AAVS_13_10_2331-2344

Introduction

Livestock farming is a fundamental pillar of economic and food security for millions of families in tropical regions of Asia, Africa and Latin America. It is particularly important in Ecuador, where the dairy industry accounts for around 4% of agri-food GDP and provides direct employment for over a million people (Medina et al., 2024; Moreno et al., 2023; Segovia, 2023). In view of the advance of the agricultural frontier, experts such as Parra et al. (2019) have pointed out the urgent need to adopt sustainable approaches that boost productivity without compromising ecological stability or the living conditions of small producers.

Milk is an essential food in the human diet due to its water-soluble vitamin content, especially B vitamins, which makes it a key nutritional resource globally (Ionita, 2022). In this context, tropical grazing-based production systems are emerging as a sustainable and efficient alternative for Latin America, optimising the use of natural resources and contributing to animal welfare (López-Vigoa et al., 2017; Pezo, 2019). Milk productivity is conditioned by multiple physiological and management factors, such as the age of the animal, the number of lactations, the quality of the diet and the general health status, all of which directly affect the quantity and quality of the final product (Patiño-Burbano et al., 2023; DANE, 2013).

First-calf heifers produce less milk, reaching their peak capacity during their second and third calving. From then on, production decreases by approximately 5% with each cycle. In addition, climatic conditions affect milk yield; in tropical and subtropical areas, production is higher during the rainy season, while in colder climates it decreases during winter (Muñoz et al., 2022).

Antimicrobial resistance (AMR) is a growing threat to public and animal health, especially in dairy production systems, where milk acts as a vehicle for the transmission of resistant microorganisms (WHO, 2021; Espinosa Castaño et al., 2019). Bovine mastitis, one of the most prevalent diseases in dairy cattle, is frequently caused by bacteria of the genus Staphylococcus spp., including S. aureus and is usually treated with β-lactam antibiotics, macrolides and aminoglycosides (Pellegrino et al., 2011; García Alarcón et al., 2025). However, the indiscriminate therapeutic and prophylactic use of these drugs has favoured the selection of multi-resistant strains, making treatment difficult and increasing the risk of antimicrobial residues in milk (Walsh, 2018; Rahman et al., 2021).

In Ecuador, recent studies have shown the presence of methicillin-resistant Staphylococcus aureus (MRSA) in raw milk samples, as well as multidrug-resistant strains in cattle with subclinical mastitis (Escobar et al., 2022). In addition, the country has a National Plan for the Prevention and Control of AMR, led by the National Institute for Public Health Research (INSPI), which has implemented surveillance in sentinel hospitals and regional laboratories to monitor resistance genes such as blaCTX-M, mecA and mcr-1 (INSPI, 2022; Ministry of Public Health (MPH), 2019).

In Peru, a worrying prevalence of subclinical mastitis in dairy cows has been revealed, reflected in high somatic cell counts that compromise milk quality and animal welfare (Alvarado et al., 2019). Most alarming is the advance of bacterial resistance: Strains of Staphylococcus spp., the main causative agents of this disease, have shown high levels of resistance to commonly used antibiotics such as amoxicillin and penicillin, reaching percentages of 92% and 96% in certain regions. This trend is not unique to Peru in Brazil, 100% resistance to penicillin has been documented in similar isolates, posing a serious health alert for the region (Dias et al., 2010).

The inappropriate use of antibiotics in livestock farming, especially without prior sensitivity testing, has led to the emergence of resistant bacteria such as Staphylococcus spp., affecting both animal and human health. This situation is exacerbated by diseases such as subclinical mastitis, which is difficult to detect but very common in dairy systems, causing economic losses on farms and compromising milk quality (García et al., 2025; Vayas, 2021). In Ecuador, recent studies reveal that the excessive use of antimicrobials and a lack of knowledge about preventive practices exacerbate this situation (Puga and Mendieta, 2025). It is therefore essential to implement control programmes that promote the responsible use of antibiotics, accompanied by training for farmers and operators to strengthen good milking practices and hygienic herd management (Patiño-Burbano et al., 2023; Agrocalidad, 2022).

This study on antimicrobial resistance in dairy farms highlights the urgent need to improve hygiene conditions through effective sanitary practices and to implement preventive strategies that reduce the systematic use of conventional antibiotics (Kaasch et al., 2024).

The main objective of the research was to evaluate the resistance profile of Staphylococcus spp. isolated from the milk of cows with subclinical mastitis, contributing to an understanding of the magnitude of the problem in dairy production systems. Furthermore, strengthening animal health is key to protecting public health, as antimicrobial residues and resistant strains in milk pose risks to consumers and food safety (Trombete and Souza, 2014; Walsh, 2018).

Materials and Methods

Location

The province of Guayas, located in the coastal region of Ecuador between parallels 0°06′ and 3°59′ south and meridians 78°42′ and 81°00′30″ west (Montaño, 2012), is characterised by its tropical savannah climate, estuarine ecosystems, mangroves and intense agricultural activity. It borders Manabí and Los Ríos to the north, Bolívar, Chimborazo, Cañar, Azuay and Los Ríos again to the east, El Oro and the Gulf of Guayaquil to the south, and Santa Elena, Manabí and the Pacific Ocean to the west (CELIR, 2019; MAGAP, 2016). In this context, the canton of Daule stands out as a key productive hub, with an area of 462.07 km² and approximate coordinates of 1°51′37″ S and 79°58′36″ W (Barzola, 2021). Recognised as the rice capital of the country, it also has significant livestock activity based on extensive systems with low technification, with an average production of 8 litres of milk per cow per day (Llanos, 2025; Vargas, 2018).

Climate

In the province of Guayas, where the climate sets the pace for productive, social and natural life. With average temperatures ranging between 26°C and 28°C, and highs that can reach 32.6 °C in the warmest months, this fertile land receives abundant rainfall between February and March, more than 280 mm per month, while August and September are much drier, with rainfall below 15 mm (GADPG, 2021). Relative humidity remains high, between 75% and 83%, and generous sunlight, which shines for 9 to 11 hours each day, favours crops and livestock farming throughout the region (Woozberley, 2020; Montero, 2022).

Characteristics of dairy farming

Regarding the racial composition of the cattle herd, crossbred animals predominate (Holstein x Brown Swiss x Bos indicus). These animals exhibit physiological adaptations to the warm, humid climate of the coastal region and are managed under extensive free-range grazing systems, complemented by strategic low-intensity nutritional supplementation (Cabezas et al., 2019; Yánez et al., 2021). These breeds have an average milk production of 6 to 8 litres per cow per day, although this yield varies according to nutritional, health and reproductive management (Almeida et al., 2025). Agroclimatic conditions such as temperature, humidity and high daily solar radiation favour the development of pastures and forage crops (Ortíz, 2025; Jarquín and Aguilar, 2025). These parameters allow for the maintenance of extensive and semi-intensive livestock systems, although they also pose challenges such as heat stress and water management (Cisneros et al., 2024).

During the first and second thirds of lactation (0–200 days postpartum), cows face a negative energy balance, as metabolic demand exceeds nutrient intake. During this period, peak production is reached between 45 and 60 days, followed by a persistence phase where production stabilises before beginning to decline (García-Roche, 2017; Ortega, 2022). Supplementation with concentrates, mineral salts and quality forage is key to sustaining performance and facilitating the recovery of body condition (Valle, 2024; Castaño and Pérez, 2017). Manual milking is the usual method in the area, carried out in open or semi-technified pens, with basic hygiene and management routines (Bonifaz and Requelme, 2011; Terán, 2012). The microbiological quality of milk can be compromised by the use of non-potable water and poor cleaning practices, which has been documented in studies conducted on manual milking systems in Ecuador (Contero and Cachipuendo, 2021).

Bioethical considerations

Milk samples for the study were collected in accordance with fundamental bioethical principles, particularly informed consent. Each participating producer was duly informed about the objectives of the study, the procedures involved and the use of the samples collected, and gave their voluntary authorization to participate (FDA, 2023). The samples were collected using non-invasive techniques that guarantee animal welfare and under hygienic conditions that preserve the microbiological quality of the milk, in accordance with good veterinary practices (FAO, 2017). This ethical approach reinforces the research team’s commitment to respecting the human and animal participants in the study (Díaz and García, 2024).

