The study utilized controlled soil column experiments to explore the impact of various biochar application rates under two distinct fertilization regimes: conventional chemical fertilizers and the innovative biogas slurry strategy. By meticulously tracking greenhouse gas emissions, such as carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄), and examining the associated shifts in soil bacterial communities, the researchers provided a detailed understanding of how biochar functions in different agricultural contexts.

Under the conventional fertilization system featuring chemical fertilizers, the incorporation of biochar consistently led to a significant reduction in CO₂ emissions, with reductions approximating one-third of the baseline emissions. Surprisingly, this reduction came at a cost; the use of biochar also correlated with increased emissions of the potent greenhouse gases CH₄ and N₂O. In stark contrast, when the research team opted for the biogas slurry fertilization approach, the observed outcomes were markedly different. CO₂ emissions fell by about 15%, while N₂O emissions experienced a staggering decline of more than 70%. This presents a complex tradeoff—while the biogas slurry strategy proved effective in curtailing specific greenhouse gas emissions, it caused a notable surge in CH₄ emissions.

The intricate dynamics of biochar efficacy became increasingly evident as the application rate of biochar varied. Researchers discovered that higher doses of biochar—specifically 4% and 6% additions—enhanced the emission reduction benefits provided by biogas slurry. Conversely, a lower application of 2% biochar seemed to reverse these benefits, underlining the importance of optimizing biochar more critically alongside other fertilization practices. This nuanced understanding encourages a more tailored approach to biochar application, moving away from the notion of a singular solution.

At the heart of this research are the soil bacterial sub-communities, critical players in the cycling of carbon and nitrogen within soils. The team observed that the addition of biogas slurry, combined with biochar application, enriched certain rare microbial sub-groups that played an unexpectedly vital role in regulating greenhouse gas emissions. These microbes influenced the metabolism of carbon and nitrogen, revealing what the researchers termed a “priority effect”—where specific bacterial groups lead the charge in determining greenhouse gas emissions. This discovery underscores the importance of a microbiome-focused perspective in agricultural practices aimed at mitigating climate change.

The implications of these findings extend beyond scientific curiosity; they provide actionable insights for agricultural producers striving for dual objectives: enhancing soil health and reducing greenhouse gas emissions. The study suggests that merely adding biochar to soils is insufficient as a comprehensive strategy for climate change mitigation. Instead, successful results are contingent upon aligning application rates of biochar with specific local practices concerning water management and fertilizer use. By thoughtfully integrating biochar with organic fertilizers like biogas slurry, farmers may not only improve soil health but also contribute to global carbon sequestration efforts.

As the agricultural sector faces increasing pressure to address climate change, this research offers critical guidance for crafting integrated soil management strategies. The authors argue that with meticulous optimization of biochar and biogas slurry combinations, there exists promising potential for agriculture to not only adapt but also proactively engage in climate change mitigation while simultaneously achieving sustainable food production goals.

Dr. Jiandong Wang, the corresponding study author, emphasizes the importance of these findings, stating, “Our results show that the effectiveness of biochar in reducing greenhouse gas emissions depends strongly on the fertilization strategy used.” This research serves as a beacon of hope, reinforcing that innovation in agricultural practices can lead to progressive results in the fight against climate change. As society seeks effective measures to combat environmental degradation, the intersection of biochar, microbial communities, and organic fertilizers offers a compelling avenue for future exploration and implementation.

Moreover, Dr. Xurong Mei, one of the co-authors of the study, highlights the significance of these insights by stating, “This research provides new scientific evidence for designing integrated soil management strategies.” This study is not merely an academic exercise but a significant leap towards developing practical solutions that can support farming communities and the global environment.

By supporting soil organisms, changing application strategies, and embracing innovative solutions, farmers are positioned to take an active role in addressing one of the most pressing challenges of our time—climate change. As more industry professionals, researchers, and policy-makers recognize the potential of combining biochar with biogas slurry, the opportunity to achieve ecological benefits while fostering agricultural productivity may soon come within reach. This understanding can catalyze efforts toward more resilient agricultural practices, creating a world where farming contributes positively to both food security and the environment.

As research in this domain continues to advance, it will be essential to keep close watch on the interactions between soil amendments and microbial communities. The exploration of biochar’s role in sustainable farming practices, particularly when paired with organic fertilizers, may quite possibly define the trajectory of future agricultural innovations.

