Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551014
Pertenecen a esta colección Tesis y Trabajos de grado de los Doctorados correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Generalisable computer vision methods for endoscopic surveillance and surgical interventions(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-05) Ali, Mansoor; Ochoa Ruiz, Gilberto; emimmayorquin, emipsanchez; School of Engineering and Sciences; Campus Estado de México; Ali, SharibAmong the most prevalent cancers in humans are gastrointestinal (GI) cancers, which mostly include cancers originating from the esophagus, stomach, and colon. Endoscopy for the upper gastrointestinal (GI) tract and colonoscopy for the lower side are considered the gold standard techniques for screening and removing precancerous lesions and abnormal tissue growth like polyps with high sensitivity. Prior research has shown higher polyp miss rates due to their peculiar morphology, variability in shape or size, and appearance. Also, endoscopic surgical interventions offer a minimally invasive approach for lesion removal or for the treatment of other diseases inside the abdominal and reproductive organs. Despite being patient-friendly in reducing trauma, hospitalisation times, and quicker post-operative recovery, minimally invasive surgeries may become complicated due to increased cognitive burden and reduced field-of-view for the clinicians. Computer-assisted detection (CADe), diagnosis (CADx), and interventions (CAI) have shown promise in providing useful support to the clinicians in both disease diagnosis and treatment, with immense potential to further improvements as the data availability becomes easier due to the endoscopes. Deep learning is increasingly being leveraged to develop methods for improving the pre-cancerous lesion detection and diagnosis, reducing the missing rates and providing intraoperative assistance to surgeons for better decision-making. However, current methods suffer from the domain shift problem, i.e., they work well on the same distribution of data and perform poorly on out-of-the-distribution data, thus lacking the real-world deployment capability. This thesis explores the impact of domain shift in endoscopic domain data on the current state-of-the-art methods, investigates the research gaps, and proposes methods for improved disease detection, surveillance, and surgical interventions with better generalisation capability. Specifically, we aim to use the feature space of the encoder networks of the state-of-the-art segmentation methods to learn discriminant information for better domain-invariant learning and improving the model generalisation on unseen out-of-the-distribution endoscopic datasets. We propose various methods for polyp segmentation in upper and lower GI tract data, full scene segmentation in laparoscopic surgery, and depth estimation in abdominal surgery. We also introduce an annotated multicentre segmentation dataset for evaluating model performance on generalisability and encouraging further research. Our results indicate improved out-of-distribution performance on multi-domain and cross-center endoscopic data. We will further work on extending the data to enhance its size and variability and explore new methods to increase robustness and generalisation performance.
- Fabrication of binary and ternary semiconductors as gas sensing devices: stoichiometric design and functional engineering studies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-05) Rueda Castellanos, Kevin; Karthik Tangirala, Venkata Krishna; mtyahinojosa, emipsanchez; Henao Martínez, José Antonio; Dutt, Ateet; García García, Andrés David; School of Engineering and Sciences; Campus Estado de México; García Farrera, BrendaMetal-oxide semiconductor (MOS) sensors play a key role in environmental monitoring, healthcare diagnostics, and industrial safety due to their robustness, scalability, and low fabrication cost. However, achieving reliable selectivity and stability under realistic conditions remains a major challenge, often limited by the interplay between material composition, defect chemistry, and synthesis-dependent microstructure. To address this issue, the present work investigates the Zn–Sn–O ternary system as a tunable materials platform for CO and acetone sensing, focusing on how synthesis route and stoichiometry influence structural and functional behavior. Three complementary fabrication methods were employed to produce Zn–Sn–O materials with controlled composition and morphology: physical vapor deposition by magnetron sputtering (PVD-RMS), ultrasonic spray pyrolysis (USP), and chemical co-precipitation (CP). Each method provided distinct thermodynamic and kinetic environments that governed phase formation, crystallinity, and grain morphology. The synthesized materials were systematically characterized through X-ray diffraction with Rietveld refinement, FTIR and Raman spectroscopy, XPS, and SEM/EDS to correlate synthesis conditions with crystal structure and surface features. Gas-sensing performance toward CO and acetone was evaluated using a custom-built dynamic sensing system under standardized temperature and concentration ranges, allowing direct comparison across thin-film and powder-based architectures. Among the tested samples, the SZ50-450-USP thin film exhibited the highest acetone sensing performance at 300 °C, with response and recovery times of 193 s and 207 s, respectively, and a maximum sensing response of 87 %. These results demonstrate that balanced Zn/Sn ratios and controlled microstructural evolution significantly enhance sensitivity and stability. Based on the structural and functional analyses, a sensing mechanism is proposed that links preferential crystallographic orientation, grain size, and oxygen-vacancy distribution to the adsorption–desorption dynamics of target gases. The comparative study highlights the importance of synthesis–structure–property relationships in optimizing gas-sensing performance and provides a reproducible framework for designing Zn–Sn–O-based semiconducting oxides for selective VOC detection, with potential applications in medical diagnostics via breath analysis.
