Beneficial Effect of Rhizospheric Soils of Some Native Mediterranean Plants on Germination and Early Growth of Almond (Prunus dulcis (Mill.))

Abstract

Native soils host diverse symbiotic microflora that contribute to sustainable agricultural practices and plant establishment. This study aims to investigate the benefits of rhizosphere soil microbiota associated with four Mediterranean native plants, Rhus pentaphylla (NS1), Drimia maritima (NS2), Pistacia lentiscus (NS3), and Withania frutescens (NS4), growing in proximity to the local Moroccan almond variety Prunus dulcis (Mill.) (NS5). Native soils were applied directly as living substrates to evaluate their effects on the germination and early development of almond, with particular emphasis on the potential of arbuscular mycorrhizal fungi (AMFs). Root analysis revealed high mycorrhizal colonization intensity (M% = 87.5–95%) and infectivity (F% = 100%). Under the tested soil conditions, three native soils (NS1, NS3, and NS5) achieved germination rates exceeding 70% after 28 days. Moreover, NS5 and NS1 soils showed the strongest effects on almond germination and seedling growth, respectively. Overall, the use of native soils enhanced almond germination and early development, highlighting the role of AMFs as natural biofertilizers. The associated native plant species may also function as nurse plants that facilitate almond establishment. These findings support the use of the rhizosphere microbiome as a bio-based strategy to promote sustainable almond cultivation in local and Mediterranean agroecosystems.

1. Introduction

Almond (Prunus dulcis (Mill.)), a member of the Rosaceae family, is one of the most economically valuable nut crops worldwide. Originating from Central Asia, it is among the earliest domesticated fruit trees [1]. Today, global production is dominated by the United States (≈50% of total supply), with Mediterranean countries such as Spain, Italy, Morocco, and Turkey also contributing significantly [2]. However, almond cultivation in the southern Mediterranean is challenged by arid and semi-arid climates [3,4], which limit the success of introduced high-yield cultivars [5]. Furthermore, the expansion of commercial almond varieties has contributed to the erosion of biodiversity and the decline of local genetic resources [6]. In contrast, traditional almond varieties frequently exhibit distinctive sensory and nutritional qualities and hold value for cosmetic and pharmaceutical applications [7,8]. The use of autochthonous varieties may provide an opportunity to conserve native genetic resources [9] while supporting resilient and sustainable agricultural systems in Mediterranean environments [10].

In southern Mediterranean countries, particularly in Morocco, local farming systems often remain traditional and depend on irregular rainfall [11]. This climatic variability increases the vulnerability of farming systems and partly explains the limited success of almond expansion and reforestation programs implemented in several regions of the country [12]. The introduction of high-yielding foreign cultivars may also contribute to these limitations, as they are often poorly adapted to local environmental conditions [13]. In this context, the adoption of regenerative agricultural practices that prioritize local varieties establish an advantageous approach to improve the sustainability of almond production systems [14]. In Morocco, local almond trees (“Beldi”) often grow wild in mountainous areas, adapted to erratic rainfall [15]. They coexist with diverse native Mediterranean vegetation that varies from well-conserved to severely degraded, depending on the degree of afforestation activities that have disturbed or replaced the plant communities [16,17]. Such vegetation assemblages form characteristic grassland, steppe, and pre-forest ecosystems dominated by a diversity of plant species [17].

Although this native vegetation is frequently used by local populations for domestic purposes [18,19], its ecological potential is often overlooked. In particular, several plant species may function as nurse plants, providing important benefits for seed germination, seedling establishment, soil fertility, and overall agricultural productivity [20,21]. This potential is closely related to their capacity to sustain diverse communities of beneficial microorganisms in the rhizosphere [22,23]. Such indigenous symbiotic microflora consists of various bacterial and fungal groups capable of enhancing plant growth. Plant growth-promoting microorganisms (PGPMs) mediate plants’ accessibility to nutrients, regulate phytohormone secretion, improve plant adaptability to external stresses, and enhance overall plant health [22,24]. Among these microorganisms, arbuscular mycorrhizal fungi (AMFs) establish symbiotic associations with plant roots, which promote the assimilation of water and nutrients and play a significant role in maintaining soil and plant health [25,26]. Previous research has demonstrated that AMFs boost the drought resilience of almond by improving their water intake [6,27] and nutrient absorption, which supports overall plant growth [28]. These findings raise the question of whether native plant rhizospheric soils can be used to sustainably improve the regeneration and cultivation of local almond varieties.

