Search results for: agricultural operations

Authors: Victoria Bessonova, Robert Dorrell, Nina Dethlefs, Evdokia Tapoglou, Katharine York

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As the global pursuit of renewable energy intensifies, offshore wind farms have emerged as a promising solution to combat climate change. The global offshore wind installed capacity is projected to increase 56-fold by 2055. However, the impacts of climate change, particularly changes in wave climate, are not widely understood. Offshore wind installation and maintenance activities often require specific weather windows, characterized by calm seas and low wave heights, to ensure safe and efficient operations. However, climate change-induced alterations in wave characteristics can reduce the availability of suitable weather windows, leading to delays and disruptions in project timelines. it applied the operational limits of installation and maintenance vessels to past and future climate wave projections. This revealed changes in the annual and monthly accessibility of offshore wind farms at key global development locations. When accessibility is only defined by significant wave height, spatial patterns in the annual accessibility roughly follow changes in significant wave height, with increased availability where significant wave height is decreasing. This resulted in a 1-6% increase in Europe and North America and a similar decrease in South America, Australia and Asia. Monthly changes suggest unchanged or slightly decreased (1-2%) accessibility in summer months and increased (2-6%) in winter. Further assessment includes assessing the sensitivity of accessibility to operational limits defined by wave height combined with wave period and wave height combined with wind speed. Results of this assessment will be included in the presentation. These findings will help stakeholders inform climate change adaptations in installation and maintenance planning practices.

Keywords: climate change, offshore wind, offshore wind installation, operations and maintenance, wave climate, wind farm accessibility

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Authors: Victor Toom

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Albeit it is never possible to anticipate the full range of difficulties after a catastrophe, efforts to identify victims of mass casualty events have become institutionalized and standardized with the aim of effectively and efficiently addressing the many challenges and contingencies. Such ‘disaster victim identification’ (DVI) practices are dependent on the forensic sciences, are subject of national legislation, and are reliant on technical and organizational protocols to mitigate the many complexities in the wake of catastrophe. Apart from such technological, legal and bureaucratic elements constituting a DVI operation, victims’ families and their emotions are also part and parcel of any effort to identify casualties of mass human fatality incidents. Take for example the fact that forensic experts require (antemortem) information from the group of relatives to make identification possible. An identified body or body part is also repatriated to kin. Relatives are thus main stakeholders in DVI operations. Much has been achieved in years past regarding facilitating victims’ families’ issues and their emotions. Yet, how families are dealt with by experts and authorities is still considered a difficult topic. Due to sensitivities and required emphatic interaction with families on the one hand, and the rationalized DVI efforts, on the other hand, there is still scope for improving communication, providing information and meaningful inclusion of relatives in the DVI effort. This paper aims to bridge the standardized world of DVI efforts and families’ experienced realities and makes suggestions to further improve DVI efforts through inclusion of victims’ families. Based on qualitative interviews, the paper narrates involvement and experiences of inter alia DVI practitioners, victims’ families, advocates and clergy in the wake of the 1995 Srebrenica genocide which killed approximately 8,000 men, and the 9/11 in New York City with 2,750 victims. The paper shows that there are several models of including victims’ families into a DVI operation, and it argues for a model of where victims’ families become a partner in DVI operations.

Keywords: disaster victim identification (DVI), victims’ families, social science (qualitative), 9/11 attacks, Srebrenica genocide

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Authors: Asiya Rezzouq, Mehdi El Bouchti, Omar Cherkaoui, Sanaa Majid, Souad Zyade

