Xiong Du

Increasing planting density can raise summer maize yield, but it also intensifies competition for light, water, and nutrients within the canopy, accelerating post-silking leaf senescence and reducing assimilatory capacity. Drip fertigation enables precise water and nitrogen supply, but the optimal nitrogen application frequency for summer maize remains unclear in the North China Plain. Therefore, a two-year field experiment was conducted in 2024 and 2025 using two planting densities (75,000 and 97,500 plants ha ^- ¹), a conventional single nitrogen application control, and several split nitrogen treatments under the same total nitrogen rate. Across the two-year average, split nitrogen application increased grain yield and 1000-kernel weight, and the four-split treatment produced the highest grain yield (14.4t ha ^- ¹). At 75,000 and 97,500 plants ha ^- ¹, the two-year average grain yield under the four-split treatment increased by 11.8% and 13.0%, respectively, and the 1000-kernel weight increased by 6.0% and 10.0%, respectively, compared with the corresponding control. Based on the two-year average, the four-split treatment also delayed leaf senescence onset by 2.1 and 6.0d, delayed the time to maximum senescence rate by 11.5 and 12.5d, and reduced the mean senescence rate by 18.0% and 20.8%, respectively. Overall, split nitrogen application, especially the four-split regime, delayed post-silking leaf senescence, improved late-season physiology, and increased grain yield in densely planted summer maize.

The spatial heterogeneity of leaf traits within canopies is an important source of uncertainty in leaf parameter estimation from unmanned aerial vehicle (UAV) imagery, especially in structurally complex orchards. In this study, we combined three-dimensional (3D) radiative transfer simulations with field measurements from litchi orchards to quantify bidirectional reflectance factor (BRF) uncertainty under four leaf trait distribution patterns within the canopy. Whole-canopy leaf traits were represented using: (1) a homogeneous canopy (HC), (2) vertically divided canopy (VDC), (3) horizontally divided canopy (HDC), and (4) a canopy divided into nine sections (CD9s). Among the simplified schemes, HDC produced BRF values most consistent with the CD9s configuration, while the largest deviation between CD9s and HC was observed at 570 nm with a maximum BRF normalized difference of 65.29%. Relative contribution rate analysis based on the symmetric relative difference (SRD, %) showed that leaf trait distribution pattern dominated the variability of several VIs, including NDVI, NDRE, CCI, SIPI, LICI, and PVI. Meanwhile, other VIs (e.g., NIRv, SAVI, OSAVI and EVI) were more strongly influenced by illumination–viewing geometry. Using multiangle UAV multispectral data improved the estimation of proxy leaf chlorophyll content (LCC, max R²cv = 0.52), while nadir-only data yielded the best results for leaf nitrogen mass-based content (LNC, max R²cv = 0.41). These results emphasize that reliable UAV-based leaf trait retrieval is closely related to leaf trait distribution pattern within the canopy and its interaction with other factors (e.g., illumination–viewing geometry).

To elucidate how exogenous regulators mitigate the impact of mechanical leaf damage on maize, field experiments were conducted on two sowing dates (S1, S2) using two cultivars (XY335, ZD958). Severe leaf damage at the six-leaf stage significantly reduced kernel number, ear number, and 100-kernel weight, causing yield losses of 21.9–48.9%. Foliar application of melatonin (MT), brassinolide (BR), and urea (UR) substantially alleviated these losses, increasing yield by 14.1–52.2% compared to damaged controls, with UR and BR being most effective, especially in ZD958. These regulators restored leaf area index (LAI) by promoting leaf width and delaying senescence, improved photosynthetic performance (Pn, Gs, Ci, and Tr), enhanced post-silking dry matter accumulation by up to 31%, and accelerated grain filling through increased maximum and mean filling rates. Structural equation modeling confirmed that kernel number and 100-kernel weight were the primary yield determinants. These findings reveal the physiological mechanisms underlying damage recovery and demonstrate the potential of targeted regulator applications—urea as a cost-effective option, brassinolide for improving kernel number under sustained stress, and melatonin for broad resilience. This study provides not only theoretical evidence but also a feasible strategy for mitigating yield loss in maize production under field conditions where leaf damage commonly occurs.

