Development Of Farming Research Articles

Metocean conditions at two Norwegian sites for development of offshore wind farms

This paper examines metocean data from NORA3, a state-of-the-art wind and wave hindcast dataset for Northern Europe. Two offshore Norwegian areas, Utsira Nord (UN) and Sørlige Nordsjø II (SN2), are investigated. Both areas offer significant potential for the offshore wind sector. UN is situated in deep-sea water, suitable for floating offshore wind turbines. In contrast, SN2 lies in intermediate waters and ranks among the North Sea’s most promising regions allocated for offshore wind. Data from NORA3, originally on a 3-km resolution grid, are resampled into unstructured grids spanning from 1982 to 2022. This refined dataset offers a climatology time scale with superior spatial and temporal resolution compared to most other hindcast and reanalysis databases. The study examines mean wind speed and direction across seven levels, ranging from 10 m to 750 m above the surface. Analyses of extreme wind and wave conditions have been conducted. Results reveal that UN experiences higher extreme wave heights than SN2 while the extreme wind speeds may be substantially larger at SN2 than UN. Moreover, this study establishes joint distribution models that encompass several parameters, including mean wind speed, significant wave height, wave spectral peak period, and direction difference between wind and waves. Thus, this metocean data is valuable for designing and analyzing floating wind farms over their lifecycles.

Analysis of Biogas Assistance Program in Dairy Farm Development

Corporate Social Responsibility (CSR) is a form of corporate social responsibility towards the community and environment around the company. The biogas assistance program is one of PJT II's CSR programs in order to accelerate the handling of damage to the Citarum river watershed (DAS) and for the purpose of empowering the community, especially dairy farmers who come from members of the KPBS Pangalengan dairy farmer group. The aim of this research is to determine the mechanism for implementing the biogas assistance program as part of CSR activities and to analyze the benefits of implementing the biogas assistance program in developing the sustainability of dairy farming businesses. This research was conducted in November – December 2023. This research was conducted using a qualitative approach using the case study method. Primary data was obtained through in-depth interviews with informants selected purposively from twenty-one people consisting of the company, participants receiving assistance and implementing parties. The results of the research show that the implementation of the biogas assistance program has been implemented through a process planning, organizing, actuating, controlling (POAC) in the program mechanism, apart from that, the analysis of the program's objectives is to reduce pollution and damage to the Citarum watershed as a result of breeder activities and provide opportunities to increase income independently and sustainably and is an effort to increase breeder awareness to better protect the surrounding environment so that it can speed up the handling of damage to river watersheds that is currently occurring.

Innovation enterprise development strategy in animal husbandry

The research relevance is determined by the need to create a strategy for the development of innovative entrepreneurial structures in livestock farming, the application of which can significantly increase the economic return on farms. The study aims to develop a strategy for the development of progressive livestock farms. The following general scientific methods were used for the study: analysis, synthesis, deduction, induction, and generalisation. Among the innovations considered were various genetic studies to improve the animal genome (the amount of meat and milk, the efficiency of feed assimilation), as well as the selection of genetically healthy embryos for breeding; the use of modern technologies in livestock farming, such as Radio Frequency Identification, Augmented Reality, Convolutional Neural Networks and Global Positioning System; technologies aimed at automating animal feeding processes. Particular attention was paid to various livestock monitoring systems created using advanced algorithms. A strategy for the development of innovative livestock farms was also presented, with drones, CCTV cameras, mixed reality glasses and scanner gloves as the main elements. Other necessary elements included a drone control module and software. Relevant calculations to prove the feasibility of implementing this strategy and its financial potential were also carried out. Provided that 82 units of various equipment are used, with a total cost of $187,970, the strategy provides for a profit of $1,072,030, with a 3-year implementation period and a payback period of less than 6 months. The practical significance of the information obtained is that it can be considered by researchers to further study the specifics of implementing innovative projects in livestock production, as well as to further develop various strategies for agricultural modernisation in Kazakhstan

The Probability of Ship Collision during the Fully Submerged Towing Process of Floating Offshore Wind Turbines

