Development Of Farming Research Articles

ANTICIPATING LOCAL ACCEPTANCE OF SOLAR FARM DEVELOPMENT IN BATANG KALI, SELANGOR, MALAYSIA: ASSESSING POTENTIAL IMPACTS

To restructure the country's economy towards a high-value economy, the government has placed the transition to a green economy as one of the main targets of its economic restructuring efforts. This transition will create a significant positive impact on every level of society, in addition to guaranteeing the continuity of the country's energy. Nonetheless, every planned development must minimise its impacts on the communities that it will affect. The main objective of this study is to explore the impact of solar farm development on a local community in the dimension of sustainability. This study employed a quantitative research methodology to evaluate the level of impact that the community may experience. The study's primary findings revealed that the community involved in the proposed development project would be significantly affected, both positively and negatively, across social, environmental, and economic dimensions. The community anticipated that the solar renewable energy generation would have a significant positive impact, and the establishment of a solar-based community would improve the quality of life. The implications of this study will facilitate policy makers, decision makers and practitioners in developing solar farms in a sustainable manner while safeguarding the interests of local communities.

Sharing and Co-Creating Value: Innovation in Platform-Based Agricultural Service Models Driven by Service Demand Collaboration—A Case Study of the JN Life

Platform-based agricultural service models have increasingly become a primary approach to agricultural socialized services in China. This study investigates a service-demand-driven platform-based agricultural service model through the case of JN Life initiated by nine ecological farms. Based on the theory of value co-creation, it traces the development of the JN platform ecosystem across three phases: emergence, formation, and expansion. The study examines how farm members and key stakeholders of the JN platform actively collaborate throughout these phases, transitioning from value propositions to institutional arrangements, resource integration, and achieving value co-creation. This process is referred to as an endogenous (vs. exogenous) platform-based agricultural service model. The findings provide valuable insights into advancing the sustainable development of ecological farms and agricultural socialized services, as well as enhancing collaborative innovation in the platform ecosystem.

Assessing the Role of Safe Agricultural Practices in Enhancing Farmers' Income from Vegetable Cultivation

In Bangladesh, farmers grow both general and high-value vegetables, which are essential for providing necessary vitamins and minerals and are cultivated throughout the year across different seasons. However, due to limited knowledge of modern farming techniques, many farmers are hesitant to produce high-value vegetables. This study aims to examine the development of vegetable farming after the implementation of safe cultivation methods for both general and high-value crops, along with the resulting changes in farmers' income. The research utilized and restructured data collected during various baseline and impact assessments to meet the study objectives. By using structured questionnaires, the study gathered key insights into the socio-economic conditions, land use for agriculture, farming techniques, marketing, and financing practices during the project period. The findings reveal that average vegetable production, revenue, and profits have increased by 20 percent, 53 percent, and 48 percent respectively since the project’s inception. The adoption of safe farming methods and improved marketing strategies has led to higher employment, better-quality vegetables free from harmful substances, enhanced soil quality, and greater income for farmers. Raising awareness and providing appropriate training along with logistical support will enable farmers to commercially grow and process both general and high-value vegetables.

Development of a molecular biological method for diagnosing hemorrhagic enteritis of turkeys

Due to the intensive development of industrial poultry farming, timely monitoring of infectious diseases of birds is an integral part of a set of measures that provides for the introduction into practice of diagnostic studies that meet the current level of scientific development.The most relevant for industrial turkey breeding is the monitoring of particularly dangerous diseases (OIE list): Newcastle disease (ND), avian influenza (AI) and economically significant diseases of turkeys - hemorrhagic enteritis of turkeys (HET), infectious encephalomyelitis of birds (IEB), respiratory mycoplasmosis and mycoplasmic synovitis caused by Mycoplasma gallisepticum (MG) and Mycoplasma meleagridis (MM).An analysis of the current state of research on this topic has shown that the development of diagnostic methods for immunosuppressive diseases of birds (hemorrhagic enteritis of turkeys) is an urgent area in the Russian Federation [1]. In order to prevent an outbreak of this disease, which is from an economic and epizootological point of view one of the most dangerous for the turkey breeding industry, it is necessary to carry out diagnostic monitoring of livestock on a planned basis in order to monitor the well-being of the farm for this disease, and in case of early detection of hemorrhagic enteritis, take all necessary measures to prevent further spread and reduce damage which she could have inflicted.That is why the purpose of our study is to develop a molecular biological method for diagnosing HET using the example of PCR in the classical version.In the course of the work carried out, the least variable GEI protein was selected, as well as the correct primers, amplification stages and the composition of the PCR mixture for this protein. When setting up the reaction, a positive result was obtained. All delivered samples reacted in accordance with the expected results.

