Journal of Geophysical Research: Biogeosciences

Primary production in the Southern Ocean (SO) plays a critical role in regulating the global carbon cycle, yet the physiological mechanisms governing phytoplankton responses to iron (Fe) limitation and variable light remain poorly constrained. Using a custom made incubation system that simulated natural diel solar variability, we examined the interactive effects of Fe availability, light intensity, and photoperiod (continuous vs. variable) on three ecologically important SO phytoplankton: Fragilariopsis cylindrus, Phaeocystis antarctica, and Thalassiosira antarctica. Physiological, photophysiological, and proteomic measurements revealed that Fe availability was the dominant factor regulating growth, carbon production, photosynthetic performance and protein expression across all species. Distinct acclimation strategies emerged: F. cylindrus exhibited marked trade-offs between productivity and photoprotection under Fe stress, consistent with adaptation to stable, low-light, Fe-poor environments; P. antarctica maintained growth by flexibly modulating photoprotective and photosynthetic capacity, reflecting high plasticity suited to dynamic, open-ocean conditions; and T. antarctica expressed a balanced strategy, sustaining productivity and photoprotection simultaneously, characteristic of coastal bloom formers with higher Fe demand. Dynamic light regimes produced smaller, species-specific effects, influencing chlorophyll content and carbon storage primarily in T. antarctica. Correlation and z-score analyses demonstrated that Fe-rich photosynthetic proteins co-varied with biomass production, whereas photoprotective traits clustered independently, underscoring divergent energy-allocation strategies. Together, these results reveal how SO phytoplankton partition resources between productivity and photoprotection under shifting Fe-light regimes, providing mechanistic insight into their ecological niches.

Root-associated microorganisms play a pivotal role in helping plants adapt to drought stress. However, the underlying mechanisms of the rhizospheric microbiome under limiting soil moisture remain largely unresolved. Integrating total and active microbiome analyses enables a more accurate interpretation of microbial responses to climate change-associated water stress. We assessed the effect of reduced rainfall on two wheat genotypes, drought-tolerant (DT) and drought-sensitive (DS), using rainout shelters that allowed 100%, 75%, 50%, and 25% of natural precipitation to reach the crop. At the peak of the growing season, rhizosphere samples were collected for metagenomic (MG) and metatranscriptome (MT) sequencing. In parallel, rhizosphere volatile organic compounds (VOCs) were collected and analysed. Differential expression analysis of metatranscriptomic data using metagenomic abundance as a cofactor was performed by comparing all treatments to the 100% precipitation control. Our results demonstrate that particularly oxidative stress-related transcripts intensify in DS as rainfall decreases. Transcriptomic shifts primarily involved upregulation of transcripts associated with antioxidant (catalase, superoxide dismutase), heat shock proteins (Hsp10, Hsp60, DnaK/DnaJ, GroEL, GroES), as well as microbial functions related to osmoregulation, proline and glycine betaine (PutA, PutP, OpuBB), and plant growth-promoting traits such as auxin production, phosphate solubilization. Moreover, volatile organic compound (VOC) emissions differed significantly between the control and drought treatments, with higher emissions, particularly acetates, in the DS genotype than in the DT genotype. Overall, pronounced drought-induced shifts in active microbial functions and VOC emissions indicate high sensitivity and functional plasticity of the active microbiome, whereas the total microbiome remains robust under medium drought.

Climate change is expected to alter plant populations not only through direct environmental shifts but also via changes in biotic interactions, such as with herbivores and pathogens. As plant species are also expected to differ in their responses to both climate and antagonists, plant responses to both factors are expected to be variable and species-specific. To assess whether interactive effects of climate and antagonists on plant population dynamics are common and whether the strength and direction of plant responses vary across species, we conducted a multi-year field experiment that manipulated realistic climate change and experimentally reduced insect herbivores and fungal pathogens. We measured responses of plant vital rates, such as survivorship, growth, and reproduction across six grassland species. Using Integral Projection Models (IPMs) and Life Table Response Experiments (LTREs), we quantified changes in population growth rate across experimental treatments and the contribution of each vital rate to that observed change. Two of the study species declined so drastically over the course of the experiment that demographic quantification of population growth rates was not possible. From the remaining species, Bromus erectus and Plantago lanceolata show significant interactive responses of climate and antagonist reduction on population growth rates. In contrast, Dianthus carthusianorum and Tragopogon orientalis showed limited responses to experimental treatments. Notably, our results indicate that in some species biotic interactions may amplify the effects of climate change: the presence of plant antagonists exacerbates the negative effects of the future climate treatment on plant population dynamics. Our findings highlight the complexity in predicting plant population responses to climate change and provide insights for grassland management under future environmental conditions.