Therefore, the focus of this work is to assess the effects of selected rhizosphere soils of indigenous plant species (Rhus pentaphylla, Drimia maritima, Pistacia lentiscus, and Withania frutescens), with particular emphasis on the potential role of AMFs in the germination and seedling growth improvement of almond (Prunus dulcis (Mill.)).

2. Materials and Methods

2.1. Soil Sampling

Six types of rhizospheric soils were obtained from the Azilal region, Morocco (31° 57′ 51″ N, 6° 34′ 27″ O), and used as substrates. Four indigenous plant species were used (Rhus pentaphylla (NS1), Drimia maritima (NS2), Pistacia lentiscus (NS3) and Withania frutescens (NS4)). Prunus dulcis (Mill.) tree soil (NS5) and a bare soil (NS0) were selected for comparison and negative control, respectively. Soils were collected along the soil profile, extending from the topsoil down to a depth of 25–35 cm, including the main zone of root–microbe interactions, in order to include the biologically active rhizospheric layer while also capturing deeper soil fractions, where a considerable diversity of AMF species can still be present [29]. During sampling, fine roots were intentionally included, and the collected material was not subjected to separation between root-adhering and loosely associated soil fractions. Consequently, the samples represent intact plant-associated soil, integrating rhizosphere soil, surrounding bulk soil, and root fragments. This approach was adopted to preserve the native structure and functional integrity of the natural system.

Samples were collected using sterilized tools according to Manaut et al.’s (2023) method [30], with slight modifications. In each homogeneous and undisturbed area, five shrubs spaced approximately 20 m apart were randomly chosen for sampling. All collected soils were homogenized to obtain a composite sample for the experimental replicates.

2.2. Selection and Preparation of Seeds

In December 2022, almond seeds were collected from a local farmer in Ait Atab, Azilal, Morocco (32° 6′ 36″ N, 6° 40′ 48″ W). These seeds correspond to the wild local almond variety “Beldi”, which has been traditionally cultivated, harvested, and conserved by the local population for decades. After collection, seeds were maintained under cool, dry conditions before being sorted to select high-quality ones based on weight, size, and integrity. Exocarps were discarded, and endocarps were sterilized on the surface using 5% sodium hypochlorite for 10 min, and rinsed well using sterile distilled water [31]. Prior to sowing, the endocarps were carefully cracked without damaging the kernel, and the seeds were sown immediately thereafter.

2.3. Experimental Design and Culture Conditions

The experiment followed a completely randomized design. Standard polyethylene nursery bags, provided by a local agricultural supplier (diameter = 10 cm; height = 20 cm), were used as a growing support in this experiment. In each bag, two seeds of uniform size were sown. The experiment was carried out in an open greenhouse at an average temperature of 20–38 °C. Direct seeding was applied, following traditional practices used by local farmers in the Azilal region. There were four treatments containing 100% of soil samples from each of the four associated native plants; one treatment with 100% soil sample from local almond trees; and one control treatment with 100% of bare soil, which had been previously sterilized at 180 °C for 4 h. Each treatment included 24 replicates for germination assays and 12 replicates for seedling growth measurements. The plants were irrigated regularly to avoid water stress.

Germination was monitored during the early establishment phase and stabilized within 28 days after sowing, at which point final germination rates were recorded. Seedling growth parameters were monitored periodically throughout the experiment to follow plant development; however, only the final measurements taken at 70 days after sowing were used for statistical analysis, as they best represent the cumulative effect of the different soil treatments.

2.4. Spore Extraction and Identification

Spore extraction was performed using the method described by Gerdemann and Nicolson (1963) [32]. Briefly, a soil–water suspension of 100 g of homogenized soil was sieved through 315 μm and 50 μm meshes with low pressure flow. Spores retained on the sieves were concentrated with a sucrose solution and enumerated using a binocular stereomicroscope at ×40 magnification (Nikon co., Tokyo, Japan). Distinct morphotypes were identified based on the descriptions provided by The International Collection of (Vesicular) Arbuscular Mycorrhizal Fungi database [33].

