Heat shock transcription factors （HSFs） play crucial roles in plant growth and development， as well as in responses to biotic and abiotic stresses. In this study， we identified the MruHSF gene family in Medicago ruthenica using genomic data and conducted bioinformatic analyses. The expression patterns of MruHSF gene under drought stress were comprehensively analyzed through transcriptomic data and quantitative real-time PCR （qRT-PCR）， preliminarily exploring their potential roles in drought stress responses. The results showed that 27 MruHSF family members， with encoded proteins ranging from 97 to 505 amino acids （aa）， isoelectric points （pI） between 4.64 and 8.72， and molecular weights of 10 998.3 to 55 296.45 Da. Except for three unassigned gene， the remaining MruHSF genes were distributed across eight chromosomes. Phylogenetic analysis classified them into three evolutionary clades. Conserved motif analysis revealed that all MruHSF proteins except MruHSF02， MruHSF03， and MruHSF27 contained Motifs 1， 2， and 4， which were highly conserved in M. ruthenica HSF protein. Additionally， multiple cis-acting elements related to hormone response， light response， and abiotic stress were identified in the promoter regions of MruHSF genes. Expression analysis shows that MruHSF01， MruHSF08， MruHSF13， MruHSF16， and MruHSF22 exhibited significant differential expression under drought stress， suggesting their potential roles in the drought response mechanism of M. ruthenica.
This study focused on root tips from four forage species in the Poaceae （Gramineous） family， including three accessions of Leymus chinensis （No. 16， No. 22 and No. 45）， one of Elytrigia repens （L2）， two of Leymus secalinus （Q16 and D51）， and three of Psathyrostachys juncea （X8， X19 and P24）， with three individual plants examined per accession. The effects of sampling time， pretreatment reagents， and pretreatment time on chromosome preparation were investigated by the conventional root tip squashing method. Additionally， karyotype analysis and phylogenetic analysis were conducted. The results showed that： （1） The optimal sampling time was 9：00 to 11：00， with the highest frequency of both division cells and metaphase cells. A 36-hour pretreatment with ice-water mixture treatment significantly increased the proportion of metaphase cells and demonstrated wider applicability. High-quality chromosome preparation with better dispersion were obtained from root tips subjected to hydrolysis in 1 mol hydrochloric acid （HCl） for 20 min， soften in 45 % acetic acid for 60 min， and hypotonic in distilled water for 30 min. （2） The karyotype formulas of Leymus chinensis accessions 16， 22 and 45 were 2n = 4x = 28 = 22m （1SAT） + 6sm， 2n = 4x = 28 = 20m （2SAT） + 8sm and 2n = 4x = 28 = 22m （4SAT） + 6sm， respectively. Those of Elytrigia repens L2 and Leymus secalinus accessions Q16 and D51 were 2n = 4x = 28 = 22m （2SAT） + 6sm， 2n = 4x = 28 = 24m （4SAT） + 4sm （2SAT） and 2n = 4x = 28 = 24m + 4sm， respectively. Psathyrostachys junceav accessions P24 is 2n = 2x = 14 = 12m + 2sm and X8 is 2n = 2x = 14 = 10m + 4sm， and that of Psathyrostachys juncea X19 is 2n = 2x = 14 = 10m + 4sm. （3） All accessions exhibited a 2A karyotype. Psathyrostachys juncea X19， with the largest average arm ratio and karyotype asymmetry coefficient， was identified as the most highly evolved. In contrast， Elytrigia repens L2 was the least evolved. Accessions No.16 and No.45 of Leymus chinensis， and accessions No.Q16 and No.D51 of Leymus secalinus， showed closer genetic relationships within their respective speices.
Salt stress is one of the most critical abiotic factors limiting plant growth and development. An in-depth understanding of the molecular mechanisms underlying salt tolerance in forage grasses is essential for the improvement of saline-alkali soils and the breeding of salt-resistant varieties. In this study， Festuca rubra L. was subjected to a series of salt concentration gradients to determine the concentration most sensitive to root response， which was identified as 100 mmol/L NaCl. Based on this， F. rubra roots exposed to 100 mmol/L NaCl were analyzed using RNA-Seq technology to elucidate transcriptomic changes under salt stress. A total of 43 091 differentially expressed genes （DEGs） were identified compared with the control group， including 16 486 significantly upregulated and 26 605 significantly downregulated genes. Gene Ontology （GO） enrichment analysis revealed that these DEGs were primarily enriched in intracellular signal transduction， protein transport， cytosol and GTPase activity. KEGG enrichment analysis showed that the DEGs were mainly involved in metabolic pathways such as the mitogen-activated protein kinase （MAPK） signaling pathway， endoplasmic reticulum protein processing， and the tricarboxylic acid （TCA） cycle. Within the MAPK signaling pathway， genes encoding MAPKs related to salt stress resistance were upregulated in F. rubra roots. Moreover， several transcription factor families， including C2H2， bHLH， NAC， MYB， WRKY， and bZIP， exhibited differential expression under salt stress， with members of the C2H2 family showing particularly strong responses. In conclusion， under 100 mmol/L NaCl stress， F. rubra roots primarily respond by upregulating MAPK gene expression， activating the MAPK signaling pathway， and regulating the activity of key transcription factors to enhance osmotic adjustment and salt tolerance.
