Rapeseed is considered as one of the most important oilseed crops in the world. Vegetable oil obtained from rapeseed is a valuable raw material for the food and energy industry as well as for industrial applications. Compared to other vegetable oils, it has a lower concentration of saturated fatty acids (5%–10%), a higher content of monounsaturated fatty acids (44%–75%), and a moderate content of alpha-linolenic acid (9%–13%). Overall, rapeseed is grown in all continents on an industrial scale, so there is a growing need to predict yield before harvest. A combination of quantitative and qualitative data were used in this work in order to build three independent prediction models, on the basis of which yield simulations were carried out. Empirical data collected during field tests carried out in 2008–2015 were used to build three models, QQWR15_4, QQWR31_5, and QQWR30_6. Each model was composed of a different number of independent variables, ranging from 21 to 27. The lowest MAPE (mean absolute percentage error) yield prediction error corresponded to QQWR31_5, it was 6.88%, and the coefficient of determination R² was 0.69. As a result of the sensitivity analysis of the neural network, the most important independent variable influencing the final rapeseed yield was indicated, and for all the analyzed models it was “The kind of sowing date in the previous year” (KSD_PY).

This article aims to present the results of research on anaerobic digestion (AD) of waste wafers (WF-control) and co-substrate system—waste wafers and cheese (WFC-control), combined with digested sewage sludge. The aim of this study was to assess the physicochemical parameters of the diatomaceous earth/peat (DEP; 3:1) carrier material and to verify its impact on the enzymatic activity and the process performance. The experiment was conducted in a laboratory, in a periodical mode of operation of bioreactors, under mesophilic conditions. The results of analyses of morphological-dispersive, spectroscopic, adsorption, thermal, and microbiological properties confirmed that the tested carrier material can be an excellent option to implement in biotechnological processes, especially in anaerobic digestion. As part of the experiment, the substrates, feedstock, and fermenting slurry were subjected to the analysis for standard process parameters. Monitoring of the course of AD was performed by measuring the values of key parameters for the recognition of the stability of the process: pH, VFA/TA ratio (volatile fatty acids/total alkalinity), the content of NH₄⁺, and dehydrogenase activity, as an indicator of the intensity of respiratory metabolism of microorganisms. No significant signals of destabilization of the AD process were registered. The highest dehydrogenase activity, in the course of the process, was maintained in the WFC + DEP system. The microbial carrier DEP, used for the first time in the anaerobic digestion, had a positive effect on the yield of methane production. As a result, an increase in the volume of produced biogas was obtained for samples fermented with DEP carrier material for WF + DEP by 13.18% to a cumulative methane yield of 411.04 m³ Mg⁻¹ VS, while for WFC + DEP by 12.85% to 473.91 m³ Mg⁻¹ VS.

Biorefining and biorefineries are the future of industry and energy. It is still a long way to complete its implementation, but small biorefineries focused mainly on the production of fuels and energy are more and more frequent in rural areas and large areas located near big cities in which, in addition to fuels and energy, various organic substances of high market value are also produced. In order to optimize biogas production and to control methane fermentation processes, fast and accurate identification of carboxylic acid concentrations, including propionic acid as a precursor to acetic acid, is needed. In this study, a process quality control method was developed to evaluate the propionic acid content of an aqueous solution from the fermentation mass. The proposed methodology is based on near infrared spectroscopy with multivariate analysis and stochastic metamodeling with a denoising procedure based on proper orthogonal decomposition (POD). The proposed methodology uses the Bayesian theory, which provides additional information on the magnitude of the correlation between state and control variables. The calibration model was, therefore, constructed by using Gaussian Processes (GP) to predict propionic acid content in the aqueous solution using an NIR-Vis spectrophotometer. The design of the calibration model was based on absorbance spectra and calculation data from selected wavelength ranges from 305 nm to 2210 nm. Measurement data were first denoised and truncated to build a fast and reliable metamodel for precise identification of the acid content of an aqueous solution at a concentration from 0 to 5.66%. The mean estimation error generated by the metamodel does not exceed 0.7%.

The article aims to present results of research on anaerobic digestion (AD) of waste wafers (WF-control) and co-substrate system–waste wafers and cheese (WFC-control), combined with digested sewage sludge, as inoculum. The purpose of this paper is to confirm the outcome of adding silica/lignin (S/L; 4:1) material, as a microbial carrier, on the process performance and genetic diversity of microbial communities. The experiment was conducted in a laboratory under mesophilic conditions, in a periodical operation mode of bioreactors. Selected physicochemical parameters of the tested carrier, along with the microstructure and thermal stability, were determined. Substrates, batches and fermenting slurries were subjected to standard parameter analysis. As part of the conducted analysis, samples of fermented food were also tested for total bacterial count, dehydrogenase activity. Additionally, DNA extraction and next-generation sequencing (NGS) were carried out. As a result of the conducted study, an increase in the volume of produced biogas was recorded for samples fermented with S/L carrier: in the case of WF + S/L by 18.18% to a cumulative biogas yield of 833.35 m³ Mg⁻¹ VS, and in the case of WFC + S/L by 17.49% to a yield of 950.64 m³ Mg⁻¹ VS. The largest total bacterial count, during the process of dehydrogenase activity, was maintained in the WFC + S/L system. The largest bacterial biodiversity was recorded in samples fermented with the addition of cheese, both in the case of the control variant and in the variant when the carrier was used. In contrast, three phyla of bacteria Firmicutes, Proteobacteria and Actinobacteria predominated in all experimental facilities.

The manner of storage of sugar beets largely influences their physical and chemical properties, which may subsequently determine their biochemical methane potential. In this study, samples of fresh sugar beets as well as beets stored in two ways—in airtight conditions and in an open-air container—were tested. In both cases, measurements were taken on specific dates, i.e., after 4, 8, 16 and 32 weeks of storage. A decrease in pH was observed in all samples, with the lowest decrease occurring in hermetically stored samples. The lowest pH value of 3.71 was obtained for sugar beets stored in an open-air container after 32 weeks of storage. During storage, a gradual decrease in total solids was also recorded along with accompanying losses of organic matter, more significant in the case of storage in an open-air container. In subsequent storage periods, the biogas/methane production efficiency differed slightly for both methods. The highest volume of biogas was obtained for fresh sugar beets—148.23 mL·g⁻¹ fresh matter (FM)—and subsequently in the 8th and 16th weeks of storage: 139.35 mL·g⁻¹ FM (H—airtight conditions) and 144.14 mL·g⁻¹ FM (O—open-air container), and 147.58 H mL·g⁻¹ FM (H) and 148.22 mL·g⁻¹ FM (O), respectively. The storage period affected the time of anaerobic decomposition of the organic matter—fresh sugar beets took the longest to ferment (26 days), while the material stored for 32 weeks took the shortest to ferment. In the experiment, the content of selected organic compounds in individual samples, i.e., sugar, methanol, ethanol, lactic acid and acetic acid, was also analysed. Within these results, significant differences were found between the samples stored using the two different methods. A high content of sugar, methanol, ethanol and other chemical compounds in the “O” materials showed the hydrolysis and acidogenesis processes taking place in an open-air container, with the participation of catalytic microorganisms.