2.5. Mycorrhization Assessment: Most Probable Number Test (MPN)

The assessment of the mycorrhization potential was carried out by the most probable number of propagules test (MPN) [34]. The MPN test was used as a first test to assess the potentialities of the frequency and intensity of mycorrhization. The experimental setup consists of 6 dilutions (1, 1/4, 1/16, 1/64, 1/256 and 1/1024) with 5 repetitions per dilution. A total of 30 plastic pots (⌀ 6 cm × 8 cm) for each soil sample were filled with 100 g of soil. The soil samples were diluted with sterile sand, which was sterilized at 180 °C for 4 h to destroy potential existing microbiota. Zea mays (maize, corn) is used as a model of mycotrophic plant. The maize seeds received a 10 min sterilization step in a 2% sodium hypochlorite solution; then, they were thoroughly washed using distilled water and placed directly in the soil samples for germination and seedling growth. The test was taken under greenhouse conditions, with daily regular irrigation for 8 weeks.

To visualize the mycorrhizal structures, the seedlings were carefully uprooted and their root systems were meticulously cleared with 10% KOH at 90 °C for 30 min, followed by a 10 min acidification step in 1% HCl; then, they were stained with Trypan blue at 90 °C for 20 min [35]. Subsequently, the roots were cut into 1 cm segments and prepared for observation under microscope. The presence of at least one point of infection in a root system was sufficient for it to be classified as mycorrhizal [36]. The most probable number of propagules (MPN) was calculated using the formula:

$$LogMPN=\left(xloga\right)-K,$$

(1)

where x represents the average of mycorrhizal pots; a represents the dilution factor; y is necessary to determine K in the Fisher and Yates table [37], which equals to s − x (s is the number of dilutions).

2.6. AMF Root Colonization

Fragments of lateral roots from the MPN test were used to assess AMF colonization. The roots were cleaned and colored as previously described (see Section 2.5.). AMF infectivity (F%) and colonization intensity (M%) were assessed on root fragments following the approach outlined by Trovelot et al. (1986) [38], using the equations below:

$$F\%=(N-n0)/N\times 100,$$

(2)

where N is the total number of examined fragments; n0: number of fragments showing no evidence of mycorrhizal colonization.

$$M\%=(95\times n5)+(70\times n4)+(30\times n3)+(5\times n2+n1)/N,$$

(3)

where n5, n4, … n1 represent the counts of fragments assigned to classes 5 through 1, respectively; class 5: >91% colonized; class 4: 51–90%; class 3: 11–50%; class 2: <10%; class 1: trace only; class 0: no mycorrhizal presence.

2.7. Soil Physicochemical Assessment

Soil physicochemical characteristics, such as total organic carbon (TOC), total nitrogen (N), available phosphorus (AP), pH and electrical conductivity (EC), were determined. pH and EC were measured in a 1:5 (v/v) soil-to-water suspension (NF ISO 10390, 2021) [39], while air-dried samples sieved to 2 mm were used to determine TOC and organic matter via the Anne method [40,41], AP by the Olsen method [42], and total nitrogen according to the procedure described by Kjeldahl (1883) [43].

2.8. Germination Parameters

After 19 days from sowing under different treatments, the appearance of dicotyledonous leaves was considered a sign of emergence following successful germination. Several germination parameters were then calculated. The First Day of Germination (FDG) corresponds to the day when the first seed germinated, with lower FDG values reflecting quicker germination [44]. The germination percentage (GP %) was determined according to Kader (2005) [45] using the following equation:

$$GP=(Numberofgerminatedseeds/Totalnumberofseeds)\times 100,$$

(4)

The Mean Germination Time (MGT) was determined according to Orchard (1977) [46]:

$$MGT\left(d\right)=\sum (f\times x)/\sum f,$$

(5)

where f represents the number of seeds germinated on day x.

A small MGT value indicates rapid seed germination. The speed of germination across the population was further quantified using the Germination Rate Index (GRI) as described by Kader (2005) [45].

$$GRI=G1/1+\cdots +Gx/x,$$

(6)

where G1 represents the germination percentage on the first day after sowing and Gx denotes the germination percentage on day x.

The GRI (% d⁻¹) indicates germination progression on each day, with higher values indicating more rapid germination.

2.9. Seedling Growth Parameters

After germination, seedling growth was assessed using parameters including Total Number of Leaves (TNL), Whole Seedling Length (WSL, cm), Growth Speed of Seedlings (GSS, cm d⁻¹), and Seedling Vigor Index (SVI).

Growth Speed of Seedlings (GSS, cm d⁻¹) was calculated as the increase in Whole Seedling Length per day, following the equation provided by El-Saifi et al. (2010) [47]:

$$GSS=(H2-H1)/t,$$

(7)

where H1 is the seedling height (cm) recorded on the first day of observation; H2 is the seedling height (cm) at the final day of the experiment (day 70); t is the number of days between the two measurements (t2-t1).