In order to improve the forage yield and quality of degraded alfalfa grassland in the semi-arid region of Ningxia， this study was conducted using a single-factor randomized block design to investigate the effects of different diammonium phosphate （DAP） application rates （0， 75， 150， and 225 kg/hm2） on the production performance and forage quality of alfalfa. The results showed that application of DAP significantly increased alfalfa plant height， branch number， and hay yield， while decreasing neutral and acid detergent fiber contents. Among these treatments， 150 kg/hm2 fertilization treatment yielded the highest two-year average plant height （79.05 cm）， hay yield （9774.50 kg/hm2）， crude protein yield （2005.31 kg/hm2）， stem phosphorus content （0.20%）， leaf phosphorus content （0.24%）， and phosphorus uptake content （21.57 kg/hm2）. 75 kg/hm2 treatment recorded the highest phosphorus use efficiency （PUE）， with a mean PUE of 8.70% across both years. Structural equation model （SEM） revealed highly significant （P<0.001） direct positive effects of plant height on phosphorus content， branch number on hay yield， and hay yield on phosphorus uptake content. The fitted equations predicted that the maximum yield potential of alfalfa was 9789.59 kg/hm2 for hay yield and 2005.56 kg/hm2 for crude protein when average DAP application rates were 149.54 kg/hm2 and 148.55 kg/hm2 over the two years. Therefore， the optimum DAP application rate for degraded alfalfa grassland in the semi-arid areas of Ningxia was 150 kg/hm2.
Mowing is a common management and utilization method in grasslands. Understanding the ecological adaptive strategies of plant to mowing disturbance is the prerequisite for scientific implementation of mowing management. This study was conducted using a pot controlled experiment to investigate the effects of three mowing intensities on the functional traits and compensatory growth of Cynodon dactylon and Lolium perenne. The results showed that with the increase of mowing intensity， plant height， leaf area， root length， and root surface area of both C. dactylon and L. perenne decreased significantly. After 15 days of mowing， the tiller number of C. dactylon significantly increased under moderate and high mowing intensities， while mowing significantly increased the growth rate of both species. The aboveground biomass of both C. dactylon and L. perenne reached the peak under light mowing intensity， which was significantly higher compared with that of the control. The specific root length of C. dactylon， and the specific leaf area and specific root length of L. perenne were significantly decreased with the rising mowing intensities. The compensation index of C. dactylon was the highest under light mowing， whereas L. perenne had the highest compensation index under moderate mowing. Both species demonstrated compensatory growth in plant height under their respective mowing intensities， reaching overcompensation levels. Based on the integrated responses of traits including tiller number， growth rate， biomass and its allocation， post-mowing response of C. dactylon primarily is characterized by increases in tiller number and growth rate， whereas under light to moderate mowing， L. perenne exhibited increased aboveground biomass， a reduced root：shoot ratio， and higher growth rates during late growth. This suggests that the two species may achieve compensatory growth through different trait adjustments.
This study investigated the effects of variety and planting density on the agronomic traits and yield of silage maize （Zea mays）， and aimed to identify optimal variety-density combinations to alleviate the silage forage supply-demand imbalance in Yuyang District， Shaanxi Province. Growth characteristics and yield performance of 10 varieties were evaluated under three planting densities （82 500， 90 000， and 97 500 plants/hm2）， and comprehensive evaluation was conducted using Grey Relational Analysis （GRA）. Results showed that variety had a significant effect on plant height （P<0.01）， with the plant heights of both Xianda 6331 and Zhongnongda 787 exceeding 320 cm. Both the leaf area index and light interception rate increased significantly with increasing planting density （P<0.01） and were positively correlated with each other （P<0.001）. The fresh forage yield was the highest under 90 000 plants/hm2. Comprehensive analysis with GRA identified varieties Zhongnongda 787， Lilong 915， and Jingke 627 as the top varieties. In conclusion， an optimal planting density of 90 000 plants/hm2 is recommended for Yuyang District， with Zhongnongda 787 and Lilong 915 as suitable varieties. This provides theoretical and technical support for efficient silage maize production in this region.
