AoB PLANTS

BackgroundCell geometry plays a central role in determining division orientation and body axis formation during early embryogenesis in Arabidopsis thaliana. However, quantitative analysis of dynamic three-dimensional (3D) morphology remains challenging because live-imaging studies often rely on two-dimensional (2D) projections, while existing 3D reconstruction approaches, including mesh-based methods, often lose the original orientation information relative to the ovule and require labor-intensive mesh correction. In addition, embryo positional fluctuation caused by floating in liquid medium and continuous growth makes it difficult to analyze temporal morphological changes within a common coordinate system. ResultsWe developed a robust framework for quantitative 3D and four-dimensional (4D; 3D + time) analysis of embryo initial cell (apical cell) morphology. The method first establishes a standardized 3D coordinate system by normalizing cell orientation based on the bottom plane and the optical axis of the observation. Cell morphology is then reconstructed through ellipse-based approximation of serial cross-sections extracted from stacked imaging data, enabling accurate geometric characterization without the need for complex surface mesh reconstruction. To evaluate shape anisotropy, we quantified the apical cell shape in 3D. The framework further supports the characterization of volumetric features of subsequent division, providing a basis for quantifying 3D embryogenesis. ConclusionOur framework provides a simple and noise-reduced approach for quantitative analysis of living cell morphology in 3D. We named the integrated method of combining coordinate normalization with elliptical cross-section-based reconstruction Apical3DTip. This method enables consistent comparison of cell shapes without extensive manual corrections. The method overcomes key limitations of 2D projection-based and mesh-dependent analyses and offers a practical platform for quantifying cell shape and daughter cell shapes in 3D. More broadly, it provides a quantitative foundation for exploring the relationship between cell geometry, morphodynamics, and developmental patterning in living plant embryos.

PremiseSeed size and morphology are critical traits in agriculture, ecology, and genetics, but high-throughput quantification of these traits is often limited by labor-intensive manual measurements or expensive, platform-specific imaging software. Methods and ResultsWe developed SeedMeasure, a lightweight, open-source, and cross-platform command-line tool written in Python that automates the measurement of seed area, length, and width from images. Using a simple imaging setup, the program processes images by correcting for perspective skew, filtering debris, and exports quantitative data alongside quality-check images. We validated SeedMeasure across nine diverse species, ranging from small Arabidopsis thaliana seeds to large Zea mays kernels. The tool quickly handles images using multithreading and demonstrates high reproducibility, yielding low coefficients of variation across repeated runs. ConclusionsCompared to existing software, SeedMeasure is free, offers faster processing through parallel computing, and provides standalone executables that require no programming dependencies. SeedMeasure offers an accessible, cost-effective, and high-throughput approach for rapid phenotypic profiling, making advanced seed morphological analysis available to researchers without specialized laboratory hardware.

Multi-environment trials are central to cultivar evaluation because they reveal how candidate cultivars perform across locations, years, management conditions, and stress environments. The resulting yield matrix is a rich source of data on genotype-by-environment interaction, and a wide literature on estimation, decomposition, visualisation, and prediction of yield potential and stability has flourished. However the ultimate question of which cultivar to recommend on the basis of such a matrix is often left implicit. The question is far from trivial, and in this paper we formulate cultivar recommendation as an axiomatic ranking problem. This framework is rich enough to encompass the existing literature on stability indices, as well as any other deterministic ranking procedure. We show that many commonly used stability-based procedures can violate minimal criteria of efficiency or consistency. The result of such violations is that a cultivar with uniformly high yield could be ranked below a cultivar with uniformly low yield, or the relative ranks of two cultivars could depend on whether or not a third cultivar is present in the matrix. Our results prove that under a small number of such criteria the space of admissible rules collapses to the family of power means and their limiting cases. If we further wish to allow multiplication normalisation of yield, we are left with the geometric mean as the unique solution.