As global warming intensifies, the development of offshore wind farms is swiftly progressing, especially deep-water Floating Offshore Wind Turbines (FOWTs) capable of energy capture in deep-sea regions, which have emerged as a focal point of both academic and industrial interest. Although numerous researchers have conducted comprehensive and multifaceted studies on various components of wind turbines, less attention has been paid to the operational stage responses of FOWTs to wind, waves, and currents and the reliability of their structural components. This study primarily employs a theoretical analysis to establish mathematical models under a series of reasonable assumptions, examining the possibility of collisions between FOWT transport fleets and other vessels in the passage area during the towing process. Using the model, this paper takes the Wanning Floating Offshore Wind Farm (FOWF) project, which is scheduled to be deployed in the South China Sea, as its research object and calculates the probability of collisions between FOWTs and other vessels in three months from the pier near Wanning, Hainan, to a predetermined position 22 km away. The findings of the analysis indicate that the mathematical model developed in this study integrates the quantities and velocities of navigational vessels within the target maritime area as well as the speeds, routes, and schedules of the FOWT transport fleet. By employing statistical techniques and geometric calculations, the model can determine the frequency of collisions between various types of vessels and the FOWT transport fleet during the transportation period. This has substantial relevance for future risk assessments and disaster prevention and mitigation measures in the context of FOWT transportation.

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming. The understanding of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited. In this study, we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats. We explored the impacts of wind farms on land surface temperature (LST) and vegetation net primary productivity (NPP) between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas. The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020. Spatially, wind farms are mainly clustered in three aggregation areas in the center. Further, wind farms increased nighttime LST, with a mean value of 0.23 °C, but had minor impacts on the daytime LST. Moreover, wind farms caused a decline in NPP, especially over forest areas, with an average reduction of 12.37 GC/m². Given the impact of wind farms on LST and NPP, we suggest that the development of wind farms should fully consider their direct and potential impacts. This study provides scientific guidance on the spatial pattern of future wind farms.

Estimating solar irradiance to predict crop yield on northern agrivoltaic farms

Improved model can guide development of mixed-use farms with solar panels.

Farmer’s willingness to accept the sustainable zoning-based organic farming development plan: A lesson from Sleman District, Indonesia

Abstract Zoning-based organic farming has become increasingly attractive in Indonesia for producing healthy food, improving the quality of land and the environment, and increasing the welfare of farmers. The problem is that organic farming areas should be certified by a legal agency called the National Standardization Agency and the cost should be paid by farmers in those areas. Zoning allows the farmers to jointly manage farming areas, including payment of certification costs. However, the success of zoning-based organic farming implementation depends on farmers’ acceptability. This study aims to analyse perceptions and knowledge regarding zoning-based organic farming plans, measure the level of farmers’ willingness to accept (WTA) zoning-based organic farming plans and determine the effect of economic, ecological, and social support factors, as well as other factors towards WTA the zoning-based organic farming system. This study found that the majority of farmers perceive zoning-based organic farming as economically viable and ecologically and socially supported compared to conventional farming since most of the farmers have good knowledge regarding the importance of zoning. Although the farmers have long been experiencing conventional farming, the number of WTA farmers in zoning-based organic farming is very high. The study confirmed that the ecological aspect is the most influential in accepting zoning-based organic farming. Economic factors have a very strong influence on increasing farmers’ WTA zoning-based organic farming. This study also suggests that the implementation of zoning-based organic farming needs to be sustainably supported by the community.

Analysis of NREL-5MW wind turbine wake under varied incoming turbulence conditions

The offshore environment is an ideal site for wind farm development as it offers abundant wind energy resources. Investigating offshore wind turbine wake under different turbulence conditions is essential for enhancing energy generation efficiency and promoting sustainable development. This paper utilizes a synthetic turbulence method called Discretizing and Synthesizing Random Flow Generation (DSRFG) to generate four categories of turbulence environments based on International Electrotechnical Commission design requirements for offshore wind turbines. A standalone NREL offshore 5-MW baseline wind turbine is then simulated using the actuator line method coupled with large eddy simulation. Proper Orthogonal Decomposition is employed to analyze the wake characteristics under different incoming turbulence conditions. For the overall wake behaviors, the flow mode, in which some tip vortices flow back towards the hub, become more significant with higher incoming turbulence intensity. Those vortices disturb the turbine and result in unfavorable effects. Meanwhile, when the detailed characteristics of the wake are studied, each primary mode experiences an increase in the number of small-scale vortices with higher incoming turbulence intensity. It results from the interaction between the wake and outer flow, which accelerates wake recovery and benefits the downstream turbine.

