Soybeans, a crucial grain and oil crop, are valued for their high protein and oil content.  Soil salinization presents a significant abiotic stress that negatively impacts soybean growth and development, leading to reduced yield and quality.  The germination period represents a critical phase in soybean development.  This study evaluated salt tolerance in 165 soybean mutant lines during germination, resulting in the identification of five elite salt-tolerant germplasm resources.  Multi-environment Genome-wide association studies (GWASs) identified 11 significantly associated and 44 suggestive SNPs, alongside five novel QTLs linked to salt tolerance.  Analysis of candidate regions qtl5-1 and qtl5-2 identified Glyma.05G097200 and Glyma.05G240200 as promising candidate genes, exhibiting distinct expression patterns between salt-tolerant and salt-sensitive genotypes. Functional characterization in Arabidopsis demonstrated that overexpression of the soybean gene GmMACPF1 induced salt sensitivity, while the macpf1 mutant of Arabidopsis displayed enhanced salt tolerance.  Additionally, GmMACPF1 underwent selection during soybean domestication, with haplotypes Hap1 and Hap3 conferring improved salt tolerance.  These results indicate that GmMACPF1 functions as a negative regulator of salt tolerance during germination, offering novel insights into the molecular mechanisms governing soybean response to salt stress during this crucial developmental stage.

Microbial necromass carbon (MNC) serves a crucial function in the formation and stabilization of soil organic carbon (SOC). Although biochar amendment is recognized as a promising approach for enhancing SOC sequestration, its impact on MNC accumulation across the paddy soil profile remains uncertain. Through a 4-year field experiment, this study examined the effect of biochar amendment on MNC accumulation across three soil layers (0–15, 15–30, and 30–45 cm) in a paddy soil profile by combining vertical soil profiling, microbial community dynamics, and biomarker analysis. The results showed that biochar amendment reduced MNC by 10.5% (0–15 cm), 7.5% (15–30 cm), and 9.6% (30–45 cm), respectively, compared to the unamended control. In the topsoil (0–15 cm), the reduction in MNC under biochar amendment was attributed to decreases in both fungal and bacterial necromass carbon (C), whereas in the subsoil (15–45 cm), it primarily resulted from the decrease in bacterial necromass C. Biochar amendment reduced MNC content by decreasing microbial biomass and increasing nitrogen (N) acquisition enzyme activities, mainly due to a shift in the microbial community toward K-strategists and intensified microbial N limitation. This study provides novel insights into the microbially-mediated SOC dynamics in response to biochar amendment.

Nitrogen limitation has been well documented in grasslands on the Qinghai- Tibet Plateau (QTP), significantly affecting predictions of plant growth and carbon sequestration potential here under future climate change scenario. Beside atmospheric deposition, asymbiotic biological nitrogen fixation (ANF) may be crucial for nitrogen input in QTP grasslands, due to the lack of artificial fertilization and legume plants. However, little is known about the ANF’s contribution to nitrogen input on the QTP. To fill this knowledge gap, we studied the composition, diversity and activity of ANF diazotrophs across the QTP grasslands by using multiple methods of transect sampling, ¹⁵N-labeling and DNA stable isotope probing (SIP), amplicon sequencing, Random Forest algorithm modelling and digital mapping. We found that Skermanella and Mesorhizobium were the most abundant diazotrophic genera. Soil pH and total phosphorus concentration were the dominant driving factors for their composition and diversity. DNA stable isotope probing with ¹⁵N₂ revealed that Mesorhizobium were the most active nitrogen-fixing microorganisms. The potential N-fixation rates of these diazotrophs ranged from 0 to 18.1 kg N ha^-1 yr^-1, resulting in an estimated annual input of approximately 0.50 Tg N across the entire QTP’s alpine grasslands (i.e. ~25% of annual nitrogen input). The most important factor affecting the ANF rate was soil micronutrient molybdenum, a cofactor in the nitrogen-fixing nitrogenase, accounting for 24.64% of the variance. These findings suggested that ANF diazotrophs play important roles in maintaining nitrogen balance in the QTP grasslands and expand our understanding of Mesorhizobium’s ecological roles beyond traditional symbiotic interactions.

Soil organic carbon (SOC) dynamics significantly influence ecosystem carbon source-sink balance, particularly in agroecosystems. However, uncertainty remains regarding optimal land use types for maximizing farmland carbon storage across different soil types, and identifying effective land management practices for enhanced carbon accumulation is essential for reducing agricultural emissions and strengthening carbon sinks. This study examined SOC variations in eastern Yunnan's subtropical highlands (2,132 sites), analyzing topsoil (0-20 cm) across five land uses (dryland, irrigated land, forestland, grassland, plantation) of five soil types (red, yellow, yellow-brown, brown, purple). The investigation explored relationships between SOC and edaphic factors (26 elements) to determine SOC influencing factors. The study area demonstrated a mean SOC content of 27.78 g kg^-1, with distinct spatial heterogeneity characterized by lower values in the southwestern sector and higher concentrations in the northeastern region. Brown soils displayed the highest SOC content (P<0.05), followed by yellow-brown then red, yellow, and purple soils. Irrigation significantly enhanced SOC storage, particularly in brown soils where irrigated land contained 2.2-, 2.4-, and 1.6-times higher SOC than forestland, grassland, and dryland, respectively. Similar irrigation benefits occurred in purple, yellow, and yellow-brown soils, indicating moisture limitation as the primary SOC constraint. Notably, SOC exhibited strong positive correlations with nitrogen (N), sulfur (S), and selenium (Se). Nitrogen fertilization demonstrated dual benefits: enhancing SOC sequestration and promoting Se enrichment in crops, potentially supporting specialty agriculture. Although land use impacts on SOC varied across soil types (P>0.05), irrigation consistently emerged as the optimal management for carbon sink enhancement. These findings suggest that targeted water management could effectively reduce farmland carbon emissions in moisture-limited subtropical highlands. Strategic nitrogen application offers co-benefits for soil fertility and selenium biofortification, providing practical pathways for climate-smart agriculture in similar ecoregions.

Following the implementation of China's "Zero-Growth Action Plan on Fertilizers" in 2015, research has predominantly focused on replacing synthetic fertilizers with organic amendments to address over-fertilization concerns. However, insufficient attention has been given to the sustainable supply capacity of soil residual nutrients accumulated from previous over-fertilization. To investigate the transformation dynamics and supply capacity of residual nutrients during crop production, a 6-year field experiment was conducted in the dryland wheat growing region of China's Loess Plateau. Five treatments were established: farmer's fertilization (FF), regulated fertilization (RF), regulated fertilization without N (RF-N), regulated fertilization without P (RF-P), and regulated fertilization without K (RF-K). The study examined wheat yield formation, variations and stability of soil N, P, and K fractions, and their correlations with yield. Results indicated that wheat yield sensitivity to nutrient deficiency followed the sequence N>P>K. During the six-year period, the average yield under RF-N decreased by 22.0% compared to RF, showing statistical significance (P<0.05). Mineral N, light fraction organic N (LFON), and heavy fraction organic N (HFON) in RF-N showed progressive decline relative to RF and initial 2018 levels. Dissolved organic N (DON) and easily oxidizable organic N (EON) in RF-N initially decreased but subsequently increased due to N fraction transformations. Under RF-P, H₂O-P, NaHCO₃-P, and NaOH-P levels decreased by 40.0, 51.5, and 10.3% respectively (P<0.05) compared to the RF treatment, while HCl-P, residual P, and total P (TP) remained stable. The absence of K application (RF-K) reduced water-soluble K (WSK) by 10.9% (P<0.05), whereas exchangeable K (EK), non-exchangeable K (NEK), mineral K (MK), and total K (TK) showed no significant changes compared to the RF treatment. These findings demonstrated that the soil nitrogen pool exhibits lower stability compared to phosphorus and potassium pools during continuous residual nutrient supply. Notably, NO₃-N and LFON significantly influenced spike number and kernels per spike, driving yield formation. This research advances our understanding of sustained residual nutrient supply capacity in soil and provides theoretical foundations for optimizing fertilization strategies in dryland agroecosystems.

