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Journal articles on the topic 'Agricultural processing plants'
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Larry Leistritz, F., and Randall S. Sell. "Socioeconomic Impacts of Agricultural Processing Plants." Journal of the Community Development Society 32, no. 1 (March 2001): 130–59. http://dx.doi.org/10.1080/15575330109489696.
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Kára, J., Z. Pastorek, J. Mazancová, and I. Hanzlíková. "New mixtures and technologies for biogas production at biogas plants of agricultural type processing livestock slurry." Research in Agricultural Engineering 55, No. 2 (June 17, 2009): 62–68. http://dx.doi.org/10.17221/3/2009-rae.
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The basis of the biogas production in agriculture is the processing of waste agricultural products (particularly excrements of farm animals but also phytomass). Different but rather similar is the biogas production from biologically degradable municipal waste (BDMW) and biologically degradable industrial waste (BDIW) coming mainly from food industry. The processing of these wastes in agricultural biogas stations could significantly improve their economy. It is necessary to note that all these biogas stations differ from the wastewater cleaning plants where municipal sludge water from public sewers is processed. The municipal sludge water processing to biogas by anaerobic fermentation is a classical technology introduced all over the world. At present, about 100 wastewater cleaning plants operate in the Czech Republic using regular sludge processing into biogas. Electricity produced is utilised mainly for the needs of own operation of waste water treatment plant (WWTP), partly it is sold into public power net. The heat energy is used for heating in the process and its surplus is utilised for operational and administrative facilities. Usually, the heat and electricity quantities produced do not cover the wastewater cleaning plant operation. Agricultural biogas stations and biogas stations for BDMW processing provide considerably higher gas yields because they work with higher dry matter contents in substratum, i.e. 8–12% (compared with waste water treatment plants – 2–6%), and are able to produce high gas surpluses for following applications. Frequently discussed issue are the processing of slaughter waste and grass (or public green areas at biogas stations).
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ja, Athira, Prof K. Geetha, S. Arulraj, N. Megala, and Prasa na. "Survey on Identify the Agricultural Diseases Using Image Processing and Soft Computing Techniques." Alinteri Journal of Agriculture Sciences 36, no. 2 (July 26, 2021): 166–70. http://dx.doi.org/10.47059/alinteri/v36i2/ajas21130.
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The agricultural land mass is more than just being a feeding sourcing in today’s world. Agriculture productivity defines the economy of India in a great manner. So, in plants, disease detection plays a vital role in agriculture field. Automatic disease detection approaches are used for detecting plant diseases during the initial stages. To identify the agricultural diseases using digital image based on various features like color, textures and shape. Research firm currently doing a research to detect and diagnosis agricultural diseases based on digital image. This survey provides a better understanding of the soft computing techniques and image processing used for researcher and farmers to identify the agricultural diseases. This survey highlights several diseases of agricultural plants like rice, apple, cucumber, graphs, banana, cherry, wheat and sugarcane. And also this analysis work provides the comparison analysis of different research techniques in terms of their merits and demerits along with numerical analysis.
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Dereszewska, Alina, and Stanisław Cytawa. "PROCESSING OF AGRO-WASTES IN THE LIGHT OF CIRCULAR ECONOMY." Annals of the Polish Association of Agricultural and Agribusiness Economists XIX, no. 6 (January 10, 2018): 73–78. http://dx.doi.org/10.5604/01.3001.0010.7903.
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The article discusses the procedures of agricultural waste management in the context of the principle of maximum closed loop for organic compounds. The concept of regional agro-waste economy is presented taking into account existing technological solutions including agricultural biogas plants as well as biogas plants located at sewage treatment plants. The biogas potential for agricultural waste co-fermented with primary sludge of the ‘Swarzewo’ wastewater treatment plant was estimated.
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Kiryluk, Aleksander. "Biogazownie w kontekście zrównoważonego rozwoju obszarów wiejskich na przykładzie województwa podlaskiego." Polish Journal for Sustainable Development 24, no. 2 (2020): 45–52. http://dx.doi.org/10.15584/pjsd.2020.24.2.5.
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One of the causes of climate change is high exhaust emissions from combined heat and power plants and many case furnaces. In order to release these verbal energy sources, gradually switch to the production of electricity from renewable sources (RES). Hence, there are many sources of renewable energy. The article presents the possibility of obtaining energy from agricultural substrates. One of the methods is the production of biogas in the methane fermentation process in agricultural biogas plants. For the production of biogas in agricultural biogas plants in agricultural biogas is maize silage, slurry, and other waste from agriculture and agri-food processing. 9 biogas plants are registered in the Podlaskie Voivodship, producing about 9.5 million m3 of biogas, allowing for the production of 7.695 MWe. The substrates in these biogas plants are mainly maize and agricultural waste (slurry). The positive effects of cultivating plants for energy purposes, as well as the impact of monoculture perennial crops on the agricultural cultivation of agrocenoses were indicated.
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Grismer, Mark E., and Heather L. Shepherd. "Plants in constructed wetlands help to treat agricultural processing wastewater." California Agriculture 65, no. 2 (April 2011): 73–79. http://dx.doi.org/10.3733/ca.v065n02p73.
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Sharma, Savita. "Pest Detection in Plants Using Convolutional Neural Network." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 1583–92. http://dx.doi.org/10.22214/ijraset.2021.38890.
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Abstract: Agriculture or farming is an imperative occupation since the historical backdrop of humanity is kept up. Artificial Intelligence is leading to a revolution in the agricultural practices. This revolution has safeguarded the crops from being affected by distinct factors like climate changes, porosity of the soil, availability of water, etc. The other factors that affect agriculture includes the increase in population, changes in the economy, issues related to food security, etc. Artificial Intelligence finds a lot of applications in the agricultural sector also which includes crop monitoring, soil management, pest detection, weed management and a lot more. Significant problems for sustainable farming include detection of illness and healthy monitoring of plants. Therefore, plant disease must automatically be detected with higher precision by means of image processing technology at an early stage. It consists of image capturing, preprocessing images, image segmentation, extraction of features and disease classification. The digital image processing method is one of those strong techniques used far earlier than human eyes could see to identify the tough symptoms. Considering different climatic situations in various regions of the world that impact local weather conditions. These climate changes affect crop yield directly. There is a great demand for such a platform in the world of today which would enable the farmer market his farm products. We have proposed in this study a system where farmers can sell their products directly to customers without the intervention of distributors and traders. The predictive analytics system is necessary for the farmer to get the maximum yield which benefit the farmer. This may be done if the environment, market conditions and knowledge of the timely planning of farms are known properly. Keywords: Pest Detection, Artificial Intelligence, Agriculture, Image processing, Convolutional Neural Networks
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Nagila, Ashish, and Abhishek K. Mishra. "The effectiveness of machine learning and image processing in detecting plant leaf disease." Scientific Temper 14, no. 01 (March 25, 2023): 8–13. http://dx.doi.org/10.58414/scientifictemper.2023.14.1.02.
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In our daily lives, the agricultural sector is crucial. Therefore, it is crucial to be clear about the steps taken to identify any diseases on agricultural plants’ leaves. Plant leaf disease is a significant issue or contributor to crop losses in an agricultural context. Some farmers are able to know every disease name and how to prevent them as it becomes increasingly crucial to recognize the sickness. Different plant leaf diseases appear during various seasons. This problem can be resolved using a deep learning-based approach by identifying the affected regions in plant leaf images, enabling farmers to better comprehend the disease. The primary goal of this research is to survey several image-processing methods for detecting plant diseases and to compare them. India is an agricultural nation, and the majority of its people depend on agriculture for a living. Focusing on farming with modern technology is essential to ensuring their comfort and ease of living. Crop productivity may be greatly increased by introducing new technologies. An autonomous plant disease detection method using image processing and a neural network methodology can be utilized to solve issues with plant and agricultural diseases. Plants can contract a wide range of illnesses. Different patterns are needed to detect various disorders.