Sampling

For this study, milk samples were collected from 75 cows belonging to local production systems. Samples were taken from three representative farms in the Daule District, Guayas province: the “Huaconcito” farm (1°52′00″S 79°59′00″W), the “Don Vito” farm and the “Tres Hermanos” farm (both at 1°33′00″S 80°01′00″W), 25 milk samples from cows at each farm, for a total of 75. These samples were selected to undergo the California Mastitis Test (CMT) as a rapid diagnostic method for subclinical mastitis, a condition that affects the mammary gland without obvious clinical manifestations (Gómez et al., 2015). Samples were collected in the field using specific materials such as CMT test strips, EDTA-free tubes, gloves, boots, sanitary uniforms, and coolers to preserve the cold chain (Lituma, 2023).

California mastitis test (CMT)

Subclinical mastitis was detected using the CMT reagent, recognised for its effectiveness and speed in identifying changes in milk associated with mammary inflammation (Kiarie, 2024; McFadden, 2025). The CMT test was applied following protocols validated by Schalm and Noorlander (1957) and adapted by the National Mastitis Council (Kerro, 2020; Gómez-Quispe et al., 2015). Before applying the test, the udder was cleaned with iodine solution and dried with disposable paper, following recommended hygiene protocols to avoid cross-contamination (Proquimia, 2023). Then, two streams of milk were extracted from each mammary quarter and mixed with 2 ml of CMT reagent on the palette, stirring to facilitate interpretation of the result (Reyes and Argüello, 2015). Once the affected quadrant was identified, the milk sample was collected in a test tube, labelled and refrigerated until analysis at the Microbiology Laboratory of the Faculty of Veterinary Medicine of the University of Guayaquil for microbiological analysis, following recommendations to ensure the viability of the pathogens present (Jurado et al., 2021; Zubieta and Quiroga, 2022; Sánchez et al., 2019).

Preparation of culture media (Blood Agar)

Blood agar was prepared under aseptic conditions to promote the growth of microorganisms and detect haemolysis, which is useful in the isolation of Staphylococcus spp. (Microbe Notes, 2022; Acharya, 2023). Following the manufacturer’s recommendations, 40 g of blood agar base was dissolved in 1000 ml of distilled water and sterilised in an autoclave at 121 °C for 15 minutes. When the medium reached 45-50 °C, 5-10% human blood was added to the mixture, mixed well, avoiding the formation of bubbles, and poured into Petri dishes under direct flame to avoid contamination. It was left to solidify for 40 minutes and then refrigerated until further use (Universidad Continenta, 2023; UNAM, 2019).

Pre-enrichment procedure for samples

Before being seeded in blood agar, milk samples underwent a pre-enrichment process in Tryptic Soy Broth (TSB) medium supplemented with 7.5% NaCl and 1% sodium pyruvate, designed to promote the slightly selective growth of halotolerant bacteria and increase their concentration to detectable levels, in a 1:10 ratio. This step is essential to improve the sensitivity of the culture, as it allows the recovery of stressed or low-abundance cells of Staphylococcus aureus and coagulase-negative Staphylococcus (CoNS) (Thurmond et al., 1989; Ding et al., 2017). Pre-enrichment significantly increases the recovery of pathogens such as Staphylococcus aureus in raw milk samples, thus optimising the effectiveness of conventional microbiological methods (Romero, 2020; Castañeda et al., 2025).

Sample inoculation on blood agar

Two millilitres of the pre-enriched culture were transferred to Petri dishes containing blood agar using a 1000-microlitre pipette under aseptic conditions to prevent cross-contamination, following recommendations for safe handling in microbiology (Microbe Online, 2023; WHO, 2021). After plating, the samples were left to dry for 5 to 6 hours at room temperature, which promotes sample adhesion to the medium without interfering with the diffusion of haemolysins (Aryal, 2022). The plates were then divided into quadrants with a previously disinfected inoculation loop between each sample, ensuring traceability and avoiding interference between cultures (ASM, 2016). The plates were labelled and placed in an incubator at 37°C for 24 hours, the optimum temperature for the growth of mesophilic bacteria such as Streptococcus spp. and Staphylococcus aureus (ATCC, 2025; UNAM, 2025). Samples that showed growth with β-haemolysis were subjected to Gram staining for morphological characterisation and classification according to their cell wall, following standard protocols for bacterial identification (Microbe Notes, 2022; Aryal, 2022).

Gram staining and catalase test

After 24 hours of incubation at 37°C, haemolysis was examined on blood agar plates, observing transparent halos around some colonies, characteristic of β-haemolysis, associated with bacteria such as Streptococcus pyogenes and Staphylococcus aureus (Microbe Notes, 2022). Gram staining was used to characterise the microscopic morphology (Monteagudo et al., 2021; Acharya, 2023). The catalase test was used to confirm the presence of Staphylococcus spp. and differentiate it from Streptococcus spp., as both are Gram-positive bacteria but differ in their enzymatic activity. A drop of hydrogen peroxide (3% H₂O₂) was placed on an isolated colony on a microscope slide, and immediate bubble formation was observed, indicating a positive reaction due to the presence of the catalase enzyme, characteristic of Staphylococcus spp. (Hardy Diagnostics, 2024; Microbe Online, 2022).

Preparation of mueller-hilton agar

Mueller-Hinton agar was prepared following standardised protocols to ensure its effectiveness in antimicrobial susceptibility testing. Thirty-eight grams of the dehydrated medium were weighed and dissolved in 1,000 ml of distilled water, heating to boiling point to ensure complete dissolution (Microbe Online, 2022). The mixture was then autoclaved at 121 °C for 15 minutes, in accordance with CLSI and FDA recommendations for culture media (Vásquez et al., 2023; Thermo Fisher Scientific, 2024). Once cooled to room temperature, the medium was poured into sterile Petri dishes under aseptic conditions, using a direct flame as a barrier against contaminants (Sanders, 2012). The plates were allowed to solidify for 20 minutes and placed upside down to prevent condensation from forming on the surface of the agar, which could interfere with the distribution of microorganisms and affect the interpretation of the results (Sanders, 2012; Aryal, 2022).

Antibiogram

The samples were seeded in a sterile work area using Petri dishes previously prepared with Mueller-Hinton agar, the medium recommended by the CLSI for antimicrobial susceptibility testing by the disc diffusion method (Mueller and Hinton, 1941; Bauer et al., 1966). One hundred microlitres of a bacterial solution dissolved in 0.85% sterile saline solution, adjusted to standard turbidity (0.5 McFarland), were inoculated into each plate, ensuring homogeneous distribution using a sterile swab extension technique (CLSI, 2020). The antibiogram was tested with antibiotic disks of gentamicin (10 µg), tetracycline (30 µg), penicillin (10 units), cephalexin (30 µg), amoxicillin + clavulanic acid (20/10 µg), which were placed equidistantly on the surface of the agar, respecting a minimum distance of 24 mm between them and 15 mm from the edge, according to the Kirby-Bauer protocol (Hudzicki, 2009). The plates were labelled and grouped in batches of six units for traceability and incubated at 37°C for 18 hours in an inverted position, optimal conditions for bacterial growth and the formation of inhibition zones (Thermo Fisher Scientific, 2024; Microbe Notes, 2022).

Reading the inhibition halos

The antibiogram was interpreted using the disc diffusion method (Kirby-Bauer), a technique standardised by the World Health Organisation and the Clinical and Laboratory Standards Institute (Rapoport, 2021; Hudzicki, 2009) to assess antimicrobial sensitivity. Staphylococcus spp. strains were classified as sensitive (S), intermediate (I) or resistant (R) by comparing the diameters of the inhibition halos with the breakpoints established by the CLSI (2020). A zone diameter of ≥15 mm was considered sensitive for gentamicin, ≥19 mm for tetracycline, ≥29 mm for penicillin, and ≥20 mm for amoxicillin with clavulanic acid. For cephalexin, CLSI and EUCAST have not established breakpoints. These values are essential for guiding antimicrobial treatment, as noted by Baroja et al. (2021), and should be updated regularly due to the evolution of resistance, according to Buldain et al. (2023). In addition, the use of media such as Mueller-Hinton agar and the standardisation of the inoculum (0.5 McFarland) are essential requirements to ensure the reproducibility and reliability of the results (Mueller and Hinton, 1941; Sader et al., 2024).

