Search Results (19)

Transgenesis and gene editing offer a promising approach for more efficient and sustainable aquaculture by generating high-performance fish to enhance global food security. This article provides a comprehensive review of the history, current status, and future perspectives of employing transgenesis and gene-editing technologies to improve fish production and welfare, focusing on catfishes, which represent a diverse group of economically important fish. We discussed the application of various genetic technologies, including gene transfer (transgenesis) and gene editing, to boost fish economic traits and achieve genetic confinement. We also reviewed the progress on integrating transgenesis and gene-editing techniques for multiple gene editing, an approach that can speed up and make the genetic modification of fish more efficient. This review also highlights several research gaps in the current literature on gene transfer and gene editing in catfishes. Specifically, it provides directions for future catfish research, including the employment of transcriptomics in phenotypic assessment of transgenic and gene-edited fish, addressing compensatory mechanisms when selecting the gene-editing targets, and accounting for gene-environment and gene-nutrition interactions. It also highlights the application of advanced gene-editing tools, integration of genomic selection and artificial intelligence with gene editing, transparent public education about the benefits and risks of genetic biotechnology, and the development of effective reproductive confinement strategies. Full article

Soybean (Glycine max (L.) Merr.) plays a pivotal role in global food security as a primary source of vegetable protein and oil. However, its production is increasingly jeopardized by the frequent concurrence of drought and heat stress, a scenario predicted to intensify under ongoing climate change. While the effects of individual stresses have been well documented, the combined occurrence of drought and heat imposes unique physiological challenges, such as the conflict between stomatal closure for water conservation and transpirational cooling, that critically impair yield stability. This review provides a comprehensive synthesis of the physiological and molecular mechanisms governing soybean responses to these combined stresses, with a specific focus on modifications of root system architecture and the sensitivity of biological nitrogen fixation. We critically analyze recent advances in genomic resources, highlighting key quantitative trait loci (QTLs) and candidate genes identified through genome-wide association studies (GWAS) and multi-omics integration. Furthermore, we propose integrated breeding strategies that bridge conventional breeding with cutting-edge technologies, including high-throughput phenotyping, speed breeding, and CRISPR/Cas9-mediated genome editing, underpinned by high-throughput phenotyping and speed breeding. By presenting a roadmap for developing climate-smart soybean cultivars, this review aims to support sustainable agricultural practices that ensure both adaptation and mitigation in a changing climate. Full article

Automated visual inspection of safety-critical metal assemblies such as automotive door lock strikes remains challenging due to their complex three-dimensional geometry, highly reflective surfaces, and scarcity of defect samples. While 3D sensing technologies are often constrained by cost and speed, traditional 2D optical methods struggle with severe imaging artifacts and poor generalization under few-shot conditions. This work constructs a complete system integrating defect imaging, generation, and detection. It proposes an integrated framework through the co-design of an image acquisition system and deep generative models to holistically enhance defect perception capability. First, we develop an imaging system using dome illumination and a small-aperture lens to acquire high-quality images of non-planar metal surfaces. Subsequently, we introduce a dual-stage generation strategy: stage one employs an improved FastGAN with Dynamic Multi-Granularity Fusion Skip-Layer Excitation (DMGF-SLE) and perceptual loss to efficiently generate high-quality local defect patches; stage two utilizes Poisson image editing and an optimized loss function to seamlessly fuse defect patches into specified locations of normal images. This strategy avoids modeling the complete complex background, concentrating computational resources on creating realistic defects. Experiments on a dedicated dataset demonstrate that our method can efficiently generate realistic defect samples under few-shot conditions, achieving 11–24% improvement in Fréchet Inception Distance (FID) scores over baseline models. The generated synthetic data significantly enhances downstream detection performance, increasing YOLOv8’s mAP@50:95 from 50.4% to 60.5%. Beyond proposing individual technical improvements, this research provides a complete, synergistic, and deployable system solution—from physical imaging to algorithmic generation—delivering a computationally efficient and practically viable technical pathway for defect detection in highly reflective, non-planar metal components. Full article