Biological ethanol production is important for the circular carbon economy and makes up 73% of the U.S. biological fuels market. Previously, we produced ethanol by reversing methanogenesis and capturing methane by cloning methyl-coenzyme M reductase (Mcr) from an unculturable population of anaerobic methanotrophic archaea; this process was predicated on the generation of the intermediate acetate and its conversion by the methanogenic host to ethanol. Moreover, methanogens are generally thought to be detrimental for converting acetate to ethanol and are usually intentionally inhibited. Here, we demonstrate that direct growth on acetate as the sole carbon and energy source by the methanogen Methanosarcina acetivorans C2A results in 40% of the metabolized acetate becoming ethanol and that there is 430% more ethanol produced, compared to growth on methane via Mcr. In addition, we found growth on methanol results primarily in methane generation and low levels of ethanol. Therefore, acetate may be readily converted by the methanogen M. acetivorans to ethanol at high yields.

Transgenerational plasticity can shape plant phenotype and influence plant response to environmental changes in interaction with the current conditions. While how past stress interact with either current optimal or stress conditions is increasingly documented within a single plant, transgenerational plasticity remains particularly poorly understood especially at the metabolome level. In our study, we investigated whether heat stress induces transgenerational metabolic and phenotypic modifications along two successive clonal ramet generations of the sub-Antarctic aquatic plant Limosella australis. We performed untargeted metabolomic approaches and measured morphologic and performance traits, to assess both transgenerational plasticity of the metabolome and the phenotype. We found that heat stress remodelled the metabolic profile and influenced the foraging strategy of our clonal plant, and that some of these metabolic changes persisted into the first clonal generation. This one therefore adopted an intermediate growth strategy, even though culture conditions were optimal. By comparing differentially accumulated features between daughter ramets from heat stressed mother ramets and from unstressed mother ramets, we identified common and specific metabolites accumulation to heat stress response, belonging to diverse compound families. However, we did not observe any adaptative advantage and any metabolic imprint during another heat stress applied on the second clonal generation. This work provides especially new clues into how plant metabolome integrates and transfers previous stressed clonal generation's information.

Premise: Rapid and accurate plant species identification is a critical challenge exacerbated by the taxonomic impediment. Although portable near-infrared (Micro NIR) spectroscopy represents a promising solution, the current absence of standardized protocols and a fundamental understanding of how critical acquisition and analysis parameters influence accuracy remain significant barriers. This study focused on the systematic optimization and validation of a comprehensive workflow designed to maximize the reliability of plant identification using this technology. To ensure methodological robustness across diverse foliar matrices, four vascular plant species were strategically selected as a representative test set to encompass morphological extremes, including significant variations in leaf thickness, pubescence, and surface texture. Methods: Using a portable spectrometer on herbarium specimens (exsiccate) of four vascular plant species, we systematically tested five spectral backgrounds, seven pre-processing methods, and four classification models. Subsequently, we optimized the number of spectral readings and evaluated the influence of the leaf scanning surface (adaxial vs. abaxial) on model accuracy. Results: The highest-performing combination was a Shiny Aluminum background, Second Derivative pre-processing, and a Random Forest model, which achieved a mean cross-validated accuracy of 99%. An average of just three spectral readings from the adaxial (upper) leaf face was sufficient to saturate model performance, proving statistically superior to other approaches (p < 0.001). Discussion: This study establishes a validated, high-accuracy protocol for plant species identification from herbarium specimens using portable NIR, offering a powerful tool for biodiversity studies. Direct applicability to fresh plants in the field requires future validation to account for the spectral influence of moisture variability.

Microbial succession can be used to estimate the postmortem interval (PMI); however, the impact of spatial variability within the cadaver decomposition island (CDI) is not well understood. This study examined spatial variation in necrobiome communities where soil samples were collected over time and across spatial locations from the CDIs of two human body donors. Microbial communities were characterized using 16S rRNA sequencing and statistical modelling of variation and PMI were conducted. Necrobiome community metrics showed no significant differences across anatomical sampling sites within the CDI at a single timepoint. Temporal modelling identified 11 taxa with significant relationships to PMI in one donor, with spatial sampling having a minimal impact on the PMI relationships. Non-linear approaches also identified taxa with likely PMI signals in the second donor. These findings demonstrate that opportunistic sampling can capture robust linear and non-linear PMI signals in later decomposition stages.

