Microbial carbon use efficiency promotes global soil carbon storage.

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5-7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8-11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation.

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis-Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

Long-term warming increased carbon sequestration capacity in a humid subtropical forest.

Tropical and subtropical forests play a crucial role in global carbon (C) pools, and their responses to warming can significantly impact C-climate feedback and predictions of future global warming. Despite earth system models projecting reductions in land C storage with warming, the magnitude of this response varies greatly between models, particularly in tropical and subtropical regions. Here, we conducted a field ecosystem-level warming experiment in a subtropical forest in southern China, by translocating mesocosms (ecosystem composed of soils and plants) across 600 m elevation gradients with temperature gradients of 2.1°C (moderate warming), to explore the response of ecosystem C dynamics of the subtropical forest to continuous 6-year warming. Compared with the control, the ecosystem C stock decreased by 3.8% under the first year of 2.1°C warming; but increased by 13.4% by the sixth year of 2.1°C warming. The increased ecosystem C stock by the sixth year of warming was mainly attributed to a combination of sustained increased plant C stock due to the maintenance of a high plant growth rate and unchanged soil C stock. The unchanged soil C stock was driven by compensating and offsetting thermal adaptation of soil microorganisms (unresponsive soil respiration and enzyme activity, and more stable microbial community), increased plant C input, and inhibitory C loss (decreased C leaching and inhibited temperature sensitivity of soil respiration) from soil drying. These results suggest that the humid subtropical forest C pool would not necessarily diminish consistently under future long-term warming. We highlight that differential and asynchronous responses of plant and soil C processes over relatively long-term periods should be considered when predicting the effects of climate warming on ecosystem C dynamics of subtropical forests.

Genome-Wide Identification and Analysis of the Aux/IAA Gene Family in Panax ginseng: Evidence for the Role of PgIAA02 in Lateral Root Development.

Panax ginseng C. A. Meyer (Ginseng) is one of the most used traditional Chinese herbal medicines, with its roots being used as the main common medicinal parts; its therapeutic potential has garnered significant attention. AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) is a family of early auxin-responsive genes capable of regulating root development in plants through the auxin signaling pathway. In the present study, 84 Aux/IAA genes were identified from the ginseng genome and their complexity and diversity were determined through their protein domains, phylogenetic relationships, gene structures, and cis-acting element predictions. Phylogenetic analyses classified PgIAA into six subgroups, with members in the same group showing greater sequence similarity. Analyses of interspecific collinearity suggest that segmental duplications likely drove the evolution of PgIAA genes, followed by purifying selection. An analysis of cis-regulatory elements suggested that PgIAA family genes may be involved in the regulation of plant hormones. RNA-seq data show that the expression pattern of Aux/IAA genes in Ginseng is tissue-specific, and PgIAA02 and PgIAA36 are specifically highly expressed in lateral, fibrous, and arm roots, suggesting their potential function in root development. The PgIAA02 overexpression lines exhibited an inhibition of lateral root growth in Ginseng. In addition, yeast two-hybrid and subcellular localization experiments showed that PgIAA02 interacted with PgARF22/PgARF36 (ARF: auxin response factor) in the nucleus and participated in the biological process of root development. The above results lay the foundation for an in-depth study of Aux/IAA and provide preliminary information for further research on the role of the Aux/IAA gene family in the root development of Ginseng.

Identification and Expression Analysis of R2R3-MYB Transcription Factors Associated with Flavonoid Biosynthesis in Panax quinquefolius.