Remote Sensing-Based Assessment of the Long-Term Expansion of Shrimp Ponds Along the Coastal and Protected Areas of the Gulf of California

Shrimp farming has expanded over coastal areas in Mexico, particularly in the protected regions of Sonora and Sinaloa. Over the past 30 years, the economic activity associated with these farms has grown so much that the amount of shrimp produced in these ponds now exceeds that harvested from traditional shrimp fisheries. Establishing shrimp ponds has led to significant land changes. The construction of these ponds has fragmented local ecosystems, resulting in permanent alterations to areas such as floodplains, mangrove forests, and dunes, many of which are protected zones. This study aimed to investigate the long-term growth of shrimp farms from 1993 to 2022 and their impact on land-use changes in surrounding ecosystems, focusing on protected areas in the Sinaloa and Sonora coastal regions. We analyzed Landsat images using the Google Earth Engine platform. Our findings indicate that shrimp farm development over the past three decades has been extensive, with protected areas experiencing fragmentation and changes. Remote sensing and platforms like Google Earth Engine enable the effective monitoring of these spatiotemporal changes and their impacts, helping to identify the most affected areas.

Renewable energy source facilities as a factor in locational conflicts in rural areas

The main purpose of this study has been to determine the emergence of locational conflicts due to the development of renewable energy source (RES) installations. The study employed a diagnostic survey method. The respondents know what renewable energy sources are and support their development. However, the NIMBY syndrome, as well as the very modest participation of local communities in social consultations, have been detected. The fact that any conclusions reached in the course of consultations are not legally binding was emphasised. Thus, local communities seek other ways to block a contested development, which results in protests and, consequently, social conflicts. Conflicts most often arise between local residents and local authorities, and they are principally ignited by fears of an adverse impact of wind turbines on human health. The survey results can fill in the gap and expand our knowledge of RES, social participation and locational conflicts. They can also help to popularise the transition from conventional sources of energy. Legislative changes are necessary to enable people to have a real influence on the space in which they live. It is unwise to hinder the development of wind farms by excessively restrictive laws.

Pemetaan Potensi Geografis Pengembangan Peternakan Ayam Ras Petelur di Kecamatan Lintau Buo Kabupaten Tanah Datar

This study aims to map the geographical potential for the development of layer chicken farming in Lintau Buo District, Tanah Datar Regency. The method used is the weighted overlay method, which works by overlaying multiple maps representing various parameters of an area's conditions. Each parameter is assigned a weight based on its importance using the Analytic Hierarchy Process (AHP) method. The alternative data used in this study consists of four nagari in Lintau Buo District: Nagari Pangian, Nagari Tigo Jangko, Nagari Buo, and Nagari Taluak. The research results indicate that Lintau Buo District has varying potential for poultry farming development. Nagari Pangian has a high-potential area of 391 hectares and a medium-potential area of 2,317 hectares. Nagari Tigo Jangko dominates the high-potential classification with an area of 3,514 hectares, while the medium-potential area covers 857 hectares, making it an ideal region for large-scale poultry farming. Meanwhile, Nagari Buo falls entirely within the medium-potential category, covering 906 hectares. Nagari Taluak has a high-potential area of 417 hectares and a medium-potential area of 3,125 hectares. These findings suggest that the development of layer chicken farming in Lintau Buo District should integrate geographical factors and regional carrying capacity to ensure sustainability and productivity.

