ASEAN Journal of Scientific and Technological Reports

Statistical Modeling of Daily Rainfall Using Zero-tweaked Data

Aneeta Kalor — 2025-12-14

The significant amount of zero rainfall led to a highly skewed distribution of rainfall, creating challenges in rainfall modeling. This study aims to introduce a zero-tweaking method for handling a large proportion of zero rainfall data and apply it to daily rainfall data collected at four stations in southern Thailand from 2010 to 2022. The fourth root transformation was used to handle the right skew of rainfall. Zero-tweaking techniques were employed, with zeros substituted by normally distributed random numbers that permitted negative values. The patterns and trends in rainfall at each of the four stations were investigated using natural cubic splines. The trend projection analysis for four rainfall stations up to 2030 revealed an increase in rainfall at two stations in the Gulf of Thailand; however, this increase was not statistically significant. However, this study introduced the zero-tweaking method to handle the zero data, which enabled the use of conventional statistical methods and enhanced the model's validity.

Dose-Dependent Genoprotective Effects of Syzygium aromaticum (Clove) Extract Against Cyclophosphamide-Induced Chromosomal Damage and Micronucleus Formation in Swiss Albino Mice

Aseel Raheem Mardan Al-Aamiri — 2025-12-14

Cyclophosphamide (CP), a classical alkylating chemotherapeutic drug, has significant genotoxic effect but its use is restricted due to safety concerns. In the present study, we investigated a protective effect of Syzygium aromaticum (clove) ethanolic extract against CP-induced chromosomal damage in Swiss albino mice. Thirty male mice were distributed among five groups (n = 6): control, clove extract only (500 mg/kg), CP only (20 mg/kg intraperitoneally), and two post-treatment groups, receiving CP followed by oral clove extract at 400 mg/kg and 500 mg/kg for seven days. Chromosomal anomalies and micronucleus formation were assessed in bone marrow cells. CP treatment significantly increased structural chromosomal anomalies from 2.24 ± 1.01 (control) to 18.72 ± 0.05 (p < 0.05) and numerical aberrations from 3.62 ± 0.03 to 15.68 ± 0.02 (p < 0.05). Micronucleated polychromatic erythrocytes (MnPCEs) increased 9.9-fold from 1.38 ± 0.02% to 13.63 ± 1.01% (p<0.05). Post-treatment with 400 mg/kg clove extract reduced structural and numerical aberrations to 10.94 ± 3.01 and 11.03 ± 0.03, respectively, representing 42% and 30% reductions in these aberrations. The 500 mg/kg dose achieved greater protection, reducing structural aberrations by 74% (4.92 ± 0.03) and numerical aberrations by 68% (5.03 ± 0.05), approaching control values. MnPCE frequency decreased to 8.84 ± 1.02% (35% reduction) and 4.98 ± 0.05% (63% reduction) at 400 mg/kg and 500 mg/kg doses, respectively. The dose-dependent genoprotective effects are attributed to the high eugenol content and phenolic compounds in cloves, which possess antioxidant properties. These findings suggest that clove extract may be a promising natural chemoprotective agent for mitigating CP-induced genotoxicity, warranting further investigation for potential clinical applications.

Gibberellic Acid and Salicylic Acid on the Growth and Yield of Kale under Kratky Method Hydroponic System

Julius D. Caritan — 2025-12-14

Phytohormones are organic compounds, other than nutrients, that modify plant physiological processes, act inside plant cells to stimulate or inhibit specific enzymes or enzyme systems, and help regulate plant metabolism. In this work, the effectiveness of foliar application of gibberellic acid (GA3) and salicylic acid (SA) on the growth and yield of kale cultivated in a hydroponic system was evaluated. The study was conducted in a completely randomized design to determine the effectiveness of gibberellins and salicylic acid. The study demonstrated that the addition of 25 ppm GA3 + 200 ppm SA stimulated plant growth and enhanced yield. GA3 + SA treatments enhanced various morphological traits. Plant height is 37.77cm ± 0.08, fresh weight at 54.05g ± 0.44, root weight at 17.35g ± 0.21, whole plant at 71.41g ± 0.34, number of leaves at 11.73 ± 0.03, TSS and TA at 1.07 ± 0.02 and 0.56 ± 0.03, respectively. The application of growth hormones had a significant influence on all evaluated plant growth parameters, demonstrating that the combined application can markedly enhance overall plant growth and development. This highlights the potential of growth regulators as practical tools for optimizing physiological processes and improving crop performance in a hydroponic system.