Data analysis

The data were organised in long format, considering, for each antibiotic evaluated, the number of isolates classified according to sensitivity criteria: sensitive (S), intermediate (I) or resistant (R). Absolute and relative frequencies were calculated and visually represented using stacked bar charts to describe the phenotypic profile of antimicrobial susceptibility. To evaluate statistical differences in the distribution of susceptibility categories among different antibiotics, Pearson’s chi-square test was applied to a contingency matrix (antibiotic × classification) (Agresti, 2018). Additionally, the Multi-Resistance Index (MAR) was calculated for each antibiotic, defined as the ratio between the number of resistant isolates and the total number of tests performed. A reference value of 0.2 was considered a critical threshold for identifying antibiotics associated with high antimicrobial pressure, as proposed by Krumperman (1983). Finally, a hierarchical clustering analysis was applied using Euclidean distances and Ward’s linkage method to identify clusters of antibiotics based on the similarity of their sensitivity profiles (Murtagh and Legendre, 2014). All analyses were performed in R software (version 4.3.2) using the tidyverse, ggplot2, dendextend, and readxl packages.

Calculation of the multiple antibiotic resistance index (MAR)

To evaluate antimicrobial pressure in bacterial isolates, the Multiple Antibiotic Resistance Index (MAR) was calculated using the following formula:

MAR=a/b

Where a corresponds to the number of antibiotics to which an isolate was resistant and b to the total number of antibiotics evaluated for that isolate. This index was calculated for each antibiotic considering the proportion of resistant isolates among the total number of strains analysed. A MAR index ≥ 0.2 was considered a critical threshold value, suggesting exposure to environments with high or indiscriminate use of antimicrobials (Krumperman, 1983).

Results and Discussion

Figure 2 shows the percentage distribution of bacterial isolates against five antibiotics, classified into three categories according to their sensitivity profile: Sensitive (S), Intermediate (I) and Resistant (R). A worrying pattern of high resistance was observed in several compounds, notably amoxicillin + clavulanic acid, penicillin and tetracycline, all with resistance rates above 40%. In the specific case of amoxicillin + clavulanic acid, more than 50% of the isolates were classified as resistant, while tetracycline showed a more distributed pattern, with similar proportions among the three categories. gentamicin was the only antibiotic with a predominance of the sensitive phenotype (approximately 44% of isolates), although it also presented intermediate and resistant levels, suggesting still acceptable efficacy but with signs of possible selective pressure. Amoxicillin and cephalexin were excluded from the graphical analysis due to the absence of clinical breakpoints established by CLSI/EUCAST for Staphylococcus spp. isolated from bovine milk, which prevents standardized interpretation and comparison with other international studies. In the case of cephalexin, although 94% resistance was observed (47 of 50 isolates), the results presented inconsistent inhibition zones and low reproducibility, which limits its analytical validity as a comparison parameter. Additionally, amoxicillin alone was tested and subsequently discarded, while amoxicillin-clavulanic acid was included, given that it has official interpretive criteria and more clinically stable results. This differentiation helps avoid confusion between the efficacy of the antibiotic as monotherapy and that of its combination with a β-lactamase inhibitor, ensuring greater precision in the interpretation of resistance profiles. A Chi-square test was applied to evaluate the association between the type of antibiotic and the sensitivity classification (S, I, R). The results showed a statistically significant association between these variables (χ² = 645.24; p < 0.001), indicating that the sensitivity profile differs significantly depending on the antibiotic evaluated. This finding reflects that resistance is not distributed evenly among antimicrobials, and that certain compounds, such as beta-lactams, have critical levels of resistance. This situation could be associated with frequent or inappropriate use in veterinary clinical practice in the study region.

The results show a worrying prevalence of antimicrobial resistance in Staphylococcus spp. especially against β-lactam antibiotics such as penicillin and amoxicillin + clavulanic acid. This pattern coincides with that reported by Castro et al. (2018), who documented that 47.5% of S. aureus isolates in Cartagena were resistant to methicillin, while S. epidermidis reached a resistance rate of 68.7%. From a molecular point of view, it has been described that S. aureus can acquire resistance through three main mechanisms: production of β-lactamases, modification of penicillin-binding proteins (PBPs), and the presence of the mecA gene, responsible for methicillin resistance. These mechanisms allow the bacteria to evade the action of β-lactam antibiotics, even those combined with β-lactamase inhibitors, such as clavulanic acid. The coexistence of multiple mechanisms in the same strain aggravates the clinical problem and hinders empirical treatment (Castellano and Perozo, 2010).

In contrast, gentamicin showed a more favourable profile in this study, with a higher proportion of sensitive strains. However, recent research in Venezuela reveals that up to 61.7% of coagulase-negative Staphylococcus strains carry gentamicin resistance genes (aac(6’)/aph(2’’), suggesting a latent threat to its future efficacy. Therefore, although gentamicin is still useful, its use should be strategic and supported by sensitivity testing (Castellanos et al., 2016). Similar studies in Colombia also reported the presence of these genes in more than 87% of S. epidermidis strains isolated in neonatal units, reinforcing concerns about their regional spread (Pinilla et al., 2009).

The results obtained in this research reveal high resistance of Staphylococcus spp. to β-lactam antibiotics, while tetracycline showed a more distributed pattern between sensitivity, intermediate resistance, and total resistance. This behaviour is partially in line with regional studies, but also presents significant contrasts with international research. Similarly, the multicentre study conducted in Colombia by De La Cadena et al. (2023) showed that, between 2018 and 2021, the resistance profiles of the 10 most frequent microorganisms remained relatively stable, except in the case of Pseudomonas aeruginosa, which showed a significant increase in resistance to piperacillin-tazobactam and carbapenems. In contrast, our research shows a more marked trend towards resistance in Staphylococcus spp., which could be due to differences in the use of antimicrobials in veterinary versus hospital settings.

On the other hand, Giono et al. (2020) identified a high prevalence of ESKAPE bacteria, including methicillin-resistant Staphylococcus aureus (MRSA), in Mexican hospitals, reinforcing the relevance of our results by demonstrating the persistence of resistant strains in clinical and veterinary settings. However, the more balanced pattern observed for tetracycline in our sample suggests that there are still opportunities to preserve its efficacy through rational use policies.

These findings reflect the selective pressure exerted by the frequent use of antibiotics in dairy production, especially in the treatment of bovine mastitis, one of the main causes of therapeutic intervention in dairy cattle (Chávez et al., 2025). From an epidemiological perspective, the MAR detected in bovine milk represents not only a risk to animal health, but also a threat to public health, as it facilitates the transfer of resistance genes through the food chain. López et al. (2022) highlight that the indiscriminate use of antibiotics in production systems has favoured the selection of resistant strains, increasing veterinary costs, loss of productivity and the burden on human health systems. In this context, it is imperative to strengthen microbiological surveillance programmes in the agricultural sector, implement rational prescription policies in veterinary medicine and encourage research into new antimicrobial agents. The dissemination of local sensitivity profiles, as recommended by Achong-Sánchez et al. (2024), allows for the optimisation of empirical treatment, reduces selective pressure on existing antibiotics, and prevents the spread of resistance through animal products.

In addition, the COVID-19 pandemic exacerbated the irrational use of antimicrobials in human medicine, especially in the empirical treatment of viral respiratory infections, accelerating the spread of resistant strains in hospital and agricultural settings without updated microbiological maps (PAHO, 2021). Zumbado et al. (2022) point out that the lack of standardised protocols during the health emergency contributed to increased resistance, especially in intensive care units and high-density animal production systems. Overall, the findings of this study are in line with the international literature, highlighting the urgency of adopting policies for the rational use of antimicrobials, strengthening microbiological surveillance systems, and promoting translational research to anticipate and mitigate the advance of resistance (WHO, 2021; PAHO, 2021).

Analysis of the multiple antibiotic resistance (MAR) index revealed high values for all antibiotics evaluated. MAR values ranged from 0.607 for gentamicin to 0.679 for penicillin, well above the critical threshold of 0.2, represented in Figure 3 by a red dotted line. This threshold indicates frequent exposure to antibiotics in the bacterial source, associated with environments where antimicrobial use is intensive or unregulated. It can also be observed that amoxicillin + clavulanic acid, tetracycline, penicillin, and gentamicin have MAR indices above 0.6, implying high selective pressure and the possible presence of acquired resistance mechanisms. In particular, penicillin was the antibiotic with the highest MAR (0.679), followed by tetracycline (0.667).

The high level of multidrug resistance (MDR) to penicillin and tetracycline is probably due to prolonged exposure in dairy production systems, where these antibiotics have been used for both therapeutic and prophylactic purposes. Recent studies have shown that routine use of tetracycline in cattle is associated with the persistence of resistance genes such as tetM and tetO, which can be transferred horizontally to other bacteria in the animal and human microbiome (Martínez et al., 2023; Vásquez et al., 2023).

