Soil salinization severely threatens global crop production. Understanding the relationship between crop saline–alkaline tolerance physiology and the rhizosphere microbiome, and leveraging beneficial microorganisms to enhance crop stress resistance, holds importance for sustainable agricultural development. This study investigated the physiological and rhizosphere microbial responses of two soybean cultivars with different saline–alkaline tolerance to stress. Under saline–alkaline conditions, the tolerant cultivar exhibited superior physiological performance, including higher chlorophyll content, photosynthetic efficiency, and elevated activities of antioxidant enzymes (SOD, POD, and CAT), alongside reduced oxidative damage (MDA) and greater biomass accumulation. Combined metagenomic and physiological analyses revealed significant correlations of Bradyrhizobium and Solirubrobacter with key physiological indicators, including dry weight, PI_ABS, φ_po, and MDA. The tolerant cultivar selectively enriched distinct marker microbes, such as Bradyrhizobium sp. and Bradyrhizobium liaoningense, in its rhizosphere. We conclude that the tolerant cultivar exhibits strong intrinsic physiological resistance. This resistance is further enhanced by a beneficially assembled rhizosphere microbiome, while the host plant’s physiology remains the dominant factor.

Soybean is rich in protein and oil and serves as the most important legume crop globally. Soybean mosaic virus (SMV) is a severe threat to soybean production worldwide. MutMap, a gene-mapping technology based on map-based cloning and whole-genome resequencing, is utilized to clone key regulatory genes for agronomic traits in plants. However, no relevant studies have reported the cloning of genes resistant to SMV. We used an M3 mutant population derived from ethyl methanesulfonate mutagenesis of Williams 82, and conducted field inoculation experiments involving the SMV-SC3 strain. After field validation, two lines with high resistance to SMV were finally identified. Using MutMap, we initially screened candidate genes for SMV resistance and found that the G-to-A transitions of one candidate resistance gene, Glyma.13G194900, were at base positions 122 and 166. These transitions resulted in the substitution of glycine with glutamic acid (GGA→GAA) and valine with aspartic acid (GTT→GAT), respectively. Transgenic functional validation in soybean showed that the mutant allele of Glyma.13G194900 (designated Glyma.13G194900^M) substantially enhanced resistance to SMV-SC3, in contrast to the wild-type allele, which did not enhance resistance. Our results demonstrate that MutMap can rapidly identify SMV resistance-related genes to provide a genetic resource that accelerates the breeding of new SMV-resistant soybean.

Straw returning is an effective means of improving soil structure and increasing soil organic matter content. However, few studies have been conducted on the effects of corn straw returning on the soil microorganism community in soybean crops. In this paper, taking conventional combined tillage (CT) as a control, the effects of no-tillage with straw mulching (NTS), no-tillage with stubble retention (NT), and deep plowing with straw incorporation (DT) on soil bacterial community under a corn–soybean rotation system were studied. The results showed that the contents of soil total nitrogen, total phosphorus, available phosphorus, the activities of soil urease and acid phosphatase, and soil bacterial richness and diversity in the NTS treatment were significantly higher than those in other treatments. Moreover, the NTS treatment increased the abundance of Acidobacteriota and MND1 (unclassified bacterial genus) in the soil. The number of unique OTUs in the NTS treatment was the greatest (26.67%), with that of the CT treatment being the smallest (7.22%). Redundancy analysis (RDA) revealed that soil total nitrogen, total phosphorus, and available phosphorus are the key driving changes in bacterial community. Consequently, NTS treatment was the optimal approach for both soil fertility improvement and bacterial community optimization. This approach combines straw mulching and no-tillage, which not only exerts the nutrient supply effect of straw but also reduces the impact of soil disturbance on microbial habitats.

Phosphorus inputs play a critical role in modulating microbial dynamics in crop rhizosphere soils, yet their specific effects remain underexplored. This study investigated the impacts of P addition on soil respiration rates, enzyme activities, and microbial communities in maize and soybean rhizosphere soils under a 20-year corn-soybean rotation system. Results demonstrated that P inputs significantly elevated rhizosphere soil respiration rates. In maize, LP treatment yielded the highest initial rate (3.2 times CK on day 0) and maximum rate (1.45 times CK), peaking early (days 0–4). In soybean, HP treatment produced the peak rate, occurring on day 4. Glucosidase activity increased under P treatments, with HP in maize showing values up to 1.5–2 times CK before day 8, and HP in soybean peaking at 1.2 times CK on day 8. Acid and neutral phosphatase activities generally declined initially, reflecting feedback inhibition, while alkaline phosphatase rose early. Microbial community structure shifted markedly. Key taxa like Reyranella and Luteimonas increased with P concentration, while Gp1 decreased. Correlation analysis indicated strong associations; e.g., Proteobacteria positively correlated with acid phosphatase and negatively with neutral phosphatase. These findings underscore the crop-specific responses of rhizosphere microbiomes to P inputs, informing targeted fertilization strategies for enhanced nutrient efficiency and sustainable agriculture.

Phosphorus (P) deficiency severely limits soybean (Glycine max L.) productivity. This study proposed a three-stage screening framework to identify reliable traits and P-efficient genotypes. In Experiment I, percent tolerance to phosphorus deficiency (PTPD) was calculated for ten growth parameters across 98 genotypes under P-deficient and control conditions. Principal component analysis and comprehensive evaluation identified six key indicators in Experiment I, which were subsequently refined to five indicators through further analysis: SPAD at V3 and R1, photosynthetic rate at R1, shoot dry weight at R8, and seed number per plant at R8. Experiment II re-evaluated these traits using 12 contrasting genotypes under three P levels, identifying CN 15 as the most P-efficient and SN 22 as the most P-inefficient. Experiment III further revealed that CN 15 maintained superior PSII performance and exhibited a 26.2% increase in grain P-utilization efficiency under 0 µM KH₂PO₄ treatment. This integrated framework offers a preliminary reference for screening P-efficient soybean genotypes under controlled conditions, pending field evaluation.