Efficient in vitro regeneration remains a major constraint in the genetic transformation, genome editing, and molecular breeding of wheat (Triticum aestivum L.), largely due to strong genotype-dependent recalcitrance and limited activation of developmental programs required for somatic embryogenesis. Plant regeneration relies on extensive transcriptional reprogramming and epigenetic remodeling orchestrated by morphogenic regulators that modulate meristem identity, as well as cellular pluri- and totipotency. In this review, we synthesize current molecular knowledge on key transcription factors (BBM, WUS/WUS2, GRF-GIF, WOX, LAX1, SERK, WIND1/ERF115) and signaling peptides (CLE/CLV-WUS module, phytosulfokine/PSK) that regulate embryogenic competence in monocot cereals, with emphasis on their orthologs and functional relevance in wheat. We highlight how controlled expression of these morphogenic genes, promoter engineering, and transient or excisable induction systems can significantly enhance regeneration capacity, reduce chimerism in CRISPR-Cas-edited plants, and facilitate genotype-independent transformation. We also discuss epigenetic and metabolic constraints underlying wheat recalcitrance and their potential modulation to improve culture responsiveness. By integrating evidence from wheat, rice, maize, and barley, we outline conserved gene-regulatory networks that reinitiate totipotency and propose strategies to accelerate doubled haploid production and speed-breeding pipelines. Collectively, morphogenic factors emerge as central molecular tools for overcoming regeneration bottlenecks and enabling next-generation wheat improvement. The objective of this review is to synthesize and critically evaluate current molecular knowledge on morphogenic regulators controlling in vitro regeneration in wheat (Triticum aestivum L.), with particular emphasis on their roles in genetic transformation and genome editing. Full article

Space-based on-orbit servicing missions impose stringent requirements for precise identification and localization of satellite components, while existing detection algorithms face dual challenges of insufficient accuracy and excessive computational resource consumption. This paper proposes SLD-YOLO, a lightweight satellite component detection model based on improved YOLO11, balancing accuracy and efficiency through structural optimization and lightweight design. First, we design RLNet, a lightweight backbone network that employs reparameterization mechanisms and hierarchical feature fusion strategies to reduce model complexity by 19.72% while maintaining detection accuracy. Second, we propose the CSP-HSF multi-scale feature fusion module, used in conjunction with PSConv downsampling, to effectively improve the model’s perception of multi-scale objects. Finally, we introduce SimAM, a parameter-free attention mechanism in the detection head to further improve feature representation capability. Experiments on the UESD dataset demonstrate that SLD-YOLO achieves measurable improvements compared to the baseline YOLO11s model across five satellite component detection categories: mAP50 increases by 2.22% to 87.44%, mAP50:95 improves by 1.72% to 63.25%, while computational complexity decreases by 19.72%, parameter count reduces by 25.93%, model file size compresses by 24.59%, and inference speed reaches 90.4 FPS. Validation experiments on the UESD_edition2 dataset further confirm the model’s robustness. This research provides an effective solution for target detection tasks in resource-constrained space environments, demonstrating practical engineering application value. Full article

Potato (Solanum tuberosum L.) is one of the most important food crops in the world, ranking fourth after rice, maize, and wheat. Potatoes are exposed to biotic and abiotic environmental factors, which lead to economic losses and increase the possibility of food security threats in many countries. Traditional potato breeding faces several challenges, primarily due to its genetic complexity and the time-consuming nature of the process. Therefore, gene editing—CRISPR-Cas technology—allows for more precise and rapid changes to the potato genome, which can speed up the breeding process and lead to more effective varieties. In this review, we consider CRISPR-Cas technology as a potential tool for plant breeding strategies to ensure global food security. This review summarizes in detail current and potential technological breakthroughs that open new opportunities for the use of CRISPR-Cas technology for potato breeding, as well as for increasing resistance to abiotic and biotic stresses, and improving potato tuber quality. In addition, the review discusses the challenges and future perspectives of the CRISPR-Cas system in the prospects of the development of potato production and the regulation of gene-edited crops in different countries around the world. Full article

Maize is a vital staple crop significantly affected by climate change, necessitating urgent efforts to enhance its resilience. This review analyzes advanced methodologies for maize improvement, focusing on the identification of genetic determinants through QTL mapping, candidate gene mining, and GWAS. We highlight the transformative potential of CRISPR gene editing for identifying key regulators in maize development and the utility of virus-induced gene silencing (VIGS) for functional genomics. Additionally, we discuss breeding strategies leveraging the genetic diversity of maize wild relatives and innovations such as speed breeding and genomic selection (GS), which accelerate breeding cycles. Marker-assisted selection (MAS) plays a critical role in developing superior maize varieties. The review also encompasses agronomic practices and technological innovations, including GS, aimed at climate mitigation. High-throughput phenotyping and omics-based approaches, including transcriptomics and metabolomics, are essential tools for developing climate-resilient maize. Climate changes have a significant impact on maize production and pose unprecedented challenges to its cultivation. Full article

