Ethephon Reduces Maize Nitrogen Uptake but Improves Nitrogen Utilization in Zea mays L.

Increasing use of plant density or/and nitrogen (N) application has been introduced to maize production in the past few decades. However, excessive planting density or/and use of fertilizer may cause reduced N use efficiency (NUE) and increased lodging risks. Ethephon application improves maize lodging resistance and has been an essential measure in maize intensive production systems associated with high plant density and N input in China. Limited information is available about the effect of ethephon on maize N use and the response to plant density under different N rates in the field. A three-year field study was conducted with two ethephon applications (0 and 90 g ha−1), four N application rates (0, 75, 150, and 225 kg N ha−1), and two plant densities (6.75 plants m−2 and 7.5 plants m−2) to evaluate the effects of ethephon on maize NUE indices (N agronomic efficiency, NAE; N recovery efficiency, NRE; N uptake efficiency, NUpE; N utilization efficiency, NUtE; partial factor productivity of N, PFPN), biomass, N concentration, grain yield and N uptake, and translocation properties. The results suggest that the application of ethephon decreased the grain yield by 1.83–5.74% due to the decrease of grain numbers and grain weight during the three experimental seasons. Meanwhile, lower biomass, NO3- and NH4+ fluxes in xylem bleeding sap, and total N uptake were observed under ethephon treatments. These resulted in lower NAE and NUpE under the ethephon treatment at a corresponding N application rate and plant density. The ethephon treatment had no significant effects on the N concentration in grains, and it decreased the N concentration in stover at the harvesting stage, while increasing the plant N concentration at the silking stage. Consequently, post-silking N remobilization was significantly increased by 14.10–32.64% under the ethephon treatment during the experimental periods. Meanwhile, NUtE significantly increased by ethephon.

Winter Wheat Nitrogen Estimation Based on Ground-Level and UAV-Mounted Sensors

A better understanding of wheat nitrogen status is important for improving N fertilizer management in precision farming. In this study, four different sensors were evaluated for their ability to estimate winter wheat nitrogen. A Gaussian process regression (GPR) method with the sequential backward feature removal (SBBR) routine was used to identify the best combinations of vegetation indices (VIs) sensitive to wheat N indicators for different sensors. Wheat leaf N concentration (LNC), plant N concentration (PNC), and the nutrition index (NNI) were estimated by the VIs through parametric regression (PR), multivariable linear regression (MLR), and Gaussian process regression (GPR). The study results reveal that the optical fluorescence sensor provides more accurate estimates of winter wheat N status at a low-canopy coverage condition. The Dualex Nitrogen Balance Index (NBI) is the best leaf-level indicator for wheat LNC, PNC and NNI at the early wheat growth stage. At the early growth stage, Multiplex indices are the best canopy-level indicators for LNC, PNC, and NNI. At the late growth stage, ASD VIs provide accurate estimates for wheat N indicators. This study also reveals that the GPR with SBBR analysis method provides more accurate estimates of winter wheat LNC, PNC, and NNI, with the best VI combinations for these sensors across the different winter wheat growth stages, compared with the MLR and PR methods.

Nitrogen Migration and Transformation Mechanism in the Groundwater Level Fluctuation Zone of Typical Medium

Because of the nitrogen pollution problem in groundwater, the migration conversion mechanism of nitrogen in groundwater level fluctuations was analyzed. Technology and methods through indoor experiments and theoretical analysis were used to study coarse sand, medium sand, and fine sand groundwater level fluctuation in the aeration zone and saturated zone under the situation of nitrogen distribution characteristics, revealing groundwater level fluctuation with the nitrogen migration mechanism. The experimental results showed that the variation range of the nitrate-nitrogen (NO3−−N) concentration with the water level is medium sand > fine sand > coarse sand. The ammonium nitrogen (NH4+−N) concentration showed a downward trend after water level fluctuations, and there were more apparent fluctuations in coarse sand and medium sand. The nitrite nitrogen (NO2−−N) in coarse sand and medium sand first increased the water level and then gradually reached a balance. The sampling points below the water level in fine sand showed a downward trend with fluctuation of the water level, and then gradually reached equilibrium. The results provide a scientific basis for the remediation and treatment of soil and groundwater pollution.