Development and Effects of Organic Farms in Poland, Taking into Account Their Location in Areas Facing Natural or Other Specific Constraints

Organic farms should, by definition, place particular emphasis on the protection of agricultural soils, landscape care and activities aimed at producing high-quality agricultural products. However, when joining this production system, the farms face many challenges in order to make these contributions to society at the expected level. The main aim of the study is to determine the scale of disproportions in production effects achieved by farms between organic and conventional production systems, taking into account the quality of natural management conditions. An equally important goal is to determine the factors in Polish agriculture that determine whether to conduct this production system. The paper aims to indicate the direction of development of organic farming in the EU, including Poland, based on the Eurostat data for 2012–2020. It was noted that the current development of the organic farming sector in EU member states has been at different rates. In Poland, its development strength largely depends on the presence of ANCs. Nearly ¾ of organic utilized agriculture area (UAA) is located in communes with a large share of them. Organic farms achieve lower production effects in comparison to conventional farms, and their disproportions also depend on the quality of natural farming conditions. In Poland, the personal competences of farmers are also an important determinant in joining organic farming.

Collaborative Development of a Farm Systems Learning Platform "4D Virtual Farm".

Over the past 20 years, a lower percentage of veterinary and animal science students entering Australian and New Zealand schools have a background or ongoing contact with livestock production systems. The increasing use of digital technologies over the same time provides a practical option to introduce students to the seasonal operations on livestock farms. This article describes the development of the 4D Virtual Farm, established to showcase 11 representative livestock farms across Australasia allowing students to virtually travel through seasons and place over each farming enterprise. Students can virtually visit different beef cattle, prime lamb, wool-sheep and dairy cattle farms, and a piggery. Any electronic device connected to the web including mobile phones, tablets, computers, and virtual reality headsets can be used to view the enterprises. For educators, the virtual farm can be used for a range of teaching and learning scenarios, such as demonstration of a particular production system via weblink for lectures or embedding within learning management systems. It also allows students to start at a particular point in time and space and guide themselves to other areas for self-learning or for a range of assessment tasks. This site provides an example that could be used in other teaching areas including abattoirs, exotic diseases, surgery, communication, and many other veterinary examples.

Monthly Pork Price Prediction Applying Projection Pursuit Regression: Modeling, Empirical Research, Comparison, and Sustainability Implications

The drastic fluctuations in pork prices directly affect the sustainable development of pig farming, agriculture, and feed processing industries, reducing people’s happiness and sense of gain. Although there have been extensive studies on pork price prediction and early warning in the literature, some problems still need further study. Based on the monthly time series data of pork prices and other 11 influencing prices (variables) such as beef, hog, piglet, etc., in China from January 2000 to November 2023, we have established a project pursuit auto-regression (PPAR) and a hybrid PPAR (H-PPAR) model. The results of the PPAR model study show that the monthly pork prices in the lagged periods one to three have an important impact on the current monthly pork price. The first lagged period has the largest and most positive impact. The second lagged period has the second and a negative impact. We built the H-PPAR model using the 11 independent variables (prices), including the prices of corn, hog, mutton, hen’s egg, and beef in lagged period one, the piglet’s price in lagged period six, and by deleting non-important variables. The results of the H-PPAR model show that the hog price in lagged period one is the most critical factor, and beef price and the other six influencing variables are essential factors. The model’s performance metrics show that the PPAR and H-PPAR models outperform approaches such as support vector regression, error backpropagation neural network, dynamic model average, etc., and possess better suitability, applicability, and reliability. Our results forecast the changing trend of the monthly pork price and provide policy insights for administrators and pig farmers to control and adjust the monthly pork price and further enhance the health and sustainable development of the hog farming industry.

ROLES OF TRADITIONAL IRRIGATION SYSTEM IN SUPPORTING RICE FARMING DEVELOPMENT: Lessons Learned from Bali Province, Indonesia

Agricultural development has still had significant roles on economic development in Indonesia. Rice farming is addressed to increase the productivity and quality of product by using improved agricultural practices including irrigation water management. In Bali province (Indonesia), the existence of subak as traditional irrigation system with socio-agrarian-religious in nature, could be a one of the local cultural institutions for supporting government in the food security program. The main functions of subak are distributing and allocating irrigation water among the subak’s members and between or among the subaks which are getting water from the separated dams on a similar river. These functions are supported by the implementation of internal by-laws own by each subak governing the mechanism of planting schedule, cropping patterns, water borrowing, including ritual ceremonies conducted in the relation to phases of rice planting. Subak system as social capital, therefore, could ensure the availability of irrigation water over the year. Thus, the rice farming development programmed by government could be achived by the effective subak system.