The timely and accurate assessment of soil nutrient information is essential for ensuring global food security and sustainable agricultural development. This study evaluated the individual and fusion performance of mid-infrared (MIR) and portable X-ray fluorescence (pXRF) spectroscopy for predicting selected soil properties. Four sensor fusion strategies were implemented: direct concatenation (DC), feature-level fusion using stability competitive adaptive reweighted sampling (sCARS) and least absolute shrinkage and selection operator (LASSO) algorithms (sCARS-C and LASSO-C), multi-block fusion via sequential orthogonal partial least squares (SO-PLS), and Granger-Ramanathan model averaging (GRA) method to enhance prediction accuracy for 13 soil properties. The findings revealed that single sensor models using either MIR or pXRF provided accurate estimations for soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), calcium (Ca), iron (Fe), manganese (Mn), and pH, but showed limitations for total potassium (TK), magnesium (Mg), copper (Cu), zinc (Zn), available potassium (AK), and total phosphorus (TP). The DC model significantly improved predictions for Mg (Rp²=0.76, RMSEp=358.76 mg kg^-1, RPDp=2.03) and TK (Rp²=0.75, RMSEp=775.96 mg kg^-1, RPDp=2.00). The LASSO-C model demonstrated superior prediction accuracy compared to the DC model for AP, AK, TP, Zn, Mn, and Cu, achieving optimal results for AP (Rp²=0.89, RMSEp=21.37 mg kg^-1, RPDp=3.01) and Zn (Rp²=0.80, RMSEp=9.88 mg kg^-1, RPDp=2.32). This enhancement is attributed to LASSO's effective selection of feature information from the complete MIR and pXRF spectra. The GRA models achieved the highest prediction accuracy for TP, pH, AK, and Cu, with Rp² values of 0.80, 0.82, 0.82, and 0.65, RMSEp values of 129.21 mg kg^-1, 0.13, 48.38 mg kg^-1, and 3.87 mg kg^-1, and RPDp values of 2.23, 2.34, 2.37, and 1.67, respectively. For single-sensor applications, MIR spectra are recommended for predicting SOM, TN, and Ca (Rp²≥0.88, RPDp≥2.87), while pXRF is more cost-effective for measuring Ca, Fe, and Mn (Rp²≥0.80, RPDp≥2.22). This research demonstrates the effectiveness of MIR and pXRF sensor fusion in enhancing soil nutrient assessment accuracy, particularly for available nutrients and micronutrients.

Brassica napus represents a major oilseed crop essential for global vegetable oil production.  Stem lodging, which constitutes the primary form of lodging, significantly reduces yield and seed quality.  Nevertheless, the agronomic characteristics and molecular mechanisms underlying stem lodging remain inadequately understood.  Through a two-year field assessment of 158 B. napus accessions, this study identified stem-breaking strength as the trait most highly correlated with stem-lodging angle, establishing it as the principal predictor of stem lodging in this species.  Comparative analysis between accessions with contrasting stem-breaking strength (‘Sy28’ high, ‘Gl210’ low) demonstrated that enhanced stem-breaking strength correlates with increased xylem and interfascicular fiber areas, along with higher concentrations of lignin, cellulose, and hemicellulose in stems.  Transcriptome analysis of these accessions revealed stem-breaking strength associated genes involved in cambium activity; lignin, cellulose, and hemicellulose biosynthesis; and transcriptional regulation of secondary cell wall formation.  This research identified the BnaC04.NST1–BnaA10.COMT pathway as a fundamental regulator of stem-breaking strength, controlling xylem and interfascicular fiber development and lignin accumulation.  These insights advance understanding of stem-breaking strength's role in lodging resistance and establish a molecular pathway for its enhancement in B. napus.

Transmissible gastroenteritis virus (TGEV) is an enteric coronavirus that poses a significant threat to the swine industry. However, the ecology, evolutionary history, and transmission dynamics of TGEV remain poorly understood. In this study, we analyzed 67 complete TGEV genomes collected globally between 1952 and 2023, employing comparative genomics to uncover the evolutionary dynamics and spatial dissemination of TGEV. Our findings reveal that TGEV can be classified into three major genotypes: the admixed GIa lineage with intercontinental distribution, the Europe-specific GIb lineage, and the U.S.-restricted GII lineage. Recombination events were identified in the ORF1a and S gene regions of GIa strains, suggesting that these genetic changes may have contributed to the evolutionary diversification of TGEV. Notably, the S gene is under strong positive selection, with five key codons under selection pressure, suggesting that the potential host–virus evolutionary arms race accelerates TGEV adaptation and diversification. Haplotype network analysis revealed that U.S. strains exhibit the highest genetic diversity, while Chinese strains are characterized by two dominant haplotypes surrounded by multiple closely related minor haplotypes. Bayesian phylogeographic analysis further confirmed that China has played an important role in the global dissemination of TGEV and clarified its transmission routes to regions such as the United States and Vietnam. Overall, this study advances our understanding of the evolution and spread of TGEV, and may contribute to the development of more effective strategies for its prevention and control.

N-terminal acetyltransferases (NATs) fundamentally regulate plant growth and development through protein N-terminal acetylation (NTA), a crucial post-translational modification.  Although their functional importance is recognized, systematic characterization of NATs remains unexplored in Oryza sativa.  This study identified 14 OsNAA genes distributed non-uniformly across 12 chromosomes in japonica rice.  Phylogenetic analysis combined with conserved domain studies revealed distinct evolutionary clades of OsNAT catalytic subunits with preserved structural architectures.  Analysis of promoter regions identified a prevalence of stress-responsive and growth-related cis-elements, corresponding to developmental stage-specific expression patterns throughout vegetative and reproductive phases.  Several OsNAA genes exhibited substantial transcriptional responses to cold, drought, NaCl, and heat stresses.  Furthermore, gibberellin (GA) promotes the upregulation of specific OsNAA genes during seedling development.  Collinear analysis demonstrated that segmental and singleton duplication events drive the expansion of the OsNAT family.  Functional characterization revealed that OsNAA30 localizes to the nucleus and cytoplasm, displaying canonical NatC activity in vitro.  Deletion of OsNAA30 led to reduced plant height and fewer tillers, accompanied by decreased cell elongation in the stem internodes.  OsNAA30 appears to regulate rice growth by suppressing the expression of GA catabolism genes and cell cycle regulators of plant height and tillering.  Additionally, analysis of the OsNAA30 haplotype links this gene to variations in plant height, culm length, and tiller number, indicating that the OsNAA30 locus may have influenced the local adaptation of plant architecture.  This research provides essential insights into the OsNAT gene family and establishes OsNAA30 as a valuable genetic target for molecular breeding in rice.