In summary, the complex relationship between biochar, soil health, and greenhouse gas emissions necessitates deeper exploration. By embracing the insights retrieved from this research, the agricultural industry stands to gain invaluable knowledge that will not only enhance soil management practices but will also aid in the global journey toward achieving sustainable food production models that are environmentally responsive and forward-thinking.

Subject of Research:
Agricultural practices involving biochar and biogas slurry implications on greenhouse gas emissions.

Article Title:
Biogas slurry strategy reshapes biochar-mediated greenhouse gas emissions via soil bacterial sub-communities.

News Publication Date:
18-Aug-2025

Web References:
(Please insert corresponding URLs if available)

References:
Liang, X., Wen, Y., Wang, C. et al. Biogas slurry strategy reshapes biochar-mediated greenhouse gas emissions via soil bacterial sub-communities. Biochar 7, 92 (2025).

Image Credits:
Xiaoyang Liang, Yongxing Wen, Chuanjuan Wang, Haitao Wang, Jiandong Wang & Xurong Mei.

Keywords

Biochar, biogas slurry, greenhouse gas emissions, soil microbial communities, carbon sequestration, sustainable agriculture, climate change mitigation, soil management strategies, microbial ecology, environmental science, agricultural practices, soil health.

Southwestern China, characterized by its unique geological formations and intensive agricultural activities, provides a compelling case study for examining the complex interactions among groundwater quality, irrigation demands, and environmental factors. The basin studied is emblematic of many regions where farmers depend heavily on groundwater extraction for irrigation, often without comprehensive monitoring or predictive assessments. This gap in knowledge poses significant risks, as declining water quality can jeopardize crop yields, soil health, and by extension, the livelihoods of rural communities.

The study meticulously collected and analyzed groundwater samples across multiple locations within the basin, employing state-of-the-art hydrochemical assessment techniques. Parameters such as pH, salinity, concentrations of nitrates, heavy metals, and other critical indicators were systematically evaluated. The result is a robust dataset that captures spatial and temporal variations of groundwater quality, reflecting the influences of natural geochemical processes intertwined with human-induced changes like fertilizer runoff and industrial pollutants.

One of the pivotal findings highlights how seasonal fluctuations and irrigation intensities correlate with sharp variations in groundwater quality. During dry seasons, water extraction rates spike, exacerbating the concentration of dissolved solids and contaminants. Conversely, wet seasons contribute to dilution but also lead to increased leaching of agricultural chemicals into aquifers. This seasonal dynamic suggests that irrigation scheduling and management must integrate adaptive strategies to mitigate episodes of water quality degradation.

Building upon this extensive empirical groundwork, the researchers developed a sophisticated prediction model that synthesizes hydrogeological data with land use, climatic variables, and farming practices. By applying machine learning algorithms and geostatistical methods, the model forecasts groundwater quality trends with remarkable accuracy. This predictive capacity equips stakeholders with a powerful tool to anticipate adverse changes and design interventions before water quality reaches thresholds detrimental to agriculture or public health.

The model’s application transcends mere prediction; it also serves policy makers and water resource managers aiming to balance water usage with quality preservation. For instance, the model can identify zones highly vulnerable to contamination or salinization, guiding targeted remediation efforts or modifications in irrigation techniques. The integration of this model into water governance frameworks could mark a transformative step toward holistic, data-driven management of agrohydrological systems.

Technically, the model incorporates multivariate regression and ensemble learning methods, enhanced by the inclusion of remote sensing data and climate projections. This multi-pronged approach ensures resilience in predictions, accounting for uncertainties inherent in environmental data. Moreover, the study explores model validation exercises, comparing predicted values against independent water quality observations, confirming the system’s reliability.

An interdisciplinary angle emerges as the research links groundwater quality dynamics not only to irrigation practices but also to socio-economic factors. For farming communities reliant on groundwater, the degradation in quality translates into greater economic burdens, given the need for water treatment or soil amendments. The study thus frames groundwater quality management as a social imperative, reinforcing the necessity for integrated approaches that marry technical solutions with community engagement.