The photosynthesis-transpiration-stomatal conductance (An-E-gs) model framework is widely used for estimating photosynthesis, transpiration, and stomatal conductance in plants. The model equations are solved by numerical iteration, and the converged model values are deemed the solution. However, there has been no general guarantee that the iterative procedure converges to a solution or that the procedure leads to convergence. Building on the recent proof of the existence of a unique set of solutions, we herewith propose a numerical algorithm that is guaranteed to converge to the solution for the An-E-gs model framework. We first analytically prove that the proposed algorithm necessarily converges to a solution. We then demonstrate the convergence across contrasting combinations of leaf temperature, relative humidity, light, atmospheric CO2, and wind speed. We further demonstrate rapid convergence with the algorithm: no more than ca. 10 iterations for approximately 10-3 mol CO2 m-2 s-1 precision in net photosynthesis and no more than ca. 20 iterations for 10-7 mol CO2 m-2 s-1 precision. By guaranteeing convergence to the solution, this algorithm eliminates concerns about nonconvergence in leaf gas-exchange calculations and is expected to serve as a robust foundation for a range of studies from leaf-level gas exchange to global-scale carbon and water cycle dynamics.

The sequence of leaf physiological thresholds underlying plant responses to water deficit is thought to be functionally coordinated; yet, to what extent this coordination is maintained across genotypes and environments remains poorly documented at the intraspecific level. We characterized the sequence of stomatal closure, turgor loss and xylem embolism in the leaves of two genotypes of the riparian species Populus nigra (DRA-038 vs. PG-31) subjected to control, additional nitrogen or additional potassium treatments. Under control conditions, embolism measurements using the optical vulnerability method showed that DRA-038 was more vulnerable than PG-31, in agreement with measurements performed on stems with the reference Cavitron method. Stomatal closure consistently preceded xylem embolism, while bulk leaf turgor loss was typically observed once xylem embolism had already reached 50%. Hydraulic thresholds responded to treatments in a genotype-dependent manner, the intrinsically more vulnerable genotype DRA-038 being typically more plastic. However, despite variations across genotypes and treatments, the trait sequence remained tightly coordinated such that stomatal safety margins (SSMs) remained virtually null. These findings support a strong mechanistic integration of leaf hydraulic thresholds in poplar across genetic units and varying environments, questioning whether to favour intrinsic tolerance or plastic capacities in breeding future drought-tolerant genotypes.

Incomplete information on distributions for a high proportion of the world's plant species together with biases in global biodiversity data mean that current estimates of plant diversity patterns are skewed. A key issue is that current predictions rely on a subset of species that is not representative of all plant species. Here we tested the feasibility of a representative sampling approach for mapping global vascular plant diversity at the finest scale where comprehensive data is available. Using the World Checklist of Vascular Plants as a reference, we generate random samples of species with increasing sample sizes from the global species pool. We compare the diversity patterns retrieved from the samples against the patterns of the reference dataset using spatially weighted correlation coefficients and four different diversity metrics. We find that at the botanical country scale, representative global maps of species and phylogenetic diversity can be created with small numbers of species (~1% [0.2% and 0.4%, respectively]) at the botanical country scale. For effective growth form and family diversity sample sizes encompassing ~20% [19.2% and 19.5%, respectively] of all species are needed. Random samples require markedly fewer species to reach high correlations than when restricting the pool of species to single plant families or genera. We show that when representative samples are used robust inferences of plant diversity patterns can be made from only a small proportion of species.

