Cultivable Rhizosphere Microbial Community Structure in the Yaqui Valley's Agroecosystems

Abstract

Agricultural practices affect the physical, chemical, and biological properties of soil in agroecosystems. This study evaluated the impact of food production strategies on the rhizosphere microbial communities in the Yaqui Valley, Mexico, on key crops (Medicago sativa, Brassica oleracea, Asparagus officinalis, Phaseolus vulgaris, Citrus sinensis, Zea mays, Solanum tuberosum, Triticum durum, and an undisturbed native ecosystem). Soil samples were collected from 30 cm depths across one-hectare fields and analyzed for bulk density, pH, organic matter content, and electrical conductivity. Standardized methods were used for these analyses, along with microbial isolation through culturing, PCR amplification, and DNA sequencing for microbial identification. The use of synthetic fertilizers in the region was linked to increased salinity and soil compaction. Organic matter content was notably low at ≤1.4%, which negatively impacted microbial diversity. A total of 317 microbial strains were isolated, with bacteria comprising 73% and fungi 27%. Bacillus was the most dominant bacterial genus (41% of isolates), while Aspergillus was the most abundant fungal genus (31% of isolates). Crop-specific microbial strains were identified. This study provides the first detailed insight into how agricultural practices shape microbial communities in the Yaqui Valley's major crops, highlighting the link between soil properties and microbial diversity.

Full text

Citation: Valenzuela Ruiz, V.;
Cubedo-Ruiz, E.; Maldonado Vega,
M.; Garatuza Payan, J.; Yépez
González, E.; Parra Cota, F.I.; de los
Santos Villalobos, S. Cultivable
Rhizosphere Microbial Community
Structure in the Yaqui Valley’s
Agroecosystems. Soil Syst. 2024,8, 112.
https://doi.org/10.3390/
soilsystems8040112
Academic Editor: Luis Eduardo
Akiyoshi Sanches Suzuki
Received: 29 August 2024
Revised: 26 October 2024
Accepted: 27 October 2024
Published: 31 October 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Cultivable Rhizosphere Microbial Community Structure in the
Yaqui Valley’s Agroecosystems
Valeria Valenzuela Ruiz 1, Edgar Cubedo-Ruiz 2, Maria Maldonado Vega 3, Jaime Garatuza Payan 1,
Enrico Yépez González 1, Fannie Isela Parra Cota 2, * and Sergio de los Santos Villalobos 1,*
1Department of Veterinary and Agri-Food Sciences and Water and Environmental Sciences,
Instituto Tecnológico de Sonora, 5 de Febrero 818 sur, Cd. Obregon 85000, Sonora, Mexico;
valeriavalenzuelaruiz@gmail.com (V.V.R.); jaime.garatuza@itson.edu.mx (J.G.P.);
eyepez@itson.edu.mx (E.Y.G.)
2Campo Experimental Norman E. Bouleaug, Cd. Obregon 85000, Sonora, Mexico; ecubedo@hotmail.com
3
Dirección de Enseñanza e Investigación, Hospital Regional de Alta Especialidad del Bajío, Blvd. Milenio 130,
San Carlos la Roncha, Leon 37544, Guanajuato, Mexico; vega.maldonado.m@gmail.com
*Correspondence: parra.fannie@inifap.gob.mx (F.I.P.C.); sergio.delossantos@itson.edu.mx (S.d.l.S.V.);
Tel.: +52-(01-55) 38-71-87-00 (ext. 81234) (F.I.P.C.); +52-(644)-410-0900 (ext. 2124) (S.d.l.S.V.)
Abstract: Agricultural practices affect the physical, chemical, and biological properties of soil in
agroecosystems. This study evaluated the impact of food production strategies on the rhizosphere
microbial communities in the Yaqui Valley, Mexico, on key crops (Medicago sativa,Brassica oleracea,
Asparagus officinalis,Phaseolus vulgaris,Citrus sinensis,Zea mays,Solanum tuberosum,Triticum durum,
and an undisturbed native ecosystem). Soil samples were collected from 30 cm depths across one-
hectare fields and analyzed for bulk density, pH, organic matter content, and electrical conductivity.
Standardized methods were used for these analyses, along with microbial isolation through culturing,
PCR amplification, and DNA sequencing for microbial identification. The use of synthetic fertilizers
in the region was linked to increased salinity and soil compaction. Organic matter content was
notably low at
≤
1.4%, which negatively impacted microbial diversity. A total of 317 microbial strains
were isolated, with bacteria comprising 73% and fungi 27%. Bacillus was the most dominant bacterial
genus (41% of isolates), while Aspergillus was the most abundant fungal genus (31% of isolates).
Crop-specific microbial strains were identified. This study provides the first detailed insight into how
agricultural practices shape microbial communities in the Yaqui Valley’s major crops, highlighting
the link between soil properties and microbial diversity.
Keywords: agriculture; microbial diversity; Yaqui Valley; soil degradation
1. Introduction
The Yaqui Valley in northwestern Mexico is one of the most intensive and productive
agricultural regions of the world, using advanced crop genotypes, irrigation systems, and
high synthetic fertilizer usage [
1
]. However, the application of high amounts of synthetic
fertilizers in combination with semi-arid climatic conditions in that region [low precipitation
(annual mean 384.5 mm), extreme temperatures (ranging from
−
2
◦
C to 44
◦
C), and high
relative humidity (annual mean 69%)] could explain the soil degradation in the Yaqui Valley,
i.e., low organic matter content (<1%), high salinity levels (electric conductivity > 4 dS/m),
and alkaline soils (pH: 8.9) [
2
–
5
]. However, the excessive use of N fertilizers can contribute to
soil compaction, as repeated mechanization and irrigation practices degrade soil structure.
Soil degradation is a growing conflict with 64% of the national territory about degraded
soil mainly due to livestock and agricultural practices [
5
]; this results in a modification of
microbial communities in agroecosystems, endangering the benefits obtained from these,
i.e., plant growth regulation, abiotic and biotic stress tolerance, plant nutrition (nutrient
availability and cycling), and biocontrol of phytopathogens [
5
–
9
]. Thus, soil microbiota is
Soil Syst. 2024,8, 112. https://doi.org/10.3390/soilsystems8040112 https://www.mdpi.com/journal/soilsystems

Soil Syst. 2024,8, 112 2 of 15
considered key for adequate ecosystem functioning since microorganisms carry ~80% to
90% of the most important edaphic functions in cropping ecosystems [10].
In addition, crops and microorganisms are involved in several biochemical and molec-
ular signaling events that establish specific symbiotic, endophytic, or associative relation-
ships focused on food production and/or microbial pathogen outbreaks for plants and
humans. However, those microbial niches vary according to the dynamics of biotic and
abiotic factors in agroecosystems, such as plant genotypes, climate and soil conditions, and
agricultural practices [
11
,
12
]. For example, the structure and diversity of soil microbial
communities are mainly influenced by fertilization strategies, soil physicochemical proper-
ties, and tillage, which may limit the ability of soil microbiota to mineralize nutrients [
13
].
Chemical fertilizers, while boosting crop yields, can have detrimental effects on these vital
soil microbial communities. Thus, excessive use of nitrogen fertilizers can contribute to soil
compaction and modify microbial community structures in agroecosystems [14].
Long-term application of chemical fertilizers has been shown to alter soil bacterial
community composition without necessarily influencing overall diversity [
15
]. These
changes can have profound effects on soil health and crop productivity. For instance, a
study found that prolonged chemical fertilization led to excessive ammonium-nitrogen
(NH4+) and available phosphorus (AP) residues in cultivated soil [
15
]. NH4+ resulted in
soil acidification and changes in bacterial community structure, while AP reduced fungal
diversity [
15
]. Similarly, a 10-year field experiment with varying nitrogen (N) application
rates demonstrated that long-term N fertilization significantly affected the most dominant
soil bacterial species by altering soil pH [
16
]. Moreover, research revealed that excessive
use of chemical fertilizers, especially nitrogen, led to the recruitment of less beneficial
bacteria and more pathogens in the rhizosphere soil of plants [
17
]. These factors specifically
affect the bacteria: fungi ratio in the soil, where conventional agricultural practices tend
to unbalance this ratio in comparison to a non-agricultural site [
14
]. Consequently, this
soil microbial degradation reduces soil fertility, ultimately impacting food production
and quality [
18
]. These findings underscore the complex interplay between fertilization
practices, soil properties, and microbial communities, highlighting the need for more
sustainable approaches to maintain soil health in agricultural systems.
Given the critical role of soil microbiota in sustainable agriculture and the potential
negative impacts of intensive chemical fertilization, there is an urgent need to understand
the relationships between fertilization practices, soil properties, and microbial communities.
This work aims to provide a first insight into the soils’ cultivable microbial communities
in agroecosystems of the Yaqui Valley in northwestern Mexico; we seek to correlate the
microbial population and diversity with soil physicochemical properties and the synthetic
fertilization doses used for the production of eight of the most important crops compared
to an undisturbed native ecosystem displaying native primary vegetation. The use of this
culture-dependent method is intended that in the future, we can bioprospecting -within
this cultivable microbial diversity- beneficial microbes related to plant growth promotion
or biological control for developing microbial inoculants with native strains adapted to
crop-specific agricultural practices, and thus, contribute to sustainable food production in
the region.
2. Materials and Methods
2.1. Soil Sampling
In the winter agricultural cycle 2015–2016, seven composite rhizospheric samples from
one-hectare commercial fields were collected randomly from each crop analyzed in the
Yaqui Valley (Table 1). Those fields were under production of the main economic crops in
the region: Triticum turgidum L. (wheat), Zea mays L. (maize), Medicago sativa L. (alfalfa),
Solanum tuberosum L. (potato), Phaseolus vulgaris L. (bean), Asparagus officinalis L. (asparagus),
Citrus sinensis L. (orange), and Brassica oleracea L. (broccoli). In addition, three composite
rhizospheric samples from one-hectare (each) undisturbed native ecosystem (for the past
60 years) were collected (native primary vegetation on site included Prosopis glandulosa,

