Assessment of Bacterial Resistance and Soil Quality Parameters in Glyphosate-Treated Agricultural Irrigation Areas

Assessment of Bacterial Resistance and Soil Quality Parameters in Glyphosate-Treated Agricultural Irrigation Areas | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessment of Bacterial Resistance and Soil Quality Parameters in Glyphosate-Treated Agricultural Irrigation Areas Karolayne Silva Souza, Milena Roberta Freire Silva, Manoella Almeida Candido, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5969006/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study evaluates bacterial resistance and soil quality parameters in agricultural irrigation areas using glyphosate, focusing on the Icó-Mandantes and Apolônio Sales projects in Petrolândia, Pernambuco. The research investigated the physicochemical characteristics of the soil, such as density, particle size composition, pH, and nutrient levels (P, Ca, Mg, Na, K, Al). Soil samples were collected and analyzed to identify the presence of antibiotic-resistant bacteria. The results show that, although the physicochemical parameters are within acceptable standards, there is a significant presence of resistant bacteria, especially Stenotrophomonas maltophilia, Bacillus cereus, and Enterobacter cloacae. The predominance of multi-resistant bacteria suggests that the continuous use of glyphosate may promote bacterial resistance, posing a risk to public health and agricultural sustainability. Therefore, the study highlights the need for more sustainable agricultural practices and continuous monitoring of glyphosate's effects on soil. Microorganisms Soil Microbiota Pesticides Agriculture Figures Figure 1 Figure 2 Introduction Brazil is one of the largest consumers of pesticides in the world, standing out for the intensive use of these substances in agriculture. Glyphosate is a pesticide of the herbicide class, used to maximize agricultural productivity, and this practice has undoubtedly contributed to the significant increase in agricultural production, essential to meet the growing demand for food (Lima, Boëchat, and Gücker, 2021). The intensive use of herbicides in modern agriculture has been a heated topic of debate due to their potential environmental and human health impacts. Among these herbicides, glyphosate stands out as one of the most widely used globally for its effectiveness in controlling a wide range of weeds (Clapp, 2021). However, this popularity brings significant concerns about the adverse effects that its continuous use may exert on the soil and associated ecosystems. Recent studies indicate that glyphosate application can alter soil microbiota and contribute to the development of antibiotic-resistant bacteria, an emerging public health issue (Meftaul et al., 2020; Qiu et al., 2022; Zhang et al., 2024). The Icó-Mandantes and Apolônio Sales irrigation projects, located in Petrolândia, Pernambuco, encompass significant agricultural production areas in the Northeast (Silva, 2016). According to data from CODEVASF (Companhia de Desenvolvimento dos Vales do São Francisco e do Parnaíba) in 2023, the Icó-Mandantes project achieved about 38,014 tons of family agricultural production, while Apolônio Sales resulted in 23,628 tons (CODEVASF, 2023). Both projects extensively use glyphosate for weed control, making them ideal areas to study the environmental impacts and soil health associated with the use of this herbicide. Bacterial resistance is one of the most concerning consequences of the indiscriminate use of herbicides like glyphosate, as resistant bacteria can emerge and proliferate in environments where the herbicide is regularly applied, posing a threat not only to agriculture but also to human and animal health (Singh et al., 2024). The soil, being a natural reservoir of microorganisms, is a critical component for ecosystem health and agricultural productivity, and changes in its microbiological composition can have profound and lasting repercussions (Banerjee and Heijden, 2023; Hartmann and Six, 2023). In light of this scenario, the objective of this study is to evaluate bacterial resistance and soil quality parameters in agricultural irrigation areas using glyphosate, specifically in the Icó-Mandantes and Apolônio Sales irrigation projects. This evaluation is crucial to understand the changes induced by glyphosate in soil microbiota and its physicochemical properties, providing valuable insights for the formulation of more sustainable agricultural practices. Methodology Sample Collection The Icó-Mandantes and Apolônio Sales areas in Petrolândia, Pernambuco, are renowned for their agricultural irrigation projects, intricately intertwining with the use of glyphosate herbicide. The Icó-Mandantes irrigation project, an intricate tapestry of agricultural innovation, is located in the municipality of Petrolândia, extending into a small part of Floresta, covering a verdant area of 22,914 hectares. The Apolônio Sales project, equally captivating, is also situated in Petrolândia and is an integral part of the region's irrigation system. Soil samples were meticulously collected in duplicates using sterile bags from distinct points as illustrated in Fig. 1 . In the Icó-Mandantes Project, samples P1 were collected near the coordinates: latitude − 8.8286 and longitude − 38.3000, and P2 near latitude − 8.9070 and longitude − 38.4143. Meanwhile, in the Apolônio Sales Project, sample P3 was collected around latitude − 8.9501 and longitude − 38.2714. These locations were strategically chosen to represent the kaleidoscopic environmental and management conditions prevailing in these intricate areas. Upon collection, the sterile bags containing the soil samples were carefully stored in thermal boxes to prevent any microbiological changes due to temperature variations. The samples, a mosaic of the local soil's intricate nature, were promptly sent to the Instituto Agronômico de Pernambuco (IPA) for soil analysis. Subsequently, to preserve their viability, the samples were stored in cold chambers at 4°C, orchestrating an environment to maintain their integrity until microbiological tests could be performed at the Molecular Biology Laboratory of the Federal University of Pernambuco (UFPE). This methodological approach certainly beckons a deep delve into the labyrinth of soil quality and bacterial resistance, offering a crucible of insights into the verdant and enigmatic dynamics of glyphosate use in these captivating agricultural projects. As we embark on this scientific journey, the intricate details of our findings will transcend conventional understanding, reimagining sustainable agricultural practices. Soil Analysis To determine soil density and particle size composition, as well as to measure pH, available phosphorus (P), and exchangeable cations (Ca, Mg, Na, K), the methodologies described in the "Manual of Soil Analysis Methods" (Teixeira et al., 2017) were followed. Soil Density Soil density was determined using the volumetric cylinder method. Undisturbed samples were collected with metal cylinders of known volume, ensuring no soil compaction during collection. After collection, the samples were dried in an oven at 105°C until a constant weight was achieved. Soil density (Ds) was calculated as the ratio of the dry soil mass (ms) to the volume of the cylinder (V). The density of solid particles was determined using the volumetric flask method, where the dry sample was transferred to a volumetric flask and filled with ethanol to eliminate air bubbles. The volume of ethanol required to fill the flask was used to calculate the volume of the particles. Particle Size Composition Particle size analysis was performed by dispersing the samples in a sodium hexametaphosphate solution followed by agitation and sedimentation. The fractions of coarse sand, fine sand, silt, and clay were separated by sieving and sedimentation, with the fractions being weighed after drying. The concentration of each fraction was calculated in g/kg. pH and Available Phosphorus (P) Determination Soil pH was measured in a soil: water suspension in a 1:2.5 ratio using a calibrated pH meter. Dry soil samples were mixed with distilled water, agitated, and left to settle before reading the pH. For available phosphorus determination, the ion exchange resin method was used. Samples were agitated with anion exchange resins, followed by elution of the phosphorus adsorbed on the resin with sodium chloride solution. The phosphorus concentration in the extract was determined colorimetrically. Exchangeable Cations Exchangeable cations (Ca²⁺-Calcium, Mg²⁺-Magnesium, K⁺-Potassium, Na⁺-Sodium) were extracted using 1 mol L⁻¹ ammonium acetate solution, pH 7.0. The concentrations of Ca²⁺ and Mg²⁺ were determined by atomic absorption, while K⁺ and Na⁺ were quantified by flame photometry. Bacterial Isolation For bacterial isolation, procedures were adopted to ensure efficient extraction and accurate identification of the present bacteria. Soil samples were homogenized, and 20 grams of each sample were transferred to glass flasks containing a disaggregation solution enriched with glyphosate. The disaggregation solution was prepared with sodium pyrophosphate (0.18 g), Tween 80 (0.18 mL), NaCl (1.53 g), and distilled water (174.6 mL). To this solution, 5.4 mL of pre-filtered commercial glyphosate solution was added, resulting in a final concentration of approximately 2.5% glyphosate. Glass beads were included in the solution to aid in the disaggregation of microorganisms present in the soil. The flasks were placed in a shaker incubator, subjected to agitation at 150 