Seedling vigor was quantified by calculating the Seedling Vigor Index (SVI) using the adapted formula originally described by Abdul-Baki and Anderson (1973) [48]:

$$SVI=Shootlength\left(cm\right)\times Germinationpercentage\left(\%\right),$$

(8)

Seed lots with higher SVI values are considered more vigorous.

2.10. Statistical Analysis

An ANOVA test was used for data analysis. Average values were statistically compared using Tukey’s post hoc test after confirming data normality, with significance set at p ≤ 0.05. Results are presented as mean ± standard deviation. Principal component analysis (PCA) was performed to evaluate the relationships between soil physicochemical properties and germination and seedling growth parameters. All data analyses were performed with IBM SPSS Statistics, version 26.0. PCA plot was generated by R software (version 4.5.0). Hierarchical Clustering Analysis was performed for all physicochemical and biological variables of the studied soils using Past software (Past 4.11 version). Also, based on the same software, the biological parametric data were converted into score ranks from 6 to 1 depending on the power of each parameter. The highest score of the parameter indicates a high-power level of the related soil sample.

3. Results

3.1. Soil Physicochemical Characterization

The physicochemical properties of the soil samples prior to direct sowing are summarized in Table 1. Differences in pH and electrical conductivity (EC) were detected among the five soil samples compared with the control. Soil pH ranged from neutral to slightly alkaline (7.7–8.12), while EC values indicated non-saline soil samples (0.12–0.69 mS/cm). Soil samples NS1 and NS5 had EC values similar to the control, whereas NS4 recorded the highest EC (0.69 mS/cm). For total nitrogen (N), available phosphorus (AP), and total organic carbon (TOC), all five soil samples differed significantly from the control, though differences among the soil samples themselves were minimal. Among the treatments, the control soil sample recorded the lowest values for TOC, N, and AP. TOC levels were highest in NS1, NS2, and NS4, showing similar values of approximately 2.35%. Available phosphorus content was moderate to slightly higher in all soil samples compared with the control, with the highest concentrations observed in NS1 (34.68 mg g⁻¹) and NS5 (48.27 mg g⁻¹). All soil samples displayed very low nitrogen contents, ranging from 0.02 to 0.03%. Overall, the soil samples exhibited alkaline pH values, intermediate electrical conductivity, elevated TOC and AP contents, and low nitrogen levels.

Table 1. Physicochemical parameters at the initial state of all soil samples.

Native Soils	pH	EC (ms cm−1)	TOC (%)	N (%)	AP (mg g−1)
NS0	9.11 ± 0.005 f	0.23 ± 0.005 c	0,00 ± 0.00 a	0.02 ± 0.00 a	6.34 ± 0.00 a
NS1	7.70 ± 0.01 a	0.24 ± 0.01 cd	2.35 ± 0.00 d	0.02 ± 0.00 b	34.68 ± 1.92 d
NS2	7.79 ± 0.01 b	0.12 ± 0.01 a	2.35 ± 0.01 d	0.03 ± 0.00 c	19.28 ± 0.43 c
NS3	8.04 ± 0.01 c	0.16 ± 0.01 b	0.79 ± 0.01 b	0.02 ± 0.01 b	13.76 ± 0.11 b
NS4	7.9 ± 0.01 d	0.69 ± 0.00 d	2.34 ± 0.00 d	0.03 ± 0.00 c	18.85 ± 1.41 c
NS5	8.12 ± 0.01 e	0.26 ± 0.005 e	1.57 ± 0.01 c	0.02 ± 0.00 b	48.27 ± 1.75 e

^a,b,c,d,e,f Different letters indicate statistically significant differences based on Tukey’s post hoc test following one-way ANOVA (p ≤ 0.05). Numbers after ± represent the standard deviation of the mean (n = 3).

3.2. Morphological Identification and Quantification of AMF Spores

A total of 21 taxa were identified across the tested soils, representing seven genera: Rhizophagus, Septoglomus, Glomus, Dentiscutata, Scutellospora, Acaulospora, and Cetraspora (Figure 1).

Figure 1. Morphological characterization of AMF spores presents in the studied indigenous soils (a–e) ((a) Scutellospora sp.; (b) Cetraspora sp.; (c) Glomus sp.; (d) Glomus maculosum; (e) Acaulospora sp.) and different AMF colonization structural patterns in maize roots (f,g) (inter- and intraradical hyphae (H); vesicles (V); spores (S); and endophytes (E)). Scale bar 100 µm (40× magnification).