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In recent years, there has been a steady increase in the exploration of new renewable and non-conventional sources for the production of biodegradable nanomaterials. Nature harbours valuable cellulose-rich materials that have so far been under-exploited and can be used to create cellulose derivatives such as cellulose microfibres (CMFs) and cellulose nanocrystals (CNCs). These unconventional sources have considerable potential as alternatives to conventional sources such as wood and cotton. By using agricultural waste to produce these cellulose derivatives, we are responding to the global call for sustainable solutions to environmental and economic challenges. Responsible management of agricultural waste is increasingly crucial to reducing the environmental consequences of its disposal, including soil and water pollution, while making efficient use of these untapped resources. In this study, the main objective was to extract cellulose nanocrystals (CNC) from melon plant residues using methods that are both efficient and sustainable. To achieve this high-quality extraction, we followed a well-defined protocol involving several key steps: pre-treatment of the residues by grinding, filtration and chemical purification to obtain high-quality (CMF) with a yield of 52% relative to the initial mass of the melon plant residue. Acid hydrolysis was then carried out using phosphoric acid and sulphuric acid to convert (CMF) into cellulose nanocrystals. The extracted cellulose nanocrystals were subjected to in-depth characterization using advanced techniques such as transmission electron microscopy (TEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction. The resulting cellulose nanocrystals have exceptional properties, including a large specific surface area, high thermal stability and high mechanical strength, making them suitable for a variety of applications, including as reinforcements for composite materials. In summary, the study highlights the potential for recovering agricultural melon waste to produce high-quality cellulose nanocrystals with promising applications in industry, nanotechnology, and biotechnology, thereby contributing to environmental and economic sustainability.

Keywords: cellulose, melon plant residues, cellulose nanocrystals, properties, applications, composite materials

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Authors: A. E. Obayelu, S. O. Olubiyo

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Food is different from other commodities because everybody needs food for survival. This has led to a shift in focus to food security in the global policy arena. However, there is paucity of studies on the interactions between food security, migration, urbanization and population rise. This paper therefore look at the linkages between migration and food security in the context of rapid urbanization and population rise of Nigeria. The study obtained data and information from both secondary sources and primary method through the voice of some selected Nigerians through telephone interview. The findings revealed that, the primary factor for the rapid urbanization in Nigeria is migration; most foods are still produced by peasant farmers who are scattered all over the rural areas and not multinational companies who produce on large scale. The country is still characterized with inadequate infrastructural facilities and services to cater for growing population. There are no protective policies enforced by the Nigeria government. In most cases, the migrants are left entirely on mercy of what they can find to due for survival. The most common coping mechanisms by migrants from rural to urban areas are changing food intake in terms of quantity, quality, diversity and frequency and prioritizing children. Policies that address urban food security need to consider the complex relationship between rapid population rise and migration and appropriate transformations that will be able to manage urbanization. With increasing rate of urbanization, the focus of food security should no longer be that of rural only

Keywords: agricultural commercialization, agricultural transformation, food security, urban, urbanization

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Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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During the last 20 years, the globalization of economies, population growth, and the increase in the consumption of fresh agricultural products have generated greater demand for ornamentals, flowers, fresh fruits, and vegetables, mainly from tropical areas. This market situation has demanded greater competitiveness and control over production, with more efficient protected agriculture technologies, which provide greater productivity and allow us to guarantee the quality and quantity that is required in a constant and sustainable way. Guatemala, located in the north of Central America, is one of the largest exporters of agricultural products in the region and exports fresh vegetables, flowers, fruits, ornamental plants, and foliage, most of which were grown in greenhouses. Although there are no official agricultural statistics on greenhouse production, several thesis works, and congress reports have presented consistent estimates. A wide range of protection structures and roofing materials are used, from the most basic and simple ones for rain control to highly technical and automated structures connected with remote sensors for monitoring and control of crops. With this breadth of technological models, it is necessary to analyze georeferenced data related to the cultivated area, to the different existing models, and to the covering materials, integrated with altitude, climate, and soil data. The georeferenced registration of the production units, the data collection with digital tools, the use of satellite images, and geographic information systems (GIS) provide reliable tools to elaborate more complete, agile, and dynamic information maps. This study details a methodology proposed for gathering georeferenced data of high protection structures (greenhouses) in Guatemala, structured in four phases: diagnosis of available information, the definition of the geographic frame, selection of satellite images, and integration with an information system geographic (GIS). It especially takes account of the actual lack of complete data in order to obtain a reliable decision-making system; this gap is solved through the proposed methodology. A summary of the results is presented in each phase, and finally, an evaluation with some improvements and tentative recommendations for further research is added. The main contribution of this study is to propose a methodology that allows to reduce the gap of georeferenced data in protected agriculture in this specific area where data is not generally available and to provide data of better quality, traceability, accuracy, and certainty for the strategic agricultural decision öaking, applicable to other crops, production models and similar/neighboring geographic areas.

