically, soil pH was measured potentiometrically using a pH meter at a soil-to-water ratio of 1:2.5. Soil organic matter content was determined by the potassium dichromate volumetric method (external heating method). The total nitrogen content was analyzed using the Kjeldahl digestion method. Alkali-hydrolyzable nitrogen was measured by the alkali diffusion method. Total phosphorus content was quantified via sulfuric–perchloric acid digestion. Available phosphorus was extracted with the double acid method and determined by molybdenum–antimony spectrophotometry. Total potassium content was measured by NaOH fusion followed by flame photometry. Available potassium was extracted with ammonium acetate and quantified by flame photometry. Slowly available potassium was extracted with 1 mol/L hot nitric acid and measured by flame photometry.

2.5. Determination of Rhizosphere Soil Microbial Community Composition in Different Coffee Cultivars

High-throughput sequencing of the fungal community in the rhizosphere soil of different coffee cultivars was conducted by Novogene Co., Ltd. (Beijing, China). The ITS1 region of fungal ribosomal DNA was amplified using the primers ITS1F (5′-GGAAGTAAAAGTCGTAACAAGG-3′) and ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′) [44]. The specific procedures included: total genomic DNA was extracted using a soil DNA extraction kit, followed by amplification with a pre-optimized high-fidelity PCR system (annealing at 55 °C for 30–35 cycles). The amplification products were purified using magnetic beads to construct sequencing libraries, which were ultimately sequenced on an Illumina NovaSeq platform using a paired-end strategy. Sequencing of the bacterial and arbuscular mycorrhizal fungal (AMF) communities was performed by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). For bacteria, the V3–V4 region of the 16S rRNA gene was amplified in a single-step PCR using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) [45] (annealing at 55 °C for 25–30 cycles). For AMF, a nested PCR targeting a partial region of the 18S rRNA gene was employed. The first round of amplification used the universal primers AML1F/AML2R (annealing at 55 °C for 32 cycles), and the second round used the specific primers AMV4.5NF (5′-AAGCTCGTAGTTGAATTTCG-3′) and AMDGR (5′-CCCCAACTATCCCTATTAATCAT-3′) [46] (annealing at 55 °C for 25 cycles). All PCR products were verified by 2% agarose gel electrophoresis, and target bands were excised and purified for library construction. The resulting libraries were then subjected to paired-end sequencing on an Illumina MiSeq platform.

2.6. Data Processing and Analysis

Bioinformatics processing of raw sequencing data was performed as follows: primers and low-quality sequences were first removed using Cutadapt (v3.3); paired-end reads were then merged using FLASH (v1.2.11), followed by further quality control with fastp (v0.23.1). After chimera removal with VSEARCH (v2.16.0), denoising was conducted using the DADA2 module in QIIME 2 (v2022.2) to generate an amplicon sequence variant (ASV) table. Representative sequences for bacterial and fungal ASVs were taxonomically annotated via the feature-classifier plugin in QIIME 2 against the SILVA (v138) 16S rRNA database and the UNITE (v8.2) ITS database, respectively.

Alpha diversity indices (e.g., Chao1) and beta diversity (based on Bray–Curtis distance) were calculated in QIIME 2. Differences in community structure were visualized using principal coordinate analysis.

Statistical analysis was performed using SPSS 26.0 (IBM Corp, Armonk, NY, USA). One-way ANOVA was used to test the significance of differences in various indices among different coffee cultivars, followed by Tukey’s test for post hoc multiple comparisons (p < 0.05). Results are presented as mean ± standard deviation.

3. Results

3.1. Analysis of Rhizosphere Soil Physicochemical Properties Among Different Coffee Cultivars

Among the rhizosphere soil physicochemical properties of different coffee cultivars in the experimental site, except for pH (4.37–4.48) and TN (1.19–1.74), which showed no significant differences, all other indicators OM, TP, TK, AN, AP, and AK exhibited significant differences (p < 0.05). Among the cultivars, S6 had the highest AN contents, S7 showed the highest levels of OM, TN, TP, TK, and AP, and S8 had the highest pH. In contrast, S1 had the lowest pH, S2 had the lowest TP and TK contents, and S3 had the lowest contents of AK, AN, TN, and OM (

Table 1. Rhizosphere soil physicochemical properties of different coffee cultivars.