Drought priming enhances plant tolerance to various abiotic stresses, including low temperature; however, its multigenerational effects in wheat remain incompletely characterized.  To address this gap, we conducted a comprehensive multi-omics investigation combining transcriptomic profiling and hormone analysis to examine how drought priming across six consecutive generations influences offspring responses.  Wheat plants primed during grain-filling produced offspring with substantial alterations in gene expression and metabolism when exposed to low-temperature stress.  Analysis identified 424 and 1,679 differentially expressed genes (DEGs) between primed and non-primed offspring under normal and low-temperature conditions, respectively.  Under low-temperature stress, primed progeny exhibited a significant reduction in N-(3-Indolylacetyl)-L-valine and marked increases in tryptamine, dihydrozeatin, and gibberellin A20 levels.  Pathway enrichment analysis revealed predominant effects on plant hormone signal transduction, brassinosteroid biosynthesis, and zeatin biosynthesis pathways, highlighting the central role of hormonal regulation in enhancing stress tolerance.  Analysis of carbohydrate metabolism revealed distinct generational patterns: grandparental drought priming primarily enhanced glucose-related enzyme activities, suggesting a sustained impact on glucose metabolism, while parental drought priming influenced sucrose metabolism more directly, indicating stage-specific regulatory roles.  These metabolic alterations corresponded with improved physiological performance under low-temperature stress, evidenced by higher chlorophyll fluorescence and increased antioxidant enzyme activities in primed offspring.  These findings demonstrate that ancestral drought priming induces heritable molecular and metabolic modifications that enhance low-temperature tolerance in wheat offspring.  This transgenerational stress memory presents a promising approach for breeding wheat varieties with improved resilience to cold stress and variable climates. Integration of both parental and grandparental environmental histories into breeding programs may optimize crop stability under abiotic stress.

目的：流行性出血病（Epizootic Hemorrhagic Disease, EHD）是一种由流行性出血病病毒（EHDV）引起、经库蠓传播的虫媒传染病，感染野生及家养反刍动物，被世界动物卫生组织（WOAH）列为须通报动物疫病。近年来我国监测显示多个EHDV血清型在南方省份流行，且血清学阳性率极高，暴发风险严峻。然而，目前缺乏适用于现场、无需复杂仪器的快速检测技术。本研究旨在开发一种基于RT-ERA和CRISPR-Cas12a技术的EHDV核酸检测新方法，以实现对EHDV的高灵敏、高特异、快速且可视化的现场检测。

方法：本研究首先通过对EHDV不同血清型基因组序列进行比对分析，选定高度保守的S1基因片段作为检测靶标，并设计特异性crRNA。通过荧光检测法筛选并优化了CRISPR-Cas12a系统中的crRNA及Cas12a蛋白的最佳工作浓度。随后，针对该靶标设计了多对RT-ERA引物，通过筛选获得了最优扩增引物对（F6/R3）。将优化的RT-ERA扩增体系与CRISPR-Cas12a检测系统联用，构建了RT-ERA/CRISPR-Cas12a检测平台。通过使用梯度稀释的病毒RNA评估了该系统的检测灵敏度；通过检测蓝舌病病毒（BTV）、中山病毒（CHUV）等其他常见反刍动物病原体评估其特异性。最后，使用54份临床样本，分别经传统TRIzol提取法和HUDSON快速处理法处理样本后，将该检测系统与已建立的实时荧光RT-PCR方法进行比较，以评估其临床应用的灵敏度和特异性。

结果：本研究成功建立了EHDV的RT-ERA/CRISPR-Cas12a检测方法。优化的CRISPR-Cas12a系统在75 ng Cas12a蛋白和400 nM crRNA1条件下效果最佳。此外，最优RT-ERA引物对为F6/R3。该联用检测系统的灵敏度极高，荧光读值法和横向流动试纸条法的检测下限分别可达1.7 × 10¹拷贝/反应和1.7 × 10²拷贝/反应。特异性试验表明，该系统能有效检测EHDV-1, 2, 4-8, 10共8种血清型，而对BTV等其他病原体无一交叉反应。在54份临床样本检测中，基于TRIzol提取RNA的方法与实时荧光RT-PCR结果完全一致（灵敏度与特异性均为100%）；基于HUDSON快速处理的样本，其检测灵敏度为96%，特异性仍保持100%，可在无需核酸纯化的条件下实现快速检测。

Global climate change has intensified drought stress, presenting a significant challenge to agricultural production and breeding. The root system, as the primary organ sensing stress signals, plays a crucial role in determining plants' drought adaptability in soil conditions. Consequently, identifying optimal root architecture under drought conditions has become essential in crop breeding. This study employed a HT-ARPP to systematically analyze a natural population of 228 representative upland cotton accessions in specialized root boxes during seedling-stage drought stress. Root phenotypes were monitored 11 times across 20 days, generating over 20,000 images through an automatic root phenotypic robot, which yielded 27 image-based digital underground root traits (i-R_traits). The drought-resistant coefficient (DRC, ratio between drought and control of i-R_traits) was utilized to evaluate phenotypic responses. A comprehensive index of drought adaptability (CIDA) was developed through root traits analysis, and stepwise regression analysis established a model of key i-R_traits, enabling classification of accessions into 5 groups based on root adaptability to water deficiency. An ideal drought-adaptability root architecture was proposed through combined analysis of aboveground and underground phenotypes. The findings indicate that medium and intermediate drought resistant cotton accessions represent optimal breeding materials for maintaining stable growth under variable conditions, offering a novel strategy for future breeding programs focused on optimized root architecture.

The temperature sensitivity (Q₁₀) of soil organic carbon (SOC) is a critical parameter in SOC response models concerning climate warming, which governs both the direction and magnitude of soil carbon-climate feedback. However, the relative importance of soil organic compounds in the regulation of the Q₁₀ remains unclear, partly due to the relative stability of SOC compounds. Long-term different fertilization could change the quantity and quality of soil organic compounds. Here, a 38-year fertilization experiment combined with pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) was used to identify the effect of key soil organic compounds on the Q₁₀. Five treatments were chosen: no fertilization (CK), nitrogen fertilization (N), N combined with phosphorus and potassium fertilization (NPK), manure (M), and NPK combined with manure (NPKM). The results revealed that the Q₁₀ under M and NPKM were 1.59 and 1.66, respectively, which were significantly higher than those under CK (1.35), N (1.29), and NPK (1.36). There was a positive linear relationship between the Q₁₀ and SOC (R⊃2;=0.76, P<0.01), whereby manure-enriched SOC is more vulnerable to decomposition under future warming. Among the soil organic compounds, esters and phenols predominated, representing 30.30% and 18.83% of the composition, respectively. Manure increased soil stable organic compounds relative to CK and chemical fertilizer. The increased stable organic compounds under manure led to a high Q₁₀. In addition to the positive effect of soil alphaproteobacteria and pH on the Q₁₀, manure increased the Q₁₀ by increasing phenols and decreasing esters, whereas chemical fertilization did the opposite. These findings first provide substantial evidence that soil organic compounds play an important role in the magnitude and mechanism of SOC response to climate change. Manure-induced SOC, when compared to chemical fertilizers, conferred a heightened sensitivity to climate warming within agroecosystems.