Soil Syst. 2024,8, 112 3 of 15
Parkinsonia praecox,Cylindropuntia fulgida, and Selenicereus vagans). Composite rhizospheric
samples (n = 3, 30 cm depth, 6 individual samples) of each one-hectare commercial field and
undisturbed native ecosystems were collected and homogenized according to SAGARPA
and National Sanitary Service [
19
]. Collected samples were transferred in paper bags and
dried at 60 ◦C for physicochemical and nutrimental analysis. Samples for microbiological
analysis were placed in moist chambers and transported to the laboratory in a cooler at 4
◦
C.
Table 1. Crop management and sample sites of agriculturally important crops for the Yaqui Valley.
Crop Fertilizer Applied ha−1
N, P, K (kg) Sample Coordinates Crop Management
(Pesticides Applied)
Triticum turgidum L. (wheat) 250:100:0 27.457028,
−109.96245546761409
Triadimenol, Propiconazole, Prochloraz
and Azoxystrobin [20]
Zea mays (maize) 290:100:0 27.399202,
−109.92227673166026 Chlorpyrifos and Carbofuran [21]
Citrus sinensis (orange trees) 200:300:0 27.399607,
−109.90357193582655
fosetyl aluminum, metalaxyl, benomyl
and mancozeb [22]
Solanum tuberosum (potato) 150:180:150 27.420078,
−109.90099258581277
Oxytetracycline, Metalaxil M,
Ftalonitrilo, Benomyl, carboxamide,
Fumisol, Basamid,
Diethyldithiocarbamate, Positron,
Cymoxanil, Copper, Propamocarb
Cymoxanil, Oxadixil, Fosetyl-Al sulfur
products, Chlorothalonil, Mancozeb,
Dimetomorf, Cymoxanil, Boscalid,
Pyraclostrobin and oxadixil
[23,24]
Brassica oleracea (brocoli) 300:120:100 27.271647,
−109.88207986359245
Carboxamide, Phthalonitrile,
Metalaxyl-M, Oxychloride, Anilazine,
Mancozeb, Maneb and Copper
Oxychloride
[25]
Medicago sativa (alfalfa) 40:200:0 27.308164,
−109.93906414410094
Carboxamide, Phthalonitrile,
Metalaxyl-M, Oxychloride, Anilazine,
Mancozeb, Maneb and
Copper Oxychloride
[26]
Asparagus officinalis
(Asparragus) 350:150:200 27.290593,
−109.88174873746256 Mancozeb, Copper oxychloride, Maneb [27]
Phaseolus vulgaris (bean) 120:60:0 27.327082,
−109.89783771757574 Elemental based sulfur fungicide [21]
undisturbed native ecosystem None applied 27.41456,
−109.83508521845414 None applied
2.2. Soil Physicochemical Parameters
Soil parameters were evaluated according to the NOM-021-RECNAT-2000 guidelines.
Soil bulk density was determined by collecting core samples using a stainless-steel coring
ring (50 mm diameter, 50 mm length) at a depth of 30 cm. These samples were oven-dried
at 105
◦
C for 24 h. Bulk density (
ρ
B) was calculated by dividing the mass of the dried soil
by the core’s volume. Gravimetric moisture content was measured as the ratio of water
mass to dry soil mass (g
·
g
−1
), and volumetric water content (
θ
v, cm
3·
cm
−3
) was obtained
by multiplying the gravimetric moisture content (
θ
m) by bulk density (
ρ
B) [
28
]. Soil pH
was determined using the AS-02 method with a 1:10 soil-to-water ratio, and readings
were taken with a HANNA HI98108 pH meter (Hanna Instruments, Inc., Woonsocket, RI,
USA). Electrical conductivity (EC) was assessed via the electrometric method, using a 1:5
soil-to-water ratio and a Thermo Scientific Orion 9107BNMD electrode (Thermo Fisher
Scientific, Waltham, MA, USA). Organic matter content was analyzed using the Walkley
and Black method (AS-07), and nitrogen, phosphorus, and potassium levels were measured
according to the AS-08, AS-10, and AS-33 methods, respectively.
2.3. Bacteria and Fungi Isolation
Ten grams of each rhizosphere sample were individually mixed in a rotary shaker for
one hour at 150 rpm with 90 mL of sterile distilled water that had been autoclaved at 121
◦
C
and 15 psi for 15 min. Following this, serial dilutions were prepared up to a concentration

Soil Syst. 2024,8, 112 4 of 15
of 10
−4
, and 1 mL from each dilution was spread onto Petri dishes containing Nutrient
Agar (NA) enriched with 80
µ
g mL
−1
of cycloheximide or Potato Dextrose Agar (PDA)
with 80
µ
g mL
−1
of nalidixic acid for the isolation of bacterial and fungal communities,
respectively. The inoculated dishes were incubated at 28
◦
C for three days. The Colony
Forming Units (CFU) per gram of dry soil were calculated to estimate the populations
of bacteria and fungi at each study site [
29
]. All isolated strains were preserved in the
Colección de Microorganismos Edáficos y Endófitos Nativos, COLMENA, https://apps2
.itson.edu.mx/colmena/ (accessed on 12 January 2024) [30].
2.4. Molecular Identification of Obtained Bacterial and Fungal Strains
Genomic DNA was extracted from all isolates exhibiting various macro- and mi-
croscopic characteristics, following the methods outlined by Raeder and Broda [
31
] and
Valenzuela-Aragon et al. [
32
]. For the bacterial strains, a 50
µ
L PCR reaction was prepared
that included 100 ng of bacterial genomic DNA as the template, 0.2
µ
mol of each primer
pair—FD1 (5
′
-CCGAATTCGTCGACAACAGAGTTTGATCCTGGCTCAG-3
′
) and RD1
(5
′
-CCCGGGATCCAAGCTTAAGGAGGTGATCCAGCC-3
′
) [
33
]—and 4 U of MyTaq DNA
polymerase (Bioline). The PCR cycling protocol started with an initial denaturation at
95
◦
C for 5 min, followed by 30 cycles of 30 s at 95
◦
C, 40 s at 57
◦
C, and 2 min at 72
◦
C,
concluding with a 5-min elongation at 72
◦
C. In contrast, for the fungal strains, the PCR
mixture also contained 50
µ
L but used 100 ng of fungal genomic DNA as the template,
along with 0.2
µ
mol of each primer pair—ITS1 (5
′
-TCCGTAGGTGAACCTGCGG-3
′
) and
ITS4 (5
′
-TCCTCCGCTTATTGATATGC-3
′
). The amplification conditions for the ITS region
comprised an initial denaturation at 94
◦
C for 3 min, succeeded by 35 cycles of 30 s at
94
◦
C, 30 s at 55
◦
C, and 1 min at 72
◦
C, culminating in a final 10-min elongation at 72
◦
C.
After amplification, the PCR products were purified using the ISOLATE II PCR and GEL
KIT, adhering to the manufacturer’s specifications, and sequenced on the Sanger platform
(ABI 3730 XL, Applied Biosystems, Foster City, CA, USA). The obtained DNA sequences
were processed using FinchTV 1.4.0 software from Geospiza, Seattle, WA, USA, and the
taxonomic classification of the bacterial and fungal strains was performed through BLASTn,
NCBI, www.ncbi.nlm.nih.gov (accessed on 18 January 2024).
2.5. Statistical Analysis
Data on the physicochemical, major nutrient and microbial population of the rhizo-
spheric samples was expressed as a mean of randomized block design experiments in
triplicates. Significant differences were analyzed by one-way analysis of variance (ANOVA)
test and Tukey–Kramer test (p< 0.05), using Statgraphics Centurion XVI.II.
2.6. Correlation Analysis
A Pearson correlation analysis was performed to evaluate the associations between
physicochemical soil properties and microbial distribution. The significance of the correla-
tion coefficients was obtained by the test of t in R version 3.4.1, 1-
α
95%, pH and electric
conductivity1-α99.9%.
2.7. Hierarchical Cluster Analysis
The matrix data was rearranged using Mothur v 1.48.1 [
34
], and bacterial and fungi
strains and primary economic regional crops were organized using Euclidean distance
and the unweighted pair group method with the arithmetic average (UPGMA) linkage
clustering procedure. Comparisons in microbial population per studied crop were made
with the default parameters of the R heatmap function.
3. Results
The bulk density of collected soil associated with the studied crops in the Yaqui Valley
did not show statistically significant differences (p< 0.05) compared with the undisturbed
native ecosystem. This soil property ranged from 1.2 g cm
−3
(broccoli) to 1.5 g cm
−3
(wheat,