Physicochemical and Microbiological Evaluation of Reverse Osmosis Drinking Water Quality in Babylon Province, Iraq

Hala Faez Al-Jawahery — 2025-12-14

The physical, chemical and microbiological quality of drinking water produced from 25 reverse osmosis (RO) plants in five districts of Babylon Province, Iraq was assessed by applying the Canadian Water Quality Index (WQI). Systematic sampling of water for water quality assessment was undertaken from October 2024 to February 2025. Results showed that pH was between 6.1 to 7.8. Conductivity difference was noted to be large, between 10 and 360 μS/cm, whereas TDS exhibited between 6.14 and 225 mg/L, indicating the outstanding salt rejection in range of from ~90–99.5%. Total hardness showed a significant decrease (10-270 mg/L) with calcium hardness and magnesium hardness decreasing from 1 to 28 mg/L, and 1.458 to 62.694 mg/L, respectively; the concentrations of ions significantly decreased: chloride (11.85-49.98 mg/L), nitrate (0-0.024 mg/), sulfate (0.698-15.938 mg/). Counts of the total bacteria and coliforms were ranging from 177-301CFU/mL and 0-27CFU/100mL respectively in the sites based on microbial test. Based on WQI evaluation, 64% (n=16) of the samples were ranked to be excellent quality(0-25), 24%(n=6) good quality (26-50) and 12% (n=3) was poor quality(51-75). This integrated approach of the great extent study clearly verifies that RO technology has an outstanding performance to remove physicochemical contaminants, while presenting ongoing mastering difficulties such as microbiological safety and aluminum contamination to require more specific applicable guidelines in monitoring actions and regular maintenance works for their optimal operations.

AI-Driven Smart Farming for Automated Plant Health Monitoring and Nutrient Deficiency Detection

J. Serin — 2025-12-14

Precision agriculture is transitioning to continuous, data-driven monitoring. Affordable sensors and edge intelligence enable near real-time crop oversight. Manual scouting is labor-intensive and inconsistent. Delayed detection of nutrient stress leads to increased yield loss and input waste. Legacy systems monitor soil or weather in isolation and depend on periodic human checks. Vision pipelines often use shallow models and are not connected to field actuators. Proposed work: We combine soil moisture, temperature, and humidity sensing with camera-based leaf analysis using a DenseNet 121 classifier. A microcontroller executes closed-loop irrigation and localized cooling, with a mobile app for telemetry and alerts. RGB leaf images were captured in field conditions and labeled by experts into healthy and deficiency classes. Images were resized to 224×224 and split into training, validation, and test sets by plot to avoid leakage. DenseNet 121 achieved 89.0% accuracy on a held-out test set and surpassed a MobileNet V2 baseline of 82.0% under identical training conditions. Prototype deployments reduced manual checks and improved response to moisture and heat stress. The integrated IoT and AI pipeline is practical for early detection of nutrient deficiencies and autonomous actuation in small plots and greenhouses.