Coffee Cultivar	Measured Indices
	PH	OM g/kg	TN g/kg	TP g/kg	TK g/kg	AN mg/kg	AP mg/kg	AK mg/kg	SK mg/kg
S1	4.37 ± 0.06 a	26.77 ± 3.71 ab	1.49 ± 0.22 a	1.34 ± 0.12 ab	30.82 ± 0.43 ab	161.39 ± 39.70 ab	267.50 ± 38.80 b	336.00 ± 58.92 b	205.33 ± 26.63 cef
S2	4.47 ± 0.52 a	24.83 ± 4.79 ab	1.39 ± 0.28 a	1.08 ± 0.27 b	28.69 ± 1.17 b	191.27 ± 70.70 a	213.75 ± 55.31 b	474.67 ± 50.01 a	224.00 ± 31.24 bcd
S3	4.48 ± 0.18 a	21.21 ± 2.75 b	1.19 ± 0.13 a	1.30 ± 0.29 ab	32.16 ± 1.20 a	106.62 ± 11.77 b	329.25 ± 173.42 b	196.00 ± 17.44 c	193.33 ± 19.73 cef
S4	4.54 ± 0.15 a	28.58 ± 0.72 ab	1.62 ± 0.03 a	1.47 ± 0.07 ab	30.60 ± 0.60 ab	195.14 ± 15.25 a	307.25 ± 59.51 b	428.00 ± 39.40 ab	238.67 ± 16.17 bc
S5	4.41 ± 0.18 a	28.46 ± 3.14 ab	1.48 ± 0.22 a	1.56 ± 0.12 ab	29.20 ± 1.40 b	176.06 ± 40.52 a	365.50 ± 20.25 ab	420.00 ± 50.12 ab	174.67 ± 15.14 ef
S6	4.47 ± 0.40 a	30.45 ± 4.86 ab	1.72 ± 0.33 a	1.89 ± 0.51 a	29.45 ± 2.23 b	204.43 ± 14.10 a	499.25 ± 130.19 a	462.67 ± 74.87 a	297.33 ± 36.30 a
S7	4.75 ± 0.19 a	31.40 ± 10.56 a	1.74 ± 0.58 a	1.92 ± 0.66 a	32.17 ± 0.69 a	150.63 ± 33.98 ab	521.50 ± 72.35 a	340.00 ± 38.16 b	158.67 ± 12.86 f
S8	4.78 ± 0.47 a	25.40 ± 1.80 ab	1.40 ± 0.09 a	1.48 ± 0.18 ab	30.17 ± 1.99 ab	159.93 ± 21.61 ab	307.50 ± 43.06 b	345.33 ± 37.17 b	257.33 ± 43.14 ab

Note: Data are presented as mean ± standard deviation (n = 3). Different lowercase letters within a row indicate significant differences among cultivars according to one-way ANOVA followed by Tukey’s HSD test (p < 0.05). Abbreviations: OM, organic matter; TN, total nitrogen; TP, total phosphorus; TK, total potassium; AN, alkali-hydrolyzable nitrogen; AP, available phosphorus; AK, available potassium; SK, slowly available potassium.

).

3.2. Spore Density and Colonization of AMF in the Rhizosphere of Different Coffee Cultivars

No significant differences (p > 0.05) were observed in the arbuscular mycorrhizal fungi (AMF) spore density in the rhizosphere soil among the different coffee cultivars in this experimental site. The average AMF spore density in the coffee rhizosphere soil was 123 spores per gram. Among the cultivars, S7 exhibited the highest spore density, while S3 showed the lowest. The AMF spore densities in the rhizosphere soil of the eight coffee cultivars were as follows: S7 (160 spores/g) > S1 (136 spores/g) > S2 (130 spores/g) > S6 (124 spores/g) > S4 (123 spores/g) > S5 (122 spores/g) > S8 (96 spores/g) > S3 (91 spores/g) (Figure 1a). Further analysis revealed a significant correlation between AMF spore density and the contents of soil organic matter (OM) and total nitrogen (TN) in the rhizosphere (

Table 2. Correlation between AMF spore density and soil factors.