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Vafoev, Safo, Ilkhomjon Turdibekov, Rustam Vafoev, and Ozoda Vafoeva. "Initial results of watering plants via sub-irrigation technology." E3S Web of Conferences 264 (2021): 03056. http://dx.doi.org/10.1051/e3sconf/202126403056.
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In this developing world, saving water is the main problem for agricultural sciences. So, in this field, scientists are using many methods to save water-for instance, traditional irrigation, drip irrigation, sprinkler irrigation, sub-irrigation, and others. Solving irrigation and the problems in this article demonstrated the sub-irrigation method for agriculture plants in the Uzbekistan regions. According to watering theory in the field condition and compared to drip irrigation in the region, scientifically experiment was done. According to the results of the study, this method will automate the stability of soil moisture in the irrigation of agricultural crops: save 4 … 5 times water and prevent soil salinization; the cost of processing plants and fuels and lubricants with the help of technical means is sharply reduced; land use coefficient increases; hardening of crop rows and the number of their processing is sharply reduced; it is guaranteed to increase crop yields by mixing the juice with water; environmental pollution and soil salinity are sharply reduced. In the case of drip irrigation of agricultural crops, flexible plastic pipes with a diameter of 16… 20 mm are laid on the soil near the crop stalks, from which water holes or cracks are formed at certain intervals, from which water drips and irrigates crops. It is also possible to mix the juice of chemical and local fertilizers with water.
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Nova Ria Sar, Romoldus W. Samiu, and Randi Tangdialla. "Pengembangkan dan Memonitoring Tanaman Hidroponik dan Saluran Pengairan Sawah di Lembang Randan Batu." ASPIRASI : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat 1, no. 5 (September 30, 2023): 109–14. http://dx.doi.org/10.61132/aspirasi.v1i5.363.
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This service aims to develop and monitor hydroponic plants in an effort to increase agricultural efficiency in Lembang Randan Batu. The hydroponic farming method was chosen as a solution to increase agricultural efficiency by utilizing water optimally and reducing land use. Apart from that, cleaning of rice field irrigation channels is carried out to reduce environmental pollution due to plastic waste. This research uses the method of selecting plants, creating a hydroponic system, planting and maintaining plants, collecting plastic waste, sorting and processing plastic waste. The research results show that hydroponic plants can grow well and provide satisfactory results, while cleaning rice field irrigation channels can reduce environmental pollution due to plastic waste. This service contributes to the development of sustainable agriculture and plastic waste management in Lembang Randan Batu.
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Apazhev, A. K., Y. A. Shekikhachev, A. G. Fiapshev, L. Z. Shekikhacheva, and B. A. Fiapshev. "Environmentally oriented disposal of waste from agricultural enterprises in a biomethane plant." IOP Conference Series: Earth and Environmental Science 1112, no. 1 (December 1, 2022): 012023. http://dx.doi.org/10.1088/1755-1315/1112/1/012023.
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Abstract The article deals with the problem of using agricultural waste for biogas production. To create the material and technical base of agriculture, it is necessary to widely introduce new technologies for the use of agricultural waste, which account for a significant share of local renewable energy sources, comprehensive mechanization and automation of production processes, as well as specialization and cooperation at all stages. A promising direction for providing agricultural enterprises with cheap energy sources is the processing of biological masses and the production of biogas, the use of agricultural waste, waste from crop production, animal husbandry and poultry farming. Disposal of the aforementioned waste is a serious problem, and the use of biogas plants as installations for obtaining alternative energy resources is the most promising direction for their processing. The use of biogas plants as an alternative energy source is largely determined by their design properties and technological processes. A technological scheme for the use of waste based on an original biomethane plant is proposed, the implementation of which will solve the problem of the practical development of potential energy at least part of bioenergy resources, which is of great importance for the development of rural energy.
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Fountsop, Arnauld Nzegha, Jean Louis Ebongue Kedieng Fendji, and Marcellin Atemkeng. "Deep Learning Models Compression for Agricultural Plants." Applied Sciences 10, no. 19 (September 30, 2020): 6866. http://dx.doi.org/10.3390/app10196866.
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Deep learning has been successfully showing promising results in plant disease detection, fruit counting, yield estimation, and gaining an increasing interest in agriculture. Deep learning models are generally based on several millions of parameters that generate exceptionally large weight matrices. The latter requires large memory and computational power for training, testing, and deploying. Unfortunately, these requirements make it difficult to deploy on low-cost devices with limited resources that are present at the fieldwork. In addition, the lack or the bad quality of connectivity in farms does not allow remote computation. An approach that has been used to save memory and speed up the processing is to compress the models. In this work, we tackle the challenges related to the resource limitation by compressing some state-of-the-art models very often used in image classification. For this we apply model pruning and quantization to LeNet5, VGG16, and AlexNet. Original and compressed models were applied to the benchmark of plant seedling classification (V2 Plant Seedlings Dataset) and Flavia database. Results reveal that it is possible to compress the size of these models by a factor of 38 and to reduce the FLOPs of VGG16 by a factor of 99 without considerable loss of accuracy.
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Fathima, Asna. "Optimizing Agricultural Residue: A Comprehensive Review on Waste Utilization and Management, with Special Emphasis on Vermicomposting." African Journal of Biological Sciences 6, no. 5 (June 27, 2024): 5639–56. http://dx.doi.org/10.48047/afjbs.6.5.2024.5639-5656.
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Agriculture wastes are the product,that are theremainsof agriculture products. These remains can be useful in many other ways. Globally, agriculture usage is increasing day by day which also leads to agriculture waste production. Agricultural waste, by-products, and co-products typically refer to residual materials from plants or animals that are not utilized as food or feed, and may contribute to extra environmental and economic challenges within the farming and initial processing stages. Therefore, management of agriculture waste is crucial.
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Russell, J. M., R. N. Cooper, and S. B. Lindsey. "Reuse of Wastewater from Meat Processing Plants for Agricultural and Forestry Irrigation." Water Science and Technology 24, no. 9 (November 1, 1991): 277–86. http://dx.doi.org/10.2166/wst.1991.0256.
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Meat-processing wastewaters contain high concentrations of nitrogen, phosphorus and potassium (in this study 40-230 g m−3, 6-35 g m−3 and 20-130 g m−3 respectively), but only low concentrations of heavy metals and other toxic compounds. The nutrients can be recovered by agricultural or forestry irrigation schemes. Application of these wastes to land in excess of plant requirements results in elevated concentrations of organic nitrogen, nitrate, phosphorus, potassium and sodium in the plant material, with nitrate approaching levels toxic to ruminant animals. Excess phosphorus that is applied to the land is precipitated as metal phosphates, and excess nitrogen is partially denitrified, thereby reducing nitrate contamination of ground water. At an experimental pasture site, receiving nitrogen loadings of 1200 kg N ha−1 y−1, denitrification losses averaged about 4% of that applied. Denitrification losses at an experimental forestry site receiving 715 kg N ha−1 y−1 averaged about 27%. Similar losses were observed at a full-scale pasture and forestry irrigation site. Sodium concentrations in meat processing wastewaters could, on occasions, detrimentally affect soil structure and sodium concentrations should be closely monitored.
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Kumar, A. V. Sumanth. "Controlling of Pest using Image Processing and Machine Learning Methods." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 15, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem34013.
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In addition to giving humans food, agriculture is a major source of resources for every nation's economy. Pests and insects cause damage to crops, making them extremely risky for the crop's overall growth. In the world of agriculture, early tormentor identification may provide significant challenges. Using insecticides is the greatest way to control the tormentor infection. On the other hand, overuse of pesticides is detrimental to animals, plants, and even the general population's automatic method of early insect detection. Digital image processing techniques are widely used in agricultural research and offer great perspectives, especially in the field of plant protection, which leads to crop management. This study discusses a novel approach to pest monitoring through early detection. Using a photography camera, one may create nonheritable images of pest-ridden leaves. An automated system that can identify the type of pests on crops in addition to examining the crops to detect infestations of tormentors is required. Support Vector Machine (SVM) is utilized for the categorization of images with and without pests, while the YOLO algorithmic method is used for tormentor detection. Key Words: Image Processing, Pesticides, Machine Learning, Agriculture, Plants, YOLO.