Soil Syst. 2024,8, 112 5 of 15
maize, alfalfa, asparagus, and bean), while the undisturbed native ecosystem had 1.3 g cm
−3
(Table 2). However, significant differences (p< 0.05) for this parameter (associated with the
particular techniques applied in each crop sowing) between broccoli vs. maize, alfalfa, and
bean were found.
Table 2. Physicochemical and major nutrient characteristics of soil collected in Yaqui Valley’s agroecosystems.
Studied Crops Bulk pH Soil Organic
Carbon
Organic
Matter Electric
Conductivity Nitrogen Phosphorus Potassium
Density N P K
g cm−3g/kg %dS cm−1mg kg−1
Wheat 1.5 ±0.1 ab 7.8 ±0.1 c 7.54 ±0.58 ab 1.3 ±0.1 ab 2.6 ±0.1 b 6.6 ±0.1 b 20.7 ±1.6 de 636.7±23.1 e
Maize 1.5 ±0.1 a 8.1 ±0.0 ab 6.96 ±0.58 ab 1.2 ±0.1 ab 1.5 ±0.1 c 8.3 ±0.3 a 40.7 ±3.5 a 738.3 ±31.6 c
Orange citrus 1.3 ±0.0 ab 8.3 ±0.1 ab 8.12 ±1.16 a 1.4 ±0.2 a 1.3 ±0.0 cd 5.5 ±0.2 c 17.0 ±2.4 ef 946.7 ±42.5 a
Potato 1.4 ±0.1 ab 7.8 ±0.2 c 5.8 ±0.58 b 1.0 ±0.1 b 3.1 ±0.2 a 8.2 ±0.1 a 22.0 ±1.8 cd
710.0
±
40.1 cd
Broccoli 1.2 ±0.3 b 7.9 ±0.2 bc 6.96 ±0.0 ab 1.2 ±0.0 ab 2.7 ±0.1 b 5.2 ±0.1 c 32.0 ±3.6 b
653.3
±
30.2 de
Alfalfa 1.5 ±0.1 a 8.1 ±0.1 ab 8.12 ±0.58 a 1.4 ±0.1 a 0.8 ±0.0 e 7.1 ±0.0 b 26.3 ±2.8 c 426.7 ±25.6 f
Asparagus 1.5 ±0.2 ab 8.3 ±0.2 ab 7.54 ±1.16 ab 1.3 ±0.2 ab 1.2 ±0.1 cd 9.1 ±0.4 a 19.7 ±1.3 de
650.0
±
32.4 de
Bean 1.5 ±0.0 a 8.1 ±0.1 ab 6.96 ±1.16 ab 1.2 ±0.2 ab 0.6 ±0.0 e 5.3 ±0.0 c 14.0 ±0.9 f 840.0 ±40.2 b
Undisturbed
native
ecosystem 1.3 ±0.1 ab 8.4 ±0.1 a 6.38 ±0.0 ab 1.1 ±0.0 ab 0.6 ±0.1 e 3.2 ±0.1 d 13.0 ±0.6f 413.3 ±21.1 f
Significant differences were analyzed by one-way analysis of variance (ANOVA) test and Tukey–Kramer test
(p< 0.05), using Statgraphics Centurion XVI.II.
±
represents the standard deviation. Letter groupings represent
statistical similarity.
pH values in all crop rhizosphere ranged from 7.8 (wheat and potato) to 8.3 (orange
citrus and asparagus), which were lower compared to the soil collected from the native
undisturbed ecosystem (8.4) (Table 2). However, only pH in soil collected from potato,
broccoli, and wheat showed significant differences (p< 0.05) compared with the native
undisturbed ecosystem.
The soil organic matter in the study sites ranged from 1.0% to 1.4% (Table 2); however,
these soil properties did not show significant differences (p< 0.05) between agricultural
and the native undisturbed ecosystem, but significant differences were found between
alfalfa and orange citrus vs. potato.
The electric conductivity of the soil was strongly impacted by agricultural activities
(mainly the application of high rates of synthetic fertilizers), which ranged from 0.6–0.8
[native undisturbed ecosystem (none application of synthetic fertilizers), bean and alfalfa
(lower application of synthetic fertilizers)] to 3.1 (potato) dS cm−1(Table 2).
Finally, similar findings were found for the N (measured in N-NO
3
), P (measured
in P-PO
4
), and K content in the soil, where these properties were strongly impacted by
agricultural activities vs. native undisturbed ecosystems. Results show that lower values
for the natural content of these nutrients were found in soil (Table 2).
3.1. Cultivable Microbial Communities
According to the cultivable rhizosphere microbiota in the study sites, wheat showed
the highest (significant differences (p< 0.05) microbial population (1.2
×
10
7
CFU g
−1
dry soil), followed by potato, in comparison with the undisturbed native ecosystem
(2.1
×
10
6
CFU g
−1
dry soil), and other agroecosystems (Table 3). The bacteria: fungi
composition in soil was contrasting, where some crops such as orange trees, alfalfa, and
asparagus had 0% cultivable bacterial population while potatoes had 0% fungal population
coinciding with the least diverse microbial niches from the studied crops. The most bal-
anced crop under this study was bean, with 47 and 53% of bacterial and fungal populations,
respectively, with a total population of cultivable microorganisms of 2.1
×
10
6
CFU g
−1
dry soil.

Soil Syst. 2024,8, 112 6 of 15
Table 3. Cultivable microbial population and composition observed in the Yaqui Valley studied sites.
Studied Total Microbial Population, Bacteria
CFU g−1Dry Soil, (%)
Fungi
CFU g−1Dry Soil, (%) Shannon Index
Crops CFU g−1Dry Soil
Wheat 1.2 ×107±2.5 ×106a9.96 ×106±2.08 ×106,
(83%) a 2.04 ×106±4.25 ×105,
(17%) a 6.1
Maize 7.8 ×105±1.8 ×105d6.32 ×105±1.46 ×105,
(81%) d 1.48 ×105±3.42 ×104,
(19%) d 4
Orange Trees 6.6 ×105±1.3 ×105d0, (0%) d 6.6 ×105±1.3 ×105,
(100%) d 1
Potato 5.2 ×106±1.0 ×106b5.2 ×106±1.0 ×106,
(100%) b 0, (0%) b 2
Broccoli 1.1 ×106±3.0 ×105d3.85 ×105±1.05 ×105,
(35%) d 7.15 ×105±1.95 ×105,
(65%) d 3.8
Alfalfa 2.0 ×106±1.0 ×106cd 0, (0%) cd 2.0 ×106±1.0 ×106,
(100%) cd 2
Asparagus 4.2 ×106±6.4 ×105bc 0, (0%) bc 4.2 ×106±6.4 ×105,
(100%) bc 1
Bean 2.1 ×106±2.6 ×105cd 9.87 ×105±1.22 ×105,
(47%) cd 1.11 ×106±1.43 ×105,
(53%) bc 3.7
Undisturbed
Native Ecosystem 2.1 ×106±2.5 ×105cd 1.45 ×106±1.73 ×105,
(69%) cd 6.51 ×105±7.75 ×104,
(31%) cd 3
Significant differences were analyzed by one-way analysis of variance (ANOVA) test and Tukey–Kramer test
(p< 0.05), using Statgraphics Centurion XVI.II.
±
represents the standard deviation. Letter groupings represent
statistical similarity.
The Shannon index showed that wheat had the highest value (6.1). Therefore, this
crop presents the most diversity in comparison to the other crops analyzed.
3.2. Results from the Correlation Analysis
A significant correlation (p< 0.05) between soil pH and total microbial population in
the Yaqui Valley studied sites was found, observing a p-value of 3.99
×
10
−3
and a Pearson
value of
−
0.54; specifically, a significant correlation (p< 0.05) between this soil property vs.
bacteria and fungi population, with 0.66 and
−
0.67 Pearson values, respectively (Table 4).
In addition, the soil pH can be associated with a highly significant relation found between
this property and electric conductivity (Pearson value of
−
0.76). The synthetic fertilization
rates applied to the study sites vs. remnant N, P, and K content in soil showed no significant
statistical differences in results.
Table 4. Significant correlations between soil physicochemical properties and bacteria and fungi
composition in the study sites. All variables (N application, relative density, pH, organic matter
content, electric conductivity, CFU, fungi, and bacterial population) were compared vs. each other
(data not shown).
Electric
Conductivity CFU Fungi
Population
Bacterial
Population
pH −0.76 −0.54 −0.67 0.66
Electric
Conductivity 0.44 0.52 −0.47
3.3. Results from the Molecular Identification of Obtained Bacterial and Fungal Strains
Based on microbiological and molecular methods, 317 microbial strains (Bacteria: 73%
and Fungi: 27%) were isolated from the studied sites (eight crops of economic interest in the
region and the undisturbed native ecosystem), which belong to 108 bacterial genera/species
(Figure 1), and 57 fungal genera/species (Figure 2).

Soil Syst. 2024,8, 112 7 of 15
Soil Syst. 2024, 8, x FOR PEER REVIEW 8 of 16
Figure 1. Heatmap of cultivable bacterial diversity from eight crops in comparison to the undis-
turbed native ecosystem in the Yaqui Valley, northwestern Mexico. Joint and hierarchical clustering
of 232 bacterial strains associated with important economic crops were calculated by using Eu-
clidean distance and an unweighted pair group method with an arithmetic average (UPGMA)
linkage clustering procedure. The dendrogram on the left represents the bacterial genetic relation,
while the dendrogram on the top represents the bacterial genera/species relation between the study
sites.
The highest fungi diversity and abundance was observed in the wheat rhizosphere
(38% of the total isolated fungi) (Figure 2), from which 15% of the total fungi isolated
were wheat-specific genera/species; Talaromyces purpureogenus, Trichoderma harzianum,
Figure 1. Heatmap of cultivable bacterial diversity from eight crops in comparison to the undisturbed
native ecosystem in the Yaqui Valley, northwestern Mexico. Joint and hierarchical clustering of
232 bacterial strains associated with important economic crops were calculated by using Euclidean
distance and an unweighted pair group method with an arithmetic average (UPGMA) linkage
clustering procedure. The dendrogram on the left represents the bacterial genetic relation, while the
dendrogram on the top represents the bacterial genera/species relation between the study sites.