Furthermore, the research shines a light on emerging contaminants and their potential impact on irrigation water safety. While traditional parameters receive significant attention, the inclusion of trace organic compounds and heavy metals in the analysis points to evolving environmental challenges. The nuanced understanding of these contaminants’ behavior in the groundwater system is crucial for anticipating long-term effects on crop quality and human health through food chains.

Notably, the study underscores the interconnectivity between groundwater quality and broader environmental health. Poor water quality can accelerate soil degradation, reduce agricultural productivity, and ultimately contribute to biodiversity loss within the basin. These cascading effects emphasize the need for sustainable water management policies that also consider ecological preservation — a theme increasingly relevant amid global climate change and intensified land use.

The methodological rigor and innovative modeling framework establish a benchmark for similar studies worldwide. By openly sharing datasets and model architectures, the authors invite collaboration and adaptation of their tools to diverse agroecological contexts. This openness facilitates the development of globally applicable solutions, crucial for regions facing rapid agricultural expansion and environmental pressures.

From a forward-looking perspective, the research hints at integrating this groundwater quality prediction model with smart irrigation technologies and IoT-based monitoring systems. Such integration could enable real-time water quality assessments and automated adjustment of irrigation parameters, optimizing water use efficiency while safeguarding resource quality. This vision aligns with the global move toward precision agriculture and sustainable resource management.

Importantly, the study also factors in policy and institutional dimensions influencing groundwater quality. Regulatory frameworks, enforcement mechanisms, and community awareness levels significantly affect how groundwater resources are exploited and conserved. The findings advocate for enhancing these governance structures, informed by scientific evidence generated through such detailed analyses and predictive modeling.

The timing of this research is particularly poignant given accelerating demands on freshwater resources worldwide. As climate variability intensifies hydrological uncertainties, understanding and predicting groundwater quality become essential for food security and environmental resilience. Southwestern China’s experience thus serves as a microcosm for global challenges and as a testing ground for innovative water management approaches.

In summation, the comprehensive characterization and predictive modeling of groundwater irrigation water quality crafted by this study open new horizons in sustainable agriculture and water resource management. By weaving together detailed hydrochemical assessments, advanced data analytics, socio-economic dimensions, and policy considerations, it presents an integrated framework poised to inform decision-making processes at multiple levels.

The implications extend beyond the boundaries of Southwestern China, offering transferable insights and tools that can be customized and scaled globally. As water scarcity and pollution pressures mount, such research embodies the essential scientific advances needed to safeguard water resources, secure agricultural productivity, and ultimately support human well-being in an increasingly constrained planet.

Subject of Research: Characteristics and prediction of groundwater irrigation water quality in an agricultural basin

Article Title: Characteristics and prediction model of groundwater irrigation water quality in a typical agricultural basin, Southwestern China

Article References:
Liu, W., Xie, Z., Yang, S. et al. Characteristics and prediction model of groundwater irrigation water quality in a typical agricultural basin, Southwestern China. Environ Earth Sci 84, 371 (2025). https://doi.org/10.1007/s12665-025-12379-x

Image Credits: AI Generated

Crop diversity has long been understood as the bedrock of agricultural sustainability. Genetic variation within crops forms the raw material from which breeders select traits necessary for adaptation—traits such as drought tolerance, heat resistance, and pest resilience. However, possessing genetic variation alone does not guarantee successful adaptation. The accessibility of these genetic resources, coupled with the ability to identify which genetic combinations will thrive under future climatic conditions, is equally vital. This dual emphasis on diversity and accessibility frames a novel methodology applied to sorghum, leveraging genomic technologies combined with environmental data to predict adaptive potential.

This study aggregates a formidable dataset comprising 1,937 genotyped and georeferenced sorghum accessions, publicly available and drawn from global genebanks. Each accession—a unique genetic sample—is mapped precisely to its native geographic origin, enabling researchers to overlay environmental variables on the genetic data. By integrating cutting-edge environmental genomic selection techniques, the researchers generated estimated adaptive values for sorghum genomes, effectively scoring each sample for its expected resilience to future climate scenarios. This genomic adaptive capacity score is a pioneering metric that quantifies how well each accession is genetically equipped to handle projected environmental stressors.

Complementing this genetic perspective, the research team devised a future climate resilience score for each accession, considering not just the raw genetic potential but also ecological and social variables. This comprehensive scoring framework allows identification of high-performing candidate parents—essentially the genomic elites—from which new, climate-hardened sorghum varieties can be developed. The implications are enormous: breeders can more precisely select parent lines without resorting to cumbersome trial-and-error methods, dramatically accelerating breeding cycles and reducing costs.

