Analysis of Methane Efficiency of Sugar Beets Used as Co-substrate in Biogas Production
Springer Proceedings in Energy, 2019
Although the methane fermentation process has been known for a long time, the use of new agricult... more Although the methane fermentation process has been known for a long time, the use of new agricultural substrates can increases the efficiency of agricultural biogas plants. Therefore, new mono-substrates and co-substrates are still being sought for increasing biogas potential. The use of beet mixed with other substrates can accelerate the fermentation process and improve the quality of biogas produced. The aim of the study was analysis of methane efficiency of sugar beets used as co-substrate in biogas production. Sugar beet mixtures with maize silage and wheat straw were studied. Sugar beet was added in various proportions, and their share was between 10 and 50%. The study was conducted at the Laboratory of Ecotechnologies, in Institute of Biosystems Engineering. To test the biogas efficiency the batch culture method has been used and the process took place in mesophilic conditions. The experiment was carried out in accordance with the German standard DIN 38414-S8. The results have...
Unsupervised neural classification of six chosen apple pests using learned vector quantization agorithm
The aim of this work was a neural identification of selected apple tree orchard pests in Poland. ... more The aim of this work was a neural identification of selected apple tree orchard pests in Poland. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning files acquired on the basis of information contained in digital photographs of pests. There has been identified 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the chosen agrofags, neural networks type Self-Organizing Feature Map (SOFM) methods supported Learned Vector Quantization (LVQ) algorithm were utilized, using by digital analysis of image techniques.
Computer image analysis in evaluating the quality of dried meat, case study: poultry meat
Modern technologies with artificial intelligence are widely used in processing industry and serve... more Modern technologies with artificial intelligence are widely used in processing industry and serve, among other things, as boost to increase efficiency and automatization of production processes, which in turn allows to increase productivity of companies while at the same increasing their competitiveness. At present a real challenge for this branch of economy is manufacturing farm and food products, characterized by best parameters in terms of quality while maintaining optical production and distribution costs of biological material which is subject to processing. The given paper touches upon the subject related to evaluation of changes of quality of dried meat made from turkey meat in the process of microwave and vacuum drying as well as its influence on the quality of meat, microstructure and sensory features.
Specific heat determined for four corn stover fractions. The thermal properties of corn stover fr... more Specific heat determined for four corn stover fractions. The thermal properties of corn stover fractions should be determined separately. All corn stover fractions are useful for insulating materials production. The applied method ensured high accuracy of measurements of corn stover specific heat.
The paper presents the research on the use of methods of computer image analysis and artificial n... more The paper presents the research on the use of methods of computer image analysis and artificial neural modeling in the process of assessing the quality of greenhouse tomatoes variety Cappricia. The subject of the study was tomatoes of the sizes from 40 mm to 67 mm and the colours: 1-6, include intermediate colours. The process of image acquisition and obtaining empirical data was conducted throughout the entire growing season in the period from the first harvest in the middle of May to the last harvest at the beginning of November. Satisfactory quality characteristics were obtained in the case of the RBF 37:37-39-1:1 and RBF 22:22-20-2:2 models. RBF 37:37-39-1:1 network, whose output variable was the colour of the tomato, the training quality was 0.930827, the validation quality was 0.911982, and the test quality was 0.979390. The RMSE rate of network training for the training set was 0.075986, for the validation set it was 0.072194, and for the test set 0.061714. For the RBF 22:22-20-2:2 network, the variables were colour and hardness. This network is characterised by a training quality of 0.985038, a validation quality of 0.990694 and a test quality of 0.985130. The RMSE rate of the network training is 0.065667, of the network validation it is 0.066187 and of the network test 0.073868. The research showed that performing a correct classification requires taking two digital images of the examined tomatoes, one of the stem and one of the front of the tomato, and generating training sets that contain average values for the extracted characteristics.