The results of the breeding work on rapeseed in Siberia

Rapeseed is one of the leading agricultural crops in the world with a wide area of cultivation. The article shows the history of the development of rapeseed farming in Siberia and presents the results of breeding work on rapeseed. The varieties of spring rapeseed of East Siberian breeding, promising for Western and Eastern Siberia, are given. A brief description of the Uzhursky rapeseed variety is the first variety created by accelerated breeding with a low content of erucic acid. The article presents the history of zoning of the aneruk and low– glucosinolate varieties of spring rapeseed in the food direction of use Dubravinsky precocious with high seed yield up to 27.2 c/ha and oil content up to 43-45%. The history of the creation of the most famous variety of spring rapeseed Reliable 92 in the Krasnoyarsk Territory and adjacent regions, obtained by the method of diallel crosses, with a yield of green mass up to 315-380 kg/ha, seeds up to 21.9 kg/ha, with a seed content of up to 22.8% protein and up to 42-44% fat. Further breeding work contributed to the creation of a variety of spring rapeseed for complex use (for green feed and seeds) The gift and varieties of the oilseed direction of use are Siberian. Over the past 15 years, work has been carried out with variety sample No. 595, called the Ladny variety, with a yield of green mass up to 50.4 t/ha (16% higher than the standard), a dry matter content of 9.36 t/ha (12% higher than the standard), a feed value of green mass feed units – 0.148 g, digestible protein – 18.18 g, digestible protein in 1 K. unit 124.6 g. Seed yield over five years of research ranged from 1.37 to 2.58 t/ha, on average 2.01 t/ha (17.5% higher than the standard Reliable 92 – 1.71 t/ha). The new Ladny variety is recommended for cultivation in Western and Eastern Siberia.

Analysis of the dynamic response of a model of an oyster farming structure

ABSTRACT Encouraged by the increase in oyster consumption, allied to the growth in the use of coastal marine areas, the development of oyster farming in open sea areas involves the joint efforts of different areas of knowledge. This interdisciplinarity is needed, given that the vibrations and hydrodynamics of structures can affect the distribution of food, the filtering capacity and hence the growth of these organisms. In this context, the article discusses the dynamic response of a hanging oyster farming structure subjected to the influence of different waves. The quantification of the relative velocity between the body and the fluid indicates that the oyster shells probably close part of the time. Lastly, by increasing the length of the cable supporting the cultivation line, an attenuation of approximately 60% can be achieved in the horizontal movement as a result of the distance from the system's natural frequency to that of excitation.

Estimating soil strength using ultra high-resolution seismic data: A case study from a shallow water wind farm

The increasing global reliance on offshore wind farms as a sustainable energy source necessitates precise soil assessment for foundation design due to their high foundation costs and complex integration into marine environments. This study explores the use of ultrahigh-resolution seismic (UHRS) data in conjunction with cone penetration test data for soil strength estimation in offshore wind farm development. We develop a convolutional neural network-based approach that leverages UHRS data for direct soil strength estimation, aiming to address the challenges of limited cone penetration test measurements and potential overfitting in complex geologic settings. Our methodology involves preprocessing UHRS and cone penetration test data, interpreting and integrating geologic unit (GU) information, and applying repeated k-fold cross validation to evaluate model performance. The field data results demonstrate the model’s efficacy in accurately predicting cone penetration test curve trends, albeit with some amplitude discrepancies. We highlight the significance of geologic interpretation in predicting soil strength and identify the dependency on valid data within each GU as a limitation.

Oral administration of recombinant Lactococcus lactis co-expressing fusion VP1 protein of duck hepatitis a virus type 1 and 3 protects ducklings against infection.

Duck viral hepatitis (DVH) is one of the most common diseases of waterfowl. Duck hepatitis A virus type 1 (DHAV-1) and type 3 (DHAV-3) have been on the rise seriously endangering the development of duck farming. In this study, we constructed a recombinant Lactococcus lactis (L. lactis) co-expressing the fusion VP1 protein of DHAV-1 and DHAV-3. Western blot and immunofluorescence analyses confirmed that the fusion VP1 protein was expressed on the cell surface of recombinant L. lactis stain. After immunization with the recombinant L. lactis by oral administration, the ducklings were challenged with highly pathogenic DHAV-1 and DHAV-3 by natural infection. The results showed that the recombinant L. lactis induced the specific IgG antibodies, and significantly increased the level of mucosal secretory immunoglobulin A (sIgA) and cytokines, such as interleukin-4 (IL-4), interleukin-10 (IL-10), and interferon gamma (IFN-γ). The immunized ducklings delayed death for around 4 days, and reduced mortality with the relative percent survival (RPS) being 64.71 %, 61.54 % and 57.89 % in DHAV-1, DHAV-3 and DHAV-1 + 3 infection group respectively. These results showed that the recombinant L. lactis constructed in this study provides a promising candidate for prevention and control of DHAV-1 and DHAV-3 infection.

