Frontiers in Plant Science

Neonicotinoid seed treatments protect maize during early growth but can induce phytotoxicity that intensifies during storage. Despite recognized genotypic variation in tolerance, standardized phenotyping methods are lacking. We evaluated nine commercial maize hybrids under three seed treatments (control, one neonicotinoid [1N], and two neonicotinoids [2N]) across two storage periods (0 and 6 months at 25 {degrees}C) using germination, accelerated aging, and cold tests. A Seed Treatment Tolerance Index (STTI) was analyzed through hierarchical clustering, principal component analysis, and multivariate analysis of variance. Results showed a significant triple interaction among genotype, seed treatment, and storage. Hybrids from female line A maintained STTI above 0.95, while female C hybrids showed germination reductions up to 48 percentage points and vigor losses up to 90 percentage points under 2N after six months. Tolerance was associated with hydrogen peroxide regulation by catalase and ascorbate peroxidase. The STTI proved a reliable tool for classifying genotypic tolerance, with direct applications for breeding programs and seed industry logistics.

Napier grass (Cenchrus purpureus syn. Pennisetum purpureum), a perennial C4 forage and bioenergy crop, exhibits strong drought resilience, yet the integrative mechanisms underlying this tolerance remain incompletely understood. This study examined physiological, hydraulic, and metabolic responses of four Napier grass cultivars under PEG-induced osmotic stress and progressive soil water deficit. Drought significantly increased the root-to-shoot ratio, indicating preferential biomass allocation to roots, which supported maintenance of shoot growth and tissue water status. All cultivars showed an approximate twofold increase in water-use efficiency (WUE) under water deficit, with cv2 and cv7 displaying superior performance. Upregulation of aquaporin genes (PIP2;2 and PIP2;3) suggested active hydraulic regulation that sustained carbon assimilation under reduced transpiration. Metabolic profiling revealed pronounced root-centered osmotic adjustment, including accumulation of galactinol, myo-inositol, raffinose family oligosaccharides, proline, and several amino acids. Enhanced expression of the galactinol synthase gene confirmed activation of raffinose biosynthesis pathways. Genotypic variation highlighted cv2 as particularly drought resilient. Rapid post-stress regrowth further underscored the importance of perennial root persistence. In conclusion, drought tolerance in Napier grass arises from coordinated hydraulic resilience, osmotic adjustment, and C4 photosynthetic efficiency, supporting its suitability for forage and bioenergy production in water-limited environments. SignificantThis study shows drought tolerance in Napier grass relies on root-driven hydraulic and metabolic regulation with efficient water-use efficiency, rather than avoidance, and that PEG responses predict field performance.

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse biobased products. Increasing biomass yield will increase profitability and environmental benefits, so is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; GxE interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for GxE interaction presented the highest PA and the lowest MSE for CNN (PA: [~]0.77, MSE: [~]0.5) and YDY (PA: [~]0.70, MSE: [~]1.3) while for TCM and AIL these ranged from [~]0.28 to 0.41 and [~]1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Accurate, simultaneous, and efficient quantification of chemically diverse phytohormone species is a critical task towards understanding the complex system of phytohormone signaling pathways. Quantification of phytohormones with the commonly used technique liquid chromatography coupled to tandem mass spectrometry is susceptible to the influence of non-phytohormone components present in the sample, a phenomenon referred to as matrix effect. To reduce matrix effect, some phytohormone quantification methods include additional steps of cleanup of crude extracts. However, to what extent additional purification steps provide increased accuracy compared to simpler, less laborious methods is seldomly evaluated. We evaluated three previously described phytohormone extraction methods, two of which include solid-phase extraction and one that does not, in their ability to minimize matrix effect and generate accurate estimates of phytohormone species spanning six classifications, from fruit and leaf tissue of Solanum lycopersicum cv. Micro-Tom (tomato). Our results show that, while the methods that included solid phase extraction occasionally outperformed each other regarding matrix effect and/or recovery efficiency for broad range of phytohormones, they rarely outperformed the simpler single-phase extraction method. Short AbstractAccurate, simultaneous quantification of chemically diverse phytohormones by LC-MS/MS is frequently confounded by matrix effects, leading to the incorporation of additional purification steps. We systematically compared three published extraction protocols with or without solid-phase extraction in tomato tissues across six hormone classes. Solid-phase methods occasionally improved matrix suppression or recovery, but did not consistently outperform the single-phase approach, questioning the added value of extra cleanup steps, particularly when high-throughput is desired, as in the case of systems biology interrogations.