RPM for 30 minutes at 37°C. After incubation, a 1 mL aliquot from each flask was taken to initiate serial dilutions. The initial sample was considered the first dilution (10^-1), and subsequent dilutions (10^-2 to 10^-5) were performed in tubes containing 9 mL of sterile saline solution (0.85%). For bacterial isolation, 50 µL of each dilution was taken and inoculated on Eosin Methylene Blue (EMB) agar, 5% Blood agar, and Nutrient agar using a Drigalski spatula. The plates were incubated at 37°C for 24 and 48 hours, with isolates showing 24-hour growth identified as A and those with 48-hour growth as B. After the incubation period, bacterial colonies were isolated by transferring portions of each colony to tubes containing Nutrient agar enriched with glyphosate, where they were stored for further analysis and characterization. Results The physicochemical analyses conducted on the soil samples collected from the Icó-Mandantes and Apolônio Sales irrigation projects in Petrolândia, Pernambuco, were compared to the threshold values set by Embrapa (Brazilian Agricultural Research Corporation). These results are presented in Table 1 . Table 1 Physicochemical Results. Parameter P1 P2 P3 Reference Values (EMBRAPA) Physical Analysis Apparent Density (g/cm³) 1.43 1.54 1.57 1.1–1.6 Particle Density (g/cm³) 2.62 2.62 2.62 ≈ 2.65 Coarse Sand (%) 41 43 45 0.2–2 mm (particle diameter) Fine Sand (%) 47 47 47 0.05–0.2 mm (particle diameter) Silte (%) 2 2 2 0.002–0.05 mm (particle diameter) Clay (%) 10 8 6 < 0.002 mm (particle diameter) Chemical Analysis Available Phosphorus (P) (mg/dm³) 92 43 29 ≥ 20 for agricultural soils pH 7.30 6.90 7.40 5.5–7.0 Calcium (Ca) (cmolc/dm³) 2.45 2.50 2.00 1.5–6 Magnesium (Mg) (cmolc/dm³) 0.75 1.20 0.85 0.5–2 Sodium (Na) (cmolc/dm³) 0.03 0.06 0.02 < 0.7 Potassium (K) (cmolc/dm³) 0.17 0.26 0.22 0.1–0.3 Aluminum (Al) (cmolc/dm³) 0.00 0.00 0.00 < 0.5 A total of 28 bacterial isolates were identified from the microbiological analysis, with 10 (36%) in P1, 10 (36%) in P2, and 8 (28%) in P3 (Fig. 1 ). Of these, 15 (54%) were gram-positive bacteria ( Bacillus cereus, Bacillus megaterium, Staphylococcus siniae, Staphylococcus capitis, Clostridium difficile, Paenibacillus sp., and Paenibacillus agaridevorans) and 13 (46%) were gram-negative bacteria (Enterobacter cloacae, Stenotrophomonas maltophilia, Pseudomonas nitroreducens, Shewanella frigidimarina, Klebsiella variicola, Burkholderia gladioli, Prevotella heparinolytica , and Rhizobium radiobacter ). The most prevalent genus was Bacillus, found at various collection points (9/28). Within this genus, Bacillus cereus was the most frequent species, present at eight different points: P1D1, P1D3B, P2D1A, P2D2B, P2D3E, P2D3G, P3D2A, and P3D3D. Another genus present at several points was Enterobacter , with the species Enterobacter cloacae identified at points P1D2B, P1D2C, P1D2D, and P1D3D. The highest species diversity was observed at point P2, where six different bacterial species were found: Staphylococcus siniae, Klebsiella variicola, Burkholderia gladioli, Bacillus cereus , and Stenotrophomonas maltophilia . These data highlight the predominance of Bacillus cereus as the most common species in the analyzed samples. The analysis of bacterial isolates revealed a varied antibiotic resistance profile, with 5 (19%) being multidrug-resistant (MDR) and 23 (81%) non-multidrug-resistant (N-MDR). Some species stood out for their significant resistance, with P2 showing the highest number of MDR bacteria, while P3 did not show any isolates with this profile (Table 2 .). Among the isolates, Stenotrophomonas maltophilia presented the highest resistance profile, being found at points P1D3C, P1D3E, and P2D3F. At point P1D3C, this species showed resistance to five different classes of antibiotics: AMI, CEFE, CIP, GEN, IMI, MER, PIP, and TRO. At point P1D3E, in addition to these antibiotics, it also showed resistance to PIPE and TOB. At point P2D3F, Stenotrophomonas maltophilia was resistant to AMOX, CEFE, CEFO, CEFT, and COLI. Another species that showed significant resistance was Staphylococcus siniae , identified at point P2D3B, which was resistant to four different classes: AMOX, AMP, CEFT, CLI, OXA, and PEN. Additionally, Klebsiella variicola , found at point P2D3C, exhibited resistance to two classes of antibiotics, AMP, PIP, and FOS. These findings underscore the presence of antibiotic-resistant bacteria in the soil of these agricultural areas, with a significant portion being MDR, particularly in P2. This resistance poses a potential risk to public health and highlights the need for careful monitoring and sustainable agricultural practices to mitigate the development of such resistance. Table 2 Resistance Profile of Bacterial Isolates. Points Species Antibiotics Classification Score MALDI-TOF MS P1D1 Bacillus cereus AMOX, AMP, CEF, OXA, PEN N-MDR 2.12 P1D2A Bacillus megaterium CLIN N-MDR 2.15 P1D2B Enterobacter cloacae AMOX, AMP N-MDR 2.20 P1D2C Enterobacter cloacae AMOX, AMP N-MDR 2.25 P1D2D Enterobacter cloacae AMOX, AMP N-MDR 2.30 P1D3A Pseudomonas nitroeducens COLI N-MDR 2.09 P1D3B Bacillus cereus AMOX, AMP, CEF, OXA, PEN N-MDR 2.18 P1D3C Stenotrophomonas maltophilia AMI, CEFE, CIP, GEN, IMI, MER, PIP, TRO MDR 2.28 P1D3D Enterobacter cloacae AMOX, AMP N-MDR 2.14 P1D3E Stenotrophomonas maltophilia AMI, CEFE, CIP, IMI, MER, PIP, PIPE, TOB MDR 2.32 P2D1A Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.21 P2D2A Clostridium difficile AMOX, GENT, SIN N-MDR 2.16 P2D2B Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.11 P2D3A Shewanella frigidimanina AZT, COLI N-MDR 2.08 P2D3B Staphylococcus siniae AMOX, AMP, CEFT, CLI, OXA, PEN MDR 2.19 P2D3C Klebsiella variicola AMP, PIP, FOS MDR 2.27 P2D3D Brukhalderia gladiali AMP, FOS N-MDR 2.10 P2D3E Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.13 P2D3F Stenotrophomonas maltophilia AMOX, CEFE, CEFO, CEFT, COLI MDR 2.22 P2D3G Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.29 P3D1A Prevotella heparinalytica AZT, COLI, ERT, FOS N-MDR 2.24 P3D2A Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.17 P3D3A Rhizobium radiobacter AZT, FOS N-MDR 2.23 P3D3B Staphylococcus capitis CLIN N-MDR 2.09 P3D3C Paenibacillus sp - N-MDR 2.20 P3D3D Bacillus cereus AMOX, AMP, CEFT, OXA, PEN N-MDR 2.30 P3D3E Pichia accidentalis - N-MDR 2.25 P3D3F Paenibacillus agaridevorans AMOX, AMP, CEFT, OXA, PEN N-MDR 2.15 Legend: Amikacin (AMI); Amoxicillin (AMOX); Ampicillin (AMP); Aztreonam (AZT); Cefepime (CEFE); Ceftriaxone (CEFT); Ciprofloxacin (CIP); Clindamycin (CLIN); Colistin (COLI); Fosfomycin (FOS); Gentamicin (GEN); Imipenem (IMI); Meropenem (MER); Oxacillin (OXA); Penicillin (PEN); Piperacillin (PIP); Piperacillin/Tazobactam (PIPE); Synercid (Quinupristin/Dalfopristin) (SIN); Tobramycin (TOB); Trimethoprim-Sulfamethoxazole (TRO). Discussion The results of the physicochemical analyses revealed that the bulk density of the samples ranged from 1.43 to 1.57 g/cm³, falling within the acceptable range for agricultural soils. The particle density was consistent across samples, with a value of 2.62 g/cm³, close to the typical value for mineral soils. These parameters indicate that the soils have good structure, with little compaction, favoring root penetration and water infiltration. Such characteristics are essential for soil health, as adequate bulk density and typical particle density ensure that the soil can support agricultural vegetation without significant issues of compaction or lack of porosity (Shaheb, Venkatesh, and Shearer, 2021). The particle size composition of the samples showed values consistent with particle diameter ranges, indicating that the soils are predominantly sandy. This type of soil can influence water and nutrient retention capacity, crucial aspects for agricultural production (Huang and Hartemink, 2020). The levels of available phosphorus (P) in the samples varied significantly. Sample 1 had a high phosphorus content (92 mg/dm³), while samples 2 and 3 had values of 43 mg/dm³ and 29 mg/dm³, respectively. All values are above the recommended minimum (≥ 20 mg/dm³) for agricultural soils, indicating good phosphorus availability for plants. Phosphorus is essential for root development, promoting more robust roots that improve water and nutrient absorption. It is a vital component of ATP, the primary energy molecule in plant cells, indispensable for photosynthesis, respiration, and the synthesis of essential molecules. Additionally, phosphorus is crucial for DNA and RNA formation, necessary for cell replication and protein synthesis (Liu, 2021). The pH of the samples ranged from 6.90 to 7.40, indicating that the soils have slightly acidic to neutral conditions, suitable for most agricultural crops. Balanced pH is crucial because it influences the solubility of essential nutrients and the activity of beneficial soil microorganisms. Soils with very acidic (pH 7.0) conditions can lead to the unavailability of vital nutrients such as phosphorus, potassium, and micronutrients, negatively affecting plant growth and crop productivity (Yadav et al., 2020; Baritz et al., 2021). The calcium (Ca) levels in the samples ranged from 2.00 to 2.50 cmolc/dm³, within the reference range. Magnesium (Mg) values ranged from 0.75 to 1.20 cmolc/dm³, also within the reference range, while sodium (Na) levels in the samples were low, ranging from 0.02 to 0.06 cmolc/dm³, well below the maximum limit, indicating no salinity problems in the soil. Potassium (K) levels ranged from 0.17 to 0.26 cmolc/dm³, within the acceptable range according to Embrapa. None of the samples showed exchangeable aluminum (Al), with values of 0.00 cmolc/dm³, indicating the absence of aluminum toxicity. Calcium is vital for the formation and stability of cell walls and improves soil structure by promoting the aggregation of clay particles, enhancing aeration and water infiltration. Magnesium is a central component of the chlorophyll molecule, essential for photosynthesis and the activation of various enzymes involved in plant metabolism. Potassium is crucial for the osmotic regulation of plants, influencing processes such as stomatal opening and closing and protein synthesis. Magnesium, as part of the chlorophyll molecule, is indispensable for photosynthesis and enzyme activation in plant metabolism (Havlin, 2020). Low sodium levels indicate no risk of soil salinity, which is important as high sodium levels can lead to clay particle dispersion, resulting in compacted and poorly structured soils that hinder water infiltration and root growth (Li and Kang, 2020). The absence of exchangeable aluminum in the samples is beneficial since high aluminum levels can be toxic to plants, inhibiting root growth and nutrient absorption (Shetty et al., 2021). While the physicochemical results of the soil samples analyzed do not directly indicate the effects of glyphosate, the presence of this herbicide can influence nutrient availability and soil health in the long term. Glyphosate is known to bind to cations such as calcium and magnesium, forming complexes that can reduce the availability of these nutrients to plants (Bortolheiro and Silva, 2021). The low sodium concentration and absence of aluminum are positive signs, but the continuous use of glyphosate may eventually alter nutrient dynamics and overall soil health (Ortiz et al., 2022). Therefore, while the current results do not show evident adverse effects of glyphosate, continuous monitoring and careful management of this herbicide use are recommended to prevent potential long-term negative impacts. In the microbiological analysis, the genus Bacillus was the most prevalent, found at various collection points, with Bacillus cereus being the most frequent species, present at eight distinct points. The prevalence of this bacterium is consistent with the literature, as it is commonly found in various environments, including agricultural soils, due to its ability to form resistant spores and survive adverse environmental conditions such as high temperatures, UV radiation, dehydration, and exposure to chemical disinfectants. This resistance allows spores to remain viable in the soil, even after rigorous agricultural practices such as crop rotation and pesticide use (Algammal et al., 2024; Jessberger et al., 2020; Liu et al., 2020). Gram-negative bacteria identified, such as Enterobacter cloacae, Stenotrophomonas maltophilia, Pseudomonas nitroreducens, Shewanella frigidimarina, Klebsiella variicola, Burkholderia gladioli, Prevotella heparinolytica , and Rhizobium radiobacter , play various roles in the soil ecosystem. Enterobacter cloacae , for example, can be an opportunistic pathogen while aiding in the decomposition of organic matter and nutrient cycling, although its presence may indicate fecal contamination (Wang et al., 2023; Ji et al., 2020). Stenotrophomonas maltophilia is known to promote plant growth through the production of auxins and siderophores and antifungal activities (Hu et al., 2021; Ghosh, Chatterjee, and Mandal, 2020). Pseudomonas nitroreducens contributes to the degradation of organic pollutants and plant growth through bioactive compounds (Jayaraj et al., 2023). Prevotella heparinolytica is commonly found in the gastrointestinal tract of humans and animals, and its presence in the soil may indicate fecal contamination (Wongkiew et al., 2022). Rhizobium radiobacter is known for its ability to form nodules on legume roots, fixing nitrogen and promoting plant growth (Atuchin et al., 2023). The bacterial diversity in agricultural soil reflects the complexity of microbial interactions and the influence of management practices such as fertilizer and pesticide use. The presence of these bacteria indicates a rich ecological dynamic, where some species promote soil and plant health, while others may pose contamination risks. The presence of glyphosate in managed agricultural soil may correlate with increased bacterial resistance to antibiotics. Studies suggest that glyphosate, a widely used herbicide, can exert selective pressure on microbial communities, favoring the proliferation of resistant strains (Kepler et al., 2020; Nielsen et al., 2018). Glyphosate can alter soil microbiota, promoting changes in bacterial composition and increasing antibiotic resistance in bacteria that share resistance mechanisms to both compounds (Talahmeh, Abu-Rumeileh, and Al-Razem, 2020). Exposure to glyphosate has been associated with the induction of cross-resistance in soil bacteria. This occurs because glyphosate can induce mutations or activate defense mechanisms in bacteria, such as efflux pumps, which also confer antibiotic resistance (Raoult et al., 2021). The presence of multidrug-resistant Stenotrophomonas maltophilia at several points suggests that this microorganism may be particularly adapted to glyphosate-contaminated environments, showing a high capacity to survive and proliferate under selective pressure (Ospino and Spira, 2023). According to the study by Costa et al. (2022), several bacteria exhibiting resistance to both antibiotics and glyphosate were identified. Among these bacteria, those with multidrug efflux pumps were effective against both agents. The study demonstrated that glyphosate exposure increases the prevalence of antibiotic resistance genes (ARGs) and mobile genetic elements, enriching the presence of these elements in soil and aquatic microbiomes. Bacteria identified as resistant to antibiotics and glyphosate include Stenotrophomonas maltophilia, which showed high resistance to multiple antibiotic classes, including aminoglycosides and cephalosporins, found at points P1D3C, P1D3E, and P2D3F in this study. Klebsiella variicola exhibited resistance to antibiotics such as ampicillin and piperacillin at point P2D3C, and Staphylococcus siniae showed resistance to various antibiotic classes, including penicillins and cephalosporins, found at point P2D3B. Moreover, the impact of glyphosate on bacterial resistance is not limited to a direct increase in resistance. The alteration of soil microbiota can lead to changes in the dynamics of gene transfer resistance among bacteria. Mechanisms such as conjugation, transformation, and transduction can be facilitated in environments where glyphosate is present, increasing the spread of resistance genes among different bacterial species. This effect is particularly concerning in agricultural environments, where resistance transfer can occur rapidly due to high bacterial density and constant soil disturbance (Liao et al., 2021). Despite the resistance profile of some bacteria, non-multidrug-resistant (N-MDR) bacterial isolates were also identified in the managed agricultural soil. Among these bacteria, Bacillus cereus was found at several points and, although not multidrug-resistant, is known for its ability to form spores and cause food poisoning. Bacillus megaterium, resistant only to clindamycin, is beneficial to the soil, helping to solubilize phosphates. Pseudomonas nitroreducens, resistant only to colistin, plays a role in the degradation of organic pollutants. Clostridium difficile and Shewanella frigidimarina participate in organic matter decomposition and bioremediation, respectively. These bacteria, although not multidrug-resistant, play crucial roles in the agricultural soil ecosystem, contributing to nutrient cycling, organic matter decomposition, and plant growth promotion (Raoult et al., 2021). Bacterial diversity in agricultural soil reflects the complexity of microbial interactions and the influence of management practices such as fertilizer and pesticide use. The presence of these bacteria indicates a rich ecological dynamic, where some species promote soil and plant health, while others may pose contamination risks. Adequate agricultural practices are essential to maintain microbial balance, favoring beneficial species that contribute to soil fertility and plant health. The interaction between microorganisms, plants, and agricultural practices underscores the importance of continuous monitoring and sustainable management strategies to ensure agricultural productivity and food security (Kelbrick, Hesse, and O'Brien, 2023). Conclusion This study presented an analysis of the impacts of glyphosate use in the Icó-Mandantes and Apolônio Sales irrigation projects located in Petrolândia, Pernambuco, indicating that glyphosate, while effective in weed control and promoting agricultural productivity, has significant effects on soil quality and bacterial resistance. The physicochemical analyses of the soil showed that although the samples were within the acceptable parameters for agricultural soils, the continuous use of glyphosate might alter the availability of essential nutrients and soil structure in the long term. The microbiological evaluation revealed a significant diversity of bacteria, predominantly of the genus Bacillus, and the presence of multidrug-resistant bacteria, particularly observed in species such as Stenotrophomonas maltophilia, Bacillus cereus, and Enterobacter cloacae. Thus, the present analysis highlights glyphosate's potential to promote bacterial resistance, which may pose a risk to both agriculture and public health in areas treated with glyphosate. These findings