Keywords: greenhouses, protected agriculture, GIS, Guatemala, satellite image, digital tools, precision agriculture

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Authors: Uzoamaka Nwugo Akwiwu

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Human Immunodeficiency Virus (HIV) among rural dwellers depletes quality of agricultural labour, and reduces quality of life. Use of Antiretroviral Therapy (ART) has not significantly reduced consequences of infection, as the effort is being compromised by inadequate dietary intake. This study analysed the dietary intake of People Living with HIV/AIDS (PLWHA) in rural communities of Imo State, Nigeria. Data was collected from 114 PLWHA randomly selected from members of two rural support groups with high prevalence of HIV in Imo State using interview schedule. The data was analysed using descriptive statistics, Pearson product moment correlation, and t-test at α0.05. Level of involvement in agriculture was (mean 12.7) and reduced to 7.0 after infection. Extent of involvement in agriculture significantly reduced after infection in Imo (t=8.1). Health status of 42.1% of PLWHA was perceived as poor. Diet diversity score (4.3±1.6) was low among majority (62.3%) of the PLWHA, with diet of 76.3% being inadequate. However, perceived health status had no significant correlation with dietary intake (r=0.09). The study concluded that diet of PLWHA in Imo State was inadequate, thus there is need for agricultural extension agents to collaborate with the health sector to develop nutritional guideline for PLWHA in rural communities.

Keywords: dietary intake, diet diversity, people living With HIV/AIDS, perceived health status

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Authors: Riham Hazzaa , Mohamed Hussien Abd El Megid

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Dyes are toxic and cause severe problems to aquatic environment. The use of agricultural solid wastes is considered as low-cost and eco-friendly adsorbents for removing dyes from waste water. Date palm fibre, an abundant agricultural by-product in Egypt was used to prepare activated carbon by physical activation method. This study investigates the use of date palm fiber (DPF) and activated carbon (DPFAC) for the removal of a basic dye, methylene blue (MB) from simulated waste water. The effects of temperature, pH of solution, initial dye (concentration, adsorbent dosage and contact time were studied. The experimental equilibrium adsorption data were analyzed by Langmuir, Freundlich, Temkin, Dubinin, Radushkevich and Harkins–Jura isotherms. Adsorption kinetics data were modeled using the pseudo-first and pseudo-second order and Elvoich equations. The mechanism of the adsorption process was determined from the intraparticle diffusion model. The results revealed that as the initial dye concentration , amount of adsorbent and temperature increased, the percentage of dye removal increased. The optimum pH required for maximum removal was found to be 6. The adsorption of methylene blue dye was better described by the pseudo-second-order equation. Results indicated that DPFAC and DPF could be an alternative for more costly adsorbents used for dye removal.

Keywords: adsorption, basic dye, palm fiber, activated carbon

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Authors: B. Z. Abubakar, J. P. Voh, B. F. Umar, S. Khalid, A. A. Barau, J. Aigbe

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The study was conducted to identify and assess the various community development programmes designed and executed by Sokoto Agricultural and Community Development Project (SACDP) with the assistance of International Funds for Agricultural Development (IFAD) among women beneficiaries in Kwacciyar-lalle and Mogonho communities of Sokoto state. A simple random sampling technique was employed to select 20 project beneficiaries in each of the selected communities, making a total of 40 beneficiaries. Structured questionnaire, descriptive statistics such as frequencies and percentages and also participatory methodologies such as focus group discussion and pair wise ranking were used to analyze the data. Results showed that majority of the beneficiaries (75%) were married and undertook animal rearing as their major occupation. Results further showed that (85%) of the beneficiaries were involved in decision making, which enhanced their participation. Pair-wise ranking showed dug well as the most preferred activity, followed by construction of Islamic school in Kwacciyar-lalle while well construction followed by provision of improved animal species were most preferred in Mogonho. Recommendations made in the light of achieving people’s participation include provision of more infrastructural facilities and working materials.