In all soil samples, the first four AMF genera (Dentiscutata, Septoglomus, Glomus, and Rhizophagus) accounted for over 85% of the total spore population. Significant differences were detected among the soil samples (p < 0.05), with spore densities ranging between 935 and 1977 spores for 100 g of soil. The highest density was observed in the rhizospheric soil of Prunus dulcis (Mill.) (NS5), whereas the lowest density was assessed in Pistacia lentiscus soil (NS3) (Table 2).

Table 2. Density of AMF spores in the tested soils and their frequency and intensity assessed by the MPN test.

Native Soils	AMF Spore Density (100 g−1 of Soil)	Mycorrhization Intensity (M %)	AMF Infectivity (F %)
NS1	1578 ± 1 e	87.83 ± 0.6 c	100% b
NS2	1542 ± 1 d	87.5 ± 0.01 b	100% b
NS3	935 ± 1 b	94.17 ± 1.4 d	100% b
NS4	1327 ± 1 c	94.17 ± 1.4 d	100% b
NS5	1977 ± 1 f	95.00 ± 0.0 e	100% b
NS0	0 ± 0 a	0 ± 0 a	0 ± 0 a

^a,b,c,d,e,f Different letters followed values indicate significant differences according to Tukey’s post hoc test after one-way ANOVA (p ≤ 0.05). Data are presented as mean ± standard deviation (n = 3).

3.3. Intensity and Frequency of Mycorrhization

Root colonization was assessed by staining the roots of a mycotrophic plant (Zea mays) used in the MPN test. Soil samples from the five target plant species exhibited comparable numbers of mycorrhizal propagules, with an estimated most probable number (MPN) of 1149.11 propagules per 100 g of rhizosphere soil.

Microscopy confirmed the presence of all the structures related to AMF infection (hyphae, vesicles, and spores) (Figure 1). All five soil samples showed maximum infectivity, with colonization frequency (F%) reaching 100% compared to the control. Regarding the intensity of mycorrhization (M%), roots grown in the five soil samples exhibited high and significant colonization (p < 0.05), ranging from 87.5% to 95%. NS3 and NS4 remained statistically comparable, while the highest intensity was observed in the Prunus dulcis (Mill.) soil (NS5), and the lowest in the Pistacia lentiscus soil (NS3).

3.4. Germination and Seedling Assessment

3.4.1. Assessment of Germination Parameters

As presented in Table 3, the use of these soil samples as living substrates had a significant influence on germination after 28 days (p < 0.05), with three treatments (NS1, NS3, and NS5) exceeding 70%. This effect became more pronounced by day 35, when all treatments recorded germination rates above 83.33%. By day 49, maximum germination levels were reached in all soil samples, with all treatments except NS3 showing significant differences compared to the control (NS0). No further increase was observed thereafter, and germination remained stable until day 70.

Table 3. Germination rate under the tested soils for 70 days.

Treatment	Day 28	Day 35	Day 42	Day 49	Day 56	Day 63	Day 70
NS1	87.50 ± 2.08 e	87.50 ± 2.08 a	87.50 ± 2.08 a	87.50 ± 2.08 a	87.50 ± 2.08 a	87.50 ± 2.08 a	87.50 ± 2.08 a
NS2	50.00 ± 4.17 c	91.67 ± 6.25 ab	95.83 ± 4.17 b	95.83 ± 4.17 bc	95.83 ± 4.17 ab	95.83 ± 4.17 ab	95.83 ± 4.17 ab
NS3	79.17 ± 3.13 de	100 ± 0.00 b	100 ± 0.00 b	100 ± 0.00 c	100 ± 0.00 b	100 ± 0.00 b	100 ± 0.00 b
NS4	33.33 ± 2.92 b	83.33 ± 5.00 a	87.50 ± 2.08 a	91.67 ± 2.50 ab	91.67 ± 4.17 ab	91.67 ± 4.17 ab	91.67 ± 4.17 ab
NS5	70.83 ± 3.75 d	87.50 ± 4.17 a	87.50 ± 4.17 a	87.50 ± 4.17 a	87.50 ± 4.17 a	87.50 ± 4.17 a	87.50 ± 4.17 a
NS0	16.67 ± 4.17 a	91.67 ± 2.92 ab	100 ± 0.00 b	100 ± 0.00 c	100 ± 0.00 b	100 ± 0.00 b	100 ± 0.00 b

^a,b,c,d,e Values with different letters differ significantly following to Tukey’s post hoc test following one-way ANOVA (p ≤ 0.05). Values are presented as mean ± standard deviation (n = 24).