Panax quinquefolius L. is an important medicinal plant, and flavonoids are among its main secondary metabolites. The R2R3-MYB transcription factor plays an irreplaceable role in plant growth, development, and secondary metabolism. In our study, we identified 159 R2R3-MYBs and analyzed their physical and chemical properties in P. quinquefolius. The protein length of 159 PqMYBs varied from 107 to 1050 amino acids. The molecular weight ranged from 12.21 to 116.44 kDa. The isoelectric point was between 4.57 and 10.34. We constructed a phylogenetic tree of P. quinquefolius and Arabidopsis thaliana R2R3-MYB family members, and PqMYB members were divided into 33 subgroups. Transcriptome data analysis showed that the expression patterns of PqMYBs in root, leaf, and flower were significantly different. Following the MeJA treatment of seedlings, five candidate PqMYB genes demonstrated a response. A correlation analysis of PqMYBs and candidate flavonoid pathway genes showed that PqMYB2, PqMYB46, and PqMYB72 had correlation coefficients that were higher than 0.8 with PqCHS, PqANS4, and PqCCoAMT10, respectively. Furthermore, a transient expression assay confirmed that the three PqMYBs were localized in the nucleus. We speculated that these three PqMYBs were related to flavonoid biosynthesis in P. quinquefolius. These results provided a theoretical basis and a new perspective for further understanding the R2R3-MYB gene family and the biosynthesis mechanism of secondary metabolites in P. quinquefolius.

Whole-genome identification and expression profiling of growth-regulating factor (GRF) and GRF-interacting factor (GIF) gene families in Panax ginseng.

BACKGROUND: Panax ginseng is a perennial herb and one of the most widely used traditional medicines in China. During its long growth period, it is affected by various environmental factors. Past studies have shown that growth-regulating factors (GRFs) and GRF-interacting factors (GIFs) are involved in regulating plant growth and development, responding to environmental stress, and responding to the induction of exogenous hormones. However, GRF and GIF transcription factors in ginseng have not been reported. RESULTS: In this study, 20 GRF gene members of ginseng were systematically identified and found to be distributed on 13 chromosomes. The ginseng GIF gene family has only ten members, which are distributed on ten chromosomes. Phylogenetic analysis divided these PgGRFs into six clades and PgGIFs into two clades. In total, 18 of the 20 PgGRFs and eight of the ten PgGIFs are segmental duplications. Most PgGRF and PgGIF gene promoters contain some hormone- and stress- related cis-regulatory elements. Based on the available public RNA-Seq data, the expression patterns of PgGRF and PgGIF genes were analysed from 14 different tissues. The responses of the PgGRF gene to different hormones (6-BA, ABA, GA3, IAA) and abiotic stresses (cold, heat, drought, and salt) were studied. The expression of the PgGRF gene was significantly upregulated under GA3 induction and three weeks of heat treatment. The expression level of the PgGIF gene changed only slightly after one week of heat treatment. CONCLUSIONS: The results of this study may be helpful for further study of the function of PgGRF and PgGIF genes and lay a foundation for further study of their role in the growth and development of Panax ginseng.

Significant effects of precipitation frequency on soil respiration and its components-A global synthesis.

Global warming intensifies the hydrological cycle, which results in changes in precipitation regime (frequency and amount), and will likely have significant impacts on soil respiration (Rs ). Although the responses of Rs to changes in precipitation amount have been extensively studied, there is little consensus on how Rs will be affected by changes in precipitation frequency (PF) across the globe. Here, we synthesized the field observations from 296 published papers to quantify the effects of PF on Rs and its components using meta-analysis. Our results indicated that the effects of PF on Rs decreased with an increase in background mean annual precipitation. When the data were grouped by climate conditions, increased PF showed positive effects on Rs under the arid condition but not under the semi-humid or humid conditions, whereas decreased PF suppressed Rs across all the climate conditions. The positive effects of increased PF mainly resulted from the positive response of heterotrophic respiration under the arid condition while the negative effects of decreased PF were mainly attributed to the reductions in root biomass and respiration. Overall, our global synthesis provided for the first time a comprehensive analysis of the divergent effects of PF on Rs and its components across climate regions. This study also provided a framework for understanding and modeling responses of ecosystem carbon cycling to global precipitation change.

Machine learning for accelerating process-based computation of land biogeochemical cycles.