KARAKTERISTIK HABITAT IKAN CUPANG LIAR (WILD BETTA) ENDEMIK SEBAGAI DASAR PENGEMBANGAN POTENSI BUDIDAYA DI KABUPATEN LABUHANBATU RAYA

Wild betta fish has high economic value as one of the ornamental fish commodities in Indonesia. The potential for cultivation development so far has not been maximized so that it still relies on the results of capture from nature. The main key to the development of wild fish farming is actually dependent on food conversion and water quality. Water quality management must adjust to its habitat in nature, however, the study of the physical chemical parameters of wild betta fish waters endemic to Sumatra has not been widely reported. Studies related to habitat characteristics can be used as the basis for aquaculture management in the future. This study aims to analyze the condition of the physical parameters of aquatic chemistry in the natural habitat of wild betta fish in the Regency Labuhanbatu Selatan, Labuhanbatu, and Labuhanbatu Utara. This research is exlorative by observing physical and chemical factors carried out insitu and exitu. The research data is analyzed quantitatively, presented discriptively and discussed based on relevant literature. The results of the main component analysis (Principal Component Analysis) show the main characteristic parameters of wild betta fish habitat in the form of: BOD, COD, DO, conductivity, temperature, and pH. Based on the results of UPGMA analysis, the percentage of similarity of stations 1 and 2 (90.5%) while station 3 (83.6%). It was concluded that the key parameters for wild betta fish farming activities are BOD, COD, DO, conductivity, temperature, and pH and these parameters need to be measured continuously.

Predicting soil cone index and assessing suitability for wind and solar farm development in using machine learning techniques

This study proposes a novel approach that combines machine learning models to predict soil compaction using the soil cone index values. The methodology incorporates support vector regression (SVR) to gather input data on key soil parameters, and the output data from SVR are used as inputs for additional machine learning techniques such as Gradient Boosting, Decision Tree, Artificial Neural Networks, and Adaptive Neuro-Fuzzy Inference System. Evaluation of Artificial Intelligent techniques shows that the XGBoost model outperforms others, exhibiting high accuracy and reliability with low mean square error and high correlation coefficient. The effectiveness of the XGBoost model has implications for soil management, agricultural productivity, and land suitability evaluations, particularly for renewable energy projects. By integrating advanced AI techniques, stakeholders can make informed decisions about land use planning, sustainable farming practices, and the feasibility of renewable energy installations. Overall, this research contributes to soil science by demonstrating the potential of AI techniques, specifically the XGBoost model, in accurately predicting soil compaction and supporting optimal soil management practices.

Sustainable urban farming development in banda aceh city

Urban farming which is known as a strategy to utilize urban areas for agriculture has turned into a trend among urbanites who prioritize a healthy lifestyle. It aims to utilize limited land in urban areas to produce food using modern techniques. This study aims to analyze the level of competence and farmers motivation of urban farming who utilize their land and identify challenges and obstacles in development of urban farming in Banda Aceh City. The types of data used are primary and secondary data. The data collection method was conducted using a questionnaire then the data will be processed and analyzed using descriptive analysis. Based on the results of the study it was known that the level of competence of urban farming farmers in Banda Aceh City reached an average score of 81.6%, which is in the high category, the high level of intrinsic motivation of farmers reached 84.7%. Extrinsic motivation of farmers is in the medium category, with a percentage value of 73%. Despite urban farming in Banda Aceh City encountering various challenges and obstacles, the farmers remain strong and persistent in overcoming all the difficulties that arise during the development process.

Fast region based convolutional neural network ResNet-50 model for on tree Mango fruit yield estimation

<p><span>The foundation of the Indian economy is agriculture, the amount of land available for agricultural activities has decreased due to numerous factors. To fulfill the demands of the expanding population, the maximum yield must be produced on the least amount of land that is accessible. To overcome the challenges of agriculture, many researches have been carried out to adopt technology into agriculture. As India is one of the world's top producers of Mangoes and has a vast market, and has encouraged extensive Mango farm development. Automatic yield estimation of Mangoes in the early stage is important to improve the quality and quantity of production which improves both domestic and export markets. The work proposes a fast region (FR) based convolutional neural network (CNN) residual network (ResNet)-50 model for efficient deep learning-based Mango crop yield estimation system to count the Mango fruit from the images of individual trees. A temporal Mango fruit database is used to estimate the yield of on tree Mango fruits, and a framework is provided to estimate Mango fruit yield in red, green, and blue (RGB) image. This experiment shows that the suggested FRCNN ResNet-50 model attained a better accuracy of 98.20% on the proposed dataset.</span></p>

Strategi Pengembangan Usahatani Sorgum pada Lahan Kering di Kabupaten Sumba Timur