Plant-microbe interactions in the rhizosphere are central to nutrient cycling and ecosystem functioning. Sedimentary ancient DNA (sedaDNA) is a promising yet underexplored tool for reconstructing past microbial communities and investigating ecological interactions among plants, animals, and microorganisms. Here, we reanalyse the previously published Kap Kobenhavn Formation (Northern Greenland) sedaDNA dataset to move beyond taxonomic ecosystem reconstruction and test whether ancient sediments preserve structured, rhizosphere-compatible plant-microbe association signals. Our results show that this ancient boreal ecosystem hosted several rhizosphere-associated taxa, comparable to those in modern boreal soils. Several bacterial genera co-occurred repeatedly with specific plant families, forming a rhizosphere-like taxonomic core with predicted plant-growth-promoting traits related to nutrient acquisition, colonisation, and stress tolerance. Although sedaDNA co-occurrence cannot demonstrate direct symbiosis, the consistency of taxonomic, network, and functional signals suggests that ancient sediments preserve interconnected ecological structure. Our findings extend sedaDNA-based ecosystem reconstruction beyond taxonomy and provide a possibility for investigating plant-microbe association signals in deep time.

Global climate change has increased the frequency and intensity of drought events, making it urgent to understand how native species respond to water deficit (WD). In biodiverse environments such as tropical forests, simple methods are needed to study multiple species simultaneously. This can help predict how natural environments will respond to climate change and guide the strategic selection of drought-resistant species for reforestation. This study aimed to: (1) adapt an existing simple and inexpensive method to apply a controlled WD on tree seedlings from tropical species commonly produced in nurseries for restoration projects, suitable for greenhouse experiments; and (2) evaluate the effectiveness of this method in generating ecophysiological responses to WD that allow the estimation of species' drought resistance. Ten native tree species from the Semideciduous Seasonal Forest (SSF), a phytophysiognomy of the Atlantic Forest, were selected. An existing method was adapted to implement capillary irrigation, in which the bases of the seedling tubes were placed in floral foam blocks positioned inside 15 L plastic containers filled with water. A gradual and severe WD was applied to five seedlings of each species by removing all water from the containers, leaving only the water retained in the saturated floral foam available for plant uptake. The remaining seedlings were maintained well-watered (containers full and foam saturated) as the control group. Stomatal conductance (gs) was measured daily for all seedlings until they reached 50% or less of their initial gs (igs); at this point, stem water potential ({Psi}w) was measured. Both gs and {Psi}w differed significantly among treatments and species (p < 0.01). Ficus guaranitica and Heliocarpus popayanensis were the only species that did not show significant {Psi}w differences between treatments, indicating higher drought resistance. In contrast, Campomanesia xanthocarpa and Eugenia uniflora had the lowest {Psi}w values under WD, suggesting lower drought resistance. The remaining species were distributed along a gradient of responses to WD. Additionally, no correlation was found between {Psi}w and gs at 50% igs in the WD group (rho = 0.16, p = 0.26). The method proved effective in inducing controlled WD and generating measurable ecophysiological responses, offering a useful tool for screening native species for drought resistance.

Tropical dry evergreen forests (TDEFs) are a unique and highly threatened forest type of the dry tropics. Their restoration could be strengthened if native species demonstrate carbon sequestration comparable to widely used non-native trees. We assessed biodiversity and carbon sequestration in a restored TDEF in India, developed over 50 years from a largely barren landscape. The site now supports high woody-plant diversity, with 91 native species across 34 families. Aboveground biomass (AGB) averaged 66.91 +/- 41.2 Mg/ha comparable to seasonally dry tropical forests globally. Although native species were planted more recently and are shorter than non-natives, they contributed 23.86 +/- 23.4 Mg/ha to AGB and show potential for future increases in basal area. Given their comparable wood densities and capacity to attain similar heights, native species are predicted to sequester carbon at levels similar to non-natives in the long term. AGB was unrelated to species diversity. Overall, native TDEF species can achieve carbon storage while maintaining ecological integrity.