Similarly, amoxicillin + clavulanic acid also showed a considerably high MAR (0.667), indicating its frequent use in the treatment of mammary infections and other pathologies in cattle. Although this combination seeks to counteract the action of β-lactamases, its repeated use can induce the emergence of extended-spectrum β-lactamases (ESBLs), as has been described in strains of Klebsiella pneumoniae and Escherichia coli isolated from dairy products (Singh et al., 2022; Ranjbar et al., 2020).

These high levels of MAR in bacteria from bovine milk pose a direct threat to public health, as raw milk can act as a vehicle for the transmission of resistance genes through the food chain. The FAO and OIE have warned that the use of antibiotics in animal production is one of the main factors contributing to the global spread of antimicrobial resistance (FAO, 2017; OIE, 2022). If control measures are not implemented, it is estimated that by 2050 MAR could exceed cancer in terms of mortality, with a devastating economic impact (Irfan et al., 2022). This behaviour is in line with recent evidence on the evolution of antimicrobial resistance, considered one of the main threats to global public health. According to Achong et al. (2024), a growing prevalence of multidrug-resistant (MDR), extremely drug-resistant (XDR) and pan-drug-resistant (PDR) bacteria has been observed in high-complexity hospitals in Latin America, especially in critical areas such as intensive care units.

Figure 4 shows the hierarchical cluster analysis based on Euclidean distance applied to sensitivity, resistance, and intermediation profiles of bacterial isolates from animals, allowing the identification of relevant therapeutic patterns in veterinary medicine. This statistical tool facilitates the grouping of antibiotics according to their behaviour against pathogens of clinical interest, which is essential for optimising treatment protocols and reducing antimicrobial pressure in veterinary settings (Sokal and Sneath, 1963). The proximity observed between amoxicillin + clavulanic acid and penicillin reflects their belonging to the beta-lactam family, widely used in veterinary medicine to treat respiratory, urinary and skin infections in species such as dogs, cats and cattle (Prescott, 2013). However, the resistance observed suggests the presence of beta-lactamases, enzymes that inactivate these antibiotics, a phenomenon widely reported in zoonotic bacteria such as Escherichia coli, Klebsiella spp. and Staphylococcus spp. isolated from domestic animals (Bradford et al., 2022; Correa et al., 2021).

Although clavulanic acid acts as an inhibitor of these enzymes, its efficacy may be compromised against extended-spectrum beta-lactamases (ESBLs), especially in environments where the indiscriminate use of antimicrobials has favoured the selection of resistant strains (Jiménez, 2021). In contrast, the independent grouping of tetracycline and gentamicin indicates marked differences in sensitivity profiles, attributable to their mechanisms of action on protein synthesis in the 30S subunit of the ribosome. These antibiotics are used in veterinary medicine to treat systemic and localised infections in production and companion animals, although their use has been regulated due to the emergence of resistance and food safety considerations (Mercer, 2022; Jara, 2024). Resistance to tetracyclines, for example, is one of the most common in the veterinary field and has been associated with the presence of tet genes in plasmids and transposons, which facilitates their horizontal spread among bacteria (Jara, 2024).

This type of analysis is particularly useful in veterinary medicine to identify therapeutic redundancies, highlight relationships between resistance profiles, and inform strategies for rotating or replacing antimicrobials. Rational antibiotic rotation in animals not only improves therapeutic efficacy but also contributes to reducing selective pressure and controlling antimicrobial resistance, a growing concern in veterinary and human public health (WHO, 2021; Laxminarayan et al., 2024). In addition, constant monitoring of the behaviour of strains against antibiotics commonly used in animals allows for the anticipation of emerging trends and the adjustment of therapeutic guidelines according to local epidemiology, which is key to preventing the spread of multi-resistant strains with zoonotic potential (CDC, 2022; Muñoz, 2022).

Conclusions and Recommendations

The high prevalence of antimicrobial resistance observed in Staphylococcus spp. isolated from bovine milk, particularly against β-lactams and tetracyclines, indicates sustained antimicrobial pressure in animal production systems. The critical values of the MAR index and the statistically significant association between the type of antibiotic and the sensitivity profile confirm intensive and possibly unregulated therapeutic use in veterinary medicine.

These findings reinforce the need to consolidate microbiological surveillance systems based on local susceptibility, optimise veterinary prescribing using pharmacodynamic and pharmacokinetic criteria, and adopt integrated strategies under the one health approach. This multidisciplinary approach allows antimicrobial resistance to be addressed as an interconnected phenomenon between animal, human and environmental health, promoting coordinated interventions to preserve therapeutic efficacy and contain the spread of resistance in clinical and agricultural systems.

Acknowledgement

We thank the dairy producers of Daule canton (Guayas, Ecuador) for facilitating access to their herds and collaborating during sampling; the Faculty of Veterinary Medicine, University of Guayaquil, for technical support; the Wildlife, Conservation, and Global Health Research Group at Universidad Regional Amazónica Ikiam for methodological guidance, scientific coordination, and microbiology laboratory support; and the Latin American Center for Dairy Studies and Issues (CLEPL) and the National University of Rosario, Argentina, for their contributions to statistical validation. This work was conducted with informed consent from producers and under good veterinary practices.

Novelty Statement

This study provides original evidence for Ecuador by (i) characterizing sensitivity phenotypes of Staphylococcus spp. isolated from bovine milk with subclinical mastitis in extensive coastal systems, (ii) quantifying antimicrobial pressure using the MAR index (with values consistently ≥ 0.6), and (iii) identifying therapeutic clusters by dendrogram (β-lactams vs. aminoglycosides/tetracyclines) that reveal functional redundancies and guide antibiotic rotation. The integration of on-farm CMT, Kirby–Bauer antibiograms with CLSI breakpoints, and multivariate analyses (χ² and Ward clustering) establishes an operational framework for local surveillance with direct implications for One Health strategies and rational antimicrobial prescribing in veterinary medicine.

Author’s Contribution

IG-P: Contributed to the design of the study and literature review.

MV-L: Participated in data tabulation and style correction.

VC-V: Carried out the fieldwork and experimental analysis.

JDT-M: Collaborated in the methodological design and statistical processing.

MR-B: Contributed to the logistics and laboratory analysis.

DY-A: Corresponding author, was responsible for overall coordination, scientific supervision and final editing.

PM: Developed the advanced statistical validation and review.

Generative AI and AI-assisted technology statement

Generative AI tools were used exclusively for editorial purposes (suggestions on clarity, grammar, and APA 7 reference formatting). No scientific text, dataset, result, figure, table, or statistical analysis was generated by AI. All data processing, χ² calculations, MAR index estimation, and cluster analyses were performed in R (v4.3.2) and verified by the authors. AI outputs were critically reviewed and, where appropriate, adjusted by the team prior to inclusion. No AI models were used to design experiments, create scientific images, or interpret results.

Conflict of interest

The authors have declared no conflict of interest.

References

Acharya T (2023). Gram staining: Principle, procedure, interpretation and errors. https://microbiologyinfo.com/gram-staining-principle-procedure-interpretation-examples-and-animation/

Achong-Sánchez J, Lazo-Paredes R, Amado-Tineo J (2024). Perfil microbiológico de sensibilidad y resistencia antimicrobiana en un hospital general de la selva peruana 2021. Rev. Fac. Med. Hum., 24(4): 35–42. https://doi.org/10.25176/RFMH.v24i4.5669

Almeida FME, Bonilla ESE, Rivera RRR, Ayala FWA, Martínez RCC, Guzmán PJV, Martínez VKL (2025). Promedio de producción lechera bovina basado en su alimentación, parroquia Santa María del Toachi. Cienc. Lat. Rev. Cient Multidis., 9(1). https://doi.org/10.37811/cl_rcm.v9i1.15818

Aryal S (2022). Endospore Staining- Principle, Reagents, Procedure and Result. MicrobiologyInfo.com. https://microbiologyinfo.com/endospore-staining-principle-reagents-procedure-and-result/

Agencia de Regulación y Control Fito y Zoosanitario (AGROCALIDAD) (2022). Manual de buenas prácticas pecuarias en la producción lechera. AGROCALIDAD. https://www.agrocalidad.gob.ec

Agresti A (2018). Statistical methods for the social sciences (5th ed.). Pearson. https://plus.pearson.com/home?nu=1

Alvarado W, González J, Quilcate C, Saucedo J, Bardales J (2019). Factores de prevalencia de mastitis subclínica en vacas lecheras del distrito de Florida, Región Amazonas, Perú. Rev. Invest. Vet. Perú., 30(2): 923-931. https://revistasinvestigacion.unmsm.edu.pe/, https://doi.org/10.15381/rivep.v30i2.16088

American Society for Microbiology (ASM) (2016). Basic microbiological techniques: streaking for isolation. ASM Education Resources.