Soil organic carbon (SOC), representing the largest terrestrial organic carbon pool, significantly influences soil quality. The incorporation of residues is widely recognized as a method to regulate SOC sequestration. A 365-day incubation experiment was conducted to evaluate the contribution of straw-derived carbon (SDC) of varying quality to SOC fractions (free particulate OC (fPOC), occluded POC and mineral-associated OC (MAOC)), and examine the relationships between microorganisms and SOC fractions by incorporating ¹³C-labelled maize stems (ST), leaves (LE), sheaths (SH) residues (1%) in Chinese Mollisol. Results indicated that compared to control (CK), ST, LE and SH treatments enhanced SOC, fPOC and MAOC by 4.8-19.5, 35.7-49.5 and 1.6-3.9%, respectively. The SDC-SOC and MAOC content of LE were 29.1-38.1% and 17.5-44.5% higher than ST and SH, respectively. The SDC-oPOC content of SH was 3.1% higher than LE. The PLFA concentration decreased steadily throughout the incubation period, while necromass remained in-fluctuating until an obvious increasing trend observed at later stage. Furthermore, structural equation model (SEM) revealed that lignin to nitrogen ratio (LigN) of ST exhibited negative association with SDC-fPOC, and bacterial diversity in SH showed negative correlation with LigN and positive correlation with SDC-oPOC, while demonstrating positive correlation between microbial necromass and SDC-MAOC in LE. These findings indicated that POC dynamics correlated with straw chemical traits, while MAOC showed links to both microbial necromass traits and straw chemical characteristics. These findings advance our understanding of how straw residue quality influences SOC turnover and stabilization through microbial community interactions, contributing to the development of policies to improve soil fertility, and promote the rational and efficient utilization of straw.

Xyloglucan is the main component of hemicellulose in the cell walls of higher plants, which provides mechanical support. The XTH gene family encodes xyloglucan endotransferase/hydrolase, which is a key enzyme in cell wall remodeling. However, studies on XTH family-related genes in apples are rare. In this study, the MdXTH30 gene, isolated from apple (Malus×domestica), was responsive to abscisic acid, NaCl, and PEG 6000, and was localized to the cytoplasm according to a subcellular mapping technique. To further investigate the role of MdXTH30 in the stress response, we generated transgenic MdXTH30 apple calli and heterologously expressed this gene in Arabidopsis by Agrobacterium-mediated transformation. The results demonstrated that MdXTH30 enhanced resistance to drought, salt stress, and pathogens by regulating the expression of relevant genes in apple calli and Arabidopsis. These findings provide valuable insight into potentially important candidate genes for improving biotic and abiotic stress resistance at the cell wall level.

Stem strength represents one of the most critical agronomic traits, as it enables plants to resist lodging and bending, thereby contributing to their overall yield and quality. Various transcription factors have been shown to regulate stem strength in crops; however, the mechanisms underlying stem strength formation and regulation remain largely unexplored, particularly in ornamental plants. This study identified a group IIe WRKY transcription factor PlWRKY29 in herbaceous peony. Tobacco plants overexpressing PlWRKY29- exhibited significantly enhanced stems, expanded xylem, thickened cell walls and elevated lignin content compared to wild-type specimens. Conversely, PlWRKY29-silenced herbaceous peony demonstrated opposite characteristics. Further investigation of the regulatory mechanism revealed that PlWRKY29 bound to the promoter of PlLAC15, which encodes a monolignol polymerization gene that facilitates lignin deposition. These findings demonstrate that PlWRKY29 positively regulates lignin biosynthesis and stem strength, advancing our understanding of lignin biosynthetic regulation in plants.

Cold stress represents a critical constraint on crop productivity, particularly in temperate climates. Despite the established role of abscisic acid (ABA) in cold stress responses, the precise mechanisms through which transcription factors mediate ABA-dependent cold tolerance remain elusive. Here, we identify VaMYB4a, a MYB transcription factor from Vitis amurensis Rupr. (Amur grape), as a key regulator of cold tolerance. It integrates ABA signaling with the CBF (C-repeat binding factors)-COR (cold-regulated) pathway to orchestrate cold stress adaptation. Through a combination of overexpression and CRISPR/Cas9-mediated knockout lines in Arabidopsis thaliana, grape callus, and Vitis vinifera.L seedlings, we demonstrate that VaMYB4a enhances freezing tolerance by promoting osmotic regulation, ROS (Reactive oxygen species) scavenging, and stomatal closure. VaMYB4a functions as a homo-dimer, with its C-terminal domain being essential for transcriptional activation. Mechanistically, VaMYB4a directly upregulates CBF and COR genes while fine-tuning ABA signaling components such as ABI1 and ABF4. Notably, ABA exhibits a dual role: enhancing VaMYB4a-mediated freezing tolerance under short-term stress but attenuating its effects during prolonged cold exposure, revealing an intricate regulatory crosstalk between cold and hormonal pathways. Our work not only advances the molecular understanding of cold adaptation but also provides a promising genetic target for developing stress-resilient grape varieties to mitigate the impacts of climate change.

Poa crymophila, a perennial Poaceae species native to the Qinghai-Tibet Plateau, exhibits remarkable adaptability to cold and drought. As a pioneer species for ecological restoration and a high-quality forage grass, it holds significant ecological and economic value. However, the lack of a clear genetic background has hindered in-depth investigation of its adaptative mechanisms. Here, Oligo-FISH analysis revealed that Poa crymophila possesses 28 chromosomes in its somatic cells (2n=28). De-novo genome assembly yielded a 3.71 Gb autotetraploid genome (2n=4x=28, monoploid size ≈0.93 Gb) with 143,547 annotated protein-coding genes. Phylogenetic analysis indicated that P. crymophila diverged from Poa infirma and Poa supina 6.19–20.09 million years ago, coinciding with the rapid uplift event of the Qinghai-Tibetan Plateau, after which a whole-genome duplication drove its autotetraploidy. Comparative genomics revealed expansions in stress-tolerance gene families (e.g., cytochrome P450s, laccase LACs, Cold-Regulated CORs, etc.), and contractions in photosynthesis-related gene families. Additionally, 622 positively selected genes involved in metabolism, stress response and signaling were detected, including KMS1, which is shared with Tibetan Barley (Hordeum vulgare var. nudum) and Tibetan semi-wild wheat (Triticum aestivum subsp. tibeticum). Notably, P. crymophila could synthesize abundant schisandrin A under stress, a hepatoprotective secondary metabolite, further enhancing its value as a forage resource. These findings provide valuable genomic resources for breeding stress-tolerant forage crops and supporting ecological restoration in high-altitude regions.

The long-term overuse of insecticides has accelerated the evolutionary development of insect resistance. In this process, carboxylesterases as pivotal enzymes in detoxification metabolism, play a critical role in the formation of pest resistance, with their enhanced activity and altered expression levels being closely associated with the development of resistance mechanisms. In this study, the VmCarEs-6 gene was screened and cloned based on the transcriptomic data of Therioaphis trifolii under reverse stress conditions. The aim was to investigate the role of this gene in the sensitivity of T. trifolii to chemical pesticides through RNA interference and inhibitor treatments. Indoor bioassay results demonstrated that exposure to LC₅₀ concentrations of lambda-cyhalothrin (LCT), isoprocarb (IPC), phoxim (PHX), and imidacloprid (IMI) significantly upregulated the expression of the VmCarEs-6 gene in T. trifolii. Following RNAi-mediated silencing of VmCarEs-6 using star polycation (SPc)-encapsulated double-stranded RNA, the mortality rates of aphids treated with the four insecticides increased by 35.6, 23.4, 31.1, and 23.3%, respectively, compared tothe control group. Additionally, the carboxylesterase inhibitor TPP exhibited a synergistic effect when combined with the aforementioned insecticides, with synergistic ratios increasing by 1.54, 1.28, 1.24, and 1.17, respectively, consistent with the RNAi results. Field trials further validated the indoor findings, showing that on the 5^th day after application, the control efficacy of LCT+TPP, IPC+TPP, PHX+TPP, and IMI+TPP combinations improved by 35.6, 21.5, 46.0, and 70.1%, respectively, compared to the use of chemical pesticides alone.The functional inhibition of the VmCarEs-6 gene in T. trifolii through RNAi and TPP treatment significantly impaired the pest's detoxification metabolism, thereby enhancing its sensitivity to chemical pesticides. This study provides a critical theoretical foundation for elucidating the mechanisms of resistance in piercing-sucking pests and developing targeted pest control products.

