Global Security Challenges Research Articles

AI and Related Technologies in the Fields of Smart Agriculture: A Review

The integration of cutting-edge technologies—such as the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and various emerging technologies—is revolutionizing agricultural practices, enhancing productivity, sustainability, and efficiency. The objective of this study is to review the literature regarding the development and evolution of AI as well as other emerging technologies in the various fields of Agriculture as they are developed and transformed by integrating the above technologies. The areas examined in this study are open field smart farming, vertical and indoor farming, zero waste agriculture, precision livestock farming, smart greenhouses, and regenerative agriculture. This paper links current research, technological innovations, and case studies to present a comprehensive review of these emerging technologies being developed in the context of smart agriculture, for the benefit of farmers and consumers in general. By exploring practical applications and future perspectives, this work aims to provide valuable insights to address global food security challenges, minimize environmental impacts, and support sustainable development goals through the application of new technologies.

Advancement in Precision Agriculture: A Comparative Analysis of Traditional and Innovative Robotics

Precision agriculture, a revolutionary approach to modern farming, leverages technology and data-driven techniques to optimize crop production and resource management. This review article delves into the advancements in precision agriculture, focusing on the integration of traditional practices with innovative robotics. The study explores the evolution of agricultural robotics, from early mechanized systems to cutting-edge autonomous robots powered by artificial intelligence, machine learning, and IoT. A comparative analysis is conducted to evaluate the efficiency, scalability, and environmental impact of traditional systems versus contemporary robotic solutions. The paper also examines the challenges in adopting robotics in agriculture, such as cost, technological complexity, and scalability for small and medium-scale farmers. Additionally, it highlights emerging trends, including drone-based crop monitoring, autonomous weeding systems, and precision seeding technologies, which aim to address global food security challenges while ensuring sustainability. This article serves as a comprehensive resource for researchers, technologists, and policymakers aiming to bridge the gap between traditional and modern agricultural systems, paving the way for smarter and more efficient farming practices

Unlocking Opportunities and Overcoming Challenges in Genetically Engineered Biofortification

Micronutrient deficiencies affect over three billion people globally; there is a particularly severe problem with iron and zinc nutrition in developing countries. While several strategies exist to combat these deficiencies, biofortification has emerged as a powerful and sustainable approach to enhance the nutritional value of staple crops. This review examines recent advances in crop biofortification and their potential to address global nutritional challenges. We present successful case studies including iron-enriched cassava, nutrient-enhanced tomatoes, and omega-3-fortified oilseed crops, demonstrating the diverse possibilities for improving nutritional outcomes. The integration of novel plant-based protein production techniques has further expanded opportunities for sustainable nutrition. However, significant challenges remain, including complex environmental interactions, regulatory considerations, and sociocultural barriers to adoption. Economic analyses suggest biofortification offers substantial return on investment, with every dollar invested generating up to seventeen dollars in benefits through reduced disease burden. As global food security challenges intensify due to climate change, biofortified crops represent a crucial tool for improving nutritional outcomes, particularly in low- and middle-income countries. We conclude by examining emerging opportunities and future directions in this rapidly evolving field.

Enhancing Food Security via selecting Superior Camelina (Camelina sativa L.) parents: a positive approach incorporating pheno-morphological traits, fatty acids composition, and Tocopherols Content