Predicting E-Commerce Purchase Intention Using Machine Learning

Om Ratna Sheshagiri Gupta Alamuri — 2025-12-14

The fast-evolving digital commerce environment demands precise predictions of consumer buying intentions to develop personalized experiences and boost conversion rates and user satisfaction on e-commerce platforms. The field has extensively utilized traditional statistical models in conjunction with behavioral theories; however, these methods fail to adapt to high-dimensional, imbalanced session-level data. This learning proposes a machine learning-based approach to predict online purchase intention using the widely recognized Online Shoppers Intention dataset. The methodology involves a reproducible pipeline that integrates data preprocessing, the synthetic minority over-sampling technique (SMOTE) to address class imbalance, chi–square–based feature selection, and a comparative evaluation of multiple classification models. The pipeline was tested on a 70:30 train-test split using stratified sampling to maintain class distribution, and further validated through 10-fold cross-validation to enhance robustness. The Support Vector Classifier (SVC) was found to be the best model in terms of both ROC-AUC and F1 score, achieving an ROC-AUC of 0.886 and an F1 Score of 0.633, thereby efficiently discriminating between purchase and non-purchase sessions. We also explore Random Forest, Decision Tree, and Ridge Classifier models to support a more holistic understanding of performance across a variety of complexity and interpretability levels. Importantly, the research also uncovers important behavioral predictors, including product-page engagement and whether the visitor is a returning one, providing interpretable insights that are consistent with real-world e-commerce practices. These results suggest the potential for implementing machine learning models for real-time behavior forecasting in online retail contexts and show that a data-driven pipeline can add value to traditional behavioral modeling counterparts.

Growth and Yield Response of Lettuce (Lactuca sativa) Using MykoPlus and Bio-N Biofertilizers

Shaina Marie Guillermo — 2025-12-14

This study was conducted to determine the growth and yield response of lettuce (Lactuca sativa), variety ‘Black Simpson’, using different amounts of MykoPlus and Bio-N biofertilizer. The experiment consisted of seven treatments: T1 (control), T2 (MykoPlus), T3 (Bio-N), T4 (50% MykoPlus and Bio-N), T5 (MykoPlus + ½ Recommended Rate or RR of synthetic fertilizer), T6 (Bio-N + ½ RR of synthetic fertilizer), and T7 (50% MykoPlus and Bio-N + ½ RR of synthetic fertilizer), arranged in a Randomized Complete Block Design (RCBD) from July to September 2022. Results revealed that T3 (Bio-N), T5 (MykoPlus + ½ RR of synthetic fertilizer), and T6 (Bio-N + ½ RR of synthetic fertilizer) had the best initial plant height response; however, in the final plant height gathered, T3, T4, T6, and T7 gave the best response. In terms of the initial leaf length and leaf width, T5 and T6 had the best responses and were comparable to T3, T4, and T7. In the final leaf length and width of lettuce, T6 and T7 showed the best results and were comparable with T2, T3, T4, and T5. No significant difference was observed in the number of leaves. On the yield parameter, T7 (50% MykoPlus and Bio-N + ½ RR of synthetic fertilizer) provided the highest weight of lettuce at harvest, comparable with T2, T3, T4, T5, and T6. The most feasible biofertilizer combination suitable for lettuce production in terms of growth parameters was T6 and T7, whereas in the yield parameter, application of T7 was recommended.

Comprehensive and Integrated Deep Learning Approaches-based Intelligent Skin Disease Diagnosis System for Pox Detection

Padmaja Bodagala — 2025-12-14

Chickenpox, measles, monkeypox, and smallpox are skin diseases that exhibit very similar signs, making accurate distinction difficult. In this study, an automated deep learning system is developed to classify pox-related skin diseases into six classes, which are Chicken_Pox, Measles, Monkey_Pox, Small_Pox, Normal, and Unknown. The system uses MobileNet to extract features efficiently using a dataset of 4099 training and 1104 evaluation images. The three tested model variants: inception-based CNN, Deep Belief Network, and MobileNet-LSTM-hybrid, Deep Belief Network (DBN) with the SGD optimizer, incurred the best classification accuracy, showing to be more effective at similar tasks to retrieve spatial and temporal features. This will ensure more efficient and quicker detection of the pox, particularly in those regions that do not have specialists in dermatology. Although it is not a replacement for clinical expertise, the system provides a potent instrument in screening and diagnosis of early diseases. The comparative evaluation of these models offers insights into the most effective approach for medical image classification of pox diseases.