Evaluating the impact of cultivation systems for improving the management of agricultural soil is... more Evaluating the impact of cultivation systems for improving the management of agricultural soil is difficult. Traditional ploughing cultivation can contribute to soil erosion. An alternative to conventional tillage is conservation tillage. The aim of our study was to determine the influence of different cultivation systems on the biochemical and biological activity of soil under sugar beets. The conventional tillage treatment with soil ploughing to a depth of 35 cm was the control treatment (CT). For comparison, we analysed the following conservation tillage systems consisting of shallow or deep-soil ripping: 1. Tillage to a depth of 35 cm and sowing into stubble mulch (MS35). 2. Tillage to a depth of 15 cm and sowing into stubble mulch (MS15). 3. Tillage to a depth of 15 cm and sowing into white mustard mulch (MG). 4. Strip-till on stubble mulch to a depth of 25 cm and instantaneous beet seed sowing (STS). 5. Strip-till to a depth of 25 cm on white mustard mulch and instantaneous beet seed sowing (STG). The soil samples that were used for biochemical and microbiological analyses were collected during four terms in each year, which coincided with the four consecutive stages of the development of sugar beets. During both years of research we obtained results concerning the influence of different soil cultivation methods on the number of selected groups of soil microorganisms and the enzymatic activity under sugar beets. In 2012-13 the highest bioactivity was noted in the period of the greatest demand of sugar beets for nutrients, at the phase when the rows of plants were closing in. At that time the content of actinobacteria in the soil collected from the sites where STS had been applied was 42% greater than in the soil from the
Optimal nutrition of sugar beets at critical growth stages is one of the crucial factors for the ... more Optimal nutrition of sugar beets at critical growth stages is one of the crucial factors for the achievement of their highest yield potential. In the present study, it was presumed that reduced systems of sugar beet cultivation had no effect on the plants' nutritional status at critical growth stages, on their yield or technological quality. In 2012-2013, two series of one-factorial field experiments with different beet crop husbandry were carried out in order to verify this hypothesis. The cultivation systems of sugar beet crops differed in the postharvest cultivation technology, mulch types and seedbed tillage. Conservation tillage systems were compared with the control treatment, which represented the conventional cultivation system with an application of manure and 35 cm deep autumn ploughing. The plant nutritional status assessment was carried out at two dates corresponding to the following growth stages: BBCH 16/17 (6-8 fully unfolded true leaves) and BBCH 39/40 (row closing). Regardless of the methods of tillage or the year of observation, the results showed that the plants at BBCH16/17 stage were well-nourished with macroelements but malnourished with microelements, mainly iron and zinc. The microelement deficiency in the plants was a result of adjusted soil reaction, which varied from slightly acidic to neutral. At the BBCH 39/40 stage, there was a decreasing trend in the content of leaf macronutrients in the no-tillage systems treatments compared to the conventional tillage with the ploughing depth to 35 cm and manure application. The reduced tillage systems in sugar beet cultivation did not result in either a yield decrease or a worse technological quality of roots. The experimental factor had no significant effect on the content of molassegenic compounds in beet roots. A decreasing trend was observed in the content of α-amino nitrogen and potassium when compared to the traditional cultivation system. The study showed that the choice of a cultivation technology is of secondary importance as long as the plant grows in optimal conditions resulting from an appropriate site selection.
Energy Use of Greenhouse Waste Materials by Methane Fermentation
In Poland, the production of fruits and vegetables covering no more than 3% of agricultural land,... more In Poland, the production of fruits and vegetables covering no more than 3% of agricultural land, constitutes more than 36% of the commodity crop production and 14% of commercial agricultural production. According to the Polish Central Statistical Office in 2012 vegetable production was at the level of 4.553 million Mg, including tomatoes and cucumbers amounted together 11.8%. When harvesting and processing the vegetables, considerable amounts are waste materials. The source of such type of waste in the greenhouse are primarily non-commercial parts of plants i.e. leaves, stems as well as unclassified vegetables. Those waste materials are characterized by high degree of hydration and high content of organic matter, which in case of methane fermentation is extremely indispensable. Therefore, there is a possibility of management of such waste by biological treatment. This paper presents the results of energetic values of vegetable waste from greenhouse production. It has been stated th...
Computer image analysis in caryopses quality evaluation as exemplified by malting barley
SPIE Proceedings, 2015
One of the purposes to employ modern technologies in agricultural and food industry is to increas... more One of the purposes to employ modern technologies in agricultural and food industry is to increase the efficiency and automation of production processes, which helps improve productive effectiveness of business enterprises, thus making them more competitive. Nowadays, a challenge presents itself for this branch of economy, to produce agricultural and food products characterized by the best parameters in terms of quality, while maintaining optimum production and distribution costs of the processed biological material. Thus, several scientific centers seek to devise new and improved methods and technologies in this field, which will allow to meet the expectations. A new solution, under constant development, is to employ the so-called machine vision which is to replace human work in both quality and quantity evaluation processes. An indisputable advantage of employing the method is keeping the evaluation unbiased while improving its rate and, what is important, eliminating the fatigue factor of the expert. This paper elaborates on the topic of quality evaluation by marking the contamination in malting barley grains using computer image analysis and selected methods of artificial intelligence [4-5].
Identification of selected apple pests based on selected graphical parameters
SPIE Proceedings, 2013
ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. T... more ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning sets acquired on the basis of information contained in digital photographs of pests. In particular, the problem of identifying 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the agrofags, neural modelling methods were utilized, supported by digital analysis of image techniques.
