scholarly journals Effects of controlled-release urea combined with fulvic acid on soil inorganic nitrogen, leaf senescence and yield of cotton

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jibiao Geng ◽  
Xiuyi Yang ◽  
Xianqi Huo ◽  
Jianqiu Chen ◽  
Shutong Lei ◽  
...  
Keyword(s):  
Controlled Release ◽  
Fulvic Acid ◽  
Leaf Senescence ◽  
Nitrogen Fertilizer ◽  
Inorganic Nitrogen ◽  
Fiber Quality ◽  
Nitrogen Fertilizers ◽  
Soil Inorganic Nitrogen ◽  
Controlled Release Urea ◽  
Soil Inorganic

Abstract A split-plot field experiment was conducted in 2018–2019 to study the effects of nitrogen fertilizer types and fulvic acid (FA) rates on soil nitrogen and cotton growth. The nitrogen fertilizers included controlled-release urea (CRU) and urea, which were applied combined with three FA rates (90, 180 and 270 kg ha-1). The main plot was the nitrogen fertilizer type, and the subplot was the FA rate. The results showed that the lint yield of the FA180 treatment was 5.2–8.6% higher than the FA90 and FA270 treatments. Moreover, moderate FA application markedly improved the cotton leaf SPAD value (chlorophyll relative value), photosynthesis and chlorophyll fluorescence parameters compared with low and high FA rates. Replacing urea with CRU significantly increased the soil inorganic nitrogen and nitrogen use efficiency and also improved cotton fiber quality parameters. Meanwhile, the boll weight and seed yield of the CRU treatments were 1.5–8.4% and 3.3–19.1% higher, respectively, than the urea treatments. The interaction between nitrogen type and FA rate had a positive effect on cotton growth. Thus, the application of CRU combined with 180 kg ha-1 FA on cotton can not only improve the fiber quality and delay leaf senescence but also increase the yield and economic benefit.

Soil Inorganic Nitrogen under Fertilized Bermudagrass Turf

Crop Science ◽  
2003 ◽  
Vol 43 (1) ◽  
pp. 247 ◽  
Author(s):  
David J. Lee ◽  
Daniel C. Bowman ◽  
D. Keith Cassel ◽  
Charles H. Peacock ◽  
Thomas W. Rufty
Keyword(s):  
Inorganic Nitrogen ◽  
Soil Inorganic Nitrogen ◽  
Soil Inorganic

Switchgrass intercropping reduces soil inorganic nitrogen in a young loblolly pine plantation located in coastal North Carolina

2014 ◽  
Vol 319 ◽  
pp. 161-168 ◽  
Author(s):  
Kevan J. Minick ◽  
Brian D. Strahm ◽  
Thomas R. Fox ◽  
Eric B. Sucre ◽  
Zakiya H. Leggett ◽  
...  
Keyword(s):  
North Carolina ◽  
Loblolly Pine ◽  
Inorganic Nitrogen ◽  
Pine Plantation ◽  
Soil Inorganic Nitrogen ◽  
Soil Inorganic

Simulating maize (Zea mays L.) growth and yield, soil nitrogen concentration, and soil water content for a long-term cropping experiment in Ontario, Canada

2014 ◽  
Vol 94 (3) ◽  
pp. 435-452 ◽  
Author(s):  
S. Liu ◽  
J. Y. Yang ◽  
C. F. Drury ◽  
H. L. Liu ◽  
W. D. Reynolds
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Inorganic Nitrogen ◽  
Nitrogen Concentration ◽  
Growth And Yield ◽  
Model Data ◽  
Soil Inorganic Nitrogen ◽  
Soil Inorganic

Liu, S., Yang, J. Y., Drury, C. F., Liu, H. L. and Reynolds, W. D. 2014. Simulating maize (Zea mays L.) growth and yield, soil nitrogen concentration, and soil water content for a long-term cropping experiment in Ontario, Canada. Can. J. Soil Sci. 94: 435–452. A performance assessment of the Decision Support Systems for Agrotechnology Transfer (DSSAT) model (v4.5) including the CERES-Maize and CENTURY modules was conducted for continuous maize production under annual synthetic fertilization (CC-F) and no fertilization (CC-NF) using field data from a long-term (53-yr) cropping experiment in Ontario, Canada. The assessment was based on the accuracy with which DSSAT could simulate measured grain yield, above-ground biomass, leaf area index (LAI), soil inorganic nitrogen concentration, and soil water content. Model calibration for maize cultivar was achieved using grain yield measurements from CC-F between 2007 and 2012, and model evaluation was achieved using soil and crop measurements from both CC-F and CC-NF for the same 6-yr period. Good model–data agreement for CC-F grain yields was achieved for calibration (index of agreement, d=0.99), while moderate agreement for CC-NF grain yields was achieved for evaluation (d=0.79). Model–data agreement for above-ground biomass was good (d=0.83–1.00), but the model consistently underestimated for CC-F and overestimated for CC-NF. DSSAT achieved good model–data agreement for LAI in CC-F (d=0.82–0.99), but moderate to poor agreement in CC-NF (d=0.46–0.64). The CENTURY module of DSSAT simulated soil inorganic nitrogen concentrations with moderate to good model–data agreement in CC-F (d=0.74–0.88), but poor agreement in CC-NF (d=0.40–0.50). The model–data agreement for soil water content was moderate in 2007 and 2008 for both treatments (d=0.60–0.76), but poor in 2009 (d=0.46–0.53). It was concluded that the DSSAT cropping system model provided generally good to moderate simulations of continuous maize production (yield, biomass, LAI) for a long-term cropping experiment in Ontario, Canada, but generally moderate to poor simulations of soil inorganic nitrogen concentration and soil water content.

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