	SD	OM	TN	AN	TP	AP	TK	AK	SK
SD	1
OM	0.637 **	1
TN	0.594 **	0.987 **	1
AN	0.361	0.634 **	0.680 **	1
TP	0.404	0.726 **	0.691 **	0.301	1
AP	0.198	0.524 **	0.509 *	0.135	0.867 **	1
TK	0.062	−0.237	−0.244	−0.469 *	−0.106	−0.066	1
AK	0.083	0.385	0.421 *	0.778 **	0.079	0.035	−616 **	1
SK	−0.031	0.263	0.294	0.505 *	0.215	0.063	−0.440 *	0.416 *	1

Note: values in the table represent Pearson correlation coefficients; ** and * indicate significant correlation at the 0.01 and 0.05 levels (two-tailed), respectively. SD: spore density; OM: Organic matter; TN: Total nitrogen; AN: Alkali-hydrolyzable nitrogen; TP: Total phosphorus; AP: Available phosphorus; TK: Total potassium; AK: Available potassium; SK: Slowly available potassium.

).

No AMF colonization was observed in the root systems of any coffee cultivars examined in this trial (Figure 1b).

3.3. Analysis of Rhizosphere Soil Microbial Communities in Different Coffee Cultivars

Sequencing results of the rhizosphere soil microbial communities from the eight coffee cultivars revealed the following: For the fungal communities, the number of effective sequences in S1 was significantly higher than that in S6 (p < 0.05). Specifically, S1 had the highest number of effective sequences (100,947), while S6 had the lowest (63,886). For the bacterial communities, no significant differences were observed in the number of effective sequences among the cultivars (p > 0.05). Among them, S7 had the highest number (48,944), and S2 had the lowest (44,155). Regarding the AMF communities, the number of effective sequences in S1 was significantly higher than those in S4 and S8 (p < 0.05). S1 had the highest number (55,919), while S4 had the lowest (40,946) (

Table 3. Microbial sequencing results of rhizosphere soil from different coffee cultivars.

Cultivar	Fungal Communities		Bacterial Communities		AMF Communities
	Raw Reads	Effective Reads	Raw Reads	Effective Reads	Raw Reads	Effective Reads
S1	109,723 ± 2966 a	100,947 ± 1332 a	56,919 ± 3856 a	45,898 ± 2844 a	61,083 ± 1548 a	55,919 ± 2207 a
S2	108,030 ± 3077 a	87,200 ± 10,937 ab	55,659 ± 1221 a	44,155 ± 1222 a	56,568 ± 4123 ab	50,047 ± 2984 ab
S3	103,753 ± 1651 a	97,021 ± 1737 ab	57,274 ± 4195 a	45,895 ± 3270 a	55,790 ± 1354 ab	47,789 ± 456 abc
S4	104,644 ± 1258 a	96,964 ± 1499 ab	60,678 ± 4322 a	47,991 ± 2947 a	49,293 ± 1233 b	40,946 ± 2799 c
S5	104,238 ± 1159 a	96,709 ± 1678 ab	63,689 ± 5260 a	46,973 ± 2651 a	56,963 ± 4584 ab	49,555 ± 4161 ab
S6	103,194 ± 553 a	63,886 ± 27,424 b	60,872 ± 5193 a	46,645 ± 3357 a	56,757 ± 3540 ab	49,592 ± 2267 ab
S7	103,449 ± 1241 a	90,542 ± 668 ab	63,153 ± 6004 a	48,944 ± 3792 a	60,020 ± 3114 a	51,471 ± 2172 ab
S8	108,815 ± 4405 a	94,847 ± 3112 ab	63,770 ± 1438 a	48,336 ± 563 a	54,040 ± 1634 ab	47,474 ± 666 bc

Note: Fungal communities were sequenced on the Illumina NovaSeq platform, while bacterial and AMF communities were sequenced on the Illumina MiSeq platform. Due to differences in the technical parameters (e.g., read length and depth) of the sequencing platforms, the absolute read counts are not directly comparable across different microbial types (between columns). The data in this table are intended to demonstrate the sequencing depth and data quality among samples within the same microbial type. Data are presented as mean ± standard error (n = 3). Within each microbial type (column), different lowercase letters indicate statistically significant differences among cultivars based on one-way ANOVA followed by Tukey’s HSD test (p < 0.05) All subsequent analyses of community structure, diversity, and statistics were performed using standardized effective data.