Keywords: community development, focus group, pair-wise ranking, infrastructure

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Narsimhulu Sanke, D. N. Reddy

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The paper is to discuss about the influence of the temperature in the advanced biomass gasifier for gasification, when tested four different biomass fuels individually in the gasification laboratory of Centre for Energy Technology (CET). The gasifier is developed in CET to test any kind of biomass fuel for gasification without changing the gasifier. The gasifier can be used for batch operations and observed and found that there were no operational problems.

Keywords: biomass fuels, temperature, advanced downdraft gasifier, tar, renewable energy sources

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Authors: Daniele Calvi, Loris Franchi, Sabrina Corpino

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Thanks to the latest Mars mission, the planetary exploration has made enormous strides over the past ten years increasing the interest of the scientific community and beyond. These missions aim to fulfill many complex operations which are of paramount importance to mission success. Among these, a special mention goes to the Entry, Descent and Landing (EDL) functions which require a dedicated system to overcome all the obstacles of these critical phases. The general objective of the system is to safely bring the spacecraft from orbital conditions to rest on the planet surface, following the designed mission profile. For this reason, this work aims to develop a simulation tool integrating the re-entry trajectory algorithm in order to support the EDL design during the preliminary phase of the mission. This tool was used on a reference unmanned mission, whose objective is finding bio-evidence and bio-hazards on Martian (sub)surface in order to support the future manned mission. Regarding the concept of operations (CONOPS) of the mission, it concerns the use of Space Penetrator Systems (SPS) that will descend on Mars surface following a ballistic fall and will penetrate the ground after the impact with the surface (around 50 and 300 cm of depth). Each SPS shall contain all the instrumentation required to sample and make the required analyses. Respecting the low-cost and low-mass requirements, as result of the tool, an Entry Descent and Impact (EDI) system based on inflatable structure has been designed. Hence, a solution could be the one chosen by Finnish Meteorological Institute in the Mars Met-Net mission, using an inflatable Thermal Protection System (TPS) called Inflatable Braking Unit (IBU) and an additional inflatable decelerator. Consequently, there are three configurations during the EDI: at altitude of 125 km the IBU is inflated at speed 5.5 km/s; at altitude of 16 km the IBU is jettisoned and an Additional Inflatable Braking Unit (AIBU) is inflated; Lastly at about 13 km, the SPS is ejected from AIBU and it impacts on the Martian surface. Since all parameters are evaluated, it is possible to confirm that the chosen EDI system and strategy verify the requirements of the mission.

Keywords: EDL, Mars, mission, SPS, TPS

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Authors: Thierry Sammour Sawaya, Heikki Deschacht

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In commercial aircraft operations, almost half of the accidents happen during approach or landing phases. Automatic guidance and automatic landings have proven to bring significant safety value added for this challenging landing phase. This is why Airbus and ScioTeq have decided to work together to explore the capability of image-based landing solutions as additional landing aids to further expand the possibility to perform automatic approach and landing to runways where the current guiding systems are either not fitted or not optimum. Current systems for automated landing often depend on radio signals provided by airport ground infrastructure on the airport or satellite coverage. In addition, these radio signals may not always be available with the integrity and performance required for safe automatic landing. Being independent from these radio signals would widen the operations possibilities and increase the number of automated landings. Airbus and ScioTeq are joining their expertise in the field of Computer Vision in the European Program called Clean Sky 2 Large Passenger Aircraft, in which they are leading the IMBALS (IMage BAsed Landing Solutions) project. The ultimate goal of this project is to demonstrate, develop, validate and verify a certifiable automatic landing system guiding an airplane during the approach and landing phases based on an onboard camera system capturing images, enabling automatic landing independent from radio signals and without precision instrument for landing. In the frame of this project, ScioTeq is responsible for the development of the Image Processing Platform (IPP), while Airbus is responsible for defining the functional and system requirements as well as the testing and integration of the developed equipment in a Large Passenger Aircraft representative environment. The aim of this paper will be to describe the system as well as the associated methods and tools developed for validation and verification.