American Type Culture Collection. (n.d.). Bacteriology culture guide. Recuperado el 9 de octubre de 2025, de https://www.atcc.org/resources/culture-guides/bacteriology-culture-guide

Bacteriology Culture Guide: Growth and propagation of bacterial strains. American type culture collection. https://www.atcc.org/resources/culture-guides/bacteriology-culture-guide

Barzola S (2021). Plan de Desarrollo y Ordenamiento Territorial del Cantón Daule 2015–2025 (Versión actualizada). Gobierno Autónomo Descentralizado Municipal de Daule. https://www.daule.gob.ec/wp-content/uploads/2023/09/PDOT_DAULE_2015-2025.pdf

Baroja, I., Guerra, S., Coral-Almeida, M., Ruíz, A., Galarza, J. M., de Waard, J. H., & Bastidas-Caldes, C. (2021). Methicillin-Resistant Staphylococcus aureus nasal colonization among health care workers of a tertiary hospital in Ecuador and associated risk factors. Infection and Drug Resistance, 14, 3433–3440. https://doi.org/10.2147/IDR.S326148

Bauer AW, Kirby WMM, Sherris JC, Turck M (1966). Antibiotic susceptibility testing by a standardized single disk method. Am. J. Clin. Pathol., 45(4): 493–496. https://doi.org/10.1093/ajcp/45.4_ts.493

Bonifaz GN, Requelme NJ (2011). Buenas prácticas de ordeño y la calidad higiénica de la leche en el Ecuador. La Granja, 14(2): 45-57. https://doi.org/10.17163/lgr.n14.2011.04

Bradford PA, Bonomo RA, Bush K, Carattoli A, Feldgarden M, Haft DH, Ishii Y, Jacoby GA, Klimke W, Palzkill T, Poirel L, Rossolini GM, Tamma PD, Arias CA (2022). Consensus on β-lactamase nomenclature. Antimicrob. Agents Chemother., 66: e00333-22. https://doi.org/10.1128/aac.00333-22

Buldain DC, Mestorino ON, Islan GA (2023). Nanobiotecnología como alternativa para el tratamiento de mastitis bovina por Staphylococcus aureus: Nanopartículas conteniendo aceite esencial de Melaleuca armillaris sm. y cloxacilina [Comunicación]. Investigación Joven, 10(3), EBEC 2022. Universidad Nacional de La Plata. https://revistas.unlp.edu.ar/InvJov/article/view/15497

Cabezas CR, Barba CC, González MA, Cevallos FO, León JJM, Aguilar RJM, García MA (2019). Estudio biométrico del bovino criollo de Santa Elena (Ecuador). Rev. Mex. Cienc. Pecu., 10(4): 819-836. http://cienciasspecuarias.inifap.gob.mx/, https://doi.org/10.22319/rmcp.v10i4.4850

Castellano GMJ, Perozo-Mena AJ (2010). Mecanismos de resistencia a antibióticos β-lactámicos en Staphylococcus aureus. Kasmera, 38(1): 18–35.

Castellanos GM, Perozo MA, Devis SR (2016). Resistencia a oxacilina, eritromicina y gentamicina en cepas de Staphylococcus coagulasa negativa aisladas de hemocultivos. Kasmera, 44(2): Artículo 00004.

Castañeda-Ruelas GM, Haros-Ramos MC, Perales-Sánchez JXK, Durán-Pérez SA, Fierros-Pérez CE, Hernández-Díaz LJ (2025). Calidad microbiológica de la leche cruda de vaca y evaluación de prácticas domésticas para su seguridad y calidad proteica: un estudio de caso. Biotecnia, 27. https://doi.org/10.18633/biotecnia.v27.2323

Castaño Á, Pérez RMR (2017). Balance energético negativo y su efecto sobre la producción y reproducción en vacas lecheras [Trabajo de grado, Universidad Cooperativa de Colombia, Facultad de Ciencias de la Salud, Medicina Veterinaria y Zootecnia, sede Ibagué]. Repositorio Institucional UCC. https://repository.ucc.edu.co/server/api/core/bitstreams/b3c5e774-616a-4344-b4b2-3d5481685c03/content

Castro-Orozco R, Villafañe-Ferrer L, Rocha-Jiménez J, Alvis-Guzmán N (2018). Resistencia antimicrobiana en Staphylococcus aureus y Staphylococcus epidermidis: Tendencia temporal (2010–2016) y fenotipos de multirresistencia, Cartagena (Colombia). Biosalud, 17(2): 25–36. https://doi.org/10.17151/biosa.2018.17.2.2

Centro de Levantamientos Integrados de Recursos Naturales por Sensores Remotos (CELIR) (2019). Mapa de ecosistemas y recursos naturales de la provincia del Guayas. ESPOL. https://www.espol.edu.ec/celir

Cisneros-Saguilán P, Hernández-Salinas G, Hernández HM (2024). Sistemas silvopastoriles, una alternativa para atenuar el impacto del cambio climático en la ganadería. Idesia, 42(2). https://doi.org/10.4067/s0718-34292024000200051

Contero R, Cachipuendo C (2021). Calidad del agua y de la leche en sistemas de ordeño manual de la Sierra Norte del Ecuador. Rev. Invest. Vet. Perú, 32(4): e20937. https://doi.org/10.15381/rivep.v32i4.20937

Centers for Disease Control and Prevention (2022). Antibiotic resistance threats in the United States, 2022. U.S. Department of Health and Human Services. https://www.cdc.gov/antimicrobial-resistance/media/pdfs/antimicrobial-resistance-threats-update-2022-508.pdf

Correa BAM, De la CVE, Rojas R, Falco A, Aranaga CA, Alonso G, Perenguez VM (2021). Estudios en resistencia a los antibióticos beta-lactámicos en bacterias Gram negativas. Editorial Universidad Santiago de Cali.

Chávez RK, Condolo OL, Vinueza VP, Tiama PN (2025). Patrones de resistencia a los antibióticos en bacterias aisladas de mastitis subclínicas. Rev. Invest. Vet. Perú, 36(1): e30199. https://doi.org/10.15381/rivep.v36i1.30199

Cherwell Laboratories (2023). Best practices for aseptic pouring of agar plates in microbiology. https://www.cherwell-labs.co.uk

Clinical and Laboratory Standards Institute (CLSI) (2020). Performance Standards for Antimicrobial Susceptibility Testing (30th ed.). CLSI supplement M100. https://clsi.org/standards/products/microbiology/documents/m100/

De La Cadena E, Pallares CJ, García-Betancur JC, Porras JA, Villegas MV (2023). Actualización sobre la resistencia antimicrobiana en instituciones de salud de nivel III y IV en Colombia entre enero del 2018 y diciembre del 2021. Biomédica, 43: 457–473. https://doi.org/10.7705/biomedica.7065

Departamento Administrativo Nacional de Estadística (DANE) (2013). Boletín mensual: Insumos y factores asociados a la producción agropecuaria (Núm. 14). SIPSA. https://www.dane.gov.co/index.php/estadisticas-por-tema

Díaz C, García Y (2024). El rol del investigador y la ética: La incansable lucha de vida. e-Revista Multidisciplinaria del Saber, 2, artículo e-RMS06122024.

Dias VL, Fontana S, Soares MJ, Giannini M, Queico C, Leite F, Toscano ME, Mariza A, Almeida F, Aparecido C, Fontana P, Matias DSC, Stella AE (2010). Etiologia da mastite bovina subclínica, sensibilidade dos agentes às drogas antimicrobianas e detecção do gene da β-lactamase em Staphylococcus aureus. Vet. Zootec., 17(4): 552–559. https://rvz.emnuvens.com.br/rvz/article/view/1169

Ding T, Luo L, Zhu W (2017). Recovery of stressed Staphylococcus aureus and coagulase-negative staphylococci using enrichment techniques in food microbiology. Food Contr., 73: 1320–1326.