O_LIFloral nectar plays a critical role in shaping the ecology and evolution of plant-pollinator interactions. Effective and efficient methods that allow for broad-scale sampling of nectar volume and sugar concentration across a diversity of taxa are needed to improve our understanding of many dimensions of mutualistic plant-pollinator interactions--including their basic ecology and evolution, their responses to environmental change, and their conservation and restoration. C_LIO_LIDespite the key importance of nectar for mediating plant-pollinator interactions, quantifying floral nectar in the field from many different plant species is challenging because there is often no one-size-fits-all sampling method that is effective across a diversity of floral structures and nectar traits. Different methods require different preparation, and sampling from many species involves a variety of logistical challenges. C_LIO_LIHere we provide a methodological roadmap for sampling floral nectar in the field from many different plant species. We describe our nectar collection methods in detail, including necessary equipment, calculations, and approaches appropriate for different floral morphologies. We also provide a troubleshooting guide for common problems encountered while collecting nectar in the field. To demonstrate the utility and effectiveness of our methods for collecting nectar from many different species, we present results on nectar trait variation from 53 species in an ecosystem. C_LIO_LIOur method illustrates that nectar traits vary considerably within and among plant species, indicating that large-scale nectar sampling projects are an important consideration for many basic and applied questions in pollination ecology and evolution. We hope that across many plant communities and ecosystems, our paper provides a practical roadmap for how to navigate the complexities of quantifying floral nectar traits. C_LI

Far-red light (FR; 700-750 nm) is increasingly incorporated into controlled-environment lighting because it can improve photosynthetic efficiency when combined with comparatively shorter wavelengths. In long-day leafy crops such as spinach, however, FR may also promote the transition from vegetative to reproductive growth and thereby reduce marketable yield. Most studies have evaluated FR fraction, intensity or end-of-day exposure, whereas the developmental timing of FR has rarely been tested, particularly in spinach. Here, we evaluated six commercial spinach cultivars (Amador, Harp, Renegade, Responder, Rubino and Santa Cruz) in an indoor vertical farm under a common red-green-blue background (PPFD 260-264 {micro}mol m-{superscript 2} s-{superscript 1}, 12 h photoperiod, 24 {degrees}C) and four FR timing treatments: no FR (Control), FR throughout production (FullFR), FR during early development only (EarlyFR), and FR during late development only (LateFR). LateFR increased marketable fresh weight relative to Control (244 vs 224 g) and reduced flowering incidence, whereas far-red supplied during early development reduced fresh weight (158 g) and increased flowering. The magnitude of the timing response differed among cultivars: switching from EarlyFR to LateFR recovered 0 % fresh weight in Amador but 107 % in Renegade and Rubino, with the largest penalties occurring in otherwise bolt-resistant cultivars. EarlyFR also increased total chlorophyll and reduced the chlorophyll a:b ratio. These results show that FR response in spinach is strongly conditioned by developmental stage and cultivar. Although LateFR received more total far-red than EarlyFR, it behaved like the Control, indicating that the penalty was set by far-red timing rather than dose. Treatment differences in bolting and yield tracked an estimated phytochrome photostationary-state deficit during early development: a phytochrome-deficit model markedly outperformed a cumulative-dose model ({Delta}AIC = 441), and the deficit x cultivar interaction was strong (p < 0.001), with bolt-resistant cultivars losing most yield when far-red coincided with the early developmental window. We therefore propose that FR should be treated as a genotype-dependent management variable rather than as a fixed spectral input, with late application and bolt-resistant cultivars offering the most favourable combination for vertical-farm spinach production. Framed within the breeders equation, the close match between the trial and production environment and the scope for shorter breeding cycles indoors suggest that genotype and far-red timing can be optimised jointly to accelerate genetic gain.

Grasslands are vulnerable to increasing drought with global warming, but process-based models lack the mechanistic knowledge required to predict the magnitude of drought impacts. While a plant hydraulics framework has been successful in advancing process understanding of drought responses in trees, and how drought responses vary across rainfall gradients, similar approaches have rarely been applied to grasses. Here, we quantified the progression of key drought response processes in sixteen dominant perennial grasses (seven C3 and nine C4) with differing climatic origins across eastern Australia. We found that stomatal closure, hydraulic impairment and leaf browning occurred concurrently, in contrast to the progressive sequence typically observed in trees. We also found that drought response traits were not correlated with species climate of origin. The early impairment of leaf hydraulic conductance and leaf browning along with the lack of correlation with climate of origin suggest that grasses may employ fundamentally different strategies to adapt to low water availability than trees. These results highlight the need for grass-specific parameterization of drought responses in process-based models.