).

3.3.1. Analysis of Rhizosphere Soil Microbial Community Composition in Different Coffee Cultivars

The predominant dominant fungal phylum in the rhizosphere soil of the eight coffee cultivars was Ascomycota, whose relative abundance was highest in S8 (82.20%) and lowest in S1 (42.83%). Other phyla with relatively high abundances were Basidiomycota, Rozellomycota, and Mucoromycota, with relative abundances ranging from 6.29% to 30.84%, 0.63% to 7.46%, and 0.08% to 5.42%, respectively. Blastocladiomycota was a unique phylum found only in S2, with a relative abundance of 1.26% (Figure 2a). The main dominant bacterial phyla in the bacterial communities were Chloroflexi, Proteobacteria, and Actinobacteriota. The relative abundance of Chloroflexi was highest in S1 (42.88%) and lowest in S6 (19.75%). Proteobacteria reached its highest relative abundance in S8 (29.70%) and was lowest in S3 (16.11%). The relative abundance of Actinobacteriota peaked in S5 (25.02%) and was lowest in S7 (13.28%). Other relatively abundant phyla included Acidobacteriota and Firmicutes, with relative abundances ranging from 8.34% to 15.57% and 3.54% to 11.40%, respectively (Figure 2b). The AMF communities included genera such as Glomus, Sclerocystis, and Claroideoglomus. The relative abundance of Glomus was highest in S4 (67.13%) and lowest in S2 (11.93%). Sclerocystis showed the highest relative abundance in S2 (60.92%), while its lowest relative abundance was observed in S7 (16.73%). Claroideoglomus was only detected in S1, S2, and S3, with its highest relative abundance in S2 (5.32%). At the species level, classifications included Sclerocystis sinuosa, among others. The relative abundance of Sclerocystis sinuosa was highest in S2 (60.92%) and lowest in S7 (16.73%) (Figure 2c).

The numbers of unique ASVs in the rhizosphere soil microbial communities of the eight coffee cultivars were as follows: Fungal community: S3 (861) > S1 (782) > S2 (779) > S6 (727) > S8 (618) > S7 (560) > S4 (549) > S5 (471) (Figure 2d). Bacterial community: S8 (2636) > S5 (1976) > S7 (1950) > S2 (1932) > S6 (1588) > S4 (1525) > S3 (1400) > S1 (1384) (Figure 2e). AMF community: S7 (90) > S8 (75) > S1 (73) > S2 (72) > S3 (70) > S4 (56) > S5 (50) > S6 (42) (Figure 2f). The number of unique ASVs common to all groups within each community type (560 for bacteria, 86 for fungi, 4 for AMF) was lower than the number of unique ASVs found in individual cultivars. This indicates substantial differences in ASV composition among the rhizosphere soil microbial communities of these eight coffee cultivars.

3.3.2. Alpha Diversity Analysis of Rhizosphere Soil Microbial Communities in Different Coffee Cultivars

Alpha diversity was evaluated using the Shannon, Chao, Pielou evenness (Pielou e), and coverage indices. The high sequencing coverage for all three microbial communities indicated that the data were accurate and reliable, effectively reflecting the diversity, richness, and evenness of the rhizosphere soil microbial communities across the different coffee cultivars. Overall, bacterial communities exhibited higher diversity and richness, whereas fungal communities showed relatively lower values. For the rhizosphere soil bacterial communities (Pielou e: 0.850–0.902), variety S8 had the highest Shannon, Chao, and Pielou e indices, indicating the greatest bacterial species diversity, richness, and evenness. In contrast, S6 showed the lowest Shannon and Chao indices, reflecting the lowest bacterial diversity and richness. In the fungal communities (Pielou e: 0.46–0.58), S6 recorded the highest Shannon and Pielou e indices, suggesting the highest fungal species diversity and evenness. S5 displayed the lowest Shannon, Chao, and Pielou e indices, indicating the lowest fungal diversity, richness, and evenness. S2 had the highest Chao index, representing the greatest fungal richness. For the AMF communities (Pielou e: 0.50–0.73), S8 exhibited the highest Shannon index, denoting the highest AMF species diversity. S7 showed the highest Chao index, indicating the greatest AMF species richness. S6 had the lowest Shannon and Chao indices, reflecting the lowest AMF diversity and richness (

Table 4. Alpha diversity indices of bacterial communities in rhizosphere soil from different coffee cultivars.