Notably, the study highlights the spatial dimension of adaptive potential. Certain geographies emerge as hotspots, harboring particularly promising genotypes that may serve as keystones for regional or even global breeding efforts. Conversely, the analysis also identifies regions where sorghum populations are especially vulnerable, lacking the diverse genetic resources needed to adapt effectively. These at-risk areas represent urgent conservation priorities, as their continued loss of genetic diversity could translate into diminishing yields and food insecurity for dependent populations.

A key innovation underpinning this research is the use of environmental genomic selection—a technique that integrates large-scale climate data with genomic profiles to predict phenotype performance under future conditions. This method moves beyond traditional breeding paradigms, which often rely on phenotypic selection observed under present-day environments. By contrast, genomic estimated adaptive values anticipate how certain alleles will perform as climates shift, offering a proactive blueprint rather than a retrospective analysis. This predictive capacity is transformative for climate-resilient crop development.

Moreover, by emphasizing publicly available genebank accessions, the study underscores the vital role of open scientific resources in addressing global challenges. Genebanks—repositories of plant genetic material—have sometimes struggled with issues of sample accessibility, documentation, and utilization. This research demonstrates that when genetic resources are adequately characterized and integrated with environmental data, their value is magnified exponentially. In essence, unlocking genetic potential is as much a social and logistical challenge as a biological one.

The implications of this work extend far beyond sorghum. The methodology provides a scalable framework applicable to myriad crops vital to food security, especially those grown predominantly by smallholder farmers in vulnerable regions. By prioritizing germplasm with validated adaptive potential, breeding programs can streamline efforts to develop varieties that will remain productive under temperature increases, altered precipitation patterns, and emerging pests and diseases. This level of strategic foresight is indispensable for meeting the dual goals of feeding a growing population and conserving biodiversity.

Intriguingly, the study reveals that some of the most genetically valuable sorghum lines for future climates are concentrated in underexplored regions, highlighting gaps in current genebank collections and the need for expanded collection missions. This finding advocates for increased investment in germplasm acquisition, particularly from areas predicted to experience pronounced climatic shifts. Simultaneously, it calls attention to the delicate social fabric surrounding traditional farming communities, as ensuring equitable benefit-sharing and access to improved varieties remains a complex challenge.

In practical breeding terms, the identification of “best potential parents” provides a catalog for immediate experimental crosses, allowing breeders to stack favorable alleles related to drought tolerance, heat resistance, and yield stability more efficiently. Such precision breeding will likely reduce the time from conception to variety release, thereby offering a timely response to rapidly evolving climate threats. Moreover, the integration of genomic data expedites the evaluation process by enabling marker-assisted selection and genomic prediction models, both of which have revolutionized crop improvement in recent decades.

The study’s emphasis on both global and national scales underscores the multi-tiered nature of crop adaptation. While global genetic resources provide a vast reservoir of adaptive potential, effective deployment necessitates localized strategies that respect the unique ecological, socio-economic, and cultural contexts of farming communities. This nuanced understanding ensures that breeding outcomes are not only scientifically robust but also socially acceptable and agronomically relevant.

Furthermore, the research illustrates that the biological risks of adaptation—such as loss of allelic diversity, inbreeding depression, or selection bottlenecks—must be managed hand-in-hand with social risks associated with germplasm exchange, intellectual property rights, and farmer adoption. Achieving a balance between these considerations will be fundamental to the success of future breeding programs committed to climate resilience. Transparency, collaboration, and capacity building emerge as critical components in this endeavor.

From a policy perspective, the study advocates for enhanced accessibility to plant genetic resources and calls on international institutions, governments, and the private sector to support the integration of genebank holdings into active breeding pipelines. Making genomic characterization widely available and linked with environmental projections fosters an enabling environment for informed decision-making. This will, in turn, help agricultural stakeholders anticipate and mitigate risks before they translate into crop failures or food shortages.

The reliance on publicly accessible genomic datasets and the adoption of sophisticated bioinformatic pipelines illustrates the transformative power of data-driven agriculture. As climate models become increasingly refined and genomic sequencing costs continue to decline, the potential for such integrative approaches will only expand. The sorghum case study presented here exemplifies how data science can be harnessed to solve some of the most pressing challenges in food security and sustainability.

