In order to explore the alleviation effect of exogenous plant growth regulators （ PGRs ） on the growth of reed canarygrass （Phalaris arundinacea L.）under salt， waterlogging and salt-waterlogging combined stress， reed canarygrass at tillering stage was used as material， and different concentrations of ethephon （ETH）， indole-3-acetic acid （IAA）， spermidine （Spd） and γ-aminobutyric acid （GABA） were applied under three stresses， and the related physiological indexes were determined. The results showed that all three stresses significantly inhibited the growth of reed canarygrass， and the application of PGRs could effectively alleviate the stress damage. Among them， the application of 80 mg·L^-1 ETH under salt stress had the best mitigation effect， the Pro content was significantly increased by 20.36% and the MDA content was decreased by 34.52% compared with the stress group. Under flooding stress， 60 mg·L^-1 ETH was the best， and the activities of SOD and CAT were significantly increased by 105.83% and 40.07%， respectively. Under combined stress， 10 mmol·L^-1 GABA had the best effect， chlorophyll content increased by 30.30%， MDA decreased by 43.75%， and CAT increased by 23.31%（P<0.05）. In summary， the application of PGRs can alleviate stress damage by enhancing osmotic adjustment and antioxidant capacity and reducing membrane lipid peroxidation， and the type and concentration of optimal regulators vary depending on the type of stress.

Grasses in Pennisetum genus are important high-quality forages in tropical and subtropical regions， characterized by high biomass， strong stress tolerance， and excellent feeding value. They serve as a key resource to alleviate the shortage of forage supply in China. To date， 17 Pennisetum cultivars have been registered in China， most of which are adapted to the southern ecological zones， while there is a lack of stress-tolerant and high-yielding cultivars in northern China， highlighting an urgent need for breeding elite new varieties. This paper reviewed the research progress in conventional breeding techniques， including introduction and domestication， cross breeding， and mutation breeding， as well as molecular breeding approaches such as molecular marker-assisted breeding and genetic engineering. It also analyzed the existing problems， including the shortage of self-incompatible lines， low efficiency of distant hybridization， and an underdeveloped molecular breeding system. Finally， the paper discussed prospects for germplasm resource exploration， optimization of breeding objectives， and application of new technologies， aiming to provide a reference for genetic improvement and industrial development of Pennisetum forages.

To clarify the key indicators for evaluating the cold tolerance of perennial forage Pennisetum spp.， a total of 42 Pennisetum germplasms were used as experimental materials in this study. Combining indoor low-temperature simulation with field trials， we analyzed the growth and physiological characteristics at the seedling stage and full growth period， overwintering rate， and their correlations of Pennisetum. The results showed that： Low-temperature stress significantly reduced seedling dry matter accumulation by 41.55% and plant height by 11.53%. The malondialdehyde （MDA） content in leaves and tiller nodes increased significantly by 90.43% and 108.48%， respectively. Osmotic regulation substances and antioxidant enzyme activities exhibited distinct responses to low temperature. A total of 9 indicators including soluble sugar and MDA contents in tiller nodes and leaves were screened out by principal component analysis to characterize cold tolerance at the seedling stage. Four accessions including ‘Sumu No.2’ ‘Guimu No.1’， Hybrid Pennisetum No.7 and Sweet Elephant Grass exhibited strong cold tolerance with an above 75% overwintering rate， while WQ Hybrid Pennisetum and Chinese Forage Grass showed weak cold tolerance with a below 50% overwintering rate.The overwintering rate was significantly negatively correlated with MDA content in tiller nodes， and significantly positively correlated with bud soluble sugar content. Soluble sugar and MDA contents were crucial indicators for characterizing the cold tolerance of Pennisetum. This study provides a theoretical foundation for the breeding and innovation of new Pennisetum germplasms with high cold tolerance.

Based on multi-year， multi-site field trials combined with physiological and photosynthetic measurements， in this study we evaluated the cold tolerance and production adaptability of a new Pennisetum purpureum line ‘Yunmu No.1’（YM-1）， in comparison with two local predominant cultivars， P. purpureum ‘Dehong’（DH） and P. purpureum ×P. typhoideum ‘Reyan No.4’（RY-4）. The results indicated that the cold tolerance of the tested materials， in descending order， was YM-1>DH>RY-4. YM-1 had the lowest semi-lethal temperature （LT₅₀） of -5.413℃. Under low-temperature stress， its superoxide dismutase （SOD） activity increased significantly by 237.12%， while malondialdehyde （MDA） content increased only marginally by 1.25%， indicating that it primarily responds to low temperature through an antioxidant mechanism. In contrast， DH mainly responded to low temperature by accumulating osmotic adjustment substances， including soluble sugar （+76.77%） and proline （+60.24%）. RY-4 exhibited weak responses in both antioxidant and osmotic adjustment mechanisms， with an MDA increase of 43.07%. The freezing injury index during the first-frost period was consistent with the above physiological ranking. At an altitude of 2350 m， YM-1 showed the highest sprouting rate （50.4%； i.e.， the proportion of stumps with newly sprouted tillers） and regreening rate （43.0%）. Its three-year average hay yield was 6.1% and 11.3% higher than those of DH and RY-4， respectively. In conclusion， ‘Yunmu No.1’ possesses both strong cold tolerance and high and stable yield potential， making it suitable for cultivation in complex environments below 2000 m elevation on the Yunnan Plateau. A comprehensive evaluation method based on LT₅₀， MDA content， SOD activity， field freezing injury phenotype， and natural overwintering capacity can be used for the systematic identification of cold tolerance in Pennisetum purpureum.