BackgroundPreserving plant genetic resources is essential for tackling global food security challenges. Effectively meeting future agricultural demands requires comprehensive and efficient assessments of genetic diversity in breeding programs and germplasm from gene banks. This research investigated the diversity of pheno-morphological traits, along with the fatty acid and tocopherol content and composition, in 135 double haploid lines of camelina.ResultsThe number of sub-branches, siliques number of main-branch and sub-branch, and seeds number in siliques of the main-branch displayed notable coefficients of variation with values of 33.19%, 30.32%, 29.23%, and 23.81% respectively. Within the current investigation, the measurements of height, sub-branch number, and thousand seed weight varied from 53.50 to 86.50 cm, 3.50 to 14, and 0.73 to 1.52 g, respectively. The analysis unveiled that the average content of omega-3, omega-6, and omega-9 fatty acids in the examined lines was approximately 33%, 20%, and 17%, respectively. The total tocopherol content varied between 675 and 877 ppm, predominantly consisting of gamma-tocopherol, which accounted for over 95% of the total content. The fatty acid C18:2 displayed a markedly strong positive correlation with alpha-tocopherol (0.99**), while C18:3 exhibited positive correlations with gamma-tocopherol (0.98**) and total tocopherol (0.98**). Furthermore, a positive correlation was evident between C20:1 and delta-tocopherol (0.98**). The scrutinized lines, specifically lines 35, 72, 94, and 126 demonstrated notable attributes regarding yield and yield components. Conversely, in the realm of biochemical traits, lines 35, 66, 47, 30, 65, 135, 83, 27, 4, 77, 62, 81, and 93 stood out for their elevated potential. The gene expression analysis related to the tocopherol biosynthesis pathway revealed distinct expression patterns. Specifically, the VTE1 gene exhibited the highest level of expression. In contrast, the VTE3 gene displayed the lowest level of expression compared to other genes.ConclusionsThe study’s findings hold great potential for improving food security by enabling the selection of superior camelina parent plants based on specific traits. This approach can drive the development of high-yielding varieties with enhanced nutritional value and better-quality camelina oil.

FIVE DECADES OF DEVELOPMENT OF RICE RESEARCH IN SWAMPLANDS: USING BIBLIOMETRIC ANALYSIS

Objective: This study aims to critically evaluate the evolution of rice research in swampland environments over the past 50 years using bibliometric analysis. It seeks to understand publication trends, identify leading authors, examine emerging research topics, and explore institutional associations related to rice farming in marsh areas. Theoretical Framework: The research is grounded in the principles of bibliometric analysis, which provide a systematic approach to examining trends, patterns, and networks within academic literature. This framework highlights the intersection of agricultural research and environmental science, focusing on the unique challenges and opportunities in swampland rice cultivation. Method: Data were collected from the Scopus database, focusing on publications from 1955 to 2024, primarily academic articles written in English. The analysis included trends in publication volume, identification of key authors and institutions, keyword co-occurrence, and patterns of collaboration among researchers and institutions. Results and Discussion: The analysis reveals a significant increase in publications since the 1970s, with a sharp rise in the last two decades, indicating growing recognition of the importance of swamplands in global rice production. Leading authors are predominantly affiliated with Asian universities, emphasizing Asia's critical role in rice science. Keyword analysis highlights central themes such as flood resilience, soil management, climate change adaptation, and nitrogen-use efficiency. Collaborative networks among authors and institutions demonstrate strong interdisciplinary and international dynamics. Research Implications: The findings underscore the need to enhance global collaborative efforts, adopt interdisciplinary research approaches, and increase funding for researcher training and technological advancements. These strategies are vital for addressing global challenges related to food security and climate change, particularly in swampland rice production. Originality/Value: This study provides a comprehensive bibliometric overview of rice research in swampland areas, addressing a critical gap in understanding historical and current trends. It offers valuable insights for researchers, policymakers, and agricultural practitioners, contributing to sustainable rice production strategies in the face of global environmental and food security challenges.