Temperament, similarly to personality, is defined by a consistency in the response of an individual to a challenge, for example, calm or agitated responses. Temperament is partly determined by genetic factors but can also be modulated by internal factors that act on the brain pathways that control temperament. In monogastric animals, the gut-brain axis (GBA) influences temperament. Recently, it has been shown that signals from the liver can impact both brain function and the gut microbiome in a three-way interaction named the GLBA. The role of the liver in GLBA signalling in the expression of temperament is unknown. Here, we report the first broad investigation on the impact of dietary tryptophan (Trp), a supplement that is known to affect temperament, on the communication pathways of the GLBA in Hu sheep of calm (C) or nervous (N) temperaments. In the rumen, Trp supplementation (T) increased the abundance of Chloroflexi and Bdellovibrionota abundance, with Flexilinea enriched in CT and Monoglobus and Sediminispirochaeta enriched in NT. Changes in the abundance of specific genera and phyla probably caused the observed changes in circulating levels of SCFAs, amino acids, and tryptophan metabolites. Changes in the rumen microbiome could partly explain the impact of dietary Trp on the temperament of nervous Hu sheep that was observed previously. The results of a metabolomics analysis of samples from the colon microbiome and the liver suggests that amino acid metabolism and SCFAs from these two tissues could be involved in the expression of temperament. Our findings highlight the GLBA as a potential signalling network modulating temperament in ruminants, with SCFAs, Trp metabolites, and microbial interactions as key mediators. Our data provide the first evidence that, in sheep, Trp affects behaviour through GLBA-dependent pathways and suggest that nutritional strategies, tailored for individuals’ temperament, would improve welfare in precision livestock farming. 

Understanding the molecular responses of tea leaves to mechanical stress is crucial for elucidating the mechanisms of post-harvest quality formation during oolong tea processing. This study emplemented an integrated multi-omics strategy to characterize the changes and interactions among metabolomic (MB), transcriptomic (TX), and proteomic (PT) profiles in mechanically stressed tea leaves. Mechanical stress initially activated damage-associated molecular patterns (DAMPs), including Ca²⁺ signaling, jasmonic acid signaling, and glutathione metabolism pathways. These processes subsequently induced quality-related metabolic pathways (QRMPs), particularly α-linolenic acid and phenylalanine metabolism. Up-regulated expression of LOX, ADH1, and PAR genes, together with the increased abundance of their encoded proteins, respectively promoted the accumulation of jasmine lactone, benzyl alcohol, and 2-phenylethanol. These findings indicate that mechanical stress influence the metabolite biosynthesis in tea leaves through coordinated molecular responses. This study provides new insights into the molecular mechanisms underlying tea leaf responses to mechanical stress and a foundation for future investigations into how early molecular events may contribute to post-harvest metabolic changes during oolong tea processing.

Brazil maintains a leading position in agricultural exports and stands as the world's foremost producer and user of bioinputs in agriculture. These bioinputs generate annual savings of billions of dollars that would otherwise be allocated to chemical fertilizers and pesticides. The nation's regulatory framework enables bioinput agriculture and serves as a model for countries transitioning toward regenerative agriculture. Brazilian legislation categorizes bioinputs into: 1) Biofertilizers (extracts); 2) biostimulants (plant growth-promoting and biocontrol agents); and 3) inoculants (active ingredient comprises one or more living microorganisms). The inoculation of soybeans with Bradyrhizobium strains provides approximately 90% of the nitrogen accumulated by this crop. Brazil has registered over six hundred inoculants, with at least 60% specifically designated for soybean cultivation. The annual sales of inoculants in Brazil reach approximately 120 million doses. Although beans (Phaseolus vulgaris and Vigna unguiculata) represent an essential food crop in Brazil's staple diet and benefit from inoculation, inoculant supply remains insufficient. Regarding biocontrol, soy, corn, sugarcane, and coffee rank among the most protected crops, employing biocontrol agents against bacteria, fungi, nematodes, and insects. Bacillus, Pseudomonas, Streptomyces, Rhizobium, Azotobacter, and Paenibacillus strains were predominantly cited in the 5,000+ bioproduct patents filed between 2022 and 2024. Among fungal genera, Trichoderma, and Penicillium received the most citations. EMBRAPA's biobanks maintain over 10,000 strains of bacteria, fungi, and viruses for biocontrol, and 14,000 strains of nutrient-fixing and plant-growth promoters. Production challenges include quality control, particularly as on-farm production of inoculants becomes prevalent on larger farms, alongside product availability and supply limitations. Brazilian farmers maintain global competitiveness partly through reduced chemical fertilizer and pesticide costs enabled by bioinput usage. As components of regenerative agriculture, bioinputs enhance soil quality, decrease carbon footprints, and support SDGs. Brazil's leadership in microbial bioinput utilization stems from its extensive agricultural sector, rich microbial biodiversity, and progressive regulatory framework.

Bud endodormancy represents an ecological adaptation mechanism in perennial deciduous fruit trees to endure winter cold conditions. Sucrose serves a crucial role in bud endodormancy as both an energy metabolizer and signaling molecule. Sugars will eventually be exported transporters (SWEETs) function as sugar-efflux transporters that respond to environmental stimuli and contribute to plant growth and development. While SWEET gene families have been identified in various plant species for sugar transport regulation, their mechanism in regulating peach bud endodormancy remains undefined. In this study, we identified 15 SWEET genes in peach. The nomenclature was established through homologous alignment with the Arabidopsis SWEET gene family, resulting in four distinct clades through phylogenetic analysis. Covariance correlation analysis revealed 6 and 12 collinear SWEET genes in peach and Arabidopsis, respectively, forming 13 collinear gene pairs. Real-time quantitative polymerase chain reaction (RT-qPCR) analysis demonstrated significantly elevated expression of PpSWEET6 during peach bud endodormancy release, correlating positively with sucrose content. Transient overexpression of PpSWEET6 enhanced peach bud endodormancy release, while overexpressing PpSWEET6 in Arabidopsis enhanced seed germination and flowering. Y2H and luciferase complementation imaging (LCI) assays confirmed PpSWEET6 interacted with PpABF2. Additionally, Dual luciferase Reporter (DLR) assays showed that PpSWEET6 significantly decreased the activation of PpDAM6 (key dormancy-inducing gene) through PpABF2, thereby modulating peach bud endodormancy release. These findings advance our understanding of SWEET genes in peach bud endodormancy regulation.