The canopy of perennial evergreen fruit trees in southern China has a unique Bidirectional Reflectance Factor (BRF) due to its complex multi-branch structure and density changes. This study aimed to address the lack of clarity regarding the changes in BRF of evergreen fruit trees in southern China. Litchi, a typical fruit tree in this region, was chosen as the subject for establishing a three-dimensional (3D) real structure model. The canopy BRF of litchi was simulated under different leaf components, illumination geometry, observed geometry, and leaf area index (LAI) using a 3D radiation transfer model. The corresponding changes in characteristics were subsequently analyzed. The findings indicate that the chlorophyll content and equivalent water thickness of leaves exert significant influences on canopy BRF, whereas the protein content exhibit relatively weak effects. Variation in illumination and observation geometry results in the displacement of hotspots, with the solar zenith angle and view zenith angle exerting significant influence on the BRF. As the LAI of the litchi orchard increases, the distribution of hotspots becomes more concentrated, and the differences in angle information are relatively smaller when observed from multiple angles. With the increase in LAI in litchi orchards, the BRF on the principal plane would be saturated, but observation at hotspots could alleviate this phenomenon. The above analysis provides a reference for quantitative inversion of vegetation parameters using remote sensing monitoring information of typical perennial evergreen fruit trees.

Drought stress, a major abiotic stress, significantly affects wheat (Triticum aestivum L.) production globally. To identify genes and metabolic pathways crucial for responding to short-term drought stress, we conducted transcriptomic and metabolomic analyses of winter wheat cultivar Jimai 418 at four developmental stages: jointing (GS31), booting (GS45), anthesis (GS65), and 8 days after anthesis (DAA8). Transcriptomic analysis identified 14,232 differentially expressed genes (DEGs) under drought stress compared to the control. Specifically, 1387, 4573, 7380, and 892 DEGs were identified at the four developmental stages, respectively. Enriched pathways associated with these DEGs included plant hormone signal transduction, mitogen-activated protein kinase (MAPK) signaling, galactose metabolism, and starch and sucrose metabolism. Totals of 222, 633, 358, and 38 differentially accumulated metabolites (DAMs) were identified at the four stages, respectively. Correlation analysis of both datasets revealed DEGs and DAMs associated with plant hormone signal transduction, arginine and proline metabolism, ABC transporters, and amino acid biosynthesis. These findings offer significant insights into Jimai 418’s molecular response to short-term drought stress. The identified DEGs, DAMs, and enriched pathways contribute to our understanding of wheat drought tolerance. This research will facilitate further investigations into drought tolerance mechanisms and guide the breeding of wheat varieties with enhanced drought resistance.

Phased warming in late winter and early spring can increase winter wheat grain yield. However, the effects of different durations of warming during this period on winter wheat grain yield and quality are not yet clear. Therefore, this study conducted field warming experiments in a movable polyethylene greenhouse during the late winter and early spring stages of the three wheat growing seasons from 2019 to 2022. The results showed that the accumulated growing degree days (GDD) of the warming treatment during the warming period were increased by 87.3–215.7 °C d compared to the control (CK). The warming treatment advanced and prolonged the duration of vegetative growth and spike differentiation after regreening, promoted spike and flower development, and increased grain length, grain width, and grain area. During the three growing seasons, the longer the warming duration (WD) of the warming treatment, the more obvious were the observed promoting effects on the kernel number per spike and 1000-kernel weight. From 2019 to 2021, compared to the CK, the spike number per unit area and grain yield of the warming treatments increased with the prolongation of WD. However, in the 2022 growing season the spike number per unit area and grain yield of the warming treatment were increased with longer WD, reaching the maximum at WD of 56 days and then gradually decreasing with longer WD. Compared to CK, the grain protein content, wet gluten content, and sedimentation value of the warming treatment decreased with the prolongation of WD. The promotion effect of longer WD on grain starch content and protein yield was more significant. In summary, the accumulated GDD during the warming period compared to CK was 155.8–181.2 °C d, and at WD of 50–56 days a relatively higher grain yield and protein yield could be obtained.