It is hoped that the development of a new production center for sorghum commodities, especially in East Sumba Regency, can increase sorghum production and supply sorghum needs nationally in order to face the world food crisis. To achieve this, it is important to be able to formulate the right strategy for developing sorghum in East Sumba Regency which has dry land conditions. The aim of this research is to analyze the internal and external environment of sorghum farming in East Sumba Regency and to determine priority strategies for developing sorghum farming in East Sumba Regency. This research is a qualitative research with analytical descriptive analysis conducted in July - December 2023 in East Sumba Regency. Respondents in this research were key informants who were determined using a purposive sampling technique. Data collection was carried out by means of field observations, Focus Group Discussions (FGD) and in-depth interviews according to research problems with key informants. The analytical methods used in this research are SWOT analysis and QSPM. The results of the SWOT matrix analysis show that there are 6 alternative strategy formulations that can be applied to the development of sorghum farming in East Sumba. Meanwhile, the results of the QSPM analysis show that the first priority alternative strategy that can be applied by farmers in developing sorghum farming on dry land in East Sumba is optimizing land use to increase production.

Technical-Economic Diagnosis and Development Prospects of Quail Farming in Burkina Faso

Poultry farming is a livestock sector that encompasses various bird species, with the most well-known in Burkina Faso being chickens and guinea fowl. These two species receive support from development programs as they significantly contribute to the livelihoods of poor populations. Quails have been recently introduced, presenting technical and economic advantages that could contribute to the development of livestock farming. The study aimed to characterize the profile of stakeholders, conduct a techno-economic diagnosis, and suggest development prospects. Thirty-three farming units were surveyed in the cities of Bobo Dioulasso, Ouagadougou, and Orodara. The socio-demographic aspects of quail farmers, zootechnical aspects of quails, and challenges faced were analyzed.On the socio-economic level, the activity is predominantly practiced by young, educated men, exclusively with secondary and higher education. Zootechnically, the animal productions consist of eggs and meat. Quail production goals prioritize egg production, quail chicks (97%), fattening (76%), and breeder farming (48%).The feeding practices are inadequate, as all farmers (100%) were providing quails with feed intended for laying hens or broilers. Breeding quails reach sexual maturity at 6 weeks, with an average of 250 eggs laid per female and a high hatching rate. Quails also exhibit a high level of hardiness, easily adapting to their environment, and a high level of adaptation to climatic factors (85% of farmers).Quail housing exclusively consists of battery cages. Economically, live quail prices range from 1,500 to 3,000 Fcfa for breeders and consumption quails, and from 2,500 to 4,000 Fcfa for a tray of thirty eggs. Income levels varied from 184,470 to 28,642,945 Fcfa from quail sales. The revealed constraints primarily involve marketing, followed by the issue of inadequate feeding.

Strategi Pengembangan Usahatani Kakao Di Desa Mayakeli Kecamatan Pamona Puselemba Kabupaten Poso Provinsi Sulawesi Tengah

This research aims to identify internal and external factors in the development of cocoa farming and formulate appropriate strategies for developing cocoa plants in Mayakeli Village, Pamona Puselemba District, Poso Regency, Central Sulawesi Province. This research was carried out in Mayakeli Village, Pamona Puselemba District, Poso Regency, Central Sulawesi from June to August 2023. The method used in sampling was purposive sampling with the consideration that this area is one of the cocoa producing areas in Pamona Puselemba District. The data obtained from the interviews and questionnaires were then analyzed using SWOT analysis. The results of the research show that cocoa development in Mayakeli Village, Pamona Puselemba District, Poso Regency, Central Sulawesi is at the point (0.98 : 1.74) which is located in the Growth I quadrant.

Traditional Chinese medicine bufalin inhibits infectious hematopoietic necrosis virus infection in vitro and in vivo.

Infectious hematopoietic necrosis virus (IHNV) is the pathogen of infectious hematopoietic necrosis (IHN) which outbreak often causes huge economic losses and hampers the healthy development of salmon and trout farming. Currently, there is only one approved DNA vaccine for IHN worldwide, but it faces some biosafety problems. Hence, more effective vaccines and antiviral drugs are needed to prevent IHNV infection. In this study, we report that bufalin, a traditional Chinese medicine, shows potential antiviral activity against IHNV both in vitro and in vivo. The bufalin-mediated block of IHNV infection occurred at the viral attachment and RNA replication stages, but not internalization, and bufalin inhibited IHNV infection by targeting Na+/K+-ATPase. The in vitro and in vivo studies showed that bufalin significantly inhibited IHNV infection and may be a promising candidate drug against the disease in rainbow trout.