Intercropping with leguminous green manure represents a sustainable approach to enhance agroecosystem resilience through improved soil fertility and resource-use efficiency. However, the synergistic mechanisms between leguminous green manure intercropping and regulated deficit irrigation in maintaining maize yield stability and enhancing kernel profiles under arid conditions remain inadequately understood. A three-year (2021-2023) split-plot field experiment incorporated main plots consisting of three green manure incorporation practices: full green manure incorporation (M||V-P), green manure stubble retention (M||V-R), and maize without green manure (maize sole cropping, SM); while split plots comprised three irrigation regimes: conventional (I3, 400 mm), 15% deficit (I2, 340 mm), and 30% deficit (I1, 280 mm). The study examined maize grain yield, kernel quality (protein, fat, starch, and essential amino acid content), net photosynthetic rate (Pn) of maize, and soil nitrate-ammonium nitrogen content. M||V-P and M||V-R increased maize grain yield compared to SM, with M||V-P producing 5.7% higher yields than M||V-R. Notably, M||V-PI2 achieved comparable yield to M||V-PI3 while reducing irrigation by 15%, demonstrating an 18.3% yield increase over SMI3. M||V-P and M||V-R enhanced kernel quality compared to SM, exhibiting higher protein, fat, starch, and essential amino acid content. Decreased irrigation led to increased kernel protein content but reduced fat and starch contents. The kernel protein content with M||V-PI2 showed no significant difference from M||V-PI1, while maintaining fat, starch, and essential amino acid content similar to M||V-PI3. M||V-PI2 improved all kernel quality parameters relative to SMI3. These enhancements primarily resulted from maize intercropped with leguminous green manure in combination with 15% deficit irrigation, which increased maize Pn by 14.3%, and elevated soil nitrate-ammonium nitrogen by 12.5 and 5.2%, respectively. These findings demonstrate a scalable approach for sustainable maize production though the integration of leguminous green manure intercropping in water-limited regions.

Globally grassland ecosystems are facing unprecedented threats from continuous degradation and about 49% of grasslands are experiencing varying degrees of degradation. Resolving the imbalance between available forage and livestock demand is a major issue for grassland ecosystems. Transforming natural grasslands, which are on the brink of ecological collapse and have extremely high repair costs, into mowing grasslands can simultaneous address forage deficiency and also reduce the cost of long-distance transportation. Exploring the biomass yield and forage quality of multiple-mowing grasslands on the QTP is essential for calculating its construction scale. For this purpose, we conducted a grass-legumes cultivation experiment on the southeastern edge of the QTP and performed multiple mowing experiments. The results showed that compared to one-time harvesting during the growth period, multiple mowing significantly improved the biomass yield and nutritional quality of the grass, and gradually balanced towards quality as the mowing process progressed. Based on the experimental results, we used the current livestock loss rates in the QTP as a reference and further established different supplementary feeding modes from an energy supply perspective. Finally, we conclude that under the premise of no restriction on feeding, the artificial grassland needs to be increased to 2.22-9.38 times the current area. Under the restriction on feeding, the QTP needs to increase by 1.55-9.38 times, and the corresponding natural grassland area needs to be reduced by 3.96-16.75% and 2.77-16.75% respectively to meet the energy demand-supply. These results provide data support for grassland management planning in the QTP and inform the development of feasible strategies for improving the grass-livestock dynamics in the QTP.

Although genome-wide interaction effects are critical for unraveling the underlying genetic architectures of complex traits, the rich landscape of biological interactions is often disregarded in statistical models for genomic dissecting and predicting complex traits/diseases. To bridge this gap, we introduce biBLUP (biological interaction Best Linear Unbiased Prediction), a novel epistatic model that integrates prior biological knowledge by focusing on interactions among genes within KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways. Simulation experiments demonstrate that biBLUP effectively captures interaction effects across diverse genetic architectures, achieving up to a 62% increase in predictive accuracy compared to models ignoring such information. We validated the performance of biBLUP using real data across species. In a specific application using data from 6,642 yeast lines, biBLUP yielded a 40.36% improvement in prediction accuracy for growth rate by modeling genetic interaction effects within the KEGG pathway associated with allantoin utilization. Furthermore, incorporating KEGG into biBLUP successfully captures validated epistatic effects associated with rice flowering time. This integration results in an improvement of 16.29% in prediction accuracy for flowering time of rice. Our findings demonstrate that integrating KEGG pathway information into genomic prediction models enables the capture of biologically relevant interaction effects, thereby enhancing both predictive ability and our understanding of the genetic basis of complex traits.

Alfalfa (Medicago sativa L.), a photoperiod sensitive long-day (LD) flowering legume forage crop, is widely cultivated for its high-yield, -quality, and -related economic benefits. However, early flowering affects the biomass yield and quality of alfalfa. Cycling DOF Factors (CDFs) play critical roles in multiple fundamental processes in higher plants, including photoperiodic flowering time regulation. Here, we identified 15 CDFs in the alfalfa genome, which is approximately three times than the number of higher plants. Duplication events are the primary driving force behind the expansion of the CDF gene family in alfalfa. Evolutionary analysis revealed that MsCDFs in the C subclade is exclusively present in leguminous plants, suggesting their diverse functions within the legume family. Among them, MsCDFc1 mRNA exhibited a rhythmic expression pattern and its mRNA levels predominantly expressed than other members. MsCDFc1 protein localized to the nucleus and exhibited no transactivation in vitro. We demonstrated that under LD conditions, MsCDFc1 has a conserved function of flowering time regulation, as overexpressed plants (Arabidopsis and alfalfa) showed delay (P<0.05) in flowering time. Therefore, the quality of the late-flowering alfalfa was improved by reduced (P<0.05) levels of neutral detergent fiber (NDF), acid detergent fiber (ADF), and lignin contents at initial flowering stage. Further investigations showed that the late flowering in the over- expressed plant was correlated with the reduced (P<0.05) transcript levels of the MsFTa1 and MsE1 gene but in a MsCO-Like independent manner. Furthermore, MsCDFc1 does not interact with MsFKF1 or bind to the MsFTa1 and MsFTb1 promoters, suggesting functional divergence from the Arabidopsis model.

Although pigs lack classical brown adipose tissue, several studies have demonstrated that porcine adipocytes possess the capacity to undergo thermogenesis through UCP1-independent mechanisms. However, the developmental processes and regulatory mechanisms underlying these thermogenic adipocytes remain poorly characterized. Here, we found that dorsal subcutaneous adipose tissue in pigs exhibits significant thermogenic potential under cold stress. Notably, we observed substantial cold-induced structural remodeling in dorsal subcutaneous adipose tissue, characterized by increased fibrotic deposition. Through integrated analysis of snRNA-seq and RNA-seq data on dorsal subcutaneous adipose tissue, we identified MFAP5, which encodes a microfibril-associated glycoprotein in the extracellular matrix, as a potential regulator for cold-induced the plasticity of dorsal subcutaneous adipose tissue. Both MFAP5 overexpression and MFAP5-conditioned medium not only inhibit preadipocytes differentiation into adipocytes but also promote their commitment to non-adipogenic fibrogenic lineages. Furthermore, MFAP5 treatments significantly enhanced mitochondrial biogenesis of these fibrogenic cells. Mechanistic investigations elucidated that these phenotypic alterations are predominantly mediated through the Hippo signaling pathway. In summary, our findings elucidate the pivotal role of MFAP5 in regulating adipocyte development following cold exposure, providing crucial insights into the molecular mechanisms underlying porcine adaptation to cold stress.

