CBQF - Contribuições em Revistas Científicas / Contribution to Journals
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- Active bio-based packaging for fresh-cut melon: antimicrobial efficacy and zinc migration of nanocellulose/ZnO nanocomposite filmsPublication . Mendes, Ana Rita; Silva, Francisco A. G. Soares; Mena, Cristina; Silva, Fátima; Silva, Cristina L. M.; Teixeira, Paula; Poças, FátimaGrowing environmental concerns, together with the need to extend shelf life and protect food from pathogens and mechanical damage, are driving the development of innovative active packaging materials. In this study, nanocellulose (NC) films incorporating zinc oxide nanoparticles (ZnO NPs) with three different morphologies (spherical, sheet and flower) were produced by solvent casting for food packaging applications. Films were characterised by scanning electron microscopy (SEM), and antimicrobial activity was addressed by agar diffusion assay against Escherichia coli and Staphylococcus aureus. NC/ZnO films were used as package for fresh-cut melon, which was stored at 4 °C for one week, and subjected to microbiological, pH and zinc migration analysis. SEM revealed a porous, and nanofibrillar cellulose, suitable for NP retention, while cross sections showed the dispersion of NPs among the films. In vitro antimicrobial studies demonstrated the influence of morphology, with the sheet shape producing the highest inhibitory halos. In contact with melon, NC/ZnO films suppressed microbial proliferation relative to controls, keeping microbiological levels within acceptable limits up to day 7. Sheet shape showed the most significant effect. Total Zn migration plateaued at 7–8 mg kg-1 under a realistic area-to-mass scenario, with no significant differences among morphologies. Measurements reflect total Zn after acid digestion and ionic versus particulate species could not be distinguished. NC/ZnO films maintained slightly higher pH than controls. Overall, these findings highlight the potential of bio-based NC/ZnO films to extend melon shelf life, with antimicrobial efficacy strongly influenced by nanoparticle morphology.
- Development of a greener flow-based analytical tool for the expeditious determination of total soluble proteinsPublication . Teixeira, Raquel; Ribas, Tânia C. F.; Almeida, André; Pintado, Manuela; Rangel, António O. S. S.Protein hydrolysates are increasingly used in feed, underscoring the need for analytical tools for the rapid, reliable determination of total protein. This study revisited a merging-zones flow-based spectrophotometric method for minimizing reagent consumption and employs the Biuret reaction for the quantification of total soluble protein in by-products hydrolysates. The analytical method was optimized across different physical and chemical parameters such as: flowrate, reactor length, sample injection volume and reagents concentration. The use of different matrices relevant in the hydrolysis processes (acetate, phosphate, and hydrochloric acid) showed no significant interference (
- Seasonal effect on the biochemical composition of Atlantic seaweeds cultivated in integrated multitrophic aquaculturePublication . Mendes, Madalena Caria; Conde, Tiago; Moreira, Ana S. P.; Lopes, Diana; Pais, Ana Rita; Batista, Joana; Neves, Mariana; Salvador, Maria; Ferreira, Andreia S.; Oliveira, Kayane; Conde, Alexandra; Coelho, Marta; Rocha, Helena R.; Gomes, Ana M.; Pintado, Manuela E.; Oliveira, Inês; Martins, Margarida; Ventura, Sónia P. M.; Nunes, Claúdia; Coimbra, Manuel A.; Abreu, Helena; Ramos, Ana; Pereira, Hugo; Domingues, M. RosárioSeaweeds are recognized as sustainable food sources rich in nutrients and bioactive compounds, but their composition is highly influenced by seasonality. This study evaluated the biochemical profiles of Ulva sp., Fucus vesiculosus, Porphyra dioica, and Palmaria palmata cultivated in integrated multitrophic aquaculture across different seasons. Results showed marked seasonal and species-specific fluctuations. Porphyra exhibited the highest protein content, except in spring. Ulva was richer in lipids and magnesium across all seasons. Palmaria displayed lowest sodium-to-potassium ratios (<1), considered beneficial in reducing the risk of cardiovascular diseases. The distinct seasonal shifts in carbohydrate composition suggest each species adapts its polysaccharide metabolism. All species contained relevant essential amino acids and essential fatty acids contents. Red seaweeds showed high content of omega-3 eicosapentaenoic acid and phycobiliproteins, highlighting their functional potential. These findings demonstrate that seasonal variability shapes the nutritional and bioactive composition of seaweeds, offering opportunities to optimize biomass production for targeted applications.
