Background: The Songnen Plain in China contains soda saline–alkaline soil, wherein salinity and alkalinity severely constrain crop productivity. Alfalfa (Medicago sativa L.) is a forage legume that has adapted to moderate saline–alkaline conditions, but how its rhizosphere microbial community facilitated this adaptation remains unclear. Methods: Using 16S rRNA gene sequencing, we compared alfalfa rhizosphere bacteria in saline–alkaline soil (AS) and control soil. Bacteria isolated from AS were screened for plant growth-promoting traits, with the most effective strains validated in pot experiments involving 50 mM NaHCO₃. Results: Compared with the control soil bacterial community, the AS bacterial community was significantly enriched with Methylomirabilota and unclassified bacteria (phylum level), with the genus RB41 identified as the most discriminative biomarker. Gene functions predicted using PICRUSt2 reflected the responsiveness of this community to environmental stressors. Inoculations with Pseudomonas laurentiana strain M73 and Stenotrophomonas maltophilia strain M81, which were isolated from AS, significantly improved alfalfa growth and health under NaHCO₃ stress. Conclusions: Saline–alkaline conditions in the Songnen Plain reshape the alfalfa rhizosphere bacterial community, enriching for specific taxa and potentially enhancing microbial functions associated with stress resistance. Strains M73 and M81 can effectively promote stress tolerance, making them useful microbial resources for improving soil conditions.

Fragaria vesca L., a widely distributed model species, serves as a key resource for studying the evolution and genetics of the Fragaria genus. Research has shown that R2R3-MYB transcription factors are crucial for plant growth and development. However, their specific role in cold resistance in F. vesca is not well understood. In this study, we used the latest genome data for the strawberry (F. vesca v6.0). We performed a genome-wide identification of the R2R3-MYB gene family in F. vesca. We identified a total of 106 R2R3-FvMYBs. Based on their predicted functions in plants, we classified these genes into 25 distinct subfamilies. We then conducted a comprehensive bioinformatics analysis of this family. We performed a detailed examination of the R2R3-FvMYBs structures and physicochemical properties. This analysis provided five key parameters for each protein: molecular weight, the number of amino acids, theoretical isoelectric point, grand average of hydropathicity (GRAVY), and instability index. Gene duplication analysis suggested that segmental duplications were a primary driver of the proliferation of this gene family. Promoter cis-acting element prediction revealed that a large proportion of R2R3-FvMYBs possess elements predominantly associated with phytohormone responsiveness and biotic/abiotic stress responses. Quantitative real-time reverse transcription PCR (qRT-PCR) results confirmed that the expression levels of several R2R3-FvMYBs were upregulated under cold stress. Furthermore, compared to wild-type controls, the overexpression of FvMYB103 in Arabidopsis thaliana enhanced cold tolerance, accompanied by increases in the relevant physiological indices. Collectively, these findings support further investigation into R2R3-MYB gene family to directly assess their contribution to cold resistance.

Global agriculture faces the dual challenges of resource constraints and international competition, making the transition from quantitative expansion to quality upgrading a central imperative. While trade competitiveness is widely considered a key driver of agricultural transformation, the pathways and mechanisms through which it influences agricultural quality upgrading are far more complex than conventionally understood. Against this backdrop, this study constructs a moderated nonlinear mediation theoretical framework. Empirical analysis based on China’s provincial panel data (2014–2023) yields three key findings: (1) Trade competitiveness exerts a significant inverted U-shaped effect on high-quality agricultural development, revealing a dynamic trade-off between “competitive escape” and “competitive suppression.” (2) Optimization of the Agricultural Sectoral Structure serves as a mediating pathway, and this mediation itself exhibits nonlinear characteristics, further underscoring the nuanced nature of “structural dividends.” (3) Regional innovation capacity significantly moderates the latter stage of this pathway (from Optimization of the Agricultural Sectoral Structure to quality development). Viewed through the lens of appropriate technology theory, a robust regional innovation system can deploy context-appropriate technologies and knowledge, thereby mitigating the potential adverse impacts of agricultural structural transformation on quality-related outcomes. This research thus provides a new strategic framework for achieving sustainable, high-quality agricultural growth.

Agricultural green total factor productivity is central to reconciling agricultural growth with increasingly binding resource and environmental constraints. Digital inclusive finance may facilitate this transition by relaxing financing constraints and expanding access to productive technologies, yet its contribution to agricultural green productivity remains insufficiently understood. To address this gap, this study develops an analytical framework that identifies technological innovation as a potential mediating transmission channel and agricultural mechanization as the threshold condition in the relationship between digital inclusive finance and agricultural green total factor productivity. Drawing on a balanced panel of 30 Chinese provinces, the empirical analysis employs a two-way fixed-effects model, mediation analysis, and a panel threshold model to test the proposed relationships. The results yield three main findings. First, digital inclusive finance is positively associated with agricultural green total factor productivity, and this relationship remains robust after robustness checks and endogeneity analyses. Second, mediation analysis provides evidence consistent with a positive mediating role of technological innovation in the relationship between digital inclusive finance and agricultural green total factor productivity. Third, the association between digital inclusive finance and agricultural green total factor productivity exhibits significant nonlinear heterogeneity across agricultural mechanization regimes. The regime-specific analysis further indicates that such heterogeneity is more evident in the relationships involving digital inclusive finance, whereas the relationship between technological innovation and agricultural green total factor productivity does not differ significantly across regimes. These findings clarify the heterogeneous relationships among digital inclusive finance, technological innovation, and agricultural green productivity and provide empirical support for coordinating financial policy with agricultural modernization strategies.