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Tedesco, Marino José, Márcio Henrique Lauschner, Clesio Gianello, Leandro Bortolon, and Claudio Henrique Kray. "Land disposal potential of tobacco processing residues." Ciência Rural 41, no. 2 (February 4, 2011): 236–41. http://dx.doi.org/10.1590/s0103-84782011005000002.
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Brazil is one of the leaders in the production and trading of tobacco leaves in the global market, which results in a large amount of residues that would be recycled and used as soil fertilizers in agriculture. This research aimed to study the land disposal potential and agricultural use of tobacco processing residues (TPRs), their mineralization and the nutrient supply to the plants. The study was carried out in an open area using pots with 32dm³ of a sandy soil (Paleudult), provided with water drainage collectors and tilled with three corn plants each. Eighteen treatments were tested with mineral fertilization, poultry manure (PM), earthworm compost (EC) and increasing rates (0, 7.5, 15, 30 e 60t ha-1) of TPR D (dust) and TPR S (stem fibers).Treatments with TPRs (15t ha-1) plus mineral supplementation two by two (NP, NK and PK) were also tested, with four replications each. The experiment started in 01/15/2004 and conducted until 03/16/2004, when corn plants were harvested. The response curves showed that the residues application rates between 15 and 20t ha-1 are most adequate for the studied soil. The results indicated that both TPRs may be important sources of biomass and potash and have potential to be recycled in the soil, supplying part of the macronutrients required for proper plant growth.
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Apazhev, A. K., B. A. Fiapshev, A. G. Fiapshev, O. Kh Kilchukova, T. Kh Pazova, and V. B. Dzuganov. "Processing of Manure in Biogas Plants." Elektrotekhnologii i elektrooborudovanie v APK 70, no. 2(51) (July 28, 2023): 100–105. http://dx.doi.org/10.22314/2658-4859-2023-70-2-100-105.
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Biogas obtained from agricultural waste is becoming increasingly important as a renewable resource. Biogas can be obtained by biological and thermochemical methods. The first is the decomposition of organic substances without air access due to the fermentation process, which takes place at a temperature of 30-40 degrees Celsius for «clean» waste (for example, microbiological industry) or 55-60 degrees Celsius for animal waste and urban wastewater. As a result of decomposition, biogas and a number of valuable components (nitrogen, phosphorus, potassium oxide) are formed, from which a highly effective organo-biofertilizer is prepared. (Research purpose) The research purpose is increasing the uniformity of the temperature field over the volume of the bioreactor to intensify the thermophilic process of anaerobic processing, increasing the yield of biogas and improvement of the quality of the biofertilizer. (Materials and methods) For the purpose of laboratory experiments, droppings from the poultry house of the peasant farm “Khemzet” of the Kabardino-Balkarian Republic were used with the analysis performed in the laboratory of the agrochemical service “Kabardino-Balkarian”. The total daily heat consumption and the capacity of the heat exchanger-agitator were determined using mathematical modeling and the laws of thermodynamics. (Results and discussion) The contents of the methane tank were heated by a heat exchanger using a coolant, and mixing was carried out using a mechanical stirrer combined into one heat exchanger–stirrer unit powered by an electric motor. It was shown that during the thermophilic process, more intensive and deeper fermentation of precipitation occurs, which contributes to a decrease in the volume of the methane tank, more effective destruction of helminths and weed seeds. It was found that during thermophilic fermentation, a greater amount of heat is needed to heat the sediment in the methane tank, 12-15 days are enough to disinfect the mass. (Conclusions) It was found that the optimal values of the temperature of the substrate processing process are 56.6 degrees Celsius; the mixing time is 17 minutes, the number of revolutions of the heat exchanger-agitator is 7.5 revolutions per minute. Chemical analysis of the obtained organo-biofertilizers was carried out.
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Muradin, Magdalena, Katarzyna Joachimiak-Lechman, and Zenon Foltynowicz. "Evaluation of Eco-Efficiency of Two Alternative Agricultural Biogas Plants." Applied Sciences 8, no. 11 (October 28, 2018): 2083. http://dx.doi.org/10.3390/app8112083.
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Implementation of the circular economy is one of the priorities of the European Union, and energy efficiency is one of its pillars. This article discusses an effective use of agri-food industry waste for the purposes of waste-to-energy in biogas plants. Its basic objective is the comparative assessment of the eco-efficiency of biogas production depending on the type of feedstock used, its transport and possibility to use generated heat. The environmental impact of the analysed installations was assessed with the application of the Life Cycle Assessment (LCA) methodology. Cost calculation was performed using the Levelized Cost of Electricity (LCOE) method. The LCA analysis indicated that a biogas plant with a lower level of waste heat use where substrates were delivered by wheeled transport has a negative impact on the environment. The structure of distributed energy production cost indicates a substantial share of feedstock supply costs in the total value of the LCOE ratio. Thus, the factor affecting the achievement of high eco-efficiency is the location of a biogas plant in the vicinity of an agri-food processing plant, from which the basic feedstock for biogas production is supplied with the transmission pipeline, whereas heat is transferred for the needs of production processes in a processing plant or farm.
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Smirnov, Igor G., Dmitriy O. Khort, Rostislav A. Filippov, Alexey I. Kutyrev, and Anatoly A. Artiushin. "Automated Unit for Magnetic-Pulse Processing of Plants in Horticulture." Mordovia University Bulletin, no. 4 (December 28, 2018): 624–42. http://dx.doi.org/10.15507/0236-2910.028.201804.624-642.
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Introduction. The current level of agricultural production, including horticulture, is determined by intelligent machine technologies and new generation technical means with modern information and instrument support. The implementation of digital intelligent agricultural technologies in industrial gardening requires a fundamental change in the paradigm of technical support, based on the development and application of new automatic and unmanned machines, equipment and software for managing work processes of machines, navigating technical means, controlling the implementation of technological operations, monitoring the yield of agricultural crops, analyzing diseases and pests on plants and other technological functions. Materials and Methods. 3D model is visualized in the computer-aided design “KOMPAS-3D” through using the methods of mathematical modeling, theoretical mechanics and optimal design. A prototype of an automated unit for magnetic pulse processing of plants is made. The program code for calculating the required movement of the actuator rod is developed in the Sublime Text editor. C++programming language was used. The functionality of the computer program is related to the capabilities of controllers STM32, Arduino Mega/ Uno/Nano. Nextion 2.4 (the TFT screen 320x240) for the graphical output and interaction was used. Results. An automated unit with the algorithm of the drive control system of working bodies were developed during the technological operation of magnetic pulse processing of plants, taking into account the agro-technological parameters of garden plantations. A computer program with both automat and remote control was designed for driving the working bodies. Conclusions. The unit allows introducing a new environmentally safe technological method of stimulating vital and growth processes of fruit crops. This device provides the most efficient operation through automatic adjustment to various agro-technological parameters of plantings, providing the required value of magnetic induction in the working area on plant objects in the field. Keywords: magnetic pulse processing, control system, automated unit, irradiation of plants, gardening, low-frequency magnetic field For citation: Smirnov I. G., Khort D. O., Filippov R. A., Kutyrev A. I., Artiushin A. A. Automated Unit for Magnetic-Pulse Processing of Plants in Horticulture. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2018; 28(4):624–642. DOI: https://doi.org/10.15507/0236-2910.028.201804.624-642
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Cahyanto, T. A., S. Wahjuni, H. Sukoco, H. Rahmawan, and S. N. Neyman. "Intelligent ubiquitous technology as a precision agri-food framework: a proposed framework." IOP Conference Series: Earth and Environmental Science 1041, no. 1 (June 1, 2022): 012022. http://dx.doi.org/10.1088/1755-1315/1041/1/012022.