Giant Miscanthus giganteus (Mxg) is one of the most promising perennial crops to generate biomass feedstock for bioenergy and biobased products. It is derived from the natural inter-species hybridization of Miscanthus sacchariflorus (Msa) and Miscanthus sinensis (Msi) species, thus population improvement within these species is crucial. Genomic selection (GS) is an attractive option to accelerate breeding of perennial grasses, such as Miscanthus, which requires up to three years of evaluation to produce reliable phenotypic data. Hence, genotypes are observed in multiple years and locations causing inconsistent response patterns from one year to the next, between location, and/or location-by-year combinations. These inconsistencies are known as the genotype-by-environment interaction effect (GxE). Although GS has been successfully implemented in multiple annual crops where straightforward cross-validation schemes exist to assess the levels of predictive ability that can be reached, for perennial crops new cross-validation schemes will help avoid data contamination. Here, we propose a series of cross-validation schemes to evaluate model performance for perennial crops. We perform a case study by analyzing one panel of each species (516 genotypes of Msa, 280 genotypes of Msi) scored for biomass yield at different locations around the world over several years. The results of the different cross-validation schemes provide insights about the usefulness of GS to accelerate the breeding process of Miscanthus species. In addition, leveraging the GxE effects of different types significantly increases predictive ability (up to 10% in Msa and 30% for Msi) compared to the conventional approaches based on main effects only.

Kernel composition traits in maize, including protein accumulation, are of broad interest. The amount of the most abundant proteins in maize endosperm, the -zeins, can vary dramatically among genotypes and in response to soil nitrogen supply. Targeted reductions in -zein accumulation can improve nitrogen utilization and the nutritional quality of maize grain but have traditionally required expensive and destructive phenotyping methods. The Floury2-RFP (Fl2-RFP) reporter gene enables rapid, non-destructive visualization of -zein accumulation in individual maize kernels under white light. This feature is due to the high expression level programmed by the Fl2 promoter, the stability of zein proteins, and the use of monomeric RFP, which emits fluorescence without the need for multimerization. This study aimed to develop a method to quickly document and quantify Fl2-RFP accumulation using camera or smartphone images of either ears or shelled kernels. Results show images of shelled kernels processed with FIJI software capture the Fl2-RFP reporter phenotype better than images of ears. Fl2-RFP confirms the strong maternal control of -zein accumulation and, like grain protein concentration, responds to soil nitrogen supply. The Fl2-RFP phenotyping pipeline effectively quantified Fl2-RFP accumulation by color features from both camera and smartphone images. Smartphone imaging of Fl2-RFP in a diverse population of inbreds followed by elastic net regression of extracted image features predicted kernel protein concentration, as measured by near-infrared spectroscopy, with moderate accuracy (R2 = 0.68, MAE = 0.76, RMSE = 0.93). The spectral features that were most predictive of kernel protein concentration varied depending on whether the background endosperm color was white or yellow. The integrated analysis of Fl2-RFP intensity and grain protein concentration indicates genetic variation for kernel protein accumulation and N-responsiveness that is distinct from the well-studied -zeins. Our findings highlight the Fl2-RFP reporter gene as a valuable tool for investigating the genetic complexity of grain protein concentration and associated traits in maize.

