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The aim of the work was to present the role of composting as one of the simple and cheapest methods to reduce GHG emissions from cow manure - conclusions from the MilKey and MELS projects. The article contains both the results of some studies analyzed within the above projects, as well as the methodology of conducting composting studies. The method of managing animal waste by composting or co-composting has been known for a long time and used in many places around the world. However, this is not always done in an appropriate way, both economically and ecologically. Improper storage of manure, its holding time, the way it is applied to the field and finally its use as fertilizer are quite significant for ammonia and greenhouse gases (GHG) emissions. These types of issues are typical of areas of intensive animal production, where farmers use natural fertilizers (slurry, manure) to increase the humus layer on agricultural fields. Most developing or still underdeveloped countries (including Poland) are undergoing intensive changes in the area of sustainable processing of natural fertilizers. The modern rules of the new Common Agricultural Policy of Poland, defined for 2021-2027, provide for the transition of farmers to sustainable agricultural production. One of the key elements for Polish farmers will be the reduction of greenhouse gas emissions from farms by introducing agricultural techniques (e.g. through appropriate nutrition or agrotechnical treatments). In addition, increasing market pressure is expected due to consumer expectations to confirm the sustainability of animal production.

Especially in non-urbanized areas there is a need to use various waste products, e.g. from agriculture, households, etc. New products that are created in a simple way should be able to be used many times without the use of complicated and expensive technology. This article presents the potential of biochar used in wastewater treatment processes and sludge management in small installations - for the maximum maintained number of users equal to 50. The possibilities of two substances used in sewage management processes, such as char and biochar will be presented. These substances, produced from pyrolysis, are stable carbon-rich compounds which have various beneficial applications like soil conditioning, remediation and wastewater treatment. In particular, biochar originating from wastewater sludge pyrolysis, possible to be generated at the place of formation, was taken into account. In addition, ways to increase the reliability of the treatment plant with biochar based filters are described. Attention was paid to the various applications of biochar and its effectiveness in the above-mentioned processes, for various pollutants, typical ones and for more demanding installations (high-efficient treatment), among others: - study of biochar filters as a replacement or complement for mineral filters for removal of pharmaceutically active compounds from wastewater in onsite wastewater treatment plants (OWTP’s). Results from the works of biodegradation, adsorption and a combination of these processes on the removal of pharmaceutically active compounds wastewater in biochar filters will be presented. worked under typical for onsite wastewater treatment plants conditions e.g. infiltration beds. Various variants of tested installations will be presented (with different forms of biochar and on various medium) - study of char and biochar use for different heavy metals after being filtered through biochar and char filters. - study of different forms of biochar, derived from natural, easily accessible sources, which can be easily reused in the environment as a fertilizer or biocompost, for example from: sludge from onsite wastewater treatment plants, Miscanthus, rice husks and wood chips, which differ in composition, porosity, active surface, sorption potential, and finally in the effectiveness of retaining various contamination.

The properties of agriculture by-products make them applicable for insulating materials production. One of the potential source of natural insulating material is corn stover, especially the stalks. In the present study the density, specific heat and volumetric specific heat capacity of individual fractions of corn stover were determined. The separation of the corn fractions allowed to identify the most suitable fractions for insulating panels production. Four separated fractions, i.e. stalks, leaves, husks and cobs, were in focus of the study. The specific heat measurements of selected corn factions were carried out with a water calorimeter. The measurements were made for the oven dry materials which were placed in a heat shrinkable membrane to prepare samples of a cylindrical shape. The obtained values of specific heat and volumetric specific heat capacity confirmed that the thermal properties of corn stover fractions should be determined separately. Only leaves and stalks were characterized by similar values of specific heat and volumetric specific heat capacity. The highest value of specific heat equal to 1723 J/(kg·K) was determined for husks. The observed high values of volumetric specific heat capacity determined for all corn stover fractions confirmed their ability of heat accumulation.