- Human learning curve forecasting & optimization framework for manual assembly operations(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-04) Peña Olvera, Carlos Adrián; Romero Díaz, David Carlos; emipsanchez; Johansson, Björn; Ruiz Loza, Sergio; Escobar Castillejos, David Escobar; Departamento de Ingenieria y Ciencias; Campus Ciudad de México; Noguez Monroy, Juana JulietaThe manufacturing industry is undergoing a significant transformation, led by the widespread adoption of Industry 4.0 technologies and data-driven production management systems. While monitoring and optimization have become common for machine operations, manual operations are mostly disconnected from these advancements, due to persistent challenges in data acquisition and the intrusiveness of monitoring methods. More importantly, low-cost countries keep manual assembly a core part of their operations, based on costs and flexibility. This second element, however, presents a challenge to companies, due to human behavior not being as perfectly repetitive as machines, leading to differences between planned production time and actual production time. One factor not currently considered in planning cycle times and production capacity is the learning effect, represented by prolonged cycle times in the first production units, but improving over time. Traditional approaches to track the learning effect have seen little application on processes in recent times, resulting in missed opportunities for productivity forecasting and optimization. The primary objective of this thesis is to present a comprehensive framework for the collection, operational forecasting, and productivity enhancement of production cycle times in manual operations by leveraging data paired with a simple data collection method. This work proposes a novel human learning curve measurement and optimization solution that mirrors the sophistication of machine monitoring applied to humans. It also considers a data problem commonly found in the manufacturing industry, which is excessive data collection, making predictions and fitting curves computationally expensive, by considering a simplification method. Key contributions of this Ph.D. thesis include a state-of-the-art review on learning curves, learning curve parameterization methods, and data simplification techniques, which led to the development of a “Human Learning Curve Forecasting and Optimization Framework”. The Ph.D. thesis also presents both controlled and industrial experimentation for the validation of the framework. The Ph.D. thesis results present the benefits of analyzing the human learning effect in productivity, presenting the industry with the opportunity to take immediate action to improve and increase efficiency in the short- and long-term, ultimately integrating the human factor in the decision-making for performance improvements. The Ph.D. thesis presented calls for a change in the way manual operations are being analyzed, by considering the learning curve effect, analyzing it in the short- and long-term, and presenting an alternative way to plan production in line.
- A comparative study on chemically and phytogenically synthesized TiO₂ nanoparticles and their role in modulating plant growth and metabolic dynamics(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-04) Bhatti, Atiya; Navarro López, Diego Eloyr; mtyahinojosa, emipsanchez; Sánchez Martínez, Araceli; Lozano Sánchez, Luis Marcelo; Mejía Méndez, Jorge L.; School of Engineering and Sciences; Campus Estado de México; López Mena, Edgar RenéThe present research provides a comprehensive investigation of the synthesis, characterization, and agricultural applications of titanium dioxide nanoparticles (TiO₂-NPs) developed via a conventional and eco-friendly (green synthesis method) route, focusing on their interactions with plant growth-promoting microorganisms (PGPMs) in order to boost the physiological and antioxidant performance of Capsicum annuum cultivars. The TiO₂-NPs synthesized through the molten salt method exhibited a nano-cuboid structure, a negative surface charge, and a moderate surface area. While green-synthesized TiO₂-NPs obtained from blueberry natural extracts using isopropanol (TiO₂-I.P) and methanol (TiO₂-M) exhibited mesoporous polyhedral anatase structures (E₉ ≈ 3.0 eV), hydrodynamic sizes of 130–150 nm, and stable ζ-potentials ranging from −33 to −50 mV. The extracts rich in flavonoid and phenolic compounds provided distinctive surface functionalities, improving the stability and bioactivity of the nanoparticles (NPs). In-vitro compatibility studies indicated that TiO₂-NPs facilitated microbial proliferation up to 150 µg/mL without exhibiting toxicity, thereby enhancing Bacillus thuringiensis (B.t) (1.56–2.92×10⁸ CFU/mL) and Trichoderma harzianum (Th) (2.50–3.90 × 10⁸ spores/mL), greenhouse experiments revealed significant enhancements in plants shoot and root growth, as well as increases in fresh weight (F.W) and dry weight (D.W) biomass and chlorophyll content. When TiO₂-NPs were utilized either independently or in combination with PGPMs B.t, Th. The synergistic treatments significantly improved antioxidant and enzymatic responses. Including peroxidase (69.90 UA/g F.W), β-1,3-glucanase (2.45 nkat/g FW), total phenolic content (29.50 GA/g FW), and chlorophyll accumulation (210.8 ± 11.4 mg/mg FW). In the context of green formulations were observed, TiO₂-I.P increased number of leaves and height of plant, whereas the root elongation not greater than control. Specifically with individual microorganism B.t, Th combined with at moderate concentration of TiO₂-I.P improved F.W and D.W. Peroxidase levels significantly increased when 50 µg/mL of TiO₂-M combined with microorganisms B.t+Th, While TiO₂-I.P stimulated a wider range of antioxidant responses, at 150 µg/mL of both formulation increased the total proteins. In case of total chlorophyll content increased at 150 µg/mL of TiO₂-I.P alone or combination of microorganism B.t+Th. The results emphasize biphasic behavior that is dependent on both formulation and dose, influenced by the surface chemistry of NPs and their compatibility with beneficial PGPMs. This work advances a practical framework for precision and sustainable agriculture through the integration of nanotechnology and microbial biotechnology. Where the surface chemistry of NPs and their biological compatibility can be tailored to ensure reliable and useful outcomes in agricultural fields.
- Valorization of berry by-products and waste based on a circular bioeconomy scheme: generation of prototypes and their biological and functional characterization(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-03) Hurtado Romero, Alejandra; García Cayuela, Tomás; mtyahinojosa, emipsanchez; Rodríquez Martínez, Verónica; Luzardo Ocampo, Iván; Paloma Barajas Álvarez; Zárate, Gabriela; García Amézquita, Luis Eduardo; Escuela de Ingeniería y Ciencias; Campus Guadalajara; Carrillo Nieves, DanayMexico is a global leader in berry production; however, the industry faces significant challenges in managing the considerable waste generated throughout the production chain. Large amounts of skins, pulp, and seeds, known as berry bagasse, remain underutilized. These residues are often discarded without treatment, resulting in the loss of valuable phytochemicals. Consequently, the development of effective strategies for the valorization of berry by-products is urgently required. Recent studies indicate that berry bagasse retains substantial levels of sugars, phenolic compounds, and other bioactive molecules, making it a promising source of functional ingredients. Comprehensive analyses of strawberry, raspberry, blueberry, and blackberry by-products have identified a wide variety of phenolic compounds, with blackberry bagasse exhibiting particularly strong antimicrobial activity. Moreover, several probiotic strains, including Lacticaseibacillus rhamnosus GG and Lentilactobacillus kefiri BIOTEC014, can utilize strawberry and blueberry bagasses as carbon sources. Solid-state fermentation (SSF) has also emerged as an innovative strategy to improve the bioactivity of blueberry residues. SSF with Aspergillus niger ATCC 6275 and Rhizopus oryzae BIOTEC018 significantly increases the release of bound phenolics, enhancing the antioxidant and anti-inflammatory potential of the resulting extracts. This approach enables the generation of metabolites with notable biological benefits and offers valuable opportunities for nutraceutical and biofortified food applications. The incorporation of berry by-products into dairy matrices further demonstrates their industrial potential. Blueberry bagasse powder and syrup have been successfully integrated into synbiotic Petit Suisse cheese, increasing fiber content, improving antioxidant capacity, and maintaining probiotic viability during storage. Sensory evaluations show high consumer acceptance, particularly in formulations combining both syrup and bagasse. Likewise, frozen dairy snacks enriched with blueberry bagasse and probiotics exhibit high nutritional quality, increased dietary fiber, strong antioxidant activity, and excellent probiotic stability during freezing and digestion. These products also receive strong consumer approval, reinforcing the feasibility of using berry residues to develop functional and sustainable foods. Overall, the valorization of berry by-products represents a sustainable strategy to reduce waste while generating high-value functional ingredients and innovative food products.
