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Sobre

Sobre

Aníbal Silva (Filipe Monteiro-Silva) licenciou-se em Química (2008) pela Faculdade de Ciências da Universidade do Porto (Portugal) e mais tarde obteve o seu mestrado, também em Química (2010), nessa mesma instituição.

Foi membro activo do CIQ-UP até 2013, REQUIMTE-LAQV de 2013-2014 e é desde então colaborador ativo do Centro de Fotónica Aplicada (CAP) do INESC TEC. Esteve envolvido em projetos internacionais como SNIFFER (SeNsory devIces network For Food supply chain sEcuRity) e AGRINUPES (Integrated monitoring and control of water, nutrients and plant protection products towards a sustainable agricultural sector), projetos nacionais como CORAL (Sustainable Ocean Exploitation: Tools and Sensors) e Smart Fertilizers. O seu trabalho tem como objectivo aumentar a eficiência da fertilização, para maior competitividade e melhoria operacional do sector primário, em nome dum aumento da segurança alimentar da sociedade, equalização no acesso a ferramentas de produtividade agrícola e em linha com a Agenda 2030 das Nações Unidas para os Objectivos de Desenvolvimento Sustentável 2, 6 e 12.

Foi distinguido com o Prémio BIP Proof 2020-2021 (Business Ignition Programme) - pela Universidade do Porto, Banco Santander Portugal e Fundação Amadeu Dias, e com o Prémio Inovação 8ª Edição (2020-2021) do Crédito Agrícola, na categoria “Categoria Agroindústria 4.0”.

Os seus interesses de pesquisa/áreas de especialização giram em torno de síntese orgânica, (bio)sensores químicos, cromatografia, com foco especial recente na sinergia entre fotónica e inteligência artificial.

Tópicos
de interesse
Detalhes

Detalhes

005
Publicações

2023

Antimicrobial Effects and Antioxidant Activity of Myrtus communis L. Essential Oil in Beef Stored under Different Packaging Conditions

Autores
Moura, D; Vilela, J; Saraiva, S; Monteiro-Silva, F; De Almeida, JMMM; Saraiva, C;

Publicação
FOODS

Abstract
The aim of this study was to assess the antimicrobial effects of myrtle (Myrtus communis L.) essential oil (EO) on pathogenic (E. coli O157:H7 NCTC 12900; Listeria monocytogenes ATCC BAA-679) and spoilage microbiota in beef and determine its minimum inhibitory concentration (MIC) and antioxidant activity. The behavior of LAB, Enterobacteriaceae, Pseudomonas spp., and fungi, as well as total mesophilic (TM) and total psychotropic (TP) counts, in beef samples, was analyzed during storage at 2 and 8 C-degrees in two different packaging systems (aerobiosis and vacuum). Leaves of myrtle were dried, its EO was extracted by hydrodistillation using a Clevenger-type apparatus, and the chemical composition was determined using chromatographical techniques. The major compounds obtained were myrtenyl acetate (15.5%), beta-linalool (12.3%), 1,8-cineole (eucalyptol; 9.9%), geranyl acetate (7.4%), limonene (6.2%), alpha-pinene (4.4%), linalyl o-aminobenzoate (5.8%), alpha-terpineol (2.7%), and myrtenol (1.2%). Myrtle EO presented a MIC of 25 mu L/mL for E. coli O157:H7 NCTC 12900, E. coli, Listeria monocytogenes ATCC BAA-679, Enterobacteriaceae, and E. coli O157:H7 ATCC 35150 and 50 mu L/mL for Pseudomonas spp. The samples packed in aerobiosis had higher counts of deteriorative microorganisms than samples packed under vacuum, and samples with myrtle EO presented the lowest microbial contents, indicating good antimicrobial activity in beef samples. Myrtle EO is a viable natural alternative to eliminate or reduce the pathogenic and deteriorative microorganisms of meat, preventing their growth and enhancing meat safety.

2023

Reagent-less spectroscopy towards NPK sensing for hydroponics nutrient solutions

Autores
Silva, FM; Queirós, C; Pinho, T; Boaventura, J; Santos, F; Barroso, TG; Pereira, MR; Cunha, M; Martins, RC;

Publicação
SENSORS AND ACTUATORS B-CHEMICAL

Abstract
Nutrient quantification in hydroponic systems is essential. Reagent-less spectral quantification of nitrogen, phosphate and potassium faces challenges in accessing information-rich spectral signals and unscrambling interference from each constituent. Herein, we introduce information equivalence between spectra and sample composition, enabling extraction of consistent covariance to isolate nutrient-specific spectral information (N, P or K) in Hoagland nutrient solutions using orthogonal covariance modes. Chemometrics methods quantify nitrogen and potassium, but not phosphate. Orthogonal covariance modes, however, enable quantification of all three nutrients: nitrogen (N) with R = 0.9926 and standard error of 17.22 ppm, phosphate (P) with R = 0.9196 and standard error of 63.62 ppm, and potassium (K) with R = 0.9975 and standard error of 9.51 ppm. Including pH information significantly improves phosphate quantification (R = 0.9638, standard error: 43.16 ppm). Results demonstrate a direct relationship between spectra and Hoagland nutrient solution information, preserving NPK orthogonality and supporting orthogonal covariance modes. These modes enhance detection sensitivity by maximizing information of the constituent being quantified, while minimizing interferences from others. Orthogonal covariance modes predicted nitrogen (R = 0.9474, standard error: 29.95 ppm) accurately. Phosphate and potassium showed strong interference from contaminants, but most extrapolation samples were correctly diagnosed above the reference interval (83.26%). Despite potassium features outside the knowledge base, a significant correlation was obtained (R = 0.6751). Orthogonal covariance modes use unique N, P or K information for quantification, not spurious correlations due to fertilizer composition. This approach minimizes interferences during extrapolation to complex samples, a crucial step towards resilient nutrient management in hydroponics using spectroscopy.

