Arbuscular mycorrhizal fungi reduce ammonia emissions under different land-use types in agro-pastoral areas

Ammonia(NH3)emissions,the most important nitrogen(N)loss form,always induce a series of environmental problems such as increased frequency of regional haze pollution,accelerated N deposition,and N eutrophication.Arbuscular mycorrhizal(AM)fungi play key roles in N cycling.However,it is still unclear whether AM fungi can alleviate N losses by reducing NH3emissions.The potential mechanisms by which AM fungi reduce NH_(3)emissions in five land-use types(grazed grassland,mowed grassland,fenced grassland,artificial alfalfa grassland,and cropland)were explored in this study.Results showed that AM fungal inoculation significantly reduced NH3emissions,and the mycorrhizal responses of NH3emissions were determined by land-use type.Structural equation modeling(SEM)showed that AM fungi and land-use type directly affected NH_(3)emissions.In addition,the reduction in NH_(3)emissions was largely driven by the decline in soil NH_(4)^(+)-N and pH and the increases in abundances of ammonia-oxidizing archaea(AOA)amoA and bacteria(AOB)amoB genes,urease activity,and plant N uptake induced by AM fungal inoculation and land-use type.The present results highlight that reducing the negative influence of agricultural intensification caused by land-use type changes on AM fungi should be considered to reduce N losses in agriculture and grassland ecosystems.

Elucidating Variations in Nitrogen Requirement According to Yield, Variety and Cropping System for Chinese Rice Production

Better understanding of the factors that influence crop nitrogen(N) requirement plays an important role in improving regional N recommendations for rice(Oryza sativa L.) production. We collected data from 1 280 plot-level measurements in different reaches of the Yangtze River, China to determine which factors contributed to variability in N requirement in rice. Yield, variety, and cropping system were significantly related to N requirement. The N requirement remained consistent at about 18.6 kg N Mg^(-1)grain as grain yield increased from 7 to 9 Mg ha^(-1), then decreased to 18.1, 16.9, and 15.9 kg N Mg^(-1)grain as yield increased to 9–10, 10–11, and > 11 Mg ha^(-1), respectively. The decreased requirement for N with increasing yield was attributable to declining N concentrations in grain and straw and increased harvest index. Super rice variety had lower N requirement(17.7 kg N Mg^(-1)grain) than ordinary inbred and hybrid varieties(18.5 and 18.3 kg N Mg^(-1)grain, respectively), which was a result of lower grain and straw N concentrations of super rice. The N requirements were 19.2, 17.8, and 17.5 kg N Mg^(-1)grain for early, middle, and late rice cropping systems, respectively. In conclusion, the rice N requirement was affected by multiple factors, including yield, variety, and cropping system, all of which should be considered when planning for optimal N management.

Nondestructive estimation of bok choy nitrogen status with an active canopy sensor in comparison to a chlorophyll meter

Precise estimation of vegetable nitrogen(N)status is critical in optimizing N fertilization management.However,nondestructive and accurate N diagnostic methods for vegetables are relatively scarce.In our two-year field experiment,we evaluated whether an active canopy sensor(GreenSeeker)could be used to nondestructively predict N status of bok choy(Brassica rapa subsp.chinensis)compared with a chlorophyll meter.Results showed that the normalized difference vegetation index(NDVI)and ratio vegetation index(RVI)generated by the active canopy sensor were well correlated with the aboveground biomass(AGB)(r=0.698–0.967),plant N uptake(PNU)(r=0.642–0.951),and root to shoot ratio(RTS)(r=-0.426 to-0.845).Compared with the chlorophyll meter,the active canopy sensor displayed much higher accuracy(5.0%–177.4%higher)in predicting AGB and PNU and equal or slightly worse(0.54–1.82 times that of the chlorophyll meter)for RTS.The sensor-based NDVI model performed equally well in estimating AGB(R2=0.63)and PNU(R2=0.61),but the meter-based model predicted RTS better(R2=0.50).Inclusion of the days after transplanting(DAT)significantly improved the accuracy of sensor-based AGB(19.0%–56.7%higher)and PNU(24.6%–84.6%higher)estimation models.These findings suggest that the active canopy sensor has a great potential for nondestructively estimating N status of bok choy accurately and thus for better N recommendations,especially with inclusion of DAT,and could be applied to more vegetables with some verification.

Fate of Basal N Under Split Fertilization in Rice with ^(15)N Isotope Tracer

Split fertilization strategy is popularly adopted in rice to synchronize soil nitrogen(N) supply and crop N demand. Attention has been paid more on mid-season topdressing N, but limited on basal N. A clearer understanding of the basal N fate under split fertilization is crucial for determining rational basal N split ratio to improve the yield and reduce the loss to environment. A two-year field experiment with two N rates of 150 and 300 kg Nha^(-1), two split ratios of basal N, 40% and 25%, and two rice varieties,Wuyunjing 23(japonica) and Y-liangyou 2(super hybrid indica), was conducted. Labelled ^(15) N urea was supplied in micro-plots as basal fertilizer to determine the plant uptake, translocation, soil residual, and loss of basal N fertilizer. The results showed that basal N absorbed by rice was only 1.6%–11.5% before tillering fertilization(8–10 d after transplanting), 6.5%–21.4% from tillering fertilization to panicle fertilization, and little(0.1%–4.4%) after panicle fertilization. The recovery efficiency of basal N for the entire rice growth stage was low and ranged from 18.7% to 24.8%, not significantly affected by cultivars or N treatments. Soil residual basal N accounted for 10.3%–36.4% and decreased with increasing total N rate and basal N ratio, regardless of variety and year. 43.8%–70.4% of basal N was lost into the environment based on the N balance. Basal N loss was significantly linearly positive related with the basal N rate and obviously enhanced by the increasing basal N ratio for both varieties in both 2012 and 2013. The N use efficiency and yield was significantly improved when decreasing the basal N ratio from 40% to 25%. The results indicated that the basal N ratio should be reduced, especially with limited N inputs, to improve the yield and reduce the N loss to the environment.