Search Results (859)

Genomic prediction has emerged as a powerful tool in aquaculture breeding, but its effectiveness depends on the careful selection of informative single nucleotide polymorphisms (SNPs) and the application of appropriate prediction models. This study aimed to enhance genomic prediction accuracy in Russian sturgeon (Acipenser gueldenstaedtii) by optimizing SNP selection strategies and exploring the performance of linear and machine learning models. Three economically important traits—caviar yield, caviar color, and body weight—were selected due to their direct relevance to breeding goals and market value. Whole-genome sequencing (WGS) data were obtained from 971 individuals with an average sequencing depth of 13.52×. To reduce marker density and eliminate redundancy, three SNP selection strategies were applied: (1) genome-wide association study (GWAS)-based prioritization to select trait-associated SNPs; (2) linkage disequilibrium (LD) pruning to retain independent markers; and (3) random sampling as a control. Genomic prediction was conducted using both linear (e.g., GBLUP) and machine learning models (e.g., random forest) across varying SNP densities (1 K to 50 K). Results showed that GWAS-based SNP selection consistently outperformed other strategies, especially at moderate densities (≥10 K), improving prediction accuracy by up to 3.4% compared to the full WGS dataset. LD-based selection at higher densities (30 K and 50 K) achieved comparable performance to full WGS. Notably, machine learning models, particularly random forest, exceeded the performance of linear models, yielding an additional 2.0% increase in accuracy when combined with GWAS-selected SNPs. In conclusion, integrating WGS data with GWAS-informed SNP selection and advanced machine learning models offers a promising framework for improving genomic prediction in sturgeon and holds promise for broader applications in aquaculture breeding programs. Full article

Understanding the interplay between plant leaf functional traits and plant and soil factors under different soil thicknesses is significant for quantifying the interaction between plant growth and the environment. However, in the context of ecological restoration of vegetation in mining areas, there has been a lot of research on trees, shrubs, and grasses, but the characteristics and correlations of leaf functional traits of vines have not been fully studied to a large extent. Here, we report the differences in leaf functional traits of six vine plants (Parthenocissus quinquefolia, Pueraria lobata, Hedera nepalensis, Campsis grandiflora, Mucuna sempervirens, and Parthenocissus tricuspidata) with distinct growth forms in different soil cover thicknesses (20 cm, 40 cm, and 60 cm). In addition, soil factor indicators under different soil cover thicknesses were measured to elucidate the linkages between leaf functional traits of vine plants and soil factors. We found that P. lobata showed a resource acquisition strategy, while H. nepalensis demonstrated a resource conservation strategy. C. grandiflora and P. tricuspidata shifted toward more conservative resource allocation strategies as the soil cover thickness increased, whereas M. sempervirens showed the opposite trend. In the plant trait–trait relationships, there were synergistic associations between specific leaf area (SLA) and leaf nitrogen content (LNC); leaf moisture content (LMC) and leaf nitrogen-to-phosphorus ratio (LN/P); and leaf specific dry weight (LSW), leaf succulence degree (LSD), and leaf dry matter content (LDMC). Trade-offs were observed between SLA and LSW, LSD, and LDMC; between leaf phosphorus content (LPC) and LN/P; and between LMC, LSW, and LDMC. In the plant trait–environment relationships, soil nutrients (pH, soil total phosphorus content (STP), and soil ammonium nitrogen content (SAN)) and soil enzyme activities (cellulase (CB), leucine aminopeptidase (LAP), enzyme C/N activity ratio, and enzyme N/P activity ratio) were identified as the primary drivers of variation in leaf functional traits. Interestingly, nitrogen deficiency constrained the growth of vine plants in the mining area. Our study revealed that the responses of leaf functional traits of different vines under different soil thicknesses have significant species specificity, and each vine shows different resource acquisition and conservation strategies. Furthermore, soil cover thickness primarily influences plant functional traits by directly affecting soil enzyme activities and nutrients. However, the pathways through which soil thickness impacts these traits differ among various functional traits. Our findings provide a theoretical basis and practical reference for selecting vine plants and optimizing soil cover techniques for ecological restoration in mining areas. Full article