Analysis of Methane Efficiency of Sugar Beets Used as Co-substrate in Biogas Production
Springer Proceedings in Energy, 2019
Although the methane fermentation process has been known for a long time, the use of new agricult... more Although the methane fermentation process has been known for a long time, the use of new agricultural substrates can increases the efficiency of agricultural biogas plants. Therefore, new mono-substrates and co-substrates are still being sought for increasing biogas potential. The use of beet mixed with other substrates can accelerate the fermentation process and improve the quality of biogas produced. The aim of the study was analysis of methane efficiency of sugar beets used as co-substrate in biogas production. Sugar beet mixtures with maize silage and wheat straw were studied. Sugar beet was added in various proportions, and their share was between 10 and 50%. The study was conducted at the Laboratory of Ecotechnologies, in Institute of Biosystems Engineering. To test the biogas efficiency the batch culture method has been used and the process took place in mesophilic conditions. The experiment was carried out in accordance with the German standard DIN 38414-S8. The results have...
Unsupervised neural classification of six chosen apple pests using learned vector quantization agorithm
The aim of this work was a neural identification of selected apple tree orchard pests in Poland. ... more The aim of this work was a neural identification of selected apple tree orchard pests in Poland. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning files acquired on the basis of information contained in digital photographs of pests. There has been identified 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the chosen agrofags, neural networks type Self-Organizing Feature Map (SOFM) methods supported Learned Vector Quantization (LVQ) algorithm were utilized, using by digital analysis of image techniques.
Computer image analysis in evaluating the quality of dried meat, case study: poultry meat
Modern technologies with artificial intelligence are widely used in processing industry and serve... more Modern technologies with artificial intelligence are widely used in processing industry and serve, among other things, as boost to increase efficiency and automatization of production processes, which in turn allows to increase productivity of companies while at the same increasing their competitiveness. At present a real challenge for this branch of economy is manufacturing farm and food products, characterized by best parameters in terms of quality while maintaining optical production and distribution costs of biological material which is subject to processing. The given paper touches upon the subject related to evaluation of changes of quality of dried meat made from turkey meat in the process of microwave and vacuum drying as well as its influence on the quality of meat, microstructure and sensory features.
Specific heat determined for four corn stover fractions. The thermal properties of corn stover fr... more Specific heat determined for four corn stover fractions. The thermal properties of corn stover fractions should be determined separately. All corn stover fractions are useful for insulating materials production. The applied method ensured high accuracy of measurements of corn stover specific heat.
The paper presents the research on the use of methods of computer image analysis and artificial n... more The paper presents the research on the use of methods of computer image analysis and artificial neural modeling in the process of assessing the quality of greenhouse tomatoes variety Cappricia. The subject of the study was tomatoes of the sizes from 40 mm to 67 mm and the colours: 1-6, include intermediate colours. The process of image acquisition and obtaining empirical data was conducted throughout the entire growing season in the period from the first harvest in the middle of May to the last harvest at the beginning of November. Satisfactory quality characteristics were obtained in the case of the RBF 37:37-39-1:1 and RBF 22:22-20-2:2 models. RBF 37:37-39-1:1 network, whose output variable was the colour of the tomato, the training quality was 0.930827, the validation quality was 0.911982, and the test quality was 0.979390. The RMSE rate of network training for the training set was 0.075986, for the validation set it was 0.072194, and for the test set 0.061714. For the RBF 22:22-20-2:2 network, the variables were colour and hardness. This network is characterised by a training quality of 0.985038, a validation quality of 0.990694 and a test quality of 0.985130. The RMSE rate of the network training is 0.065667, of the network validation it is 0.066187 and of the network test 0.073868. The research showed that performing a correct classification requires taking two digital images of the examined tomatoes, one of the stem and one of the front of the tomato, and generating training sets that contain average values for the extracted characteristics.