Escobar M, Gonzáles A, Buela L, Cuenca M, Guamán M, Yarzábal L (2022). Detección de cepas multirresistentes de Staphylococcus aureus en leche de vacas con mastitis clínica y subclínica, en el cantón Biblián, Provincia de Cañar, Ecuador. Jornadas Científicas Unidad Académica de Salud y Bienestar. Ecuador. https://www.researchgate.net/profile/Mercy-Cuenca/publication/370815291

Espinosa CI, Báez AM, Hernández FRE, López DY, Lobo RE, Corona-González B (2019). Resistencia antimicrobiana en bacterias de origen animal: Desafíos para su contención desde el laboratorio. Rev. Salud. Anim., 41(3): 1–12. http://www.scielo.sld.cu/scielo.php?script=sci_arttextandpid=S0253-570X2019000300008

Food and Agriculture Organization of the United Nations (2017). Hygienic and quality milk production: Training package for dairy extension workers [Manual de capacitación]. FAO. https://a.storyblok.com/f/191310/10aa080f2e/hygienic_ning_manual_and_guideline.pdf

Food and Drug Administration (2023). Informed Consent Guidance for IRBs, Clinical Investigators, and Sponsors. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/informed-consent

GADPG (Gobierno Autónomo Descentralizado de la Provincia del Guayas) (2021). Plan de Desarrollo y Ordenamiento Territorial de la Provincia del Guayas.

García AZN, Alderete-Gutiérrez JJ, Rodriguez-Trejo C, Leal-Rodriguez JA, Olave LJI, Martínez-Juarez VM (2025). Resistencia a antimicrobianos en bovinos leche y bovinos carne y su posible impacto en la salud pública a nivel mundial. Bol. Cienc. Agropec. ICAP, 11(21): 21–29. https://doi.org/10.29057/icap.v11i21.13111

García-Roche SMM (2017). Impacto del balance energético negativo sobre la función mitocondrial en el hígado bovino [Tesis de maestría, Universidad de la República]. Colibrí.

Giono-Cerezo S, Santos-Preciado JI, Del RM-OM, Torres-López FJ, María Y, Alcántar-Curiel D (2020). Resistencia antimicrobiana. Importancia y esfuerzos por contenerla. Gac. Med. Mex., 156(2): 172–180. https://doi.org/10.24875/GMM.20005624

Gómez-Quispe OE, Santivañez-Ballón CS, Arauco-Villar F, Espezua- Flores OH, Manrique-Meza J (2015). Criterios de interpretación para California Mastitis Test en el diagnóstico de mastitis subclínica en bovinos. Rev. Invest. Vet. Perú, 26: 86-95. https://doi.org/10.15381/rivep.v26i1.10912

Hardy Diagnostics (2024). How to perform a catalase test to differentiate Staphylococcus from Streptococcus. https://hardydiagnostics.com/blog/How-to-perform-a-catalase-test

Hudzicki J (2009). Kirby-Bauer disk diffusion susceptibility test protocol. American Society for Microbiology. https://asm.org/getattachment/2594ce26-bd44-47f6-8287-0657aa9185ad/kirby-bauer-disk-diffusion-susceptibility-test-protocol-pdf.pdf

Ionita E (2022). La producción de leche en Ecuador. Vet. Digit. https://www.veterinariadigital.com/articulos/la-produccion-de-leche-en-ecuador/

Instituto Nacional de Investigación en Salud Pública (INSPI) (2022). Boletín N° 1-Centro de Referencia Nacional de Resistencia a los Antimicrobianos (CRN-RAM). Quito, Ecuador. https://www.investigacionsalud.gob.ec/webs/ram/wp-content/uploads/2022/11/2do-Boletin-CRN-Resistencia-Antimicrobiana.pdf

Irfan M, Almotiri A, Al-Zeyadi ZA (2022). Antimicrobial resistance and its drivers. A review. Antibiotics, 11(10): 1362. https://doi.org/10.3390/antibiotics11101362

Jara Gatica ME (2024). Comparación de las características de las reacciones adversas de antibióticos desde 2019 a 2022 en el Departamento de Medicina Interna del Hospital Clínico Universidad de Chile [Informe de internado en farmacia clínica, Universidad de Chile]. Repositorio Académico Universidad de Chile. https://repositorio.uchile.cl/bitstream/handle/2250/200186/comparacion-de-las-caracteristicas-de-las-reacciones-adversas-de-antibioticos-desde-2019-a-2022.pdf

Jarquín R, Aguilar A (2025). Uso de pastos mejorados para pastoreo directo o para corte en sistemas silvopastoriles. CATIE, Serie Técnica Boletín Técnico No. 125. ISBN: 978-9977-57-820-0. https://repositorio.catie.ac.cr/bitstream/handle/11554/13326/BCO25079869e.pdf?sequence=4

Jiménez BMM (2021). Uso de antibióticos en medicina veterinaria y su implicación en la resistencia bacteriana zoonótica [Trabajo académico, Facultad de Veterinaria, Universidad Complutense de Madrid]. Producción Científica UCM. https://produccioncientifica.ucm.es/documentos/613c14913a1d9314579a16a8221f340.pdf

Jurado-Gámez HA, Quitiaquez-Montenegro DA, Muñoz-Domínguez LC (2021). Valoración de calidad composicional, sanitaria y microbiológica de leche cruda en diferentes tercios de lactancia. Biotecnol. Sect. Agropec. Agroind., 19(2): 1–15. https://doi.org/10.18684/bsaa.v19.n2.2021.1675

Kaasch AJ, López-Cortés LE, Rodríguez-Baño J, Cisneros JM, Navarro MD, Fätkenheuer G, Jung, N., Rieg, S., Lepeule, R., Coutte, L., Bernard, L., Lemaignen, A., Kösters, K., MacKenzie, C. R., Soriano, A., Hagel, S., Fantin, B., Lafaurie, M., Talarmin, J.-P., Dinh, A., Guimard, T., Boutoille, D., Welte, T., Reuter, S., Kluytmans, J., Martin, M. L., Forestier, E., Stocker, H., Vitrat, V., Tattevin, P., Rommerskirchen, A., Noret, M., Adams, A., Kern, W. V., Hellmich, M., & Seifert, H., SABATO Study Group(2024). Efficacy and safety of an early oral switch in low-risk Staphylococcus aureus bloodstream infection (SABATO): An international, open-label, parallel-group, randomised, controlled, non-inferiority trial. Lancet Infect. Dis., 24(5): 523–534.

Kerro DO (2020). Bovine mastitis: Part I. En F. Aral, R. Payan-Carreira and M. Quaresma (Eds.), Animal reproduction in veterinary medicine (cap. 8). IntechOpen. https://doi.org/10.5772/intechopen.93483

Kiarie S (2024). How to test for mastitis using CMT method (California Mastitis Test). Dairyverse Kenya. https://dairyversekenya.com/testing-for-mastitis-using-cmt-method/

Kour S, Sharma N, Balaji N, Kumar P, Soodan JS, Santos MV, Son YO (2023). Advances in diagnostic approaches and therapeutic management in bovine mastitis. Vet. Sci., 10(7): 449. https://doi.org/10.3390/vetsci10070449

Krumperman PH (1983). Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of fecal contamination of foods. Appl. Environ. Microbiol., 46(1): 165–170. https://doi.org/10.1128/aem.46.1.165-170.1983

UNAM (2019). Base de agar sangre: preparación y usos. https://amyd.quimica.unam.mx/pluginfile.php/9875/mod_folder/content/0/Agar%20Sangre.pdf

Laxminarayan R, Impalli I, Rangarajan R, Cohn J, Ramjeet K, Trainor BW, Strathdee S, Sumpradit N, Berman D, Wertheim H, Outterson K, Srikantiah P, Theuretzbacher U (2024). Expanding antibiotic, vaccine, and diagnostics development and access to tackle antimicrobial resistance. Lancet, 403(10443): 2534–2550. https://doi.org/10.1016/S0140-6736(24)00878-X

Lituma RVB (2023). Determinación de la prevalencia de mastitis subclínica en ganado bovino de una finca ganadera localizada en el cantón Naranjal, provincia del Guayas [Tesis de grado, Universidad Agraria del Ecuador]. Facultad de Medicina Veterinaria y Zootecnia. https://cia.uagraria.edu.ec/Archivos/LITUMA%20ROCHA%20VANESSA%20BEATRIZ.pdf