Precisely predicting photovoltaic (PV) output is crucial for reliable grid integration; so far, most models rely on site-specific sensor data or treat large meteorological datasets as black boxes. This study proposes an explainable machine-learning framework that simultaneously ranks the most informative weather parameters and reveals their physical relevance to PV generation. Starting from 27 local and plant-level variables recorded at 15 min resolution for a 1 MW array in Çanakkale region, Türkiye (1 August 2022–3 August 2024), we apply a three-stage feature-selection pipeline: (i) variance filtering, (ii) hierarchical correlation clustering with Ward linkage, and (iii) a meta-heuristic optimizer that maximizes a neural-network R² while penalizing poor or redundant inputs. The resulting subset, dominated by apparent temperature and diffuse, direct, global-tilted, and terrestrial irradiance, reduces dimensionality without significantly degrading accuracy. Feature importance is then quantified through two complementary aspects: (a) tree-based permutation scores extracted from a set of ensemble models and (b) information gain computed over random feature combinations. Both views converge on shortwave, direct, and global-tilted irradiance as the primary drivers of active power. Using only the selected features, the best model attains an average R² ≅ 0.91 on unseen data. By utilizing transparent feature-reduction techniques and explainable importance metrics, the proposed approach delivers compact, more generalized, and reliable PV forecasts that generalize to sites lacking embedded sensor networks, and it provides actionable insights for plant siting, sensor prioritization, and grid-operation strategies. Full article

Tissue hypoxia is commonly observed in head cancers and contributes to both molecular and functional changes in tumour cells. It is known to stimulate erythropoiesis, angiogenesis, and metabolic alterations within tumour cells. Glioblastoma, a type of brain tumour, is characterized by rapid proliferation and aggressive growth. Recent studies have indicated that natural products may hold potential as components of cancer therapy. Among these, Polish propolis and its active compound, quercetin, have demonstrated promising anti-cancer properties. The aim of this study was to evaluate the concentrations of selected cytokines—specifically IL-6, IL-9, vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF-BB), interferon gamma-induced protein 10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1)—produced by astrocytes of the CCF-STTG1 cell line. The cytotoxic effects of ethanolic extract of propolis (EEP) and quercetin were assessed using the MTT assay. Astrocytes were stimulated with lipopolysaccharide (LPS, 200 ng/mL) and/or IFN-α (100 U/mL), followed by treatment with EEP or quercetin (25–50 µg/mL) under hypoxic conditions for two hours. Cytokine concentrations were measured using the xMAP Luminex Multiplex Immunoassay and the Multiplex Bead-Based Cytokine Kit. Our study demonstrated that Polish propolis and its component quercetin modulate the tumour microenvironment in vitro, primarily by altering the levels of specific cytokines. The HCA analysis revealed that IL-6 and MCP-1 formed a distinct cluster at the highest linkage distance (approximately 100% of Dmax), suggesting that their expression patterns are significantly different from those of the other cytokines and that they are more similar to each other than to the rest. PCA analysis showed that EEP-PL (50 μg/mL) with IFN-α and EEP-PL (50 μg/mL) with LPS exert similar activities on cytokine secretion by astrocytes. Similar effects were demonstrated for EEP-PL 50 μg/mL + LPS + IFN-α, EEP-PL 25 μg/mL + IFN-α and EEP-PL 25 μg/mL + LPS + IFN-α. Our findings suggest that Polish propolis and quercetin may serve as promising natural agents to support the treatment of stage IV malignant astrocytoma. Nonetheless, further research is needed to confirm these results. Full article

Urban flooding presents a growing challenge amid rapid urbanization, climate variability, and fragmented governance. Although simulation and risk assessment tools have advanced considerably, their integration into urban planning remains limited. This study utilized a comprehensive bibliometric analysis of 1293 articles from the Scopus database, selected through a PRISMA-guided workflow, to examine the temporal, structural, and conceptual evolution of simulation, flood risk, and planning in urban flood research from 1980 to 2025. The findings reveal a thematic progression from engineering-centric approaches to broader discourses on resilience, adaptation, and systemic risk. However, disciplinary fragmentation persists, with technical modeling, infrastructure planning, and governance still weakly connected. Despite a shared vocabulary around climate risk and resilience, practical integration into decision-making frameworks remains underdeveloped. The study highlights the need for more cohesive research-practice linkages and calls for frameworks that better align simulation outputs with urban planning imperatives. Full article

The commercialization of selective broccoli harvesters, a critical response to agricultural labor shortages, is hampered by end effectors with large operational envelopes and poor adaptability to complex field conditions. To address these limitations, this study developed and evaluated a novel end-effector with an integrated transverse cutting mechanism and a foldable grasping cavity. Unlike conventional fixed cylindrical cavities, our design utilizes actuated grasping arms and a mechanical linkage system to significantly reduce the operational footprint and enhance maneuverability. Key design parameters were optimized based on broccoli morphological data and experimental measurements of the maximum stem cutting force. Furthermore, dynamic simulations were employed to validate the operational trajectory and ensure interference-free motion. Field tests demonstrated an operational success rate of 93.33% and a cutting success rate of 92.86%. The end effector successfully operated in dense planting environments, effectively avoiding interference with adjacent broccoli heads. This research provides a robust and promising solution that advances the automation of broccoli harvesting, paving the way for the commercial adoption of robotic harvesting technologies. Full article