Global change ecology nowadays embraces ever-growing large observational datasets (big-data) and complex mathematical models that track hundreds of ecological processes (big-model). The rapid advancement of the big-data-big-model has reached its bottleneck: high computational requirements prevent further development of models that need to be integrated over long time-scales to simulate the distribution of ecosystems carbon and nutrient pools and fluxes. Here, we introduce a machine-learning acceleration (MLA) tool to tackle this grand challenge. We focus on the most resource-consuming step in terrestrial biosphere models (TBMs): the equilibration of biogeochemical cycles (spin-up), a prerequisite that can take up to 98% of the computational time. Through three members of the ORCHIDEE TBM family part of the IPSL Earth System Model, including versions that describe the complex interactions between nitrogen, phosphorus and carbon that do not have any analytical solution for the spin-up, we show that an unoptimized MLA reduced the computation demand by 77%-80% for global studies via interpolating the equilibrated state of biogeochemical variables for a subset of model pixels. Despite small biases in the MLA-derived equilibrium, the resulting impact on the predicted regional carbon balance over recent decades is minor. We expect a one-order of magnitude lower computation demand by optimizing the choices of machine learning algorithms, their settings, and balancing the trade-off between quality of MLA predictions and need for TBM simulations for training data generation and bias reduction. Our tool is agnostic to gridded models (beyond TBMs), compatible with existing spin-up acceleration procedures, and opens the door to a wide variety of future applications, with complex non-linear models benefit most from the computational efficiency.

Compensatory water effects link yearly global land CO2 sink changes to temperature.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Shape Discrimination of Individual Aerosol Particles Using Light Scattering.

We established an experimental apparatus by combining polarized light scattering and angle-resolved light scattering measurement technology to rapidly identify the shape of an individual aerosol particle. The experimental data of scattered light of Oleic acid, rod-shaped Silicon dioxide, and other particles with typical shape characteristics were analyzed statistically. To better study the relationship between the shape of particles and the properties of scattered light, the partial least squares discriminant analysis (PLS-DA) method was used to analyze the scattered light of aerosol samples based on the size screening of particles, and the shape recognition and classification method of the individual aerosol particle was established based on the analysis of the spectral data after nonlinear processing and grouping by particle size with the area under the receiver operating characteristic curve (AUC) as reference. The experimental results show that the proposed classification method has a good discrimination ability for spherical, rod-shaped, and other non-spherical particles, which can provide more information for atmospheric aerosol measurement, and has application value for traceability and exposure hazard assessment of aerosol particles.

Integrated Transcriptomic and Metabolomic Analyses Reveal the Effects of Grafting on Special Metabolites of Acanthopanax senticosus Leaves.

Acanthopanax senticosus (A. senticosus) is a member of Acanthopanax Miq. and is used in traditional Chinese medicine, and it has been found that grafting technology can be used to alter plant metabolite composition and transcriptome characteristics. In this study, shoots of A. senticosus were grafted onto the rootstocks of the vigorous Acanthopanax sessiliflorus (A. sessiliflorus) to improve its varietal characteristics. In order to investigate the changes in metabolites and transcriptional patterns in grafted A. senticosus leaves (GSCL), fresh leaves were collected from 2-year-old grafted A. senticosus scions, while self-rooted seedling A. senticosus leaves (SCL) were used as controls to analyse the transcriptome and metabolome. Metabolic profiles and gene expression patterns were further identified and correlated in special metabolite target pathways. The content of chlorogenic acid and triterpenoids in the GSCL was higher than in the control, while the quercetin content was lower. All these metabolic changes were associated with changes in the expression pattern of transcripts. Our results revealed the transcriptome and metabolome characteristics of GSCL. This may help to improve leaf quality in A. senticosus cultivation, suggesting that it is feasible to improve the medicinal quality of GSCL through asexual propagation, but the long-term effects need further investigation. In conclusion, this dataset provides a useful resource for future studies on the effects of grafting on medicinal plants.

Nonlinear interactions of land carbon cycle feedbacks in Earth System Models.