- Design of novel oven-baked sweet potato snack enhanced with brewery byproduct: the effect on sensory and nutritional content(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-03) Gómez Cisneros, Analaura; Calderón Oliver, Mariel; emimmayorquin, emipsanchez; Escalante Alburto, Anayansi; Pino Espinosa Ramírez, Johanan del; Ponce Alquicira, Edith; School of Engineering and Sciences; Campus Monterrey; Santos Sea, LilianaThis doctoral thesis investigates the potential of converting sweet potatoes into flour and analyzes how different drying techniques affect the preservation of bioactive compounds. It also assesses the role of ultrasound as a pretreatment strategy to improve the content of these compounds during processing. The obtained flour was subsequently used on the design of a novel baked snack enriched with brewer's spent grain (BSG), a by-product of the brewing industry, to evaluate the effects of this enrichment on its sensory and nutritional attributes. The main motivation lies in the growing demand for more nutritious snacks and the valorization of agro-industrial by-products. The general objective was to apply and evaluate the effects of ultrasound, storage, and drying methods in the processing of sweet potato to obtain flour with increased phenolic and carotene content, and to use it as an ingredient in an oven-baked snack enriched with BSG, aiming to achieve improved nutritional properties and acceptable sensory characteristics. The methodology included the production of sweet potato flour (SPF), evaluation of the effect of ultrasound treatment, different storage times (0, 24, 48, 72, and 96 h), and drying methods (dehydration and freeze-drying) on the content of bioactive compounds (phenolics and carotenoids), and physicochemical properties. Subsequently, a base snack was formulated using the produced sweet potato flour with corn flour and wheat flour, and the proportions were optimized through mixture design, based on sensory evaluation, and texture analysis. Finally, different proportions of ground BSG (6.25%, 12.5%, 18.75%, and 25%) were added to the base snack to evaluate its impact on sensory properties, color, texture, nutritional composition (moisture, fat, protein, fiber, ash, starch), and content of bioactive compounds (phenolics, carotenoids, and antioxidant activity). The results showed that ultrasound treatment significantly affected the polyphenol content of sweet potato flour, increasing it by 93%, highlighting the effectiveness of US as an abiotic elicitor for the accumulation of phenolic compounds even in processed foods. The drying method influenced the carotenoid content, achieving 65% more content when the samples were freeze-dried. In addition, the b* and L* values were affected by these two factors, resulting in higher values for both parameters. The processing methodology was defined as the use of US-pretreatment, storage for 48 h and dehydration, and the produced flour was used to develop a novel oven-baked snack with nixtamalized corn (CF) and wheat flour (WH). The optimal formulation consisted of 28.29% SPF, 41.45% CF, and 30.3% WF, achieving satisfactory overall acceptability with a score of 7.05±0.22 ("moderate liking"). The addition of BSG (up to 25%) to the optimized formula significantly modified the color by reducing the a* and b* values, and texture by increasing the hardness, gumminess, and chewiness of the snack. However, the overall sensory acceptance according to the hedonic scale remained at acceptable levels with scores above 6, defined as like slightly, even with the addition of up to 25% BSG. Nutritional analysis showed that adding BSG significantly increased 1.6 more times of dietary fiber and double the ash content, as well as three times more in the phenolic content and 33% more in antioxidant activity of the snack. The formulation containing 6.25% BSG proved to be the best final formula, offering the greatest balance between improved nutritional properties and favorable sensory attributes, with the highest overall acceptability score. Overall, this work brings together two main contributions: first, it proposes a novel processing strategy for sweet potato that combines ultrasound, cold storage, and dehydration, which resulted in a flour with enhanced bioactive content. Rather than limiting the contribution to improved flour, the study extends this development into an oven-baked snack that aligns with consumer demand for more nutritious foods. The combination of the produced sweet potato flour with corn, wheat, and brewer’s spent grain represents a mixture that has been scarcely explored, and working with it provided new information on how they can improve the nutritional profile of an oven-baked snack. These findings not only offer a promising direction for new added-value snack products but also respond to current trends in health-focused eating and sustainable food development. By valorizing an agro-industrial by-product and incorporating plant-based ingredients, the final product contributes to more responsible and forward-looking food systems.