Sustainable Organic Vegetable Production in Low-Cost Greenhouses and Post-Harvest Safety: A Community-Based Approach in Phatthalung Province, Thailand

Wanphen Buakong — 2025-12-14

This participatory action research assessed a community model for organic vegetable production using low-cost greenhouse systems among 20 households in Khok Muang sub-district, Phatthalung Province, Thailand. The study evaluated organic vegetable production efficiency and microbial safety involved three parts of research: 1) evaluating organicvegetable production in low-cost greenhouses, 2) detecting fecal coliform and Escherichia coli (E. coli) contamination in fresh vegetable produce and 3) Analysis of contamination of parasite in fresh vegetables; results demonstrated successful knowledge transfer, with participating households reducing monthly vegetable expenses by 55.6 USD while generating a monthly income of 88.6 USD through the cultivation of seven vegetable types annually. Microbiological analysis revealed Coliform contamination in unwashed vegetables at 4.87, 4.55, and 4.18 log CFU/g for Kale (Brassica oleracea L.), Green Oak Lettuce (Lactuca sativa L.), and Chinese cabbage (Brassica sativa var. crispa L.), respectively, with E. coli detected only in Green Oak Lettuce (1.24 log CFU/g). Post-washing, Coliform levels decreased to 3.71, 3.58, and 3.06 log CFU/g, respectively, with no detectable E. coli. Vinegar (100 ppm) treatment significantly reduced Coliform levels by 35.60%. Parasite analysis of three vegetable types across 7 greenhouses found 37.5% of 24 samples contaminated with at least one parasite species, with Green Oak Lettuce showing highest contamination rates. The community model successfully improved household food security and income while highlighting the importance of proper post-harvest handling practices to meet Thai public health standards for commercialising fresh produce.

Enhancing Methane Production from Palm Oil Industry Waste through Thermotolerant Bacterial Bio-augmentation: Optimization and Kinetic Analysis

Sittikorn Saelor — 2025-12-14

This study investigated bio-augmentation strategies to enhance biogas production from palm oil industry residues through thermotolerant anaerobic digestion. Two bacterial strains, Cellulomonas sp. (HD19AZ1) and Themoanaerobacterium thermosaccarolyticum (PSU-2), were evaluated at various inoculum to microorganism (I:S) ratios for both single digestion of empty fruit bunches (EFB) and co-digestion with palm oil mill effluent (POME). Results demonstrated that bio-augmentation significantly improved substrate biodegradability and methane yields. With HD19AZ1, the optimal I:S ratio of 70:10% for single digestion achieved methane yields of 146.38 mL-CH₄/gVS (a 24.94 mL-CH₄/gVS substrate improvement), while the 65:15% ratio for co-digestion yielded 166.55 mL-CH₄/gVS (33.38 m³/tonne substrate improvement). These represented increases of 33.59% and 39.65% in biodegradability for single and co-digestion, respectively. Volatile solids removal reached 41.82% in single digestion and 47.59% in co-digestion under optimal conditions. Kinetic analysis revealed that bio-augmentation with HD19AZ1 achieved methane production rates of 3.90 mL-CH₄/d for single digestion and 6.70 mL-CH₄/d for co-digestion, while PSU-2 augmentation increased rates by 2.14 times compared to control samples. The hydrolysis constant (Kh) ranged from 0.0214-0.0375 d⁻¹ for single digestion and 0.0095-0.0232 d⁻¹ for co-digestion, with lag phases of 5.15-16.11 days and 18.29-43.14 days, respectively. Modified Gompertz modeling confirmed these parameters with R² values exceeding 0.97. This study demonstrates that strategic bio-augmentation with thermotolerant bacteria significantly enhances methane production from palm oil industry waste by improving substrate accessibility and accelerating the hydrolysis of recalcitrant lignocellulosic components, offering promising applications for industrial-scale biogas production.