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Abstract Agri-Food is another term for the agriculture-based food sector, which is currently one of Indonesia’s main pillars of the national economy. One of the well-known plants for agricultural-based food processing called Agri-Food in Indonesia is Cocoa. Cocoa is one of the plantation commodities that has an essential role in economic activities in Indonesia. Given the critical role of cocoa as a source of the country’s economy, it must guarantee productivity and quality of cocoa and sustainability. To ensure cocoa productivity and quality sustainability, agricultural activities in today’s era can integrate intelligent ubiquitous technology as a framework for obtaining precise production results. What can measure precision production results from three aspects: increasing agricultural land productivity, reducing production costs, and minimizing the environmental impact. This paper discusses the proposed framework with intelligent ubiquitous technology to support precision agri-food that focuses on context-aware systems. The context-aware system in the proposed framework is expected to become a control center in collecting and processing data in real-time to help farmers make the best decisions regarding weather conditions and diseases caused by plants.
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Ngadisih, Ngadisih, Azka Sinatrya, Indah Retno Wulan, Jeane Claudea Tanjung, Sahidatun Fahima, and Prieskarinda Lestari. "Potensi Ancaman dan Upaya Mitigasi Emisi Gas Rumah Kaca di Sektor Pertanian Indonesia : Tinjauan Sistematis atas Literatur." Jurnal Teknologi Lingkungan Lahan Basah 12, no. 1 (January 15, 2024): 245. http://dx.doi.org/10.26418/jtllb.v12i1.74231.
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Agriculture in Indonesia is a vital sector that can fulfill food needs and provide livelihoods. However, agriculture also contributes to greenhouse gas (GHG) emissions. Indonesia's agricultural sector contributes around 14% of emissions globally and 7% nationally. Greenhouse gas emissions such as methane gas CH4, carbon dioxide CO2, and nitrous oxide N2O are generated from agricultural activities ranging from land preparation, fertilization, transportation of agricultural products, to processing in factories. These greenhouse gas emissions influence the climate change that occurs and affect the increase in temperature and rainfall patterns. In mitigation efforts, this study noted several steps taken. Energy conversion, such as the use of biogas from animal manure can reduce CH4 emissions and the use of pellets from palm waste processing can reduce CO2 emissions. Reforestation with special carbon-absorbing plants to reduce CO2 emissions. The use of organic fertilizers as a partial replacement for inorganic fertilizers is useful in reducing CH4 and N2O emissions. Through this systematic review, it is expected to contribute to the understanding of the role of the agricultural sector in greenhouse gas emissions in Indonesia and provide insight into mitigation efforts that can be applied in achieving sustainable agriculture.
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Trifonov, S. V., N. A. Tubol, and A. A. Tikhomirov. "Testing of the method of human metabolites gas products processing deep purification on lettuce plants." IOP Conference Series: Earth and Environmental Science 981, no. 3 (February 1, 2022): 032092. http://dx.doi.org/10.1088/1755-1315/981/3/032092.
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Abstract Development of technologies for fabricating environmentally friendly fertilizers from organic wastes is an important factor for establishing environmentally friendly zero-waste production, including agriculture. Implementation of this approach entails problems associated with the treatment of byproducts of such processes. In the present study, the technology of physicochemical purification of gases produced by human waste processing was tested on lettuce plants. It has been shown experimentally that the proposed method of deep purification is able to reduce the inhibitory effect of gas on plants. The results can be used to develop agricultural technologies, closed-loop production technologies in other fields, and scientific principles for constructing life support systems intended for space missions.
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Sachan, Dhruvendra Singh, K. Jaisimha Reddy, Akhilesh Mishra, Avinash Kumar Rai, Anam Khan, Barinderjit Singh, and Charu Rajpal. "Nanomaterials and Diverse Agricultural Applications: A Comprehensive Review." International Journal of Environment and Climate Change 13, no. 9 (June 27, 2023): 131–40. http://dx.doi.org/10.9734/ijecc/2023/v13i92215.
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Climate change, the population explosion and the growing demand for good food and health require better, more reliable and more efficient. The different shape, size, composition and ability to interact with organic compounds make nanomaterials and technology widely used. Nano formulations and their applications in agriculture in the form of agrochemicals for crop protection, toxicity identification by nanobiosensors, genetic manipulation of plants treated by nanodevices, and rapid and efficient diseases of plants. The delivery of genetic material and proteins via nano-arrays has been proven in crop engineering, drug delivery and environmental monitoring. Nanotechnology also benefits the food industry by improving all stages of food production from food processing to production, processing, packaging, safety, extending shelf life, testing for disease and creating smart foods. Therefore, technology can meet the needs of most consumers, including the improvement of food products and their sensations, and can improve product quality, texture soft and nutritious food without affecting its natural properties.
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Santos, Neisvaldo Barbosa Dos. "ECONOMIC PERFORMANCE OF MOTOR GRADERS IN SUGARCANE (Saccharum spp.) PROCESSING PLANTS." ENERGIA NA AGRICULTURA 32, no. 3 (December 20, 2017): 209. http://dx.doi.org/10.17224/energagric.2017v32n3p209-214.
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Brazil is the world's largest producer of sugarcane for mills. They use tractors with various agricultural of equipment in the mechanized operations of periodic soil preparation, planting, cropping and harvesting. Therefore, several studies have proven the economic importance of the cost generated by these machines. However, few studies highlight the performance of a motor grader, which has both functional and economic importance, due to its wide use in the agricultural activities in the mill. The objective of this study was evaluated of the systemic mode, the influence of economic performance variables in the cost and in time useful lifespan of a motor grader in an agricultural operation. In this study, machines with nominal power of 116 kW (158 cv) and 159 kw (216 cv) were utilized. For this study, a computational model called “TerraPlanCana” was developed in electronic spreadsheet and programming language. The results showed that the increase in the useful life in years reduces the fixed annual cost of the machines and when the hours of useful life increase, the hourly cost decreases. The increase of the useful life in year or hour raises the total cost, reducing the gains of the mill.KEYWORDS: Cost, Agricultural mechanization, Computer model, Income, Fleet renewal.DESEMPENHO ECONÔMICO DE MOTONIVELADORAS EM USINA DE CANA-DE-AÇÚCAR (Saccharum spp.)Resumo: O Brasil é o maior produtor mundial de cana-de-açúcar para as usinas. Estas utilizam tratores com diversos equipamentos agrícolas, nas operações mecanizadas de preparo periódico do solo, plantio, tratos culturais e colheita. Devido a isso, diversos estudos tem comprovado a importância econômica do custo gerado por estas máquinas. Entretanto, existe a motoniveladora, que tem importância funcional e econômica, devido sua ampla utilização nas atividades agrícolas das usinas e poucos estudos destacam seu desempenho. O objetivo do trabalho foi avaliar de modo sistêmico, a influência das variáveis de desempenho econômico no custo e no tempo de vida útil da motoniveladora em operação agrícola. No trabalho foram consideradas máquinas com potência nominal de 116 Kw (158 cv) e de 159 Kw (216 cv). Para o trabalho foi desenvolvido um modelo computacional, denominado “TerraPlanCana”, em planilha eletrônica e em linguagem de programação. Os resultados evidenciaram que o aumento da vida útil em anos reduz o custo fixo anual das máquinas e quando crescem as horas de vida útil o custo horário diminui. O crescimento da vida útil em ano ou em hora eleva o custo total, diminuindo os ganhos da usina.PALAVRAS-CHAVE: Custo, Mecanização Agrícola, Modelo computacional, Renda, Renovação de frota.
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Górny, Mieczysław. "Ekorozwój jedyną drogą polskiej wsi i rolnictwa." Studia Ecologiae et Bioethicae 2, no. 1 (December 31, 2004): 389–98. http://dx.doi.org/10.21697/seb.2004.2.1.23.