Soybeans are a primary source of plant-based protein, with seeds containing approximately 40% protein—a key quality trait. Selecting superior hybrid combinations and managing progeny effectively are crucial for developing high-protein soybean varieties. Using a recombinant inbred line population (RIL3613) derived from Dongnong L13 × Heihe 36 and its previously constructed high-density genetic linkage map, QTLs and QTL × environment interactions (QEIs) associated with seed protein content (SPC) were identified through the bi-parental population (BIP) model and multi-environment trials (MET) model in QTL IciMapping v4.2. Candidate genes were then predicted via sequence alignment and haplotype analysis between the parents. Finally, simulated breeding was conducted using the B4L function in the In Silico Breeding (ISB) module of the Blib platform to determine optimal breeding strategies across diverse environments. The analysis identified 19 QTLs associated with SPC and 97 QEIs linked to SPC. These QTLs collectively explained 84.442% of the phenotypic variance, with four QTLs exhibiting significant contributions. A key candidate gene, Glyma.12G231400, associated with soybean SPC, was predicted within the 38,995,090–39,293,825 bp interval on chromosome 12. Across 11 environments, three to six optimal breeding schemes were selected, all employing modified pedigree selection. These findings enhance our understanding of the genetic basis of soybean protein formation and provide technological support for molecular breeding for seed quality improvement. Full article

Bacterial blight (BB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is a major threat to global rice productivity. Although hybrid rice breeding has significantly enhanced yields, persistent genetic vulnerabilities within restorer lines continue to compromise BB resistance. This study addresses this challenge by implementing functional marker-assisted selection (FMAS) to pyramid two broad-spectrum resistance (R) genes, Xa21 and Xa23, into the elite, yet BB-susceptible, restorer line K608R. To enable precise Xa23 genotyping, we developed a novel three-primer functional marker (FM) system (IB23/CB23/IR23). This system complements the established U1/I2 markers used for Xa21. This recombination-independent FMAS platform facilitates simultaneous, high-precision tracking of both homozygous and heterozygous alleles, thereby effectively circumventing the linkage drag limitations typical of conventional markers. Through six generations of marker-assisted backcrossing followed by intercrossing, we generated K608R2123 pyramided lines harboring both R genes in homozygous states, achieving a recurrent parent genome recovery rate of 96.93%, as determined by single nucleotide polymorphism (SNP) chip analysis. The pyramided lines exhibited enhanced resistance against six virulent Xoo pathogenic races while retaining parental yield performance across key agronomic traits. Our FMAS strategy overcomes the historical trade-off between broad-spectrum resistance and the preservation of elite phenotypes, with the developed lines exhibiting resistance coverage complementary to that of both introgressed R genes. This integrated approach provides breeders with a reliable molecular tool to accelerate the development of high-yielding, disease-resistant varieties, demonstrating significant potential for practical deployment in rice improvement programs. The K608R2123 germplasm represents a dual-purpose resource suitable for both commercial hybrid seed production and marker-assisted breeding programs, and it confers synergistic resistance against diverse Xoo races, thereby providing a pivotal breeding resource for sustainable BB control in epidemic regions. Full article

Balancing mechanisms require the minimization of both the Shaking Moment ($ShM$) and Shaking Force ($\mathbf{ShF}$), a complex multi-criteria challenge often tackled using single-objective algorithms. However, these methods face difficulties in navigating competing objectives. In contrast, multi-objective algorithms provide a more efficient and adaptable framework, while Fully Cartesian Coordinates ($FCC$) simplify the balancing equations compared to conventional Cartesian formulations. This study focuses on optimizing the dynamic balance of a six-bar Watt linkage using $FCC$. A wide set of optimization methods is analyzed and compared, and among them, the S-Metric Selection Evolutionary Multi-objective Optimization Algorithm (SMS-EMOA) demonstrates superior performance. This algorithm achieves the most significant hypervolume value in only 10.44 min of execution. The results indicate that multi-objective algorithms outperform single-objective approaches, offering faster and more diverse optimization solutions. Additionally, this study introduces an analytical method that enables the straightforward identification of removable counterweights, achieving an equally effective balance while minimizing the number of counterweights required. Full article

