Agricultural Problems Research Articles

Rapid detection of salmon louse larvae in seawater based on machine learning

The proliferation of salmon lice is one of the most challenging problems in salmon farming, seriously affecting the welfare of both farmed and wild salmonids. The detection of salmon lice in seawater, especially in the (pre-) infectious stage, supports the accurate management of salmon lice proliferation. Methods for detecting salmon lice in seawater to date involve traditional light and fluorescence microscopy and Polymerase Chain Reaction (PCR) methods. However, these methods require sample pre-processing and are laborious and time-consuming, rendering them difficult to apply for the task of continuous, rapid salmon lice detection in large water volumes. This study aims to develop a rapid and easy-to-use method for the detection of salmon lice in seawater. A novel approach was introduced for the detection of salmon lice at different larval stages in seawater by leveraging machine learning. A setup for the rapid acquisition of images of salmon lice in seawater was developed, and a dataset comprising 8316 images encompassing salmon lice “Nauplius Live,” “Nauplius Shell” and “Copepodite” was created. Then 16 object detection models including one- and two-stage Convolutional Neural Network (CNN-) based models and Transformer-based models were trained, tested, and compared on this comprehensive dataset. RT-DETR showed the best performance among all models tested with a precision of 0.972 and a recall of 0.978. The YOLO series models, except for YOLOv3, showcased remarkable inference speeds (ranging from 152 to 416 frames per second) while maintaining high precision (ranging from 0.968 to 0.977) and recall (ranging from 0.964 to 0.970). To our knowledge, this is the first time machine learning has been applied to the task of rapidly detecting salmon louse larvae at different stages in seawater samples. The results demonstrate that the machine learning approaches can achieve rapid easy-to-use and cost-effective detection of salmon lice in seawater. In the future, this study has the potential for application in measuring salmon louse larvae numbers in aquatic environments, supporting the enhancement of the welfare of both farmed and wild salmon.

Pear (Pyrus communis)-based agroecosystem improves soil nutrient dynamics, microbial biomass, enzymatic activity, farm productivity and profitability

North-western Indian farmers are increasingly showing interest in adopting horticulture-based systems to enhance their farm productivity with anticipated profits. So, there is a need for systematic evaluation of different pear-based agroecosystems with respect to its productivity, profitability, soil health, and biodiversity to tackle the problems of modern agriculture (food security, declining soil health, and sustainability). Therefore, an intercropping experiment comprising 11 treatments viz. [T1: Pear (Pyrus communis) + Pea (Pisum sativum), T2: Pear + Radish (Raphanus sativa), T3: Pear + Coriander (Coriandrum sativum), T4: Pear + Kasuri fenugreek (Trigonella corniculata), T5: Pear + fenugreek (Trigonella foenum-graecum), T6: Pear + Spinach (Spinacia oleracea), T7: Pear + Green onion (Allium fistolosum), T8: Pear + Cauliflower (Brassica oleraceae var. botrytis), T9: Pear + Toria (Brassica rapa), T10: Pear + Knol khol (Brassica oleraceae var. gongylodes) and T11: Pear monoculture] were laid out in randomized block design with three replications at farmer's field, Tarn Taran district, Punjab, India during 2021–22 and 2022–23. The results showed that the lesser values of bulk density (1.30 g/cm3) and higher water holding capacity (42.52%) were observed in the Pear + kasuri fenugreek intercropping system. All the legumes-based intercropping systems viz. Pear + kasuri fenugreek, Pear + fenugreek, and Pear + pea were significantly efficient in bringing enhancements to the chemical properties of the orchard's soil. Under various pear-based intercropping systems, different microbial populations (bacteria, fungi, actinomycetes, and diazotrophs) were significantly higher in legume-based intercropping systems of Pear + kasuri fenugreek, Pear + fenugreek, and Pear + pea and resulting in more enzymatic activity in the soil in terms of dehydrogenase (63.02, 61.88, and 60.48 µg TPF/g of soil/hour, respectively), alkaline phosphatase (10.05, 9.92, and 9.75 µg PNP/g of soil/hour, respectively) and urease (17.84, 17.18, 17.00 µg /g of soil/hour, respectively). The intercropping system of Pear + kasuri fenugreek significantly increased microbial biomass carbon (42.20%) and microbial biomass nitrogen (65.02%) over Pear monoculture. The correlation analysis of various soil's physiochemical and biological parameters indicated significant associations among themselves at p = 0.01, 0.05. The intercropping system of Pear + kasuri fenugreek also produced significantly higher system productivity in early (122.20 kg/ha/day in 2021–22 and 123.86 kg/ha/day in 2022–23) and main season (119.08 kg/ha/day in 2021–22 and 121.60 kg/ha/day in 2022–23) due to significantly higher pear yield (340.02 q/ha in 2021–22 and 341.89 q/ha in 2022–23) and higher pear equivalent yield (105.99 in early season, 94.64 q/ha in main season of 2021–22 & 110.20 in early season, 101.94 q/ha in main season of 2022–23) observed by kasuri fenugreek, resulting in higher net returns, BC ratio and economic efficiency in both seasons during both years over other intercropping systems.