Plutella xylostella represents a significant agricultural pest affecting cruciferous crops globally. The extensive use of synthetic insecticides has resulted in environmental contamination and resistance development, necessitating research into environmentally sustainable biopesticides. Serine protease inhibitors (serpins) serve essential functions in melanization during innate immunity, reproduction, and metamorphic development. Through proteomic analyses conducted across developmental stages of P. xylostella, serpin15 was identified as a crucial member of the typical inhibited serpin family, though its precise function remained undetermined.  RT-qPCR analyses of gene expression patterns across tissues and developmental stages demonstrated that the serpin15 gene exhibits high expression in male adult gonads and reaches maximum levels in hemolymph. The serpin15 mRNA levels showed dynamic regulation in the midgut following Serratia marcescens (PS-1) infection, characterized by an initial decline followed by upregulation. CRISPR/Cas9-mediated knockout of serpin15 in homozygous lines led to decreased oviposition and embryonic hatching rates in offspring. Functional analyses confirmed that serpin15 inhibits phenoloxidase (PO) activity, while exogenous supplementation with recombinant serpin15 protein effectively suppressed hemolymph melanization, establishing its regulatory role in countering PS-1 through immune melanization. These findings demonstrate serpin15's dual functionality in regulating both fecundity and immunity against PS-1 in P. xylostella. This research establishes a theoretical foundation for developing biocontrol strategies targeting insect immune and developmental systems.

Home plant-soil feedbacks (home-PSFs) typically demonstrate negative effects in vegetable crops, substantially inhibiting their growth. Phosphorus (P), an essential plant nutrient crucial for growth, influences vegetable crop growth patterns through soil availability levels. However, the relationship between soil available P levels and home-PSFs in vegetable crops requires further investigation. This study established a home PSF system incorporating 12 vegetable crops from 6 families to examine growth responses under two P conditions (low P level: 40 mg P kg^-1 soil; high P level: 200 mg P kg^-1 soil). The findings revealed that low P conditions significantly decreased overall biomass across all vegetables, with preferential biomass allocation to root development. Furthermore, low P conditions enhanced mycorrhizal colonization and rhizosphere acid phosphatase activity while notably decreasing root length. While vegetables generally exhibited negative home PSFs, allium and nonmycorrhizal plants demonstrated positive responses under high P conditions. Wild tomatoes displayed greater variation in feedback values across P levels compared to common tomatoes. Under high-P conditions, mycorrhizal colonization showed positive correlations with feedback values of biomass and P concentration. Root diameter and mycorrhizal colonization demonstrated distinct correlations with these feedback values under low-P conditions. The research concludes that high P levels effectively mitigate negative home-PSFs in vegetables while increasing biomass production. Additionally, high P levels demonstrated superior efficacy in alleviating negative home-PSFs in wild tomatoes compared to common tomatoes.

Composting represents a crucial component of sustainable waste management, providing significant resource recovery and environmental advantages. However, nitrogen loss during composting remains a significant challenge, necessitating the development of a predictive model for nitrogen loss during the composting process. This investigation implemented five machine learning models, utilizing 307 data points encompassing composting strategies, physicochemical properties, and composting time stages, to predict nitrogen loss during organic solid waste composting. The findings demonstrated that the adaptive boosting (AdaBoost) algorithm achieved optimal performance with a coefficient of determination of 0.847 after eliminating redundant features (scale and C/N). Moreover, Shapley additive explanation analysis identified several key factors significantly influencing nitrogen losses during composting, including composting time stages, bulking agents, raw materials, and ammonium nitrogen levels. Notably, the initial phase of composting emerged as the most critical period for nitrogen loss. The utilization of sawdust, rice husk, and corn stalk as bulking agents enhanced nitrogen retention in compost. Furthermore, implementing static aeration for ventilation and applying chemical additives effectively reduced nitrogen losses during the composting process. These results provide a scientific foundation for identifying optimal composting conditions to minimize nitrogen loss, thereby offering practical guidance for effective composting operations.

Cropland abandonment significantly impacts food security and agricultural sustainability, yet comprehensive analyses of its dynamics in rapidly developing regions remain scarce. This study investigates the spatiotemporal patterns, labor migration influences, and food security implications of cropland abandonment in China from 1992 to 2022. Analysis reveals that abandonment evolved through four distinct phases: slow growth, rapid increase, high-level fluctuation peaking at 3.98% in 2016, and gradual decline. We further identified three primary abandonment patterns—single long-term (≥10 yr), progressive degradation, and occasional (3-9 yr)—with distinctive spatial distributions. Specifically, long-term abandonment is concentrated in the marginal agricultural areas of southwestern mountainous regions, while occasional abandonment is prevalent in the more economically developed eastern coastal areas, and progressive degradation patterns are found in the transitional zones between plains and mountains. Labor migration influenced abandonment non-linearly with distinct regional thresholds. Short-distance (within-county) migration reduced abandonment rates, while medium-distance (within-province) migration significantly increased them. Although 57.50% of abandonment occurred on low-suitability land, 42.50% affected high-suitability cropland, resulting in peak potential grain losses of 15.0 and 8.8 million tonnes for low and high suitability land respectively in 2010. These findings provide support for regionally differentiated land management strategies that integrate land suitability assessments, labor migration patterns, and local socioeconomic conditions to ensure agricultural sustainability.

The intelligent pest-monitoring light trap based on machine vision employs specific light spectra to attract pests, infrared heating to eliminate pests, and artificial intelligence models to recognize and count them. Achieving optimal model performance requires a high-quality insect annotated dataset. However, traditional manual annotation is expert-dependent, time-consuming, and inefficient for large-scale multi-class insect labeling. This study establishes an efficient, few-shot learning approach to construct a large-scale light-trapped insect dataset through a two-stage annotation framework: detection followed by classification. Specifically, a MLTIDD addresses scale and receptive field disparities between large and tiny insects. Based on a fine-tuned Grounding DINO, SAM and SAHI are integrated to detect insects at multiple scales. Subsequently, InsectSSRL, an iBOT-based self-supervised method, learns robust insect feature representations from the extensive set of unlabeled insect sub-images detected by MLTIDD. It enhances feature extraction capability for insect sub-images through three proxy tasks. This feature extractor supports a classification model to pre-classify insect sub-images. Following expert correction, labels are traced back to original images to complete annotation work for the light-trapped insect dataset.

Experimental results demonstrate that under limited samples, MLTIDD achieved 79.6% average precision (AP)_50-95 and 90.8% average recall (AR), surpassing DINO by 7.0 and 4.7 percentage points. InsectSSRL attained 85.87% top-1 accuracy in k-NN evaluation. In few-shot classification, Swin-T pre-trained with InsectSSRL and fine-tuned on 5% of InsectID achieved 80.35% accuracy, exceeding iBOT by 2.08 and COCO-based transfer learning by 11.3 percentage points. The proposed pipeline improved mAP_50-95 by 10.91 and AR by 8.26 percentage points compared to DINO and iBOT, while reducing expert annotation time by approximately 80% relative to manual labeling.

Ostrinia furnacalis represents a destructive lepidopteran pest causing up to 30% yield losses in maize crops globally. Its larvae penetrate plant tissues, disrupt nutrient transport, and transmit viral and microbial pathogens, exacerbating food security concerns. Current management approaches for O. furnacalis primarily rely on synthetic pesticides. Targeting chitin metabolism presents a promising strategy for green insecticide development. Specifically, OfChi-h, an essential chitinase for O. furnacalis molting and survival, has emerged as a viable target. This study identified a N-phenyl-isoindole-1,3-dione (PI) scaffold as a novel class of OfChi-h inhibitor through virtual screening strategy. Notably, compound PI-17 demonstrated potent inhibitory activity against OfChi-h with a K_i value of 2.3 μmol L^-1. PI-17 exhibited significant insecticidal activity against lepidopteran pests O. furnacalis, comparable to the control drug hexaflumuron. scanning electron microscopy (SEM) analysis revealed morphological alterations in the cuticles of O. furnacalis larvae treated with PI-series compounds. ESP and DFT calculations explored the variations in biological activities of the PI-series compounds at atomic and electronic levels. Additionally, comprehensive safety evaluations assessed the impact on the natural enemy Trichogramma ostriniae and nontarget organisms. These findings introduce a novel class of lead compounds, N-phenyl-isoindole-1,3-dione derivatives, showing significant potential for developing eco-friendly insect growth regulators to control O. furnacalis.