The non-indigenous brown macroalga Rugulopteryx okamurae has emerged as one of the most aggressive marine invaders in European waters, deeply altering benthic communities and causing severe socioeconomic impacts. While its expansion has been extensively documented along the southern Iberian Peninsula, understanding the dynamics of its northward range expansion along the Spanish Mediterranean coast remains critical for coastal management. This study documents the first formal record of R. okamurae in Calpe (Alicante), representing its current northernmost distribution limit within the Comunitat Valenciana. Sampling was conducted through an initial opportunistic scuba diving observation along the surrounding waters of the Penyal dIfac Natural Park, followed by targeted underwater surveys and an ad hoc inspection of commercial bottom-trawling nets drying at the port of Calpe during June 2026. Morphological and anatomical identification was confirmed through cross-sections of the thallus under optical microscopy, revealing the presence of both the thick and intermediate morphotypes of the species. The collected specimens were found either entangled within a native photophilic algal canopy in shallow waters or recovered from deeper offshore fishing grounds. Given the absence of records in the area during 2023-2025 surveys, these findings suggest either a very recent front-wave colonization event or a contribution from nearby, yet undetected, established patches, driven by secondary local dispersal mechanisms such as drifting fragments and explicitly highlighting commercial fishing activities as an active vector. Furthermore, considering that the species was recorded within a marine protected area and deeper environments, these results highlight a potential ecological threat to local benthic ecosystems, emphasizing the urgent need f or competent authorities to implement spatiotemporal monitoring and public awareness campaigns to prevent the definitive establishment of this invader.

Plants accumulate somatic mutations during growth, and some of these mutations can spread from local cell lineages into branches, organs, or reproductive tissues. There is growing interest in these variants because they can underlie bud-sport traits in crops, contribute to within-organism somatic selection, and provide genetic variation that may be transmitted vegetatively or sexually to future generations. Recent genomic sequencing of bulk and layer-enriched plant tissues has shown that de novo somatic variants can generate complex variant allele-frequency (VAF) spectra. Interpreting these spectra requires understanding how mutations arising during mitotic cell division are filtered or amplified through shoot growth, branching, and organ formation. Because these processes interact across multiple scales, their combined effects are difficult to derive analytically. Here, we present simSOMA, a modular simulator that links rooted plant topologies to explicit cell-lineage dynamics. simSOMA models somatic mutation accumulation during stem-cell self-renewal in the shoot apical meristem, clonal expansion from the stem-cell niche to the meristem periphery, branch founding, and organ formation. Applying simSOMA across diverse growth scenarios revealed how individual processes can be isolated, varied, and combined to assess their effects on organ-level VAF spectra and among-organ variant sharing. The same simulated spectra can also be transformed to represent bulk or layer-enriched sampling and phased or unphased variant readouts, separating effects of developmental history from those introduced by tissue composition and allele counting. Because simSOMA is organized around modules with defined input-output interfaces, individual developmental components can be replaced or extended as new empirical information becomes available. This makes simSOMA a flexible tool for testing alternative models of somatic mosaicism in plants and for guiding the design and interpretation of VAF-based sequencing studies. The simulator is available at https://github.com/jlab-code/simSOMA.