ACCUMULATION AND VERTICAL DISPLACEMENT OF NUTRIENTS AT IRRIGATED FRUIT GROWING AREAS

The application of soluble fertilizers without planning burdens agricultural production and leads to soil salinization, a very evident problem in irrigated agriculture in the semiarid region. The soil management practices used in grape and mango cultivation are the main responsible for the loss of nutrients by leaching and soil salinization in the São Francisco submedium’ Valley. The objective of the work was to quantify the accumulation and vertical displacement of nutrients in 0-20, 20-40, 40-60, 60-80 and 80-100 cm layers of cultivated and native areas. The study was carried out in the municipality of Petrolina/PE, in 43 areas with different cultivated grapevine, mango and Caatinga crops in the São Francisco submedium’ Valley. PH, EC, OM, P, K+, Ca++ and M++ were evaluated at different depths. The movement of nutrients, especially P, was favored by the continuous application of high fertilizer doses as well as by the sandy texture of the soils studied. The high levels of nutrients observed in the areas cultivated with grapevine suggest an adjustment in the recommended fertilizer doses, aiming at the reduction of environmental impacts and fertilizer losses.

Soil compaction in progressive agricultural tractor treads

Soil compaction is one of the main problems in world agriculture. It is known that, even in soil conservation management, such as in no-till, the transit of agricultural machinery damages the soil structure, therefore, it is essential to better understand the compaction processes and ways to alleviate the problem. In soils that have traditional tillage management, just one machine pass can damage the physical structure. This research aimed to evaluate the levels of compaction as a function of different passages of an agricultural tractor, considering the hypothesis that, during agricultural operations, a machine transits several times through the same place in the crop. The experiment was carried out on plowed and harrowed agricultural soil in the state of São Paulo. Resistance to soil penetration at different depths was evaluated, and the averages were correlated as a function of the number of steps taken by the tractor. Results showed that approximately 60% of the total soil compaction occurs in the first passes of the agricultural tractor, and above five passes the increase in compaction is minimal. At depths of 20 to 30 cm, the largest RSPs were found. It is concluded that a good planning of machinery traffic is essential, because in the case of a motor-mechanized set moving out of its predestined route, the soil structure is permanently affected.

Profitability and Problems of Commercial Pig Farming in Punjab

Profitability and Problems of Commercial Pig Farming in Punjab

IoT-based prediction and classification framework for smart farming using adaptive multi-scale deep networks