Sorghum is a climate-resilient crop which has been cultivated as a staple food in the semi-arid areas of Africa and Asia for food and nutrition security. However, the current climate change is increasingly affecting sorghum performance, especially at the flowering stage when water availability is critical for grain filling, thus lowering the sorghum grain yield. The development of climate-resilient, biotic and abiotic stress-tolerant, market-preferred, and nutrient-dense sorghum varieties offers a potentially cost-effective and environmentally sustainable strategy for adapting to climate change. Some of the common technologies for sorghum improvement include mass selection, single seed descent, pure line selection, and marker-assisted selection, facilitated by backcrossing and genotyping using molecular markers. In addition, recent advancements including new machine learning algorithms, gene editing, genomic selection, rapid generation advancement, and recycling of elite material, along with high-throughput phenotyping tools such as drone- and satellite-based images and other speed-breeding techniques, have increased the precision, speed, and accuracy of new crop variety development. In addition to these modern breeding tools and technologies, enhancing genetic diversity to incorporate various climate resilience traits, including against heat and drought stress, into the current sorghum breeding pools is critical. This review covers the potential of sorghum as a staple food crop, explores the genetic diversity of sorghum, discusses the challenges facing sorghum breeding, highlights the recent advancements in technologies for sorghum breeding, and addresses the perceptions of farmers on sorghum production under the current climate change conditions. Full article

In 2009, the International Building Code (IBC) introduced a new requirement for an additional exit stair or evacuation elevators in buildings (except residential buildings) over 420 ft. (128 m) tall. This new requirement has emerged as a critical innovation in occupant evacuation in supertall buildings, offering the potential for faster egress during emergencies. In the 2018 edition of the IBC, the analysis of full building evacuation with elevators is further required to demonstrate an evacuation time of less than 1 h. This paper examines the implementation of evacuation elevators in accordance with recent building code developments, such as the International Building Code (IBC), Chinese “General Code for Fire Protection of Buildings and Constructions” (GB 55037-2022), and the Korean Building Code (KBC). This study provides a comparative analysis of these regulations, highlighting the evolving acceptance of elevator-based evacuation methods. Since the requirements on means of egress in the codes in China and Korea follow similar concepts in the IBC, case studies of supertall buildings in China and Korea, where evacuation elevators were integrated into the overall egress strategy, are carried out to demonstrate the capability of evacuation elevators in achieving the IBC’s requirement for full evacuation within one hour. Using computer-based egress modeling, the study evaluates practical solutions for reducing evacuation times, exploring factors such as elevator capacity, speed, and coordination with traditional stairwell egress. The results suggest that, while evacuation elevators can significantly improve evacuation efficiency, achieving the one-hour target remains a challenge in complex, high-occupancy environments. The study indicates the importance of optimizing the balance between stair and elevator usage and explores the future role of artificial intelligence (AI) in enhancing evacuation systems. Full article

To address the issues with traditional genetic algorithm (GA) path planning, which often results in redundant path nodes and local optima, we propose an Improved Genetic Algorithm that incorporates an ant colony algorithm (ACO). Firstly, a new population initialization method is proposed. This method adopts a higher-quality random point generation strategy to generate random points centrally near the start and end of connecting lines. It combines the improved ACO algorithm to connect these random points quickly, thus greatly improving the quality of the initial population. Secondly, path smoothness constraints are proposed in the adaptive function. These constraints reduce the large-angle turns and non-essential turns, improving the smoothness of the generated path. The algorithm integrates the roulette and tournament methods in the selection stage to enhance the searching ability and prevent premature convergence. Additionally, the crossover stage introduces the edit distance and a two-layer crossover operation based on it to avoid ineffective crossover and improve convergence speed. In the mutation stage, we propose a new mutation method and introduce a three-stage mutation operation based on the idea of simulated annealing. This makes the mutation operation more effective and efficient. The three-stage mutation operation ensures that the mutated paths also have high weights, increases the diversity of the population, and avoids local optimality. Additionally, we added a deletion operation to eliminate redundant nodes in the paths and shorten them. The simulation software and experimental platform of ROS (Robot Operating System) demonstrate that the improved algorithm has better path search quality and faster convergence speed. This effectively prevents the algorithm from maturing prematurely and proves its effectiveness in solving the path planning problem of AGV (automated guided vehicle). Full article