To assess the effect of native rhizospheric soils on germination, three parameters were determined and combined (FDG, MGT, and GRI). Each indicator was assigned a numerical rating on a scale from 1 to 6, reflecting its relative strength (Table 4).

Table 4. Classification of the target soils based on the hierarchical strength of germination indicators * on day 28.

Treatment	FDG (Day)	FDG Rank	MGT-28 (Day)	MGT-28 Rank	GRI-28 (%/day)	GRI-28 Rank	Germination Mean Rank
NS1	20	2	25.20	2	4.6	1	1.66
NS2	22	4	25.81	4	1.64	4	4
NS3	20	2	25.20	2	4.36	2	2
NS4	22	4	26.10	5	1.43	5	4.66
NS5	19	1	24.65	1	4.15	3	1.66
NS0	25	6	26.75	6	0.44	6	6

* FDG, First Day of Germination; MGT, Mean Germination Time; GRI, Germination Rate Index.

The average germination ranking revealed that NS1 and NS5 soil samples exhibited the strongest effects on almond seed germination, followed by NS3, NS2, and NS4, as reflected by the germination indicators, whereas the control soil sample (NS0) ranked lowest. Accordingly, the rhizospheric soils can be classified by their progressively decreasing effects on germination in the following order: NS1 = NS5 > NS3 > NS2 > NS4 > NS0 (Table 4).

3.4.2. Assessment of Seedling Growth Parameters

Seedling growth parameters measured at day 70 and mean values of WSL-70, TNL-70, SVI-70, and GSS-70 were calculated (Table 5). Each seedling growth parameter was assigned a numerical rating from 1 to 6, reflecting its relative hierarchical effect. The combined evaluation of these parameters allowed the soil samples to be arranged by their impact on seedling growth, resulting in the decreasing order NS1 > NS4 > NS3 > NS2 > NS5 = NS0 (Table 5). This classification identifies NS1 as the soil sample most conducive to almond seedling growth, followed by NS4, NS3, and NS2, whereas NS5 and the control soil sample (NS0) exhibited similar and lowest scores.

Table 5. Seedling growth parameters * at day 70 under the tested soil treatments.

Treatment	WSL-70 (cm)	WSL-70 Rank	TNL-70	TNL-70 Rank	SVI-70	SVI-70 Rank	GSS-70 (cm/day)	GSS-70 Rank	Seedling Mean Rank
NS1	33.79 ± 5.6	1	48.92 ± 9.8	1	29.56	1	0.57	2	1.25
NS2	25.33 ± 5.6	4	38.25 ± 6.6	6	24.27	4	0.45	4	4.5
NS3	28.54 ± 3.4	3	39.83 ± 8.7	5	28.54	3	0.49	3	3.5
NS4	32.25 ± 4.2	2	42.5 ± 8.2	2	29.56	1	0.59	1	1.5
NS5	24.45 ± 4.7	5	41.81 ± 9.2	3	21.39	6	0.41	6	5
NS0	23.85 ± 5.2	6	39.92 ± 16.7	4	23.85	5	0.43	5	5

Results are shown as mean ± standard deviation (n = 12). * WSL, Whole Seedling Length; TNL, Total Number of Leaves; GSS, Growth Speed of Seedlings; SVI, Seedling Vigor Index.

The soil samples exhibited distinct germination and seedling growth effects (Figure 2). NS1 and NS5 were the most effective in promoting germination. However, the impact on seedling growth differed; NS1 had the strongest effect, while NS5 this time showed the lowest performance. These results suggest that soil samples that favor germination do not necessarily ensure the highest seedling growth.

Figure 2. Experimentation at day 28 of almond seedlings in different soil treatments ((a) bare soil (NS0); (b) Rhus pentaphylla (NS1); (c) Drimia maritima (NS2); (d) Pistacia lentiscus (NS3); (e) Withania frutescens (NS4); (f) Prunus dulcis (Mill.) (NS5)).

