Search Results (521)

Background: Conventional practices for the cultivation of “Cipollotto Nocerino” spring onion are mainly based on growers’ experience, and up to 250 kg/ha for N is commonly furnished among growing cycles. Facing the issue of reduced availability of natural resources for crop production (for example mineral resources), we investigated the optimization of the productivity. Methods: In our research, we tested the use of depletion nutrient supply strategy (CAL-FERT^®) to enhance fertilization in accordance with the principle of sustainable agriculture included in the Farm to Fork strategy. In our study, besides the common initial fertilization, three different strategies for cover fertilizations have been elaborated with the support of CAL-FERT^® software. The treatments were as follows: (i) commercial standard fertilization as control (named CF); (ii) fertilization equivalent to 50% of the N applied in the control (named F-50); (iii) fertilization corresponding to 25% of the N applied in the control (named F-25); and (iv) strongly reduced fertilization compared to the control (named F-0). The parameters investigated included the following: plant height, yield, SPAD index, nitrogen use efficiency, dry matter, soluble solid content, and pyruvate contents in bulbs and leaves. Nitrogen content was also analyzed for both hypogeous and epigeous apparatuses. Results: Among the most interesting vegetative results, plant height and SPAD readings were reduced only by the extreme treatment F-0 compared with the other treatments at 104 days after planting. Regarding qualitative and productive parameters, the treatments F-50 and F-25 showed the highest yield without prejudging Soluble Solid Content and reducing pungency. Conclusion: In nutritional experiments, onion could be considered as a crop model to investigate quality in vegetables due to its consumption as fresh product and for its particular response, in terms of yield and quality, to fertilization. The use of simulation software can support the identification of strategies to reduce the nutrient supply without any detrimental effect on yield and other vegetative and qualitative parameters in onion crops. Full article

This study evaluated the effects of dietary supplementation with omega-3 polyunsaturated fatty acids from extruded linseed, alone and combined with Padina pavonica algae extract, on growth performance and metabolic status in fattening rabbits. Sixty New Zealand White rabbits were assigned to three groups, as follows: control (CNT), L (5% linseed), and LPP (3.5% linseed + 0.2% algae extract) from weaning (37 days) to slaughter (85 days). Productive performance was assessed through body weight (BW), average daily gain (ADG), feed conversion ratio (FCR), and feed intake (FI). Blood was sampled at weaning, 60 days, and slaughter and analyzed for insulin, leptin, cortisol, thyroid hormones (T3, T4), glucose, and non-esterified fatty acids (NEFAs). The L group showed significantly higher ADG (41.0 ± 1 g/d) and improved FCR (4.1 ± 0.2) compared to LPP (ADG: 37 ± 1 g/d, FCR: 4.6 ± 0.2; p = 0.001). No differences were observed in final BW or FI among groups (p < 0.001). Insulin peaked at 60 days across all groups (p < 0.001), with the LPP group showing the lowest levels (9.8 ± 0.9 µUI/mL; p = 0.043). T3 and T4 increased significantly with age (p < 0.001), and the T3/T4 ratio varied by diet and time (p = 0.005). Cortisol rose only at slaughter (p < 0.001) and negatively correlated with insulin and thyroid hormones. The results suggest that omega-3-rich nutraceuticals can enhance growth performance without disrupting metabolic balance and may modulate specific hormonal responses due to their bioactive compounds. Full article

The growing concern for environmental sustainability has led to an increased interest in biodegradable materials derived from renewable resources. This study explores the innovative use of residual biomass from the green photosynthetic microalga Chlamydomonas reinhardtii, left over after polysaccharide extraction, as a natural filler in the development of the compostable protein-based material SP-Milk^®. The microalgal biomass was characterized using Fourier transform infrared spectroscopy (FTIR) and UV-Visible Spectroscopy to assess its chemical and structural composition. Subsequently, it was incorporated into a biodegradable protein matrix, and the resulting biocomposites were evaluated for mechanical and thermal properties. The results demonstrate that the incorporation of algal filler improves the mechanical strength and elasticity of the material while reducing its glass transition temperature, highlighting its potential for use in sustainable applications as a possible substitute for conventional plastics. The biocomposite materials developed, based on the protein-based material SP-Milk^® and residual microalgal biomass, are environmentally friendly, contributing to the reduction in pollution and the risks associated with plastic accumulation. Thus, this study offers a simple, effective, and sustainable strategy for the valorization of microalgal biomass, enabling the production of biodegradable materials with enhanced mechanical performance, suitable for applications such as sustainable packaging within a circular economy framework. Full article