Nightlily (Hemerocallis citrina Baroni) is mainly cultivated for bud consumption with medicinal, nutritional, and economic value. Enhancing nightlily yield is one of the most significant breeding goals of modern agriculture of H. citrina breeding objective, but it also faces great challenges. In this study, an intraspecific hybridization population crossed between two varieties, ‘Liuyuehua’ and ‘Datong Huanghua’ of Hemerocallis, was used to establish 715 F₁ individuals. Phenotypic data for eight floral traits, including scape number, bud number, scape length, scape diameter, bud length, bud diameter, fresh flower bud weight, and dry flower bud weight, were collected from 715 F₁ individuals over a three-year period (2022, 2023, and 2024). The Simple Repeat Sequence (SSR) markers were validated to genotype the 116 random F₁ individuals and to construct a linkage map. The intraspecific hybridization map contained 11 linkage groups. A total of 169 SSR markers were used to construct a linkage map, spanning a total map length of 1605.3 cM, with an average marker interval of 9.50 cM. The linkage map revealed 11 floral QTLs from 7.21% to 24.29% of phenotypic variation. Through collinearity analysis, it was found that 122 markers could be aligned to the published genome sequence of H. citrina. A total of five candidate genes for floral traits were predicted. The linkage map is essential for mapping and marker-assisted progeny selection that will accelerate the pace of nightlily breeding. Full article

The optimal exploitation of genetic variability is essential for the success of breeding programs and for identifying quantitative trait loci (QTLs) in genetic association studies. These benefit from populations with a high number of individuals; however, they are expensive since extensive plant maintenance, characterization, and evaluation are required. Core collections offer a practical solution by reducing the number of individuals while representing the original diversity of the population. This study aimed to construct a core collection for Japanese plum to serve as pre-breeding material and enable genetic association studies for traits that are difficult to evaluate. Starting from a population of 1062 individuals genotyped by sequencing, genetic distance and allele coverage metrics were applied to construct several core collections. Genetic parameters and phenotype distribution comparisons allowed for the selection of a core collection of 108 individuals that maximized genetic variability while representative of the original population, confirmed by linkage disequilibrium and population structure analyses. Its usefulness was validated by successfully mapping flowering and maturity dates through marker–trait association. The core collection constructed here will help in the study of fruit quality traits and biotic and abiotic responses, ultimately generating molecular markers to assist the crop’s molecular breeding. Full article

Jabal Akhdar goats, native to Oman’s high-altitude Jabal Akhdar mountain range, are recognized for their high growth rate, remarkable twinning rate, and adaptability to harsh environmental conditions. This study assesses the genetic structure, inbreeding levels, effective population size (N_e), and linkage disequilibrium (LD) of Jabal Akhdar goats while identifying genomic regions under positive selection that may contribute to their environmental adaptation. The SNP genotypes from 72 Jabal Akhdar goats and two desert breeds from Egypt (153 Barki and 60 Saidi) revealed a clear genetic distinction between both groups. Within the Jabal Akhdar goats, genetic differentiation was also identified among the three sampled villages, indicating a village-specific genetic structure. The Jabal Akhdar breed exhibited a moderate level of inbreeding (F_ROH = 0.16), greater than that of the Barki and Saidi breeds. Additionally, Jabal Akhdar goats displayed greater LD and lower N_e levels compared to the Egyptian breeds. Analysis of runs of homozygosity (ROH) and extended haplotype homozygosity-based statistics (iHS and Rsb) identified 93 genomic regions exhibiting signatures of positive selection (80 from ROH, 5 from iHS, and 8 from Rsb). These regions harbor genes associated with traits essential for environmental adaptability, including hypoxia tolerance (SUCNR1, ANGPTL1, MITF, MTUS2), muscle development and function (MBNL1, ACTC1, CAPN5), fertility (GNRHR, CCNA1, SPAG1), UV radiation resistance (UVRAG, BRCA1), bone development (SOST, MEOX1), and lipid metabolism for energy utilization (DGAT2, G6PC, SUCLG2). The results of this study provide valuable insights for identifying causative variants and haplotypes underlying the Jabal Akhdar goat’s superior adaptability. These findings can guide breeders in designing conservation strategies and improving the productivity of this unique indigenous breed. Full article