Non-Destructive Monitoring of Maize Nitrogen Concentration Using a Hyperspectral LiDAR: An Evaluation from Leaf-Level to Plant-Level

Advanced remote sensing techniques for estimating crop nitrogen (N) are crucial for optimizing N fertilizer management. Hyperspectral LiDAR (HSL) data, with both spectral and spatial information of the targets, can extract more plant properties than traditional LiDAR and hyperspectral imaging systems. In this study, we tested the ability of HSL in terms of estimating maize N concentration at the leaf-level by using spectral indices and partial least squares regression (PLSR) methods. Subsequently, the N estimation was scaled up to the plant-level based on HSL point clouds. Biomass, extracted with structural proxies, was utilized to exhibit its supplemental effect on N concentration. The results show that HSL has the ability to extract N concentrations at both the leaf-level and the canopy-level, and PLSR showed better performance (R2 > 0.6) than the single spectral index (R2 > 0.4). In comparison to the stem height and maximum canopy width, the plant height had the strongest ability (R2 = 0.88) to estimate biomass. Future research should utilize larger datasets to test the viability of using HSL to monitor the N concentration of crops, which is beneficial for precision agriculture.

Estimation of Critical Nitrogen Concentration Based on Leaf Dry Matter in Drip Irrigation Spring Maize Production in Northern China

Background: The application of nitrogen (N) fertilizer not only increases crop yield but also improves the N utilization efficiency. The critical N concentration (Nc) can be used to diagnose crops N nutritional status. The Nc dilution curve model of maize was calibrated with leaf dry matter (LDM) as the indicator, and the performance of the model for diagnosing maize N nutritional status was further evaluated. Three field experiments were carried out in two sites between 2018 and 2020 in Ningxia Hui Autonomous Region with a series of N levels (application of N from 0 to 450 kg N ha-1). Two spring maize cultivars, i.e., Tianci19 (TC19) and Ningdan19 (ND19), were utilized in the field experiment. Results: The results showed that a negative power function relationship existed between LDM and leaf N concentration (LNC) for spring maize under drip irrigation. The Nc dilution curve equation was divided into two parts: when the LDM < 1.11 t ha-1, the constant leaf Nc value was 3.25%; and when LDM > 1.11 t ha-1, the Nc curve was 3.33*LDM-0.24. Conclusion: The LDM based Nc curve can well distinguish data the N-limiting and non-N-limiting N status of maize, which was independent with maize varieties, growing seasons and stages. Additionally, the N nutrition index (NNI) had a significant linear correlation with the relative leaf dry matter (RLDM). This study revealed that the LDM based Nc dilution curve could accurately identify spring maize N status under drip irrigation. NNI can thus, be used as a robust and reliable tool to diagnose N nutritional status of maize.

Revisiting Why Plants Become N Deficient Under Elevated CO2: Importance to Meet N Demand Regardless of the Fed-Form

An increase in plant biomass under elevated CO2 (eCO2) is usually lower than expected. N-deficiency induced by eCO2 is often considered to be a reason for this. Several hypotheses explain the induced N-deficiency: (1) eCO2 inhibits nitrate assimilation, (2) eCO2 lowers nitrate acquisition due to reduced transpiration, or (3) eCO2 reduces plant N concentration with increased biomass. We tested them using C3 (wheat, rice, and potato) and C4 plants (guinea grass, and Amaranthus) grown in chambers at 400 (ambient CO2, aCO2) or 800 (eCO2) μL L−1 CO2. In most species, we could not confirm hypothesis (1) with the measurements of plant nitrate accumulation in each organ. The exception was rice showing a slight inhibition of nitrate assimilation at eCO2, but the biomass was similar between the nitrate and urea-fed plants. Contrary to hypothesis (2), eCO2 did not decrease plant nitrate acquisition despite reduced transpiration because of enhanced nitrate acquisition per unit transpiration in all species. Comparing to aCO2, eCO2 remarkably enhanced water-use efficiency, especially in C3 plants, decreasing water demand for CO2 acquisition. As our results supported hypothesis (3) without any exception, we then examined if lowered N concentration at eCO2 indeed limits the growth using C3 wheat and C4 guinea grass under various levels of nitrate-N supply. While eCO2 significantly increased relative growth rate (RGR) in wheat but not in guinea grass, each species increased RGR with higher N supply and then reached a maximum as no longer N was limited. To achieve the maximum RGR, wheat required a 1.3-fold N supply at eCO2 than aCO2 with 2.2-fold biomass. However, the N requirement by guinea grass was less affected by the eCO2 treatment. The results reveal that accelerated RGR by eCO2 could create a demand for more N, especially in the leaf sheath rather than the leaf blade in wheat, causing N-limitation unless the additional N was supplied. We concluded that eCO2 amplifies N-limitation due to accelerated growth rate rather than inhibited nitrate assimilation or acquisition. Our results suggest that plant growth under higher CO2 will become more dependent on N but less dependent on water to acquire both CO2 and N.