- Effect of porosity and microstructure defects in out-of-plane properties of 3D printed composite materials made by continuous fiber reinforcement(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-03) Moreno Núñez, Benjamín Alberto; Treviño Quintanilla, Cecilia Daniela; mtyahinojosa, emipsanchez; Cuán Urquizo, Enrique; Sánchez Santana, Ulises; Pérez Santiago, Rogelio; School of Engineering and Sciences; Campus Monterrey; Pincheira Orellana, GonzaloThis research presents a comprehensive experimental and predictive analysis of 3D printed composite materials (3DPCM) made with Onyx reinforced Kevlar fibers. The mechanical behavior was characterized through three in-plane (tensile, compression and flexural) and four out-of-plane (Mode I, Mode II, Mixed-Mode I/II fracture, and short-beam strength) tests to evaluate both intralaminar and interlaminar responses. In-plane results revealed a strong dependence on fiber orientation, with the 0° fiber orientation achieving higher tensile and flexural, while the 90° fiber orientation exhibited slightly greater compressive modulus. Out-of-plane results demonstrated higher Mode I fracture toughness in 90° fiber orientation, whereas Mode II and mixed mode responses were dominated by shear effects, following the relationship 𝐺𝐼𝐼𝑐 >𝐺𝐼𝑐 > 𝐺𝐼/𝐼𝐼𝑐. Microstructural analysis identified voids, matrix peeling, fiber exposure, and poor impregnation as the key defects influencing crack initiation and delamination. Also, void content of the samples demonstrated an impact in mechanical properties as in traditionally made composites, the higher the void content the higher the mechanical variation. Finally, a machine-learning predictive model was developed to predict load-displacement curves in Short-Beam Strength tests, enabling accurate prediction of mechanical responses (𝑅2 > 0.94) based on number of fiber layers and fiber orientation configuration. These findings highlight the strong coupling between printing parameters and mechanical performance, providing valuable insights for the design and optimization of 3DPCM.
- A methodology to select downsized object detection algorithms for resource-constrained hardware using custom-trained datasets(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-03) Medina Rosales, Adán; Ponce Cruz, Pedro; emipsanchez; López Cadena, Edgar Omar; Montesinos Silva, Luis Arturo; Balderas Silva, David Christopher; Ponce Espinosa, Hiram Eredín; School of Engineering and Sciences; Campus Ciudad de MéxicoDownsized object detection algorithms have gained relevance with the exploration of edge computing and implementation of these algorithms in small mobile devices like drones or small robots. This has led to an exponential growth of the field with several new algorithms being presented every year. With no time to test them all most benchmark focus on testing the full sized versions and comparing training results. This however, creates a gap in the state of the art since no comparisons of downsized algorithms are being presented, specifically using custom built datasets to train the algorithms and restrained hardware devices to implement them. This work aims to provide the reader with a comprehensive understanding of several metrics obtained not only from training metrics, but also from implementation to have a more complete picture on the behavior of the downsized algorithms (mostly from the YOLO algorithm family), when trained with small datasets, by using a fiber extrusion device with three classes: one that has no defects, one that is very similar looking with small changes and one that has a more immediate tell in the difference, showcasing how good the algorithms tell apart each class using two different size of datasets, while also providing information on training times and different restrained hardware implementation results. Providing results on implementation metrics as well as training metrics.