To elucidate the drying dynamics and nutrient depletion in alfalfa （Medicago sativa） following harvest and to identify the major environmental factors influencing hay drying， alfalfa samples from different cutting stages were collected at regular intervals to measure plant water content and key nutrient components. Concurrently， meteorological parameters and soil moisture were monitored to examine the relationships among drying rate， nutrient variation， and primary environmental factors during the drying process. The results showed that： （1） The physiological drying stage accounted for 20.83%—47.75% of the total natural drying process， while the biochemical drying stage had a greater impact on overall drying time. During the physiological drying stage， drying rates followed the order： leaves>whole plant>stems， whereas during biochemical drying stage， the order was stems>whole plant>leaves. （2） The contents of crude protein （CP）， water-soluble carbohydrates （WSC）， ether extract （EE）， and relative feed value （RFV） decreased throughout the drying process （including the beginning and end of drying， and both physiological and biochemical drying stages）， while crude ash， neutral detergent fiber （NDF）， and acid detergent fiber （ADF） contents increased. The magnitude of nutrient loss or accumulation showed a non-linear change with drying duration. Losses of EE， RFV， WSC or gains of crude ash， NDF， and ADF， mainly occurred during the physiological stage， with loss rates of 56.17%—68.76% and gain rates of 51.05%—59.52%. CP loss primarily occurred during the biochemical drying stage， accounting for 62.00% and 55.21% of total loss. （3） Air temperature， solar radiation intensity， and wind speed were identified as the keys environmental factors influencing the drying rate of alfalfa， while air temperature， wind speed， relative air humidity， and soil water content of 0—10 cm depth were the primary factors affecting nutrient composition. Higher air temperature， solar radiation， and wind speed accelerated alfalfa drying and reduced CP， EE and RFV loss rates. Both air temperature and drying rate were significantly （P<0.05） positively correlated with crude ash content， while wind speed showed the opposite trend.
As an important leguminous green manure crop， Astragalus sinicus plays a crucial role in improving soil physicochemical properties and enhancing crop yield and quality. To investigate the diversity of seed-borne fungi associated with A. sinicus， this study conducted isolation and identification analyses on seeds from three varieties： Xiangzi No. 1 （XZ）， Xinzi No. 2 （HX）， and Yijiangzi （YJ）. Using traditional isolation and culture methods， a total of 13 fungal species belonging to 13 genera were identified. Among them， Penicillium sp. was predominant， accounting for 42.5%， 27.0%， and 17.5% of isolates from XZ， HX， and YJ， respectively. 3 species were uniquely isolated from XZ and HX， and Fusarium oxysporum and Mucor circinelloides from both XZ and YJ. High-throughput sequencing showed that the dominant fungal taxa associated with the seeds of the three A. sinicus varieties were Ascomycota， Basidiomycota， and unclassified fungi， collectively comprising 90.29% of the total fungal community. A total of 72， 53， and 64 genera were detected in XZ， HX， and YJ， respectively， with Alternaria and Fusarium being among the common genera. Notably， several genera identified through high-throughput sequencing （Penicillium， Fusarium， Chaetomium， and Cladosporium） were also detected by traditional culture methods， validating the consistency between the two approaches. Compared with traditional isolation， high-throughput sequencing greatly expanded the detected diversity of seed-associated fungal. In conclusion， A. sinicus seeds harbor a highly diverse fungal community， including common pathogenic genera such as Penicillium， which can cause storage mold， and Alternaria， which is known to cause field diseases.
In order to explore potassium-solubilizing microbial resources and investigate their effects on alfalfa （Medicago sativa） growth， this study isolated and screened potassium-solubilizing bacteria （KSB） with strong potassium-solubilizing ability from the rhizosphere soil of alfalfa using selective media. The potassium-solubilizing， phosphate-solubilizing， and indole-3-acetic acid （IAA）-producing capabilities of these strains were measured， and their identities were confirmed via 16S rRNA gene sequencing. Subsequently， pot experiments were conducted using the selected superior strains to validate their impact on alfalfa growth. The results demonstrated that 21 KSB strains were isolated and screened from the alfalfa rhizosphere， among which 10 exhibited potassium-solubilizing activity， with solubilized potassium levels ranging from 1.57 to 7.96 μg/mL and solubilization rates ranging from 12.07% to 57.50%. Five strains （jk6-5、jk20-1、jk20-2、jk20-3 and jk20-8） with high potassium-solubilizing activity also demonstrated IAA production and phosphate-solubilizing abilities. Their IAA secretion levels ranged from 9.60 to 11.77 μg/mL， while inorganic phosphate solubilization ranged from 2.84 to 173.96 μg/mL， and organic phosphate solubilization from 35.34 to 62.55 μg/mL. Based on 16S rRNA gene sequencing， strains jk20-8， jk20-1， and jk20-2 were identified as Pantoea ananatis， strain jk20-3 belonged to the Paenibacillus hordei group， and strain jk6-5 was identified as Priestia megaterium. Inoculation of the superior strains jk20-8， jk20-3， and jk6-5 into alfalfa significantly increased plant height， root length， aboveground biomass， underground biomass， and nitrogen （N）， potassium（K）， and phosphorus （P） contents in plants. Additionally， soil available N， available P， available K， and organic matter contents were enhanced， with strain jk20-8 exhibiting the most pronounced growth-promoting effects. In conclusion， the potassium-solubilizing strain jk20-8 serves as a promising candidate for developing potassium-solubilizing microbial fertilizers.