1. Stomata and leaf traits are key regulators of plant water use efficiency and are expected to have changed in response to rising atmospheric CO2 concentrations and climate warming over the past centuries. However, long-term data documenting such changes are rare. 2. We leveraged herbarium collections to track changes in stomatal characteristics and leaf traits in 656 individuals of invasive Japanese knotweed and its hybrid Bohemian knotweed collected across their European range and spanning 160 years of invasive spread. 3. We found that several functional traits including stomatal density and maximum anatomical stomatal conductance did not show significant changes over time but that plants adjusted their stomatal size and shape over time, and that these changes were associated with increased atmospheric CO2 levels. Interestingly, Reynoutria japonica showed increases in stomatal size and stomatal elongation, while the hybrid R. x bohemica showed a reduction in stomatal size. Traits also varied systematically with climates of origin. Plants from warmer origins with higher evaporative demands during the growing season had thicker leaves, lower SLA, smaller stomata and higher stomatal density, indicating more conservative water-use strategies. Stomatal density and gas exchange capacity co-varied with leaf structural traits, and there was a trade-off between stomatal size and number. Overall, fast leaf economic traits were associated with slow physiological traits. 4. Our results suggest that stomatal anatomical plasticity may enhance climate resilience by maintaining a stable maximum gas exchange capacity across environmental gradients. Herbarium collections provide a unique resource for reconstructing plant responses to historical environmental changes and understanding intraspecific trait variation.

Nutrient-rich food-processing wastewaters represent valuable yet under-utilised side streams for sustainable protein production in the form of microbial biomass. Here we present an integrated dual-loop bioprocess that converts soybean-processing wastewater into microbial single-cell protein (SCP) while achieving substantial nutrient removal and product refinement. In the first loop, previously enriched microbial consortia were inoculated and cultivated in four parallel sequencing batch reactors (SBRs) for 44days at a hydraulic retention time (HRT) of 3days. This bioprocess configuration demonstrated features that support future scale-up while maintaining process stability, achieving a protein content of 33.3{+/-}3.2%, doubling the protein yield (15.32{+/-}3.49g dry weight per g soluble TKN) and quadrupling the production rate (0.29{+/-}0.06g dry weight L-1 d-1) compared to operating reactors without inoculation (HRT: 7.2days). Effluent treatment was stable, with 84% carbon and 78% nitrogen removal efficiencies, demonstrating efficient nutrient recovery. The SCP biomass was enriched in functional taxa, including Acidipropionibacterium, Lactococcus, Megasphaera, and Azospirillum, suggesting that reactor conditions and inoculum selection promoted a stable, protein-productive microbial community with potential probiotic benefits. In the second loop, bioreactor effluent was reused as aqueous matrix for heat treatment (60{degrees}C) of the SCP biomass, reducing the RNA content from 8.6% to 2.6%, with a 39% biomass loss accompanied by a 30% increase in total amino acid concentration. Hence, our valorisation approach integrates microbial biomass production, effluent reuse, and product refinement within a circular framework. The system provides a resource-efficient pathway for converting food-sector side streams into high-quality microbial community-based SCP, highlighting its potential scalability for sustainable nutrient and water management.

Natural products are central mediators of microbial interactions. However, once released into the environment, they also become available for neighboring microorganisms capable of degrading and modifying them through biotransformation. These biotransformations may fundamentally reshape metabolomes and influence community behavior, yet our understanding of these processes remains limited. Ribosomally synthesized peptides are particularly compelling in this context because their structural complexity and potent antimicrobial activity coexist with the potential to yield essential nutrients and reduced bioactivity through biotransformation. Identifying the pathways underlying these biotransformations is essential for understanding mechanisms that support microbial coexistence and nutrient recycling in soil microbiomes. Here, we used nisin as a model peptide to investigate biotransformation by soil bacteria. Selective isolation under nisin-rich, carbon-limited conditions yielded two Gram-negative isolates, Burkholderia stabilis and Pseudomonas fragi. Using growth assays and liquid chromatography-mass spectrometry, we found that both isolates grow in the presence of nisin while biotransforming and depleting the peptide. Burkholderia stabilis completely converted nisin through sequential cleavage of the C-terminus, hinge region and lanthionine ring C, whereas Pseudomonas fragi showed more limited processing restricted to the C-terminal region. Although these biotransformations dismantled structural features required for nisins antimicrobial activity, the intrinsic resistance of both isolates suggests a role beyond detoxification. We further detected nisin biosynthetic genes in the source environment, supporting nisins ecological relevance and suggesting that these bacteria may participate in its turnover in soil. Together, these findings reveal extensive microbial processing of nisin and support a role for antimicrobial peptide recycling in soil microbiomes.