Authentication of acai products is increasingly important due to the risk of species substitution among morphologically similar Euterpe taxa, with implications for food quality, labeling accuracy, and consumer trust. Despite advances in molecular methods, rapid and cost-effective tools for discriminating closely related Euterpe species in processed commercial matrices remain limited. This study evaluated High-Resolution Melting (HRM) analysis targeting two complementary chloroplast markers -- psbK-I and ycf1b -- as a practical approach for species-level authentication of acai (Euterpe oleracea and E. precatoria) and jucara (E. edulis) products. In silico specificity analysis confirmed that the ycf1b primer pair shows amplification restricted to the Arecaceae family, supporting the analytical robustness of the method. The combined markers enabled reliable differentiation of all target species, including closely related taxa, with a detection limit of approximately 10% in admixed samples. When applied to 50 commercial products, HRM successfully authenticated 46 samples, substantially outperforming DNA sequencing, which was limited by amplification failure and mixed chromatograms. Mislabeling was detected in one acai sorbet and three frozen acai pulps marketed as acai but molecularly identified as E. edulis, constituting a violation of Brazilian food labeling regulations. These findings demonstrate that HRM analysis provides a robust, rapid, and scalable strategy for routine species authentication in processed plant-based matrices, with potential for integration into food quality control workflows and large-scale commercial monitoring programs.

Maximum utilization of existing genetic variability in a breeding program depends on the efficient classification of the inbred lines into heterotic groups, particularly under stress conditions. This study applied practical breeding approaches to determine the mode of genetic inheritance for Striga resistance and proposes a weighted heterotic grouping method based on the general combining ability of multiple traits (WHGCAMT) and compares its effectiveness with other existing methods in classifying the inbred lines into heterotic groups in Striga-infested and optimum environments. Using Diallel design IV, 300 crosses were generated from 21 inbred lines and 4 standard testers. The crosses, along with six checks, were evaluated in an 18 x 17 alpha lattice design with two replications at two locations, in both artificial Striga-infested and Striga-free environments. The inbred lines were genotyped using DArTtag SNP markers. Phenotypic and genotypic data were analyzed using R. Analysis of variance revealed significant mean squares for hybrid, general combining ability (GCA), specific combining ability (SCA) and their interactions with environment. Significant positive and negative GCA and SCA effects were detected for grain yield and other measured traits. However, a larger proportion of additive gene action than non-additive gene action was observed for grain yield and most measured traits. The analysis of molecular variance also showed substantial genetic differences within and between clusters. Except for HSCA, the mean grain yield between the inter-group and intra-group hybrids was significant for each method. Pairwise comparison of the inter- and intra-group hybrids of all the methods showed significant differences between the WHGCAMT and all other methods in most cases. WHGCAMT consistently produced higher-yielding inter-group hybrids and lower-yielding intra-group hybrids, achieving breeding efficiency improvements of 55.8%, 4.3%, 15.7%, and 11.4% over the HSCA, HSGCA, HGCAMT and molecular marker methods, respectively, under Striga infestation. Thus, WHGCAMT offers more precise, reliable and biologically meaningful heterotic groups among early-maturing maize inbred lines.

Though currently a minor crop, faba bean is a promising source of plant-based protein as global diets shift towards more plant-based nutrition. To realise this potential, advances in breeding and cultivation are crucial. To exploit heterosis, faba bean breeding frequently utilises synthetic cultivars, which involves open pollination of inbred lines to produce a mixture of F1 hybrid seeds and self-pollinated offspring. Pure F1 hybrid cultivars are currently unavailable due to unstable cytoplasmic male sterility (CMS) systems. An ability to distinguish F1 seeds from their parental inbreds via characteristics associated with xenia effects could change this. The xenia effect refers to the influence of paternal pollen on seed traits, for example seed weight and cotyledon cells in faba bean. In this study, we exploited the xenia effect captured in hyperspectral imaging data to develop machine learning scenarios for discriminating between parental and F1 seeds of open pollinated synthetic combinations (Syn-1). The hyperspectral data were pre-processed using Savitzky-Golay filtering to reduce noise and smooth the spectra. Various machine learning algorithms were applied, incorporating Bayesian hyperparameter optimisation. The scenarios achieved up to 98.9 % accuracy in separating parental components of Syn-1. When including all seeds, the model achieved 40.7 %, indicating moderate detection and classification performance. As the harmonic mean of precision and recall, the F1 score accounts for both the correctness of F1 seed detections and the completeness with which F1 seeds were detected. While this approach does not yet enable the development of full hybrid cultivars, it paves the way for hybrid-enriched cultivars. These could help to streamline breeding for synthetic cultivars and potentially increase yields, for example by increasing the proportion of F1 hybrid seeds in synthetic cultivars. This study extends knowledge of the xenia effect in faba bean and provides a basis for further research aimed at enhancing breeding methods and productivity.