Circular economy in the context of municipal organic waste management has boosted the emergence of novel composting scenarios, such as community composting and decentralized urban composting in small installations, which favors localized management and valorization of organic waste streams. However, there is little information about the agronomic use of the composts obtained from these new organic waste management systems as an alternative for inorganic fertilization in crop production. In this work, municipal solid waste-derived composts from two decentralized composting scenarios (CM1 and CM2 from community composting, and CM3 and CM4 from decentralized urban small-scale composting plants) were applied and mixed in the top layer of a calcareous clayey-loam soil to assess their effects as alternative substitutes for conventional soil inorganic fertilization (IN) during two successive cultivation cycles of lettuce (Lactuca sativa L.) grown in pots with the amended soils. These treatments were also compared with an organic waste (goat–rabbit manure, E) and a control treatment without fertilization (B). The effects of the fertilizing treatments on the crop yield and quality, as well as on the properties of the soil considered were studied. In general, the application of the different composts did not produce negative effects on lettuce yield and quality. The compost-derived fertilization showed similar lettuce yields compared to the inorganic and manure-derived fertilizations (IN and E, respectively), and higher yields than the soil without amendment (B), with increases in the initial yield values of B, for the first cycle from 34.2% for CM1 to 53.8% for CM3, and from 20.3% for CM3 to 92.4% for CM1 in the second cycle. Furthermore, the organically amended soils showed a better crop development, obtaining higher values than the control treatment in the parameters studied. In addition, the incorporation of the organic treatments improved the soil characteristics, leading to 1.3 and 1.2 times higher organic matter contents in the soils with CM2 and in the soils with CM1, CM3, and E, respectively, compared to the control soil without fertilizing treatment (B), and 2.0 and 1.8 times greater organic matter contents, respectively, compared to soil with inorganic fertilization (IN). Therefore, the use of municipal solid waste-derived composts from these new organic waste management systems, such as the decentralized composting scenarios studied (community composting and urban decentralized small-scale composting plants), is presented, not only as a sustainable valorization method, but also as an alternative for the use of inorganic fertilizers in lettuce cultivation, while enhancing soil properties, contributing to increasing the circularity of agriculture. Full article

Marine archaea play crucial roles in global biogeochemical cycles and climate regulation, yet their ecological functions in many coastal environments remain poorly understood. Jinhae Bay (JB), a eutrophic and environmentally stressed coastal system in Korea, has attracted growing attention; however, its archaeal community composition has not been characterized. In this preliminary study, we investigated the summer archaeal community structure in JB water columns based on a survey conducted in July 2018. We identified 5 archaeal phyla—primarily Euryarchaeota and Thaumarchaeota—along with 11 classes and 18 orders, with Nitrosopumilales and Methanobacteriales as dominant orders. Several ammonia-oxidizing archaea (AOA), including Candidatus Nitrosopumilus adriaticus, Candidatus Nitrosopumilus salaria, Candidatus Nitrosopumilus sediminis, and unclassified Nitrosopumilus spp., were detected. Additionally, the presence of methane-oxidizing archaea (MOA) such as Candidatus Methanoperedens nitroreducens, although at low relative abundance, suggests potential roles in nitrogen and methane cycling. These findings provide initial insights into the archaeal contributions to biogeochemical processes in JB, highlighting the need for further seasonal and functional investigations. Full article

This research paper provides a conceptualization of a new type of plasma thruster based on screw-pinch physics and on the magnetic mirror concept. The article proposes a method to size a screw-pinch with a non-uniform axial magnetic field as a plasma thruster and to estimate its propulsive performance. The results obtained show that the plasma thruster is suitable for space missions inside the Earth’s sphere of influence and for space transportation of small satellites. Full article

Fused filament fabrication (FFF) is a 3D printing technology that has been successfully demonstrated aboard the International Space Station (ISS), proving its suitability for space applications. In this study, we aimed to apply FFF to the 3D printing of recycled space beverage packaging, made of LDPE and a PET-Aluminum-LDPE (PAL) trilaminate. To minimize material waste and optimize the experimental process, we first conducted numerical simulations of additive manufacturing. Using Digimat-AM 2021.1 software, we analyzed residual stresses and warpage in an LDPE/PAL composite with a 10 wt% filler content, processed through the FFF technique. Three key printing parameters, including printing speed and infill pattern, were varied across different levels to assess their impact. Once the optimal combination of parameters for minimizing residual stresses and warpage was identified, we proceeded with the experimental phase, printing objects of increasing complexity to validate the correlation between numerical predictions and the 3D-printed models. The successful fabrication of all geometries under optimized conditions confirmed the numerical predictions, particularly the reduction in warpage and residual stress, validating the material’s viability for additive manufacturing. These findings support the potential application of the LDPE/PAL composite for in situ resource utilization strategies in long-term space missions. Full article