The emergence of vascular plants on land is one of evolution greatest triumphs. This success was contingent on the capacity of roots and their symbionts to acquire resources from exposed geology. However, how rock chemistry shapes plant root architectural strategies, and their return on investment during early ecosystem colonization remains poorly understood. Here we use a two-year mesocosm experiment with Bouteloua dactyloides grass and an arbuscular mycorrhizal symbiont, grown on four mineral substrates of contrasting composition, to show that rock geochemistry predictably determines root topological strategy, from herringbone architecture on nutrient-poor granite to dichotomous-like branching on nutrient-rich basalt. Substrate identity governed investment allocation between root complexity and biomass, with plants consolidating existing transport pathways as weathering-derived nutrients subsided. Traits associated with exploratory effort were generally decoupled from those related to biomass buildup. In basalt and rhyolite plants preferentially invested in complexity, generating the largest numbers of prospective tips for mining and biomass buildup; in granite, plants chose a surviving strategy, limiting branching to preserve biomass; while in schist, plants balanced biomass with complexity, extending growth on low investment, which increased tissue density. Surprisingly, mycorrhizal fungi did not alter the whole root system size, but reallocated investment between specific root orders, discouraging investment in embryonic roots in some substrates, and stimulating lateral expansion of the rooting system in others. This extends the functional balance mechanism from plant to the plant-fungus system. The extensive phenotypic plasticity of the root-mycorrhiza system shown here provides an evolutionary space for natural selection, which must have played a crucial role in the success of plants on land in the past, and is crucial for understanding plant ecological dynamics today.

Biodiversity is predicted to stabilize ecosystems if species have different environmental responses. How this response diversity is shaped by ecological and evolutionary processes remains poorly understood. We determine the drivers of thermal response diversity of 16 Swiss peri-alpine lake-fish communities. We report the first evidence that evolutionary diversification of lineages through adaptive radiation can increase the response diversity of an ecosystem. In-situ diversification increases response diversity in the cold-deep lake environment, but non-endemic and non-native species contributed only weakly to response diversity. The loss of endemic species during historical anthropogenic eutrophication led to a negative legacy on present thermal response diversity in cold and deep lake strata. Overall, the interplay of evolutionary diversification, ecological assembly and anthropogenic impacts drives variation in response diversity. Conserving and restoring processes that generate diversity may help maintain ecosystem stability beyond the Anthropocene.

Microbial fuel cells (MFCs) technology offers sustainable electricity production. Current research largely focuses on few select model organisms, therefore the true prevalence of exoelectrogenesis amongst bacteria remaining largely unknown. We present a broad-scale survey of monomicrobial electricity production among environmental bacterial isolates inoculated in MFCs, using model organism Shewanella oneidensis MR-1 as a benchmark. Of the assessed taxa, 11-22% displayed exoelectrogenic activity, exceeding current predictions and identifying a further three novel exoelectrogenic species. Phylogenetic analysis based on the 16S sequences enabled the evolutionary relationship between isolates to be visualised, revealing that exoelectrogenesis is non-randomly distributed and phylogenetically conserved. Polarisation studies were implemented, revealing that numerous electron transfer mechanism were being utilised to perform exoelectrogenesis. The results of this study imply that bacterial electricity production is more widespread amongst culturable bacteria than previously estimated, with implications for bioprospecting novel exoelectrogens and predicting electrogenic activity in diverse microbial communities.

Chytrids are unicellular fungi that infect and degrade phytoplankton as parasites or saprotrophs. They impact not only food availability and quality in surface waters but also carbon cycling and sequestration. So far, their ecological significance has mostly been investigated for freshwater environments, whereas observations for marine environments are scarce -- even though chytrids can be highly abundant there, too (as shown for the Arctic Ocean). To test the chytrids' potential to control phytoplankton dynamics in the Arctic Ocean, we analysed metabarcoding and photosynthetic pigment data from two expeditions, Tara Polar Circle and MOSAiC; the latter providing a dense sampling transect across one year from the under-ice water column and sea ice samples. The phytoplankton communities of both environments were dominated by diatoms, with strong seasonal effects indicating blooms in the water column. Chytrids dominated fungal communities in both environments and revealed a strong cryo-pelagic coupling. They were especially abundant during the sea ice melt in water samples and in ice-associated (sympagic) samples, where they represented >2% and up to 61%, respectively, of all combined reads assigned to chytrids or phytoplankton. Co-occurrences of the two most abundant chytrid taxa with some of the most abundant diatom taxa and niche differentiation from other potential diatom parasites are consistent with the chytrids' critical role in controlling diatom blooms, especially in sympagic habitats.