Bacterial	Group
	S1	S2	S3	S4	S5	S6	S7	S8
Shannon	6.464	6.941	6.789	6.724	6.737	6.386	6.958	7.061
Chao	1983.311	2208.776	2024.002	2062.396	2188.894	1903.979	2341.831	2486.182
Pielou e	0.856	0.902	0.893	0.883	0.878	0.850	0.898	0.874
coverage	0.999	0.999	0.999	0.998	0.998	0.998	0.998	0.998

Note: The data in the table represent the mean values of Alpha diversity indices calculated from high-quality sequences. Fungal community data were derived from sequencing on the Illumina NovaSeq platform, while bacterial and AMF community data were derived from the Illumina MiSeq platform. Due to technical differences between the sequencing platforms, the absolute index values are not directly comparable across different microbial types (Bacteria, Fungi, AMF). All analyses and comparisons were performed within each respective microbial type. The Coverage index reflects the comprehensiveness of the sequencing in capturing the community’s species composition. For the same microbial type, different lowercase letters following the index values for different cultivars indicate statistically significant differences based on one-way ANOVA followed by Tukey’s HSD test (p < 0.05).

,

Table 5. Alpha diversity indices of fungal communities in rhizosphere soil from different coffee cultivars.

Fungal	Group
	S1	S2	S3	S4	S5	S6	S7	S8
Shannon	5.138	4.639	5.000	4.366	3.930	5.368	4.795	4.307
Chao	617.760	623.731	612.219	437.129	389.768	592.001	501.886	467.983
Pielou e	0.560	0.501	0.542	0.500	0.457	0.584	0.536	0.487
coverage	0.999	0.999	0.999	1.000	1.000	0.999	1.000	0.999

Note: The data in the table represent the mean values of Alpha diversity indices calculated from high-quality sequences. Fungal community data were derived from sequencing on the Illumina NovaSeq platform, while bacterial and AMF community data were derived from the Illumina MiSeq platform. Due to technical differences between the sequencing platforms, the absolute index values are not directly comparable across different microbial types (Bacteria, Fungi, AMF). All analyses and comparisons were performed within each respective microbial type. The Coverage index reflects the comprehensiveness of the sequencing in capturing the community’s species composition. For the same microbial type, different lowercase letters following the index values for different cultivars indicate statistically significant differences based on one-way ANOVA followed by Tukey’s HSD test (p < 0.05).

and

Table 6. Alpha diversity indices of AMF communities in rhizosphere soil from different coffee cultivars.

AMF	Group
	S1	S2	S3	S4	S5	S6	S7	S8
Shannon	1.819	2.467	2.484	2.141	2.502	1.668	2.428	2.508
Chao	37.083	43.333	44.333	33.333	32.111	24.444	48.067	45.333
Pielou e	0.499	0.633	0.660	0.614	0.729	0.520	0.636	0.662
coverage	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000

Note: The data in the table represent the mean values of Alpha diversity indices calculated from high-quality sequences. Fungal community data were derived from sequencing on the Illumina NovaSeq platform, while bacterial and AMF community data were derived from the Illumina MiSeq platform. Due to technical differences between the sequencing platforms, the absolute index values are not directly comparable across different microbial types (Bacteria, Fungi, AMF). All analyses and comparisons were performed within each respective microbial type. The Coverage index reflects the comprehensiveness of the sequencing in capturing the community’s species composition. For the same microbial type, different lowercase letters following the index values for different cultivars indicate statistically significant differences based on one-way ANOVA followed by Tukey’s HSD test (p < 0.05).

).