The hemagglutinin (HA) protein of the H9N2 subtype avian influenza virus (AIV) undergoes frequent antigenic drift, which compromises the efficacy of existing inactivated vaccines. We have identified 12 key HA residues responsible for antigenic differences between the 2 major H9N2 antigenic groups; however, their role in eliciting broad cross-reactive immunity remains undefined. In this study, we systematically evaluated the impact of single- and multi-residue mutations in HA antigenic regions A, B1, B2, and E on viral antigenicity using antigenic cartography and monoclonal antibody profiling. 4 recombinant viruses—R118-A, R118-AE, R118-B1, and R118-AB1E—demonstrated broadened antigenic reactivity and were selected for further analysis. Among them, R118-A elicited immune sera with high hemagglutination inhibition and microneutralization titers against a diverse panel of H9N2 strains and exhibited broad antigenic coverage on antigenic cartography. In chicken challenge experiments, immunization with R118-A conferred cross-protection against group 1 (B4.4+B4.6) and group 2 (B4.7) H9N2 viruses, underscoring the critical role of site A modifications in broadening vaccine protection. These findings offer theoretical support and practical strategies for the rational design of next-generation H9N2 vaccines with improved cross-protective efficacy.

Phosphorus (P) availability influences the spatial distribution of carbon (C)-cycling enzyme activities in the rhizosphere through its effects on plant growth and microbial activity. However, the influence of P availability on the spatial patterns of C and P hydrolase activities remains unclear in the rhizosphere of Maize (Zea mays L.) and narrow-leaf lupine (Lupinus angustifolius L.), which exhibit contrasting P deficiency adaptation and acquisition strategies. This study analyzed the spatial patterns of C and P hydrolase activities through zymography and correlated them with bacterial community structure in maize and lupine rhizospheres. Under P-deficient conditions, maize exhibited severe growth restriction while demonstrating a 2.2–9.6-fold increase in root exudation compared to P-sufficient conditions. The enhanced exudation under P deficiency promoted r-strategist bacterial proliferation (e.g., Ktedonobacteria and Xanthomonadales) while reducing K-strategist abundance (Actinobacteriota, Chloroflexia, and Alphaproteobacteria). Maize rhizosphere enzyme activities and hotspot areas demonstrated positive correlation with K-strategist abundance and negative correlation with r-strategist abundance. P-sufficient maize exhibited 15–550% higher C- and P-cycle-related enzyme activity and hotspot areas, attributed to its enhanced root system and predominance of K-strategists with superior enzyme synthesis capabilities. Lupine demonstrated superior P deficiency adaptation, producing 2–19 times more DOC and organic acids than maize. Consequently, lupine showed no significant alterations in enzyme activity, hotspot areas, or bacterial community composition in response to P availability. These findings demonstrate that plant-specific P deficiency adaptation mechanisms distinctly influence the spatial distribution of C-cycling enzyme activity and bacterial community structure in the rhizosphere.

Soil salinization represents a primary manifestation of land degradation and presents a significant threat to sustainable agricultural development. Remote sensing-based methodologies currently constitute the preferred approach for salinization monitoring. Environmental factors' spatial heterogeneity substantially constrains the modeling process in accurately capturing the soil salt content (SSC)-modeling factor relationship, thereby affecting monitoring accuracy . This study proposes a classification modeling framework based on dominant salinization factors , establishing distinct remote sensing inversion models through categorization of soil texture and surface drainage conditions. Results indicate that classification modeling substantially improves the capture of SSC-modeling factor relationships. The efficacy of identical modeling indicators and methods varies significantly across different classification scenarios. Among the three modeling approaches, random forest demonstrates superior overall robustness. Of the three variable selection methods, Light Gradient Boosting Machine (LightGBM) shows the strongest compatibility with the modeling approaches. The classification strategy significantly enhances model accuracy: compared to non-classified modeling (R²_V=0.62), the testing set R⊃2; increases by up to 24% (R²_V=0.77). Models under poor surface drainage category demonstrate optimal performance, with coupled models achieving R²_C=0.82 (training set) and R²_V =0.77 (testing set). This research provides valuable insights for remote sensing monitoring of soil salinization in precision agriculture contexts.

Root exudates serve a vital function in recruiting beneficial phosphate-solubilizing bacteria (PSB), thereby enhancing plant adaptation to phosphorus (P) deficiency. The C2H2-type zinc finger transcription factor STOP1 (sensitive to proton rhizotoxicity1) regulates root organic acid (OA) exudation in plants. However, the impact of STOP1-regulated root OA exudation on rhizosphere microbial composition remains unexplored. This study revealed enhanced vegetation properties of soybean with higher P content in P-rich soils, while rhizosphere organic acid concentrations were elevated in P-poor soils. The soybean genotype YC03-3 in P-deficient soils specifically recruited three PSB in acid soils: Gammaproteobacteria_Incertae_Sedis, KF_JG30_C25, and Solirubrobacterales. These PSB abundances correlated positively with rhizosphere oxalate and citrate concentrations. Under P-sufficient conditions, GmSTOP1-3 overexpression in soybean plants increased oxalate and citrate exudation compared to wild-type (WT) plants, leading to preferential colonization by the same three PSB species naturally present in P-deficient WT rhizosphere. The population dynamics of these PSB demonstrated strong positive correlations with the abundance of key genes involved in P cycling, particularly those governing acid/alkaline phosphatase activities and organic-P mineralization. Given the phosphate starvation-enhanced expression pattern of GmSTOP1-3, the findings indicate that specific PSB recruitment for organic-P remobilization in soybean rhizosphere depends on GmSTOP1-3-mediated oxalate and citrate exudation in P-deficient acid soils. This research establishes GmSTOP1-3 as a crucial regulator of rhizosphere microbiome assembly and P-acquisition efficiency in acid soils.

Drought stress represents one of the most significant abiotic constraints on plant growth, development, and productivity. Fodder soybean (Glycine max), a high-nutritional-value forage crop, experiences substantial reductions in both yield and quality under soil water deficit conditions. Strigolactones (SLs), a novel class of plant hormones, play crucial regulatory roles in various plant developmental processes. However, the mechanisms underlying SLs-mediated drought stress alleviation in fodder soybean remain poorly understood. In this study, we demonstrated that exogenous SLs application not only enhanced photosynthetic parameters and chlorophyll content but also improved drought tolerance through multiple mechanisms: regulating stomatal closure, accumulating osmoregulatory substances, and enhancing antioxidant capacity. Integrated transcriptomic analysis and subsequent validation revealed that SLs augment drought tolerance by modulating phytohormone signaling pathways, particularly the abscisic acid (ABA) signaling pathway. Furthermore, weighted gene co-expression network analysis (WGCNA) identified GmPP2C56 as a key candidate gene, whose pivotal role in drought tolerance was functionally validated. Our results demonstrate that GmPP2C56 significantly enhances drought tolerance by negatively regulating ABA signaling. This investigation provides a theoretical foundation for improving plant drought tolerance through exogenous hormone application and proposes innovative strategies for fodder soybeans breeding and cultivation under arid conditions.