Keywords: aircraft landing system, aircraft safety, autoland, avionic system, computer vision, image processing

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Adewale Oladapo, Carolyn A. Afolami

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Agricultural production should be the major financial contributor to the Nigerian economy; however, the petroleum sector had taken the importance attached to this sector. The situation tends to be more worsening unless necessary attention is given to adequate credit supply among food crop farmers. This research analyses the effect of credit use on the technical efficiency of cassava farmers in Ondo State, Nigeria. Primary data were collected from two hundred randomly selected cassava farmers through a multistage sampling procedure in the study area. Data were analysed using descriptive statistics and stochastic frontier analysis (SFA). Findings revealed that 95.0% of the farmers were male while 56.0% had no formal education and were married. The SFA showed that cassava farmer’s efficiency increased with farm size, herbicide and planting material at 5%,10% and 1% respectively but decreased with fertilizer application at 1% level while farmers’ age, education, household size, experience and access to credit increased technical inefficiency at 10%. The study concluded that cassava farmers are technically inefficient in the use of farm resources and recommended that adequate and workable agricultural policy measures that will ensure availability and efficient fertilizer distribution should be put in place to increase efficiency. Furthermore, the government should encourage youth participation in cassava production and ensure improvement in farmer’s access to credit to increase farmer’s technical efficiency.

Keywords: agriculture, access to credit, cassava farmers, technical efficiency

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Authors: S. H. Nasseri, A. Ebrahimnejad

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Fuzzy set theory has been applied to many fields, such as operations research, control theory, and management sciences. In this paper, we consider two classes of fuzzy linear programming (FLP) problems: Fuzzy number linear programming and linear programming with trapezoidal fuzzy variables problems. We state our recently established results and develop fuzzy primal simplex algorithms for solving these problems. Finally, we give illustrative examples.

Keywords: fuzzy linear programming, fuzzy numbers, duality, sensitivity analysis

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: develop, production markets, progress, strategic role, technology

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Authors: Ahmed Azizeldein Abubaker Abdelhafez

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This review explores the application of biochar as a strategy for enhancing soil fertility in arid regions, with a focus on Arab countries. Biochar, derived from the carbonization of biomass under low-oxygen conditions, has shown promise in improving the physical and chemical properties of soil, such as increasing water retention and nutrient availability. Despite the challenging conditions of arid and semi-arid regions, characterized by poor soil fertility and severe land degradation, biochar application has emerged as a viable method to enhance agricultural productivity and mitigate environmental issues. This paper examines various aspects of biochar, including production methods, such as pyrolysis and gasification, and the effects of biochar on soil fertility. It discusses different application techniques and presents case studies from Arab countries like Egypt, the United Arab Emirates, Saudi Arabia, Qatar, Oman, and Kuwait, highlighting the successes and challenges faced in implementing biochar technology. The review also addresses the limitations of biochar use in arid regions and suggests future research directions to optimize its effectiveness. Overall, this study underscores the potential of biochar to contribute significantly to sustainable agriculture and ecological restoration in arid environments, advocating for integrated strategies that combine biochar application with other innovative agricultural practices.

