The worldwide problem of infectious diseases has appeared in recent years, and antimicrobial agents are crucial in reducing disease emergence. Nevertheless, the development and distribution of multidrug-resistant (MDR) strains in pathogenic bacteria, such as Escherichia coli, Staphylococcus aureus, Salmonella Typhi and Citrobacter koseri, has become a major society health hazard. Essential oils could serve as a promising tool as a natural drug in fighting the problem with these bacteria. The current study aimed to investigate the antimicrobial effectiveness of tea tree (Melaleuca alternifolia (Maiden and Betche) Cheel), rosemary (Rosmarinus officinalis L.), eucalyptus (Eucalyptus obliqua L’Hér.), and lavender (Lavandula angustifolia Mill) essential oils. The antimicrobial properties of essential oils were screened against four pathogenic bacteria, E. coli, S. aureus, S. Tyhpi, and C. koseri, and two reference bacterial strains, while for the testing, the agar well diffusion method was used. Gas chromatography (GC) and gas chromatography–mass spectrometric (GC–MSD) analyses were performed on essential oils. The obtained results showed that M. alternifolia essential oil is the richest in terpinen-4-ol, R. officinalis and E. oblique essential oils in 1,8-cineole, and L. angustifolia essential oil in α-terpinyl acetate. In addition, the main bioactive compounds present in the essential oil of tea tree are rich in α-pinene (18.38%), limonene (7.55%) and γ-terpinene (14.01%). The essential oil of rosemary is rich in α-pinene (8.38%) and limonene (11.86%); eucalyptus essential oil has significant concentrations of α-pinene (12.60%), p-cymene (3.24%), limonene (3.87%), and γ-terpinene (7.37%), while the essential oil of lavender is rich in linalool (10.71%), linalool acetate (9.60%), α-terpinyl acetate (10.93%), and carbitol (13.05%) bioactive compounds, respectively. The obtained results from the in vitro study revealed that most of the essential oils exhibited antimicrobial properties. Among the tested essential oils, tea tree was discovered to demonstrate the strongest antimicrobial activity. The recorded MIC of S. Typhi was 6.2 mg/mL, 3.4 mg/mL of C. koseri, 3.1 mg/mL of E. coli, and 2.7 mg/mL of E. coli ATCC 25922, compared to M. alternifolia. Similarly, only S. aureus ATCC 25923 showed antimicrobial activity towards R. officinalis (1.4 mg/mL), E. oblique (2.9 mg/mL), and L. angustifolia (2.1 mg/mL). Based on the obtained results, it is possible to conclude that tea tree essential oil might be used as an ecological antimicrobial in treating infectious diseases caused by the tested pathogens.

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect’s appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

Lymantria dispar L. is the most devastating polyphagous pest of deciduous forests, orchards and urban greenery. To prevent damages that L. dispar larvae cause in forestry, agriculture and horticulture, mechanical measures and the use of biological insecticides are the most frequently applied practices. However, the use of conventional insecticides is inevitable in crop protection and forest management on smaller areas, especially in gradation years. However, inadequate use of these chemicals has led to disturbance of biocoenotic balance, outbreaks of some previously less harmful organisms and pesticide residues in soil and watercourses in some regions. To mitigate these consequences it is necessary to harmonize L. dispar control with integrated management principles by applying selective and less toxic insecticides. Therefore, the potential of botanical insecticides and antifeeding substances is gaining in importance. The aim of this study was to assess the influence of ethanol extracts (1, 2 and 5%) of Ambrosia artemisiifolia L., Erigeron canadensis L., Daucus carota L., Morus alba L. and Aesculus hippocastanum L. on the feeding intensity of L. dispar larvae, i.e. to evaluate their antifeeding activity under the conditions of ?no-choice? test. Ten larvae per repetition were placed in Petri dishes and offered oak leaf slices (2 x 9 cm2/repetition) previously dipped in plant extract or ethanol (1, 2, and 5%) for the control. Feeding intensity, expressed as a percentage of consumed leaf area (%), was measured after 48 h. For assessing the antifeeding activity of plant extracts AFI was calculated and the extracts were classified according to scale: no antifeeding activity, slight antifeeding activity, moderate antifeeding activity and strong antifeeding activity. Data were analyzed using a two-way ANOVA and Duncan`s multiple range test. The results indicate that plant species, i.e. the origin of extracts, had a significant influence on the feeding intensity of L. dispar larvae, while concentration and interaction (plant species x concentration) were not factors of influence. Ae. hippocastanum and M. alba extracts significantly reduced the consumed leaf area (6.24, 18.93%, respectively), compared to the control (97.59%), while the extract of D. carota had a phagostimulative effect (98.88%). Based on AFI values, Ae. hippocastanum extract (87.10-89.05%) had a strong antifeeding activity, and M. alba medium-to-strong (64.33-71.37%).

An objective evaluation of maize hybrids in intensive cropping systems requires identification not only of yield components and other agronomically important t...

The aim of this research was the visual characterization and investigating the effects of Alternaria spp. contaminated wheat grains in the starter stage of broilers nutrition on productive parameters and oxidative stress. The research was divided into two phases. Bunches of wheat in post-harvest period of year 2020 was collected from a various locality in Serbia and Albania. In the first phase, collected samples were visual characterized by Alternaria spp. presence by color measurement methods. Gained results are conferred in the range of the color properties of grain color properties of Alternaria toxins. Wheat grain samples were significantly different (p < 0.05) in terms of all measured color parameters (L*, a*, b*). Classification of field fungi in analyzed wheat grain samples showed that the significant field fungi were Rhizopus spp., followed by Alternaria spp., and Fusarium spp. In the second phase, biological tests with chickens were carried out during the broiler chickens’ dietary starter period in the first 14th days of age. At the beginning of the experiment, a total of 180-day-old Ross 308 strain broilers were equally distributed into three dietary treatments, with four replicates each. Dietary treatments in the experiments were as follows: basal diet without visual contamination of Alternaria spp. with 25% wheat (A1), a basal diet with visual contamination of Alternaria spp. with 25% wheat from Serbia (A2), basal diet with visual contamination of Alternaria spp. with 25% wheat from Albania (A3). The trial with chickens lasted for 14 days. After the first experimental week, wheat infected with Alternaria spp. in treatment A2 and A3 expressed adverse effects. The highest body weight of chickens of 140.40 g was recorded in broilers on control treatment A1 with statistically significant differences (p < 0.05) compared to treatments A2 (137.32 g) and A3 (135.35 g). At the end of the second week of test period, a statistically significant (p < 0.05) difference in body weight of broiler chickens could be noticed. The highest body weight of 352.68 g was recorded in control treatment A1, with statistically significant differences compared to other Alternaria spp. treatments. The lowest body weight of chickens was recorded in treatment A3 (335.93 g). Results of feed consumption and feed conversion ratio showed some numerical differences between treatments but without any statistically significant differences (p > 0.05). Alternaria spp. contaminated diet increased glutathione (GSH), glutathione reductase (GR), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) and decreased peroxidase (POD) and superoxide dismutase (SOD) serum levels, respectively. Built on the achieved results, it can be concluded that the wheat contaminated with Alternaria spp. in broilers nutrition negatively affected growth, decreased oxidative protection and interrupted chicken welfare in the first period of life.