Effect of Commercial Slow-Release Urea Product on in Vitro Rumen Fermentation and Ruminal Microbial Community Using RUSITEC Technique

Background The objectives of this study were to determine the effect of commercial slow-release urea (SRU) on in vitro fermentation characteristics, nutrient digestibility, gas production, microbial protein synthesis and bacterial community using rumen simulation technique (RUSITEC). The experiment was a completely randomized design with four treatments and four replications of each treatment. Treatments were: control diet (no SRU addition), control diet plus 0.28% SRU (U28), or plus 0.56% SRU (U56), and control diet that was modified for substituting with 0.35% SRU for equavelant soybean protein (MU35; dry matter [DM] basis). The experiment consisted of 8 days of adaptation and 7 days of data and sample collection. Rumen inoculum was obtained from three ruminally fistulated Angus cows fed the same diet to the substrate incubated. Results Digestibility of DM, organic matter (OM), crude protein (CP), fibre and starch was not affected, but daily production of gas (P < 0.07) and methane (P < 0.05) was quadratically changed with increasing SRU supplementation. The increase of SRU addition did not affect fermentation pH and total volatile fatty acid (VFA) production, whereas linearly (P < 0.01) decreased proportion of propionate, and linearly (P < 0.01) increased acetate to propionate ratio and ammonia nitrogen (N) concentration. The microbial N efficiency also linearly (P < 0.03) improved with increasing supplementation of SRU. In comparison with control diet, the dietary substitution of SRU for part of soybean meal increased (P < 0.05) the digestibility of DM, OM and CP and decreased (P < 0.02) the total gas production. The total VFA production and acetate to propionate ratio did not differ between control and MU35, whereas the proportion of butyrate was lower (P < 0.05) and that of branched-chain VFA was greater (P < 0.05) with MU35 than control diet. Total and liquid-associated microbial N production as well as ammonia N concentration were greater (P < 0.03) with MU35 than control diet. Observed OTUs, Shannon diversity index, and beta diversity of the microbial community did not differ among treatments. Taxonomic analysis revealed no effect of adding SRU on the relative abundance of bacteria at the phylum level, while at the genus level, the impact of SRU addition on microbial community was greater with MU35 either for liquid associate bacteria or feed particle-associated bacteria. Conclusions Supplementation of a dairy cow diet with SRU showed potential of increase in ammonia N concentration and microbial protein production, and change fermentation pattern to more acetate production. Adding SRU in dairy cow diet also showed beneficial effect on improving digestibility of OM and fibre. The results suggest that SRU can partially substitute soybean meal in dairy cow diet to increase microbial protein production without impairing rumen fermentation.