Soil Syst. 2024,8, 112 8 of 15
Soil Syst. 2024, 8, x FOR PEER REVIEW 9 of 16
and Taifanglania sp. with the highest wheat specific specie populations. The native
undisturbed ecosystem only presented two site-specific fungal strains, Curvularia lunata
and Humicola fuscoatra, which are not found under agricultural sites. Other crops (alfalfa,
broccoli, bean, maize, and orange citrus) also presented crop-specific fungi.
Alfalfa-specific fungi were Aspergillus niveus, Bipolaris sorokiniana, and Fusarium
oxysporum. Bean-specific species isolated were Alternaria alternata, Aspergillus unguis,
Acrophialophora levis, and Corynascus verrucosus. Maize presented Fusarium proliferatum
and Fusarium equiseti as crop-specific fungi, while orange citrus and broccoli presented
only one crop-specific fungi, Dothide-omycetes sp. and Fusarium chlamydosporum,
respectively. The fungi clustering heatmap (Figure 2) showed (i) maize and bean shared a
high population of Mortierella alpina and Talaromyces pinophilus; (ii) wheat and broccoli
were the most fungal diverse crops and showed high population values of fungi with
38% and 18% respectively of the total isolated fungi; (iii) the fungal population in potato
was not able to be isolated; (iv) Curvularia lunata and Humicola fuscoatra were
specific-species isolated from the un-disturbed ecosystem, which were not isolated in any
other of studied crops.
Figure 2. Cultivable fungal diversity from eight crops in comparison to an undisturbed native
ecosystem in the Yaqui Valley, Sonora, Mexico. Joint and hierarchical clustering of 85 fungi strains
associated with important economics were calculated by using Euclidean distance and an un-
weighted pair group method with an arithmetic average (UPGMA) linkage clustering procedure.
The dendrogram on the left represents the fungi genetic relation, while the dendrogram on the top
represents the fungi genera/species relation between the study sites.
Figure 2. Cultivable fungal diversity from eight crops in comparison to an undisturbed native ecosys-
tem in the Yaqui Valley, Sonora, Mexico. Joint and hierarchical clustering of 85 fungi strains associated
with important economics were calculated by using Euclidean distance and an unweighted pair
group method with an arithmetic average (UPGMA) linkage clustering procedure. The dendrogram
on the left represents the fungi genetic relation, while the dendrogram on the top represents the fungi
genera/species relation between the study sites.
Some crops (wheat, maize, bean, and potato, as well as the undisturbed native ecosys-
tem) presented crop-specific bacteria. Wheat showed not only the highest bacterial strains
(Table 2) but also the highest bacterial diversity (79% of the total bacterial diversity in
the study sites), from which 52% were wheat-specific genera/species (such as Bacillus en-
dophyticus,Paenibacillus polymyxa and Delftia tsuruhatensis with the highest bacterial popu-
lations). Of the total identified species, 8% were maize-specific: Massilia oculi,Rhodococcus
erythropolis,Sphingomonas panni,Curtobacterium oceanosedimentum, and Staphylococcus succinus.
Arthrobacter sp., Pseudarthrobacter defluvii, and Cronobacter sakazakii were specific to the bean
crop. Potato presented crop-specific bacterial species, Streptomyces roseofulvus,Pseudoxan-
thomonas indica, and Cupriavidus taiwanensis. The undisturbed native ecosystem -presented
one site-specific bacterial species, Serratia marcescens. In addition, Bacillus was the most pre-
dominant bacterial genus isolated in the study sites (representing 41% of the total isolated
bacterial strains) (Figure 1). This genus was the most abundant in wheat (44%) and maize
(36%) crops.
Based on the comparison presented in the heatmaps, several bacterial dynamical
groups were shared between the analyzed crops (Figure 1): (i) maize and potato, sharing
high populations of Stenotrophomonas maltophilia,Pseudomonas sp., Achromobacter sp., and
Bacillus safensis; (ii) the clustering of orange, alfalfa, and asparagus due to the absence of
cultivable bacteria for the mentioned crops; (iii) it is important to mention the high relation
and clustering of wheat with the rest of the crops due to the high diversity and population

Soil Syst. 2024,8, 112 9 of 15
of bacteria isolated from wheat; and (iv) the bacteria(s) isolated from the undisturbed native
ecosystem could be found in broccoli, maize, potato, and wheat.
The highest fungi diversity and abundance was observed in the wheat rhizosphere
(38% of the total isolated fungi) (Figure 2), from which 15% of the total fungi isolated
were wheat-specific genera/species; Talaromyces purpureogenus,Trichoderma harzianum, and
Taifanglania sp. with the highest wheat specific specie populations. The native undis-
turbed ecosystem only presented two site-specific fungal strains, Curvularia lunata and
Humicola fuscoatra, which are not found under agricultural sites. Other crops (alfalfa, broc-
coli, bean, maize, and orange citrus) also presented crop-specific fungi. Alfalfa-specific
fungi were Aspergillus niveus,Bipolaris sorokiniana, and Fusarium oxysporum. Bean-specific
species isolated were Alternaria alternata,Aspergillus unguis,Acrophialophora levis, and
Corynascus verrucosus. Maize presented Fusarium proliferatum and Fusarium equiseti as crop-
specific fungi, while orange citrus and broccoli presented only one crop-specific fungi,
Dothide-omycetes sp. and Fusarium chlamydosporum, respectively. The fungi clustering
heatmap (Figure 2) showed (i) maize and bean shared a high population of Mortierella alpina
and Talaromyces pinophilus; (ii) wheat and broccoli were the most fungal diverse crops and
showed high population values of fungi with 38% and 18% respectively of the total isolated
fungi; (iii) the fungal population in potato was not able to be isolated; (iv) Curvularia lunata
and Humicola fuscoatra were specific-species isolated from the un-disturbed ecosystem,
which were not isolated in any other of studied crops.
4. Discussion
The bacterial population dynamics observed in the study crops (wheat, potato, maize,
and the undisturbed native ecosystem) presented a higher population of bacteria over
fungi (1.2
×
10
7
CFU g
−1
dry soil) (Table 3), mainly due to the current soil granulometric
composition being sandy clay loam (~49%, 33% and 17% respectively) and other soil
properties such as; alkaline soils; high salinity levels, as well as the crop cultivar techniques
applied; like, intensive tillage, humidity levels (69% annual mean, crop genotype and root
exudate [
35
]. Since the highest population pertained to the wheat crop (also the most
diverse, with a Shannon value of 6.1) differing by one order of magnitude (positively) from
the undisturbed native ecosystem, suggesting that over the years, traditional agriculture
has diversified and augmented the presence of microorganisms in the agrosystem [36].
The absence of bacterial population was observed in asparagus, alfalfa, and orange
citrus, which suggests that the applications of high bactericides (Table 1) through conven-
tional agriculture practices in those crops to control plant diseases result in the complete
elimination of both beneficial and harmful bacterial. On the other hand, high doses of fungi-
cides are applied to the potato crop, for example, for late and early blight and parachute:
Metalaxil, Chlorothalonil, Fosetil Al, Mancozeb, Dimetomorf, Cymoxanil, Boscalid, and
Pyraclostrobin, explaining the null cultivable fungi population for this crop [
19
]. The
application of these fungicides alters the microbial presence in soil, attacking a wide
range of microorganisms due to their broad-spectrum characteristic, thus resulting in a
co-elimination of beneficial fungi [37].
The intrinsic interactions carried out by soil microorganisms and physicochemical
parameters are co-dependent variables, where the evaluation of each individual becomes
complex; therefore, correlative statistical analyses were performed to associate them. pH
and electric conductivity showed the highest significant negative correlation (Pearson
value of
−
0.76) due to the application of N-based fertilizers acidifying soil, resulting in a
rise of the electric conductivity (salinity levels) [
3
,
38
,
39
], which may impact the diversity
and abundance of microorganisms [microbial (fungi and bacteria) population and electric
conductivity, Pearson value of 0.44]. In addition, the positive correlation between pH and
bacterial and the negative correlation to fungi population was significant (p< 0.05) (Table 3)
because the optimal pH for the bacteria and fungi growth is >6.5 and <6.5, respectively.
Thus, this study showed that at lower pH values, there is a higher abundance of fungi, and
at higher pH values, a higher bacteria population was found [
40
]. Like so, lower pH values