reinforce the need for more sustainable agricultural practices and continuous monitoring of glyphosate's effects on the soil. Additionally, the implementation of integrated pest management strategies that reduce dependence on chemical herbicides is essential to preserve soil health and prevent the proliferation of resistant bacteria. Declarations Ethical Approval Not applicable. Consent to Participate All study participants gave their informed consent to participate in this research. Consent to Publish All study authors and participants gave their consent for the publication of the results of this research. Author Contributions All authors contributed to the conception and design of the study. The preparation of the material and data collection were carried out by Karolayne Silva Souza, Milena Roberta Freire da Silva, Manoella Almeida Candido and Gabriela de Lima Torres. Soil physicochemical analysis was conducted by Kaline Catiely Campos Silva, Ricardo Marques Nogueira Filho and Fabricio Motteran. The microbiological evaluation was performed by Kátia Cilene da Silva Felix, Lívia Caroline Alexandre de Araújo. Data analysis was carried out by Milena Danda Vasconcelos Santos and Maria Betânia Melo de Oliveira. The critical review of the manuscript was conducted by all authors. All authors read and approved the final version of the manuscript. Funding The authors declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by Coordination for the Improvement of Higher Education Personnel (CAPES/Brazil—Proc. no 88887.500819/2020-00). Competing Interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Data Availability Not applicable. References Algammal, A. M., Eid, H. M., Alghamdi, S., Ghabban, H., Alatawy, R., Almanzalawi, E. A., ... & El-Tarabili, R. M. (2024). Meat and meat products as potential sources of emerging MDR Bacillus cereus: gro EL gene sequencing, toxigenic and antimicrobial resistance. BMC microbiology , 24 (1), 50. Atuchin, V. V., Asyakina, L. K., Serazetdinova, Y. R., Frolova, A. S., Velichkovich, N. S., & Prosekov, A. Y. (2023). Microorganisms for bioremediation of soils contaminated with heavy metals. Microorganisms , 11 (4), 864. Banerjee, S., & Heijden, M. G. (2023). Soil microbiomes and one health. Nature Reviews Microbiology , 21 (1), 6-20. Clapp, J. (2021). Explaining growing glyphosate use: The political economy of herbicide-dependent agriculture. 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Cultivating antimicrobial resistance: how intensive agriculture ploughs the way for antibiotic resistance. Microbiology , 169 (8), 001384. Kepler, R. M., Epp Schmidt, D. J., Yarwood, S. A., Cavigelli, M. A., Reddy, K. N., Duke, S. O., ... & Maul, J. E. (2020). Soil microbial communities in diverse agroecosystems exposed to the herbicide glyphosate. Applied and environmental microbiology , 86 (5), e01744-19. Jayaraj, J., Shibila, S., Ramaiah, M., Alahmadi, T. A., Alharbi, S. A., Mideen, P. K., ... & Sivagnanam, A. (2023). Isolation and Identification of bacteria from the agricultural soil samples to tolerate pesticides dimethoate, thiamethoxam and Imidacloprid. Environmental Research Communications , 5 (7), 075011. Jessberger, N., Dietrich, R., Granum, P. E., & Märtlbauer, E. (2020). The Bacillus cereus food infection as multifactorial process. Toxins , 12 (11), 701. Ji, C., Liu, Z., Hao, L., Song, X., Wang, C., Liu, Y., ... & Liu, X. (2020). Effects of Enterobacter cloacae HG-1 on the nitrogen-fixing community structure of wheat rhizosphere soil and on salt tolerance. Frontiers in Plant Science , 11 , 1094. Li, X., & Kang, Y. (2020). Agricultural utilization and vegetation establishment on saline-sodic soils using a water–salt regulation method for scheduled drip irrigation. Agricultural water management , 231 , 105995. Liao, H., Li, X., Yang, Q., Bai, Y., Cui, P., Wen, C., ... & Zhu, Y. G. (2021). Herbicide selection promotes antibiotic resistance in soil microbiomes. Molecular Biology and Evolution , 38 (6), 2337-2350. Lima, I. B., Boëchat, I. G., & Gücker, B. (2021). Glyphosate in Brazil: use, aquatic contamination, environmental effects and dangers to human health. Geography Notebook , 31(e1), 90-115. Liu, C., Yu, P., Yu, S., Wang, J., Guo, H., Zhang, Y., ... & Ding, Y. (2020). Assessment and molecular characterization of Bacillus cereus isolated from edible fungi in China. Bmc Microbiology , 20 , 1-10. Liu, D. (2021). Root developmental responses to phosphorus nutrition. Journal of Integrative Plant Biology , 63 (6), 1065-1090. Meftaul, I. M., Venkateswarlu, K., Dharmarajan, R., Annamalai, P., Asaduzzaman, M., Parven, A., & Megharaj, M. (2020). Controversies over human health and ecological impacts of glyphosate: Is it to be banned in modern agriculture?. Environmental Pollution , 263 , 114372. Nielsen, L. N., Roager, H. M., Casas, M. E., Frandsen, H. L., Gosewinkel, U., Bester, K., ... & Bahl, M. I. (2018). Glyphosate has limited short-term effects on commensal bacterial community composition in the gut environment due to sufficient aromatic amino acid levels. Environmental Pollution , 233 , 364-376. Ortiz, P., Tapia-Torres, Y., Larsen, J., & García-Oliva, F. (2022). Glyphosate-based herbicides alter soil carbon and phosphorus dynamics and microbial activity. Applied Soil Ecology , 169 , 104256. Ospino, K., and Spira, B. (2023). Glyphosate affects persistence and tolerance but not antibiotic resistance. BMC microbiology , 23 (1), 61. Qiu, D., Ke, M., Zhang, Q., Zhang, F., Lu, T., Sun, L., & Qian, H. (2022). Response of microbial antibiotic resistance to pesticides: An emerging health threat. Science of The Total Environment , 850 , 158057. Raoult, D., Hadjadj, L., Baron, S. A., and Rolain, J. M. (2021). Role of glyphosate in the emergence of antimicrobial resistance in bacteria?. Journal of Antimicrobial Chemotherapy , 76 (7), 1655-1657. Shaheb, M. R., Venkatesh, R., & Shearer, S. A. (2021). A review on the effect of soil compaction and its management for sustainable crop production. Journal of Biosystems Engineering , 1-23. Shetty, R., Vidya, C. S. N., Prakash, N. B., Lux, A., & Vaculík, M. (2021). Aluminum toxicity in plants and its possible mitigation in acid soils by biochar: A review. Science of the Total Environment , 765 , 142744. Silva, K. C. C. (2016). Biomonitoring of pesticides and heavy metals in irrigation projects on the São Francisco River using biochemical and genotoxic markers of Cichla ocellaris . Singh, R., Shukla, A., Kaur, G., Girdhar, M., Malik, T., & Mohan, A. (2024). Systemic Analysis of Glyphosate Impact on Environment and Human Health. ACS omega . Talahmeh, N., Abu‐Rumeileh, S., and Al‐Razem, F. (2020). Development of a selective and differential media for the isolation and enumeration of Bacillus cereus from food samples. Journal of applied microbiology , 128 (5), 1440-1447. Teixeira, P. C., Donagemma, G. K., Fontana, A., & Teixeira, W. G. (2017). Manual de métodos de análise de solo. Wang, X., Wu, Z., Xiang, H., He, Y., Zhu, S., Zhang, Z., ... & Wang, J. (2023). Whole genome analysis of Enterobacter cloacae Rs-2 and screening of genes related to plant-growth promotion. Environmental Science and Pollution Research , 30 (8), 21548-21564. Wongkiew, S., Chaikaew, P., Takrattanasaran, N., & Khamkajorn, T. (2022). Evaluation of nutrient characteristics and bacterial community in agricultural soil groups for sustainable land management. Scientific reports , 12 (1), 7368. Yadav, D. S., Jaiswal, B., Gautam, M., & Agrawal, M. (2020). Soil acidification and its impact on plants. Plant responses to soil pollution , 1-26. Zhang, Q., Lei, C., Jin, M., Qin, G., Yu, Y., Qiu, D., ... & Qian, H. (2024). Glyphosate Disorders Soil Enchytraeid Gut Microbiota and Increases Its Antibiotic Resistance Risk. Journal of Agricultural and Food Chemistry , 72 (4), 2089-2099. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5969006","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":412558471,"identity":"c7554b77-3cf2-4dbf-901d-900c1a02b185","order_by":0,"name":"Karolayne Silva 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Center","correspondingAuthor":false,"prefix":"","firstName":"Kátia","middleName":"Cilene Silva","lastName":"Felix","suffix":""},{"id":412558477,"identity":"9398c040-c2d0-4491-96c7-b6884105e540","order_by":5,"name":"Kaline Catiely Campos Silva","email":"","orcid":"","institution":"University of the State of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Kaline","middleName":"Catiely Campos","lastName":"Silva","suffix":""},{"id":412558481,"identity":"e6627e41-8611-4f2c-a474-08a6a6969c9d","order_by":6,"name":"Ricardo Marques Nogueira Filho","email":"","orcid":"","institution":"University of the State of Bahia","correspondingAuthor":false,"prefix":"","firstName":"Ricardo","middleName":"Marques Nogueira","lastName":"Filho","suffix":""},{"id":412558482,"identity":"f16dfa40-ab2b-4c72-9fe1-be8c642021a4","order_by":7,"name":"Milena Danda Vasconcelos Santos","email":"","orcid":"","institution":"Federal University of Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Milena","middleName":"Danda Vasconcelos","lastName":"Santos","suffix":""},{"id":412558483,"identity":"efdb90f7-285c-4c3d-89ea-4fa32cf7ee0c","order_by":8,"name":"Lívia Caroline Alexandre Araújo","email":"","orcid":"","institution":"Federal University of Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Lívia","middleName":"Caroline Alexandre","lastName":"Araújo","suffix":""},{"id":412558484,"identity":"dd040873-95d7-49b2-b0ec-4af814994b86","order_by":9,"name":"Fabricio Motteran","email":"","orcid":"","institution":"Federal University of Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Fabricio","middleName":"","lastName":"Motteran","suffix":""},{"id":412558485,"identity":"9633f738-2ecd-4373-9520-781daa19d94c","order_by":10,"name":"Maria Betânia Melo Oliveira","email":"","orcid":"","institution":"Federal University of Pernambuco","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Betânia Melo","lastName":"Oliveira","suffix":""}],"badges":[],"createdAt":"2025-02-06 00:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5969006/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5969006/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75936663,"identity":"9140bd9b-0a0d-4cd5-a5f7-cdda222a4c34","added_by":"auto","created_at":"2025-02-10 17:10:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":167365,"visible":true,"origin":"","legend":"\u003cp\u003eDescription of Sampling Points\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5969006/v1/701b888cb23082c7c1a25835.png"},{"id":75936669,"identity":"d4686ed6-bcd1-4794-a08c-046cb7c30f47","added_by":"auto","created_at":"2025-02-10 17:10:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":235053,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 1. Map of the distribution of bacterial isolate species at the three collection points (P1, P2, and P3).