The seed yield and quality of the leguminous forage alfalfa （Medicago sativa L.） are significantly influenced by water and fertilizer management. This study aimed to investigate the effects of different water and phosphorus fertilizer treatments on seed yield and seed quality of alfalfa. The experiment was designed to combine treatments with different irrigation levels （600， 900， and 1200 m³·hm^-2） and phosphorus fertilizer rates （100， 200， and 300 kg·hm^-2）. Seed yield， yield components， soluble protein content， and starch content were measured. Additionally， multispectral information of 19 bands was acquired， and an nCDA-CNN model was constructed to evaluate the potential of multispectral image technology for seed detection under different water and fertilizer treatments. The results showed that the appropriate water and phosphorus fertilizer application significantly increased seed yield， protein content， and starch content （P<0.05）. Among all treatments， the combination of 600 m³·hm^-2 irrigation and 200 kg·hm^-2 phosphorus fertilizer achieved the highest seed yield （885.44 kg·hm^-2）， representing an increase of 287.96 kg·hm^-2 compared to the control. Higher soluble protein and starch contents of seeds were observed under the treatment with 600 m³·hm^-2 irrigation and 100 kg·hm^-2 phosphorus fertilizer. Path analysis indicated that the number of seeds per pod had a greater influence on seed yield. Multispectral image analysis revealed that the nCDA-CNN model accurately predicted alfalfa seeds subjected to different water and fertilizer treatments， with a recognition accuracy of 95%. This provides a high-throughput， non-destructive detection method for alfalfa seed production. Optimized water and fertilizer manag-ement can significantly enhance alfalfa seed production. Multispectral image technology combined with deep learning models holds important application prospects for quality detection and sustainable development in the grass seed industry.

The mechanisms by which the root systems of invasive plants respond to nutrient and water deficiency remain poorly understood.In this study， we conducted a paired comparison between Asteraceae invasive plants （Senecio vulgaris， Symphyotrichum subulatum） and native plants （Senecio scandens， Aster ageratoides）， examined their root traits， Arbuscular Mycorrhizae Fungi （AMF） colonization rate， and biomass performance under normal and water and nutrient deficient conditions. The results showed that although both water and nutrient deficiencies reduced aboveground biomass and AMF colonization rates by more than 20% on average across all species， the invasive plants exhibited significantly greater aboveground biomass and higher AMF colonization rates compared to native plants. Nutrient deficiency significantly increased specific root length and specific root surface area， promoted root length and surface area of roots with diameters <0.5 mm， and reduced root tissue density in native plants， with average changes ranging from 8.23% to 32.64% in native plants. However， invasive plants showed opposite or no significant changes. With the exception of Symphyotrichum subulatum， water deficiency enhanced specific root length， specific root surface area， root length and surface area across all diameter classes， while reducing root tissue density in the other species. In summary， the invasive plants demonstrated stronger stress resistance. Under nutrient stress， invasive plants relied more on maintaining high AMF colonization， whereas native plants primarily depended on adjustments in root morphology. Under water deficiency， both invasive and native plants exhibited similar root adaptation strategies， but the invasive plants maintained higher AMF colonization. Combined stress responses tended to resemble those under single nutrient deficiency. These findings are important for elucidating the mechanisms underlying the adaptation of invasive plants to nutrient- and water-deficient environments.

To address production problems such as low seed setting rate， in this study， a total of 300 Leymus chinensis accessions were evaluated across three consecutive years of field trials and systematically measured their four growth traits： Plant Height of Reproductive Branch at Heading Stage （PH_RBHS）， Plant Height of Reproductive Branch at Maturity Stage （PH_RBMS）， Leaf Length （LL）， Leaf Width （LW）， and eight seed setting-related traits： Spike Weight （SW）， Spike Length （SL）， Number of Spike Nodes （NSN）， Seed Setting Rate （SSR）， Number of Spikelets （NS）， Floret Number per Spikelet （FNPS）， and Seed Number per Spike （SNPS）. Diversity analysis and cluster analysis jointly revealed a rich genetic background within the population： the coefficient of variation ranged from 10.73% to 51.86%， and the genetic diversity index ranged from 1.853 to 2.068； the 300 accessions could be classified into four distinct clusters. Correlation analysis indicated that seed setting rate （SSR） was correlated to varying degrees with 11 traits， such as Spike Weight （SW）， Spike Length （SL）， and Seed Number per Spike （SNPS）. The first four principal components accounted for 79.26% of the total variance， effectively capturing most of the information of the original traits. Finally， based on the best linear unbiased estimate （BLUE） of phenotypic data， a comprehensive evaluation was conducted using a membership function analysis that integrated heading rate （HR） and seed setting rate （SSR）， and 50 elite accessions were identified. This study provides support for further gene mining， genotype-phenotype association analysis， and molecular breeding.