Soil Syst. 2024,8, 112 10 of 15
favor fungal development; however, non-beneficial agricultural traits may be generated for
crop health, where pH values < 5.5 increase the solubility of Al (aluminum), which is the
primary source of toxicity to plants, which may consequently reduce crop yields [41,42].
In this study, the most abundant wheat-specific bacteria were (i) Bacillus endophyticus
(Figure 1); this species has been isolated from wheat and identified as a plant growth-
promoting rhizobacteria with biocontrol traits against Fusarium graminearum,Rhizoctonia
solani, and Macrophomina phaseolina [
43
]; (ii) Paenibacillus polymyxa was frequent in the
studied agroecosystems, which is an acidophilic bacilli with the ability to solubilize K, Zn,
P, also identified as a PGPB [
44
]; and (iii) Delftia tsuruhatensis as a niche-specific bacteria
associated to wheat, and also presents biocontrol activity against Cladosporium herbarum
and PGPB traits (IAA production, phosphate solubilization, ACC deaminase activity,
and antibiotic production) [
45
]. As for maize, the crop-specific bacteria present were re-
lated to auxin production and N-fixing bacteria, such as Rhodococcus erythropolis [
46
] and
Sphingomonas panni [
47
]. Also, bacteria are involved in radical elongation, such as
Curtobacterium oceanosedimentum [
48
]. The potato crop showed the association of Strepto-
myces roseofulvus identified with biocontrol activity [
49
], Pseudoxanthomonas indica which
presents biocontrol activity against Aspergillus fumigatus,Enterobacter aerogenes,
Staphylococcus epidermidis and Shigella flexneri [
50
] and Cupriavidus taiwanensis a PGPB
strain by ACC deaminase activity [
51
]. The undisturbed native ecosystem presented one
specific crop bacteria species, Serratia marcescens, which is a PGPB by the production of IAA
and siderophore and presents biocontrol against Lasiodiplodia theobromae,Rhizoctonia solani,
Sphaerostilbe repens,Fomes lamaoensis,Ustulina zonata,Poria hypobrunnae,Pestalotiopsis theae,
Colletotrichum camelliae and Curvularia eragrostidis [52].
Thus, few investigations have been carried out to understand the specific diversity and
dynamics of this genus in the rhizosphere and how these bacterial communities respond to
soil fertility and plant root exudates positively, which vary with the crop phenology and
genotype [
6
,
32
,
53
]. The most predominant bacterial genus in the studied agroecosystems
in the Yaqui Valley was Bacillus.Bacillus species in agriculture provide positive effects by
promoting plant growth, enhancing nutrient availability, and offering biological control
against pests and diseases, ultimately improving crop health and yields. For example,
B. thuringiensis has been characterized as a natural biopesticide [
54
], B. safensis regulates
plant growth by biosynthesis of plant hormone [
55
], B. megaterium is identified as a PGPB
due to the production of indoles and siderophores [
56
], B. pumilus,B. cereus,B. endophyticus,
B. amyloliquefaciens, and B. licheniformis have been reported as plant growth promoting
bacteria as well as biological control agents [
57
], where many of these species are widely
used as biopesticides and biofertilizers.
The most abundant fungi associated with wheat were (Figure 2) (i) Rhizopus oryzae,
which has been reported as a lactic acid producer from wheat straw [
58
], (ii) Talaromyces
purpureogenus which was reported as a wheat plant growth promoter that increased var-
ious physio-biochemical growth parameters under normal and stressed conditions [
59
],
(iii) Trichoderma harzianum which is highly used in biopesticides and as growth promoters [
60
],
and (iv) Taifanglania sp. which was previously reported in wheat [
3
]. In the bean crop, the most
abundant fungi were (i) Alternaria alternata which was identified as a fungal pathogen causing
root rot and leaf spot diseases [
61
], (ii) Aspergillus unguis which presents antibacterial activity
against Staphylococcus aureus [
62
], (iii) Acrophialophora levis antibiotic activity of soil-borne fungi,
including Pythium sp. and Rhizoctonia sp. [
63
] and (iv) Corynascus verrucosus which has the
capacity of decomposing crop residue such as cellulose, lipid and lignin in the composting
process [
64
]. Alfalfa showed the following crop-specific fungal species: Aspergillus niveus, a
xylanase producer [
65
]; Bipolaris sorokiniana, identified as a plant pathogen causing spot
blotch [
66
]; and Fusarium oxysporum, a plant pathogen causing vascular wilt [
67
]. Maize
also shared with alfalfa a few fusarium species: Fusarium proliferatum, the main source
of fumonisins, a health risk mycotoxin, contaminating agro-products [
68
], and Fusarium
equiseti which causes stalk rot in maize [
69
,
70
]. On the other hand, broccoli showed the
presence of specific fungal species of Fusarium chlamydosporum, and although this species

Soil Syst. 2024,8, 112 11 of 15
has been reported to cause wilt disease in other crops, to the best of our knowledge, it has
not been reported in broccoli [71–73].
Ecosystem functions rely on microbial consortia, and various functional groups of soil
organisms often enhance each other’s roles in supporting plant growth [
70
]. Therefore,
the loss of certain soil biota due to intensive practices can significantly influence the
performance of the remaining microbial community. For example, greater soil biodiversity
can hinder the ability of pathogens to invade and colonize the soil [
70
]. Additionally,
anticipating how microbes will behave under future environmental conditions, such as
climate change, presents challenges, as the functional capacity of individual organisms
may be compromised. Agricultural management practices, such as intensive soil tillage,
repeated and intensive fertilization, application of pesticides, and low plant diversity, have
been shown to have adverse effects, reducing overall soil microbial biomass, hindering the
substantial eco-systemic services, and affecting overall soil health and sub, consequently
food production.
Physicochemical properties in the Yaqui Valley are also being impacted by the in-
tense agricultural cropping ecosystems applied. In this study, the soil bulk density values
(Table 2) showed a tendency to soil compaction. Thus, traditional synthetic fertilization
tends to compact soil, increasing bulk density alongside mechanical machinery in agricul-
tural practices, which may play a negative role in the fostering of beneficial microorganisms
in the porous space [
70
]. Therefore, the compact soils in our study sites are evidence of
the intensive agricultural history in the Yaqui Valley [70]. The high fertilizer rates applied
to crops through traditional techniques have risen to 7.4 times (from the 1970s to date),
whereas the overall crop yield has only increased 2.4 times, meaning that plant-efficient
assimilation of N-based fertilizers has declined over 50% and up to 70% of the N applied is
lost by leaching into the soil [
74
]. Another important factor to consider is the Yaqui Val-
ley’s soil composition, classified as coarse, sandy-clay, mixed with montmorillonite (typic
caliciorthid under the U.S. 7th soil classification scheme), where clay-composed soils can
directly stabilize N [
75
,
76
]. This reaffirms the relation found between N-based application
doses and remnant N in the soil of the studied crops, where asparagus had not only the
highest remnant value (9.1 mg kg
−1
) but also the highest application dose of N-based
fertilizer (350 kg ha
−1
) similar to the behavior found in maize where the remnant value is of
8.3 mg kg
−1
and the applied dose is of 290 kg ha
−1
of N (Table 2). These results can also be
associated with crop genotype, agricultural practices, and/or soil properties fluctuations,
such as pH and electrical conductivity. Long-term fertilization impacts microbial com-
munities and subsequently alters the provided eco-systemic functions [
77
,
78
] due to the
high application of N, P, and K fertilizers, modifying the abundance of specific microbial
groups associated with nutrient cycling [
78
] and microbial ecological functions in soil [
79
].
Fertilization rates may also be related to the range of pH levels at the rhizosphere observed
between the studied crops; the lowest observed values were for wheat, potato, and broccoli
(Table 1), where the application of urea tends to acidify soil by the nitrification process resulting
in slightly alkaline (~8.0) soils [
80
,
81
]. In addition, crops with lower soil electric conductivity
(undisturbed native ecosystem, bean and alfalfa) may be associated with the lower application
of synthetic fertilizers compared to the rest of the studied crops (Table 2) due to their ability to
establish symbiosis with N
2
fixing rhizobia [
82
] The studied sites can be classified in two main
groups: (i) soil with lower salinity (E.C. < 1.0 dS cm
−1
): undisturbed native ecosystem (0.6),
bean (0.6) and alfalfa (0.8); and (ii) saline soil (E.C. > 1.0 dS cm
−1
): asparagus (1.2), orange
trees (1.3), maize (1.5), wheat (2.6), broccoli (2.7), potato (3.1) (Table 1). The main cause
of saline soils in the Yaqui Valley is attributed to the application of high doses of insolu-
ble synthetic fertilizers in combination with poor soil quality, as well as irrigation water
quality [
83
,
84
]. Salinity in the soil is associated with nutrient cycling in agroecosystems,
which modulate microbial communities. Thus, the soil microbial community is highly
impacted by soil properties, climatic conditions, crop genotypes, and agricultural practices.