In the last decade, an increasingly common method of maize stover management is to use it for energy generation, including anaerobic digestion for biogas production. Therefore, the aim of this study was to provide a chemical and structural characterization of maize stover fractions and, based on these parameters, to evaluate the potential application of these fractions, including forbiogas production. In the study, maize stover fractions, including cobs, husks, leaves and stalks, were used. The biomass samples were characterized by infrared spectroscopy (FTIR), X-ray diffraction and analysis of elemental composition. Among all maize stover fractions, stalks showed the highest C:N ratio, degree of crystallinity and cellulose and lignin contents. The high crystallinity index of stalks (38%) is associated with their high cellulose content (44.87%). FTIR analysis showed that the spectrum of maize stalks is characterized by the highest intensity of bands at 1512 cm−1 and 1384 cm−1, which are the characteristic bands of lignin and cellulose. Obtained results indicate that the maize stover fraction has an influence on the chemical and structural parameters. Moreover, presented results indicate that stalks are characterized by the most favorable chemical parameters for biogas production.

The aim of this study was technological research of maize stover digestion in an agricultural biogas plant and to determine the parameters of digestion under real-life conditions. The authors calculated the electric and thermal power of the cogeneration system in a biogas plant using maize stover. The load of the digestion mixture was maintained at 12% and the volumetric load (BR) at 3.62 kg LOI/m3/day by applying daily amounts of 3.33 Mg of cow slurry and 109.59 kg of maize stover silage into the digestion chamber. The substrates were mixed at a 9:1 ratio. The daily yield of biogas containing 54.0% of methane amounted to 28.71 m3, i.e. 15.50 m3 of methane daily. The annual yield of biogas from the substrates would have amounted to 10,480.6 m3. This biogas plant using the testing substrates produced 16.5 MWh of electricity and 19.9 MWh of heat per year. Maize stover silage can be used as a substrate in installations for biogas production. However, due to the high content of dry matter and low volumetric density its share in the digestion mixture should not exceed 10–20% to ensure optimal volumetric load in the digestion chamber of the biogas plant.

Research was conducted for the purpose of qualitative identification of convection-dried strawberries using artificial neural networks. 2 samples of raw material were subjected to a drying process, each representing different qualitative classes: ripe and overripe fruit. The generated MLP neural network was based on shape and color characteristics; 11 parameters of the quality of dried strawberry were specified. Empirical data was obtained from digital images which served as learning sets for the artificial neural networks simulator. The created neural network was to identify individual learning cases as one of the following cases: "good" - ripe or "bad" - overripe strawberry. Furthermore, a correlation analysis was performed, which showed a strong relationship between some variables.

Civilization development has reduced the number of farming areas, which has led to the situation in which farmers are forced to obtain a higher yield from much smaller acreage. It has resulted in the growth of new methods in agriculture, including precise grain drilling. Under the LIDER project developing the tube clogging control system, there has been identified the need for determining caryopses speed affecting a sensor. Therefore in the article, following the review of all available methods of measuring particle speed it was concluded that there was no speed measurement method for caryopses flying out of a tube as a result of the aerodynamic force which could register the flight trajectory. The aim of the article is to introduce the method and a test stand to measure caryopsis speed by the image analysis method. The method involves applying series of images taken with a high-speed LAVISION camera: HighSpeedStar5 and the FOTOPOMIARY programme. The error difference between the developed innovative method and an analytical method was at the acceptable level of 2%. The developed method and the stand are universal as they make it possible to measure speed for various grains and crops in a seed drill tube.

Various mechanisms of mapping relational structures in graph database Neo4j presented in previous publications describing both detailed and more universal solutions, did not take into account the whole complexity of relational databases. The main aim of the aforementioned actions was to utilize the possibilities of graph database of programming languages paying special attention to searching for connections between tables when both their number and relations is very high and documentation is incomplete or unavailable. The effects of queries realization were presented with graph form, which resulted from the potential of the client program of the platform called Neo4j used for the needs of this research. The problem that the authors have failed to take into consideration so far, and that is presented now, is the case of intermediate tables occurrence, which are used in great measure to eliminate many to many relations on the level of relational bases as well as to eliminate relations based on complex keys. Another improvement of the presented application is new user interface, which eliminates the necessity for user of having Cypher language skill in order to query graph database. At the same time the application ensures results visualization in richer form than client program with the engine Neo4j that is available and offered.