Heat stress (HS) is a major threat to crop productivity and is expected to be more frequent and severe due to climate change challenges. The predicted increase in global temperature requires us to understand the dimensions of HS experienced by plants, particularly during reproductive stages, as crop productivity is majorly dependent on the success of plant reproduction. The impact of HS on crop productivity is relatively less-studied than the other abiotic stresses, such as drought and salinity. Plants have evolved diverse mechanisms to perceive, transduce, respond, and adapt to HS at the molecular, biochemical, and physiological levels. Unraveling these complex mechanisms underlying plant HS response and tolerance would facilitate designing well-informed and effective strategies to engineer HS tolerance in crop plants. In this review, we concisely discuss the molecular impact of HS on plant reproductive processes and yield, with major emphasis on transcription factors. Moreover, we offer vital strategies (encompassing omics studies, genetic engineering and more prominently gene editing techniques) that can be used to engineer transcription factors for enhancing heat tolerance. Further, we highlight critical shortcomings and knowledge gaps in HS tolerance research that should guide future research investigations. Judicious studies and a combination of these strategies could speed up the much-needed development of HS-resilient crop cultivars. Full article

Coconut (Cocos nucifera L.) is a perennial palm with a wide range of distribution across tropical islands and coastlines. Multitude use of coconut by nature is important in the socio-economic fabric framework among rural smallholders in producing countries. It is a major source of income for 30 million farmers, while 60 million households rely on the coconut industry directly as farm workers and indirectly through the distribution, marketing, and processing of coconut and coconut-based products. Stagnant production, inadequate planting materials, the effects of climate change, as well as pests and diseases are among the key issues that need to be urgently addressed in the global coconut industry. Biotechnology has revolutionized conventional breeding approaches in creating genetic variation for trait improvement in a shorter period of time. In this review, we highlighted the challenges of current breeding strategies and the potential of biotechnological approaches, such as genomic-assisted breeding, next-generation sequencing (NGS)-based genotyping and genome editing tools in improving the coconut. Also, combining these technologies with high-throughput phenotyping approaches and speed breeding could speed up the rate of genetic gain in coconut breeding to solve problems that have been plaguing the industry for decades. Full article

Trail running is an increasingly popular discipline, especially over long-distance races (>42.195 km). Pacing strategy, i.e., how athletes modulate running speed for managing their energies during a race, appears to have a significant impact on overall performance. The aims of this study were to investigate whether performance level, terrain (i.e., uphill or downhill) and race stage affect pacing strategy and whether any interactions between these factors are evident. Race data from four race courses, with multiple editions (total races = 16), were retrieved from their respective events websites. A linear mixed effect model was applied to the full dataset, as well as to two subgroups of the top 10 male and female finishers, to assess potential differences in pacing strategy (i.e., investigated in terms of relative speed). Better finishers (i.e., athletes ranking in the best positions) tend to run downhill sections at higher relative speeds and uphill sections at lower relative speeds than slower counterparts (p < 0.001). In the later race stages, the relative speed decrease is larger in downhill sections than in uphill ones (p < 0.001) and in downhill sections, slower finishers perform systematically worse than faster ones, but the performance difference (i.e., between slower and faster finishers) becomes significantly larger in the later race stages (p < 0.001). Among elite athletes, no difference in pacing strategy between faster and slower finishers was found (p > 0.05). Both men (p < 0.001) and women (p < 0.001), in the later race stages, slow down more in downhill sections than in uphill ones. Moreover, elite women tend to slow down more than men (p < 0.001) in the later race stages, regardless of the terrain, in contrast to previous studies focusing on road ultramarathons. In conclusion, running downhill sections at higher relative speeds, most likely due to less accentuated fatigue effects, as well as minimizing performance decrease in the later race stages in downhill sections, appears to be a hallmark of the better finishers. Full article

Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based ‘dietary protein’ biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk. Full article

Grass pea (Lathyrus sativus L.) is an annual cool-season grain legume widely cultivated in South Asia, Sub-Saharan Africa, and in the Mediterranean region. It is a stress-resilient crop with high nutritional value, considered a promising source of traits to breed for adaptation/mitigation of climate change effects. It is also reported as a suitable crop for more sustainable production systems such as intercropping. In this review, we elaborate an integrative perspective including not only an agronomic-based but also a variety-breeding-based strategy in grass pea to deal with climate change impacts, summarizing the current knowledge on grass pea biotic/abiotic stress resistance. Additionally, we highlight the importance of implementing fundamental techniques to create diversity (as interspecific hybridization or gene editing) and increase genetic gains (as speed breeding or the efficient identification of breeding targets via genomics) in the development of multiple stress-resistant varieties that simultaneously provide yield and quality stability under climate vulnerable environments. Full article