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5969006/v1/9c9da3ed705d7a6b6bd7dc42.png"},{"id":81422270,"identity":"d43c841a-ba97-4c83-9eb7-fa5b1d9391e6","added_by":"auto","created_at":"2025-04-26 05:01:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1170552,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5969006/v1/b77fbb1e-9584-47ab-9c37-e2eb2939895d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of Bacterial Resistance and Soil Quality Parameters in Glyphosate-Treated Agricultural Irrigation Areas","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBrazil is one of the largest consumers of pesticides in the world, standing out for the intensive use of these substances in agriculture. Glyphosate is a pesticide of the herbicide class, used to maximize agricultural productivity, and this practice has undoubtedly contributed to the significant increase in agricultural production, essential to meet the growing demand for food (Lima, Bo\u0026euml;chat, and G\u0026uuml;cker, 2021).\u003c/p\u003e \u003cp\u003eThe intensive use of herbicides in modern agriculture has been a heated topic of debate due to their potential environmental and human health impacts. Among these herbicides, glyphosate stands out as one of the most widely used globally for its effectiveness in controlling a wide range of weeds (Clapp, 2021).\u003c/p\u003e \u003cp\u003eHowever, this popularity brings significant concerns about the adverse effects that its continuous use may exert on the soil and associated ecosystems. Recent studies indicate that glyphosate application can alter soil microbiota and contribute to the development of antibiotic-resistant bacteria, an emerging public health issue (Meftaul et al., 2020; Qiu et al., 2022; Zhang et al., 2024).\u003c/p\u003e \u003cp\u003eThe Ic\u0026oacute;-Mandantes and Apol\u0026ocirc;nio Sales irrigation projects, located in Petrol\u0026acirc;ndia, Pernambuco, encompass significant agricultural production areas in the Northeast (Silva, 2016). According to data from CODEVASF (Companhia de Desenvolvimento dos Vales do S\u0026atilde;o Francisco e do Parna\u0026iacute;ba) in 2023, the Ic\u0026oacute;-Mandantes project achieved about 38,014 tons of family agricultural production, while Apol\u0026ocirc;nio Sales resulted in 23,628 tons (CODEVASF, 2023). Both projects extensively use glyphosate for weed control, making them ideal areas to study the environmental impacts and soil health associated with the use of this herbicide.\u003c/p\u003e \u003cp\u003eBacterial resistance is one of the most concerning consequences of the indiscriminate use of herbicides like glyphosate, as resistant bacteria can emerge and proliferate in environments where the herbicide is regularly applied, posing a threat not only to agriculture but also to human and animal health (Singh et al., 2024). The soil, being a natural reservoir of microorganisms, is a critical component for ecosystem health and agricultural productivity, and changes in its microbiological composition can have profound and lasting repercussions (Banerjee and Heijden, 2023; Hartmann and Six, 2023).\u003c/p\u003e \u003cp\u003eIn light of this scenario, the objective of this study is to evaluate bacterial resistance and soil quality parameters in agricultural irrigation areas using glyphosate, specifically in the Ic\u0026oacute;-Mandantes and Apol\u0026ocirc;nio Sales irrigation projects. This evaluation is crucial to understand the changes induced by glyphosate in soil microbiota and its physicochemical properties, providing valuable insights for the formulation of more sustainable agricultural practices.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample Collection\u003c/h2\u003e \u003cp\u003eThe Ic\u0026oacute;-Mandantes and Apol\u0026ocirc;nio Sales areas in Petrol\u0026acirc;ndia, Pernambuco, are renowned for their agricultural irrigation projects, intricately intertwining with the use of glyphosate herbicide. The Ic\u0026oacute;-Mandantes irrigation project, an intricate tapestry of agricultural innovation, is located in the municipality of Petrol\u0026acirc;ndia, extending into a small part of Floresta, covering a verdant area of 22,914 hectares. The Apol\u0026ocirc;nio Sales project, equally captivating, is also situated in Petrol\u0026acirc;ndia and is an integral part of the region's irrigation system.\u003c/p\u003e \u003cp\u003eSoil samples were meticulously collected in duplicates using sterile bags from distinct points as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the Ic\u0026oacute;-Mandantes Project, samples P1 were collected near the coordinates: latitude \u0026minus;\u0026thinsp;8.8286 and longitude \u0026minus;\u0026thinsp;38.3000, and P2 near latitude \u0026minus;\u0026thinsp;8.9070 and longitude \u0026minus;\u0026thinsp;38.4143. Meanwhile, in the Apol\u0026ocirc;nio Sales Project, sample P3 was collected around latitude \u0026minus;\u0026thinsp;8.9501 and longitude \u0026minus;\u0026thinsp;38.2714. These locations were strategically chosen to represent the kaleidoscopic environmental and management conditions prevailing in these intricate areas.\u003c/p\u003e \u003cp\u003eUpon collection, the sterile bags containing the soil samples were carefully stored in thermal boxes to prevent any microbiological changes due to temperature variations. The samples, a mosaic of the local soil's intricate nature, were promptly sent to the Instituto Agron\u0026ocirc;mico de Pernambuco (IPA) for soil analysis. Subsequently, to preserve their viability, the samples were stored in cold chambers at 4\u0026deg;C, orchestrating an environment to maintain their integrity until microbiological tests could be performed at the Molecular Biology Laboratory of the Federal University of Pernambuco (UFPE).\u003c/p\u003e \u003cp\u003eThis methodological approach certainly beckons a deep delve into the labyrinth of soil quality and bacterial resistance, offering a crucible of insights into the verdant and enigmatic dynamics of glyphosate use in these captivating agricultural projects. As we embark on this scientific journey, the intricate details of our findings will transcend conventional understanding, reimagining sustainable agricultural practices.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSoil Analysis\u003c/h3\u003e\n\u003cp\u003eTo determine soil density and particle size composition, as well as to measure pH, available phosphorus (P), and exchangeable cations (Ca, Mg, Na, K), the methodologies described in the \"Manual of Soil Analysis Methods\" (Teixeira et al., 2017) were followed.\u003c/p\u003e\n\u003ch3\u003eSoil Density\u003c/h3\u003e\n\u003cp\u003eSoil density was determined using the volumetric cylinder method. Undisturbed samples were collected with metal cylinders of known volume, ensuring no soil compaction during collection. After collection, the samples were dried in an oven at 105\u0026deg;C until a constant weight was achieved. Soil density (Ds) was calculated as the ratio of the dry soil mass (ms) to the volume of the cylinder (V).\u003c/p\u003e \u003cp\u003eThe density of solid particles was determined using the volumetric flask method, where the dry sample was transferred to a volumetric flask and filled with ethanol to eliminate air bubbles. The volume of ethanol required to fill the flask was used to calculate the volume of the particles.\u003c/p\u003e\n\u003ch3\u003eParticle Size Composition\u003c/h3\u003e\n\u003cp\u003eParticle size analysis was performed by dispersing the samples in a sodium hexametaphosphate solution followed by agitation and sedimentation. The fractions of coarse sand, fine sand, silt, and clay were separated by sieving and sedimentation, with the fractions being weighed after drying. The concentration of each fraction was calculated in g/kg.\u003c/p\u003e\n\u003ch3\u003epH and Available Phosphorus (P) Determination\u003c/h3\u003e\n\u003cp\u003eSoil pH was measured in a soil: water suspension in a 1:2.5 ratio using a calibrated pH meter. Dry soil samples were mixed with distilled water, agitated, and left to settle before reading the pH.\u003c/p\u003e \u003cp\u003eFor available phosphorus determination, the ion exchange resin method was used. Samples were agitated with anion exchange resins, followed by elution of the phosphorus adsorbed on the resin with sodium chloride solution. The phosphorus concentration in the extract was determined colorimetrically.