Carbon cycle feedbacks were often quantified through the carbon-concentration and carbon-climate feedbacks with the assumption of no significant interaction between the two feedbacks in most previous studies. Here we calculated the strength of the interactions between the two responses using simulations of models participated in the phase 6 of the Coupled Model Intercomparison Project (CMIP6). We found that the nonlinear interaction contributed 11% of the land-atmosphere carbon exchange on average with large intermodel variation (from -20% to +162%). This nonlinear interaction is largely driven by the pattern of net primary production (NPP), with shifts in heterotrophic respiration that dampen the overall positive interactions from NPP. Photosynthetic rate per unit leaf area alone cannot adequately explain a wide variation of interactions in global NPP simulated by CMIP6 models. Plant respiration and processes that regulate leaf area are also important contributors to the interactions. Dominant factors that induce carbon-concentration and carbon-climate interactions are highly variable among models. One of those dominant factors is nutrient limitation. Using additional simulations of ACCESS-ESM1.5 that include both nitrogen and phosphorus limitation, we found that the estimated interactions by ACCESS-ESM1.5 with or without nutrient limitations covered the large intermodel variations among the CMIP6 models. It remains largely unknown how nutrient limitation complicates ecosystem's responses to simultaneously CO2 fertilization and warming at the global scale. Our modeling results point to a potential important role of nutrients, especially phosphorus on the nonlinear interactions. Yet, more studies are needed on ecosystem responses to concurrent changes in nutrient availability, atmospheric CO2 concentration, and warming.

Mycorrhizal fungi alleviate acidification-induced phosphorus limitation: Evidence from a decade-long field experiment of simulated acid deposition in a tropical forest in south China.

South China has been experiencing very high rate of acid deposition and severe soil acidification in recent decades, which has been proposed to exacerbate the regional ecosystem phosphorus (P) limitation. We conducted a 10-year field experiment of simulated acid deposition to examine how acidification impacts seasonal changes of different soil P fractions in a tropical forest with highly acidic soils in south China. As expected, acid addition significantly increased occluded P pool but reduced the other more labile P pools in the dry season. In the wet season, however, acid addition did not change microbial P, soluble P and labile organic P pools. Acid addition significantly increased exchangeable Al3+ and Fe3+ and the activation of Fe oxides in both seasons. Different from the decline of microbial abundance in the dry season, acid addition increased ectomycorrhizal fungi and its ratio to arbuscular mycorrhiza fungi in the wet season, which significantly stimulated phosphomonoesterase activities and likely promoted the dissolution of occluded P. Our results suggest that, even in already highly acidic soils, the acidification-induced P limitation could be alleviated by stimulating ectomycorrhizal fungi and phosphomonoesterase activities. The differential responses and microbial controls of seasonal soil P transformation revealed here should be implemented into ecosystem biogeochemical model for predicting plant productivity under future acid deposition scenarios.

Tropical tall forests are more sensitive and vulnerable to drought than short forests.

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Network Pharmacology Combined with Metabolomics Approach to Investigate the Toxicity Mechanism of Paclobutrazol.

Paclobutrazol (PBZ) is a commonly used plant growth regulator (PGR) with good antibacterial activity. It has widespread applications in agricultural production. However, there is limited research reported on the potential risks of human health resulting from PBZ residues. In this study, using Sprague-Dawley rats, we carried out a systematic study on the hepatotoxicity and nephrotoxicity of PBZ in different doses (0.2, 0.5, and 1.0 g/kg). The metabolic profiles and network pharmacology were combined to construct a PBZ-endogenous substances-gene-hepatorenal diseases network to elucidate the underlying mechanism of PBZ's hepatorenal toxicity. At first, metabolomics analysis was done to investigate the metabolites and the related metabolic pathways associated with PBZ. Secondly, the network pharmacology approach was used in further exploration of the toxic targets. Additionally, molecular docking was carried out to investigate the interactions between PBZ and potential targets. The results indicated that PBZ showed obvious toxicity towards the liver and kidney of rats. The metabolomics analysis showed that PBZ mainly affected 4 metabolic pathways, including tryptophan metabolism, arachidonic acid metabolism, linoleic acid metabolism, and purine metabolism. Network pharmacology and molecular docking revealed that CYP1A2, CYP2A6, CYP2E1, MAOA, PLA2G2A, PTGS1, and XDH were critical targets for PBZ hepatorenal toxicity. This preliminary study revealed PBZ's hepatorenal toxicity and provided a theoretical basis for the rational and safe use of PBZ. Furthermore, it provided possible intervention targets for further research on how to avoid or reduce the damage caused by pesticides to the human body.