Soil Syst. 2024,8, 112 12 of 15
5. Conclusions
The agricultural practices used for crop production in the Yaqui Valley, as well as
soil physicochemical properties, modify the genetic diversity of soil microorganisms. A
total of 108 bacterial and 57 fungal cultivable species were identified in the Yaqui Valley
under the studied crop sites analyzed. Bacillus was the most predominant bacterial genus
isolated from the study sites, representing 41% of the total isolated bacterial strains. The
genus Aspergillus was the most abundant fungal genus, representing 31% of all the isolated
fungi. However, more research is required to understand the ecological role of cultivable
rhizosphere microbial community structure in the agroecosystems in the Yaqui Valley. This
information will allow the design of suitable agrobiotechnologies for sustainable food
production, amplifying their effectivity regarding the edaphic, climatic, and microbial
declaration from the Yaqui Valley, potentially reducing the economic and environmental
cost of conventional agriculture in that region.
Author Contributions: Conceptualization, V.V.R., F.I.P.C., E.C.-R., M.M.V. and S.d.l.S.V.; methodology,
V.V.R., F.I.P.C., E.C.-R. and S.d.l.S.V.; software, V.V.R., F.I.P.C., E.C.-R. and S.d.l.S.V.; validation, V.V.R.,
F.I.P.C., E.C.-R. and S.d.l.S.V. formal analysis, V.V.R., F.I.P.C., E.C.-R. and S.d.l.S.V.; investigation,
V.V.R., F.I.P.C. and S.d.l.S.V.; resources, S.d.l.S.V. data curation, V.V.R., F.I.P.C., E.C.-R. and S.d.l.S.V.;
writing—original draft preparation, V.V.R., F.I.P.C. and S.d.l.S.V.; writing—review and editing, V.V.R.,
F.I.P.C., E.C.-R., M.M.V., J.G.P., E.Y.G. and S.d.l.S.V.; visualization, V.V.R., F.I.P.C., E.C.-R., M.M.V.,
J.G.P., E.Y.G. and S.d.l.S.V.; supervision, S.d.l.S.V.; project administration S.d.l.S.V.; funding acquisition,
S.d.l.S.V. All authors have read and agreed to the published version of the manuscript.
Funding: This study was funded by Cátedras CONACyT Program (Project 1774, “Alternativas
agrobiotecnológicas para incrementar la competitividad del cultivo de trigo en el Valle del Yaqui:
desde su ecología microbiana hasta su adaptabilidad al cambio climático”), CONACyT (Project 253663,
“Fortalecimiento de la infraestructura del Laboratorio de Biotecnología del Recurso Microbiano del
ITSON para la creación de COLMENA: COLección de Microrganismos Edáficos y Endófitos NAtivos,
para contribuir a la seguridad alimentaria regional y nacional”, and CONACyT (Project 257246,
“Interacción trigo x microorganismos promotores del crecimiento vegetal: identificando genes con
potencial agro-biotecnológico”).
Data Availability Statement: All of the strains used for this analysis are available on the COLMENA
database available on https://apps2.itson.edu.mx/colmena/ (accessed on 12 January 2024).
Acknowledgments: The authors acknowledge support by CONACyT for the Master scholarship
CVU 924892 (Valeria Valenzuela Ruiz). In addition, we thank Dulce Pacheco and Osbaldo Zepeta for
their support in the sampling and bacterial isolation, and Angélica Herrera for her support in the
molecular identification of microorganisms.
Conflicts of Interest: The authors declare no conflicts of interest.
References
1.
McCullough, E.B.; Matson, P.A. Evolution of the knowledge system for agricultural development in the Yaqui Valley, Sonora,
Mexico. Proc. Natl. Acad. Sci. USA 2016,113, 4609–4614. [CrossRef] [PubMed]
2.
Argentel-Martínez, L.; Peñuelas-Rubio, O. Investigaciones Biológicas, Agrícolas y Ambientales de México; Pantanal Editora: Nova
Xavantina, Brazil, 2022. [CrossRef]
3.
Ibarra-Villarreal, A.L.; Rojas-Padilla, J.; Chaparro-Encinas, L.A.; Díaz-Rodríguez, A.M.; Valenzuela Ruiz, V.; Herrera-Sepúlveda,
A.; Parra-Cota, F.I.; de los Santos Villalobos, S. Soil salinity shifts cultivable microbial communities of wheat (Triticum turgidum
subsp. durum) rhizosphere in the yaqui valley, mexico. Agrociencia 2023,57, 882–919. [CrossRef]
4.
Lares-Orozco, M.F.; Robles-Morúa, A.; Yepez, E.A.; Handler, R.M. Global warming potential of intensive wheat production in the
Yaqui Valley, Mexico: A resource for the design of localized mitigation strategies. J. Clean. Prod. 2016,127, 522–532. [CrossRef]
5. Miransari, M. Soil microbes and plant fertilization. Appl. Microbiol. Biotechnol. 2011,92, 875–885. [CrossRef] [PubMed]
6.
Villa-Rodríguez, E.; Parra-Cota, F.I.; Castro-Longoria, E.; López-Cervantes, J.; de los Santos-Villalobos, S. Bacillus subtilis TE3:
A promising biological control agent against Bipolaris sorokiniana, the causal agent of spot blotch in wheat (Triticum turgidum L.
subsp. durum). Biol. Control 2019,132, 135–143. [CrossRef]
7.
Robles Montoya, R.I.; Valenzuela Ruiz, V.; Parra Cota, F.I.; Santoyo, G.; de los Santos-Villalobos, S. Description of a Polyphasic
Taxonomic Approach for Plant Growth-Promoting Rhizobacteria (PGPR). In Microbial Services in Restoration Ecology; Elsevier:
Amsterdam, The Netherlands, 2020; pp. 259–269. [CrossRef]

Soil Syst. 2024,8, 112 13 of 15
8.
Morales Sandoval, P.H.; Valenzuela Ruiz, V.; Ortega, M.E.; Martinez Vidales, A.D.; Félix Pablos, C.M.; Chávez Luzania, R.A.;
Parra-Cota, F.I.; de los Santos Villalobos, S. Taxonomía bacteriana basada en índices relacionados al genoma completo. Soc. Acad.
2021,58, 39–49.
9.
Ortiz García, S.; Saynes Santillán, V.; Bunge Vivier, V.; Anglés-Hernánez, M.; Pérez, M.E.; Prado, B. Soil governance and sustainable
agriculture in Mexico. Soil Secur. 2022,7, 100059. [CrossRef]
10.
De los Santos Villalobos, S.; Parra Cota, F.I.; Herrera Sepulveda, A.; Valenzuela Aragón, B.; Estrada Mora, J.C. Collection of
edaphic microorganisms and native endophytes to contribute to national food security. Rev. Mex. Cienc. Agríc. 2018,9, 191–202.
11. Malard, L.A.; Guisan, A. Into the microbial niche. Trends Ecol. Evol. 2023,38, 936–945. [CrossRef]
12.
Groenenboom, A.E.; van den Heuvel, J.; Zwaan, B.J.; Smid, E.J.; Schoustra, S.E. Species dynamics in natural bacterial communities
over multiple rounds of propagation. Evol. Appl. 2022,15, 1766–1775. [CrossRef]
13. Zhao, Z.-B.; He, J.-Z.; Quan, Z.; Wu, C.-F.; Sheng, R.; Zhang, L.-M.; Geisen, S. Fertilization changes soil microbiome functioning,
especially phagotrophic protists. Soil Biol. Biochem. 2020,148, 107863. [CrossRef]
14.
Yao, L.; Wang, D.; Kang, L.; Wang, D.; Zhang, Y.; Hou, X.; Guo, Y. Effects of fertilization on soil bacteria and fungi communities in
a degraded arid steppe revealed by high through-put sequencing. PeerJ 2018,6, e4623. [CrossRef]
15.
Bai, Y.C.; Chang, Y.Y.; Hussain, M.; Lu, B.; Zhang, J.P.; Song, X.B.; Lei, X.S.; Pei, D. Soil chemical and microbiological properties
are changed by long-term chemical fertilizers that limit ecosystem functioning. Microorganisms 2020,8, 694. [CrossRef] [PubMed]
16.
Ren, N.; Wang, Y.; Ye, Y.; Zhao, Y.; Huang, Y.; Fu, W.; Chu, X. Effects of Continuous Nitrogen Fertilizer Application on the
Diversity and Composition of Rhizosphere Soil Bacteria. Front. Microbiol. 2020,11, 1948. [CrossRef] [PubMed]
17.
Shen, M.C.; Zhang, Y.Z.; Bo, G.D.; Yang, B.; Wang, P.; Ding, Z.Y.; Wang, Z.B.; Yang, J.M.; Zhang, P.; Yuan, X.L. Microbial Responses
to the Reduction of Chemical Fertilizers in the Rhizosphere Soil of Flue-Cured Tobacco. Front. Bioeng. Biotechnol. 2022,9, 812316.
[CrossRef]
18.
Gomiero, T. Soil Degradation, Land Scarcity and Food Security: Reviewing a Complex Challenge. Sustainability 2016,8, 281.
[CrossRef]
19.
Sagarpa, S.I. Agenda Tecnica Agricola Sonora. D.F., Mexico. 2015, p. 187. Available online: https://www.compucampo.com/
tecnicos/26_Sonora_2015_SIN.pdf (accessed on 18 January 2024).
20.
Villaseñor Mir, H.E.; Santa Rosa, R.H.; Martínez Cruz, E.; Mariscal Amaro, L.A.; Leyva Mir, S.G.; Huerta Espino, J. Control
químico de las enfermedades: Una alternativa para la producción de trigo de temporal en Chemical control of diseases: An
alternative for rainfall wheat production in Tlaxcala. Rev. Mex. Cienc. Agríc. 2012,3, 595–600.
21.
INIFAP. Guía para la Asistencia Técnica Agrícola Área de Influencia del Campo Experimental Ébano; INIFAP: Mexico City, Mexico, 2001;
pp. 6–7.
22.
Rocha-Peña, M.A.; Padrón Chávez, J.E. El Cultivo de los Cítricos en el Estado de Nuevo León Libro Científico No 1 Instituto Nacional de
Investigaciones Forestales Agrícolas y Pecuarias; C.I.R.N.E.: Gral Terán, México, 2009.
23. INIFAP. Paquete Tecnológico para papa de Riego. Ciclo Agrícola Primavera-Verano 2009; INIFAP: Mexico City, Mexico, 2009.
24.
Molina, J.; Mairena Santos, B.; Aguilar, L. Guía MIP en el cultivo de la papa. In Manejo Integrado de Plagas; Managua, Nicaragua,
2004; pp. 1–60. Available online: https://cenida.una.edu.ni/relectronicos/RENH10M722.pdf (accessed on 18 January 2024).
25.
Vargas Dolores, A.R. Factores que Determinan la Producción de Brócoli (Brassica oleracea L. var. Itálica) en Cultivos a cielo Abierto;
Universidad Autónoma del estado de México: Zumpango, Mexico, 2014.
26. Agrios, G.N. Fitopatología; Universidad Nacional Autónoma de México: Mexico City, Mexico, 2004.
27. SENASICA. Agenda Técnica Agrícola—Baja California Sur; INIFAP: Mexico City, Mexico, 2016; pp. 75–76.
28.
Jabro, J.D.; Stevens, W.B.; Iversen, W.M. Comparing Two Methods for Measuring Soil Bulk Density and Moisture Content. Open J.
Soil Sci. 2020,10, 233–243. [CrossRef]
29.
Parra-Cota, F.I.; Coronel-Acosta, C.-B.; Amézquita-Avilés, C.F.; de los Santos-Villalobos, S.; Escalante-Martínez, D.I. Metabolic
diversity of edaphic microorganisms associated with corn cultivation in the Yaqui Valley, Sonora. Rev. Mex. Cienc. Agríc. 2018,
9, 431–442.
30.
De los Santos-Villalobos, S.; Díaz-Rodríguez, A.M.; Ávila-Mascareño, M.F.; Martínez-Vidales, A.D.; Parra-Cota, F.I. Colmena: A
culture collection of native microorganisms for harnessing the agro-biotechnological potential in soils and contributing to food
security. Diversity 2021,13, 337. [CrossRef]
31. Raeder, U.; Broda, P. Rapid preparation of DNA from filamentous fungi. Lett. Appl. Microbiol. 1985,1, 17–20. [CrossRef]
32.
Valenzuela-Aragon, B.; Parra-Cota, F.I.; Santoyo, G.; Arellano-Wattenbarger, G.L.; de los Santos-Villalobos, S. Plant-assisted
selection: A promising alternative for
in vivo
identification of wheat (Triticum turgidum L. subsp. durum) growth promoting
bacteria. Plant Soil 2019,435, 367–384. [CrossRef]
33.
Weisburg, W.G.; Barns, S.M.; Pelletier, D.A.; Lane, D.J. 16S ribosomal DNA amplification for phylogenetic study. J. Bacteriol. 1991,
173, 697–703. [CrossRef] [PubMed]
34.
Kunin, V.; Engelbrektson, A.; Ochman, H.; Hugenholtz, P. Wrinkles in the rare biosphere: Pyrosequencing errors can lead to
artificial inflation of diversity estimates. Environ. Microbiol. 2010,12, 118–123. [CrossRef] [PubMed]
35.
Setiawati, T.C. Correlations between Soil Microbe and Soil Chemical Properties in Limestone Mining Area: Case Study at Southern
Jember Indonesia. In Proceedings of the International Conference on Chemical, Environment & Biological Sciences (CEBS-2014),
Kuala Lumpur, Malaysia, 17–18 September 2014. [CrossRef]