Evaluating the impact of cultivation systems for improving the management of agricultural soil is... more Evaluating the impact of cultivation systems for improving the management of agricultural soil is difficult. Traditional ploughing cultivation can contribute to soil erosion. An alternative to conventional tillage is conservation tillage. The aim of our study was to determine the influence of different cultivation systems on the biochemical and biological activity of soil under sugar beets. The conventional tillage treatment with soil ploughing to a depth of 35 cm was the control treatment (CT). For comparison, we analysed the following conservation tillage systems consisting of shallow or deep-soil ripping: 1. Tillage to a depth of 35 cm and sowing into stubble mulch (MS35). 2. Tillage to a depth of 15 cm and sowing into stubble mulch (MS15). 3. Tillage to a depth of 15 cm and sowing into white mustard mulch (MG). 4. Strip-till on stubble mulch to a depth of 25 cm and instantaneous beet seed sowing (STS). 5. Strip-till to a depth of 25 cm on white mustard mulch and instantaneous beet seed sowing (STG). The soil samples that were used for biochemical and microbiological analyses were collected during four terms in each year, which coincided with the four consecutive stages of the development of sugar beets. During both years of research we obtained results concerning the influence of different soil cultivation methods on the number of selected groups of soil microorganisms and the enzymatic activity under sugar beets. In 2012-13 the highest bioactivity was noted in the period of the greatest demand of sugar beets for nutrients, at the phase when the rows of plants were closing in. At that time the content of actinobacteria in the soil collected from the sites where STS had been applied was 42% greater than in the soil from the
Optimal nutrition of sugar beets at critical growth stages is one of the crucial factors for the ... more Optimal nutrition of sugar beets at critical growth stages is one of the crucial factors for the achievement of their highest yield potential. In the present study, it was presumed that reduced systems of sugar beet cultivation had no effect on the plants' nutritional status at critical growth stages, on their yield or technological quality. In 2012-2013, two series of one-factorial field experiments with different beet crop husbandry were carried out in order to verify this hypothesis. The cultivation systems of sugar beet crops differed in the postharvest cultivation technology, mulch types and seedbed tillage. Conservation tillage systems were compared with the control treatment, which represented the conventional cultivation system with an application of manure and 35 cm deep autumn ploughing. The plant nutritional status assessment was carried out at two dates corresponding to the following growth stages: BBCH 16/17 (6-8 fully unfolded true leaves) and BBCH 39/40 (row closing). Regardless of the methods of tillage or the year of observation, the results showed that the plants at BBCH16/17 stage were well-nourished with macroelements but malnourished with microelements, mainly iron and zinc. The microelement deficiency in the plants was a result of adjusted soil reaction, which varied from slightly acidic to neutral. At the BBCH 39/40 stage, there was a decreasing trend in the content of leaf macronutrients in the no-tillage systems treatments compared to the conventional tillage with the ploughing depth to 35 cm and manure application. The reduced tillage systems in sugar beet cultivation did not result in either a yield decrease or a worse technological quality of roots. The experimental factor had no significant effect on the content of molassegenic compounds in beet roots. A decreasing trend was observed in the content of α-amino nitrogen and potassium when compared to the traditional cultivation system. The study showed that the choice of a cultivation technology is of secondary importance as long as the plant grows in optimal conditions resulting from an appropriate site selection.
Energy Use of Greenhouse Waste Materials by Methane Fermentation
In Poland, the production of fruits and vegetables covering no more than 3% of agricultural land,... more In Poland, the production of fruits and vegetables covering no more than 3% of agricultural land, constitutes more than 36% of the commodity crop production and 14% of commercial agricultural production. According to the Polish Central Statistical Office in 2012 vegetable production was at the level of 4.553 million Mg, including tomatoes and cucumbers amounted together 11.8%. When harvesting and processing the vegetables, considerable amounts are waste materials. The source of such type of waste in the greenhouse are primarily non-commercial parts of plants i.e. leaves, stems as well as unclassified vegetables. Those waste materials are characterized by high degree of hydration and high content of organic matter, which in case of methane fermentation is extremely indispensable. Therefore, there is a possibility of management of such waste by biological treatment. This paper presents the results of energetic values of vegetable waste from greenhouse production. It has been stated th...
Computer image analysis in caryopses quality evaluation as exemplified by malting barley
SPIE Proceedings, 2015
One of the purposes to employ modern technologies in agricultural and food industry is to increas... more One of the purposes to employ modern technologies in agricultural and food industry is to increase the efficiency and automation of production processes, which helps improve productive effectiveness of business enterprises, thus making them more competitive. Nowadays, a challenge presents itself for this branch of economy, to produce agricultural and food products characterized by the best parameters in terms of quality, while maintaining optimum production and distribution costs of the processed biological material. Thus, several scientific centers seek to devise new and improved methods and technologies in this field, which will allow to meet the expectations. A new solution, under constant development, is to employ the so-called machine vision which is to replace human work in both quality and quantity evaluation processes. An indisputable advantage of employing the method is keeping the evaluation unbiased while improving its rate and, what is important, eliminating the fatigue factor of the expert. This paper elaborates on the topic of quality evaluation by marking the contamination in malting barley grains using computer image analysis and selected methods of artificial intelligence [4-5].
Identification of selected apple pests based on selected graphical parameters
SPIE Proceedings, 2013
ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. T... more ABSTRACT The aim of this work was a neural identification of selected apple tree orchard pests. The classification was conducted on the basis of graphical information coded in the form of selected geometric characteristics of agrofags, presented on digital images. A neural classification model is presented in this paper, optimized using learning sets acquired on the basis of information contained in digital photographs of pests. In particular, the problem of identifying 6 selected apple pests, the most commonly encountered in Polish orchards, has been addressed. In order to classify the agrofags, neural modelling methods were utilized, supported by digital analysis of image techniques.
Uploads
Papers by Jacek Przybył