It is important to correctly predict the microclimate of a greenhouse for control and crop management purposes. Accurately forecasting temperatures in greenhouses has been a focus of research because internal temperature is one of the most important factors influencing crop growth. Artificial Neural Networks (ANNs) are a powerful tool for making forecasts. The purpose of our research was elaboration of a model that would allow to forecast changes in temperatures inside the heated foil tunnel using ANNs. Experimental research has been carried out in a heated foil tunnel situated on the property of the Agricultural University of Krakow. Obtained results have served as data for ANNs. Conducted research confirmed the usefulness of ANNs as tools for making internal temperature forecasts. From all tested networks, the best is the three-layer Perceptron type network with 10 neurons in the hidden layer. This network has 40 inputs and one output (the forecasted internal temperature). As the networks input previous historical internal temperature, external temperature, sun radiation intensity, wind speed and the hour of making a forecast were used. These ANNs had the lowest Root Mean Square Error (RMSE) value for the testing data set (RMSE value = 3.7 °C).

The influence of harvest period and drying method of Salvia officinalis L. leaves on the content of essential oils, polyphenols and antioxidant properties was investigated. Sage leaves were collected twice during plant blossoming (in June and July) and dried traditionally in natural conditions and at 35 °C. Antioxidant activity was assayed in methanol-acetone extracts and infusions of dried leaves with the use of free radical scavenging activity (DPPH) and ferric reducing antioxidant power (FRAP) technique. Total phenolic content in extracts as well as in infusions was determined by the means of Folin–Ciocalteu method. Based on the LC/MS analysis, the polyphenol compounds present in both extracts and in infusions were identified. The extracts contained more polyphenols and were characterized by higher antioxidant activity than infusions. In the extracts significant amount of ferulic acid was found, which was influenced both by the harvest period and drying method. The amount of ferulic acid found in extracts obtained from the June leaves dried traditionally was three times lower (6.185 μg/g DW) than in extracts from July leaves dried in the same conditions. Harvest period had a significant effect on the essential oils’ content, leaves collected in July contained 15% more oils than those collected in June.

The aim of the paper was to summarize and discuss current research trends in biomass thermal treatment (torrefaction process). Quantitative analyses were carried out, in which the main countries, research units and scientists were indicated. The analysis showed a clear upward trend in number of publications after 2010. Most scientists on selected topics come from China, USA, Canada, South Korea, Republic of China, Poland (Web od Science—Core Collection (WoS-CC) and Scopus databases). Quantitative analysis also showed that the most relevant WoS-CC categories in the summary are: Energy Fuels, Engineering Chemical, Agricultural Engineering, Biotechnology Applied Microbiology and Thermodynamics and Scopus Subject area: Energy, Chemical Engineering, Environmental Science, Engineering and Chemistry. Thematic analysis included research topics, process parameters and raw materials used. Thematic groups were separated: torrefaction process (temp.: 150–400 °C), hydrothermal carbonization process (HTC) (temp: 120–500 °C), pyrolysis process (temp.: 200–650 °C) and gasification and co-combustion process (temp.: 350–1600 °C). In the years 2015–2019, current research topics were: new torrefaction technologies (e.g., HTC), improvement of the physico-mechanical, chemical and energetic properties of produced fuel as well as the use of torrefied biomass in the process of pyrolysis, gasification and co-combustion. The raw materials used in all types of biomass thermal treatment were: energy crops, wood from fast-growing and exotic trees, waste from the agri-food industry, sewage sludge and microalgae.

Cornelian cherry (Cornus mas) is a valuable source of phenolic antioxidants. Flavonoid derivatives as nonenzymatic antioxidants are important in the pathophysiology of many diseases including neurological disorders (e.g., Alzheimer’s disease) or heart disease. In this study, we examined the effect of an addition of freeze-dried fruit of cornelian cherry on three types of diets: control diet, fructose diet, and diet enriched in fats (high-fat diet). This effect was studied by determining the following antioxidant parameters in both brain tissue and plasma in rats: catalase, ferric reducing ability of plasma, paraoxonase, protein carbonyl groups, and free thiol groups. Results indicate that both fructose diet and high-fat diet affect the antioxidant capacity of the organism. Furthermore, an addition of cornelian cherry resulted in increased activity of catalase in brain tissue, while in plasma it caused the opposite effect. In turn, with regard to paraoxonase activity in both brain tissue and plasma, it had a stimulating effect. Adding cornelian cherry to the tested diets increased the activity of PON in both tested tissues. Moreover, protective effect of fruits of this plant was observed in the process of oxidation of proteins by decreasing levels of protein carbonyl groups and thiol groups in brain tissue as well as in plasma.

Flowers of red clover (Trifolium pratense), sweet violet (Viola odorata) and elderflowers (Sambucus nigra) were dried by means of air drying at 30 °C and 50 °C and by freeze drying. The content of polyphenols was determined using the Folin–Ciocalteu reagent, while anthocyanins were quantified by the pH differential method. Antioxidant activities of aqueous and ethanolic extracts of the dried flowers were measured by the DPPH and ABTS assays, as well as FRAP and reducing power methods. The highest amount of polyphenols was determined in the ethanolic extracts of fresh red clover flowers (854.76 mg/100 g), while the highest concentration of anthocyanins was determined in the aqueous extracts of fresh sweet violet flowers (99.41 mg/100 g). The results showed that, in general, the extracts of red clover flower were characterized by the highest antioxidant activity, while the sweet violet extracts had the poorest antioxidant properties, although these values fluctuated depending on the method used. There was strong correlation between antioxidant activity and TPC (r = 0.9196, FRAP method). In most cases, freeze drying was found to be the best conservation method, retaining well the antioxidant properties of the tested flowers and the compounds determining these properties.

The biomass is regarded as a part of renewable energy sources (RES), which can satisfy energy demands. Biomass obtained from plantations is characterized by low bulk density, which increases transport and storage costs. Briquetting is a technology that relies on pressing biomass with the aim of obtaining a denser product (briquettes). In the production of solid biofuels, the technological as well as material variables significantly influence the densification process, and as a result influence the end quality of briquette. This process progresses differently for different materials. Therefore, the optimal selection of process’ parameters is very difficult. It is necessary to use a decision support tool—decision support system (DSS). The purpose of the work was to develop a decision support system that would indicate the optimal parameters for conducting the process of producing Miscanthus and willow briquettes (pre-comminution, milling and briquetting), briquette parameters (durability and specific density) and total energy consumption based on process simulation. Artificial neural networks (ANNs) were used to describe the relationship between individual parameters of the briquette production process. DSS has the form of a web application and is opened from a web browser (it is possible to open it on various types of devices). The modular design allows the modification and expansion the application in the future.