Keywords: biochar, soil fertility, arid region, Arab countries, challenges and limitations

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Authors: Bolanle Deborah Motilewa, E. K. Rowland Worlu, Gbenga Mayowa Agboola, Ayodele Maxwell Olokundun

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In the pursuit of profit maximization as a major objective of business organizations, several firms forfeit their social and economic responsibility whilst focusing on activities that are deemed to solely profit the firm, without taking into cognizance the effect of their operations on the society in which they operate. Business analysts have, however, realized the determinant role of social responsibility in corporate performance, such that firms that are able to imbibe corporate social responsibility in their core business operations may be able to take advantage of the social reputation gained across their several stakeholders. Small and medium enterprises operating in highly competitive markets are also advised to leverage on this reputation gained from being socially responsible, if they seek ways to remain relevant in the same markets dominated by multinational corporations. Adapting a case study approach, this study highlights the advantages (such as employee and customer loyalty) gained by House of Tara, a small business operating in the beauty and make-up industry in Nigeria, resulting from the firm’s commitment to advancing the society in which it operates through several social responsibility activities. It is observed that although competing with major makeup brands such as MAC, Maybelline, Dior, Mary Kay and others, House of Tara has been able to not only thrive, but gain a sizeable market in the Nigerian makeup industry, because several consumers purchase their products not solely because of the quality or price of their product, but because they perceive themselves as buying into the firm’s CSR vision. This study, therefore, recommends that small and medium enterprises that may lack adequate resources (manpower, technology, capital) needed to successfully compete with multinationals, can harness the potentials in the reputation and loyalty gained from adequate investment in corporate social responsibility.

Keywords: corporate social responsibility, small and medium enterprises, House of Tara, sustainability

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Authors: Khalifa Abdunaser, Salem Eljawashi

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Study area is threatened by numerous petroleum activities. The most important risk is associated with dramatic dangers of misuse and oil and gas pollutions, such as significant volumes of produced water, which refers to waste water generated during the production of oil and natural gas and disposed on the surface surrounded oil and gas fields. This work concerns the impact of oil exploration and production activities on the physical and environment fate of the area, focusing on the investigation and observation of crude oil migration as toxic fluid. Its penetration in groundwater resulted from the produced water impacted by oilfield operations disposed to the earth surface in Al Wahat area. Describing the areal distribution of the dominant groundwater quality constituents has been conducted to identify the major hydro-geochemical processes that affect the quality of water and to evaluate the relations between rock types and groundwater flow to the quality and geochemistry of water in Post-Eocene aquifer. The chemical and physical characteristics of produced water, where it is produced, and its potential impacts on the environment and on oil and gas operations have been discussed. Field work survey was conducted to identify and locate a large number of monitoring wells previously drilled throughout the study area. Groundwater samples were systematically collected in order to detect the fate of spills resulting from the various activities at the oil fields in the study area. Spatial distribution maps of the water quality parameters were built using Kriging methods of interpolation in ArcMap software. Thematic maps were generated using GIS and remote sensing techniques, which were applied to include all these data layers as an active database for the area for the purpose of identifying hot spots and prioritizing locations based on their environmental conditions as well as for monitoring plans.

Keywords: Sirt Basin, produced water, Al Wahat area, Ground water

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Authors: Anurag Bhambhani, Jan Peter Van Der Hoek, Zoran Kapelan