Utilization of Information and Communication Technology (ICT) Tools Among Masbate Rice Seed Growers

Mohammad D. Dollison — 2025-12-14

This study aimed to determine the awareness, adoption, and utilization of the active rice seed growers of the different ICT-based resources on rice production, their competence and technological capacities to access the different resources, and the recommended practices available for adoption, particularly along: improved agricultural management practices; early warning system and weather updates; and agricultural mechanization. A total of 36 active rice seed growers participated in a series of focus group discussions. Findings revealed that seed growers have a very low level of awareness, competence, and technological capacity in the presence of various ICT-based resources. Some seed growers do not have internet connections due to high connection costs with lower internet speeds. Accordingly, a huge number of rice seed growers were non-adopters, there were very few who adopted the ICT-based resources, particularly in terms of agricultural management practices and experienced the benefits of accessing the resources such as getting prompt answers to pest and disease problems, fertilizer recommendation, characteristics of rice seed varieties and rice seeds that are adaptable in their areas, new technologies in rice farming. They suggested producing IEC materials for seed growers on ICT-based resources on rice and promote technology adoption to farmers to address the lack of awareness; enhancement of internet signal speed by regulating the internet service providers to address the problem; inclusion topic on ICT usage during training/retooling of rice seed growers to address the problem on lack of technical know-how on ICT; provision of tablet to rice seed growers and provision of free internet Wi-Fi for all farmers as solutions to the problems on lack of computer and internet connection at home.

Development of Ultrasonic Extraction Techniques for Bioactive Compounds from Banana Peel Waste: A Comparative Study of Biological Activities

Napattaorn Buachoon — 2025-12-14

Banana peel (Musa spp.), an abundant agricultural by-product, represents a valuable source of bioactive compounds with potential applications in functional food and cosmeceutical industries. This study investigated the influence of ultrasound-assisted extraction (UAE) on total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity, and tyrosinase inhibitory capacity of peel extracts from four economically important cultivars: Cavendish, Bluggoe, Pisang Awak, and Red Dacca. Extraction was conducted using 70% (v/v) aqueous ethanol under ultrasonic conditions at three temperatures (30, 50, and 70 °C) and three time intervals (30, 60, and 120 min). The results demonstrated that Pisang Awak peel extract exhibited the highest TPC (4.63 mg GAE/g extract) and TFC (4.28 mg QE/g extract). Antioxidant capacity evaluated by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays revealed superior activity for Pisang Awak extract (IC₅₀ = 1.27 µg/mL; FRAP = 3.71 mg TE/g extract). This cultivar also demonstrated significant tyrosinase inhibitory activity (IC₅₀= 1.34 mg/mL). Optimization studies identified 50 °C and 60 min as optimal extraction parameters, yielding maximum extraction efficiency across all cultivars. These findings establish UAE as an effective technology for recovering bioactive compounds from banana peel waste, particularly the Pisang Awak cultivar, which shows considerable promise for development into nutraceutical and cosmeceutical formulations. This valorization approach promotes sustainable waste management and circular bioeconomy principles in the agricultural sector.

Exploring the Role of AI in Marketing and Technology Readiness in Enhancing Customer Satisfaction and Business Performance in E-commerce

Taqwa Hariguna — 2025-12-14

This study examines the relationships between technology readiness (TR), AI in marketing (AIM), customer satisfaction (CS), customer performance (CP), customer experience (CE), and financial performance (FP) in the context of Indonesian e-commerce businesses. Using structural equation modeling (PLS-SEM) on survey data from 314 business owners, the study finds strong positive relationships, with CS and CP acting as key mediators. The findings indicate that higher levels of TR significantly enhance CS, which in turn drives improved financial outcomes. Furthermore, the integration of AIM, particularly through personalized marketing tools, was found to have a substantial impact on both customer engagement and financial performance. The Sobel test results confirm that CS serves as a crucial mediator in the relationships between AIM, TR, and FP. This paper contributes to the existing literature by offering a comprehensive model that integrates several key constructs, providing new insights into the intersection of technology adoption and business performance in e-commerce. However, results are limited by convenience sampling and demographic concentration, which constrain generalizability. Practical recommendations emphasize prioritizing staff readiness, adopting AI-powered personalization tools, and actively tracking CS metrics to improve profitability.