Agriculture is one of the prime economical sources of India and most of the people directly or indirectly depend on farming. The researchers are focusing on plant ailment detection and managing the imbalanced nutrition in plants. Automation is introduced in agricultural fields and most of these automation strategies use the Internet of Things (IoT) for enhance productivity and automate processes. With the help of several deep and machine learning approaches the endless decision-making performance is performed. Here, the endless decision performance shows appropriate outcomes which helps to solve the unstructured problems in smart farming. It is monitored that the traditional analysis doesn’t have enough decision-making ability in the selection of fertilizer quantity that is to be used in farming. This inability leads to crop ailments and that affects the lifestyle of humans too. So, the prior detection of ailments in crops is essential. Enforcing Smart Agriculture is a hot topic in research nowadays to overcome crop damage in the future. Therefore, a new IoT-based smart farming model using deep learning is proposed to increase crop yield. By detecting disease, pests, smart irrigation, and yield, the smart farming model can reduce the amount of water and chemicals used in agriculture. This smart farming model consists of four phases a) disease prediction, b) pest detection c) smart irrigation, and d) yield prediction. In the first phase, the crop images are gathered from online datasets. The diseases in crops are predicted using Multi-scale Adaptive CNN with LSTM layer (MA-CNN-LSTM), where the parameters in MA-CNN-LSTM are optimized using Advanced Mountaineering Team-Based Optimization Algorithm (AMTBO). In the second phase, the input images are given to MA-CNN-LSTM to detect crop pests. Here, the AMTBO is utilized for tuning parameters. In the third phase, the soil quality and environment data are fed into the Multi-scale Adaptive 1DCNN with LSTM layer (MA-1D CNN-LSTM) to predict the smart irrigation, where the parameter optimization is done using the AMTBO. Smart irrigation enhances the growth of crops and minimizes water usage. In the final phase, the input data such as crop quality, soil quality, and environment data are given to the MA-1D CNN-LSTM to check the overall yield prediction in an agricultural region. Here, the parameters in MA-1D CNN-LSTM are optimized via the AMTBO. The simulation results are compared with other algorithms and classification techniques to check the performance of the developed model.

Determination of the 1L-5-6L MGF110 Genes Influence on the Biological Properties of the African Swine Fever Virus (Asfarviridae; Asfivirus) “Volgograd/14c” in vivo

Abstract African swine fever continues to pose a global agricultural problem due to the absence of vaccine prevention and the high cost of anti-epizootic measures. This study examines the functional role of the African swine fever virus (ASFV) 1L-5-6L multigene family 110 genes in vivo. Four clinically healthy Large White pigs were used in this study. Two groups of animals were inoculated with either the parental strain or the deletion variant, respectively. For subsequent challenge infection, the homologous virulent strain “Stavropol 01/08” was used. Blood samples were collected at specific time intervals. The ASFV infectious activity was determined by titration in porcine blood-derived macrophages. Virus-specific antibodies to the ASFV p30 protein were detected using an enzyme-linked immunosorbent assay (ELISA). The results of real-time polymerase chain reaction (PCR) showed a significant difference in Ct values between samples from the two groups of animals. The determination of ASFV infectious activity in blood samples demonstrated the presence of the virus in animals immunized with the parental strain. The virus was not detected in samples from animals immunized with the deletion strain. The ELISA method demonstrated the presence of p30 protein antibodies in serum samples from 10 to 14 days after immunization with the parental strain, while no antibodies were detected in serum samples from animals immunized with the deletion strain. The properties of the ASFV recombinant strain “Volgograd/D(1L-5-6L) MGF110” were studied in an in vivo experiment. It was found that the deletion strain does not reproduce in animals, unlike the parental strain.

FINANCING MODEL OF SHARIA ECONOMY-BASED COFFEE AGROINDUSTRY USING DYNAMIC SYSTEM SIMULATION IN BANDUNG DISTRICT

West Java Province is one of the producers of export quality Arabica coffee, namely Java Preanger Coffee. The problem that often arises in the agricultural sector is that most farmers do not have the funds to make capital. Another problem in agriculture is capital. This can cause crop failure due to a lack of capital so the process of agriculture is delayed and hampered. The aim of the Islamic financing modelling research is to determine the relationship between variables in the Islamic economic-based financing system as well as a comparison between the application of the concept of profit-sharing margins for mudharabah and musyarakah between farmers and Muhammadiyah Branch Managers (PCM) using the system dynamics method using the Powersim Software. System dynamics are defined to address large-scale and complex systems and understand the relationships among behavior in a given system over time and the underlying structures and decision rules. The sharia economy-based coffee agroforestry financing model results in the application of profit sharing that reflects more justice. The principle of profit sharing carried out by PCM is beneficial for both parties who have achieved the principle of justice, by avoiding things that are unlawful. This can be seen from the results of the profits and losses are not on one side. The simulation results can be used as a consideration for decision making for financing coffee agroforestry in Bandung Regency.