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Limiting agricultural production with the use of industrial methods is in society's best interest. Industrial farms are places where the natural degradation of soil, rural landscapes, and ground waters takes place. They are also places where farm animals are mistreated and suffer. The crops, being high are, at the same time, of low quality, posing threat to people's and animals' health. The only agricultural managing system which complies with the idea of eco-development is ecological farming, whose initiators were: Dezydery Chłapowski at the beginning of the 9th century, officer, Napoleon's aide-de-camp as well as Rudolf Steiner from Austria, philosopher, theologian, and occultist at the beginning of the 20th century. Neither of them had agricultural education, both were active in the area now belonging to Poland (in Turew in Wielkopolska district and in Kobierzyce near Wroclaw respectively). Ecological farming based on family farms is a combination of ethical, ecological, and economic approaches. Not only does it provide the highest quality food and feeding stuff but it also helps protect the environment, fertilizes the soil, caters to good growth conditions of cultivated plants and animals, provides new jobs, and improves living conditions in rural areas.
The ecological farm must make sure: there is a balance between plant and animal production, take care of the landscape, prevent and not only fight pests. Every ecological farmer's duty is a continuous struggle to increase the fertility of the soil. He should not misunderstand the aim or the methods of fertilizing so that he can deliver high-quality food which undergoes the system of control.
There are about 2 000 certified ecological farms in Poland with an average area of 15 hectares, the total acreage being 50 000 ha. There are more than 20 ecological products processing plants (mills, bakeries, dairy plants, fruit, vegetables, and meat processing plants). There are 8 agricultural high schools where the rules of ecological farming are taught. Some schools run their own ecological farms and an experimental ecological farm is being prepared by the Warsaw University of Agriculture (SGGW). There are also 3 associations of ecological farmers and gardeners as well as 6 organizations that control and issue certificates to farms and processing plants. In the Ministry of Agriculture, there is the Department of Ecological Agriculture as well as the Ecological Farming Board.
Ecological farms are used in medical and social therapy, play an important role in ecological education, and increasing people's awareness. It should be hoped that ecological farming, bringing much good and being based on the idea of sustainable development, will eventually become part of far-reaching plans concerning rural and agricultural development in Poland.
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Piekutin, Janina, Monika Puchlik, Michał Haczykowski, and Katarzyna Dyczewska. "The Efficiency of the Biogas Plant Operation Depending on the Substrate Used." Energies 14, no. 11 (May 28, 2021): 3157. http://dx.doi.org/10.3390/en14113157.
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The study aimed to assess the most efficient solution of raw material management in selected biogas plants into the concept of circular economy and evaluate the most efficient solution of raw material management in selected biogas plants due to the quality and quantity of the feed and the final product obtained, which is biogas, as well at the closed circulation (circular economy). The study evaluated two agricultural biogas plants on a real scale and one at the sewage treatment plant (in real scale) in northeastern Poland. A year-long study showed that in technical terms, the best work efficiency is achieved by agricultural biogas plants processing: silage, manure, apple pomace, potato pulp (biogas plant No. 1), followed by biogas plant No. 3 processing chicken manure, decoction, cattle manure, poultry slaughterhouse waste (sewage sludge, flotate, feathers), and finally, the lowest efficiency biogas plant was No. 2, the sewage treatment plant, which stabilized sewage sludge in the methane fermentation process. Moreover, based on the results, it was found that agricultural biogas gives the best efficiency in energy production from 1 ton of feed.
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Jung, Wongeon, Kyungran Kim, Hyocher Kim, and Mintae Seo. "Analysis on the Root Cause of Safety Accidents in Agricultural Product Processing Plants." Journal of the Ergonomics Society of Korea 40, no. 6 (December 31, 2021): 401–11. http://dx.doi.org/10.5143/jesk.2021.40.6.401.
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FUKUDA, Mamoru, Nobuhide ITOH, Hitoshi OHMORI, Teruko KATO, and Shinjiro UMEZU. "Development of agricultural grinding wheel for processing by using the material from plants." Proceedings of Ibaraki District Conference 2018.26 (2018): 721. http://dx.doi.org/10.1299/jsmeibaraki.2018.26.721.
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Anarbaev, Anvar, Obid Tursunov, Dilshod Kodirov, Zayniddin Sharipov, and Farrukh Mukhtarov. "Changes of chemical reactions in soil during electric processing by means of UV-radiation." E3S Web of Conferences 304 (2021): 01014. http://dx.doi.org/10.1051/e3sconf/202130401014.
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The technology of electro-processing by UV-radiation soil of agricultural plants is considered. The mechanism of the effect of UV irradiation to change by redox reactions a chemical potential of the soil is shown. As the result of experimental researches, optimum parameters for processing soils with ultraviolet radiation lamps for increasing the absorption of the most mobile manganese forms in plants are defined.
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Kuz’michev, Aleksey V., Dmitriy A. Tikhomirov, Aleksey V. Khimenko, Nikolay G. Lamonov, and Stanislav S. Trunov. "Possible Directions in the Improvement of Small-Sized Household Drying Plants." Elektrotekhnologii i elektrooborudovanie v APK 3, no. 44 (September 2021): 9–14. http://dx.doi.org/10.22314/2658-4859-2021-68-3-9-14.
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The main problem that we have to face in agriculture is processing and storage of agricultural products. One of the most preferred processing methods is drying. The dried product is stored longer, while the requirements for storage conditions are more tolerant. Standard dryers are a sealed chamber where the dried product is located; they work in cycles: loading-drying-unloading. Such characteristics are well suited for small agricultural enterprises. Traditional drying methods, as a rule, involve large energy costs and take a long time. The development of highly efficient drying equipment is possible because of improving the technology and designs of devices that intensify heat and mass transfer, by creating combined dryers and optimal drying schemes, combining the drying process with other processes. (Research purpose) The research purpose is in considering rational methods of physically justified processes of high-intensity drying of agricultural products for the development of effective drying equipment. (Materials and methods) The description of heat and mass transfer processes allows you to choose a rational method; solve the problem of forecasting processes; determine the way to increase the efficiency of drying and equipment. (Results and discussion) The rate of moisture transfer in the material depends on the moving of moisture inside and the surface of the material to the drying agent. The value of the drying speed depends on the temperature, humidity and air speed, the dried air accelerates the drying process. (Conclusions) The magnitude and relative direction of the thermodynamic forces of moisture conductivity and thermal moisture conductivity determines the intensity of material dehydration. For a specific drying method, optimal technological modes of dehydration should be created, ensuring the production of high-quality materials. Closed-cycle devices with recirculation of the drying agent and heat energy recovery reduce the energy consumption for the process.
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Kříž, Jan, Lidmila Hyšplerová, Marek Smolík, Stanislav Eminger, Agáta Vargová, Josef Keder, Radomír Srněnský, Agnieszka Dołhańczuk-Śródka, Zbigniew Ziembik, and Maria Wacławek. "Modelling of Emissions from Large Biogas Plants." Chemistry-Didactics-Ecology-Metrology 20, no. 1-2 (December 1, 2015): 49–58. http://dx.doi.org/10.1515/cdem-2015-0005.
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Abstract The main objective of the “Guidelines for the development of agricultural biogas plants in Poland within 2010-2020”, is a construction of biogas plants processing agricultural biomass resources with suitable conditions in each municipality. In the Czech Republic produces about 6.5% of energy from renewable sources. Biogas plants give - contrary to solar and wind electricity stations - the stable performance throughout the whole year. Biomass should be a key source for achieving the Czech EU commitment to produce 13% of energy from renewable sources in 2020. The experience, where 317 Agricultural biogas plants are currently in operation, has shown that there are considerable problems with a proper location of newly designed agricultural biogas plants in the landscape. The Czech-Polish border area is mainly flat wooded recreation region. For these reasons, the Gaussian model SYMOS’97 (version 2013), adapted for odour dispersion modelling from large agricultural sources is supposed to be suitable for this area. It is appropriate for training of students. For these reasons, students from the University of Hradec Kralove and the University of Opole in the frame of their academic exchange and professional internships are acquainted with the technological principles of biogas plants and in environmental mathematical and statistical modelling of the spread of emissions from large industrial and agricultural sources. In this article we present methods for education on these professional areas.