Smart Sensor Technologies Shaping the Future of Precision Agriculture: Recent Advances and Future Outlooks

The rapid advancement of smart sensor technologies has transformed the landscape of precision agriculture, ushering in a new era of data‐driven and sustainable farming practices. This study presents a comprehensive review of recent innovations and future perspectives in the domain of smart sensors for precision agriculture. By harnessing the power of the Internet of Things (IoT) and artificial intelligence, these sensors have revolutionized how farmers collect, analyze, and utilize data to optimize crop yield, conserve resources, and enhance overall agricultural efficiency. The review delves into various types of smart sensors used in precision agriculture, including soil sensors for monitoring moisture, nutrient levels, and soil health; crop health sensors for detecting diseases, pests, and stress factors; weather and environmental sensors for real‐time climate monitoring; and automated irrigation systems for precise water management. Cutting‐edge technologies such as drone‐based sensors, hyperspectral imaging, and sensor fusion are explored, highlighting their potential to revolutionize data acquisition and decision‐making in agriculture. Furthermore, the manuscript addresses the incorporation of smart sensors with data analysis systems. This enables farmers to acquire practical observations and render knowledgeable choices regarding watering schedules, fertilizing regimens, and safeguarding approaches for crops. The role of data‐driven agriculture in mitigating environmental impact, optimizing resource utilization, and promoting sustainable practices is emphasized. Despite the significant strides made in smart sensor technology, challenges such as sensor calibration, data privacy, interoperability, and adoption barriers remain pertinent. To address these hurdles, the manuscript outlines potential research directions and emerging trends in sensor development, including miniaturization, energy efficiency, and wireless communication advancements. In conclusion, this manuscript provides a comprehensive assessment of the recent advancements and future prospects of smart sensors in precision agriculture. With the potential to revolutionize traditional farming practices and address global food security challenges, smart sensors offer an unprecedented opportunity for farmers to enhance productivity, conserve resources, and foster sustainable agricultural practices regardless of an ever‐changing climate and growing demand for food.

Exploring the link between soil health and crop productivity.

Understanding the complex interactions of plants and soils in the face of global food security and environmental degradation challenges is critical to the future of sustainable agriculture. This review discusses the important link between soil health and crop productivity by providing and comprehensive assessment of soil properties and management methods. By examining the physical, chemical, and biological properties of soil, it uncovers the key limitations posed by the soil environment on crop growth. The review highlights how soil texture, nutrient availability, and moisture levels directly impact on root growth, water uptake, and nutrient use efficiencies, while also exploring how diverse cropping systems enhance soil ecology and biodiversity. By utilizing state-of-the-art bioinformatics, we offer an in-depth exploration of rhizosphere microbial communities, emphasizing the functions of phosphate-solubilizing and nitrogen-fixing bacteria in promoting vital nutrient cycles. The potential of using microbial fertilizers to increase crop resistance to disease and stress hold a major premise for future sustainability in agriculture. In this regard, this review highlights the long-term impacts of crop cultivation on soil microbial diversity, revealing intricate selection processes between crops and their microbial partners in shaping crop-soil-microbe interactions. In terms of soil management, practical nutrient management strategies are proposed based on soil testing, emphasizing the benefits of organic farming and conservation tillage for soil health. Modern precision agricultural tools and remote sensing technologies are encouraged to be refined for effective nutrient management. At the policy level, we evaluate international guidelines aimed at fostering agricultural sustainability, suggesting new research pathways for crop-soil dynamics and offering approaches for developing soil health indicators in the face of global environmental challenges.

Integration of Islamic Jurisprudence Principles within the UN Global Human Security Framework

This study explores the integration of Islamic jurisprudence principles, particularly maqāṣid al-Sharīʿa (objectives of Islamic law) and ḍawābiṭ (regulatory principles ensuring adherence to justice and moderation), into the United Nations' (UN) Global Human Security Framework. Using a recommendatory legal research methodology, this study analyses international legal documents, such as UNGA Resolution 66/290, and classical Islamic texts, including Al-Ghazali’s Al-Mustasfa. The findings reveal a strong alignment between maqāṣid al-Sharīʿa and the human security dimensions outlined by the UN, encompassing protection of religion, life, intellect, lineage, and wealth. By incorporating Islamic principles, this research offers a culturally inclusive and ethically grounded approach to global security challenges. The application of ḍawābiṭ highlights the importance of balancing justice and moderation in addressing critical issues such as economic inequality, humanitarian crises, and governance challenges. This study contributes to the discourse on global human security by proposing a novel framework that bridges religious law and international governance, providing a foundation for future interdisciplinary studies.