Technical Guidance on The Integration of Cattle and Food Crops in Sindang Kasih Village, South Konawe District

This technical guidance aims to provide understanding to cattle breeders regarding the benefits of integrating cattle and food crops in one area so that participants are motivated and encouraged to carry out integration between cattle and food crops. This technical guidance was implemented at Sindang Kasih Village, West Ranomeeto District. Implementation of technical guidance uses lecture and discussion methods. The tools and materials used are vehicles, cell phones, and laptops. In general, Cattle Farmers in Sindang Kasih Village already understand the integration of cattle and food crops and its benefits and are committed to implementing this integration as indicated by the ability of all participants to answer questions correctly at the end of the activity session (100%). The challenges and problems of beef cattle farming include maintenance and waste processing systems. Integrating livestock with food crops in Sindang Kasih Village has been implemented well. The livestock in Sindang Kasih needs to be further improved to become one of the breeding and fattening centers in Southeast Sulawesi.

Heavy metals immobilization and bioavailability in multi-metal contaminated soil under ryegrass cultivation as affected by ZnO and MnO2 nanoparticle-modified biochar

Pollution by heavy metals (HMs) has become a global problem for agriculture and the environment. In this study, the effects of pristine biochar and biochar modified with manganese dioxide (BC@MnO2) and zinc oxide (BC@ZnO) nanoparticles on the immobilization and bioavailability of Pb, Cd, Zn, and Ni in soil under ryegrass (Lolium perenne L.) cultivation were investigated. The results of SEM–EDX, FTIR, and XRD showed that ZnO and MnO2 nanoparticles were successfully loaded onto biochar. The results showed that BC, BC@MnO2 and BC@ZnO treatments significantly increased shoots and roots dry weight of ryegrass compared to the control. The maximum dry weight of root and shoot (1.365 g pot−1 and 4.163 g pot−1, respectively) was reached at 1% BC@MnO2. The HMs uptake by ryegrass roots and shoots decreased significantly after addition of amendments. The lowest Pb, Cd, Zn and Ni uptake in the plant shoot (13.176, 24.92, 32.407, and 53.88 µg pot−1, respectively) was obtained in the 1% BC@MnO2 treatment. Modified biochar was more successful in reducing HMs uptake by ryegrass and improving plant growth than pristine biochar and can therefore be used as an efficient and cost effective amendment for the remediation of HMs contaminated soils. The lowest HMs translocation (TF) and bioconcentration factors were related to the 1% BC@MnO2 treatment. Therefore, BC@MnO2 was the most successful treatment for HMs immobilization in soil. Also, a comparison of the TF values of plant showed that ryegrass had a good ability to accumulate all studied HMs in its roots, and it is a suitable plant for HMs phytostabilization.

Effect of Cold Plasma Seed Treatment on Physiological and Biochemical Changes in Aged Mustard Seed Variety-RH0749

The low rate of seed germination is a major problem in modern agriculture. Cold-activated air plasma has been tested as a pre-treatment method to improve the rate and uniformity of the germination. In view of the widespread cultivation of mustard in India and other parts of the world, This study was conducted to determine alternative non-destructive seed treatment method based on cold plasma chemistry would offer a more viable alternative over traditional seed coating technologies Seed physiological characteristics as was modified in aged low vigour mustard seeds by coating the surface of the seeds with cold plasma process using a rotating plasma reactor during 2023-24 at CCS HAU, College of Agriculture Bawal. The source of atmospheric oxygen gas, nitrogen and heliun gas entering the plasma chamber during the reaction process determined the type of coating. Among the different treatments imposed, seed treatment with 300V at 10 Min significantly enhanced seed quality attributes viz., germination ( 92 %), root length ( 4.37 cm), shoot length ( 6.98 cm), mean seedling length (11.0 cm ), Seedling dry weight (2.67 mg) and SVI-I (1115), SVI-II (254), TDH (0.78 A480 nm) with lower electrical conductivity (14.20 dsm-1). The inhibitory effect noticed with a higher dose of plasma of 400v at 10 min suggested the need for judicious usage of these plasma frequencies in such applications. The first-ever report on the effect of new plasma state on seed germination and establishment of mustard revealed the positive influence that could be used as a seed treatment to enhance seed yield and quality.