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Warnita, Warnita, Nalwida Rozen, and Novizar Nazir. "Empowerment of Community with the Application of Compost on the Cultivation and Post-Harvest of Onion." AJARCDE | Asian Journal of Applied Research for Community Development and Empowerment 4, no. 1 (March 5, 2020): 13–21. http://dx.doi.org/10.29165/ajarcde.v4i1.32.
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Kenagarian (West Sumatra traditional village) Andaleh is located at the base of Mount Marapi in Batipuh Tanah Datar District, West Sumatra. The main livelihoods of the population are farming by planting rice, vegetable crops, ornamental plants, and cinnamon. In general, farmers in this location increase the yield of vegetables (onion) using artificial fertilizers. Sometimes it requires limited chemical fertilizer, difficult to obtain and expensive. Of course, this will burden farmers in the production of onion is a daily necessity of the community. At this location, there are many titonia plants and agricultural waste. The solution given is agricultural waste and plant processing into compost. Compost can increase growth and yield of onion bulbs. The objectives to be achieved in Community Service and Empowerment Program (KKN-PPM) activities are 1) Making compost using straw and agricultural waste and its application as organic fertilizer when mapping the red plotters, 2) Applying agricultural waste compost in the cultivation of onion 3) Processing the onion bulbs into the fried onion. The methods applied were debriefing students, counseling, training and demonstration plots with farmers. Activities that have been carried out are counseling about good onion cultivation, counseling about the benefits of organic fertilizer (compost) to 1) improve soil improvement and sources of nutrients for plants. 2) training to make compost from straw and agricultural waste using Effective Microorganism EM-4, 3) supporting compost application in onion cultivation in farmers' fields and 4) processing of fried onion.
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Monigari, Vaishnavi. "Plant Leaf Disease Prediction." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 15, 2021): 1295–305. http://dx.doi.org/10.22214/ijraset.2021.36582.
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The Indian economy relies heavily on agriculture productivity. A lot is at stake when a plant is struck with a disease that causes a significant loss in production, economic losses, and a reduction in the quality and quantity of agricultural products. It is crucial to identify plant diseases in order to prevent the loss of agricultural yield and quantity. Currently, more and more attention has been paid to plant diseases detection in monitoring the large acres of crops. Monitoring the health of the plants and detecting diseases is crucial for sustainable agriculture. Plant diseases are challenging to monitor manually as it requires a great deal of work, expertise on plant diseases, and excessive processing time. Hence, this can be achieved by utilizing image processing techniques for plant disease detection. These techniques include image acquisition, image filtering, segmentation, feature extraction, and classification. Convolutional Neural Network’s(CNN) are the state of the art in image recognition and have the ability to give prompt and definitive diagnoses. We trained a deep convolutional neural network using 20639 images on 15 folders of diseased and healthy plant leaves. This project aims to develop an optimal and more accurate method for detecting diseases of plants by analysing leaf images.
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Mikhalchuk, M. V., and A. A. Bryl. "FEATURES OF HEAVY METAL ACCUMULATION IN PLANTS OF THE ZONE OF INFLUENCE OF ENTERPRISES PROCESSING LEAD-CONTAINING WASTE." Nature Management, no. 2 (December 12, 2022): 122–35. http://dx.doi.org/10.47612/2079-3928-2022-2-122-135.
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Information on the peculiarities of contaminant elements accumulation by cultivated and wild-growing plants in the zone of influence of Belinvesttorg-Splav LLC (Beloozersk), whose emissions into the air contain hazardous pollutants, including (heavy metals) HM, is presented. Analysis of the degree of elements accumulation by agricultural plants was carried out in comparison with subregional background values and permissible levels of veterinary and sanitary rules for ensuring the safety of feed, feed additives and raw materials for the production of mixed feed. As the main criterion for assessing the degree of contamination of HM leaves of wild plants, indicators of their background concentrations, as well as world averages, were used.
The established aero lead pollution of cultivated agricultural plants in the sanitary protection zone of Belinvesttorg-
Splav LLC and in the adjacent lands repeatedly exceeds the background and sanitary-hygienic values. Among the wild
plant species studied the most sensitive indicators of aerogenic pollution are: among the woody plants – common pine
(needles), in the group of bushes and shrubs – white mistletoe and common raspberry, among herbaceous plants – dioica
nettle. Research results testify to the necessity of sanitary protection zone extension for Belinvesttorg-Splav LLC at least
up to 1000 m (especially – according to the rose of prevailing winds) and cessation of agricultural activities within it.
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Golda Dilip, D. Prabhu,. "Chilly Leaves Diseases Identification Using MobileNet V2 Deep Learning Model." Journal of Electrical Systems 20, no. 3s (April 4, 2024): 150–57. http://dx.doi.org/10.52783/jes.1263.
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This work describes the application of pre-trained deep learning models (Mobile Net V1, Mobile Net V2) to image classification issues such as plant disease diagnosis. Regarding this, We provide a deep learning-based feature extraction technique for classifying leaf diseases of cold plants and identifying plant species. The automated diagnosis of plant diseases has brought about a transformation in the agriculture industry. Our main goal is to use neural networks for agricultural disease diagnosis and treatment. Plant diseases seriously impair the agriculture industry's financial standing. Managing an illness is a challenging endeavor. Usually, infections appear on the leaves or stems of plants, as do their symptoms, which include colorful spots or steaks. Compared to human labor, image processing technology enables faster and more accurate illness detection. Image processing is critical in the detection of plant diseases because it gives the best results with the least amount of human intervention. Deep learning helps to diagnose diseases and provide focused treatment.
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Mosslah, Abd Abrahim, and Amel H. Abbas. "An Analysis of Image Processing In Forestry and Agriculture Review." IOP Conference Series: Earth and Environmental Science 1202, no. 1 (July 1, 2023): 012003. http://dx.doi.org/10.1088/1755-1315/1202/1/012003.
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Abstract Numerous techniques have been demonstrated for computer technologies to increase agricultural output. One method that is becoming into a valuable tool for picture processing. In order to help academics and farmers improve agricultural practices, this study provides a brief assessment on the use of image processing in forestry and agriculture. Modern agricultural techniques, pesticides and herbicides, plant nutrition management and plant development monitoring benefit greatly from image processing techniques. A future potential for image processing in various agricultural business situations is highlighted in this research. Segmentation in this context refers to the division of pixels in a picture into plant and nonplant pixels. For subsequent plant analysis, like plant categorization (in another meaning: determining this plant was considered either a crop or maybe a weed. Based on this analysis, the successful work depends herbicide application in smart agricultural applications, In this process, excellence is crucial. Fragmentation is first focused on through survey and then image pre-processing is carefully examined. Here, at this stage, the backgrounds of the plants are segmented (i.e., the soil attachments are isolated on one side and the plant on the other). The main plant harvesting strategies are three of which are segmentation based on threshold, segmentation based on deep learning and segmentation based on color index. The focus of our review is on color index methods due to their abundance in the literature. Therefore, according to literature research completed in last decade, specifically starting in the year 2008 to 2021, a thorough evaluation of the Color index-based categorization approaches are shown. Finally, we list the difficulties and a few chances for new breakthroughs in this field.
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Ibrahim, Dr Abdul-Wahab Sami, and Dr Baidaa Abdul khaliq Atya. "Detection of Diseases in Rice Leaf Using Deep Learning and Machine Learning Techniques." Webology 19, no. 1 (January 20, 2022): 1493–503. http://dx.doi.org/10.14704/web/v19i1/web19100.
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Plant diseases have a negative impact on the agricultural sector. The diseases lower the productivity of the production yield and give huge losses to the farmers. For the betterment of agriculture, it is very essential to detect the diseases in the plants to protect the agricultural crop yield while it is also important to reduce the use of pesticides to improve the quality of the agricultural yield. Image processing and data mining algorithms together help analyze and detection of diseases. Using these techniques diseases detection can be done in rice leaves. In this research, the image processing technique is used to extract the feature from the leaf images. Further for the classification of diseases various machine learning algorithm like the random forest, J48 and support vector machine is used and the result is compared among different machine learning algorithm. After model evaluation, classification accuracy is verified using the n-fold cross-validation technique.