3.3.3. Analysis of Differences in Rhizosphere Soil Microbial Communities Among Different Coffee Cultivars

Non-metric multidimensional scaling (NMDS) based on Weighted Unifrac distance was performed to assess the fungal, bacterial, and arbuscular mycorrhizal fungal (AMF) communities in the rhizosphere soil of the eight coffee cultivars. The stress values for the fungal, bacterial, and AMF communities were 0.13, 0.14, and 0.11, respectively, indicating that the NMDS results accurately reflected the differences among samples. In the fungal communities, the within-group variation in community abundance was relatively highest in S4 and lowest in S6. The between-group differences in fungal community abundance were relatively larger between S3 and S5, and between S4 and S5 (Figure 3a). For the bacterial communities, the within-group variation was relatively highest in S1 and lowest in S4. Notable between-group differences were observed between S1 and S4, S1 and S6, and S1 and S7 (Figure 3b). In the AMF communities, the within-group variation was relatively highest in S5 and lowest in S1. The between-group differences in AMF community abundance were relatively larger between S5 and S6, and between S5 and S3 (Figure 3c).

3.3.4. Influence of Rhizosphere Soil Factors on Microbial Communities in Different Coffee Cultivars

Redundancy analysis (RDA) of the rhizospheric soil fungal (phylum level), bacterial (phylum level), and AMF (genus level) communities from eight coffee cultivars against soil physicochemical properties revealed distinct drivers for each microbial group. For the fungal community, the soil factors were ranked by explanatory strength in the order: AK > OM > TN > AN > SK > TK > AP > TP > pH, among which AK, OM, TN, and AN exerted significant effects (Figure 4a). In the bacterial community, the influencing factors followed the sequence: AK > TK > AP > AN > TP > TN > OM > pH > SK, with AK, TK being identified as significant drivers (Figure 4b). Regarding the AMF community, soil variables were ordered as: TK > SK > AP > pH > TP > AN > TN > OM > AK, where TK, SK exerted a relatively stronger influence on AMF community composition (Figure 4c).

3.3.5. Functional Prediction of Rhizosphere Soil in Different Coffee Cultivars

Functional prediction of the fungal communities in the rhizosphere soil of the eight coffee cultivars was performed using FunGuild. The top 10 trophic modes by relative abundance were identified as: Saprotroph–Pathotroph–Symbiotroph, Pathogen–Saprotroph–Symbiotroph, Pathotroph–Symbiotroph, Symbiotroph, Saprotroph–Symbiotroph, Pathotroph, Pathotroph–Saprotroph–Symbiotroph, Pathotroph–Saprotroph, Saprotroph, and Unassigned. Among these, Saprotroph (10.73%–39.58%), Pathotroph–Saprotroph (6.29%–32.79%), and Pathotroph–Saprotroph–Symbiotroph (4.18%–18.77%) displayed relatively high abundances. The Saprotroph–Pathotroph–Symbiotroph mode (0.0031%) was exclusively identified in S6 (Figure 5a).

PICRUSt2 analysis of the bacterial communities in the rhizosphere soils of the eight coffee cultivars revealed that the predominant COG functional categories by relative abundance were amino acid transport and metabolism (10.51%–10.77%), energy production and conversion (7.40%–7.68%), and translation, ribosomal structure and biogenesis (6.90%–7.31%), while the remaining categories—including V: defense mechanisms; B: chromatin structure and dynamics (typically eukaryotic/archaeal; bacteria may possess histone-like proteins such as HU protein); L: replication, recombination and repair; K: transcription; W: extracellular structures (mainly found in eukaryotes/bacterial secretion systems such as type IV pili); I: lipid transport and metabolism; M: cell wall (Figure 5b).