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eExchangeable Cations\u003c/h2\u003e \u003cp\u003eExchangeable cations (Ca\u0026sup2;⁺-Calcium, Mg\u0026sup2;⁺-Magnesium, K⁺-Potassium, Na⁺-Sodium) were extracted using 1 mol L⁻\u0026sup1; ammonium acetate solution, pH 7.0. The concentrations of Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ were determined by atomic absorption, while K⁺ and Na⁺ were quantified by flame photometry.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBacterial Isolation\u003c/h3\u003e\n\u003cp\u003eFor bacterial isolation, procedures were adopted to ensure efficient extraction and accurate identification of the present bacteria. Soil samples were homogenized, and 20 grams of each sample were transferred to glass flasks containing a disaggregation solution enriched with glyphosate. The disaggregation solution was prepared with sodium pyrophosphate (0.18 g), Tween 80 (0.18 mL), NaCl (1.53 g), and distilled water (174.6 mL). To this solution, 5.4 mL of pre-filtered commercial glyphosate solution was added, resulting in a final concentration of approximately 2.5% glyphosate. Glass beads were included in the solution to aid in the disaggregation of microorganisms present in the soil.\u003c/p\u003e \u003cp\u003eThe flasks were placed in a shaker incubator, subjected to agitation at 150 RPM for 30 minutes at 37\u0026deg;C. After incubation, a 1 mL aliquot from each flask was taken to initiate serial dilutions. The initial sample was considered the first dilution (10^-1), and subsequent dilutions (10^-2 to 10^-5) were performed in tubes containing 9 mL of sterile saline solution (0.85%).\u003c/p\u003e \u003cp\u003eFor bacterial isolation, 50 \u0026micro;L of each dilution was taken and inoculated on Eosin Methylene Blue (EMB) agar, 5% Blood agar, and Nutrient agar using a Drigalski spatula. The plates were incubated at 37\u0026deg;C for 24 and 48 hours, with isolates showing 24-hour growth identified as A and those with 48-hour growth as B. After the incubation period, bacterial colonies were isolated by transferring portions of each colony to tubes containing Nutrient agar enriched with glyphosate, where they were stored for further analysis and characterization.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe physicochemical analyses conducted on the soil samples collected from the Ic\u0026oacute;-Mandantes and Apol\u0026ocirc;nio Sales irrigation projects in Petrol\u0026acirc;ndia, Pernambuco, were compared to the threshold values set by Embrapa (Brazilian Agricultural Research Corporation). These results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysicochemical Results.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference Values (EMBRAPA)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePhysical Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApparent Density (g/cm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.1\u0026ndash;1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticle Density (g/cm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026asymp;\u0026thinsp;2.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoarse Sand (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u0026ndash;2 mm (particle diameter)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFine Sand (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u0026ndash;0.2 mm (particle diameter)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilte (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u0026ndash;0.05 mm (particle diameter)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClay (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002 mm (particle diameter)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemical Analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailable Phosphorus (P) (mg/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;20 for agricultural soils\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u0026ndash;7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium (Ca) (cmolc/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium (Mg) (cmolc/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (Na) (cmolc/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (K) (cmolc/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u0026ndash;0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAluminum (Al) (cmolc/dm\u0026sup3;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA total of 28 bacterial isolates were identified from the microbiological analysis, with 10 (36%) in P1, 10 (36%) in P2, and 8 (28%) in P3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 15 (54%) were gram-positive bacteria (\u003cem\u003eBacillus cereus, Bacillus megaterium, Staphylococcus siniae, Staphylococcus capitis, Clostridium difficile, Paenibacillus sp., and Paenibacillus agaridevorans)\u003c/em\u003e and 13 (46%) were gram-negative bacteria \u003cem\u003e(Enterobacter cloacae, Stenotrophomonas maltophilia, Pseudomonas nitroreducens, Shewanella frigidimarina, Klebsiella variicola, Burkholderia gladioli, Prevotella heparinolytica\u003c/em\u003e, and \u003cem\u003eRhizobium radiobacter\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThe most prevalent genus was Bacillus, found at various collection points (9/28). Within this genus, \u003cem\u003eBacillus cereus\u003c/em\u003e was the most frequent species, present at eight different points: P1D1, P1D3B, P2D1A, P2D2B, P2D3E, P2D3G, P3D2A, and P3D3D. Another genus present at several points was \u003cem\u003eEnterobacter\u003c/em\u003e, with the species \u003cem\u003eEnterobacter cloacae\u003c/em\u003e identified at points P1D2B, P1D2C, P1D2D, and P1D3D. The highest species diversity was observed at point P2, where six different bacterial species were found: \u003cem\u003eStaphylococcus siniae, Klebsiella variicola, Burkholderia gladioli, Bacillus cereus\u003c/em\u003e, and \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e. These data highlight the predominance of \u003cem\u003eBacillus cereus\u003c/em\u003e as the most common species in the analyzed samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analysis of bacterial isolates revealed a varied antibiotic resistance profile, with 5 (19%) being multidrug-resistant (MDR) and 23 (81%) non-multidrug-resistant (N-MDR). Some species stood out for their significant resistance, with P2 showing the highest number of MDR bacteria, while P3 did not show any isolates with this profile (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.). Among the isolates, \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e presented the highest resistance profile, being found at points P1D3C, P1D3E, and P2D3F. At point P1D3C, this species showed resistance to five different classes of antibiotics: AMI, CEFE, CIP, GEN, IMI, MER, PIP, and TRO. At point P1D3E, in addition to these antibiotics, it also showed resistance to PIPE and TOB. At point P2D3F, \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e was resistant to AMOX, CEFE, CEFO, CEFT, and COLI.\u003c/p\u003e \u003cp\u003eAnother species that showed significant resistance was \u003cem\u003eStaphylococcus siniae\u003c/em\u003e, identified at point P2D3B, which was resistant to four different classes: AMOX, AMP, CEFT, CLI, OXA, and PEN. Additionally, \u003cem\u003eKlebsiella variicola\u003c/em\u003e, found at point P2D3C, exhibited resistance to two classes of antibiotics, AMP, PIP, and FOS. These findings underscore the presence of antibiotic-resistant bacteria in the soil of these agricultural areas, with a significant portion being MDR, particularly in P2. This resistance poses a potential risk to public health and highlights the need for careful monitoring and sustainable agricultural practices to mitigate the development of such resistance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResistance Profile of Bacterial Isolates.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoints\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAntibiotics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eScore MALDI-TOF MS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEF, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D2A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus megaterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCLIN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D2B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D2C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D2D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D3A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePseudomonas nitroeducens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D3B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEF, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D3C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMI, CEFE, CIP, GEN, IMI, MER, PIP, TRO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D3D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter cloacae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1D3E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMI, CEFE, CIP, IMI, MER, PIP, PIPE, TOB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D2A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eClostridium difficile\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, GENT, SIN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D2B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eShewanella frigidimanina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAZT, COLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus siniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, CLI, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella variicola\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMP, PIP, FOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBrukhalderia gladiali\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMP, FOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, CEFE, CEFO, CEFT, COLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2D3G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePrevotella heparinalytica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAZT, COLI, ERT, FOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D2A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRhizobium radiobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAZT, FOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eStaphylococcus capitis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCLIN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePaenibacillus sp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePichia accidentalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3D3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePaenibacillus agaridevorans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAMOX, AMP, CEFT, OXA, PEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN-MDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLegend: Amikacin (AMI); Amoxicillin (AMOX); Ampicillin (AMP); Aztreonam (AZT); Cefepime (CEFE); Ceftriaxone (CEFT); Ciprofloxacin (CIP); Clindamycin (CLIN); Colistin (COLI); Fosfomycin (FOS); Gentamicin (GEN); Imipenem (IMI); Meropenem (MER); Oxacillin (OXA); Penicillin (PEN); Piperacillin (PIP); Piperacillin/Tazobactam (PIPE); Synercid (Quinupristin/Dalfopristin) (SIN); Tobramycin (TOB); Trimethoprim-Sulfamethoxazole (TRO).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of the physicochemical analyses revealed that the bulk density of the samples ranged from 1.43 to 1.57 g/cm\u0026sup3;, falling within the acceptable range for agricultural soils. The particle density was consistent across samples, with a value of 2.62 g/cm\u0026sup3;, close to the typical value for mineral soils. These parameters indicate that the soils have good structure, with little compaction, favoring root penetration and water infiltration. Such characteristics are essential for soil health, as adequate bulk density and typical particle density ensure that the soil can support agricultural vegetation without significant issues of compaction or lack of porosity (Shaheb, Venkatesh, and Shearer, 2021).\u003c/p\u003e \u003cp\u003eThe particle size composition of the samples showed values consistent with particle diameter ranges, indicating that the soils are predominantly sandy. This type of soil can influence water and nutrient retention capacity, crucial aspects for agricultural production (Huang and Hartemink, 2020).\u003c/p\u003e \u003cp\u003eThe levels of available phosphorus (P) in the samples varied significantly. Sample 1 had a high phosphorus content (92 mg/dm\u0026sup3;), while samples 2 and 3 had values of 43 mg/dm\u0026sup3; and 29 mg/dm\u0026sup3;, respectively. All values are above the recommended minimum (\u0026ge;\u0026thinsp;20 mg/dm\u0026sup3;) for agricultural soils, indicating good phosphorus availability for plants. Phosphorus is essential for root development, promoting more robust roots that improve water and nutrient absorption. It is a vital component of ATP, the primary energy molecule in plant cells, indispensable for photosynthesis, respiration, and the synthesis of essential molecules. Additionally, phosphorus is crucial for DNA and RNA formation, necessary for cell replication and protein synthesis (Liu, 2021).\u003c/p\u003e \u003cp\u003eThe pH of the samples ranged from 6.90 to 7.40, indicating that the soils have slightly acidic to neutral conditions, suitable for most agricultural crops. Balanced pH is crucial because it influences the solubility of essential nutrients and the activity of beneficial soil microorganisms. Soils with very acidic (pH\u0026thinsp;\u0026lt;\u0026thinsp;5.5) or very alkaline (pH\u0026thinsp;\u0026gt;\u0026thinsp;7.0) conditions can lead to the unavailability of vital nutrients such as phosphorus, potassium, and micronutrients, negatively affecting plant growth and crop productivity (Yadav et al., 2020; Baritz et al., 2021).\u003c/p\u003e \u003cp\u003eThe calcium (Ca) levels in the samples ranged from 2.00 to 2.50 cmolc/dm\u0026sup3;, within the reference range. Magnesium (Mg) values ranged from 0.75 to 1.20 cmolc/dm\u0026sup3;, also within the reference range, while sodium (Na) levels in the samples were low, ranging from 0.02 to 0.06 cmolc/dm\u0026sup3;, well below the maximum limit, indicating no salinity problems in the soil. Potassium (K) levels ranged from 0.17 to 0.26 cmolc/dm\u0026sup3;, within the acceptable range according to Embrapa. None of the samples showed exchangeable aluminum (Al), with values of 0.00 cmolc/dm\u0026sup3;, indicating the absence of aluminum toxicity.\u003c/p\u003e \u003cp\u003eCalcium is vital for the formation and stability of cell walls and improves soil structure by promoting the aggregation of clay particles, enhancing aeration and water infiltration. Magnesium is a central component of the chlorophyll molecule, essential for photosynthesis and the activation of various enzymes involved in plant metabolism. Potassium is crucial for the osmotic regulation of plants, influencing processes such as stomatal opening and closing and protein synthesis. Magnesium, as part of the chlorophyll molecule, is indispensable for photosynthesis and enzyme activation in plant metabolism (Havlin, 2020).\u003c/p\u003e \u003cp\u003eLow sodium levels indicate no risk of soil salinity, which is important as high sodium levels can lead to clay particle dispersion, resulting in compacted and poorly structured soils that hinder water infiltration and root growth (Li and Kang, 2020). The absence of exchangeable aluminum in the samples is beneficial since high aluminum levels can be toxic to plants, inhibiting root growth and nutrient absorption (Shetty et al., 2021).\u003c/p\u003e \u003cp\u003eWhile the physicochemical results of the soil samples analyzed do not directly indicate the effects of glyphosate, the presence of this herbicide can influence nutrient availability and soil health in the long term. Glyphosate is known to bind to cations such as calcium and magnesium, forming complexes that can reduce the availability of these nutrients to plants (Bortolheiro and Silva, 2021). The low sodium concentration and absence of aluminum are positive signs, but the continuous use of glyphosate may eventually alter nutrient dynamics and overall soil health (Ortiz et al., 2022). Therefore, while the current results do not show evident adverse effects of glyphosate, continuous monitoring and careful management of this herbicide use are recommended to prevent potential long-term negative impacts.\u003c/p\u003e \u003cp\u003eIn the microbiological analysis, the genus \u003cem\u003eBacillus\u003c/em\u003e was the most prevalent, found at various collection points, with Bacillus cereus being the most frequent species, present at eight distinct points. The prevalence of this bacterium is consistent with the literature, as it is commonly found in various environments, including agricultural soils, due to its ability to form resistant spores and survive adverse environmental conditions such as high temperatures, UV radiation, dehydration, and exposure to chemical disinfectants. This resistance allows spores to remain viable in the soil, even after rigorous agricultural practices such as crop rotation and pesticide use (Algammal et al., 2024; Jessberger et al., 2020; Liu et al., 2020).\u003c/p\u003e \u003cp\u003eGram-negative bacteria identified, such as \u003cem\u003eEnterobacter cloacae, Stenotrophomonas maltophilia, Pseudomonas nitroreducens, Shewanella frigidimarina, Klebsiella variicola, Burkholderia gladioli, Prevotella heparinolytica\u003c/em\u003e, and \u003cem\u003eRhizobium radiobacter\u003c/em\u003e, play various roles in the soil ecosystem. \u003cem\u003eEnterobacter cloacae\u003c/em\u003e, for example, can be an opportunistic pathogen while aiding in the decomposition of organic matter and nutrient cycling, although its presence may indicate fecal contamination (Wang et al., 2023; Ji et al., 2020). \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e is known to promote plant growth through the production of auxins and siderophores and antifungal activities (Hu et al., 2021; Ghosh, Chatterjee, and Mandal, 2020). \u003cem\u003ePseudomonas nitroreducens\u003c/em\u003e contributes to the degradation of organic pollutants and plant growth through bioactive compounds (Jayaraj et al., 2023).\u003c/p\u003e \u003cp\u003e \u003cem\u003ePrevotella heparinolytica\u003c/em\u003e is commonly found in the gastrointestinal tract of humans and animals, and its presence in the soil may indicate fecal contamination (Wongkiew et al., 2022). \u003cem\u003eRhizobium radiobacter\u003c/em\u003e is known for its ability to form nodules on legume roots, fixing nitrogen and promoting plant growth (Atuchin et al., 2023). The bacterial diversity in agricultural soil reflects the complexity of microbial interactions and the influence of management practices such as fertilizer and pesticide use. The presence of these bacteria indicates a rich ecological dynamic, where some species promote soil and plant health, while others may pose contamination risks.