Against the background of long-term climate change, quantifying the response of maize growth and development to climate change during critical growth stages will contribute to future decision-making in maize production. However, there have been few reports on the impact of climate change on maize dry matter accumulation and yield formation using long-term field trial data. In this study, field trial data from 13 agricultural meteorological stations in the Beijing–Tianjin–Hebei region from 1981 to 2017 were analyzed using partial correlation analysis and multiple regression models to investigate the effects of climate change on maize growth and yield. The results showed that the average temperature (Tavg) and accumulated effective precipitation (EP) during the maize growing season increased while the accumulated solar radiation (SRD) decreased from 1981 to 2017. During the seedling stage (GS1, VE-V8) and ear development stage (GS2, V8-R1), Tavg increased by 0.34 °C and 0.36 °C/decade, respectively, and EP increased by 1.83 mm and 3.35 mm/decade, respectively. The significant increase in Tavg during GS1 was the main reason for the inhibitory effect of climate change on maize growth, development, and biomass accumulation. However, the increase in SRD during the grain formation stage (GS3, R1–R3) and grain filling stage (GS4, R3–R6) was favorable for yield formation, increasing the grain number per ear (GN) and grain weight (GW) by 5.00% and 2.84%, respectively. SRD significantly increased after the silk stage, partially offsetting the adverse effects of temperature on maize yield formation, but the final result was a 0.18% and 0.94% reduction in maize plant dry weight (TDW) and grain yield (GY), respectively, due to the combined effects of the three climate factors. Spatially, climate change mainly had a negative impact on maize in the eastern and western parts of the central region of Beijing–Tianjin–Hebei, with a maximum GY reduction of up to 34.06%. The results of this study can provide a scientific basis for future decision-making in maize production against the background of climate change.

Enhancing maize lodging resistance with plant growth retardants (PGRs) is common in maize production. However, the underlying mechanisms of yield formation as affected by PGRs are still poorly understood. A field experiment contained PGR application (a mixture of ethephon and cycocel, EC) with normal (T1) and double (T2) doses and water control (CK) was conducted at four maize plant densities (4.5, 6.0, 7.5, and 9.0 plants m⁻²) in 2020 and 2021. In this two-year study, the grain yield and kernel number per ear (KNE) of EC treatments were reduced by 4.8–9.0% and 3.3–12.2%, respectively, compared with CK under densities of 4.5, 6.0, and 7.5 plants m⁻² without lodging. However, under the density of 9.0 plants m⁻², EC treatments had no pronounced effects on grain yield and yield components. Across all densities, EC significantly decreased the leaf area index (LAI), and the lowest LAI was recorded in T2. The concentrations of nonstructural carbohydrates (NSCs; starch and soluble sugar) in the stem were significantly decreased by 9.9–10.2% in T2 averaged all densities. The sucrose and starch concentrations in grains also declined in the EC treatments. The key enzymes (cell wall acid invertase, sucrose synthase, and adenosine diphosphate pyrophosphorylase) and grain polyamine concentrations showed a slight downward trend under EC treatments compared to CK. NSCs in stems and grains, kernel enzyme activities, and polyamines in grains presented significant positive correlations with KNE. Additionally, structural carbohydrate (SC; including cellulose, hemicellulose, and lignin) concentrations in stems were improved with enhanced lodging resistance by spraying EC. Significant negative relationships were observed between SC with kernel number m^-2 (KNM) and yield, suggesting that improved SC in stems might affect the availability of NSCs for kernel set. Although the lowest kernel weight and KNE were obtained at 9.0 plant m⁻², relatively high LAI still ensured high KNM and high yield. Collectively, EC treatment increased SC in stems, enhanced lodging resistance of maize and reduced NSC availability for kernels, ultimately presenting adverse effects on maize kernel number and yield under relative low density.