López-Vigoa O, Sánchez-Santana T, Iglesias-Gómez JM, Lamela-López L, Soca-Pérez M, Arece-García J, Milera-Rodríguez MDLC (2017). Los sistemas silvopastoriles como alternativa para la producción animal sostenible en el contexto actual de la ganadería tropical. Pastos y forrajes, 40(2): 83-95. https://dialnet.unirioja.es/servlet/articulo?codigo=10054293

López GY, Gamboa PY, Rodríguez CY, Artega YYL (2022). Resistencia microbiana a los antibióticos: un problema de salud creciente. Rev. Cient. Hallazgos, 21, 7(1): 103–114. Universidad Metropolitana de Ecuador. https://dialnet.unirioja.es/servlet/articulo?codigo=8474991, https://doi.org/10.69890/hallazgos21.v7i1.562

Llanos VCD (2025). Caracterización de sistemas de producción bovina de leche en el cantón Daule, provincia de Guayas [Trabajo de titulación de grado, Universidad Agraria del Ecuador]. Universidad Agraria del Ecuador. https://cia.uagraria.edu.ec/Archivos/LLANOS%20VEGA%20CARLOS%20DAVID.pdf

Martínez-Vázquez AV, Vázquez-Villanueva J, Leyva-Zapata LM, Barrios-García H, Rivera G, Bocanegra-García V (2021). Multidrug resistance of Escherichia coli strains isolated from bovine feces and carcasses in Northeast Mexico. Front. Vet. Sci., 8: 643802. https://doi.org/10.3389/fvets.2021.643802

Medina PGE, Pereda MJJ, Curbelo RLM (2024). Producción de leche en Ecuador, su proyección a partir de escenarios con énfasis en la cuenca baja del Guayas. Rev. Prod. Anim., 36(1): 38-56. https://dialnet.unirioja.es/servlet/articulo?codigo=9965562

Mercer MA (2022). Uso de penicilinas en animales. En MSD Veterinary Manual. University of California, Davis. https://www.msdvetmanual.com/es/farmacolog%C3%ADa/agentes-antibacterianos/uso-de-penicilinas-en-animales

Microbe Notes (2022). Zone of inhibition definition, principle, procedure, examples. https://theory.labster.com/es/zoneofinhibition/

Microbe Online (2023). Cómo manipular correctamente la placa de Petri en el laboratorio. https://enlaboratorio.com/como-se-manipula-la-caja-de-petri

Ministerio de Agricultura, Ganadería, Acuacultura y Pesca (MAGAP) (2016). Agenda zonal de desarrollo agropecuario de la provincia del Guayas. MAGAP. https://www.agricultura.gob.ec

Ministerio de Salud Pública del Ecuador (2019). Plan Nacional para la Prevención y Control de la Resistencia a los Antimicrobianos 2019–2023. Quito, Ecuador. https://aplicaciones.msp.gob.ec/salud/archivosdigitales/documentosDirecciones/dnn/archivos/AC-00011-2019%20AGOSTO%2007.PDF

Montaño AMJ (2012). Ecosistema Guayas y conocimiento tropical: nuevas apuestas para la prosperidad del Ecuador. ESPOL, ICQA. http://www.dspace.espol.edu.ec/handle/123456789/20835

Monteagudo FJM, Espartero GA, López FS, Urcía JY, Bayod GA, Jiménez MB (2021). Examen microscópico, tipos de tinciones bacterianas. Rev Sanit Investig. https://revistasanitariadeinvestigacion.com/examen-microscopico-tipos-de-tinciones-bacterianas/

Montero TJ (2022). Relación de la radiación solar con la producción de plantas agroproductivas. Rev. Invest. Innov. Agropec. Rec. Nat., 9(1): 52–66. https://doi.org/10.53287/oqym7033yy88k

Moreno S, Ibarra FA, Martín MH, Retes R, Hernández JE (2023). La Técnica del destete precoz como herramienta de apoyo al cumplimiento de los objetivos de desarrollo sustentable, en la ganadería Sonorense. Rev. Mex. Agroneg., 52: 459-470.

Muñoz-Ibarra E, Molina-López RA, Durán I, Garcias B, Martín M, Darwich L (2022). Antimicrobial resistance in bacteria isolated from exotic pets: The situation in the Iberian Peninsula. Animals, 12(15): 1912. https://doi.org/10.3390/ani12151912

Mueller JH, Hinton J (1941). A protein-free medium for primary isolation of Neisseria gonorrhoeae and Neisseria meningitidis. Publ. Health Rep., 56: 1488–1491. https://www.tmmedia.in/wp-content/uploads/TD/TD-TRM-339.pdf

Murtagh F, Legendre P (2014). Ward’s hierarchical agglomerative clustering method: Which algorithms implement Ward’s criterion? J. Classif., 31(3): 274–295. https://doi.org/10.1007/s00357-014-9161-z

McFadden M (2025). California mastitis test and milk quality. Michigan State University Extension. https://www.canr.msu.edu/uploads/234/76581/cmt.pdf

Ortega AG (2022). Influencia de la alimentación en el desempeño reproductivo del ganado bovino lechero en el trópico medio colombiano. [Monografía]. Repositorio Institucional UNAD. https://repository.unad.edu.co/handle/10596/44965

Ortiz PYM (2025). Influencia de la radiación solar en la acumulación de materia seca del llantén forrajero (Plantago lanceolata L.) [Tesis de pregrado, PUCE]. https://repositorio.puce.edu.ec/items/8dda5d38-df94-4b82-8fef-57bd48441dda/full

Organización Mundial de la Salud (OMS) (2021a). Resistencia a los antimicrobianos. Notas descriptivas. https://www.who.int/es/news-room/fact-sheets/detail/antimicrobial-resistance

Organización Panamericana de la Salud (OPS) (2021b). Resistencia antimicrobiana en producción animal. Centro Panamericano de Fiebre Aftosa y Salud Pública Veterinaria. https://www.paho.org/es/panaftosa/resistencia-antimicrobiana-produccion-animal

Organización Mundial de Sanidad Animal (OIE) (2022). Sexto informe anual sobre los agentes antimicrobianos destinados a ser utilizados en animales. OIE. https://www.woah.org/app/uploads/2022/07/es-sixth-annual-report-amu-final.pdf

Parra R, Magaña MA, Piñeiro AT (2019). Intensificación sostenible de la ganadería bovina tropical basada en recursos locales: Alternativa de mitigación ambiental para América Latina. Revisión bibliográfica. ITEA Inf. Tec Econ. Agrar., 115(4): 342-359.

Pan American Health Organization (PAHO) (2021). Americas report surge in drug-resistant infections due to misuse of antimicrobials during the pandemic. https://www.paho.org/en/news/17-11-2021-americasant-infections-due-misuse-antimicrobials-during

Patiño-Burbano RE, Jiménez-Velásquez S, Cabrera-Cabrera SL, Guerrero-Narváez EM, Montes-Vergara JC, Castro-Rincon E, Rodríguez-Bautista JL, Parra-Arango JL (2023). Caracterización higiénico-sanitaria de la leche bovina del departamento de Nariño. Rev MVZ Córdoba, 28(2): e2895–e2895. https://doi.org/10.21897/rmvz.2895

Pellegrino M, Frola I, Odierno L, Bogni C (2011). Mastitis bovina: Resistencia a antibióticos de cepas de Staphylococcus aureus asiladas de leche. REDVET, 12(7): 1-14. https://www.redalyc.org/pdf/636/63622567006.pdf

Pezo D (2019). Intensificación sostenible de los sistemas ganaderos frente al cambio climático en América Latina y el Caribe: Estado del arte. Banco Interamericano de Desarrollo. https://doi.org/10.18235/0001722

Pinilla G, Muñoz L, Ruiz AI, Chavarro B, Cifuentes Y (2009). Aislamiento de Staphylococcus epidermidis portador de integrón clase 1 en un paciente con sepsis neonatal. Infection, 13(3): 180–186. http://www.scielo.org.co/scielo.php?script=sci_arttextandpid=S0123-93922009000300007

Puga-Torres B, Vera-Mendieta M (2025). Factors associated with the presence of antibiotic residues in raw milk from cows in the canton of El-Carmen, Manabí, Ecuador. Rev. Fac. Med. Vet. Zootec., 72(1). https://doi.org/10.15446/rfmvz.v72n1.113703

Prescott, J. F. (2013). Beta-lactam antibiotics: Penicillins (penams). En S. Giguère, J. F. Prescott, & P. M. Dowling (Eds.), Antimicrobial Therapy in Veterinary Medicine (5.ª ed., pp. xx–xx). Wiley-Blackwell. https://doi.org/10.1002/9781118675014.ch8