Economia solidária e produção de alimentos

Alternative economies are responses to conventional economic systems, such as the solidarity economy, which tend to have an impact on changes in food supply systems, aiming for a transition to sustainability. With this in mind, the article addresses the importance of the solidarity economy for food production in the interrelation between the terms solidarity economy and food. This is a comprehensive review, which its approach is organized into four sections: the first discusses the path to food security and the sustainability of food systems, demonstrating the challenges for global food security. The second refers to the principles of cooperativism, particularly its social organizations, with an emphasis on cooperatives and the solidarity economy. The third describes the influence of short chains on alternative food supply networks, based on an overview of the interdisciplinary dimension of these short food circuits. And finally, the fourth covers the debate on organic production as an alternative in food networks, presenting innovations achieved by organic farming. This is an analysis of studies already carried out on the global food system linked to a complex multifactorial dimension, in which organic farming and the solidarity economy can be an alternative to the transition to sustainability in food production chains.

Sensing Technologies for Outdoor/Indoor Farming.

To face the increasing requirement for grains as the global population continues to grow, improving both crop yield and quality has become essential. Plant health directly impacts crop quality and yield, making the development of plant health-monitoring technologies essential. Variable sensing technologies for outdoor/indoor farming based on different working principles have emerged as important tools for monitoring plants and their microclimates. These technologies can detect factors such as plant water content, volatile organic compounds (VOCs), and hormones released by plants, as well as environmental conditions like humidity, temperature, wind speed, and light intensity. To achieve comprehensive plant health monitoring for multidimensional assessment, multimodal sensors have been developed. Non-invasive monitoring approaches are also gaining attention, leveraging biocompatible and flexible sensors for plant monitoring without interference with its natural growth. Furthermore, wireless data transmission is crucial for real-time monitoring and efficient farm management. Reliable power supplies for these systems are vital to ensure continuous operation. By combining wearable sensors with intelligent data analysis and remote monitoring, modern agriculture can achieve refined management, resource optimization, and sustainable production, offering innovative solutions to global food security and environmental challenges.

GROWTH AND YIELD RESPONSES OF SOYBEAN (Glycine max L.) TO ZINC OXIDE (ZnO) NANOPARTICLES FOLIAR APPLICATION

Aim. This study was purposed to investigate the effects of zinc oxide nanoparticles (ZnO NPs) on the growth and yield performance of two soybean (Glycine max L.) varieties, TGX1904-6F and TGX1951-3F, under controlled experimental conditions. Methods. Zinc oxide nanoparticles were synthesized and characterized following standard protocols, and their effects were evaluated across five treatment levels (20, 40, 60, 80, and 100 ppm) in a completely randomized design with five replicates. Growth parameters, including plant height, leaf morphology, stem diameter, and branch number, were assessed alongside phenological and yield traits such as days to flowering, flower production, pod metrics, and seed weights. The results revealed significant improvements in plant growth and yield metrics at intermediate ZnO NP concentrations, with enhancements observed in plant height, branch number, pod weight, and seed yield. Specifically, 60 ppm ZnO NP treatment resulted in the highest branch production, while 40 and 80 ppm treatments significantly promoted floral and pod development. Conversely, higher concentrations (100 ppm) exhibited inhibitory effects on plant height and leaf morphology, suggesting potential toxicity at elevated ZnO NP levels. Statistical analyses, including one-way ANOVA and Pearson’s correlation, confirmed significant treatment effects (P ≤ 0.05) on growth and yield parameters, highlighting the critical role of dose optimization. Conclusions. The findings underscore the potential of ZnO NPs as a novel agricultural supplement to enhance soybean productivity while emphasizing the need for balanced application to mitigate toxicity risks. This study contributes valuable insights into sustainable farming practices, leveraging nanotechnology to optimize crop performance and address global food security challenges.

Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020

Amid persistent global food security challenges, the efficient utilization of cultivated land resources has become increasingly critical, as optimizing Cultivated Land Utilization Efficiency (CLUE) is paramount to ensuring food supply. This study introduced a cultivated land utilization index (CLUI) based on Fractional Vegetation Cover (FVC) to assess the spatiotemporal variations in Henan Province’s CLUE. The Theil–Sen slope and the Mann–Kendall test were used to analyze the spatiotemporal variations of CLUE in Henan Province from 2000 to 2020. Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. The results reveal the following: (1) From 2000 to 2020, the CLUE in Henan province showed an overall upward trend, with strong spatial heterogeneity across various regions: the central and eastern areas generally showed decline, the northern region remained stable with slight increases, the western region saw significant growth, while the southern area exhibited complex fluctuations. (2) Natural and economic factors had notable impacts on CLUE in Henan province. Among these factors, population and economic factors played a dominant role, whereas average temperature exerted an inhibitory effect on CLUE in most parts of the province. (3) The influenced factors on CLUE varied spatially, with human activity impacts being more concentrated, while topographical and climatic influences were relatively dispersed. These findings provide a scientific basis for land management and agricultural policy formulation in major grain-producing areas, offering valuable insights into enhancing regional CLUE and promoting sustainable agricultural development.

Bibliometric synthesis of intelligent systems in agriculture

Abstract This study undertakes a bibliometric analysis of recent investigations centered on intelligent systems in agriculture, a combined quantitative and qualitative approach is adopted, which is based on Visualization of Similarities (VOS) method. We then map prominent areas of interest, evaluate international collaboration extents, and identify potential research gaps. Aligned with the United Nations’ vision, the Sustainable Development Goals (SDGs) place a spotlight on the interconnection of poverty eradication (SDG 1), zero hunger (SDG 2), and fostering innovation and infrastructure development (SDG 9). The United Nations recognizes the profound challenges posed by global food insecurity, malnutrition, and the increasing vulnerability of the food system to environmental changes. As populations grow and the demand for food surges, there is an imperative to innovate and transform our agricultural and food systems. Adopting advanced technologies, like precision agriculture, remote sensing, Internet of Things (IoT), artificial intelligence (AI), and robotics, offers a promising avenue to address these challenges. Yet, despite the profound implications of these technologies in transforming agriculture, there remains a notable need for comprehensive research in this domain. Enhancing agricultural productivity, reducing resource wastage, and championing sustainability are pressing concerns. This study undertakes a bibliometric analysis of recent investigations centered on intelligent systems in agriculture, sourcing data from the Scopus database. To comprehensively analyze this vast dataset, a combined quantitative and qualitative approach is adopted, which is based on the visualization of similarities (VOS) method. We then map prominent areas of interest, evaluate international collaboration extents, and identify potential research gaps. Our findings offer pivotal insights that can shape the trajectory of future research and development in the agricultural sector. The significance of our analysis extends beyond academic interest. The insights derived hold the potential to catalyze the growth of smart systems in agriculture, addressing global food security challenges in the process. Moreover, by championing sustainable agricultural practices via intelligent systems, our study underscores its alignment with SDGs, notably those aiming at ensuring zero hunger and promoting responsible consumption and production.

Promoting artificial meat to improve food security and reduce resource-environment pressure: is it practicable in China?

