Pressure-induced collapse of guanidinium nitrate N–H⋯O bonded honeycomb layers into a 3-D pattern with varied H-acceptor capacity

2011 ◽  
Vol 47 (7) ◽  
pp. 2107-2109 ◽  
Author(s):  
Andrzej Katrusiak ◽  
Marek Szafrański ◽  
Marcin Podsiadło
Keyword(s):  
Nitrate N ◽  
Guanidinium Nitrate ◽  
Acceptor Capacity

Impact of Fertigation versus Controlled-release Fertilizer Formulations on Nitrate Concentrations in Nursery Drainage Water

2011 ◽  
Vol 21 (2) ◽  
pp. 176-180 ◽  
Author(s):  
P. Chris Wilson ◽  
Joseph P. Albano
Keyword(s):  
Water Quality ◽  
Controlled Release ◽  
Drainage Water ◽  
Plant Production ◽  
Fertilization Program ◽  
Median Concentration ◽  
Nitrate N ◽  
Production Area ◽  
Foliage Plant ◽  
Production Areas

Nitrate-nitrogen (N) losses in surface drainage and runoff water from ornamental plant production areas can be considerable. In N-limited watersheds, discharge of N from production areas can have negative impacts on nontarget aquatic systems. This study monitored nitrate-N concentrations in production area drainage water originating from a foliage plant production area. Concentrations in drainage water were monitored during the transition from 100% reliance on fertigation using urea and nitrate-based soluble formulations (SF) to a nitrate-based controlled-release formulation (CRF). During the SF use period, nitrate-N concentrations ranged from 0.5 to 322.0 mg·L−1 with a median concentration of 31.2 mg·L−1. Conversely, nitrate-N concentrations during the controlled-release fertilization program ranged from 0 to 147.9 mg·L−1 with a median concentration of 0.9 mg·L−1. This project demonstrates that nitrate-N concentrations in drainage water during the CRF program were reduced by 94% to 97% at the 10th through 95th percentiles relative to the SF fertilization program. Nitrate-N concentrations in drainage water from foliage plant production areas can be reduced by using CRF fertilizer formulations relative to SF formulations/fertigation. Similar results should be expected for other similar containerized crops. Managers located within N-limited watersheds facing N water quality regulations should consider the use of CRF fertilizer formulations as a potential tool (in addition to appropriate application rates and irrigation management) for reducing production impacts on water quality.

N Deprivation in Maize During Grain‐Filling. I. Accumulation of Dry Matter, Nitrate‐N, and Sulfate‐S 1

1979 ◽  
Vol 71 (3) ◽  
pp. 461-465 ◽  
Author(s):  
J. W. Friedrich ◽  
L. E. Schrader ◽  
E. V. Nordheim
Keyword(s):  
Dry Matter ◽  
Grain Filling ◽  
Nitrate N

The post-effect of lucerne on nitrate-N accumulation in a maize-wheat double cropping long-term experiment

2000 ◽  
Vol 28 (1-2) ◽  
pp. 147-152
Author(s):  
T. Szalai ◽  
F. H. Nyárai ◽  
S. Holló ◽  
M. Birkás
Keyword(s):  
N Accumulation ◽  
Double Cropping ◽  
Nitrate N ◽  
Term Experiment ◽  
Long Term Experiment

scholarly journals The implications of lag times between nitrate leaching losses and riverine loads for water quality policy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. W. McDowell ◽  
Z. P. Simpson ◽  
A. G. Ausseil ◽  
Z. Etheridge ◽  
R. Law
Keyword(s):  
Water Quality ◽  
Mean Transit Time ◽  
Lag Time ◽  
Practice Change ◽  
N Leaching ◽  
N Losses ◽  
Leaching Losses ◽  
Nitrate N ◽  
The Mean ◽  
Lag Times

AbstractUnderstanding the lag time between land management and impacts on riverine nitrate–nitrogen (N) loads is critical to understand when action to mitigate nitrate–N leaching losses from the soil profile may start improving water quality. These lags occur due to leaching of nitrate–N through the subsurface (soil and groundwater). Actions to mitigate nitrate–N losses have been mandated in New Zealand policy to start showing improvements in water quality within five years. We estimated annual rates of nitrate–N leaching and annual nitrate–N loads for 77 river catchments from 1990 to 2018. Lag times between these losses and riverine loads were determined for 34 catchments but could not be determined in other catchments because they exhibited little change in nitrate–N leaching losses or loads. Lag times varied from 1 to 12 years according to factors like catchment size (Strahler stream order and altitude) and slope. For eight catchments where additional isotope and modelling data were available, the mean transit time for surface water at baseflow to pass through the catchment was on average 2.1 years less than, and never greater than, the mean lag time for nitrate–N, inferring our lag time estimates were robust. The median lag time for nitrate–N across the 34 catchments was 4.5 years, meaning that nearly half of these catchments wouldn’t exhibit decreases in nitrate–N because of practice change within the five years outlined in policy.

Relationship Between Basal Corn Stem Nitrate N Content at V6 Growth Stage and Grain Yield

jpa ◽  
1988 ◽  
Vol 1 (4) ◽  
pp. 322-326 ◽  
Author(s):  
Edwin J. McClenahan ◽  
Randy Killorn
Keyword(s):  
Grain Yield ◽  
Growth Stage ◽  
N Content ◽  
Nitrate N

ChemInform Abstract: Green and Metal-Free Catalytic Oxidation of Urazoles into Triazolinediones by Guanidinium Nitrate and Catalytic Amounts of Silica Sulfuric Acid.

ChemInform ◽  
2010 ◽  
Vol 42 (1) ◽  
pp. no-no
Author(s):  
Mohsen Nikoorazm ◽  
Arash Ghorbani-Choghamarani ◽  
Hamid Goudarziafshar ◽  
Shadpour Mallakpour
Keyword(s):  
Sulfuric Acid ◽  
Catalytic Oxidation ◽  
Silica Sulfuric Acid ◽  
Metal Free ◽  
Guanidinium Nitrate

scholarly journals Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest

2018 ◽  
Vol 22 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Tian Guo ◽  
Margaret Gitau ◽  
Venkatesh Merwade ◽  
Jeffrey Arnold ◽  
Raghavan Srinivasan ◽  
...  
Keyword(s):  
Calculation Method ◽  
Assessment Tool ◽  
Curve Number ◽  
Surface Flow ◽  
Tile Drainage ◽  
Random Pattern ◽  
Field Site ◽  
Nitrate N ◽  
Simulated Surface ◽  
Tile Flow

Abstract. Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern US and enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991–2003) field site and river station data from the Little Vermilion River (LVR) watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine) and SWAT2012 revisions 615 and 645 (the new routine). Both the old and new routines provided reasonable but unsatisfactory (NSE  <  0.5) uncalibrated flow and nitrate loss results for a mildly sloped watershed with low runoff. The calibrated monthly tile flow, surface flow, nitrate-N in tile and surface flow, sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE  =  0.48–0.65) and nitrate in tile flow (NSE  =  0.48–0.68) for field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE  =  0.00–0.32 and −0.29–0.06, respectively). The new modified curve number calculation method in revision 645 (NSE  =  0.50–0.81) better simulated surface runoff than revision 615 (NSE  =  −0.11–0.49). The calibration provided reasonable parameter sets for the old and new routines in the LVR watershed, and the validation results showed that the new routine has the potential to accurately simulate hydrologic processes in mildly sloped watersheds.

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