2023

LIBS-Based Analysis of Elemental Composition in Skin, Pulp, and Seeds of White and Red Grape Cultivars

Autores
Tosin, R; Monteiro Silva, F; Martins, R; Cunha, M;

Publicação
CSAC 2023

Abstract

2022

Point-of-Care Using Vis-NIR Spectroscopy for White Blood Cell Count Analysis

Autores
Barroso, TG; Ribeiro, L; Gregorio, H; Monteiro Silva, F; dos Santos, FN; Martins, RC;

Publicação
CHEMOSENSORS

Abstract
Total white blood cells count is an important diagnostic parameter in both human and veterinary medicines. State-of-the-art is performed by flow cytometry combined with light scattering or impedance measurements. Spectroscopy point-of-care has the advantages of miniaturization, low sampling, and real-time hemogram analysis. While white blood cells are in low proportions, while red blood cells and bilirubin dominate spectral information, complicating detection in blood. We performed a feasibility study for the direct detection of white blood cells counts in canine blood by visible-near infrared spectroscopy for veterinary applications, benchmarking current chemometrics techniques (similarity, global and local partial least squares, artificial neural networks and least-squares support vector machines) with self-learning artificial intelligence, introducing data augmentation to overcome the hurdle of knowledge representativity. White blood cells count information is present in the recorded spectra, allowing significant discrimination and equivalence between hemogram and spectra principal component scores. Chemometrics methods correlate white blood cells count to spectral features but with lower accuracy. Self-Learning Artificial Intelligence has the highest correlation (0.8478) and a small standard error of 6.92 x 10(9) cells/L, corresponding to a mean absolute percentage error of 25.37%. Such allows the accurate diagnosis of white blood cells in the range of values of the reference interval (5.6 to 17.8 x 10(9) cells/L) and above. This research is an important step toward the existence of a miniaturized spectral point-of-care hemogram analyzer.

2021

Antimicrobial Activity of Myrtus communis L. and Rosmarinus officinalis L. Essential Oils against Listeria monocytogenes in Cheese

Autores
Saraiva, C; Silva, AC; Garcia Diez, J; Cenci Goga, B; Grispoldi, L; Silva, AF; Almeida, JM;

Publicação
FOODS

Abstract
Listeria monocytogenes has been referred to as a concern microorganism in cheese making due to its ability to survive and grow in a wide range of environmental conditions, such as refrigeration temperatures, low pH and high salt concentration at the end of the production process. Since cheese may be a potential hazard for consumers, especially high-risk consumers (e.g., pregnant, young children, the elderly, people with medical conditions), efforts of the dairy industry have been aimed at investigating new conservation techniques based on natural additives to meet consumers' demands on less processed foods without compromising the food safety. Thus, the aim of this study was to evaluate the efficacy of Myrtus communis L. (myrtle) and Rosmarinus officinalis L. (rosemary) essential oils (EO) against Listeria monocytogenes ATCC 679 spiked in sheep cheese before ripening. After the cheesemaking process, the samples were stored at 8 degrees C for 2 h, 1 d, 3 d, 14 d and 28 d. The composition of EO was identified by gas chromatography-mass spectrometry (GC-MS) analysis. Constituents such as 1,8-cineole, limonene, methyl-eugenol, alpha-pinene, alpha-terpineol, alpha-terpinolene and beta-pinene were present in both EO, accounting for 44.61% and 39.76% from the total of chemical compounds identified for myrtle and rosemary EO, respectively. According to the chemical classification, both EO were mainly composed of monoterpenes. Minimum inhibitory concentration (MIC) against L. monocytogenes was obtained at 31.25 mu L/mL to myrtle EO and at 0.40 mu L/mL to rosemary EO. Then, cheeses were inoculated with L. monocytogenes (Ca. 6 log CFU/mL) and EO was added at MIC value. The addition of rosemary and myrtle EO displayed lower counts of L. monocytogenes (p < 0.01) (about 1-2 log CFU/g) during the ripening period compared to control samples. Ripening only influences (p < 0.001) the growth of L. monocytogenes in control samples. Since rosemary and myrtle EO do not exert any negative impact on the growth of native microflora (p > 0.05), their use as natural antimicrobial additives in cheese demonstrated a potential for dairy processors to assure safety against L. monocytogenes.