Artificial meat is increasingly recognized as a crucial innovation for addressing global food security challenges and reducing environmental pressures. This study aims to understand the practicability of promoting artificial meat consumption to achieve the dual goals of improving food security and reducing resource-environment pressure by evaluating Chinese consumers’ willingness to pay (WTP) for artificial meat. A discrete choice experiment was conducted via an online survey involving 998 consumers from five representative Chinese cities. The experiment was designed to elicit preferences and WTP for artificial meat. A random information intervention providing positive information about artificial meat was included to examine its impact on consumer choices. The estimation results indicate significantly lower WTP for both cultured and plant-based meat compared to farm-raised meat, with plant-based meat receiving higher WTP than cultured meat. The information intervention notably reduced the WTP gap between artificial meat and farm-raised meat, suggesting that consumer education can positively influence acceptance. The findings suggest that the market introduction of artificial meat in China faces considerable challenges, particularly regarding consumer acceptance and perceived value. While positive information can reduce the disparity in WTP, the practicability of promoting artificial meat to achieve food security and environmental sustainability goals is currently limited. This study contributes to the literature on consumer attitudes towards artificial meat in China and provides critical insights for policymakers aiming to promote the consumption of artificial meat.

Leveraging Robotics for Sustainable Agriculture: A Comparative Analysis of Africa and the EU’S Food Security Strategies

The intensifying demand for food production, driven by population growth and climate pressures, has placed a strain on agricultural systems worldwide, particularly in Africa and the European Union (EU). This paper presents a comparative analysis of the adoption of robotics in agriculture across these regions, exploring the current practices, limitations, and advancements shaping the future of sustainable farming. In Africa, limited infrastructure, high costs, and technological barriers hinder the integration of robotics, challenging smallholder farmers and reducing productivity. Conversely, the EU demonstrates more advanced adoption, supported by robust policy frameworks and technology infrastructure, although it faces challenges including workforce aging and the need for ethical guidelines in AI applications. This study highlights significant case studies within the EU, such as those in the Netherlands and Germany, showcasing the economic and environmental impacts of robotics in diverse farming models. The analysis extends to the benefits of robotics in increasing productivity and resource efficiency while reducing labor dependency, contributing to precision farming practices and environmental sustainability. The findings underscore the critical role of robotics in future agricultural systems, suggesting that while Africa faces more immediate barriers to adoption, targeted investments and policy adaptations could bridge these gaps. The study concludes by advocating for tailored, region-specific strategies to achieve sustainable agriculture through robotics, underscoring the technology's potential to address global food security challenges in Africa and the EU.

Efficient sorghum and maize transformation using a ternary vector system combined with morphogenic regulators.

Sorghum bicolor (sorghum) is a vital C4 monocotyledon crop cultivated in arid regions worldwide, valued for its significance in both human and animal nutrition. Despite its agricultural prominence, sorghum research has been hindered by low transformation frequency. In this study, we examined sorghum transformation using the pVS1-VIR2 ternary vector system for Agrobacterium, combined with the morphogenic genes BABY BOOM and WUSCHEL2 and selection using G418. We optimized Agrobacterium-mediated infection, targeting key parameters such as bacterial optical density, co-cultivation time, and temperature. Additionally, an excision-based transformation system enabled us to generate transgenic plants free of morphogenic regulators. The method yielded remarkable transformation frequencies, reaching up to 164.8% based on total isolated plantlets. The same combination of ternary vector, morphogenic genes and geneticin-based selection also resulted in a marked increase in transformation efficiency of the Zea mays (maize) inbred line B104. The potential for genomic editing using this approach positions it as a valuable tool for the development of sorghum and maize varieties that comply with evolving European regulations. Our work marks a significant stride in sorghum biotechnology and holds promise for addressing global food security challenges in a changing climate.