\u003c/p\u003e \u003cp\u003eThe presence of glyphosate in managed agricultural soil may correlate with increased bacterial resistance to antibiotics. Studies suggest that glyphosate, a widely used herbicide, can exert selective pressure on microbial communities, favoring the proliferation of resistant strains (Kepler et al., 2020; Nielsen et al., 2018). Glyphosate can alter soil microbiota, promoting changes in bacterial composition and increasing antibiotic resistance in bacteria that share resistance mechanisms to both compounds (Talahmeh, Abu-Rumeileh, and Al-Razem, 2020).\u003c/p\u003e \u003cp\u003eExposure to glyphosate has been associated with the induction of cross-resistance in soil bacteria. This occurs because glyphosate can induce mutations or activate defense mechanisms in bacteria, such as efflux pumps, which also confer antibiotic resistance (Raoult et al., 2021). The presence of multidrug-resistant \u003cem\u003eStenotrophomonas maltophilia\u003c/em\u003e at several points suggests that this microorganism may be particularly adapted to glyphosate-contaminated environments, showing a high capacity to survive and proliferate under selective pressure (Ospino and Spira, 2023).\u003c/p\u003e \u003cp\u003eAccording to the study by Costa et al. (2022), several bacteria exhibiting resistance to both antibiotics and glyphosate were identified. Among these bacteria, those with multidrug efflux pumps were effective against both agents. The study demonstrated that glyphosate exposure increases the prevalence of antibiotic resistance genes (ARGs) and mobile genetic elements, enriching the presence of these elements in soil and aquatic microbiomes. Bacteria identified as resistant to antibiotics and glyphosate include Stenotrophomonas maltophilia, which showed high resistance to multiple antibiotic classes, including aminoglycosides and cephalosporins, found at points P1D3C, P1D3E, and P2D3F in this study. Klebsiella variicola exhibited resistance to antibiotics such as ampicillin and piperacillin at point P2D3C, and Staphylococcus siniae showed resistance to various antibiotic classes, including penicillins and cephalosporins, found at point P2D3B.\u003c/p\u003e \u003cp\u003eMoreover, the impact of glyphosate on bacterial resistance is not limited to a direct increase in resistance. The alteration of soil microbiota can lead to changes in the dynamics of gene transfer resistance among bacteria. Mechanisms such as conjugation, transformation, and transduction can be facilitated in environments where glyphosate is present, increasing the spread of resistance genes among different bacterial species. This effect is particularly concerning in agricultural environments, where resistance transfer can occur rapidly due to high bacterial density and constant soil disturbance (Liao et al., 2021).\u003c/p\u003e \u003cp\u003eDespite the resistance profile of some bacteria, non-multidrug-resistant (N-MDR) bacterial isolates were also identified in the managed agricultural soil. Among these bacteria, Bacillus cereus was found at several points and, although not multidrug-resistant, is known for its ability to form spores and cause food poisoning. Bacillus megaterium, resistant only to clindamycin, is beneficial to the soil, helping to solubilize phosphates. Pseudomonas nitroreducens, resistant only to colistin, plays a role in the degradation of organic pollutants. Clostridium difficile and \u003cem\u003eShewanella frigidimarina\u003c/em\u003e participate in organic matter decomposition and bioremediation, respectively. These bacteria, although not multidrug-resistant, play crucial roles in the agricultural soil ecosystem, contributing to nutrient cycling, organic matter decomposition, and plant growth promotion (Raoult et al., 2021).\u003c/p\u003e \u003cp\u003eBacterial diversity in agricultural soil reflects the complexity of microbial interactions and the influence of management practices such as fertilizer and pesticide use. The presence of these bacteria indicates a rich ecological dynamic, where some species promote soil and plant health, while others may pose contamination risks. Adequate agricultural practices are essential to maintain microbial balance, favoring beneficial species that contribute to soil fertility and plant health. The interaction between microorganisms, plants, and agricultural practices underscores the importance of continuous monitoring and sustainable management strategies to ensure agricultural productivity and food security (Kelbrick, Hesse, and O'Brien, 2023).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presented an analysis of the impacts of glyphosate use in the Icó-Mandantes and Apolônio Sales irrigation projects located in Petrolândia, Pernambuco, indicating that glyphosate, while effective in weed control and promoting agricultural productivity, has significant effects on soil quality and bacterial resistance.\u003c/p\u003e\n\u003cp\u003eThe physicochemical analyses of the soil showed that although the samples were within the acceptable parameters for agricultural soils, the continuous use of glyphosate might alter the availability of essential nutrients and soil structure in the long term. The microbiological evaluation revealed a significant diversity of bacteria, predominantly of the genus Bacillus, and the presence of multidrug-resistant bacteria, particularly observed in species such as Stenotrophomonas maltophilia, Bacillus cereus, and Enterobacter cloacae.\u003c/p\u003e\n\u003cp\u003eThus, the present analysis highlights glyphosate's potential to promote bacterial resistance, which may pose a risk to both agriculture and public health in areas treated with glyphosate. These findings reinforce the need for more sustainable agricultural practices and continuous monitoring of glyphosate's effects on the soil. Additionally, the implementation of integrated pest management strategies that reduce dependence on chemical herbicides is essential to preserve soil health and prevent the proliferation of resistant bacteria.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study participants gave their informed consent to participate in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study authors and participants gave their consent for the publication of the results of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the conception and design of the study. The preparation of the material and data collection were carried out by Karolayne Silva Souza, Milena Roberta Freire da Silva, Manoella Almeida Candido and Gabriela de Lima Torres. Soil physicochemical analysis was conducted by Kaline Catiely Campos Silva, Ricardo Marques Nogueira Filho and Fabricio Motteran. The microbiological evaluation was performed by Kátia Cilene da Silva Felix, Lívia Caroline Alexandre de Araújo. Data analysis was carried out by Milena Danda Vasconcelos Santos and Maria Betânia Melo de Oliveira. The critical review of the manuscript was conducted by all authors. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by Coordination for the Improvement of Higher Education Personnel (CAPES/Brazil—Proc. no 88887.500819/2020-00).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlgammal, A. M., Eid, H. M., Alghamdi, S., Ghabban, H., Alatawy, R., Almanzalawi, E. A., ... \u0026amp; El-Tarabili, R. M. (2024). 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Glyphosate Disorders Soil Enchytraeid Gut Microbiota and Increases Its Antibiotic Resistance Risk. \u003cem\u003eJournal of Agricultural and Food Chemistry\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(4), 2089-2099.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microorganisms, Soil Microbiota, Pesticides, Agriculture","lastPublishedDoi":"10.21203/rs.3.rs-5969006/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5969006/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study evaluates bacterial resistance and soil quality parameters in agricultural irrigation areas using glyphosate, focusing on the Ic\u0026oacute;-Mandantes and Apol\u0026ocirc;nio Sales projects in Petrol\u0026acirc;ndia, Pernambuco. The research investigated the physicochemical characteristics of the soil, such as density, particle size composition, pH, and nutrient levels (P, Ca, Mg, Na, K, Al). Soil samples were collected and analyzed to identify the presence of antibiotic-resistant bacteria. The results show that, although the physicochemical parameters are within acceptable standards, there is a significant presence of resistant bacteria, especially Stenotrophomonas maltophilia, Bacillus cereus, and Enterobacter cloacae. The predominance of multi-resistant bacteria suggests that the continuous use of glyphosate may promote bacterial resistance, posing a risk to public health and agricultural sustainability. Therefore, the study highlights the need for more sustainable agricultural practices and continuous monitoring of glyphosate's effects on soil.\u003c/p\u003e","manuscriptTitle":"Assessment of Bacterial Resistance and Soil Quality Parameters in Glyphosate-Treated Agricultural Irrigation Areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-10 17:09:55","doi":"10.21203/rs.3.rs-5969006/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f58f0a5-dfb8-4c57-be1e-0aec2aa5e7a0","owner":[],"postedDate":"February 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-26T04:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-10 17:09:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5969006","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5969006","identity":"rs-5969006","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}