14 research outputs found
Potencial energético de la biomasa procedente de årboles frutales podados en Croacia
 The world's most developed countries and the European Union (EU) deem that the renewable energy sources should partly substitute fossil fuels and become a âbridgeâ to the utilization of other energy sources of the future. This paper will present the possibility of using pruned biomass from fruit cultivars. It will also present the calculation of potential energy from the mentioned raw materials in order to determine the extent of replacement of non-renewable sources with these types of renewable energy. One of the results of the intensive fruit-growing process, in post pruning stage, is large amount of pruned biomass waste. Based on the calculated biomass (kg ha-1) from intensively grown woody fruit crops that are most grown in Croatia (apple, pear, apricots, peach and nectarine, sweet cherry, sour cherry, prune, walnut, hazelnut, almond, fig, grapevine, and olive) and the analysis of combustible (carbon 45.55-49.28%, hydrogen 5.91-6.83%, and sulphur 0.18-0.21%) and non-combustible matters (oxygen 43.34-46.6%, nitrogen 0.54-1.05%, moisture 3.65-8.83%, ashes 1.52-5.39%) with impact of lowering the biomass heating value (15.602-17.727 MJ kg-1), the energy potential of the pruned fruit biomass is calculated at 4.21 PJ.Los principales países desarrollados del mundo y de la Unión Europea (UE) consideran que las fuentes de energía renovables deberían sustituir parcialmente a los combustibles fósiles y convertirse en el futuro en un “puente” hacia la utilización de otras fuentes de energía. En este trabajo, se planteó la posibilidad de utilizar biomasa cortada procedente de cultivos frutales con el propósito de calcular el potencial energético del mencionado material en bruto, así como determinar el grado de remplazo de fuentes no renovables con este tipo de fuentes de energía renovable. Uno de los resultados del proceso de cultivo de frutales en intensivo, tras la época de poda, es la gran cantidad de biomasa cortada inútil. En base al cálculo de biomasa (kg ha-1) de los frutales leñosos de cultivo intensivo más comunes en el territorio de Croacia (manzano, peral, albaricoquero, melocotonero y nectarino, cerezo, guindo, ciruelo, nogal, avellano, almendro, higuera, viña y olivo) y en base al análisis de partículas combustibles (carbono 45,55-49,28%, hidrógeno 5,91-6,83% y azufre 0,18-0,21%) y de partículas no combustibles (oxígeno 43,34-46,6%, nitrógeno 0,54-1,05%, vapor de agua 3,65-8,83% y cenizas 1,52-5,39%) que influyen en el poder calorífico inferior de la biomasa (15,602-17,727 MJ kg-1), se calcula que la energía potencial de los restos de poda de frutales es 4.21 PJ
Ultrasound-assisted extraction of bioactive compounds from lemon balm and peppermint leaves
Biochar effect on crop performance and Pb and Zn uptake of tomato (Solanum lycopersicum, L.) plants grown on heavy metals contaminated Kosovo soils
A greenhouse pot experiment was conducted to evaluate the effect of biochar on the growth and uptake of Pb and Zn by tomato plants (Solanum lycopersicum, L.) cultivated in two highly contaminated Kosovo soils, A and B. Plants were cultivated in the biochar amended and unamended soils. As expected, the biochar addition to the two polluted soils has contributed to significantly improve the crop yields, in terms of both fresh and dry weight. Further, results indicated that the effect of biochar on metal mobility is closely related, besides its properties, to soilâs native characteristics. In fact, the addition of biochar to soil B had also beneficial effects on the uptake of both metals, halving in some cases the values of the biological accumulation and transfer coefficients, while it did not show the same efficacy on soil A
Optimization of ultrasound assisted extraction of functional ingredients from Stevia rebaudiana Bertoni leaves
The aim of the present study was to reveal an effective extraction procedure for maximization of the yield of steviol glycosides and total phenolic compounds as well as antioxidant activity in stevia extracts. Ultrasound assisted extraction was compared with conventional solvent extraction. The exami-ned solvents were water (100ÂșC/24 h) and 70% ethanol (at 70°C for 30 min). Qualitative and quantitative analyses of steviol glycosides in the extracts obtained were performed using high performance liquid chromatography. Total phenolic compounds, flavonoids, and radical scavenging capacity by 2, 2-azino-di-3-ethylbenzothialozine-sulphonic acid) assay were also determined. The highest content of steviol glycosides, total phenolic compounds, and flavonoids in stevia extracts were obtained when ultrasound assisted extraction was used. The antioxidant activity of the extracts was correlated with the total amount of phenolic compounds. The results indicated that the examined sonication parameters represented as the probe diameter (7 and 22 mm) and treatment time (2, 4, 6, 8, and 10 min) significantly contributed to the yield of steviol glycosides, total phenolic compounds, and flavonoids. The optimum conditions for the maximum yield of steviol glycosides, total phenolic compounds, and flavonoids were as follows: extraction time 10 min, probe diameter 22 mm, and temperature 81.2oC
Performance and Emission Studies of Castor Bean (Ricinus Communis) Oil Biodiesel and Its Blends with Diesel Fuel
Meta-humanization enhances positive reactions to prosocial cross-group interaction
The present research investigated whether learning that an outgroup humanizes the ingroup (i.e., meta-humanization) enhances how people react to intergroup prosocial behaviours and their willingness to engage in intergroup contact. In three experiments conducted in two cultural contexts (Kosovo and North Macedonia; n = 601), we manipulated meta-humanization by informing participants that their ingroup is perceived to be as human as the outgroup by outgroup members. We compare this metahumanization condition with a meta-dehumanization condition in which the participant's ingroup is perceived to be less human than the outgroup (Experiments 1 and 3), a metaliking condition in which the participant's ingroup is liked as much as the outgroup (Experiment 2), and a control condition (Experiments 1 and 2). Overall, results showed that participants in the meta-humanization condition attributed more empathy and prosocial motives to a potential outgroup helper and were more willing to accept outgroup help and engage in future intergroup contact than participants in the other conditions. In addition, positive perceptions of the outgroup helper mediated the effect of meta-humanization on willingness to accept outgroup help and engage in intergroup contact. We discuss the theoretical and practical implications of these findings for intergroup relations and reconciliation efforts
Food Recognition and Food Waste Estimation Using Convolutional Neural Network
In this study, an evaluation of food waste generation was conducted, using images taken before and after the daily meals of people aged between 20 and 30 years in Serbia, for the period between 1 January and 31 April in 2022. A convolutional neural network (CNN) was employed for the tasks of recognizing food images before the meal and estimating the percentage of food waste according to the photographs taken. Keeping in mind the vast variates and types of food available, the image recognition and validation of food items present a generally very challenging task. Nevertheless, deep learning has recently been shown to be a very potent image recognition procedure, while CNN presents a state-of-the-art method of deep learning. The CNN technique was implemented to the food detection and food waste estimation tasks throughout the parameter optimization procedure. The images of the most frequently encountered food items were collected from the internet to create an image dataset, covering 157 food categories, which was used to evaluate recognition performance. Each category included between 50 and 200 images, while the total number of images in the database reached 23,552. The CNN model presented good prediction capabilities, showing an accuracy of 0.988 and a loss of 0.102, after the network training cycle. The average food waste per meal, in the frame of the analysis in Serbia, was 21.3%, according to the images collected for food waste evaluation