Soil Syst. 2024,8, 112 14 of 15
36.
Gupta, A.; Singh, U.B.; Sahu, P.K.; Paul, S.; Kumar, A.; Malviya, D.; Singh, S.; Kuppusamy, P.; Singh, P.; Paul, D.; et al. Linking Soil
Microbial Diversity to Modern Agriculture Practices: A Review. Int. J. Environ. Res. Public Health 2022,19, 3141. [CrossRef]
37.
Ma, G.; Gao, X.; Nan, J.; Zhang, T.; Xie, X.; Cai, Q. Fungicides alter the distribution and diversity of bacterial and fungal
communities in ginseng fields. Bioengineered 2021,12, 8043–8056. [CrossRef]
38.
Tkaczyk, P.; Mocek-Płóciniak, A.; Skowro ´nska, M.; Bednarek, W.; Ku´smierz, S.; Zawierucha, E. The Mineral Fertilizer-Dependent
Chemical Parameters of Soil Acidification under Field Conditions. Sustainability 2020,12, 7165. [CrossRef]
39.
Hao, T.; Zhu, Q.; Zeng, M.; Shen, J.; Shi, X.; Liu, X.; Zhang, F.; de Vries, W. Impacts of nitrogen fertilizer type and application rate
on soil acidification rate under a wheat-maize double cropping system. J. Environ. Manag. 2020,270, 110888. [CrossRef]
40.
Bárcenas-Moreno, G.; Rousk, J.; Bååth, E. Fungal and bacterial recolonisation of acid and alkaline forest soils following artificial
heat treatments. Soil Biol. Biochem. 2011,43, 1023–1033. [CrossRef]
41.
Rousk, J.; Brookes, P.C.; Bååth, E. Contrasting Soil pH Effects on Fungal and Bacterial Growth Suggest Functional Redundancy in
Carbon Mineralization. Appl. Environ. Microbiol. 2009,75, 1589–1596. [CrossRef]
42.
Rousk, J.; Brookes, P.C.; Bååth, E. Fungal and bacterial growth responses to N fertilization and pH in the 150-year Park Grass UK
grassland experiment. FEMS Microbiol. Ecol. 2011,76, 89–99. [CrossRef] [PubMed]
43.
Verma, P.; Yadav, A.N.; Khannam, K.S.; Kumar, S.; Saxena, A.K.; Suman, A. Molecular diversity and multifarious plant growth
promoting attributes of Bacilli associated with wheat (Triticum aestivum L.) rhizosphere from six diverse agro-ecological zones of
India. J. Basic Microbiol. 2016,56, 44–58. [CrossRef] [PubMed]
44.
Hussain, A.; Ahmad, M.; Nafees, M.; Iqbal, Z.; Luqman, M.; Jamil, M.; Maqsood, A.; Mora-Poblete, F.; Ahmar, S.; Chen, J.T.; et al.
Plant-growth-promoting Bacillus and Paenibacillus species improve the nutritional status of Triticum aestivum L. PLoS ONE 2020,
15, e0241130. [CrossRef] [PubMed]
45.
Verma, P.; Yadav, A.N.; Khannam, K.S.; Mishra, S.; Kumar, S.; Saxena, A.K.; Suman, A. Appraisal of diversity and functional
attributes of thermotolerant wheat associated bacteria from the peninsular zone of India. Saudi J. Biol. Sci. 2019,26, 1882–1895.
[CrossRef] [PubMed]
46.
Tekdal, D. Rhodococcus erythropolis an endophytic bacterium isolated from root nodules of Lupinus latifolius.Fresenius Environ.
Bull. 2021,30, 2464–2469.
47.
Li, Q.; Xiang, P.; Li, L.; Zhang, T.; Wu, Q.; Bao, Z.; Tu, W.; Zhao, C. Phosphorus mining activities alter endophytic bacterial
communities and metabolic functions of surrounding vegetables and crops. Plant Soil 2024,497, 155–174. [CrossRef]
48.
Sitlaothaworn, K.; Budsabun, T.; Booncharoen, A.; Panphut, W.; Savarajara, A.; Tanasupawat, S. Diversity of Plant Growth-
Promoting Endophytic Bacteria, Genome Analysis of Strain Sx8-8 and Its Rice Germination Promoting Activity. Microbiology 2023,
92, 269–283. [CrossRef]
49.
Veliz, E.A.; Martínez-Hidalgo, P.; Hirsch, A.M. Chitinase-producing bacteria and their role in biocontrol. AIMS Microbiol. 2017,
3, 689–705. [CrossRef]
50.
Nayaka, S.; Chakraborty, B.; Swamy, P.S.; Bhat, M.P.; Airodagi, D.; Basavarajappa, D.S.; Rudrappa, M.; Hiremath, H.; Na-
garaja, S.K.; Madhappa, C. Isolation, characterization, and functional groups analysis of Pseudoxanthomonas indica RSA-23 from
rhizosphere soil. J. Appl. Pharm. Sci. 2019,9, 101–106. [CrossRef]
51.
Nascimento, F.X.; Tavares, M.J.; Glick, B.R.; Rossi, M.J. Improvement of Cupriavidus taiwanensis Nodulation and Plant Growth
Promoting Abilities by the Expression of an Exogenous ACC Deaminase Gene. Curr. Microbiol. 2018,75, 961–965. [CrossRef]
52.
Purkayastha, G.D.; Mangar, P.; Saha, A.; Saha, D. Evaluation of the biocontrol efficacy of a Serratia marcescens strain indigenous to
tea rhizosphere for the management of root rot disease in tea. PLoS ONE 2018,13, e0191761. [CrossRef] [PubMed]
53.
Villarreal-Delgado, M.F.; Villa-Rodríguez, E.D.; Cira-Chávez, L.A.; Estrada-Alvarado, M.I.; Parra-Cota, F.I.; de los Santos-
Villalobos, S. El género Bacillus como agente de control biológico y sus implicaciones en la bioseguridad agrícola. Rev. Mex. Fit.
2018,36, 95–130. [CrossRef]
54.
Ortiz, A.; Sansinenea, E. Bacillus thuringiensis based biopesticides for integrated crop management. In Biopesticides; Elsevier:
Amsterdam, The Netherlands, 2022; pp. 1–6. [CrossRef]
55.
Nazli, F.; Wang, X.; Ahmad, M.; Hussain, A.; Bushra Dar, A.; Nasim, M.; Jamil, M.; Panpluem, N.; Mustafa, A. Efficacy of Indole
Acetic Acid and Exopolysaccharides-Producing Bacillus safensis Strain FN13 for Inducing Cd-Stress Tolerance and Plant Growth
Promotion in Brassica juncea (L.). Appl. Sci. 2021,11, 4160. [CrossRef]
56.
Robles Montoya, R.I.; Parra Cota, F.I.; de los Santos Villalobos, S. Draft genome sequence of Bacillus megaterium TRQ8, a plant
growth-promoting bacterium isolated from wheat (Triticum turgidum subsp. durum) rhizosphere in the Yaqui Valley, Mexico. 3
Biotech 2019,9, 201. [CrossRef]
57.
Dobrzy´nski, J.; Jakubowska, Z.; Kulkova, I.; Kowalczyk, P.; Kramkowski, K. Biocontrol of fungal phytopathogens by Bacillus
pumilus.Front. Microbiol. 2023,14, 1194606. [CrossRef]
58.
Groff, M.C.; Scaglia, G.; Gaido, M.; Kassuha, D.; Ortiz, O.A.; Noriega, S.E. Kinetic modeling of fungal biomass growth and
lactic acid production in Rhizopus oryzae fermentation by using grape stalk as a solid substrate. Biocatal. Agric. Biotechnol. 2022,
39, 102255. [CrossRef]
59.
Kaur, R.; Saxena, S. Evaluation of drought-tolerant endophytic fungus Talaromyces purpureogenus as a bioinoculant for wheat
seedlings under normal and drought-stressed circumstances. Folia Microbiol. 2023,68, 781–799. [CrossRef]
60.
Sadeq Alkuwaitii, N.A.; Aish, A.A.; Abdulmalak, S.T.; Kareem, T.A.; Sulaiman, M.M. Field treatment of three wheat varieties
with Trichoderma harzianum bioagent to control Anguina tritici.J. Appl. Biol. Biotechnol. 2023,11, 200–204. [CrossRef]