Potato common scab is one of the major diseases posing a threat to potato production on a global scale. No chemical agents have been found to effectively control the occurrence of this disease, and research on the identification of resistance genes and the development of molecular markers remains relatively limited. In this study, a diploid potato variety H535, which exhibits resistance to the predominant pathogen Streptomyces scabies, was utilized as the male parent, whereas the susceptible diploid potato variety H012 served as the female parent. Building upon the resistance QTL intervals pinpointed through a genome-wide association study, two potential resistance loci were localized on chromosome 2 of the potato genome, spanning the regions between 38–38.6 Mb and 41.3–42.7 Mb. These intervals accounted for 18.03% of the total phenotypic variance and are presumed to be the primary QTLs underlying scab resistance. Building upon this foundation, we expanded the hybrid progeny population, conducted resistance assessments, selected individuals with extreme phenotypes, developed molecular markers, and conducted fine mapping of the resistance gene. A phenotypic evaluation of scab resistance was carried out using a pot-based inoculation test on 175 potato hybrid progenies to characterize the F1 generation population. Twenty lines exhibiting high resistance and thirty lines displaying high susceptibility were selected for investigations. Within the preliminary mapping interval on potato chromosome 2 (spanning 38–43 Mb), a total of 214 SSR (Simple Sequence Repeat) and 133 InDel (Insertion/Deletion) primer pairs were designed. Initial screening with parental lines identified 18 polymorphic markers (8 SSR and 10 InDel) that demonstrated stable segregation patterns. Validation using bulked segregant analysis revealed that 3 SSR markers (with 70–90% linkage) and 6 InDel markers (with 70–90% linkage) exhibited significant co-segregation with the resistance trait. A high-density genetic linkage map spanning 104.59 cm was constructed using 18 polymorphic markers, with an average marker spacing of 5.81 cm. Through linkage analysis, the resistance locus was precisely mapped to a 767 kb interval (41.33–42.09 Mb) on potato chromosome 2, flanked by SSR-2-9 and InDel-3-9. Within this refined interval, four candidate disease resistance genes were identified: RHC02H2G2507, RHC02H2G2515, PGSC0003DMG400030643, and PGSC0003DMG400030661. This study offers novel insights into the genetic architecture underlying scab resistance in potato. The high-resolution mapping results and characterized markers will facilitate marker-assisted selection (MAS) in disease resistance breeding programs, providing an efficient strategy for developing cultivars with enhanced resistance to Streptomyces scabies. Full article

Malaria remains a health problem, with Plasmodium falciparum accounting for 96% of cases in Africa and 15% in Brazil. The growing threat of drug resistance to artemisinin-based combination therapies (ACTs) jeopardizes progress toward elimination. This study examined P. falciparum samples collected from 141 patients in Brazil (2013–2023) by PCR and DNA sequencing to identify single-nucleotide polymorphisms in the pfcrt, pfmdr1, and pfk13 genes. Half of the samples carried the SVMNTMCGI haplotype in pfcrt, and none of the samples showed C350R mutations. In pfmdr1, the NYCDY haplotype was dominant (70%), with low occurrences of N86Y (4%) and no Y184F polymorphisms. No mutations linked to artemisinin partial resistance were detected in pfk13. Only one Amazonas sample exhibited wild-type haplotypes across all genes. Genetic diversity was more pronounced in pfcrt than pfmdr1, reflecting selective drug pressure. Significant linkage disequilibrium (LD) was observed within pfcrt (C72S and K76T) and pfmdr1 (S1034C and N1042D), but not between the two genes. The absence of pfk13-resistant mutations and the low prevalence of key pfmdr1 markers support the efficacy of ACTs. The persistence of diverse haplotypes and intragenic LD reflects ongoing drug pressure, underscoring the need for continuous genetic surveillance to anticipate emerging resistance. Full article

Viticulture is facing challenges, like the impact of climate change and various pests and pathogens. Alongside powdery and downy mildew, black rot is one of the most prevalent fungal diseases in European wine-growing regions. The focus of grapevine breeding research has so far been mainly on resistance to mildew diseases, and marker-assisted selection (MAS) in breeding material is possible for the most important resistance loci. However, only a few loci have been described for black rot resistance and these cannot yet be used for MAS. Thus, the characterization of genetic resistance to black rot and the establishment of closely linked genetic markers is important for the breeding of cultivars with multifungal resistances. In this study, an improved SSR marker-based genetic map of the biparental mapping population V3125 (‘Schiava Grossa’ x ‘Riesling’) x ‘Börner‘ (Vitis riparia x Vitis cinerea) was used to perform QTL analysis for black rot resistance. A total of 195 F1 individuals were analyzed at 347 SSR marker positions distributed on all 19 chromosomes. QTL analysis detected two QTLs conferring resistance to black rot on linkage groups 14 (Rgb1) and 16 (Rgb2). Our results revealed for the first time that Rgb1 and Rgb2 are derived from the wild species V. riparia. The presence of both loci in F1 individuals showed a clear additive effect for black rot resistance, supporting the breeding strategy of pyramiding two or more resistance factors to achieve a stronger overall resistance. Full article