- Comparative study of mass-accommodation methods and energy balances for melting paraffin wax in cylindrical thermal energy storage systems(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-03) Silva Nava, Valter; Otero Hernández, José Antonio; Hernández Cooper, Ernesto Manuel; emimmayorquin, emipsanchez; Santiago Acosta, Rubén Darío; Melo Máximo, Dulce Viridiana; School of Engineering and Sciences; Campus Ciudad de México; Chong Quero, Jesús EnriqueThis study introduces two innovative methods for modeling how paraffin wax melts inside a centrally heated annular space. Both approaches tackle the challenge of volume changes during melting by ensuring total mass is conserved, keeping the material mass constant, and adding a new equation of motion. To manage these volume shifts in a cylindrical setup, one method allows the outer radius to expand or contract radially, while the other treats the extra liquid volume as a dynamic variable along the central axis. Each method’s energy–mass balance at the boundary between the liquid and solid yields equations that describe how the interface moves, with only slight differences that still respect mass conservation. When melting occurs rapidly, the steady-state values for both volume and interface position are directly linked to the densities of the liquid and solid forms. The methods were put to the test in a vertical annular region filled with para!n wax, where thermodynamic properties were fine-tuned by minimizing the gap between measured and predicted temperatures. The widely used local energy balance at the melting front can sometimes mislead, depending on starting conditions, boundaries, and material traits. In contrast, the total energy balance method aligns closely with equilibrium, as shown by its agreement with thermodynamic equilibrium in saturated mixtures, and it delivers much smaller errors than the local approach. In a melting experiment using para!n RT50 inside a thermally insulated cylinder, the local energy balance underestimated the melting front position by 2.4% to 6.9%, whereas the total energy balance method kept discrepancies between 0.28% and 5.71%.
- Phytogenic synthesis of ZnO nanoparticles: towards eco-friendly strategies for antibacterial applications(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-12-02) Mustafa, Ghulam; Lozano Sánchez, Luis Marcelo; mtyahinojosa, emipsanchez; Eloyr Navarro, Diego; Melo Máximo, Dulce Viridiana; Vera Estrada, Irma Lucía; Iturbe-Ek, Jackeline; Escuela de Ingeniería y Ciencias; Campus Estado de México; Sánchez López, Angelica LizethThe accelerating threat of antimicrobial resistance (AMR) underscores the urgent need for sustainable, safe, and cost-effective alternatives to conventional antibiotics. The field of nanotechnology has advanced significantly, with zinc oxide nanoparticles (ZnO-NPs) gaining attention for their exceptional stability, biocompatibility, and strong antimicrobial potential. However, traditional fabrication techniques frequently utilize hazardous chemicals and require high energy inputs, leading to ecological and safety issues. In contrast, green synthesis mediated by plant extracts presents a viable, eco-friendly substitute. This approach is not only cost-effective and simple but also enhances nanomaterials (NMs) by integrating bioactive phytocompounds. This research employs a facile, green chemistry route to fabricate ZnO-NPs, utilizing pulp extracts from Agave azul (Agave tequilana), Chiku (Manilkara zapota), and Soursop (Annona muricata). acting as bio-reducing, stabilizing, and capping agents. Zinc acetate dihydrate was selected as the metal precursor, subjected to controlled thermal treatment and calcination. This methodology successfully yielded stable nanoparticles while completely avoiding the use of hazardous synthetic reagents. Comprehensive characterization confirmed the successful formation of ZnO-NPs. XRD validated their crystalline wurtzite structure, while electron microscopy revealed distinct morphologies: flower-like quasi-spherical aggregates for Agave-derived ZnO, mixed quasi-spherical and hexagonal particles for Chiku-derived ZnO, and predominantly quasi-spherical particles with occasional rod-like structures for Soursop-derived ZnO. The average NPs sizes were 15.94 nm, 18.08 nm, and 23.32 nm, respectively. FTIR confirmed Zn–O bonding with minimal organic residues, and UV-Vis spectroscopy revealed absorption edges between 345–380 nm, with band gap energies ranging from 3.08 to 3.17 eV respectively. Disc diffusion method was employed to evaluate the antibacterial performance. Agave-derived ZnO-NPs consistently produced the maximum inhibition zones (22.03 mm for E. coli; 19.06 mm for S. aureus at 50 μg/mL), followed by Chiku-derived ZnO-NPs and Soursop-derived ZnO-NPs. These results highlight the strong influence of nanoparticle size, morphology, and dispersion on biological efficacy. E. coli exhibited greater susceptibility than S. aureus, reflecting differences in their cell wall structures. This study introduces a novel sustainable pathway for nanoparticle synthesis, showing that natural extracts can produce antimicrobial NMs with strong activity. Beyond confirming their antibacterial efficacy, it underscores the role of green nanotechnology in minimizing environmental chemical burdens and advancing sustainable practices. Future directions include optimizing synthesis conditions, advancing toward scalable industrial production and extending evaluations against multidrug-resistant pathogens to unlock broader applications of Phytosynthesized ZnO-NPs in biomedical, pharmaceutical, food safety and sustainable material development domains.