The transformation of the free nuclear syncytium into cellular endosperm tissue with starch and protein accumulation is a well-established phenomenon, at least in the fruits of cereals of the Triticeae tribe. The present article demonstrates that there is considerable diversity inherent in this type of caryopsis morphogenesis. By examining various taxa (species, varieties, and cultivars) of wheat, oats, and some wild grasses, this research reveals significant deviations in endosperm morphogenesis from the typical state. A new developmental pattern of endosperm was identified, characterized by several distinctive features such as incomplete cellularization of the syncytium and starch accumulation within the acellular endosperm domains and the endosperm cavity. A large number of plastids were observed in the syncytium stage, which served as the basis for the later amyloplast stage. The acellular endosperm domains and the cavity domain exhibited connections at specific discontinuities in the modified aleurone layer surrounding the cavity. The peripheral parts of the caryopsis received fewer assimilates necessary for starch synthesis, which was attributed to their increased distance from the transfer system and a likely reduction in the efficiency of assimilate transport through the apoplast in these areas. The starch cavity volume constituted a few percent of the overall caryopsis volume, which could serve as a foundation for potential breeding improvements to enhance starch yields across different varieties.

Lucerne is gaining interest as a living mulch in agroecological productions. However, its vigorous growth can lead to competition with cash crops for light and nutrients, necessitating new ideotypes. This study investigated the genetic basis of traits relevant to ideotype breeding: dormancy, spring regrowth, height, growth habit, leaflet size, stem diameter, and plant structure. Individuals from a diversity panel of 27 accessions and a synthetic population were phenotyped in a spaced plant nursery. Over 100,000 SNP markers were used for genotyping. Genome-wide association study (GWAS) and genomic prediction were conducted, considering population structure. Heritability estimates ranged from moderate to high in diversity panel (h{superscript 2} = 0.36-0.70) but were lower in synthetic population (h{superscript 2} = 0.17-0.33), reflecting reduced genetic variance. Trait correlations differed markedly between populations, indicating the possibility of recombining traits to create new ideotypes. GWAS identified a few QTL (r{superscript 2} up to 0.27) for leaflet size, height, growth habit, and plant structure, with candidate genes linked to growth, stress response, and signalling pathways. Genomic prediction was highly accurate in diversity panel, where broad genetic variation allowed reliable estimation of marker effects, with prediction accuracies exceeding 0.8 for heritable traits, including growth habit and leaflet size. In contrast, accuracies were low in synthetic population, reflecting its limited diversity and small size, whether training was based on the synthetic population itself or on the diversity panel. These results highlight the potential to recombine traits and develop lucerne ideotypes using molecular tools such as QTL detection and genomic prediction.

Neonicotinoid insecticides used in seed treatment present phytotoxic potential that may accelerate seed deterioration during storage; however, how this effect interacts with genotype remains poorly understood. We evaluated the physiological quality of five maize genotypes sourced from the Maize Breeding Programme of the Federal University of Lavras, comprising three inbred lines (L44, L91 and L64) and two half-sib hybrids (H44 and H91), treated with a neonicotinoid-based insecticide formulation (thiamethoxam and cyantraniliprole) and stored for up to nine months at 25{degrees}C. Physiological quality was assessed through germination on rolled paper + vermiculite, cold test, primary root length, a phytotoxicity index, projection pursuit multivariate analysis, and scanning electron microscopy of pericarp and aleurone layer. Insecticide treatment reduced germination and increased phytotoxicity indices, with inbred line L44 showing the most severe response, reaching phytotoxicity values up to 15.89 percentage points above hybrid H91 at six months of storage. Scanning electron microscopy revealed that L44 presented a thinner pericarp and pronounced aleurone layer disorganisation following treatment, whilst L91 remained structurally preserved. Tolerance to post-treatment storage is highly genotype-dependent, and pericarp thickness may represent a useful morphological marker for selecting tolerant genotypes in maize breeding programmes.