4. Discussion

In this study, a high density of AMF spores (91–160 spores/g) was found in the rhizosphere soil of eight coffee cultivars, yet no root colonization was observed. This apparent paradox may be explained by the combined effects of soil legacy and inhibited symbiosis. The spores likely represent a persistent “legacy bank” accumulated from past vegetation rather than from current-season association with coffee [47]. While soil organic matter could support the maintenance of this spore bank, the relatively high levels of available phosphorus and potassium probably suppressed symbiotic establishment. Since high phosphorus availability is a well-documented suppressor of AMF colonization, the elevated soil available phosphorus levels measured in this study (Table 1) likely constitute a major factor inhibiting colonization [48]. Under such nutrient-replete conditions, AMF may adopt a “persistence strategy”, allocating resources to dormant spores instead of costly hyphal growth aimed at host colonization [49]. This pattern is consistent with the distinct AMF dynamics shaped by long-term perennial cropping systems, where stable soil conditions allow spore banks to accumulate over time [50]. When AMF perceive an unfavorable soil environment (e.g., high phosphorus) or receive weak symbiotic signals from a host plant such as coffee—whose complex carbon allocation priorities as a perennial crop may reduce its dependence on AMF under certain conditions—the colonization process is aborted. The fungus may then revert to a “persistence strategy,” allocating resources to spore dormancy rather than to energetically costly and non-rewarded hyphal growth [41,51]. Additionally, it is important to acknowledge the methodological limitation of the trypan blue staining technique used, which may fail to detect early or low-intensity colonization events. Thus, the observed spore density reflects historical accumulation and a stress response to conditions unfavorable for symbiosis, rather than an indication of functional mycorrhizal activity.

The results indicate that the rhizosphere soils of all coffee cultivars were acidic, with pH values in the relatively low range of 4.37–4.78. This characteristic is likely the result of the combined effects of regional natural soil-forming processes and agricultural activities. First, the hot and humid tropical-subtropical climate of the study area leads to intense leaching of base cations, which is a key natural process shaping the inherently acidic soil matrix. Sampling at the end of the rainy season precisely captured the cumulative effect of this leaching process [52]. Second, long-term agricultural nitrogen input, particularly ammonium-based fertilizers, releases hydrogen ions through nitrification, which may further exacerbate the anthropogenic acidification process of the soil [53].

Analysis of the physicochemical properties in the rhizosphere soil of the eight coffee cultivars revealed significant differences in the contents of OM, TP, TK, AN, AP, AK, and ASK. This indicates varying requirements for soil chemical conditions among different coffee cultivars. Different plant cultivars, due to their genetic characteristics and differences in root exudates, necessitate distinct growth conditions. For example, plants with different genetic traits secrete varying types and quantities of enzymes, such as acid phosphatase, to enhance soil phosphorus activation, leading to differences in available phosphorus content and other physicochemical properties (e.g., P, Fe, pH) in the rhizosphere soil [54]. Some plants secrete organic acids (e.g., oxalic acid, acetic acid, citric acid) to mobilize insoluble phosphorus and potassium in the soil, thereby increasing their availability [55]. Alpha diversity analysis of the rhizosphere microbial communities of the eight cultivars indicated that bacterial communities exhibited higher diversity and richness than fungal communities. Specifically, S8 showed the highest bacterial and AMF community diversity, while S6 had the highest fungal diversity. Conversely, S6 displayed the lowest bacterial and AMF community diversity and richness. However, the differences in Alpha diversity indices among the cultivars were not significant (p > 0.05), which might be attributed to the non-significant differences in rhizosphere pH (4.37–4.78) (p > 0.05) and the influence of root exudates. For instance, although the Alpha diversity index (Chao1) of rhizosphere bacteria among maize inbred lines showed no significant differences, the abundance of the core community (e.g., Agrobacterium, Devosia) was significantly correlated with the host genotype, and Alpha diversity was more influenced by environmental factors such as pH [56]. Similarly, no significant differences were found in the Alpha diversity indices (Shannon, Simpson) of rhizosphere bacteria and fungi between highbush and rabbiteye blueberries, but significant differences in community structure were observed (p < 0.05). Research suggests that the non-significant differences in Alpha diversity are related to the regulation of microbial community evenness by the composition of root exudates (e.g., phenolic compounds) from different host cultivars [57].