Fiber-based biomaterial scaffolds for cell support towards the production of cultivated meat

The in vitro production of animal-derived foods via cellular agriculture is emerging as a key solution to global food security challenges. Here, the potential for fiber-based scaffolds, including silk and cotton, in the cultivation of muscle cells for tissue formation was pursued. Mechanical properties and cytocompatibility with the mouse myoblast cell line C2C12 and immortalized bovine muscle satellite cells (iBSCs) were assessed, as well as pre-digestion options for the materials due to their resilience within the human digestive track. The fibers supported cell adhesion, proliferation, and guided muscle cell orientation, facilitating myotube formation per differentiation. A progressive increase in biomass was also documented. Interestingly, iBSC proliferation was enhanced with coatings of recombinant proteins while C2C12 cells showed minimal response. Thus, both cotton and silk yarns were suitable as fiber-based scaffolds towards cell supportive goals, suggesting an alternative path toward structured protein-rich foods via this initial stage of textile engineering for food. Biomass prediction models were generated, enabling forecasts of cell growth and maturation across various scaffold conditions and cell types. This capability enhances the precision of the cultivation process towards an engineering approach, building on the inherent benefits of hierarchical muscle tissue structure, but here via textile engineering with these initial muscle-coated edible fibers. Further, the approach offers to reduce costs by optimizing cultivation time and media needs. These approaches are part of a foundation for future scalable and sustainable cultivated meat production. Statement of SignificanceThis research investigates the use of one-dimensional fiber-based scaffolds for cultivated meat production, contributing to advancements in cellular agriculture. It introduces a method to measure changes in biomass and scaffold degradation throughout the cultivation process. Additionally, our development of biomass prediction models improves the precision and predictability of cultivated meat production. This research not only aids in scaling up cultivated meats but also enhances the use of textile engineering techniques in tissue engineering, paving the way for producing complex, three-dimensional meat structures more sustainably.

Modern Plant Breeding for Achieving Global Food Security.

Modern plant breeding technologies have played a central role in addressing global food security challenges. These technologies, including next-generation sequencing (NGS) and multi-omics analysis, genome-wide association analysis (GWAS), genome editing and transgenics, machine learning, and speed breeding, have been improving crop yield and quality as well as crop adaptability under climate change conditions, such as tolerance to both biotic and abiotic stresses. Furthermore, identification, searching, assessment, and combining desirable integrated (morphological, physiological, and biochemical) attributes have been achieved with greater accuracy, efficiency, time, and cost-effectiveness, all of which are essential to meeting global food demands. These advancements hold promises for increasing food security in the face of population growth and climate change, ensuring a more resilient and sustainable food production system. Therefore, this topical collection was developed to feature the latest developments in modern plant breeding approaches to understand and improve plant attributes essential for ensuring sustainable crop production.

ЕВОЛЮЦІЯ СЮЖЕТНОГО НАРАТИВУ НАТО В КОНТЕКСТІ СТРАТЕГІЧНИХ КОМУНІКАЦІЙ ФІНЛЯНДІЇ Й ШВЕЦІЇ

The article traces the change in the vector of international and security policy of Finland and Sweden in view of their accession to NATO. The author analyses the transformation of the role of these countries in the international community and the impact of their strategic communications on solving global problems and confronting global security challenges both now and in the future. The main focus is on the intergovernmental consensus policy of Finland and Sweden, the relationship between domestic public debates on security and defence, public opinion and strategic thinking in the Nordic countries. It is predicted that the strengthening of the Northern bloc in NATO can enhance the military potential of not only Northern but also the whole of Europe, thus not only reducing the vulnerability of NATO’s frontline countries but also possibly changing the course of the Russian-Ukrainian war.

Al-driven Precision Agriculture: Advancing Crop Yield Prediction

This article explores the integration of Artificial Intelligence (AI) in precision agriculture, focusing on its role in advancing crop yield prediction and improving overall agricultural productivity. It examines three key areas: satellite imagery analysis, soil health monitoring, and weather data integration. The paper discusses how AI techniques such as Convolutional Neural Networks, IoT sensor networks, and ensemble methods are revolutionizing farming practices. It highlights the technical implementations of these technologies, their applications, and their significant impact on yield optimization, resource efficiency, and decision-making in agriculture. The study emphasizes the crucial role of AI in addressing global food security challenges and improving agricultural resilience to climate change.