Early, precise, and non-destructive stress detection is essential for maintaining crop productivity, particularly in high-density plant growth systems like controlled environment agriculture (CEA), where manual monitoring is often impractical. Using plant motion as a proxy for growth and plant health, we demonstrate a method for early, non-invasive stress detection through quantitative leaf-movement analysis in lettuce and five other CEA relevant crops. Leaf-movement dynamics under stress were imaged with a low-cost, scalable Raspberry Pi imaging setup and quantified using a repurposed open-source motion estimation algorithm; Tracking Rhythms in Plants (TRiP). Our system detected stress-induced changes in leaf-movement within 1 hour of stress, with the timing dependent on the nature of the stress. Sustained reductions in leaf-movement coincide with decreased biomass accumulation. This approach offers a non-invasive, rapid, scalable, and cost-effective solution for continuous crop monitoring, with potential for application in both terrestrial and space farming CEA systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/732190v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@19ee20eorg.highwire.dtl.DTLVardef@b0804org.highwire.dtl.DTLVardef@3b3fa8org.highwire.dtl.DTLVardef@1d04026_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract:C_FLOATNO Quantification of leaf-movement dynamics as a high-throughput proxy for plant physiological status, enabling early stress detection and timely intervention to mitigate yield penalties in CEA settings (image made with biorender.org). C_FIG

The article introduces a new Forest Stress Index (ISF) based on a plant hydraulic modelling approach rather than classical climatic drought indices. Unlike other index like scPDSI or SPEI, ISF is grounded in xylem embolism dynamics simulated with the mechanistic SurEau model. The goal is to better link climatic anomalies to tree physiological functioning and mortality risk. ISF is defined using a locally adapted ideotype characterized by an optimal P50 value under a reference hydraulic functioning threshold. Simulations are performed across Europe and France using multiple climate datasets. The index is robust to model parameterization choices and assumptions about plant functional traits. Results show strong spatial and temporal consistency and significant correlations with SPEI and scPDSI. However, ISF more strongly highlights extreme drought years and exhibits a more skewed distribution. Future projections under SSP5-8.5 indicate a widespread increase in hydraulic stress with strong regional contrasts. Overall, ISF provides a mechanistic and complementary drought indicator more directly linked to forest mortality processes.

O_LIHybridisation is frequently associated with plant invasions; however, its consequences for genome organisation and chromosome evolution remain poorly understood in invasive species. We investigated the extent of hybridisation in the invasive Carpobrotus edulis--acinaciformis hybrid complex and determined the cytogenomic contribution of parental species in hybrid accessions. C_LIO_LIWe combined whole-genome sequencing, population genomic analyses, genome size estimation, repeatome characterisation, chromosome counting and fluorescence in situ hybridisation to compare parental species and hybrid accessions from South Africa and the Mediterranean Basin. C_LIO_LIPopulation genomic analyses revealed widespread hybridisation and introgression, with most invasive accessions showing admixed ancestries. Pattersons D-statistic supported asymmetric allele sharing towards C. edulis. Hybrid accessions displayed genome sizes indistinguishable from C. edulis, whereas C. acinaciformis possessed significantly larger genomes. Repeatome analyses identified marked differences in repetitive DNA composition, particularly in satellite DNA abundance and chromosomal distribution. A newly identified satellite repeat (CarpoSat) showed contrasting chromosomal patterns between parental species, whereas hybrids resembled C. edulis satellite pattern. C_LIO_LIOur results demonstrate that Carpobrotus hybrid accessions are a swarm of later-generation hybrids and backcrosses showing a strong bias towards C. edulis, indicating asymmetric introgression. These findings highlight the value of integrating cytogenetic and genomic approaches to understand genome evolution in invasive hybrid complexes. C_LI

In vitro regeneration of Citrus plants is a widely used method, however, induction of adventitious roots from regenerated shoots remains a major bottleneck, limiting the recovery of healthy plants for commercial production and genomic research for crop improvement. We established an in vitro regeneration system producing profuse, healthy roots for sweet orange (Citrus sinensis cv. Benyenda) by optimising combinations and concentrations of auxins. Prior to optimising the rooting media (RTMs), we obtained a shoot regeneration rate of 90.6% from sweet orange epicotyl explants using a cytokinin, 6-benzylaminopurine (BAP). Across twelve auxin-supplemented RTMs containing different concentrations of indole-3-butyric acid (IBA) and/or 1-naphthaleneacetic acid (NAA), rooting percentages ranged from 8 - 87.5%. The combination of IBA 1.0 mg L-1 and NAA 0.1 mg L-1 promoted the best overall performance, 75 {+/-} 7.2% rooting percentage with healthy, callus-free roots ([&ge;]5 cm in length), whereas other RTMs with other auxin combinations induced callus and limited root elongation. The best-performing SRM and RTM were subsequently used for selection and recovery of transgenic sweet orange lines carrying an empty CRISPR/Cas9 construct, resulting in an 4.8% transformation efficiency. Both transgenic and non-transgenic rooted plantlets were successfully acclimatised under glasshouse conditions with a survival rate of 90%. This enhanced regeneration system overcomes rooting bottleneck and improves plant survival,enabling faster recovery of transgenic citrus lines within four months. It supports accelerated development for commercial applications and advances in citrus genetic improvement.