- Machine learning-based stratification of chagas heart failure severity using ECG power spectral biomarkersPublication . Ribeiro, Pedro; Marques, João Alexandre Lobo; Barbosa, Maria Inês; Pedrosa, Roberto C.; Madeiro, João Paulo do Vale; Rodrigues, Pedro MiguelPurpose This study presents a machine learning methodology to automatically classify heart failure severity in Chagas disease (CD) patients using non-invasive 24-hour ECG-Holter signals. Methods Following American Heart Association (AHA) guidelines, the cohort was stratified into three Left Ventricular Ejection Fraction (LVEF)-based severity groups: Normal (LVEF ≥ 0.50, n=197), Moderate (0.40 ≤ LVEF < 0.50, n=106), and Severe (LVEF < 0.40, n=77), totaling N=380 patients. From short 10-second ECG segments, we extracted eleven spectral features derived from the power spectral density (PSD). Class imbalance was addressed through oversampling applied to the training folds. All classifiers were evaluated over 50 random stratified train-test splits (80/20) across three pairwise tasks (Normal vs. Moderate, Normal vs. Severe, Moderate vs. Severe). Results Analysis revealed a consistent leftward shift in PSD, with increased low-frequency power in more severe cases, consistent with morphological ECG changes including P-wave attenuation, QRS alterations, and ST-segment shifts. Using this spectral biomarker, the best models achieved mean AUC/PR-AUC values of 0.79/0.76 for Normal vs. Severe and 0.83/0.85 for Moderate vs. Severe across 50 random states. The Normal vs. Moderate task showed moderate separability (AUC = 0.75, PR-AUC = 0.72). Conclusion These findings highlight the potential of power spectral ECG analysis as a low-cost, fully automated tool for risk stratification in CD. The methodology shows promise for improving triage and clinical decision-making in resource-limited settings where CD remains highly prevalent.
- High-throughput phenotyping for revealing key morpho-physiological traits for drought tolerance in pea (Pisum sativum and wild relatives)Publication . Bagheri, Maryam; van de Zedde, Rick; Rubiales, Diego; Santos, Carla S.; Vasconcelos, Marta W.Pea (Pisum sativum) production is challenged by drought stress. Traditional methods for assessing drought tolerance are limited,and high-throughput phenotyping (HTP) can facilitate the rapid and automated assessment of plant traits. Herein, 180 Pisumspp. accessions were evaluated using an indoor HTP platform under two irrigation treatments, control (70% field capacity) anddrought stress (30% field capacity), for 50 days. A combination of digital phenotyping via imaging and manual measurements wasused to analyse biomass-related, architectural, and physiological traits. Drought conditions resulted in significant reductions inbiomass-related traits including fresh weight (47%), total leaf area (43%), and dry weight (41%). In contrast, PSII photochemicalefficiency, leaf weight ratio, and solidity showed negative sensitivity index values (ranging from −7% to −1%), indicating com-paratively lower sensitivity to drought and suggesting relative stability of these traits under water-limited conditions. The highheritability value for water use efficiency (0.87) suggests that this parameter may be useful for distinguishing pea's responsesto suboptimal soil moisture levels. Principal component analysis (PCA) highlighted patterns of trait variation and associationsamong biomass-related traits, such as fresh weight, dry weight, and leaf area, which were sensitive to drought conditions. Thissuggests that the plants may use a combination of strategies to cope with water limitations. Furthermore, studying the significantvariation in drought response among the diverse Pisum species and subspecies revealed distinct adaptation strategies. Thesefindings support the development of crops that are resilient to the negative effects of climate change.
- Exploring textile fibre characterisation: a review of vibrational spectroscopy and chemometricsPublication . Santos, Diva; Teixeira, A. Margarida; Sousa, M. Leonor; Marinho, Andréa; Sousa, ClaraThe identification/classification of textile fibres is essential in manufacturing, forensic science, cultural heritage preservation, and recycling. Conventional methods, including solubility tests, optical microscopy, and chromatographic techniques, are often destructive, labour-intensive, and limited in scope. Vibrational spectroscopy, particularly near-infrared (NIR), Fourier-transform infrared (FTIR), and Raman spectroscopy, has emerged as a rapid, non-destructive, and accurate alternative for fibre analysis. However, multi-composition textiles, dyes, finishing agents, and ageing effects frequently cause overlapping spectral features, hampering direct interpretation. This review examines the combined use of vibrational spectroscopy and chemometrics for textile fibre discrimination. It critically evaluates the performance of different spectroscopic techniques in classifying natural, synthetic, and blended fibres. The role of multivariate analysis methods, such as PCA, PLS, LDA, SIMCA, and machine learning algorithms, in improving spectral interpretation and classification accuracy is highlighted. Key factors affecting model robustness, including spectral pre-processing, sample heterogeneity, moisture, and colour, are also discussed. The integration of spectroscopy with chemometrics provides a robust, scalable, and sustainable solution for fibre identification, supporting quality control, fraud detection, and circular economy initiatives. This approach demonstrates significant potential for both research and industrial applications.