Identification of dragon trees and fruits in ham Thuan Bac growing areas, Phan Thiet city, Binh Thuan province, Vietnam

With the development of Computer Vision, we can effectively and accurately identify trees, fruit or object images. But to build a high-performance image dataset for tree identification problems in Agriculture is a challenge. Realizing that Vietnam is a country with strong agriculture with many tropical fruits grown widely such as Dragon fruit, Mangosteen, Mango, Orange, Lychee, Longan … We chose the Dragon Fruit tree for the data set. of my proposed images, all images will be collected using the close-up method, including tasks such as taking photos of Dragon Fruit trees from many angles and in different conditions (weather, temperature, light, …). In this article, we want to improve the data quality of the collected images so we have applied image processing techniques such as noise filtering (using Gaussian filter), image quality enhancement (image rotation), flip the image, zoom out, zoom in, etc.). From the collected Dragon Fruit tree data set, we will propose to use the Faster R–CNN model for this data set to build a tree and Dragon Fruit identification system.

Decision framework for public-private partnership in agricultural commodities

Public-private partnerships are critical to advancing sustainability in the agricultural sector and increasing global food security. Partnerships are a means of increasing productivity and encouraging growth in the agricultural sector. The Partnership encourages private sector participation to reduce risks that occur in the agricultural sector. The aim of this research is to understand how supply chains are configured, to identify drivers of supply chain partnerships and to synthesize partnership strategies. Currently, agricultural areas in East Java are trying to build sustainable partnerships to improve farmers’ abilities in managing the agricultural sector. By using data from surveys and observations of 50 private companies and 50 farmers spread across the research object locations, it was found that there was quite a significant interaction between intensive coordination, partnership quality, quantity and quality of partners. The mechanisms used in partnerships can encourage sustainable agricultural management. It is hoped that the implementation of these findings can encourage partnerships between the private sector and the public sector to achieve significant development. It is hoped that this partnership can play an important role in addressing agricultural problems. Partnerships are formed to create shared values in the form of an institutional framework to address the root of problems.

Behavioral and metabolic markers of cow morbidity in early lactation

The high productivity of cows on modern dairy farms means that their bodies are used almost at full capacity. Even minor violations in the conditions of keeping or feeding can lead to a significant increase in the morbidity of animals. In such conditions, preventive veterinary medicine is the main task of a veterinarian. In practice, preventing the development of the disease means the veterinarian's ability to predict the occurrence of a problem, identify its cause in time and offer preventive measures. The purpose of this work was to get acquainted with behavioral and metabolic markers for predicting morbidity in cows during early lactation. According to the methodology for systematic reviews of the literature, a search and analysis of scientific articles according to the topic of the study, which were published during 2000–2023, was carried out. To search for scientific articles, the scientometric databases of the Web of Science Core Collection and PubMed were used. Analysis of the study of behavioral and metabolic markers of morbidity in cows during early lactation showed the significant relevance of the problem for dairy farming. A significant number of scientific articles are devoted to the study of this issue. A significant amount of the results of scientific research has practical significance and is used in production. The other part serves as a basis for the formation of new substantiated scientific hypotheses. This gives reason to believe that solving the problem of timely diagnosis and prevention of cow diseases during the transition period is a matter of the near future. Certain physiological and behavioral parameters (duration of chewing and feeding, time of rest and motor activity, social interaction) during the dry period can be important indicators of metabolic changes or diseases in cows at the beginning of lactation. The accuracy of forecasting with the help of such parameters increases with the increase in the duration of the study and the number of indicators used. Physiological and behavioral parameters recorded by automated milking systems can be successfully used to diagnose and predict health problems of dairy cows. Further research in this field is an important challenge for veterinary science. An increase in the time spent in a lying position, the number of periods of rest and agonistic contractions per day, a decrease in the duration of chewing, feeding and motor activity, especially in the last trimester of pregnancy, are associated with an increased likelihood of transition period diseases (ketosis, abomasum displacement, reproductive disorders, etc.). The study of behavioral and metabolic markers of morbidity in cows during early lactation proved the significant relevance of the problem for dairy farming. A significant number of scientific articles are devoted to the study of this issue. We believe that solving the problem of timely diagnosis and prevention of cow diseases during the transition period is an important task of veterinary medical science today.