Foliar N Application on Tea Plant at Its Dormancy Stage Increases the N Concentration of Mature Leaves and Improves the Quality and Yield of Spring Tea

Over 30% of the Chinese tea plantation is supplied with excess fertilizer, especially nitrogen (N) fertilizer. Whether or not foliar N application on tea plants at the dormancy stage could improve the quality of spring tea and be a complementary strategy to reduce soil fertilization level remains unclear. In this study, the effects of foliar N application on tea plants were investigated by testing the types of fertilizers and their application times, and by applying foliar N under a reduced soil fertilization level using field and 15N-labeling pot experiments. Results showed that the foliar N application of amino acid liquid fertilizer two times at the winter dormancy stage was enough to significantly increase the N concentration of the mature leaves and improved the quality of spring tea. The foliar application of 2% urea or liquid amino acid fertilizer two times at the winter dormancy stage and two times at the spring dormancy stage showed the best performance in tea plants among the other foliar N fertilization methods, as it reduced the soil fertilization levels in tea plantations without decreasing the total N concentration of the mature leaves or deteriorating the quality of spring tea. Therefore, foliar N application on tea plants at its dormancy stage increases the N concentration of the mature leaves, improves the quality and yield of spring tea, and could be a complementary strategy to reduce soil fertilization levels.

Solar radiation effects on leaf nitrogen and phosphorus stoichiometry of Chinese fir across subtropical China

Background Solar radiation (SR) plays critical roles in plant physiological processes and ecosystems functions. However, the exploration of SR influences on the biogeochemical cycles of forest ecosystems is still in a slow progress, and has important implications for the understanding of plant adaption strategy under future environmental changes. Herein, this research was aimed to explore the influences of SR on plant nutrient characteristics, and provided theoretical basis for introducing SR into the establishment of biochemical models of forest ecosystems in the future researches. Methods We measured leaf nitrogen (N) and phosphorus (P) stoichiometry in 19 Chinese fir plantations across subtropical China by a field investigation. The direct and indirect effects of SR, including global radiation (Global R), direct radiation (Direct R) and diffuse radiation (Diffuse R) on the leaf N and P stoichiometry were investigated. Results The linear regression analysis showed that leaf N concentration had no association with SR, while leaf P concentration and N:P ratio were negatively and positively related to SR, respectively. Partial least squares path model (PLS-PM) demonstrated that SR (e.g. Direct R and Diffuse R), as a latent variable, exhibited direct correlations with leaf N and P stoichiometry as well as the indirect correlation mediated by soil P content. The direct associations (path coefficient = − 0.518) were markedly greater than indirect associations (path coefficient = − 0.087). The covariance-based structural equation modeling (CB-SEM) indicated that SR had direct effects on leaf P concentration (path coefficient = − 0.481), and weak effects on leaf N concentration. The high SR level elevated two temperature indexes (mean annual temperature, MAT; ≥ 10 °C annual accumulated temperature, ≥ 10 °C AAT) and one hydrological index (mean annual evapotranspiration, MAE), but lowered the soil P content. MAT, MAE and soil P content could affect the leaf P concentration, which cause the indirect effect of SR on leaf P concentration (path coefficient = 0.004). Soil N content had positive effect on the leaf N concentration, which was positively and negatively regulated by MAP and ≥ 10 °C AAT, respectively. Conclusions These results confirmed that SR had negatively direct and indirect impacts on plant nutrient status of Chinese fir based on a regional investigation, and the direct associations were greater than the indirect associations. Such findings shed light on the guideline of taking SR into account for the establishment of global biogeochemical models of forest ecosystems in the future studies.

The Migration and Transformation of Nitrogen in the Danjiangkou Reservoir and Upper Stream: A Review

The Danjiangkou Reservoir in China is characterized by significantly high concentrations of total nitrogen (TN), and the sources are not clear. Recently, research on this reservoir has focused on the N cycle, the spatial and temporal distribution characteristics of N, and the factors influencing N concentration. Significant temporal and spatial differences in TN concentrations exist, both in the reservoir area and the tributaries. N concentration in the area is affected by numerous factors, including N transported by tributaries, nonpoint source pollution around the reservoir, internal N release, and atmospheric N deposition. Moreover, a dam heightening project led to a larger water-fluctuation zone and more bays in the reservoir, directly affecting its N cycle. However, further research is required to explore the N cycle on a large watershed scale in the Danjiangkou Reservoir and upper stream areas, determine N pollution sources using satellite remote sensing, and conduct simulations of a water body N cycle model based on data fusion. Although the issue of excessive TN has been alleviated to some extent by the South-North Water Diversion Project, the excessively high TN concentrations require more research to aid the implementation of N-reducing strategies.