Robotics plays a pivotal role in contemporary space missions, particularly in the development of robotic manipulators for operations in environments that are inaccessible to humans. In accordance with the trend of integrating multiple functionalities into a single system, this study evaluates the feasibility of using a robotic manipulator, termed a C-arm, for passive attitude control of a 1U CubeSat. A simplified multibody model of the CubeSat system was employed to assess the robotic arm’s functionality as a gravity gradient boom and subsequently as a passive magnetic control mechanism by utilising a permanent magnet at its extremity. The effectiveness of the C-arm as a gravitational boom is constrained by size and weight, as evidenced by the simulations; the pitch angle oscillated around ±40°, while roll and yaw angles varied up to 30° and 35°, respectively. Subsequent evaluations sought to enhance pointing accuracy through the utilisation of permanent magnets. However, the absence of dissipative forces resulted in attitude instabilities. In conclusion, the integration of a robotic arm into a 1U CubeSat for passive attitude control shows potential, especially for missions where pointing accuracy can tolerate a certain range, as is typical of CubeSat nanosatellite missions. Full article

Spinach, leafy vegetables with growing demand and high nutritional value, has a heightened focus on nitrate content. An open-field experiment evaluated the potential of vis-NIR-SWIR hyperspectral data for classifying spinach nitrate content. Shallow artificial neural networks (ANN) and ensemble techniques—majority voting (MV) and stacked generalization (stacked)—were applied. The competitive adaptive reweighted sampling (CARS), its stability version (SCARS), Elastic Net, and modified boosted versions of each (CARSplus, SCARSplus, and ENplus) were used as feature selection methods. ANNs were optimized for hidden layer size. The resulting models were further used in ensemble techniques by grouping them into two sets: one with all models and another with models trained using the three boosted feature selection subsets (fifty-three wavelengths). The best-performing ANNs were based on the SCARS, SCARSplus, and full datasets, achieving an accuracy (Acc) of 0.83. While the majority voting approach did not improve performance (Acc 0.82), the stacked ensemble models reached Acc 0.88. Notably, stacked performed well also with models trained on 53 wavelengths, demonstrating strong potential for transferability as the required sensors would be less complex than those used in this study. Furthermore, a simulation of the practical application was conducted using Italian Ministry of Health official data with the scope of showing a potential use case in improving nitrate management and for advancing efficient farming practices in agriculture. The stacked models demonstrated their utility in doubling the monitoring capacity for internal quality assurance in spinach farming within a regulated framework. Full article

The increasing demand for critical raw materials (CRMs), driven by global energy transition, underscores the need for innovative approaches to identify secondary resources, such as mining residues. Mining residues, often overlooked during initial mining activities, now represent valuable sources of raw materials thanks to technological advancements, including hyperspectral remote sensing. This study investigates the potential of hyperspectral satellite imagery to detect and map CRMs in mining residues of the abandoned Sidi Bou Azzouz mine in Morocco. The proposed approach is based on the integration between satellite data, field spectroscopy, chemical, and mineralogical analyses in a strong multi-scale and interdisciplinary framework. The integration between advanced laboratory techniques, including LIBS, XRF, XRPD, and SEM-EDS, was employed to enhance hyperspectral data interpretation. The integration of remote sensing and laboratory results provided a comprehensive understanding of mineral composition, confirming the effectiveness of hyperspectral methods for characterizing heterogeneous surface deposits. This research demonstrates the potential of hyperspectral observations to identify valuable raw materials and to map them using PRISMA imagery in abandoned mining residues, offering a tool useful for planning cost-effective and sustainable solutions aimed at answering the growing demand for CRMs crucial to industrial competitiveness and sustainable growth. Full article