Optimizing Crop Water Productivity in Greenhouse Pepper

Although advanced production systems have been developed in the last 20 years, water scarcity is still a growing problem in agriculture. This study aims to evaluate the effect of different strategies that combine the application of seaweed and microbial biostimulants with regulated deficit irrigation (RDI) strategies on the irrigation water productivity (WPI), fruit quality parameters and soil enzymatic activity in pepper plants (Capsicum annum sp.) under two commercial greenhouse conditions. In each trial, two treatments were applied: (i) irrigation according to Farmer criteria without biostimulant applications and (ii) a combined treatment of RDI and the same biostimulation program, composed of Bacillus paralicheniformis and Ascophillum nodosum extracts. RDI was applied in different phenological stages in each greenhouse after the establishment until the 1st harvest in trial 1 or during the ripening and harvest period in trial 2. On average, the irrigation was reduced by 600 m3 ha−1 compared to the Farmer irrigation schedule. In both trials, biostimulation promoted an increase in fruit numbers, punctually in trial 1, leading to yield precocity, or generally in trial 2, obtaining a higher yield. Globally, WPI was increased when RDI was combined with biostimulation. This combined treatment also enhanced the root water absorption and improved the soil enzymatic activity in both greenhouses, suggesting that nutrients in the soil would become more available to plants. Thus, the combined action of biostimulation under different RDI strategies has been proved to be a useful strategy to improve agricultural sustainability.

A note on “A new method for intuitionistic fuzzy multi-objective linear fractional optimization problem and its application in agricultural land allocation problem”

Moges et al. (Inf. Sci. 625 (2023) 457–475) proposed a method to find a Pareto-optimal solution (POS) of intuitionistic fuzzy multi-objective linear fractional optimization problem (MOLFOP). In this method, firstly, an intuitionistic fuzzy MOLFOP is transformed into a crisp MOLFOP with the help of a ranking function. Then, using the existing method (Fuzzy Sets Syst. 125 (2002) 335–342), the transformed crisp MOLFOP is transformed into a crisp multi-objective linear optimization problem (MOLOP). Finally, it is assumed that to find a POS of the considered intuitionistic fuzzy MOLFOP is equivalent to find a POS of the transformed crisp MOLOP. It is pertinent to mention that this assumption is valid only if the transformed crisp MOLFOP is equivalent to the considered intuitionistic fuzzy MOLFOP as well as the transformed crisp MOLOP is equivalent to the transformed crisp MOLFOP. In this note, a numerical example is considered to show that the transformed crisp MOLFOP is not equivalent to the considered intuitionistic fuzzy MOLFOP. Also, on the basis of the existing results (Fuzzy Sets Syst. 246 (2014) 156–159), it is pointed out that the transformed crisp MOLOP is not equivalent to the transformed crisp MOLFOP. Therefore, Moges et al.’s method is not valid and hence, the results of agricultural planning problem of Ethopia for cultivation of different crops, obtained by Moges et al. with their proposed method, are not correct.

Study on the Coupling and Coordinated Development Mechanism and Implementation Path of Digital Economy Drive and Rural E-Commerce

The rural revitalization strategy is taken as an important measure to solve the problem of agriculture, rural areas and farmers, and a powerful starting point for realizing this strategy is agricultural e-commerce. The vigorous development of agriculturale-commerce helps farmers eliminatepoverty, increase income, and promote agricultural industrialization. While bringing new development opportunities, it is also faced with new challenges, mainly including the lag of related supporting construction, the imbalance of regional development, and the unsustainability of development structure. With the rapid development of the digital economy, using digital technology to promote the reform of agricultural e-commerceis particularly critical, which plays an important role in promoting the digital transformation process of the agricultural economy and accelerating rural revitalization.Therefore, China should actively use a variety of digital technologies, take digital agricultural e-commerce as the core, and focus on optimizing and implementing the construction of relevant supporting facilities, innovating the development mode of agricultural e-commerce, and constructing a sustainable chain development system, thus providing new ideas and directions for the development of agricultural e-commerce and better promoting the revitalization of digital rural areas.