A Bibliometric Analysis of Stress Memory and Priming in Plants: Research Trends, Mechanisms, and Implications for Agricultural Resilience

Harry C. Luces — 2025-12-14

This bibliometric analysis explores research trends and collaborative networks surrounding the concepts of "stress memory" and "priming" in plants, with a focus on their implications for agricultural resilience. A total of 270 studies published between 2007 and 2024 were analyzed, revealing a growing interest in this relatively new area of plant science. While the global research output saw a slight decline in 2021, publication activity rebounded in 2024, reaching a peak of 51 documents in 2024. The majority of studies were published in Frontiers in Plant Science, and prominent authors such as Isabel Bäurle contributed significantly to the field. Co-authorship analysis highlighted strong international collaboration, particularly between Germany and China, with Germany emerging as the leading country in both publication volume and collaborative efforts. Keyword analysis indicated that "priming" was the most frequently used term, reflecting its central role in research on plant stress memory. The focus on genetic, epigenetic, and metabolic mechanisms provides valuable insights into how plants "remember" stress and adapt to recurring challenges. These findings underscore the multidisciplinary nature of the field, with contributions from plant physiology, molecular biology, and agricultural sciences. The results emphasize the importance of continued global collaboration and the integration of theoretical and applied research to develop climate-resilient crops. Furthermore, the high proportion of open-access publications highlights the increasing accessibility of this research, fostering wider dissemination and application of findings. This analysis provides a comprehensive understanding of the evolving landscape of stress memory and priming research, offering valuable directions for future studies aimed at enhancing agricultural sustainability and resilience.

Enhanced Thermal Efficiency of Solar Air Heaters Using Porous Material: An Experimental Approach

Eakpoom Boonthum — 2025-12-14

This study presents a detailed experimental investigation into the energy and exergy efficiencies of a double-pass solar air heater (SAH) augmented with porous materials. The primary objective was to assess the impact of integrating steel-based hollow square porous elements, featuring porosities of 0.98 and 0.99, on the thermodynamic performance of the SAH under tropical environmental conditions. A prototype SAH with dimensions of 0.75 m × 1.85 m × 0.25 m was developed and evaluated based on empirical data encompassing solar irradiance, air inlet and outlet temperatures, and mass flow rate. The results demonstrate a significant improvement in both energy and exergy efficiencies with the incorporation of porous materials. Notably, the configuration with 0.98 porosity yielded superior results, with energy efficiencies ranging from 6.19% to 9.01% and a peak exergy efficiency of 0.26%. In comparison, the reference system without porous material exhibited lower average energy and exergy efficiencies of 4.98% and 0.11%, respectively. Furthermore, the porous media contributed to enhanced thermal inertia, leading to improved heat retention and a more stable outlet temperature profile under fluctuating solar irradiance. These findings underscore the thermodynamic advantages of utilizing high-porosity materials within a double-pass SAH, emphasizing their potential for efficient thermal energy conversion in agricultural and industrial drying applications, particularly in regions with high solar potential.

Quality-based assessment of natural ripening agents as alternatives to calcium carbide in ‘Latundan’ banana using mixed statistical methods