In conclusion, adapting agriculture to future climate conditions is an intricate, multi-faceted challenge that demands harnessing both biological innovation and social collaboration. This pioneering research on sorghum sets a precedent for how genomic data, environmental insights, and genebank resources can be synergized to drive crop improvement. By prioritizing genetic resources with validated adaptive potential, the scientific community can empower breeding programs to deliver varieties that safeguard livelihoods and nourish populations amid unprecedented environmental change.

While substantial hurdles remain—ranging from resource mobilization to equitable sharing—this study offers a tangible roadmap. It highlights the centrality of genetic diversity not just as a static archive but as a dynamic, deployable asset critical to future food security. As climate risks escalate, harnessing this diversity with scientific rigor and ethical foresight will be essential to maintaining resilient agricultural systems worldwide.

Subject of Research:
Crop adaptation to future climate conditions through genomic characterization and prioritization of genetic resources in sorghum.

Article Title:
Prioritizing parents from global genebanks to breed climate-resilient crops.

Article References:
Campbell, Q., Castañeda-Álvarez, N., Domingo, R. et al. Prioritizing parents from global genebanks to breed climate-resilient crops. Nat. Clim. Chang. (2025). https://doi.org/10.1038/s41558-025-02333-x

Image Credits: AI Generated

At the core of this study are the pistachio farmers themselves—predominantly middle-aged individuals whose expertise accumulates over years, yet whose resource constraints limit the scope of their agricultural interventions. Operating within a multifaceted risk environment shaped by operational uncertainties, shifting climate variables, political frameworks, economic fluctuations, and financial pressures, these producers underscore the critical importance of developing comprehensive risk management paradigms tailored to local realities. The study’s sophisticated analysis confirms that risk attitudes among these farmers are not monolithic; instead, they vary considerably, influencing the adoption of strategies and ultimately the viability of their production systems.

The PLS-SEM approach enabled a nuanced understanding of how environmental limitations, particularly water scarcity, drastically reshape the contours of risk management in the region. Water resource constraints emerged as a pivotal variable influencing producers’ behavior—heightening their reliance on agricultural extension services and information networks while concurrently placing strains on their ability to comply with marketing standards. This paradox highlights the intricate balancing act pistachio farmers must perform between operational efficiency and market demands under resource-limited conditions.

Intriguingly, the findings illuminate distinct behavioral divides grounded in risk tolerance. Producers displaying higher risk tolerance often exhibit diminished sensitivity to environmental and political uncertainties, possibly due to an inherent confidence or a strategic choice to prioritize potential gains over conservative maneuvers. Conversely, risk-averse farmers meticulously navigate policy shifts and demonstrate enhanced financial risk control, frequently leveraging conservative financial frameworks to stabilize their operations against market shocks. This behavioral dichotomy carries profound implications for extension services and policy formulations aimed at supporting diverse producer profiles.

Age and educational attainment further stratify these risk attitudes. The study reveals a positive correlation between advancing age, higher educational levels, and increased risk aversion. Older, more educated producers tend to favor cautious, calculated approaches, underscoring the role of experiential learning and formal knowledge acquisition in shaping agricultural decision-making frameworks. Simultaneously, experience introduces an intriguing complexity, as it sharpens the ability to engage in calculated risk-taking coupled with effective mitigation strategies—suggesting a dynamic interplay between accumulated knowledge and risk navigation capabilities.

Based on a rigorous synthesis of these multidimensional insights, the study advocates for targeted interventions to forge a resilient pistachio sector in Siirt Province. Central to these efforts is the establishment of institutional support structures that address the unique challenges faced by small-scale producers. Strategic public investment in policies, credit facilities, and infrastructure—particularly those enhancing water management—are critical levers for bolstering sectoral stability. Such interventions must prioritize proactive engagement, enabling farmers to adopt advanced risk mitigation techniques before crises materialize.

Incentivization frameworks tailored to farmer risk profiles promise to catalyze more widespread uptake of innovative risk management tools. Subsidies for crop insurance, financial assistance for deploying advanced technologies, and capacity-building workshops form a comprehensive toolkit for empowering producers, particularly those who are risk-averse. Infrastructure upgrades, from modern irrigation systems to the provision of low-interest loans, represent tangible enablers that directly address resource limitations undermining productivity and sustainability.