3.5. Potential of Interdependencies of All Quantified Parameters

To examine the interrelationships among germination and seedling growth responses in relation to initial soil physicochemical properties, arbuscular mycorrhizal fungus (AMF) spore density, and mycorrhizal infectivity and intensity derived from the MPN test, a principal component analysis (PCA) was carried out. This multivariate approach allowed the reduction of a large set of measured variables into a limited number of factors, grouping variables according to their underlying correlation structures. The PCA indicated that most variables were explained by two principal components, accounting for a cumulative variance of 50.96% (Figure 3). The first axis (F1) accounted for 30.7% of the overall variance and was mainly related to spore density, mycorrhizal intensity (M%), available phosphorus (AP), total organic carbon (TOC), and germination rank, exhibiting correlation coefficients between 0.62 and 0.98. These results indicate that almond germination is strongly linked to AMF spore density, mycorrhizal intensity, and soil organic carbon and phosphorus contents. The second axis (F2) captured 20.26% of the overall variability, reflecting the influence of soil electrical conductivity, nitrogen content, and seedling growth rank, with correlation coefficients exceeding 0.63. These results indicate that almond seedling growth is primarily influenced by initial soil conductivity and nitrogen availability.

Figure 3. Principal component analysis of germination parameters and seedling growth, in response to the initial physicochemical parameters of soil samples. (M%) Intensity of infection; (F%) frequency of mycorrhization; (Ds) density of AMF spores; (AP) available phosphorus; (N) total nitrogen; (TCO) total organic carbon; (pH) potential hydrogen; (EC) electrical conductivity; (GP) germination parameters; (SP) seedling parameters.

4. Discussion

The transition toward sustainable agricultural systems requires reducing dependence on synthetic inputs while maintaining crop performance. This study suggests that native rhizospheric soils, through their rich microbial communities, can contribute to promoting almond germination and early growth, supporting low-input and ecologically based farming practices. However, these results, obtained under open greenhouse conditions, may not fully reflect field conditions, due to the complexity of the natural environment. Nevertheless, similar studies have shown that native soils enhance seedling growth compared to sterilized or artificial substrates, emphasizing the key role of soil microbial communities and plant–soil interactions in early plant development [49]. Marked differences (p < 0.05) were detected among soil samples in terms of arbuscular mycorrhizal fungus (AMF) spore density and root colonization. Across all treatments, mycorrhizal colonization was consistently high, with intensity values between 87.5% and 95% and full colonization frequency (F% = 100%), supporting a potential role of indigenous AMF communities.

A positive association between AMF spore density and colonization intensity suggests that higher propagule abundance enhances root–fungus symbiosis. The almond-associated soil sample (NS5) exhibited the greatest spore density and colonization levels, while Pistacia lentiscus (NS3) showed the lowest values (Table 2). Spore density is widely considered a reliable indicator of mycorrhizal inoculum potential and ecological persistence, particularly under variable environmental conditions [50,51]. These results support the role of native soils as reservoirs of functional microbial diversity capable of sustaining plant–soil interactions [52].

The beneficial effects observed can be attributed not only to AMFs but also to the broader rhizosphere microbiome, which is closely linked to AMF spores and extraradical mycelium [53]. These interactions stimulate spore germination and enhance root colonization [54]. This complex microbial network contributes to various plant growth-promoting activities, such as phosphorus solubilization, nitrogen fixation, as well as the production of biocontrol metabolites [55,56]. Notably, numerous studies have demonstrated that seeds inoculated with AMFs improve germination performance and plant vigor through these mutualistic interactions [26,57].

Accordingly, the soil samples classification based on germination parameters revealed that NS1 and NS5 had the strongest and statistically comparable effects at early stages, followed by NS3, NS2, and NS4 (Table 4). In contrast, seedling growth was most pronounced in NS1, followed by NS4, NS3, NS2, and NS5, with the control consistently showing the lowest performance (Table 5; Figure 2). This divergence indicates that soil samples favorable for germination are not necessarily optimal for subsequent growth, reflecting differences in nutrient availability and microbial functionality. While certain rhizospheric soils enhance early germination through active microbial signaling, others appear more effective in sustaining plant growth over time. This suggests complementary ecological roles among native plant–soil systems, reinforcing their potential contribution to sustainable and resilient agroecosystems.

The strong effect on germination response observed in the soil of the almond tree (NS5) and the soil of Rhus pentaphylla (NS1) may be explained by the presence of well-adapted indigenous microbial communities, particularly AMFs [58]. In particular, the high spore density and colonization levels recorded in NS5 indicate a favorable rhizospheric environment that supports early plant establishment (AMF density (spores per 100 g of soil) was 1977; M%= 95%; F%= 100%). Similar colonization levels have been reported in arid Moroccan systems, such as date palm rhizospheres in the Figuig oasis, where mycorrhization rates reached 91–93% in soils with high propagule abundance, despite low soil fertility and harsh environmental conditions [59]. This effect can be attributed to indigenous soil of the mother plant providing a favorable rhizosphere condition that promotes both seed germination and natural regeneration [60,61]. The plant engages in chemical signaling that regulates phytohormones, fatty acids, and phenolic compounds, which promote germination [24].