BackgroundExtensin peroxidases (EPs) are class III plant peroxidases and are responsible for intermolecular covalent crosslinking of extensin (EXT) monomers to create scaffolds within plant cell walls. The formation of these scaffolds impacts plant development, mechanical wounding, and response to pathogen attacks. Therefore, elucidating the molecular mechanism controlling covalent crosslinking of EXT monomers is crucial for understanding cell wall deposition and potentially improving plant growth and adaptation. The focus of this work is to use in silico analysis to determine the structural characteristics of an EP from tomato (TomEP) to elucidate its specificity for crosslinking of EXT monomers. ResultsIn this study the two-dimensional (2D) and three-dimensional (3D) structures of TomEP were determined using several advanced bioinformatics tools and compared to two other peroxidases: GvEP1 (a known EP) and HRP-C (having a low affinity for EXT substrates). The results revealed that TomEP is a stable and hydrophilic protein with high thermal stability. The heme binding pockets of TomEP and GvEP1 have more hydrophobic residues and larger volume and pocket area compared to HRP-C. Molecular docking at the active site, which includes a heme heteroatom, showed that the ligands consisting of the hydrophobic Tyrosine-X-Tyrosine [-Y-X-Y-] motifs (i.e., [-Y-K-Y-], [-Y-V-Y-], and [-Y-Y-Y-] found in EXTs, and their derivatives, Isodityrosine (IDT), Pulcherosine (Pul), Di-Isodytirosine (diIDT), bind perfectly to the active site of TomEP with dominant interactions of Val54, Ser94, Ala96 and Phe196 residues. Pulcherosine had the highest binding affinity, while [-Y-K-Y-] showed the lowest binding affinity. Molecular dynamics simulations showed that [-Y-X-Y-] motifs (and the derivative substrate ligands) remain bound to the active site of TomEP throughout the 100 ns long simulation. Furthermore, the binding of these substrates stabilized the protein structure. ConclusionThese results may explain why TomEP is particularly well-suited for EXT crosslinking and will have significant implications on biochemistry, biotechnology, and the potential use of these EPs in crops improvement.

During drought, numerous compounds accumulate in plant tissues, but their physiological roles remain unclear - they may function as osmolytes, osmoprotectants, or merely arise as by-products of stress-induced metabolic shifts. We developed an experimental approach to link accumulation patterns with specific functions, using Scots pine (Pinus sylvestris L.) saplings subjected to water deprivation and subsequent rewatering as a model system. We monitored changes in relative water content (RWC) and osmotic adjustment dynamics, employed untargeted primary metabolite profiling for preliminary screening of compounds correlated with water status, and performed quantitative GC-MS and LC-MS analyses of selected metabolites. Major inorganic cations (K, Ca{superscript 2}, Mg{superscript 2}) were also quantified to assess their potential roles. Our results revealed that tryptophan, valine, and lysine - though generally present in low abundance - exhibited selective accumulation under severely reduced RWC ([≤] 70%), suggesting their involvement as osmoprotectants. Major organic acids, particularly shikimic acid, showed trends consistent with osmotic adjustment. Notably, neither sucrose nor inorganic cations appeared to function as primary osmolytes in this context. The proposed approach offers a viable strategy for identifying compounds involved in plant adaptation to water deficit, with potential applications in breeding programs aimed at improving drought tolerance. HighlightsAn approach to identify osmolytes and osmoprotectants was implemented Accumulation of Trp, Val and Lys was consistent with their role in osmoprotection Osmotic adjustment relied predominantly on organic acids than on inorganic ions Monosaccharides but not sucrose correlates with changes in needle water status