Toward a Global Model for Soil Inorganic Phosphorus Dynamics: Dependence of Exchange Kinetics and Soil Bioavailability on Soil Physicochemical Properties.

The representation of phosphorus (P) cycling in global land models remains quite simplistic, particularly on soil inorganic phosphorus. For example, sorption and desorption remain unresolved and their dependence on soil physical and chemical properties is ignored. Empirical parameter values are usually based on expert knowledge or data from few sites with debatable global representativeness in most global land models. To overcome these issues, we compiled from data of inorganic soil P fractions and calculated the fraction of added P remaining in soil solution over time of 147 soil samples to optimize three parameters in a model of soil inorganic P dynamics. The calibrated model performed well (r 2 > 0.7 for 122 soil samples). Model parameters vary by several orders of magnitude, and correlate with soil P fractions of different inorganic pools, soil organic carbon and oxalate extractable metal oxide concentrations among the soil samples. The modeled bioavailability of soil P depends on, not only, the desorption rates of labile and sorbed pool, inorganic phosphorus fractions, the slope of P sorbed against solution P concentration, but also on the ability of biological uptake to deplete solution P concentration and the time scale. The model together with the empirical relationships of model parameters on soil properties can be used to quantify bioavailability of soil inorganic P on various timescale especially when coupled within global land models.

Dynamic changes of ginsenosides in Panax quinquefolium fruit at different development stages measured using UHPLC-Orbitrap MS.

RATIONALE: Some studies have shown that Panax quinquefolium fruit (PQF) could also be used as a potential medicinal resource. However, little is known about the composition of ginsenosides and their dynamic changes at different development stages of PQF. Therefore, this study is of great significance for the metabolomics and rational utilization of PQF. METHODS: The samples were analyzed using ultra-high-performance liquid chromatography combined with an Orbitrap mass spectrometer (UHPLC-Orbitrap MS), and the method of metabonomics was applied to profile the dynamic changes of ginsenosides in PQF at different development stages. RESULTS: A total of 109 ginsenosides were identified or tentatively characterized. Samples collected from different development stages were significantly discriminated according to ginsenoside contents. A total of 25 potential chemical markers enabling the differentiation were discovered. CONCLUSIONS: For the first time, the study developed an UHPLC-Orbitrap MS-based approach to detect ginsenoside in PQF at different development stages using a non-targeted mode. This comprehensive phytochemical profile study revealed the structural diversity and discrimination of ginsenosides in PQF at different development stages, which could provide the basis for the metabolomics and rational application of PQF.

Multiresidue screening of pesticides in Panax Ginseng C. A. Meyer by ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry.

In this study, an efficient screening method based on a modified quick, easy, cheap, effective, rugged, and safe extraction method combined with ultra-high-performance liquid chromatography coupled to tandem quadrupole time-of-flight mass spectrometry was established for the determination of 90 pesticides residues in Panax Ginseng. The accuracy of the method was then verified by analyzing the false positive rate and the screening detection limit in Ginseng. The results revealed that the screening detection limit of 33 of 90 pesticide residues were 0.01 mg·kg-1 , 22 species were 0.05 mg·kg-1 , 11 species were 0.10 mg·kg-1 , 8 species were 0.20 mg·kg-1 , and another 16 species were greater than 0.20 mg·kg-1 . A total of 73 pesticides were ultimately suitable to be practically applied for rapid analysis of pesticide residues in Ginseng. Finally, the established method was used to analyze the pesticide residues in 35 Ginseng samples available on the market. And the residual of dimethomorph, azoxystrobin, tebuconazole, and pyraclostrobin was relatively severe in Ginseng samples. This work expanded the range of pesticides detected and provided a rapid, effective method for pesticides screening in Ginseng.