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Braguglia, Camilla M., and Simona Rossetti. "Editorial for Special Issue “Microorganisms and Organic Waste Valorisation”." Microorganisms 10, no. 8 (July 25, 2022): 1493. http://dx.doi.org/10.3390/microorganisms10081493.
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Pecenka, Ralf, Carsten Lühr, and Hans-Jörg Gusovius. "Design of Competitive Processing Plants for Hemp Fibre Production." ISRN Agronomy 2012 (July 24, 2012): 1–5. http://dx.doi.org/10.5402/2012/647867.
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Despite an annually growing demand for natural fibres accompanied by worldwide increasing fibre prices as well as long tradition and experience in fibre processing, the production facilities for hemp and flax fibres are very limited in Europe. At present, the lack of modern harvesting and economic processing technologies seem to be the greatest obstacles for hemp fibre producers under the changing conditions of international raw material markets. Therefore, detailed investigations of all process stages of hemp fibre processing have been carried out at the Leibniz Institute for Agricultural Engineering (ATB). A novel hemp processing line has been developed, installed, and tested at industrial scale in the last 3 years. Investigations regarding optimum plant layout have shown that a straw throughput of approximately 4 t h−1 is required for economic fibre production for all new processing lines at currently high straw prices of more than 150 € t−1. Throughputs in the range from 4 to 6 t h−1 showed a favourable relation between profit and investment cost. At throughputs higher than 6 t h−1, the profit per ton processed straw can be further increased. But investment and straw logistic cost increase at these high-throughput levels often much faster.
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Bharanidharan, R., M. Nithya, A. Kavitha, and B. Senthil Kumar. "Using Artificial Intelligence for Plant Disease Classification Based on Convolutional Neural Network." Asian Pacific Journal of Health Sciences 9, no. 4 (June 25, 2022): 120–23. http://dx.doi.org/10.21276/apjhs.2022.9.4s.24.
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The plant disease prediction is useful in increasing agricultural production. The plant disease diagnosis through deep learning is a branch of artificial intelligence (AI). It is very important to diagnose plant diseases to improve productivity in agriculture. The plant leaf disease analysis provides us a problem of plant leaf lowest accuracy. The plant for identifying plant disease is to prevent the yield loss of agricultural products. We have proposed a model to validate the data set of the various plants through image processing. The AI-based plant disease detection is very important for sustainable agricultural development. The diseased plant needs to be monitored manually. It requires a lot of work and too much expertise is needed to cope with the plant’s disease in time. The proposed system Convolution Neural Network image processing is to predict the tomato plant diseases. Preprocessing is done in plant leaf image dataset image using Gaussian filter, and then data cleaning, data reduction, and classification are done in disease detection. This describes a method for predicting the disease of plants using the image of their leaves. Further, the algorithm used for the detection of plant diseases and final result of classification in plant disease prediction is described. This demonstrates the technical feasibility of CNN for plant disease classification and provides the accurate result for AI solutions.
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Permatasari, Dwi Kusuma, Syamsuhaidi Syamsuhaidi, Tjokorda S. Binetra, Pardi Pardi, Sumiati Sumiati, and S. Sulastri. "Pelatihan Pengolahan Limbah Pertanian dan Peternakan Pada Masyarakat Tani Ternak di Desa Tete Batu Kecamatan Sikur Kabupaten Lombok Timur." Jurnal Gema Ngabdi 2, no. 3 (November 30, 2020): 248–55. http://dx.doi.org/10.29303/jgn.v2i3.112.
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This activity is based on potensial of Tete Batu Village as agricultural area so that the availability of agricultural waste is abundant and so far it has not been used optimally as animal feed. Community service activities are carried out by providing materials on the technology of processing agricultural waste using various fermenters and local feed ingredients that can be used as alternative feed ingredients, then continuing the practice of processing livestock waste into liquid organic ferlizer and processing agricultural waste into silage. The service activity was attended by the Lombok Regional Government which involved in fostering livestock, head and management of Tete Batu, the livestock farming community, alumni and student, avarage 40 people. The community service activities have succeeded in increasing the knowledge and skills of breeders in processing livestock waste into liquid organic ferlizer which can be used to increase the fertility of agricultural plants and become products that can be sold so as to increase the income of the livestock farming community. Community service activities have resulted in good commitment from the livestock farming community, village administrators and related local government agencies to assist livestock farming communities in processing agricultural and livestock waste into useful products.
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Porsev, Igor, Andrey Sozinov, Georgy Karpov, and Ksenia Salomatina. "Promising varieties of fiber and oil flax plants for agricultural technologies of Trans-Urals." BIO Web of Conferences 27 (2020): 00096. http://dx.doi.org/10.1051/bioconf/20202700096.
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Cultivation of fiber flax and oil flax in Kurgan region is of current interest due to the presence of flax seed and straw processing enterprise – SUE Len Zauralya, Kurgan. To increase the production of highquality flaxseed oil and flax products, the level of flax production should be increased via theoretically substantiated cultivation technologies. Propagating a new variety, plant breeders consider the needs of two categories of consumers – flax producers and flax processors. Some of them need fiber flax varieties of high yield (seed and fiber) and high fiber quality resistant to diseases and lodging, adapted to conditions of Trans-Urals and Siberia. Other consumers need fiber flax varieties that meet numerous requirements of textile, construction, automotive, aviation, medical, and other sectors of the economy, and are suitable for processing by state-of-the-art flax processing equipment. The approach to develop a variety has currently become targeted and customized. Varieties grown in the study area and used as a standard showed high fiber yields: Tomsky 17 – 0.68 t/ha, Tomsky 18 – 0.69 t/ha. The results of the three-year study showed high yields of new varieties: Tost 3 – 0.98 t/ha, Tost 4 – 0.86 t/ha, Tost 5 – 0.82 t/ha. The fiber yield of these varieties was also high: Tost 3 – 0.71 t/ha, Tost 4 – 0.68 t/ha, Tost 5 – 0.66 t/ha.
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Shcherbakov, A., and M. Baramykov. "The concept of agricultural complex based on agrivoltaics and precision agriculture." IOP Conference Series: Earth and Environmental Science 949, no. 1 (January 1, 2022): 012127. http://dx.doi.org/10.1088/1755-1315/949/1/012127.
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Abstract The article presents the concept of an agricultural complex that combines elements of agrivoltaics and precision farming. The purpose of the development of this complex is the ability to implement the principle of multipurpose use of sown areas for basic agricultural crops production (wheat, corn, etc.). The design of this complex and the operation of individual elements are described. In terms of agrivoltaics, it is proposed to use rotating photovoltaic panels; for precision farming - the natural division of the structure of the complex into separate areas. The information is collected by sensors for each site. It includes the required characteristics of air, soil, plants, etc. The collection, storage and processing of measured data are carried out in the control center, where all elements of the complex are also remotely controlled. The complex is supplied with electrical energy due to the energy produced by photovoltaic panels. To smooth the unevenness of production and consumption of energy, including in the absence of agricultural work period, the complex includes the electrical energy storage.
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Singh Rajput, Arpan, Shailja Shukla, and S. S. Thakur. "DETECTION OF PLANT LEAF DISEASES IN AGRICULTURE USING RECENT IMAGE PROCESSING TECHNIQUES – A REVIEW." International Journal of Students' Research in Technology & Management 7, no. 1 (November 25, 2019): 29–33. http://dx.doi.org/10.18510/ijsrtm.2019.716.
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Purpose: Agricultural productivity is something on which the economy highly depends in India as well in all over the world. India is an agriculture-dependent country; wherein about 70% of the population depends on agriculture.
Methodology: This is one of the main reasons that disease detection in agriculture plays an important role, as having the disease in plant leaf is quite natural. If proper observations are not taken in the agriculture field then it causes serious effects on plants due to which respective product quality and productivity are affected. Detection of plant leaf disease through effective and accurate automatic technique is beneficial at the starting stage as it reduces a large work of monitoring in big farms of crops.