2.Hairy root disease (HRD), caused by rhizogenic Agrobacterium, is an economically important disease affecting hydroponic tomato (Solanum lycopersicum L.) production worldwide. HRD-affected plants show extensive root proliferation, resulting in decreased energy expenditure towards fruit production. Host plant susceptibility to rhizogenic Agrobacterium is typically evaluated through artificial wounding-based infection bioassays. However, under natural infection settings, rhizogenic Agrobacterium can induce disease symptoms without deliberate, artificial wounding. We developed a soil-based, non-wounding bioassay that closely mimics natural rhizosphere interactions and permits quantitative and qualitative assessment of HRD symptoms. The assay measured root dry weight, documented agravitropic root development typical of HRD and confirmed in planta T-DNA gene expression using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). We used this bioassay to evaluate disease symptoms towards rhizogenic Agrobacterium in tomato cv. Moneymaker and the rootstocks Optifort, Maxifort, and Arnold. Optifort and Maxifort exhibited significantly higher root biomass than Arnold and Moneymaker, indicating more pronounced symptom development. The bioassay also differentiated virulence levels amongst various rhizogenic Agrobacterium strains isolated from HRD-affected plants. Together, these results show that our soil-based bioassay provides a robust and ecologically relevant platform for screening tomato genotypes and comparing virulence levels of rhizogenic Agrobacterium strains supporting resistance breeding and disease management efforts.

This study investigated the mutagenic effects of ethyl methane sulfonate (EMS) on the M{square} generation in cowpea (Vigna unguiculata (L.) Walp.) cultivar Wang Kae. A total of 275 M{square} seeds were treated with EMS concentrations of 20 mM, 40 mM, and 80 mM (75 seeds per treatment) by soaking for six hours, while 50 untreated seeds served as the control (0 mM). Phenological, yield-related and yield traits were recorded, and data were analysed using Jamovi 2.7.15 and JASP 0.95.4.0 through one-way ANOVA with post hoc contrast, principal component biplot, and cluster analyses. No optimal mutagenic concentration (LD50) was identified. Seed germination and seedling survival rates increased with increasing EMS concentration, ranging from 70.00% and 62.00% in the control (0 mM) to 89.33% and 74.67% at 80 mM, following the trend 0 mM < 20 mM < 40 mM < 80 mM. Significant differences (P < 0.05) were observed among treatments for all phenological traits, pod length, locule number, seed traits, and yield per plant. Yield was significantly higher (P = 0.047) at 20 mM (61.19 {+/-} 3.34 g) compared to the control. Contrast analysis identified genotypes B33 and D56 as the most productive mutants, with yields of 125.44 g and 111.85 g, respectively. Principal component analysis extracted eighteen components, with the first four cumulatively explaining 50.60% of total variation. Biplot analysis of PC1 and PC2 captured all phenological traits, key seed traits, and yield attributes, highlighting the superior performance of B33 and D56. Cluster analysis partitioned the 190 genotypes into six groups, with B33 and D56 constituting distinct clusters. EMS mutagenesis effectively induced heritable phenotypic variation, with putative superior genotypes identified for advancement to M{square} and evaluation in replicated multi-environment trials toward the development of farmer- and consumer-preferred cowpea varieties.