Beyond infrastructure and financial support, fostering collaborative platforms—such as farmer cooperatives—can dramatically shift the power dynamics within the pistachio value chain. Cooperative models in Siirt Province have the potential to consolidate resources, facilitate knowledge sharing, and amplify collective bargaining power. Through coordinated efforts, producers can negotiate higher prices, share access to costly agricultural machinery, and collectively implement best practices, generating economies of scale and enhanced market positioning.

Recognizing the inherent vulnerability posed by narrow market dependency, the research proposes diversification strategies, including adapting marketing approaches under water-related constraints. Adding value through the development of pistachio-derived products—such as pistachio butter, oil, and snack foods—can unlock new revenue channels. Targeting differentiated market segments with these value-added goods introduces buffers against economic instabilities occasioned by environmental challenges, underscored by the increasing unpredictability of global agricultural markets.

Insect pests and diseases represent another front where coordinated policy intervention can mitigate risk. The promotion of early detection systems and integrated pest management (IPM) techniques, alongside stringent regulatory oversight to ensure safe pesticide use, is vital to safeguarding crop yield and consumer health alike. Government-led initiatives providing subsidized crop insurance, disseminating cutting-edge research, and enacting supportive regulatory frameworks are instrumental in cementing sustainable practices within the pistachio sector.

Educational efforts tailored to the heterogeneity of risk profiles further enhance adoption rates of sustainable farming methods. Workshops designed to illustrate the long-term economic and environmental consequences of inadequate risk management can persuade risk-taking farmers to embrace more balanced approaches. In parallel, risk-averse producers benefit from information sessions highlighting innovative irrigation technologies, organic farming potentials, and sophisticated financial analysis tools. Hands-on demonstrations, including the use of drone technology for precision field monitoring, exemplify practical initiatives that bridge knowledge gaps and foster technological acceptance.

Innovative financial instruments and microinsurance products emerge as pivotal tools to shield producers from acute financial shocks. Microinsurance policies that cover site-specific risks—drought, frost, and plant diseases—offer targeted protection, enhancing financial resilience. Complementary mechanisms such as forward contracts and crop-backed loans facilitate access to working capital, enabling investments that improve both production quality and risk mitigation.

However, the study’s scope is geographically concentrated, focusing solely on Siirt Province, which invites caution in extrapolating the findings to broader contexts without further corroboration. Variables such as market volatility, soil fertility gradients, and climate variability warrant comprehensive investigation across diverse ecological zones. Longitudinal studies tracking risk behavior evolution correlated with farming experience would deepen understanding and inform more nuanced policy development.

The integration of advanced modeling techniques, including scenario-based analyses accounting for climate change projections and non-linear environmental interactions, is essential in future research to quantify and prepare for the escalating uncertainty in agricultural landscapes. The study also highlights methodological considerations regarding how categorical socio-demographic variables, like education level, are incorporated into PLS-SEM analyses. Employing ordinal-specific analytical techniques could yield more precise modeling outcomes and better reflect the nuanced effects of such variables on risk perception and management.

In sum, this comprehensive investigation into pistachio production risk management in Siirt Province paints a vivid portrait of a sector navigating intensifying environmental and market pressures. It underscores the necessity for integrated approaches blending public policy, cooperative organization, technological innovation, and tailored education to sustain and enhance pistachio agriculture. Through such multifaceted efforts, producers can be better equipped to anticipate, absorb, and adapt to an uncertain future—securing the longevity and prosperity of this storied livelihood in the face of mounting challenges.

Subject of Research: Risk perception, risk attitude, and management strategies of pistachio producers in Siirt Province, Türkiye, analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Article Title: Analyzing risk perception, risk attitude, and management strategy using Partial Least Squares Structural Equation Modeling (PLS-SEM) in pistachio production: the case of Siirt Province, Türkiye.

Article References:
Şengül, Z. Analyzing risk perception, risk attitude, and management strategy using Partial Least Squares Structural Equation Modeling (PLS-SEM) in pistachio production: the case of Siirt Province, Türkiye. Humanit Soc Sci Commun 12, 660 (2025). https://doi.org/10.1057/s41599-025-04983-w

Image Credits: AI Generated