Result: This paper presents the review on the state of the art disease classification techniques presently used using image processing that can be used for plant leaf disease detection in agriculture.
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Fountas, Spyros, Nikos Mylonas, Ioannis Malounas, Efthymios Rodias, Christoph Hellmann Santos, and Erik Pekkeriet. "Agricultural Robotics for Field Operations." Sensors 20, no. 9 (May 7, 2020): 2672. http://dx.doi.org/10.3390/s20092672.
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Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.
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Novkovic, Nebojsa, Sandor Somodji, and Milenko Matkovic. "Selection of agricultural land for multifunctional agriculture." Applied Studies in Agribusiness and Commerce 4, no. 1-2 (July 30, 2010): 49–52. http://dx.doi.org/10.19041/apstract/2010/1-2/6.
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The modern concept of rural development implies the use of agricultural resources, primarily agricultural land, for other (non-agricultural) activities besides its agricultural purpose. The integral aim of this concept of rural development is the maximization of economic results, besides the sustainable development of rural areas, environmental protection and the production of strategic (staple) agricultural products. The objective of this paper is to define the general, theoretical, quantitative model for the determination of the size and quality of agricultural land which, considering the above-mentioned demands (criteria), is optimal for the utilization in agricultural production in certain regions. The remaining agricultural land would be available for the non-agricultural purposes. The economic optimal model for the selection of agricultural land in the traditional agriculture is the model of linear programming. The criteria of the land selection for traditional agriculture are the economic effectiveness (measured by net income or by gross national product) and the economic efficiency (measured by the production economy). The maximum economic effectiveness is determined by the standard method of linear programming and the maximum economy by the method of broken linear programming. The solution of compromise can be determined by multi-criteria programming, based on the minimum differences. The limitation groups in the mentioned variations of the model are: limitations of production quotas of agricultural products, minimum quantities of staple agricultural products, limitations of processing plants in a region (minimum and maximum), limitation of crop rotation, limitations of the needs in animal husbandry for bulky for age and limitations of agricultural land according to various types of utilization. By quantitative defining of the structure and size of agricultural land for traditional agriculture, “the surplus” and structure of agricultural land available for non-agricultural purposes is automatically determined.
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Amalia, Khairunisa, Ai Nurlaila, and Yayan Hendrayana. "ETNOBOTANI TUMBUHAN BERGUNA PADA MASYARAKAT DESA LEGOKHERANG KECAMATAN CILEBAK KABUPATEN KUNINGAN." Journal of Forestry And Environment 6, no. 1 (June 30, 2023): 18–28. http://dx.doi.org/10.25134/jfe.v6i1.9069.
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Legokherang Village is an agrarian village so that agriculture, livestock and plantations develop well. Besides that, there are still traditional cultures such as Sidekah Bumi and Pesta Dadung that take advantage of agricultural products and plants from their environment. It is important to document the ethnobotany knowledge of the Legokherang Village community to determine the use of plants, the parts of plants used and how to process them so that the community's knowledge in the use of plants is not lost. Research on ethnobotany of useful plants in Legokherang Village was carried out by survey methods and semi- structured interviews or questionnaires with the determination of respondents based on the snow ball sampling technique.. The results showed that the number of species obtained from ethnobotany were 125 species and 53 plant families. Food-producing plants and medicinal plants were mostly used, namely 39 species and 31 species. The most useful part of the plant is the leaves, for plant processing it is done in several ways, namely burning, boiling, pounding, slicing and using it directly without processing.Keywords: ethnobotany, useful plants
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Zapalowska, Anita, and Ulyana Bashutska. "The use of agricultural waste for the renewable energy production." Наукові праці Лісівничої академії наук України, no. 18 (March 28, 2019): 138–44. http://dx.doi.org/10.15421/411914.
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In addition to hydroelectric power plants, solar and wind power plants, biogas plants are important in the production of electricity and heat from renewable energy sources. It is known that depending on the type of substrate used for processing and the design features of biogas plants, they have their own advantages and disadvantages. Nevertheless, properly localized biomass installation is able to decrease the use of conventional materials reducing greenhouse gas emissions. Bio-waste, plant residues and other by-products can be used to produce electricity, heat and purified methane as fuel for repaired vehicles. Biogas production is a key technology for the sustainable use of agricultural biomass as a renewable energy source. Both, Poland and Ukraine, have a large agricultural area, and well developed animal cattery, which creates opportunities for alternative energy sources from biomass development.
Agricultural biogas plant energy produced from waste such manure, slurry and another agricultural waste, is an excellent source of heat, likewise, electricity. Therefore the importance of using agricultural waste as an energy source in the production of biogas shall be emphasized. A significant drawback of the system is the need to provide low economic and environmental losses. For this purpose, the place of biomass harvesting, transport and its preparation together with storage should be taken into account. To achieve the highest efficiency, small biogas plants should have permanent composition of substrate consisting of various ingredients.
Ukraine and Poland has considerable potential of renewable energy sources development of which can provide significant economic, ecological, and social benefits. The production of biogas has become an attractive source of extra income for many farmers. Biogas production has a useful effect not only on economic, but ecological development, particularly in the rural regions. At the same time, environmental protection aspects have gained additional importance, so that anaerobic treatment processes have become a key technology for environmental and climate protection.
On the basis of the submitted documentation by the municipal administration and the manufacturer, the operation of biogas plants for the processing of organic agricultural waste in Gorajec and Odrzechowa (Poland) has been presented.
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Satyanarayana, L. V., and D. Chandrasekhar Rao. "Applications of CNN in leaf diseases: A critical survey." ITM Web of Conferences 54 (2023): 01014. http://dx.doi.org/10.1051/itmconf/20235401014.
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Crop diseases can significantly impact crop yield and overall productivity, posing challenges for farmers in increasing output and market prices. Early detection of these diseases is crucial for preventing further spread and reducing their impact. To overcome this, researchers have utilized image processing technology, including deep learning techniques such as convolutional neural networks (CNNs), to detect crop diseases. In this critical survey, we provide a comprehensive review of recent studies and developments in the use of CNNs for identifying leaf diseases in agricultural plants. We discuss the benefits and drawbacks of different deep learning techniques and image processing methods for disease diagnosis and management in agriculture. Our research highlights the potential of CNNs and deep learning to significantly advance the field of agricultural research and development. We also analyze the factors affecting the outcomes of each technique, including the accuracy, precision. Our study emphasizes the need for further research and development to optimize the use of CNNs in agricultural applications, particularly for improving disease management and crop productivity.
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Ginda, Grzegorz, and Marta Szyba. "Identification of Key Factors for the Development of Agricultural Biogas Plants in Poland." Energies 16, no. 23 (November 26, 2023): 7779. http://dx.doi.org/10.3390/en16237779.
Full textAbstract:
Agricultural biogas plants are a renewable source of energy and at the same time enable the disposal of biodegradable waste generated in agriculture and the food industry. In Poland, a program aimed at constructing agricultural biogas plants has been in operation since 2010 with the goal of producing 1.7 billion Nm3 of biogas, which has not been achieved. Factors that could influence the development of this energy source were identified based on a register of agricultural biogas producers from the National Agriculture Support Center and data from the Energy Regulatory Office. These factors are technology, substrates, state energy policy, profitability, population density in the commune and the spatial arrangement of the commune resulting from spatial development plans. A pairwise comparison analysis using the DEMATEL method was conducted for these factors. It allowed us to conclude that they are population density and the lack of local spatial development plans in most rural areas. The situation may be improved by the obligation to develop such plans for the entire area of each commune and by locating biogas plants near livestock farms and agri-food processing plants. The selected DEMATEL method is mature and comprehensively verified. It enables research to be carried out in other contexts, taking into account the correlations between factors. It is a universal method, and after collecting expert opinions, research can be expanded. The obtained results of the analysis will allow for further research by collecting the opinions of experts such as biogas plant users, local communities, local government officials and other stakeholders. In addition, further analysis of key factors will be carried out using the DEMATEL method for several scenarios. The PESTEL method will be used to identify key factors.