Proquimia (2023). Higiene de las ubres antes y después del ordeño. https://www.proquimia.com/higiene-ubres-ordeno/

Ranjbar M, Cabanillas-Rodríguez L, Rodríguez-Quiñones H, Mercado-Martínez P, Castillo-Díaz R, Zavaleta-Verde D (2020). E. coli y K. pneumoniae productores de BLEE, blaKPC, blaVIM y blaNDM en un hospital de referencia, Trujillo-Perú. Gac. Med. Boliv., 47(2), Artículo 61. https://doi.org/10.47993/gmb.v47i2.817

Rapoport M (2021). Novedades CLSI 2021: Actualización de puntos de corte y categorías interpretativas en pruebas de susceptibilidad antimicrobiana. Instituto Nacional de Enfermedades Infecciosas ANLIS “Dr. C. G. Malbrán”. https://antimicrobianos.com.ar/ATB/wp-content/uploads/2021/05/NOVEDADES-CLSI-2021.pdf

Rahman MS, Hassan MM, Chowdhury S (2021). Determination of antibiotic residues in milk and assessment of human health risk in Bangladesh. Heliyon, 7(8). https://doi.org/10.1016/j.heliyon.2021.e07739

Reyes SEA, Argüello SJS (2015). Estudio comparativo entre los métodos diagnósticos para mastitis subclínicas: California Mastitis Test y DRAMINSKI 4Q en vacas Jersey, Diriamba – Carazo, Agosto – Octubre 2015 [Tesis de licenciatura, Universidad Nacional Agraria]. https://cenida.una.edu.ni/Tesis/tnl73r457.pdf

Romero Pérez, I. A. (2020). Técnica de pre-enriquecimiento para análisis microbiológico. Tecnológico de Estudios Superiores de Ecatepec. https://www.studocu.com/es-mx/document/tecnologico-de-estudios-superiores-de-ecatepec/microbiologia-general/tecnica-de-preenriquecimiento/46582321

Sader HS, Carvalhaes CG, Kimbrough JH, Mendes RE, Castanheira M (2024). Activity of aztreonam-avibactam against Enterobacterales resistant to recently approved beta-lactamase inhibitor combinations collected in Europe, Latin America, and the Asia-Pacific Region (2020–2022). Int. J. Antimicrob. Agents, 63(4): 107113. https://doi.org/10.1016/j.ijantimicag.2024.107113

Sanders, E. R. (2012). Aseptic laboratory techniques: Plating methods. Journal of Visualized Experiments, (63), e3064. https://doi.org/10.3791/3064 (acceso abierto: https://pmc.ncbi.nlm.nih.gov/articles/PMC4846335/

Sánchez-Romero MI, García-Lechuz MJM, González LJJ, Orta MN (2019). Recogida, transporte y procesamiento general de las muestras en el laboratorio de Microbiología. Enferm. Infec. Microb. Clin., 37(2): 127–134. https://doi.org/10.1016/j.eimc.2017.12.002

Segovia C (2023). Sustentabilidad agroecológica del sistema agroproductivo bóvido en la región del bajo apure. Rev. Episteme, 5. http://revistas.unellez.edu.ve/index.php/retm/article/view/2026

Sokal RR, Sneath PHA (1963). Principles of numerical taxonomy. W. H. Freeman and Co. https://www.cabidigitallibrary.org/doi/full/10.5555/19650300280

Singh S, Ochoa AM, García MI, Cienfuegos AV, Vásquez-Jaramillo L (2022). Isolation of Escherichia coli and Klebsiella pneumoniae strains producing extended-spectrum β-lactamases from dog urine in the Aburrá Valley (Antioquia, Colombia). Rev. Fac. Med. Vet. Zootec., 69(3): 245–254. https://doi.org/10.15446/rfmvz.v69n3.103805

Schalm OW, Noorlander DO (1957). Experiments and observations leading to development of the California Mastitis Test. J. Am. Vet. Med. Assoc., 130(5): 199–204. https://digital.nls.uk/dcn6/7549/75495602.6.pdf

Terán MDA (2012). Diseño de un programa de buenas prácticas de ordeño en la hacienda ganadera productora de leche “El Chorro” [Tesis de grado, Universidad del Azuay]. https://dspace.uazuay.edu.ec/bitstream/datos/1382/1/09577.pdf

Thermo Fisher Scientific (2024). Heratherm microbiological incubators: Product specifications and usage guidelines. https://www.fishersci.es/shop/products/heratherm-compact-microbiological-incubators/10699640

Trombete FM, dos Santos RR, Souza ALR (2014). Residuos de antibióticos en la leche comercializada en Brasil: una revisión de los estudios publicados en los últimos años. Rev. Chil. Nutr., 41(2). https://doi.org/10.4067/S0717-75182014000200010

Thurmond MC, Holmberg CA, Picanso JP (1989). Effect of enrichment on isolation of Staphylococcus aureus from bovine intramammary infections. J. Clin. Microbiol., 27(4): 862–864.

Universidad Continental (2023). Guía de laboratorio de microbiología clínica (GL_504_24.01). Fondo Editorial. https://repositorio.continental.edu.pe/bitstream/20.500.1_24UC00739_2025.pdf

Universidad Nacional Autónoma de México (2025). Requerimientos de crecimiento en microbiología: Streptococcus y más. Studocu. https://www.studocu.com/es-mx/document/universidad-nacional-autonoma-de-mexico/microbiologia-i/requerimientos-microbiologia/87993429

Valle SK (2024). Mastitis y calidad de la leche en vacas lecheras. e-Rev Multidiscip Saber, 2. https://reciena.espoch.edu.ec/index.php/reciena/article/view/49

Vásquez-Jaramillo L, Cardozo-Herrera LK, Correa VNMDP (2023). A systematic review of tetracycline resistance genes in animals and derived products in Latin America and the Caribbean. Braz. J. Vet. Res. Anim. Sci., 60: e213883. https://doi.org/10.11606/issn.1678-4456.bjvras.2023.213883

Vázquez FC, Olivares FA, Olivares FR, García GAJ, García AV, Espeleta VA (2023). Esterilización de material en autoclave: métodos y consideraciones. Rev. Sanit. Invest., https://revistasanitariadeinvestigacion.com/esterilirial-en-autoclave-metodos-y-consideraciones

Vayas CGM (2021). Influencia económica de la mastitis en tres ganaderías de la provincia de Chimborazo período 2014–2016 [Trabajo de titulación, Escuela Superior Politécnica de Chimborazo]. DSpace ESPOCH.

Vargas SJG (2018). Análisis del impacto del sector arrocero en el Cantón Daule 2012-2016. Universidad de Guayaquil, Facultad de Ciencias Económicas. https://repositorio.ug.edu.ec/items/16dc18b9-88ea-4368-9680-bad8ba69acf6repositorio.ugimage.jpg

Zumbado MR, Barquero MA, Hidalgo MO (2022). Resistencia a los antibióticos: Una revisión bibliográfica. Rev. Cienc Salud Integrando Conocim, 6(3): 145–153. https://doi.org/10.34192/cienciaysalud.v6i3.500

Zubieta DMS, Quiroga CC (2022). Manual de toma, conservación, transporte y envío de muestras. Ministerio de Salud y Deportes de Bolivia. https://www.minsalud.gob.bo/images/Descarga/laboratorio/publicacion%20166.pdf

Walsh TR (2018). A one-health approach to antimicrobial resistance. Nat. Microbiol., 3(8): 854-855. https://doi.org/10.1038/s41564-018-0208-5

Woozberley M (2020). Influencia de la radiación solar en el crecimiento de frutos de mango Tommy Atkins en zonas dedicadas a la exportación [Tesis de grado, Universidad Agraria del Ecuador]. https://cia.uagraria.edu.ec/Archivos/MOISE%20WOOZBERLEY.pdf

World Health Organization (2021). Resistencia a los antimicrobianos. https://www.who.int/es/news-room/fact-sheets/detail/antimicrobial-resistance

Yánez-Avalos DO, Barbona I, López-Parra JC, Marini PR (2021). Protocolo J-Synch con y sin ECG en vacas Brown Swiss y sus cruzas con Bos indicus en la Amazonía ecuatoriana. La Granja Rev. Cienc. Vida, 33(1). https://doi.org/10.17163/lgr.n33.2021.01