Centre for the Research and Technology of Agro-Environmental and Biological Sciences

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Organizational Unit

Publications

Lidocaine supplementation in clove-oil and 2-phenoxyethanol anesthesia for gilthead seabream (Sparus aurata)

Publication . Tchobanov, Carolina F.; Vaz, Mariana; Pires, Damiana; Passos, Ricardo; Antunes, Luís M.; Baptista, Teresa

Animal welfare and reducing stress during procedures are key objectives for success in animal production. Anesthesia has been used for procedures to reduce animal stress and its negative impact on welfare. This study aimed first to refine the concentrations of the anesthetic clove-oil (CO) and lidocaine (L) in gilthead seabream (Sparus aurata) juveniles (56.0 ± 15.09 g) and then combine clove-oil and 2-phenoxyethanol (2PHE) with the refined concentration of lidocaine. The concentrations of clove-oil (30, 45, and 60 mg L− 1), and the concentrations of lidocaine (2.5, 5, and 7.5 mg L− 1), were evaluated in the refinement trial. Based on these results, a second trial was performed with 45 mg L− 1 CO or 0.4 mL L− 1 2PHE as anesthetics alone or combined with 2.5 mg L− 1 of lidocaine. Results from this work showed an improvement in induction times for 2-phenoxyethanol when lidocaine was added (2PHE 179.53 ± 63.21 s; 2PHE + L 130.65 ± 40.16 s). Recovery time also showed a reduction for clove-oil when lidocaine was used (CO 349.90 ± 123.69 s; CO + L 250.11 ± 51.99 s). The use of lidocaine showed better results, reducing lactate and histological progressive alterations. Lidocaine showed stress-induced oxidative alterations when it was combined with 2-phenoxyethanol. Lidocaine exposure increased ALT, AST, histological regressive alterations for both anesthetics, and gene expression of hsp70 in the gills when clove-oil was used. Further studies are necessary to comprehend the synergistic effects of lidocaine when combined with synthetic and natural anesthetics and to discern potential acute or chronic toxic responses in fish. These insights will be crucial for refining anesthesia protocols and ensuring the well-being of aquatic species in aquaculture practices and research settings.

2024-08Journal article

Open access

A Near-Real-Time Operational Live Fuel Moisture Content (LFMC) Product to Support Decision-Making at the National Level

Publication . Benali, Akli; Baldassarre, Giuseppe; Loureiro, Carlos; Briquemont, Florian; Fernandes, Paulo M.; Rossa, Carlos; Figueira, Rui

Live fuel moisture content (LFMC) significantly influences fire activity and behavior over different spatial and temporal scales. The ability to estimate LFMC is important to improve our capability to predict when and where large wildfires may occur. Currently, there is a gap in providing reliable near-real-time LFMC estimates which can contribute to better operational decision-making. The objective of this work was to develop near-real-time LFMC estimates for operational purposes in Portugal. We modelled LFMC using Random Forests for Portugal using a large set of potential predictor variables. We validated the model and analyzed the relationships between estimated LFMC and both fire size and behavior. The model predicted LFMC with an R2 of 0.78 and an RMSE of 12.82%, and combined six variables: drought code, day-of-year and satellite vegetation indices. The model predicted well the temporal LFMC variability across most of the sampling sites. A clear relationship between LFMC and fire size was observed: 98% of the wildfires larger than 500 ha occurred with LFMC lower than 100%. Further analysis showed that 90% of these wildfires occurred for dead and live fuel moisture content lower than 10% and 100%, respectively. Fast-spreading wildfires were coincident with lower LFMC conditions: 92% of fires with rate of spread larger than 1000 m/h occurred with LFMC lower than 100%. The availability of spatial and temporal LFMC information for Portugal will be relevant for better fire management decision-making and will allow a better understanding of the drivers of large wildfires.

2025-04-30Journal article

Open access

Funding agency

Fundação para a Ciência e a Tecnologia

Funding programme

6817 - DCRRNI ID

Funding Award Number

UIDP/04033/2020