Seismic Interferometry for Single-Channel Data: A Promising Approach for Improved Offshore Wind Farm Evaluation

Single-channel seismic (SCS) methods play a crucial role in offshore wind farm assessments, offering rapid and continuous imaging of the subsurface. Conventional SCS methods often fall short in resolution and signal completeness, leading to potential misinterpretations of geological structures. In this study, we propose the application of seismic interferometry as a powerful tool to address these challenges by utilizing multiple reflections that are usually considered as noise. First, we demonstrate the feasibility of using seismic interferometry to approximate the primary wavefield. Then, we evaluate a series of seismic interferometry applied in SCS data, including cross-correlation, deconvolution, and cross-coherence, and determine the most appropriate one for our purpose. Finally, by comparing and analyzing the differences in amplitude, continuity, time–frequency properties, etc., between conventional primary wavefield information and reconstructed primary wavefield information by seismic interferometry, it is proved that incorporating multiples as supplementary information through seismic interferometry significantly enhances data reliability and resolution. The introduction of seismic interferometry provides a more detailed and accurate geological assessment crucial for optimal site selection in offshore wind farm development.

The effects of adopting large farms’ agricultural mechanization services on agricultural productivity

ABSTRACT Using data from 2,000 farm households in Henan province in China, this study investigates the relationship between large farms’ provision of agricultural mechanization services (AMS) and agricultural productivity. The statistics show that 75.02%, 74.12%, and 73.79% of farm households adopt large farms’ AMS for ploughing, sowing, and harvesting, respectively. The empirical results indicate that the development of large farms’ AMS significantly reduces agricultural productivity. Further analysis reveals that it not only induces smallholder farms to rent out their land, thereby reducing their agricultural income, but also increases their preference for renting out land. Additionally, we find that the machinery assets owned by large farms are of poorer quality than those owned by professional service providers, as demonstrated by the positive impact of the number of combine harvesters owned by professional service providers on farm productivity. Our analysis suggests that, with the structural transformation of the AMS market, Chinese agriculture may experience a period of low efficiency. The government should work on improve the quality of large farms’ machinery assets and compensate for the loss of efficiency caused by smallholder farmers’ incomplete exit from agriculture.

Numerical Modeling and Analysis of Shadow Flicker Using Solar Path Functions for Enhanced Predictive Accuracy

Shadow flicker caused by wind turbine blades passing through sunlight can significantly affect nearby residential buildings, raising environmental and regulatory concerns in wind farm development. The accurate assessment of shadow flicker exposure is critical for compliance and minimizing community impacts. We present a novel method for accurately determining the exposure of shadow flicker from wind turbines on residential buildings, addressing a key regulatory concern in wind farm planning. Current simulation techniques rely on discrete sampling of solar positions, resulting in potential inaccuracies tied to sampling resolution. Our proposed approach models shadow flicker as a continuous function and applies numerical minimization and numerical root finding to compute the duration of exposure. Our evaluation proves that this method achieves a superior balance between precision and computational efficiency, significantly improving existing techniques.

Potential Development of Cavendish Banana as a New Leading Commodity in South Sulawesi

South Sulawesi Province has great potential in developing superior horticultural commodities, especially the Cavendish banana (Musa acuminata). This study aims to analyze the potential and opportunities for the development of Cavendish banana farming as a new superior commodity in South Sulawesi and assess its economic feasibility. With the large amount of fertile land that has not been optimized, the Cavendish banana can be a significant source of income for local communities while supporting the improvement of regional competitiveness. The analysis results show that Cavendish banana farming provides promising financial returns with productivity reaching 80,000 kg per hectare per year and an average selling price of IDR 4,500 per kilogram. Based on the financial feasibility analysis, the NPV value of IDR 499.48 million, IRR of 211.82%, and payback period of 0.5 years were obtained. In addition, the Cavendish banana also has the potential for product diversification and environmental benefits that support sustainability. This study recommends optimal resource management and collaboration between the government, private sector, and farmers to maximize the potential of this commodity as a regional economic driver.

Sustainable solar energy deployment: a multi-criteria decision-making approach for site suitability and greenhouse gas emission reduction.