The principal component analysis further provided an exploratory overview of these relationships and separated the studied variables into two main groups (Figure 3). The first group includes spore density, mycorrhization intensity (M%), seed germination parameters, TOC, and available phosphorus (AP), suggesting a possible association with soil biological activity and organic matter dynamics. The second group comprising seedling growth parameters, soil nitrogen (N), and electrical conductivity showed a different distribution pattern. Overall, the initial soil conditions can be described as poor to moderately fertile, characterized by an alkaline pH, intermediate conductivity (EC), relatively elevated TOC and AP, and low N content (Table 1). These relationships may be explained by intense beneficial microbial activity, which promotes strong AMF spore germination under nutrient-poor soil conditions. Indeed, higher AMF infectivity and spore activity are frequently observed in low-fertility soils compared to fertilized ones [50,62,63]. This enhanced mycorrhizal activity subsequently facilitates nutrient mobilization, ultimately benefiting plant development and promoting seedling growth. However, these interpretations should be considered as indicative patterns rather than direct relationships.

In the present study, the classification of the soil samples identifies NS1 as the most effective soil in promoting both almond germination and seedling growth. The associated plant Rhus pentaphylla can therefore be considered a potential nurse plant for sustainable almond growth, facilitating its establishment through both biotic and abiotic mechanisms. These results shed light on new perspectives for Rhus pentaphylla as a source of beneficial microbial inoculum from the rhizosphere, particularly arbuscular mycorrhizal fungi (AMFs). This observation is consistent with studies showing that native plant communities can enhance AMF abundance and propagation, particularly in Mediterranean environments, where vegetation structure plays a key role in maintaining symbiotic fungal networks [64]. However, further studies are needed to confirm this role and elucidate the underlying mechanisms. To our knowledge, Rhus pentaphylla has not previously been reported as a nurse plant or as a reservoir of beneficial AMFs, unlike other plants species such as Pistacia lentiscus [65] and Withania frutescens [66].

The PCA suggests that almond seedling growth tends to be associated with abiotic factors, particularly soil nitrogen content and electrical conductivity. However, this analysis reflects patterns of association rather than direct causality. Although almond cultivation typically requires neutral to alkaline soils, the species can also adapt to moderately acidic conditions [67]. In the present study, AMFs, as a symbiotic component of the soil microflora, may therefore also contribute to seedling development [26,56]. Both nearby nurse plants and more distant native species can positively influence germination and early growth [52]. Despite the global presence of almond trees in non-native habitats, field data on their naturalization and associated wild flora remain limited.

Overall, this study highlights the potential of native plant-associated soils as a resource for sustainable agriculture. Using locally adapted plant–microbe interactions may contribute to improve crop establishment, reduce reliance on synthetic inputs, and promote the conservation of native biodiversity. Such approaches align with sustainable agriculture and offer a foundational framework to enhance the resilience of agroecosystems under changing environmental conditions.

The development of targeted bioinoculants derived from native soils, particularly those associated with Rhus pentaphylla, represents a promising direction for sustainable almond production. However, the findings of this study have to be seen in light of some limitations. First, future studies should incorporate the assessment of other soil nutrient and abiotic environmental parameters to better understand nutrient dynamics and optimize plant growth and nutrition strategies.

The second limitation concerns validation under field conditions to evaluate the consistency and applicability of these results in more complex and variable agroecosystems. Furthermore, long-term investigations are needed to assess the persistence of these effects on mature plant performance, yield, and soil health. In addition, future studies should incorporate molecular approaches to achieve species-level identification and better characterize the functional composition of AMFs and associated microbial communities.

5. Conclusions

Native soils associated with the surrounding flora, under the conditions of this study, enhanced almond germination and early seedling development, highlighting the potential role of rhizosphere microbial communities in early plant establishment. The results suggest that inocula based on locally adapted microbial communities can support crop establishment and reduce reliance on synthetic inputs, which offer promising perspectives for sustainable almond cultivation. This study therefore mentions the promising potential of AMFs as a sustainable strategy to facilitate the naturalization of almonds through direct sowing, particularly in poor or moderately fertile soils. However, future research under field conditions is required to assess the persistence of these effects in productive almond trees, where environmental variability and multiple stress factors may influence plant–soil–microbe interactions.