While mutualistic symbioses with nitrogen-fixing bacteria enable plants to access fixed nitrogen, they also require substantial carbon investment. Under carbon limitation, such as shading, shifts in biomass allocation can decouple symbiotic investment from leaf and root growth, potentially compromising plant nitrogen status. Because shading shifts biomass allocation toward light acquisition, it could influence nitrogen fixing symbiosis in two opposing ways. If nodulation remains coupled to leaves rather than roots, nitrogen status should be maintained despite reduced root growth. Alternatively, if root growth constrains nodulation, nitrogen status should decline. We tested these hypotheses by manipulating light availability (full sunlight vs. 50% shade) and quantifying biomass allocation and symbiotic nodulation. Under shading, plants allocated proportionally more biomass to shoots than to roots and invested less biomass in root nodules. Relationships between nodulation and leaf or root biomass differed between treatments but converged with increasing plant size, although shaded plants never attained the root biomass observed in full sunlight. Leaf nitrogen concentration was maintained under shading because nodulation remained coupled to leaf investment despite reduced root allocation. These findings highlight that, under carbon limitation, maintaining leaf and nodule coupling enables plants to reduce nodule investment without compromising the nitrogen benefits of symbiosis.

Background: Human activities such as mining generally lead to increased heavy metal concentrations in the environment. While traditional remediation techniques are often costly, the use of fungi as bioremediators, known as mycoremediation, is increasingly gaining attention as a sustainable approach for removal of heavy metals. Here, we evaluated heavy metal levels inside the Kiirunavaara iron ore mine in Northern Sweden and analysed fungal responses to various metal concentrations by comparing growth and metal uptake in mine-derived isolates and closely related control isolates. Results: Sediments inside the mine were enriched in heavy metals compared to those from the outlet of the mine to natural lakes. Six Fusarium isolates were recovered from contaminated mining environments: five isolates from inside the mine were identified as Fusarium oxysporum, and one isolate from the outlet was identified as Fusarium tricinctum. Isolates from the mine and outlet showed overall higher survival and biomass production in presence of copper, iron, and zinc across a range of concentrations (up to 1000 mg/L) compared to control isolates. At the same time, these isolates often exhibited reduced relative metal uptake. As a result, mycoremediation potential, assessed as total uptake in the grown mycelium, was isolate-dependent. Conclusions: Based on these results, we conclude that Fusarium isolates from the Kiirunavaara mine show increased growth in media enriched with heavy metals compared to closely related control isolates. We additionally show that mycoremediation potential is not necessarily associated with environmental origin. Instead, mycoremediation potential should be evaluated on a case-by-case basis for each isolate and based on specific needs for mycoremediation.

While whole genome sequencing captures millions of single nucleotide polymorphisms (SNPs) and hyperspectral imaging (HSI) enables non destructive plant phenotyping, integrating these modalities to link genotype to phenotype remains challenging due to their high dimensionality and non linearity. This study presents DeepPheno a deep learning framework that predicts SNP genotypes from HSI data, using model predictability as a proxy for genotype phenotype association. HSI data were acquired from 194 lettuce genotypes under field conditions. HSI data patches (20 x 20 pixels x 224 spectral bands) were used to train a hybrid CNN to predict the variant of a specific SNP. The framework was validated on SNPs with known phenotypic effects (anthocyanin, leaf serration, pale pigmentation), achieving high predictive performance (AUC ranging from 0.806 to 0.935), whereas models trained on randomly shuffled labels performed at chance (mean AUC {approx} 0.51). Extending the workflow to 50 randomly selected putatively neutral SNPs, most yielded low predictability, but two showed high performance (AUC > 0.76), suggesting uncharacterized genotype phenotype links. Explainable AI, including SHAP and Grad CAM, identified relevant spectral and spatial features driving these predictions, particularly the green and red edge wavelengths associated with pigment dynamics and leaf structure. These results establish a framework for understanding complex genotype phenotype interactions in plants and extracting these links from HSI data without predefining the exact trait values. It provides an avenue for high throughput trait discovery and description and extends the integration of image based phenomics with plant genetics.