The buffalo species (Bubalus bubalis) is crucial for the global economy, supplying high-nutritional-value animal proteins vital for children’s growth. These animals efficiently convert fiber into energy and thrive in various harsh environments, from frigid climates to hot, humid areas, including wetlands. They produce milk and meat while supporting the sustainability of ecosystems that other ruminants cannot inhabit. Buffalo offers a unique opportunity to supply resources for both rural communities and larger farms located in specific regions, such as marshlands and humid savannahs. They also thrive on extensive pastures and family farms, thus preserving biodiversity, habitats, and cultural practices. Intensive farming brings distinct challenges and is often criticized for its negative effects on climate change. To counter these impacts, multiple strategies have been researched and implemented. These include enhancing livestock genetics, adopting sustainable agricultural practices, optimizing local feed resources (including by-products), managing manure (with an emphasis on renewable energy), and improving animal health and welfare. This review explores various buffalo farming system applications in different global contexts. It is based on the hypothesis that the adaptable traits of buffalo, as well as the environmental and economic challenges that must be addressed for sustainability, are the key factors in determining the viability of such enterprises. Full article

Predicting macroseismic intensity from instrumental ground motion parameters remains a complex task due to the nonlinear relationship with observed damage patterns. An explainable machine learning model based on the XGBoost algorithm was developed to address the challenge. The model is trained on data from Italian earthquakes recorded between 1972 and 2016, linking ground motion recordings to MCS observations located within 3 km. The dataset has been enhanced with site-specific correction factors to better capture local amplification effects. Key input features include Arias Intensity, spectral accelerations at four representative periods (0.15 s, 0.4 s, 0.6 s, and 2 s), and site condition proxies, such as slope and Vs30. The model achieves strong predictive performance (RMSE = 0.73, R² = 0.76), corresponding to a 33% reduction in residual standard deviation compared to traditional GMICE-based regression methods. To ensure transparency, Shapley Additive Explanations (SHAPs) are used to quantify the contribution of each feature. Arias Intensity emerges as the dominant predictor, followed by spectral ordinates in line with structural response mechanics. As damage severity increases, feature importance shifts from PGA to PGV, while site-specific variables (slope, Vs30) act as refiners rather than amplifiers of shaking. The proposed approach enables near real-time prediction of local damage scenarios and supports data-driven decision-making in seismic emergency management. Full article

This study evaluated the effect of two levels of extruded linseed (EL) in the diet on growth performance, carcass yield, and meat quality of growing rabbits. Sixty-nine New Zealand White male rabbits (Oryctolagus cuniculus) were assigned after weaning to three dietary groups: control (C), 2.5% EL (L2.5%), and 5% EL (L5%). At the end of the fattening period (from 37 to 93 days of age), rabbits were slaughtered. EL supplementation significantly reduced average daily weight gain (ADG) in the L5% group (p < 0.05), while other performance parameters were not significantly affected. Meat from the L5% group exhibited a higher fat content (p < 0.001) and lower water-holding capacity (p < 0.05) compared to the others. The fatty acid profile showed a significant increase in n-3 polyunsaturated fatty acids (PUFAs) and a decrease in n-6 PUFA (p < 0.05), resulting in a markedly reduced n-6/n-3 ratio (p < 0.001) in supplemented groups. EL supplementation also enhanced long-chain n-3 PUFA levels, particularly docosapentaenoic acid (DPA). Although lipid oxidation was slightly increased (p < 0.05), sensory attributes remained unaffected. These findings support EL supplementation as a nutritional strategy to increase the n-3 fatty acids in rabbit meat without compromising physical and sensory quality. Full article

Monitoring the variation of urban expansion is crucial for sustainable urban planning and cultural heritage management. This paper proposes an approach for the semantic segmentation of very-high-resolution (VHR) satellite imagery to detect the changes in urban sprawl in the surroundings of Chan Chan, a UNESCO World Heritage Site in Peru. This study explores the effectiveness of combining Mix Transformer encoders with U-Net architectures to improve feature extraction and spatial context understanding in VHR satellite imagery. The integration of active contour loss functions further enhances the model’s ability to delineate complex urban boundaries, addressing the challenges posed by the heterogeneous landscape surrounding the archaeological complex of Chan Chan. The results demonstrate that the proposed approach achieves accurate semantic segmentation on images of the study area from different years. Quantitative results showed that the U-Net-scse model with an MiTB5 encoder achieved the best performance with respect to SegFormer and FT-UNet-Former, with IoU scores of 0.8288 on OpenEarthMap and 0.6743 on Chan Chan images. Qualitative analysis revealed the model’s effectiveness in segmenting buildings across diverse urban and rural environments in Peru. Utilizing this approach for monitoring urban expansion over time can enable managers to make informed decisions aimed at preserving cultural heritage and promoting sustainable urban development. Full article