Background. DNA-based molecular markers underpin plant genetic diversity assessment, germplasm characterisation, and conservation prioritisation. Four marker systems dominate the field: Amplified Fragment Length polymorphisms (AFLPs), simple sequence repeats (SSRs), single nucleotide polymorphisms (SNPs), and random amplified polymorphic DNA (RAPDs). No quantitative meta-analysis had pooled their performance on the canonical diversity metrics: polymorphism information content (PIC), expected heterozygosity (He), and resolution power, across plants. Existing reviews are narrative, marker-restricted, or qualitatively conclusive of infeasibility. Methods. A PRISMA 2020-compliant systematic review (registered at the Open Science Framework) was executed. Eligible studies were within-study paired comparisons genotyping the same accession panel with at least two of {SNP, SSR, AFLP, RAPD} and reporting at least one diversity metric. Effect sizes were paired standardised mean differences (Hedges' g) computed under the Bernoulli-variance approximation. Random-effects REML meta-analysis used metafor 5.0.1 with Knapp-Hartung adjustment, leave-one-out, and r-sensitivity. Results. Fifteen within-study paired contrasts were eligible, distributed across three pools. Pool 2 (SSR vs SNP, He, k = 5) yielded a pooled Hedges' g of 0.494 (95% CI: -0.078 to 1.066, p = 0.075; I-squared = 90.2%; 95% PI [-0.82, 1.81]). SSRs exceeded SNPs on He in 4 of 5 studies; leave-one-out removal of the panel-size-asymmetric outlier raised the estimate to g = 0.644 (p = 0.025). Pool 3a (dominant-marker stratum, k = 6) yielded g = 0.419 (95% CI: -0.121 to 0.960, p = 0.103; I-squared = 56.5%); five of six contrasts showed SSR or AFLP exceeding RAPD on per-locus PIC. Pool 1 (PIC, k = 3, exploratory) gave a consistent direction (g = 0.453). All three pools point in the same direction: codominant or AFLP markers carry more per-locus information than the alternative being compared. Conclusions. SSR markers reported higher per-locus diversity than SNP and RAPD markers in plant within-study paired comparisons, mechanistically grounded in the SNP biallelic ceiling and the multi-allelic richness of SSRs. The effect attenuated or reversed in selfing/low-diversity panels and at the per-panel level when SNP panels exceeded approximately 1000 loci. RAPDs show the lowest per-locus information content of the four classes.

Crop photoperiodism models assume that flowering time is primarily controlled by daylength, yet many field observations contradict this view. We previously proposed an alternative framework integrating daily changes in sunrise and sunset times (dSR and dSS). Variety trials in Madagascar and in Argentina supported this concept: mid-late sorghum varieties from the northern hemisphere flowered late or very late when sown in November and December, consistent with the higher dSR/dSS values of the southern hemisphere summer. One Malian variety, sown monthly over six years in West Africa, exhibited high interannual variability in flowering time when sown between November and February. This revealed that up to four photoperiodic responses -- two quantitative and two qualitative, occurring at different times of the year -- may coexist within a single late photoperiod sensitive variety. All responses use only dSR and dSS cues. The qualitative responses are triggered by an internal phasic coincidence, which is set by a linear relationship between dSR and dSS at the onset of plant photoperiod sensitivity, and between dSR+dSS at panicle initiation. The research model fitted data from 28 varieties grown in Mali well. It also accurately fitted the duration to PI observed in three varieties sown at tropical and temperate latitudes. HighlightThe seasonal photoperiodic adaptation of flowering time in sorghum plants may rely on several signal transduction pathways regulated by sunrise and sunset times rather than day length.