In recent years, growing evidence has highlighted the close relationship between coffee rhizosphere soil factors and microbial communities. It should be noted that the redundancy analysis (RDA) conducted in this study reveals statistical correlations between soil variables and microbial community composition, but does not account for potential co-correlation among the explanatory variables. Our analysis identified that OM, TN, AK, ASK, and AN were significantly correlated with the fungal community; TP, AP, AK, and ASK showed significant correlations with the bacterial community; and TK was strongly correlated with the AMF community. In contrast, pH exhibited only a weak correlation with all communities. This pattern can be interpreted through the mechanism of coffee roots maintaining pH balance during growth by increasing NO₃⁻ uptake and HCO₃⁻ release or regulating the NH₄⁺/NO₃⁻ uptake ratio [42]. Supporting this, studies on coffee rhizosphere soils at different altitudes found that OM content was significantly positively correlated with fungal diversity at high altitudes (1400 m–1600 m), while TN at low altitudes (800 m–1000 m) was associated with shifts in community composition, likely through promoting the proliferation of saprotrophic fungi (e.g., Trichoderma). ASK was linked to indirect effects on fungal community structure in acidic soils (pH 4.8–5.2) via regulating the activity of sulfur-oxidizing bacteria [58]. Similarly, research on rhizosphere soils of C. canephora and C. arabica in Malang, East Java, Indonesia, demonstrated that TP and AP were significantly correlated with bacterial community structure, potentially through promoting the proliferation of phosphate-solubilizing bacteria (e.g., Pseudomonas putida). In alkaline soils (pH 6.8–7.2), ASK was associated with enhanced bacterial mineralization of organic phosphorus, possibly by regulating the activity of sulfur-reducing bacteria [59].

This study revealed significant differences in rhizosphere soil physicochemical properties and microbial communities among different varieties of Yunnan Coffea arabica, providing new insights for varietal selection, soil quality regulation, and fertilizer reduction. Our findings demonstrate distinct differentiation in both rhizosphere nutrient profiles and microbial community characteristics across varieties. Specifically, S7 exhibited optimal levels of OM, TN, TP, TK, and AK, suggesting its potential for strong nutrient activation or enrichment capabilities that contribute to a comprehensively nutrient-rich rhizosphere environment. In contrast, S6 showed superior performance in AN and slowly available potassium, indicating possible specialization in microbial functions related to nitrogen and potassium cycling, potentially mediated through root exudate regulation. Regarding microbial community structure, S8 demonstrated the highest diversity in both bacterial and AMF communities, reflecting greater ecological complexity and stability in its rhizosphere microecosystem. S6 displayed optimal fungal diversity and evenness, suggesting a more stable fungal community structure with potentially enhanced functional capacity, environmental stress resistance, and resource utilization efficiency. The notable AMF species richness observed in S7 may synergize with its comprehensive soil nutrient status to promote efficient nutrient utilization. However, it should be noted that this study did not elucidate the regulatory mechanisms of variety-specific root exudates (such as organic acids and phenolic compounds) on microbial communities. Future research should integrate metabolomics to analyze root exudate composition with metagenomics to decipher microbial functional genes, thereby further clarifying the relationships between coffee varieties, root exudates, and microorganisms to establish a theoretical foundation for high-quality and efficient cultivation systems.

5. Conclusions

The findings of this study demonstrate that coffee variety significantly influences the nutrient contents in the rhizosphere soil, including OM, TP, and TK. The fungal communities across varieties were predominantly dominated by Ascomycota, while the bacterial communities were mainly composed of Chloroflexi and Proteobacteria. The AMF communities were primarily represented by Glomus and Sclerocystis. Redundancy analysis confirmed that soil OM, AK, and TN were key drivers shaping the distribution of both fungal and bacterial communities. These results elucidate the mechanisms by which genetic factors and soil properties collectively influence the rhizosphere microbial community of Coffea arabica, providing a theoretical basis for targeted variety selection and rhizosphere microenvironment management. Among the tested varieties, S7 (316: yellow Catuai) exhibited the most comprehensive nutrient profile with the highest overall element content, identifying it as a high-yielding genotype suitable for intensive cultivation systems. In contrast, S8 (036: Castillo) demonstrated superior microbial community stability and ecosystem robustness, characterizing it as an ecological genotype ideal for organic coffee production and sustainable farming practices. It is recommended that these two varieties be promoted as core genetic resources for future breeding programs and microbial ecology-based management strategies, thereby facilitating the dual objectives of high productivity and ecological sustainability in coffee cultivation. Thus, we recommend that these two varieties be prioritized as core subjects in future breeding programs that integrate rhizosphere ecology with yield evaluation, thereby exploring pathways toward the dual objectives of productivity and sustainability.