To screen Pennisetum forage varieties suitable for cultivation in the Chengdu Plain and surrounding ecological zones and clarify their production performance， nutritional quality， and cold resistance， Using nine elephant grass and hybrid Pennisetum varieties （lines） as materials， a three-year field experiment was conducted in Chongzhou. Agronomic traits， yield， nutritional quality， winter survival rate， and physiological indicators under low-temperature stress were measured. Comprehensive evaluation was performed using the membership function method and grey correlation degree analysis. GMY had the highest fresh yield （203 121 kg·hm^-2）， followed by CY1 （183 138 kg·hm^-2） and JMLC （168 798 kg·hm^-2）， respectively. CN005 had the highest soluble sugar content （91.19 mg·g^-1）. GM1 had the highest crude protein （6.82%） and crude fat （1.03%） content， indicating the best nutritional quality. CY1 achieved a winter survival rate of over 95% in low-altitude areas such as Chongzhou and Xinjin， and also showed stable performance in high-altitude cold areas such as Meigu， Sichuan， ranking first in the comprehensive evaluation of cold resistance physiology. GMY was suitable for promotion as a high-yielding variety， GM1 was suitable for silage， and CY1 possessed strong cold resistance， making it suitable for promotion in high-altitude areas. This study provides a scientific basis for variety selection and cold resistance mechanism analysis of Pennisetum in the Chengdu Plain and similar ecological zones.

To investigate the effects of various additives on the quality and microbial diversity of mixed silage prepared from tea stems （Camellia sinensis） and broad bean straw （Vicia faba）， mixed at a ratio of 2：8， the experiment comprised one control group （CK） and four treatment groups： T₁ （with Lactobacillus acidophilus added）， T₂ （with Lactobacillus plantarum added）， T₃ （with Bacillus subtilis added）， and T₄ （with a mixture of Lactobacillus plantarum and Bacillus subtilis added）， with three replicates per group. After 60 days of ensiling， the sensory quality， ensiling quality and microbial diversity were analyzed. Results indicated that all the additive treatments significantly improved sensory scores compared to CK （P<0.05）. Compared with CK， all treatment groups exhibited significantly higher concentrations of water-soluble carbohydrates （WSC） and significantly lower pH values （P<0.05）. Crude protein content increased significantly in T₂， T₃， and T₄ （P<0.05）， while the lactate-to-acetate ratio was significantly elevated in T₁， T₂， and T₄ （P<0.05）. Microbial profiling revealed a significant reduction in the relative abundance of certain Lactobacillus operational taxonomic units （OTUs） in T₁， T₂， and T₄—suggesting potential niche competition or functional redundancy among lactic acid bacteria （P<0.05）. Notably， the T₄ group displayed significantly greater phylogenetic diversity （PD_whole_tree index） and alpha diversity （Shannon index） than CK （P<0.05）. Furthermore， principal coordinate analysis indicated that bacterial community composition in T₁， T₂， and T₄ correlated positively with both WSC content and relative feed value （RFV）. Collectively， these findings demonstrate that microbial additives enhance silage fermentation quality and reshape the silage microbiome； moreover， distinct additives confer complementary benefits across key quality and ecological metrics.

The symbiont formed by legumes and rhizobia plays a crucial role in the nitrogen cycle， and root exudates significantly affect the nodulation process. The pretreatment and detection methods for metabolites of rhizobia from Lespedeza daurica have not been systematically optimized. In this study， the extraction efficiency of rhizobial metabolites was improved by optimizing pretreatment conditions， including ultrasonic temperature （A）， ultrasonic time （B）， derivatization temperature （C）， and derivatization time （D）. Single-factor experiments were used to determine the ranges of detection conditions， followed by a four-factor， three-level Box-Behnken response surface methodology （ultrasonic temperature： 30-40℃ ultrasonic time： 7-11 min derivatization time： 20-100 min derivatization temperature： 50-90℃） for optimization design. A quadratic regression model was established to determine the optimal conditions and verify their reliability. The optimal conditions determined by single-factor experiments were ultrasonic temperature 35℃， ultrasonic time 9 min， derivatization temperature 70℃， and derivatization time 60 min. The response surface model （R²=0.9035） showed that the linear terms A and C， the interaction term CD， and the quadratic terms A²， C²， and D² had extremely significant effects on the results （P<0.01）， while the interaction term AD had a significant effect （P<0.05）. After optimization， 145 metabolites were detected， representing an increase of 198.60% compared with the pre-optimization level， with an error of 3.5%. Methodological validation showed that the peak area RSD of the internal standard L-2-chloro-phenylalanine was 8.2% （n=6）， and the signal-to-noise ratio （S∶N） was 9.9∶1， which met the requirements for metabolomic detection. This study established a pretreatment method for the detection of metabolites from rhizobia of Lespedeza daurica， providing a technical basis for their extraction and analysis.