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The food system depends on the availability of Phosphorus (P) and Nitrogen (N). Growing population, depleting Phosphorus reserves and energy-intensive industrial nitrogen fixation are threats to their future availability. Recovering P and N from domestic sewage water offers a solution. Recovered P and N can be applied to agricultural land, replacing virgin P and N. Thus, recovery from sewage water offers a solution befitting a circular economy. To ensure minimum waste and maximum resource efficiency a circularity assessment method is crucial to optimize nutrient flows and minimize losses. Material Circularity Indicator (MCI) is a useful method to quantify the circularity of materials. It was developed for materials that remain within the market and recently extended to include biotic materials that may be composted or used for energy recovery after end-of-use. However, MCI has not been used in the context of nutrient recovery. Besides, MCI is time-static, i.e., it cannot account for dynamic systems such as the terrestrial nutrient cycles. Nutrient application to agricultural land is a highly dynamic process wherein flows and stocks change with time. The rate of recycling of nutrients in nature can depend on numerous factors such as prevailing soil conditions, local hydrology, the presence of animals, etc. Therefore, a dynamic model of nutrient flows with indicators is needed for the circularity assessment. A simple substance flow model of P and N will be developed with the help of flow equations and transfer coefficients that incorporate the nutrient recovery step along with the agricultural application, the volatilization and leaching processes, plant uptake and subsequent animal and human uptake. The model is then used for calculating the proportions of linear and restorative flows (coming from reused/recycled sources). The model will simulate the adsorption process based on the quantity of adsorbent and nutrient concentration in the water. Thereafter, the application of the adsorbed nutrients to agricultural land will be simulated based on adsorbate release kinetics, local soil conditions, hydrology, vegetation, etc. Based on the model, the restorative nutrient flow (returning to the sewage plant following human consumption) will be calculated. The developed methodology will be applied to a case study of resource recovery from wastewater. In the aforementioned case study located in Italy, biochar or zeolite is to be used for recovery of P and N from domestic sewage through adsorption and thereafter, used as a slow-release fertilizer in agriculture. Using this model, information regarding the efficiency of nutrient recovery and application can be generated. This can help to optimize the recovery process and application of the nutrients. Consequently, this will help to optimize nutrient recovery and application and reduce the dependence of the food system on the virgin extraction of P and N.

Keywords: circular economy, dynamic substance flow, nutrient cycles, resource recovery from water

Procedia PDF Downloads 189

Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

Procedia PDF Downloads 89

Authors: Shwu-Ling Peng, Chiung-Man Tsai, Chia-Jui Weng

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Chronic micro-inflammation is a hallmark of many aging-related neurodegenerative and metabolic syndrome-driven diseases. In high glucose (HG) environment, reactive oxygen species (ROS) is generated and the ROS induced inflammation, cytokines secretion, DNA damage, and cell cycle arrest to lead to cellular senescence. Water chestnut shell (WCS) is a plant hull which containing polyphenolic compounds and showed antioxidant and anticancer activities. Orchid, which containing a natural polysaccharide compound, possesses many physiological activities including anti-inflammatory and neuroprotective effects. These agricultural plants might be able to reduce oxidative stress and inflammation. This study was used HG-induced human normal dermal fibroblasts (HG-HNDFs) as an in vitro model to disclose the effects of water extract of Phalaenopsis orchid flower (WEPF) and ethanol extract of water chestnut shell (EEWCS) on the anti-aging and their underlying molecular mechanisms. The toxicity of extracts on human normal dermal fibroblasts (HNDFs) was determined by MTT method. The senescence of cells was assayed by β-galactosidase (SA-β-gal) kit. ROS and nitrate production was analyzed by Intracellular ROS contents and ELISA, respectively. Western blotting was used to detect the proteins in cells. The results showed that the exposure of HNDFs to HG (30 mM) for 72 h were caused cellular senescence and arrested cells at G0/G1 phase. Indeed, the treatment of HG-HNDFs with WEPF (200 μg/ml) and EEWCS (10 μg/ml) significantly released cell cycle arrest and promoted cell proliferation. The G1/S phase transition regulatory proteins such as protein retinoblastoma (pRb), p53, and p16ᴵᴺᴷ⁴ᵃ depressed by WEPF and EEWCS were also observed. Additionally, the treatment of WEPF and EEWCS increased the activity of HO-1 through upregulating Nrf2 as well as decreased the ROS and NO of HG-HNDFs. Therefore, the senescence marker protein-30 (SMP30) in cells was diminished. In conclusion, the WEPF and EEWCS might inhibit HG-induced aging of HNDFs by reducing oxidative stress and free radicals.