Conventional power generation methods have led to adverse environmental impacts. Thus, the need for a strategic transition to alternative energy sources arises. This study presents a comprehensive approach to sustainable solar energy deployment using multi-criteria decision-making (MCDM) techniques. The research aims to identify suitable sites for utility-scale solar photovoltaic (PV) installations, estimate potential energy output, and assess solar PV deployment's environmental and economic impacts. The methodology integrates analytic hierarchy process (AHP), fuzzy logic, and geographic information systems (GIS) to evaluate land suitability across four scenarios. The analysis considers technical, economic, environmental, and social factors, including solar radiation, proximity to infrastructure, land use, topography, and stakeholder opinions. Results reveal that Scenario 1 analytic hierarchy process multi-criteria-decision-making (AHP-MCDM) identified 2824.1 km2 of suitable land, while the combined approach in Scenario 3 yielded 666.9 km2. The study estimates potential annual energy generation ranging from 19.69 to 109.15 GWh/km2/year, depending on the scenario and solar PV technology used. Environmental impact assessments indicate potential annual CO2 emission reductions of up to 51,365.84 tons, with associated cost savings of US $3.28 million. The research provides valuable insights for policymakers and investors, highlighting 16 optimal sites for utility-scale solar farm development across Jamaica, with the most promising in the Westmoreland, Manchester, and St. Mary parishes. These findings contribute to Jamaica's renewable energy goals and offer a replicable, sustainable solar energy planning framework in similar geographical contexts.

Human resources development in farming and fisheries for food security

The article delves into the issues of providing food security in the Maldives, a nation that regularly faces adverse weather conditions and natural disasters. These challenges include tsunamis, heavy rainfall, and strong winds that damage infrastructure, fishing vessels, agricultural land, contaminate freshwater resources and wash away entire islands during the monsoon season. The research purpose was to support workforce development to compensate for shortage of natural and technical resources in farming and fisheries. The explored data was collected from Maldives Bureau of Statistics. The applied statistical and clustering methods proved that training in farming should share knowledge of cutting-edge technologies like Hydroponics and Pest control, benefit female farmers, involve the youth in local agriculture and be evenly distributed among the Atolls. The study findings based on ranking and trend analysis argue that unstable employment is the paramount problem in fisheries. It is recommended to optimize a number of fishermen per vessel by Atolls and promote acquiring skills of advanced eco-friendly fishing. Overall research results created a reliable foundation for systematic development of qualified human resources in farming and fisheries that are crucial for strengthening food security in a risky environment.

Towards machine learning applications for structural load and power assessment of wind turbine: An engineering perspective

Over the past decades, the increasing energy demand has accelerated the construction of wind farms, raising higher expectations for precise load and power assessments in wind turbine performance. Traditional methods, which rely on analytical wake models and performance curves, often fail to adapt to complex inflow scenarios, leading to significant inaccuracies in predicting turbine loads and power output. This research addresses these challenges by introducing a novel two-phase framework for various phases of wind farm planning and development, using the NREL 5MW baseline wind turbine as a case study. The first part involves deriving recommended values for simplified thrust modulation factors at the preliminary design phase, enabling swift evaluation of maximum and fatigue thrust loads crucial for wind farm optimization. The second part focuses on designing and training a machine learning model at the detailed design phase. A gradient-boosting-based framework based on LightGBM provides comprehensive methods for assessing wind turbine load and power, enhancing the precision and efficiency of these assessments. The proposed model achieves significant improvements in predictive accuracy, achieving mean R-Squared of 0.995, 0.988, and 0.995 for power, peak load, and damage equivalent load evaluation, respectively. The framework streamlines the assessment process, enhancing both the accuracy and speed of power and load evaluations for wind farm design. This is expected to reduce computational costs and improve the effectiveness of downstream tasks, such as layout optimization and wake steering.

Development of Container-Type Vertical Farm for Year-Round Production of Long Stem Plants and Study on Flow Distribution

Development of Container-Type Vertical Farm for Year-Round Production of Long Stem Plants and Study on Flow Distribution

Barriers to the Consumption of Organic Food in Visegrad Group Countries

The consumption of organic food fits into the sustainable development goals and constitutes a justification for the further development of organic farming. The research aimed to identify the most important limitations to the growth of organic food consumption in the Visegrad Group countries and to indicate the differences and similarities in their perception. Therefore, at the turn of 2024, a survey was conducted among consumers in each of the countries of the Visegrad Group on a population of 600 people using an identical survey questionnaire. The research shows that in all four countries, the most important barrier to the growth of organic food is its high price, which is of great importance to Slovak consumers. The low availability and narrow offer, as well as insufficient information on organic food, were also important for consumers. On average, over 80% of the surveyed consumers rate the price level of organic food as high – the highest percentage was observed in Slovakia and the lowest in Czechia. Also, approximately 80% of the surveyed can accept a price up to 20% higher than conventional food. In the opinion of the respondents, the most important factors that would increase organic food consumption include lowering its prices, increasing income, and expanding the offer and availability.