Accurate segmentation of plant disease symptoms is essential for crop monitoring and phenotyping, yet it typically requires costly pixel-level annotations. Weakly supervised semantic segmentation (WSSS) alleviates this burden using image-level labels, but its performance depends on the quality of spatial priors such as class activation maps (CAMs). We investigate whether text-guided segmentation with the Segment Anything Model 3 (SAM3) can serve as an alternative weak supervision signal. Three pseudo-mask generation strategies are compared: (i) CAMs refined with SAM or SAM3, (ii) zero-shot text-guided SAM3, and (iii) a hybrid approach combining weak spatial cues with text prompts. The resulting pseudo-masks are used to train a DeepLabV3 model. Text guidance alone matches or outperforms conventional WSSS, achieving up to 0.46 IoU without spatial supervision and 0.61 IoU on a public dataset, although performance is sensitive to text prompt formulation. The hybrid strategy improves robustness, reaching 0.50 IoU on the primary dataset and 0.58 IoU on the additional dataset while reducing prompt sensitivity. Overall, text guidance is a promising alternative to conventional weak supervision, while hybrid approaches provide a more robust solution for plant disease segmentation.

Premise: Genome skimming (GS) is a cost-effective approach for plant phylogenomics, but its ability to recover informative datasets from different genomic compartments, particularly genome-wide SNPs, remains poorly explored in Solanum. Methods: We evaluated shallow GS for phylogenetic inference in South American prickly Solanum lineages by recovering plastid, mitochondrial, and nuclear datasets, including coding regions and genome-wide SNPs. Phylogenies were inferred using maximum-likelihood and coalescent approaches under different SNP filtering strategies. Results: GS successfully recovered complete plastomes, organellar coding regions, and large SNP datasets, but failed to consistently assemble mitochondrial genomes or recover low-copy nuclear genes. SNP-based analyses, especially from the nuclear genome, produced stable, well-supported phylogenies that were largely congruent across inference methods. In contrast, coding-region datasets, particularly from the mitochondrial genome, showed greater topological discordance, revealing cytonuclear conflict. Discussion: Our results demonstrate that shallow GS is an effective strategy for generating informative SNP datasets for phylogenetic inference in Solanum, despite limitations in recovering complete mitochondrial genomes and low-copy nuclear loci. SNP-based analyses substantially expand the phylogenetic potential of GS, providing a practical and cost-effective alternative for systematic studies.

Applications of tissue culture are critical for Cannabis sativa L. (cannabis), supporting clonal propagation, germplasm preservation, pathogen elimination, among other biotechnological applications. However, extensive genetic diversity associated with cannabis results in highly variable responses to in vitro conditioning, and no consensus basal media formulation exists to support reproducible micropropagation across genotypes. To address these limitations, a hybridized ensemble-NSGA-II approach was employed for concurrent optimization of individual media components to create a species specific, cultivar inclusive basal salt formulation for cannabis micropropagation. The resulting PHJ media represents a unique formulation that overcomes recalcitrance across a wide array of cannabis cultivars, facilitating improved growth and uniformity for the nine cultivars used in its development and validation. These results remain consistent from explant initiation through multiple rounds of subculture. The ability of PHJ to overcome genotypic recalcitrance is telling of its potential applicability with an array of plant species beyond cannabis. Additionally, robust performance both with and without plant growth regulators underscores the plausible use of PHJ for diverse applications beyond standard micropropagation. Ultimately, this cultivar-inclusive basal medium demonstrates utility for both scientific research and industrial-scale operations.