Optimizing the interaction between planting density and nitrogen (N) application rate is critical for simultaneously improving grain yield and nitrogen use efficiency (NUE) in winter wheat (Triticum aestivum L.). However, the underlying regulatory mechanism remains poorly understood in the fluvo-aquic soil region of the southern Huang–Huai–Hai Plain. This study aimed to elucidate the physiological mechanism by which planting density and nitrogen application interactively regulate source–sink coordination to achieve synergistic high grain yield and high NUE, and to screen the optimal local cultivation combination for winter wheat in southeastern Henan. A two-year consecutive field experiment was conducted from 2018 to 2020 in Shangshui, Henan, using a split-plot design. Three planting densities (D1: 225 × 10⁴ plants ha⁻¹; D2: 375 × 10⁴ plants ha⁻¹; D3: 525 × 10⁴ plants ha⁻¹) and five N rates (N0: 0; N1: 180; N2: 240; N3: 300; N4: 360 kg N ha⁻¹) were established. Results demonstrated that planting density, N rate, and their interaction significantly regulated grain yield, NUE, and dry matter and N allocation, with consistent trends across both years. Increasing density enhanced total biomass and N accumulation, but dry matter and N partitioning to grains declined when density exceeded 375 × 10⁴ plants ha⁻¹. Grain yield exhibited a quadratic response to N rate; the optimal N rate for maximum yield decreased from 296.33 kg ha⁻¹ at low density (D1) to 237.50–245.38 kg ha⁻¹ at medium and high densities. The combination of 240 kg N ha⁻¹ and 375 × 10⁴ plants ha⁻¹ (D2N2) produced the highest average grain yield (8875.35 kg ha⁻¹), with simultaneous improvements in spike number and kernels per spike as well as superior dry matter and N partitioning to grains. This combination also maintained high nitrogen recovery efficiency (NRE) and nitrogen agronomic efficiency (NAE). Correlation analysis revealed that grain yield and NUE were significantly positively correlated with dry matter accumulation, N accumulation, and their partitioning proportions to grains. Overall, D2N2 achieved simultaneous high yield and high NUE by coordinately optimizing dry matter and N partitioning to grains. We therefore recommend reducing N fertilizer to approximately 240 kg ha⁻¹ combined with a moderate planting density of 375 × 10⁴ plants ha⁻¹ as the preferred strategy for sustainable and intensive winter wheat production in the fluvo-aquic soil region of southeastern Henan and adjacent areas.

Arbuscular mycorrhizal (AM) fungi form mutualistic symbioses with about 80% of land plants and play a key role in improving host inorganic phosphate (Pi), nitrogen, and water acquisition. Traditional AM fungi research relies on field trials, compartmented cultivation, and pot cultures—methods that are time-consuming (taking months to years) and unable to monitor dynamic transport, thus limiting efficient strain screening. We developed a real-time fluorescence imaging platform integrating sterile symbiotic microchambers with photodiode array detection. This system enables the non-invasive, quantitative tracking of hyphal cytoplasmic streaming and transport kinetics at the plant–fungal interface. Distinct AM fungi strains exhibit significant differences in fluorescence kinetics—such as accumulation rate and peak intensity—providing measurable indicators of transport efficiency. Our method overcomes the temporal and technical limitations of conventional AM fungi screening approaches. By enabling simultaneous real-time monitoring, it shortens screening cycles and provides new insights for the (1) precise screening of AM fungi strains for efficient nutrient transport; (2) investigation of nutrient exchange mechanisms; (3) development of sustainable microbial inoculants.

Nitrate (NO₃⁻) serves as a pivotal molecule with dual functions in nutrient supply and signaling during plant growth and development. Precise monitoring of its spatiotemporal dynamics in planta is therefore essential for dissecting the regulatory mechanisms underlying plant nitrogen metabolism. However, conventional nitrate detection methods suffer from inherent limitations, including destructive sampling, insufficient spatiotemporal resolution, and an inability to achieve real-time whole-plant monitoring. Here, we report a genetically encoded nitrate biosensor, designated NitNRCL1, constructed using a split firefly luciferase complementation system. Functional validation in both prokaryotic and eukaryotic systems demonstrates that NitNRCL1 responds to changes in nitrate availability and generates stable chemiluminescent signals in bacteria and diverse plant species. Importantly, NitNRCL1 enables non-invasive, real-time, and whole-plant monitoring of nitrate levels in living plants. Using NitNRCL1, we successfully imaged the spatiotemporal dynamics of nitrate signaling in Arabidopsis thaliana. Collectively, our findings establish NitNRCL1 as a robust and novel tool for investigating nitrate transport, signaling, and metabolic pathways in plants. This biosensor advances our mechanistic understanding of plant nitrate biology and provides a technical foundation for breeding nitrogen-use-efficient crops and developing precision fertilization strategies.