Rational allocation of grassland tenure rights is essential for implementing the grass-livestock balance system and protecting grassland ecosystems， as herder households'capital endowments influence their tenure arrangements. Based on survey data from Xinjiang herders， this study employs the entropy method and multinomial Logit model to analyze the selection mechanism of grassland tenure allocation （individual， joint， or cooperative） from dual perspectives of capital endowment level and structure. The results indicated that significant heterogeneity in capital endowments among herder households. In terms of endowment level， social capital endowment （0.108） was highest， whereas natural capital endowment （0.037） was lowest. Structurally， social endowment-type households constitute the majority （51.05%）. The influence of aggregate capital endowment on grassland tenure allocation followed a descending pattern： individual households > joint households > cooperatives. At the level dimension， human and natural capital endowments significantly promote individual tenure， whereas social capital most strongly influences joint tenure. At the structure dimension， tenure allocation is more dependent on human， natural， financial， and social endowment types. Enhancing herder capital stocks and optimizing endowment allocation can facilitate rational tenure allocation， thereby improving livelihood resilience and grassland ecological sustainability.
Smart prataculture represents a vital component of modern agriculture and serves as a key strategy for promoting sustainable agricultural development and advancing the initiative “Big Food View” in China. As global challenges such as climate change and land degradation intensify， traditional grassland management models are increasing unable to meet the requirements of modernization. The integration of artificial intelligence （AI） technologies presents unprecedented opportunities for the advancement of prataculture， greatly enhancing the efficiency， precision， and intelligence of grassland management. AI-driven smart prataculture employs cutting-edge technologies such as machine learning， deep learning， big data analytics， and the Internet of Things （loT）. Through comprehensive data collection and analysis， these technologies enable real-time monitoring， precise prediction， and adaptive management of grassland growth， resource allocation， and livestock production. While the application of AI demonstrates substantial potential in optimizing grassland productivity， ecological restoration， and livestock health monitoring， significant challenges remain in data collection， technological dissemination， infrastructure development， talent cultivation， economic feasibility， and policy support. In the future， continued innovation in AI technologies and the integration of interdisciplinary approaches are expected to accelerate the intelligent transformation of prataculture in China. This evolution will promote comprehensive intelligence， precision， and transparency across the entire industry chain， from production and ecological protection to resource utilization and market systems， thereby providing new insights for the sustainable development of smart agriculture.
Against the backdrop of China’s “dual-carbon” strategy and the advancement of ecological civilization， scientific assessment of the ecosystem service values and the realization of ecological product value have becomeacritical approach to harmonize ecological protection and economic development. As the dominant type of grassland ecosystem in China， temperate grasslands play crucial roles in carbon sequestration， water conservation， wind erosion control， and biodiversity maintenance. This article systematically reviews the research progress and methodological framework in economic valuation of temperate grassland ecosystem services， both in China and internationally. The applicability and limitations of major models were compared， and deficiencies in current Chinese research regarding data precision， parameter localization， service coverage， and policy integration were analyzed. This review proposes that future research should focus on constructing multi-scale integrated assessment frameworks， improving model localization and data sharing mechanisms， and strengthening the integration between assessment results and policies such as ecological compensation， GEP accounting， carbon trading， etc.， thereby forming the closed-loop mechanism of “Assessment-Accounting-Compensation-Feedback”. This study aims to provide theoretical foundation and decision support for valuing temperate grassland ecosystem services and realizing the value of ecological products.
Setaria viridis （L.） P. Beauv， a widely adaptable herbaceous plant distributed throughout China， possesses significant ecological and forage value. Due to its notable stress tolerance and its role as an important model plant， Setaria viridis has attracted wide interest in recent years. This article reviews research findings on the biological characteristics， genetic diversity， ecological value， and cultivar development of Setaria viridis， and offers perspectives for further research. It will provide theoretical references for the development， utilization， and breeding of new Setaria viridis varieties.
