Blue light serves as a critical environmental cue regulating Glycine max (soybean) stem morphology, yet the hormonal mechanisms underlying varietal differences remain unclear. Previous studies have highlighted the role of blue light in modulating plant architecture, but the specific hormone interactions driving morphological divergence between soybean varieties remain underexplored. Two soybean varieties with contrasting stem phenotypes—Henong 60 (HN60, tall) and Heinong 48 (HN48, dwarf)—were subjected to 0% (full light) and 30% (shade) transmittance conditions, supplemented with blue light (450 nm, 45.07 ± 0.03 μmol·m⁻²·s⁻¹). Stem anatomical traits (xylem area, cell length), hormone profiles, and proteomic changes were analyzed. Grey correlation analysis quantified relationships between hormone ratios and plant height. Blue light increased soybean stem xylem area and diameter while reducing plant height and cell longitudinal length. This treatment concurrently reduced growth-promoting hormones (gibberellin A₃ (GA₃), indole-3-acetic acid (IAA), brassinolide (BR)) and increased growth-inhibiting hormones (salicylic acid (SA), jasmonic acid (JA), strigolactones (SLs)), thereby inhibiting stem elongation. Although exogenous GA₃ promoted hypocotyl elongation, it failed to counteract blue-light-induced inhibition. Proteomic analysis identified 16 differentially expressed proteins involved in hormone signal transduction pathways. Grey correlation analysis highlighted cultivar-specific hormone ratio impacts: GA₃/JA, GA₃/SA, and BR/SLs significantly influenced HN60 plant height, while GA₃/SLs, IAA/SLs, and BR/SLs were critical for HN48, demonstrating highly significant positive correlations. The differential sensitivity of growth-promoting/inhibiting hormone ratios to blue light drives varietal morphological divergence in soybean stems. This study establishes a hormonal regulatory framework for blue-light-mediated stem architecture, offering insights for crop improvement under light-limited environments.

The redistribution of solar radiation, temperature, soil moisture and heat by topography affects the physical and chemical properties of the soil and the spatial distribution characteristics of crop growth. Analyses of the relationship between topography and these variables may help to improve the accuracy of digital elevation models (DEMs). The purpose of correcting Shuttle Radar Topography Mission (SRTM) data is to obtain high-precision DEM data in cultivated land. A typical black soil area was studied. A high-precision reference DEM was generated from an unmanned aerial vehicle (UAV) and extensive measured ground elevation data. The normalized differential vegetation index (NDVI), perpendicular drought index (PDI) extracted from SPOT-6 remote sensing images and potential solar radiation (PSR) extracted from SRTM. The interactions between topography and NDVI, PDI, and PSR were analyzed. The NDVI, PDI and PSR in June, July, August and September of 2016 and the SRTM were used as independent variables, and the UAV DEM was used as the dependent variable. Linear stepwise regression (LSR) and a back-propagation neural network (BPNN) were used to establish an elevation prediction model. The results indicated that (1) The correlation between topography and NDVI, PSR, PDI was significant at 0.01 level. The PDI and PSR improved the spatial resolution of SRTM data and reduce the vertical error. (2) The BPNN (R²₁ = 0.98, root mean square error, RMSE₁ = 0.54) yielded a higher SRTM accuracy than did the studied linear model (RMSE₁ = 1.00, R²₁ = 0.90). (3) A series of significant improvements in the SRTM were observed when assessed with the reference DEMs for two different areas, with RMSE reductions of 91% (from 14.95 m to 1.23 m) and 93% (from 15.6 m to 0.94 m). The proposed method improved the accuracy of existing DEMs and could provide support for accurate farmland management.