The contribution of soil chemistry to plant growth and resilience, including presence of phytohormones, is increasingly recognized. However, comprehensive characterization of soil phytohormones remains limited by chemical complexity of soil matrices, diversity and low- abundance of metabolites. To enable further discoveries we developed and validated performance of a liquid chromatography-mass spectrometry method with solid phase extraction, integrating targeted and untargeted hormonomic approaches for comprehensive soil phytohormone profiling. Method performance was evaluated for sixteen plant growth-regulating compounds and precursors, including abscisic acid, auxins, cytokinins, gibberellic acid, jasmonic acid, salicylic acid, karrikins, melatonin, serotonin, and tryptophan. The method demonstrated strong linearity (R{superscript 2} = 0.989-0.999), high sensitivity (limits of detection and quantification 0.1-50.2 and 1.4-167.3 pg on-column, respectively), and acceptable precision (1.3-9.6% intraday; 3.4-34.8% interday). Soil composition had a significant effect on recovery, with recovery being poor in some soils such as clay-rich soils; however, recovery for most phytohormones were within 20% of the matrix- adjusted spiked value. Validation results confirm that the method is suitable for use and was then used to quantify analytes in representative soil types. Integration of untargeted analysis expanded coverage to 250 additional putative phytohormones and hormone-related metabolites, revealing chemical signatures potentially associated with plant community composition. The method is robust across these soils spanning sandy, peat-rich, and clay-rich textures. This approach provides a versatile framework for investigating belowground phytohormone dynamics and their roles in plant physiology, resilience, and soil-plant feedbacks.

Wide hybridization between related species and genera provides valuable opportunities for broadening genetic diversity and introducing desirable traits. In the tribe Maleae (Rosaceae), Malus (apple) and Pyrus (pear) are phylogenetically closely related, and apple x pear hybrids represent promising materials such as for disease-resistance breeding. However, the effective utilization of such hybrids in breeding programs is constrained by long juvenile period. In this study, we established a tissue culture-based regeneration and genetic transformation platform for apple x pear hybrids. Key stages affecting adventitious shoot regeneration were optimized, and appropriate ranges of antibiotic selection pressure and bacterial elimination conditions were systematically evaluated. Regeneration capacity was predominantly genotype-dependent and became further restricted under Agrobacterium infection, necessitating precise balancing between regeneration competence and selection pressure. Using the highly competence line and the established transformation system, MdFT1 gene was successfully introduced and over-expressed in intergeneric hybrids, resulting in transgenic plants exhibiting floral bud initiation approximately six months after infection under in vitro conditions. This study provides a practical and efficient regeneration-transformation framework for apple x pear hybrids and demonstrates its applicability for FT-mediated early flowering. The established system offers technical support for accelerated breeding strategies and facilitates the utilization of novel resources in genetic improvement of pome fruit.

Soil salinity is a rapidly intensifying abiotic stress that significantly limits wheat productivity, particularly in coastal and irrigated agroecosystems. Although sodium (Na+) ion exclusion has been recognized as a key tolerance mechanism, the integration of physiological performance with Nax1-mediated molecular regulation among regionally adapted wheat genotypes remains insufficiently characterized. The present study aimed to dissect salinity tolerance by combining hydroponic phenotyping, multivariate trait analysis, molecular marker profiling, and quantitative expression analysis of the Na+ ion transporter gene Nax1. Seventeen spring wheat genotypes were evaluated under four salinity levels (0.0, 10, 12, and 14 dS m-{superscript 1}). Germination and survival rate, shoot and root growth, and biomass accumulation were measured. Principal component analysis (PCA) and hierarchical clustering were performed to classify genotypes, while SSR (simple sequence repeat) and Nax-linked markers assessed genetic diversity. Relative Nax1 expression was quantified using qRT-PCR (quantitative real-time polymerase chain reaction). Salinity significantly reduced germination, survival, elongation, and biomass, with strong genotype-dependent variation. Multivariate analyses clearly separated tolerant and sensitive genotypes, with biomass retention and survival contributing most to total variation. Marker analysis revealed moderate genetic polymorphism. Notably, tolerant genotypes exhibited 3-6-fold induction of Nax1 under severe salinity, positively correlating with biomass maintenance. These findings demonstrate that salinity tolerance in wheat is associated with coordinated physiological resilience and enhanced Nax1-mediated Na ion exclusion, thereby advancing mechanistic understanding and supporting molecular-assisted breeding for salt-affected environments.

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multi-kernel models, using additive and two alternative non-additive genomic relationship matrices, to estimate the variance components associated with the GCA of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability (SCA) arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multi-kernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both types of non-additive matrices produced similar results, affirming the robustness of the inferred genetic architecture. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multi-kernel models can improve the efficiency of hybrid breeding programs.