Bryl I. Manigo — 2025-12-14

Calcium carbide (CaC₂) is widely utilized for its affordability and efficiency in ripening fruits. However, it poses health risks, which makes natural ethylene-rich alternatives a safer choice. This study evaluated the effectiveness of natural ripening agents such as Gliricidia leaves, Calopo leaves, tomato fruit, and banana peel, as alternatives to CaC₂ in enhancing the postharvest quality of ‘Latundan’ banana (Musa × paradisiaca, AAB Group). Treated fruits were assessed for multiple quality parameters, including peel color, sensory firmness, chemical properties, organoleptic attributes, weight loss, shriveling, visual quality rating, disease incidence, and shelf life. A one-way analysis of variance (ANOVA) was performed to determine treatment effects, followed by Tukey’s HSD test (p ≤ 0.05) for mean separation. For non-normally distributed variables, the Kruskal-Wallis test was applied. To further evaluate treatment similarities based on overall trait performance, hierarchical cluster analysis (HCA) was conducted using Ward’s method and Euclidean distance on standardized trait means. Results showed that CaC₂significantly enhanced ripening characteristics, followed closely by tomato fruit. Natural agents, particularly the leaves of Gliricidia and Calopo, and banana peel, provided moderate improvements across several parameters, while the untreated control consistently ranked lowest. Although CaC₂ induced rapid ripening, it resulted in earlier deterioration and a shorter shelf life. Moreover, HCA revealed three distinct clusters: (1) CaC₂ and tomato fruit, (2) Gliricidia and Calopo leaves, and banana peel, and (3) control. These findings support the use of natural agents, especially tomato fruit, as viable alternatives for inducing uniform ripening and maintaining acceptable postharvest quality in bananas.

Biodegradation of Oil and Grease in Synthetic Wastewater Using Lipase-Producing Bacteria Isolated from University Canteen Wastewater

Pradabduang Kiattisaksiri — 2025-12-14

This study aims to isolate lipase-producing bacteria from university canteen wastewater and assess their effectiveness in the degradation of oil and grease in synthetic wastewater. The results showed that the bacteria isolated from the grease trap wastewater of the central canteen exhibited a bacterial count of 9.3 × 10⁸ CFU/mL. In total, 11 bacterial isolates, labeled A1 to A11, were obtained, displaying six distinct colony morphologies. Lipase-producing bacteria were selected based on the size of the clear zone formed, with isolates A6 and A11 being selected for further evaluation. The effectiveness of these isolates in degrading oil and grease in synthetic wastewater was then assessed. The optimal initial concentration of oil and grease for bacterial degradation was found to be 10,480 mg/L at 32 °C over 40 hours. Bacteria A6 and A11 demonstrated average degradation efficiencies of 24.52% and 18.14%, respectively. Therefore, this study serves as a preliminary laboratory investigation aimed at generating essential data for the potential future applications in treating wastewater contaminated with oil and grease.

Molecular Characterization and Integron Gene Prevalence in Bacterial Pathogens from Neonatal Omphalitis

Rehab Riyadh Raheem — 2025-12-14

Neonatal umbilical cord infections (omphalitis) remain a significant cause of morbidity and mortality in developing countries. This study aimed to characterize bacterial pathogens associated with neonatal omphalitis using both phenotypic and molecular methods, and to determine the prevalence of integron genes. One hundred umbilical swabs were collected from neonates (3-28 days old) with clinical omphalitis. Bacterial identification was performed using conventional culture, the Vitek 2 Compact system, and 16S rRNA gene PCR sequencing. PCR detected integron genes (intI1, intI2, intI3). Phylogenetic analysis was conducted using MEGA X software. Bacterial growth occurred in 48/100 (48%) samples. The predominant isolates were Staphylococcus aureus (14/48, 29.16%), Escherichia coli (14/48, 29.16%), and Pseudomonas aeruginosa (14/48, 29.16%), followed by Enterococcus spp. (4/48, 8.33%) and Bacteroides spp. (2/48, 4.16%). All 24 tested isolates yielded 1500 bp 16S rRNA amplicons. Sequenced P. aeruginosa isolates showed 99-100% identity with GenBank references. Phylogenetic analysis revealed bootstrap values of 63-100% for P. aeruginosa, 99-100% for Enterococcus faecalis and Bacteroides sp., and 32-70% for E. coli. Integron gene prevalence varied significantly, with intI1 being the highest in E. coli (85.71%) and Enterococcus spp. (100%); intI2 predominated in P. aeruginosa (75%) and S. aureus (71.42%); intI3 was detected only in S. aureus (57.14%) and E. coli (28.57%). Gram-positive and Gram-negative bacteria equally contributed to neonatal omphalitis. High integron prevalence, particularly classes 1 and 2, indicates a significant potential for antimicrobial resistance, requiring enhanced surveillance and stewardship strategies.