Nitrogen (N) pulse is a frequent event in agroecosystems caused by fertilization. Understanding the responses of nitrogen metabolisms in native crops and invasive weeds to N pulses is essential in investigating the invasive mechanism of invasive weeds. A pot experiment was carried out to study the impacts of N pulse and the interspecific competition on nitrogen metabolism of an invasive weed (Amaranthus retroflexus) and a native crop (Glycine max); the plants were applied with an equal amount of N in three N pulse treatments, i.e., sole-summit treatment (SS) with N only applied on the seeding date, double-summit treatment (DS) with twice N applied (the fertilizer was applied on both the seeding date and the flowering date), and no-summit treatment (NS) in which N was applied evenly during the experiment. The results showed that A. retroflexus increased the nitrate reductase (NR) activity more than G. max (except for the roots) in the early growing stage, and increased the glutamine synthetase (GS) and glutamate dehydrogenase (GDH) activities in stem more than G. max in SS and DS treatments during the last two growing stages, however, the advantages were far weaker in the NS treatment. Interspecific competition had negative effects on the nitrogen metabolism of the two species among most of the sample times, and the effects of interspecific competition exerted a tissue-specific influence on nitrogen metabolism in the two species. A. retroflexus switched to reproductive growth earlier in SS treatment than in the DS and NS treatments when it was grown in mixed planting, and its height was the lowest in the NS treatment, so the competitive ability of A. retroflexus was higher in the SS and DS treatments than in the NS treatment, while SS treatment was the common application method of N fertilizer in the G. max farmland in China. Thus, the results of this study suggest that, if the farmer changed the N fertilizer application mode to a constant multiple fertilization mode, the competitive capacity of A. retroflexus will be reduced.

Optimizing nitrogen (N) fertilizer application within conventional rice production systems remains essential for improving grain quality while avoiding inefficient resource use. This study examined how different N application levels influence rice quality, starch structure, and physicochemical properties in two japonica rice types cultivated under cold-region conditions in Northeast China. Using two cultivars, common japonica rice ‘Putian 1498’ and glutinous japonica rice ‘Longjing 57’, four nitrogen levels were established under machine-transplanting conditions: N0 (0 kg/hm²), N1 (80 kg/hm²), N2 (135 kg/hm²), and N3 (190 kg/hm²). The results indicate that increasing nitrogen application differentially affected the milling quality of the two rice types: it reached its maximum at the N1 level for common japonica rice and at the N3 level for glutinous japonica rice. However, the taste value decreased and chalkiness increased in both types. Regarding starch properties, increased nitrogen application led to rougher starch granule surfaces, a decrease in large granules, and an increase in medium and small granules. Starch content decreased, and the amylose-to-amylopectin ratio declined. Relative crystallinity increased, while the FTIR ratio of 1045/1022 cm⁻¹ decreased. Solubility showed an increasing trend, whereas swelling power exhibited the opposite trend. The gelatinization enthalpy and pasting temperatures were positively correlated with nitrogen rate, whereas retrogradation degree showed a negative correlation. These results demonstrate that nitrogen application regulates rice quality through changes in starch structure and physicochemical properties, with distinct responses between common and glutinous japonica rice. Moderate nitrogen input improves milling quality, but excessive application reduces eating quality, indicating a trade-off between processing performance and consumer-oriented quality. This study provides mechanistic evidence to support more precise nitrogen management in conventional rice systems, contributing to improved resource-use efficiency without overstating broader sustainability claims. In conclusion, moderate nitrogen application optimizes rice quality by balancing milling performance and eating quality through its effects on starch structure, whereas excessive nitrogen input leads to quality deterioration and inefficient resource use.

Cadmium (Cd) contamination accelerates soil degradation and threatens the safe utilization of agricultural land, making sustainable remediation strategies urgently needed. To evaluate the remediation efficacy of a microbial inoculant (MI) composed of Bacillus subtilis, Bacillus thuringiensis, and Bacillus amyloliquefaciens in Cd-contaminated wheat soils, we conducted a field experiment. The results showed that, compared with the control (CK), MI treatments increased soil pH and soil organic matter (SOM) and enhanced the activities of urease, sucrase, dehydrogenase, and alkaline phosphatase by 3.83–249.28%, 0.54–1.08%, 5.61–109.68%, and 2.76–13.38%, respectively. With MI application, Cd shifted from the exchangeable and Fe-Mn oxide-bound fractions to the residual fraction, a key pathway reducing Cd bioavailability. At the wheat maturity stage, MI treatments reduced Cd content in wheat grains by 12.83–33.15% compared with CK. High-throughput sequencing revealed increased relative abundances of bacteria tolerant to heavy metals and bacteria associated with heavy metal remediation, including the phyla Pseudomonadota, Acidobacteriota, Bacillota, and Actinomycetota and the genera Pseudomonas, Arthrobacter, and Bacillus. Mantel tests indicated that soil pH, SOM, enzyme activities, and Cd accumulation were most strongly correlated with bacterial community composition. Overall, MI demonstrates practical feasibility for remediating Cd-contaminated wheat-field soils.