Maize stover is a morphologically diverse biomass, consisting of cobs, leaves, husks and stalks. Technological solutions allow separation of maize stover fractions depending on harvest term, tissular and chemical composition. Different chemical compositions of lignocellulose biomasses affect energy efficiency of specific fractions in methane fermentation. The aim of this study was to correlate the chemical composition of maize stover fractions (cobs, husks, leaves and stalks) with methane yield and energy value while considering different harvest times for biogas fermentation. Pearson correlation coefficients were calculated for all results, with a very strong negative correlation (r = −0.86) between methane yield and lignin content in the maize stover fractions. The lowest methane yield (185.3 m3/Mg of TS) and the longest HRT (40 days) activity of maize stalks were obtained from those samples. Moderately negative correlation between methane yield and cellulose content (r = 0.53) or between methane yield and Na content (r = −0.52) were also observed. This helps explain why the lowest methane yields were found in peduncles with high levels of sodium, cellulose and lignin.

The increase in energy demand creates a need to look for new ways of energy production, as fossil fuel resources are limited and nuclear energy is not always well perceived, thus new directions for fuel production are being sought for. One of them is agricultural biogas obtained in the process of methane fermentation, the by-product of which is digested pulp (digestate), having a fertilizing potential, often underestimated. The purpose of the following study is to determine the fertilizer value of digested pulp coming from a Polish biogas plant. The obtained results of digestate chemical analyzes and available information on mineral fertilizers enabled to estimate the value of digestate from the analyzed biogas plant. Based on the adopted methodology, it has been calculated that the value of the analyzed digestate is 24,9 PLN. It should be emphasized, however, that there are more nutrients in the digestate than just the analyzed nitrogen, phosphorus and potassium and therefore its value increases.

The aim of the study was to determine and analyse the costs of harvesting and storage of maize straw for biogas production. The investigations showed that it was the most economical to harvest maize straw with a self-loading wagon equipped with a cutting system and to store it in a field prism. The cost of this technology amounts to €12.5 per Mg d.m. The cost of maize straw harvest with a field chopper and storage in a flexible silo was the highest, amounts to €126.9 per Mg d.m. The research findings can be used for estimating the profitability of harvesting maize straw for energy production and other industrial purposes.

The aim of the study was to assess how the harvesting and ensilage technology influenced the quality of maize straw silages. The research findings showed that it was best to make maize straw silage in a flexible silo, whereas it was least favourable to make it in a film-covered field prism. The choice of the adequate ensilage method results in a high quality silage even if there is high content of dry matter in maize straw.

In the recent years, there has been a continuously increasing demand for vegetables and dried vegetables. This trend affects the growth of the dehydration industry in Poland helping to exploit excess production. More and more often dried vegetables are used in various sectors of the food industry, both due to their high nutritional qualities and changes in consumers’ food preferences. As we observe an increase in consumer awareness regarding a healthy lifestyle and a boom in health food, there is also an increase in the consumption of such food, which means that the production and crop area can increase further. Among the dried vegetables, dried carrots play a strategic role due to their wide application range and high nutritional value. They contain high concentrations of carotene and sugar which is present in the form of crystals. Carrots are also the vegetables which are most often subjected to a wide range of dehydration processes; this makes it difficult to perform a reliable qualitative assessment and classification of this dried product. The many qualitative properties of dried carrots determining their positive or negative quality assessment include colour and shape. The aim of the research was to develop and implement the model of a computer system for the recognition and classification of freeze-dried, convection-dried and microwave vacuum dried products using the methods of computer image analysis and artificial neural networks.

The work aims to examine and discuss the fertilizing properties of digestate (digested pulp) from three different agricultural biogas plants in terms of the substrates used. Based on the market prices of fertilizers, the economic value of the digestate has been assessed. For a selected biogas plant, the economic balance has been calculated, taking into account the income resulting from the sale of the digestate. The results obtained allow for stating that samples of digestate were rich in nitrogen (up to 6.58 g kg−1), and potassium (up to 16.3 g kg−1) in fresh matter (FM). The value of the digestate for installations was estimated in the range of 6.08–15.36 EUR·Mg−1. The analysis for one of the 1 MW biogas plants shows that under current conditions of supporting systems, the daily income for a biogas plant is 1,414 EUR and the digestate produced is worth another 334.4 EUR. Its application, especially on fields adjacent to biogas plants, is part of the principle of nutrient recovery in the circular economy.