Keywords: agricultural plant extract, anti-aging, high glucose, Phalaenopsis orchid flower, water chestnut shell

Procedia PDF Downloads 137

Authors: Andrea Bikfalvi, Josep Llach, Ferran Lazaro, Bojan Jovanovski

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Due to the continuous need to foster university-business cooperation in both developed and developing countries, some higher education institutions face the challenge of designing, piloting, operating, and consolidating knowledge and technology transfer units. University-business cooperation has different maturity stages worldwide, with some higher education institutions excelling in these practices, but with lots of others that could be qualified as intermediate, or even some situated at the very beginning of their knowledge transfer adventure. These latter face the imminent necessity to formally create the technology transfer unit and to draw its roadmap. The complexity of this operation is due to various aspects that need to align and coordinate, including a major change in mission, vision, structure, priorities, and operations. Qualitative in approach, this study presents 5 case studies, consisting of higher education institutions located in the Western Balkans – 2 in Albania, 2 in Bosnia and Herzegovina, 1 in Montenegro- fully immersed in the entrepreneurial journey of creating their knowledge and technology transfer unit. The empirical evidence is developed in a pan-European project, illustratively called KnowHub (reconnecting universities and enterprises to unleash regional innovation and entrepreneurial activity), which is being implemented in three countries and has resulted in at least 15 pilot cooperation agreements between academia and business. Based on a peer-mentoring approach including more experimented and more mature technology transfer models of European partners located in Spain, Finland, and Austria, a series of initial lessons learned are already available. The findings show that each unit developed its tailor-made approach to engage with internal and external stakeholders, offer value to the academic staff, students, as well as business partners. The latest technology underpinning KnowHub services and institutional commitment are found to be key success factors. Although specific strategies and plans differ, they are based on a general strategy jointly developed and based on common tools and methods of strategic planning and business modelling. The main output consists of providing good practice for designing, piloting, and initial operations of units aiming to fully valorise knowledge and expertise available in academia. Policymakers can also find valuable hints on key aspects considered vital for initial operations. The value of this contribution is its focus on the intersection of three perspectives (service orientation, organisational innovation, business model) since previous research has only relied on a single topic or dual approaches, most frequently in the business context and less frequently in higher education.

Keywords: business model, capacity building, entrepreneurial education, knowledge transfer

Procedia PDF Downloads 132

Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

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In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

Procedia PDF Downloads 267

Authors: V. D. Povolockiy, V. E. Roshchin, Y. Kapelyushin

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Smelting of copper matte is followed by production of a large amount of slag. This slag mostly contains silicates and can be utilized in a construction industry. In addition to silicates it also contains Fe; if the Fe content is high, the density of the silicate phases increases and such a slag cannot be used as an additive for the concrete. Furthermore, slags obtained during copper matte production contain copper, sulphur, zinc and some other elements. Fe is the element with the highest price in these slags. An extraction of Fe is possible even using the conventional methods, e.g., the addition of slag to the charge materials during production of sinter for the blast furnace smelting. However, in this case, the blast furnace hot metal would accumulate sulphur and copper which is very harmful impurity for the steelmaking. An accumulation of copper by the blast furnace hot metal is unacceptable, as copper cannot be removed during further steelmaking operations having a critical effect on the properties of steel. In present work, the technological scheme for non-waste utilization of the copper smelting slags has been suggested and experimentally confirmed. This scheme includes a solid state reduction of Fe and smelting for the separation of cast iron and slag. During solid state reduction, the zinc vapor was trapped. After the reduction and smelting operations, the cast iron containing copper was used for the production of metal balls with increased mechanical properties allowing their utilization for milling of ore minerals. Such a cast iron could also be applied in the production of special types of steel with copper. The silicate slag freed from Fe might be used as a propping agent in the oil industry, or granulated for application as an additive for concrete in a construction industry. Thereby, the suggested products for a Mini Mill plant with non-waste utilization of the copper smelting slags are cast iron grinding balls for the ore minerals, special types of steel with copper, silicate slag utilized as an additive for the concrete and propping agents for the oil industry.

Keywords: utilization of copper slag, cast iron, grinding balls, propping agents

Procedia PDF Downloads 142

Authors: Saeid Gharechelou, Ryutaro Tateishi

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Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid damage monitoring, 2015-Nepal earthquake

Procedia PDF Downloads 160

Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 365

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

Procedia PDF Downloads 63