Soil Syst. 2024,8, 112 15 of 15
61.
Kumar, P.; Singh, S.K.; Kumar, K.; Kumar, A.; Singh, A.; Kumar, A. Strategy on Management of Alternaria Leaf Spot of Broad Bean
(Vicia faba L.). Int. J. Curr. Microbiol. App Sci. 2021,11, 3181–3189.
62.
Phainuphong, P.; Rukachaisirikul, V.; Phongpaichit, S.; Sakayaroj, J.; Kanjanasirirat, P.; Borwornpinyo, S.; Akrimajirachoote, N.;
Yimnual, C.; Muanprasat, C. Depsides and depsidones from the soil-derived fungus Aspergillus unguis PSU-RSPG204. Tetrahedron
2018,74, 5691–5699. [CrossRef]
63.
Daroodi, Z.; Taheri, P.; Tarighi, S. Direct antagonistic activity and tomato resistance induction of the endophytic fungus
Acrophialophora jodhpurensis against Rhizoctonia solani.Biol. Control 2021,160, 104696. [CrossRef]
64.
Patel, H.; Rawat, S. Thermophilic fungi: Diversity, physiology, genetics, and applications. In New and Future Developments in
Microbial Biotechnology and Bioengineering; Elsevier: Amsterdam, The Netherlands, 2021; pp. 69–93. [CrossRef]
65.
De Oliveira Simas, A.L.; Guimarães, N.C.d.A.; Glienke, N.N.; Galeano, R.M.S.; Teles, J.S.d.S.; Kiefer, C.; Nascimento, K.M.R.d.S.;
Masui, D.C.; Zanoelo, F.F.; Giannesi, G.C. Production of Phytase, Protease and Xylanase by Aspergillus niveus with Rice Husk as a
Carbon Source and Application of the Enzymes in Animal Feed. Waste Biomass Valoriz. 2024,15, 3939–3951. [CrossRef]
66.
Villa-Rodriguez, E.; Lugo-Enríquez, C.; de los Santos-Villalobos, S.; Parra-Cota, F.I.; Figueroa-López, P. First Report of Cochliobolus
sativus Causing Spot Blotch on Durum Wheat (Triticum durum) in the Yaqui Valley, Mexico. Plant Dis. 2016,100, 2329. [CrossRef]
67.
Yang, J.; Han, J.; Jing, Y.; Li, S.; Lan, B.; Zhang, Q.; Yin, K. Fusarium isolates with diverse morphologies show similar invasion and
colonization strategies in alfalfa. Front. Plant Sci. 2024,15, 1390069. [CrossRef]
68.
Cendoya, E.; Nichea, M.J.; del Pilar Monge, M.; Zachetti VG, L.; Chiacchiera, S.M.; Ramirez, M.L. Effect of fungicides commonly
used for Fusarium head blight management on growth and fumonisin production by Fusarium proliferatum.Rev. Argent. Microbiol.
2021,53, 64–74. [CrossRef]
69.
Swamy, S.D.; Mahadevakumar, S.; Hemareddy, H.; Amruthesh, K.; Mamatha, S.; Kunjeti, S.G.; Swapnil, R.; Kumar, T.V.;
Lakshmidevi, N. First report of Fusarium equiseti—The incitant of post flowering stalkrot of maize (Zea mays L.) in India. Crop Prot.
2020,129, 105035. [CrossRef]
70.
Parihar, T.J.; Yaseen Sofi, M.; Rasool, R.S.; Khursheed, S.; Bhat, Z.A.; Hussain, K.; Dhekale, B.; Majeed Zargar, S.; Hakak, A.S.;
Shah, M.D.; et al. Fusarium chlamydosporum, causing wilt disease of chili (Capsicum annum L.) and brinjal (Solanum melongena L.) in
Northern Himalayas: A first report. Sci. Rep. 2022,12, 20392. [CrossRef]
71.
Majeed, R.A.; Shahid, A.A.; Ashfaq, M.; Saleem, M.Z.; Haider, M.S. First Report of Curvularia lunata Causing Brown Leaf Spots of
Rice in Punjab, Pakistan. Plant Dis. 2016,100, 219. [CrossRef]
72.
AbdElfatah, H.-A.S.; Sallam NM, A.; Mohamed, M.S.; Bagy HM, M.K. Curvularia lunata as new causal pathogen of tomato early
blight disease in Egypt. Mol. Biol. Rep. 2021,48, 3001–3006. [CrossRef]
73.
Ibrahim SR, M.; Mohamed SG, A.; Altyar, A.E.; Mohamed, G.A. Natural Products of the Fungal Genus Humicola: Diversity,
Biological Activity, and Industrial Importance. Curr. Microbiol. 2021,78, 2488–2509. [CrossRef]
74.
Van Ruijven, J.; Ampt, E.; Francioli, D.; Mommer, L. Do soil-borne fungal pathogens mediate plant diversity–productivity
relationships? Evidence and future opportunities. J. Ecol. 2020,108, 1810–1821. [CrossRef]
75.
Van den Berg, N.I.; Machado, D.; Santos, S.; Rocha, I.; Chacón, J.; Harcombe, W.; Mitri, S.; Patil, K.R. Ecological modelling
approaches for predicting emergent properties in microbial communities. Nat. Ecol. Evol. 2022,6, 855–865. [CrossRef] [PubMed]
76.
Assefa, S.; Tadesse, S. The Principal Role of Organic Fertilizer on Soil Properties and Agricultural Productivity—A Review. Agric.
Res. Technol. 2019,22, 556192. [CrossRef]
77.
Hirel, B.; Tétu, T.; Lea, P.J.; Dubois, F. Improving Nitrogen Use Efficiency in Crops for Sustainable Agricultur. Sustainability 2011,
3, 1452–1485. [CrossRef]
78.
Meisner, C.A.; Acevedo, E.; Flores, D.; Sayre, K.; Ortiz-Monasterio, I.; Byerlee, D. Wheat Production & Grower Practices in the Yaqui
Valley, Sonora, Mexico; Wheat Special Report No.6; CIMMYT: El Batán, Mexico, 1992.
79.
Barrett, J.E.; Burke, I.C. Nitrogen Retention in Semiarid Ecosystems Across a Soil Organic-Matter Gradient. Ecol. Appl. 2002,
12, 878–890. [CrossRef]
80.
Guo, Z.; Han, J.; Li, J.; Xu, Y.; Wang, X. Effects of long-term fertilization on soil organic carbon mineralization and microbial
community structure. PLoS ONE 2019,14, e0211163. [CrossRef]
81.
Zhang, S.; Li, X.; Chen, K.; Shi, J.; Wang, Y.; Luo, P.; Yang, J.; Wang, Y.; Han, X. Long-term fertilization altered microbial community
structure in an aeolian sandy soil in northeast China. Front. Microbiol. 2022,13, 979759. [CrossRef]
82.
Gu, Y.; Wang, Y.; Lu, S.; Xiang, Q.; Yu, X.; Zhao, K.; Zou, L.; Chen, Q.; Tu, S.; Zhang, X. Long-term Fertilization Structures Bacterial
and Archaeal Communities along Soil Depth Gradient in a Paddy Soil. Front. Microbiol. 2017,8, 1516. [CrossRef]
83.
Dal Molin, S.J.; Ernani, P.R.; Gerber, J.M. Soil acidification and nitrogen release following application of nitrogen fertilizers.
Commun. Soil Sci. Plant Anal. 2020,51, 2551–2558. [CrossRef]
84.
Berg, G.; Smalla, K. Plant species and soil type cooperatively shape the structure and function of microbial communities in the
rhizosphere. FEMS Microbiol. Ecol. 2009,68, 1–13. [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual
author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to
people or property resulting from any ideas, methods, instructions or products referred to in the content.