The aim of the study was create a new, non-invasive method of assessing the quality of sugar beet topping using computer image analysis and artificial neural networks. In paper was carried out the analysis the methods used so far to topping assessment of roots and analysis of the possibilities of using the new proposed method. Classical methods allow an assessment only after harvest of roots (after pull out roots), and the proposed method enables the assessment before harvesting sugar beets. The study used 50 images of topped sugar beet roots, which have been subjected to computer analysis in order to improve the image contrast and brightness. The image was converted from color to images in grayscale, and was carried out segmentation and morphological transformations. Binary image was used to determine the surface area and root circuit and topping circiut. This information was used as input to the neural network, which was expanded to two features, ie. the ratio of the areas and circuits. On the output of the network was information about the topping in the form 0 and 1. Created neural network MLP 6:6-26-1:1 allowed for a sensitivity analysis, which returned information about two important features independent, ie. the surface area of the root and root surface area to topping. The analysis found that it is possible to use methods of computer image analysis for non-invasive assessment of the quality topping sugar beets.

A total number of 270 ultrasound images of m. longissimus behind the 13th thoracic vertebrae were obtained on 90 lamb carcasses. Three different scanning frequencies were used (5.0, 7.5 and 10.0 MHz) in order to analyse how the frequency of the ultrasound wave affects the changes of pixel brightness in the ultrasound image. In the images obtained with 10 MHz probe the brightness of the 1st region was higher by 27% and 25% (P≤0.01) compared to the same region of images obtained with 5 MHz and 7.5 MHz frequency probe. The 3rd region of muscle cross-sections obtained with 10 MHz frequency was very dark, with the brightness lower by 22,5% and 28,3% compared to the same region of images obtained with 5 MHz and 7.5 MHz frequency. In the images obtained with 10 MHz scanning frequency, the decrease of brightness from the 1st to the 3rd region of the image was very sharp. While in the images obtained by means of 5 and 7.5 MHz ultrasound frequency, the brightness changes between the regions were very fluent. To conclude, the results of the presented research reveal that high ultrasound frequency has a negative impact on ultrasound image brightness and may reduce the information value of the image.

This paper describes the research, whose goal was to develop an effective method based on the image analysis techniques for the evaluation of the slugs behaviour in the laboratory studies. The main task of the developed computer method is to assist in evaluating the degree of slugs’ acceptance of different plant species and varieties as food and to evaluate the effectiveness of active substances used against slugs. The laboratory tests are conducted in a climate chamber, into which are placed containers with grazing slugs, leaf circles and a hiding place. A video camera is installed in each container to monitor the slugs’ activity. The data from the cameras are stored on hard disks connected to a digital recording device. The task of the proposed computer algorithms is to perform automatic analysis of the stored video material. Video image analysis can be used to determine parameters relating to the slugs’ daily activity, the speed and trajectory of their movement, and the rate and extent of the damage done to the leaves. This task is performed in several stages including: movement detection, object recognition, object tracking and determination of the quantity of leaf damage.

The aim of the research was to investigate the possibility of using the methods of neural image analysis and neural modeling to determine the content of dry weight of compost based on photographs taken under mixed visible and UV-A light conditions. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model RBF 30:30-8-1:1 characterized by RMS error 0,076378 and this networks is more effective than RBF 19:19-2:1:1 which works in visible light conditions.

Even sowing of the seeds is very important because the quality of the crop depends on it. For this reason, the aim is to sow without a culvert caused by an obstruction of the seed hose. For this purpose, a patency control system has been developed for hoses that allow the seed to enter the ground. This allows to ensure the uniformity of seeding, which is very desirable nowadays. The developed method consists in mounting parallel sensors built into the head or on the output nozzles from the head and sensors in the coulters from which information will be transmitted to the monitoring system.