- FTIR-based machine learning identification of virgin and recycled polyester for textile recycling in industry 4.0Publication . Barbosa, Maria Inês; Teixeira, Ana Margarida; Sousa, Maria Leonor; Ribeiro, Pedro; Sousa, Clara; Rodrigues, Pedro MiguelAdvances in Industry 4.0 manufacturing have accelerated the adoption of machine learning (ML) for automated classification. Polyester (PES), a widely used synthetic fiber, competes with natural fibers like cotton and other synthetics, highlighting the need for continuous research and improvement. In the textile sector, distinguishing recycled polyester (rPES) from virgin polyester (vPES) remains challenging due to overlapping chemical signatures and material variability. A combination of Fourier transform infrared (FTIR) spectroscopy and ML has not been explored for this purpose. In this study, we evaluated ML models to discriminate three PES fiber types (45 vPES, 65 rPES, and 55 mixed PES) using 165 FTIR spectra across four spectral regions, R1, R2, R3, and R4, as well as their combined representation. Six ML approaches were tested on data reduced with fast independent component analysis (FastICA) (1–30 components) using an 80/20 train–test dataset split. The Decision Tree classifier achieved the highest Accuracy in four of the five spectral evaluations, with classification accuracies ranging from 66.67% to 77.78% for region R4, which also had a balanced classification profile with an area-under-the-curve (AUC) value of 0.81. Notably, despite the moderate overall Accuracy, the model achieved 100% discrimination of rPES when distinguishing it from both mixed and vPES. Mixed fibers remained the most difficult to classify, highlighting the need for improved feature representation.
- Sharing of bacteria between water and plants in wastewater treatment and hydroponic productionPublication . Teixeira, A. Margarida; Teixeira, Paula; Manaia, Célia M.Aims: To assess bacterial sharing between plants and their water environments by identifying bacteria present both in surrounding water and as plant endophytes in soft rush (Juncus effusus) grown in a full-scale floating wastewater treatment wetland, lettuce (Lactuca sativa) or cress (Lepidium sativum) in commercial hydroponic production systems, and lettuce seeds germinated in tap water inoculated with a blaKPC-positive Escherichia coli strain. Methods and results: The microbiological analysis included enumeration of coliforms and total heterotrophic bacteria, quantification of the genes 16S rRNA, intI1, and uidA, and bacterial community analysis based on 16S rRNA gene metabarcoding. Of the bacterial genera identified in wastewater (n = 2220) and water (n = 1631 cress; n = 1170 lettuce), at least a quarter were also detected as endophytes in roots, and mainly belonged to the phylum Pseudomonadota. The genes uidA and intI1 were significantly more prevalent (∼1 log-unit/16S rRNA gene) in wastewater than in soft rush roots. In the hydroponic systems, the gene uidA was not detected and the gene intI1, detected in cress but not in lettuce, was significantly more prevalent in water (∼1 log-unit/16S rRNA gene) than in the roots. In lettuce seeds germinated in tap water inoculated with E. coli, uptake values of 11%–48% of the gene blaKPC were observed. Conclusions: These results suggest that plants share a significant proportion of the bacteria thriving in their external environment, highlighting the importance of microbiological water quality. Antibiotic-resistant bacteria or pathogens can be taken up alongside with natural microbiota, a potentially critical human health hazard for edible crops.
- International Code of Nomenclature of Prokaryotes. Prokaryotic Code (2025 Revision)Publication . Oren, Aharon; Arahal, David R.; Christensen, Henrik; Göker, Markus; Manaia, Célia M.; Moore, Edward R. B.
- Nitrite reduction in cooked ham: an organoleptic and food safety concern?Publication . Nunes, Maria J. M.; Pereira, Rui C.; Noronha, Lúcia; Cruz, Inês; Komora, Norton; Barbosa, Joana Bastos; Monteiro, Maria João P.; Ribas, Tânia C. F.; Mesquita, Raquel B. R.; Rangel, António O. S. S.; Carvalho, Fátima; Brandão, Teresa R. S.; Teixeira, PaulaCooked meat products, particularly ham, are widely consumed, and reducing nitrite levels has become a priority due to health concerns and regulatory pressure. This study evaluated the microbiological safety, technological performance, physicochemical properties, and sensory attributes of whole cooked ham formulated with reduced nitrite (from 150 to 80 ppm) during shelf life. Microbiological analyses were conducted every 15 days, including total viable counts (TVC), lactic acid bacteria (LAB), Enterobacteriaceae, Staphylococcus aureus and Escherichia coli. TVC and LAB remained below the safety threshold (<104 CFU/g), while all other parameters were below detection limits. Sulphite reducing Clostridium spores, Salmonella spp. and Listeria monocytogenes were absent from all samples. Challenge testing with L. monocytogenes and Clostridium sporogenes was performed to assess the product's ability to inhibit pathogen growth under simulated storage conditions (up 35 and 90 days, respectively) and temperature abuse conditions (8 °C). The reduced-nitrite ham formulation effectively inhibited the growth of C. sporogenes and delayed the growth of L. monocytogenes. Technological assessments included colour measurements, water retention capacity, and texture profile analysis (TPA), with no significant differences observed between the standard and nitrite reduced formulations (P > 0.05). Physicochemical parameters such as pH (6.0–6.2), water activity (aw, 0.9669–0.9482), and residual nitrite content (4 to 1 mg/kg) were evaluated at 0, 45 and 90 days. These findings demonstrate that reducing nitrite levels to 80 ppm can ensure the product safety and quality, as evidenced by stable physicochemical properties and the preservation of sensory characteristics such as appearance, odour, texture, and flavour.