Surveillance of Rotavirus A Genotypes in Diarrheal Cases from Humans and Bovine in Basra Province, Iraq

Rawaa Bannay Zubairi — 2025-12-14

Rotavirus A (RVA) remains a leading cause of acute gastroenteritis in humans and animals, with potential for zoonotic transmission. Limited molecular surveillance data exist from Iraq regarding circulating genotypes in both populations. This cross-sectional study investigated the prevalence and genotype distribution of RVA in human and bovine diarrheal cases in Basra Province, Iraq. Fifty-four fecal samples, each from humans and bovines with acute diarrhea (≥3 episodes/day within 72 hours), were collected from January to September 2024. A partial VP7 gene segment (897 bp) was amplified using RT-PCR, followed by sequencing and phylogenetic analysis for G-genotype determination. Statistical analysis was employed to assess the relationships between demographic factors and infection rates. RVA prevalence was 22.22% (12/54) in humans and 25.92% (14/54) in bovines. Neither age nor sex showed a significant association with infection rates (P > 0.05, chi-square < 3.841). Based on VP7 sequencing of 26 positive samples, predominant G-genotypes were G6 (38%), G8 (38%), and G2 (23%). Binomial classification revealed G6(P11) (30.8%), G2(P4) (23%), and G8(P8) (15%) as most frequent combinations. In humans, G2 and G8 predominated with P-genotypes P2>P7=P4>P1=P14. In bovines, G6 and G8 were most common, with P11 > P1> P4 = P5 = P8. Notably, G8(P4) was identified as a shared genotype between species, suggesting potential zoonotic transmission. This study demonstrates comparable RVA prevalence in human and bovine populations, with an overlapping genotype distribution, particularly G8 and its associated P-genotypes. These findings support the need for integrated One Health surveillance approaches and consideration of circulating animal genotypes in vaccine formulation strategies for Iraq.

Phenotypic-Genotypic Characterization of Macrolide-Lincosamide-Streptogramin B Resistance in Staphylococcus saprophyticus UTI Isolates from Iraq

Ahlam Ali Soghi Al-Galebi — 2025-12-14

Staphylococcus saprophyticus is a significant uropathogen, particularly in young women. Rising macrolide-lincosamide-streptogramin B (MLSB) resistance poses therapeutic challenges. This study characterized phenotypic and genotypic MLSB resistance patterns among S. saprophyticus UTI isolates in Najaf, Iraq. Forty-two S. saprophyticus isolates were collected from urine samples (February-April 2025) from patients aged 1-70 years. Phenotypic resistance was assessed using the D-test methodology following CLSI guidelines. PCR amplification targeted eight resistance genes: erm(C) and msr(A). Isolates predominantly originated from females (28/42, 66.7%), with the highest frequency in age groups 21-30 (11/42, 26.2%) and 31-40 years (10/42, 23.8%). The D-test revealed that 25/42 (59.5%) isolates exhibited MLSB resistance: 9/42 (21.4%) demonstrated an inducible MLSB (iMLSB) phenotype, 16/42 (38.1%) exhibited a constitutive MLSB (cMLSB) phenotype, and 8/42 (19.0%) displayed a macrolide-streptogramin B (MS) phenotype, while 9/42 (21.4%) were MLSB-negative. Molecular analysis detected resistance genes in only 9 of 25 (36%) phenotypically MLSB-positive isolates. The erm(C) gene alone was present in 2/25 (8%) isolates, while erm(C)+msr(A) combination dominated at 7/25 (28%). High MLSB resistance prevalence (59.5%) among S. saprophyticus isolates, with cMLSB predominance and significant genotype-phenotype discordance (64% phenotypically positive lacking detected genes), emphasizes the necessity for routine D-testing and expanded molecular surveillance to guide antimicrobial therapy in Iraqi healthcare settings.