Adaptive Reactive Power Optimization in Offshore Wind Farms Based on an Improved Particle Swarm Algorithm

To address the reactive power optimization control problem in offshore wind farms (OWFs), this paper proposes an adaptive reactive power optimization control strategy based on an improved Particle Swarm Optimization (PSO) algorithm. Firstly, an OWF multi-objective optimization control model is established, with the total sum of voltage deviations at wind turbine (WT) terminals, active power network losses, and reactive power margin of WTs as comprehensive optimization objectives. Innovatively, adaptive weighting coefficients are introduced for the three sub-objectives, enabling the weights of each optimization objective to be adaptively adjusted based on real-time operating conditions, thus enhancing the adaptability of the reactive power optimization model to changes in operating conditions. Secondly, a Uniform Adaptive Particle Swarm Optimization (UAPSO) algorithm is proposed. On one hand, the algorithm initializes the particle swarm using a uniform initialization method; on the other hand, it improves the particle velocity update formula, allowing the inertia coefficient to adaptively adjust based on the number of iterations and the fitness ranking of particles. Simulation results demonstrate the following: (1) Under various operating conditions, the proposed adaptive multi-objective reactive power optimization strategy can ensure the stability of node voltages in offshore wind farms, reduce active power losses, and simultaneously improve reactive power margins. (2) Compared with the traditional PSO algorithm, UAPSO exhibits an approximately 10% improvement in solution speed and enhanced solution accuracy.

KEY ASPECTS OF THE TRANSFORMATION OF THE CHARACTER OF COMPETITION ON THE UKRAINIAN FOOD MARKET

The set of opportunities of an agricultural enterprise to create competitive advantages make up the potential of its competitiveness. However, competitive advantages, especially those that can be characterized as sustainable, are formed on the basis of the mobilization of the economic potential of the enterprise, which is a set of opportunities for the long-term implementation of the main activity of the business entity. Accordingly, the study identified the place and role of the potential of competitiveness in the structure of the enterprise's potential and its relationship with the economic potential. In turn, it was established that the components of economic potential are production potential in combination with commercial and sales opportunities, the basis of all types of enterprise potential is resource potential, and the potential of product competitiveness and enterprise competitiveness is based on the economic potential of the enterprise, contributing to the growth of the latter. Agricultural producers face many problems that can prevent them from growing and selling their products profitably. The problem of ensuring the effective economic activity of the studied subjects of agricultural production lies in the relative complexity of the relationships between them within the framework of the current market environment. the market environment of the functioning of commercial structures is not homogeneous, and the levers of state regulation do not have an unequivocal effect on all operators of one or another commodity market at the same time. To increase productivity and expand participation in market relations, they absolutely need appropriate mechanisms and policy measures. In the current situation, it becomes necessary for each manufacturer to analyze its competitiveness and develop effective means to increase it. An important condition for ensuring the competitiveness of enterprises is the effective use of resources, personnel qualifications, achievements of modern management, innovative, financial and informational capabilities of the enterprise, which together represent its potential. State determination of the legal field of existence of market participants requires a clear understanding of the relevant state of their interaction and the development trends of this interaction. The consequences of agricultural regulation policy and the manifestation of market forces in relation to the productivity and evolution of the food industry vary depending on the field, direction of production, etc.

Impacts of Heavy Metal Pollution on Agricultural Production and Response Strategies

Agriculture is one of human beings’ most essential productive activities, and it is closely linked to human sustenance. Due to the ignorance of environmental production, production waste treatment in industries, and the lack of government regulation, the heavy metal pollution problem in agriculture has gradually become an important problem that needs to be solved urgently. Heavy metal pollution in agricultural land is a widespread problem that can contaminate downstream water systems, reduce crop yields, and threaten human safety. This paper examines the main sources of heavy metal pollutants and their impacts on agriculture and proposes related treatment measures for the public. Firstly, in part, by analyzing the sources of heavy metal pollutants, researchers find out that the pollutants are usually categorized into factory emissions, municipal waste pollution, and the use of pesticides. Secondly, the paper focuses on illustrating the impacts on agriculture. Mentioning the destruction of crop growth and health hazards posed on humans. Finally, the treatment measure is divided into the aspects of present technologies (including Laser-induced breakdown spectroscopy (LIBS) and Phytoremediation), treatments for governments, and measures for farmers. In the future, to ensure people’s health, human beings should put more effort into solving heavy metal pollution, caring for agricultural safety, and protecting the environment. The paper will contribute to recalling society’s awareness of environmental protection, offering new aspects of viewing heavy metal pollution, and providing practical methods of solving the agricultural pollution problem.