The effect of green manure and organic amendments on potato yield, nitrogen uptake and soil mineral nitrogen

Dry matter and nitrogen uptake of wheat tops at flowering, dry matter and nitrogen of wheat grain at maturity, and soil mineral nitrogen (0-90 cm) at sowing and flowering, were measured at 68 sites (1 experiment per site in 5 Shires) in southern New South Wales to test the hypotheses that: (i) mineral nitrogen below 30 cm would improve the prediction of wheat yields, (ii) soil mineral nitrogen would be better indicated by wheat yields at flowering than those at maturity, and (iii) soil mineral nitrogen would be better indicated by nitrogen uptake by wheat than by dry matter yields. Mineral nitrogen concentrations in soil at depths greater than 30 cm did not improve the prediction of wheat attributes, but hypotheses (ii) and (iii) were validated. Curvilinear regressions, significant (P< 0.05) on 2 occasions, were not important in this study. The best regression of wheat dry matter at flowering against soil mineral nitrogen at sowing was a single straight line, but the best models for the other 3 wheat variables were all bilinear. The best of the latter related the uptake of nitrogen by wheat at flowering to mineral nitrogen in the soil at sowing as follows: FNUH = (31.6 � 5.9) + (0.892 � 0.110) TMNS30 and FNUL = (9.7 � 7.3) + (0.892 � 0.110) TMNS30 where FNUH is nitrogen uptake by wheat at flowering (kg/ha) in 1960, 1964 and 1966 (when Shire wheat yields were above the Shire's long term average), FNUL is nitrogen uptake by wheat at flowering (kg/ha) in 1961, 1965 and 1974 (when Shire wheat yields were below the Shire's long term average), and TMNS30 is total mineral nitrogen (0-30 cm) (kg/ha) at sowing.

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Influence of Nitrogen Form Supply on Soil Mineral Nitrogen Dynamics, Nitrogen Uptake, and Productivity of Sugarcane

Agronomy Journal ◽

10.2134/agronj14.0422 ◽

2015 ◽

Vol 107 (2) ◽

pp. 641-650 ◽

Cited By ~ 19

Author(s):

Eduardo Mariano ◽

José M. Leite ◽

Michele X. V. Megda ◽

Luis Torres-Dorante ◽

Paulo C. O. Trivelin

Keyword(s):

Nitrogen Uptake ◽

Nitrogen Dynamics ◽

Mineral Nitrogen ◽

Nitrogen Form ◽

Soil Mineral ◽

Soil Mineral Nitrogen

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Link between paddy soil mineral nitrogen release and iron and manganese reduction examined in a rice pot growth experiment

Geoderma ◽

10.1016/j.geoderma.2018.04.002 ◽

2018 ◽

Vol 326 ◽

pp. 9-21 ◽

Cited By ~ 6

Author(s):

Masuda Akter ◽

Heleen Deroo ◽

Eddy De Grave ◽

Toon Van Alboom ◽

Mohammed Abdul Kader ◽

...

Keyword(s):

Paddy Soil ◽

Mineral Nitrogen ◽

Nitrogen Release ◽

Growth Experiment ◽

Soil Mineral ◽

Soil Mineral Nitrogen ◽

Manganese Reduction ◽

Iron And Manganese

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Stubble retention and tillage in a semi-arid environment: 2. Soil mineral nitrogen accumulation during fallow

Field Crops Research ◽

10.1016/s0378-4290(97)00035-x ◽

1997 ◽

Vol 52 (3) ◽

pp. 221-229 ◽

Cited By ~ 16

Author(s):

G.J. O'Leary ◽

D.J. Connor

Keyword(s):

Arid Environment ◽

Mineral Nitrogen ◽

Nitrogen Accumulation ◽

Soil Mineral ◽

Soil Mineral Nitrogen ◽

Stubble Retention ◽

Semi Arid

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Soil mineral nitrogen and nitrate leaching losses in soil tillage systems combined with a catch crop

Soil and Tillage Research ◽

10.1016/s0167-1987(98)00197-4 ◽

1999 ◽

Vol 50 (2) ◽

pp. 115-125 ◽

Cited By ~ 78

Author(s):

Maria Stenberg ◽

Helena Aronsson ◽

Börje Lindén ◽

Tomas Rydberg ◽

Arne Gustafson

Keyword(s):

Nitrate Leaching ◽

Mineral Nitrogen ◽

Soil Tillage ◽

Catch Crop ◽

Soil Mineral ◽

Soil Mineral Nitrogen ◽

Tillage Systems ◽

Leaching Losses

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Application of the Bayesian calibration methodology for the parameter estimation in CoupModel

Advances in Geosciences ◽

10.5194/adgeo-21-13-2009 ◽

2009 ◽

Vol 21 ◽

pp. 13-24 ◽

Cited By ~ 8

Author(s):

Y. Conrad ◽

N. Fohrer

Keyword(s):

Soil Water ◽

Parameter Space ◽

Mineral Nitrogen ◽

Soil Mineral ◽

Soil Mineral Nitrogen ◽

Bayesian Calibration ◽

Soil Temperatures ◽

Simulation Results ◽

Water Contents ◽

Soil Water Contents

Abstract. This study provides results for the optimization strategy of highly parameterized models, especially with a high number of unknown input parameters and joint problems in terms of sufficient parameter space. Consequently, the uncertainty in model parameterization and measurements must be considered when highly variable nitrogen losses, e.g. N leaching, are to be predicted. The Bayesian calibration methodology was used to investigate the parameter uncertainty of the process-based CoupModel. Bayesian methods link prior probability distributions of input parameters to likelihood estimates of the simulation results by comparison with measured values. The uncertainty in the updated posterior parameters can be used to conduct an uncertainty analysis of the model output. A number of 24 model variables were optimized during 20 000 simulations to find the "optimum" value for each parameter. The likelihood was computed by comparing simulation results with observed values of 23 output variables including soil water contents, soil temperatures, groundwater level, soil mineral nitrogen, nitrate concentrations below the root zone, denitrification and harvested carbon from grassland plots in Northern Germany for the period 1997–2002. The posterior parameter space was sampled with the Markov Chain Monte Carlo approach to obtain plot-specific posterior parameter distributions for each system. Posterior distributions of the parameters narrowed down in the accepted runs, thus uncertainty decreased. Results from the single-plot optimization showed a plausible reproduction of soil temperatures, soil water contents and water tensions in different soil depths for both systems. The model performed better for these abiotic system properties compared to the results for harvested carbon and soil mineral nitrogen dynamics. The high variability in modeled nitrogen leaching showed that the soil nitrogen conditions are highly uncertain associated with low modeling efficiencies. Simulated nitrate leaching was compared to more general, site-specific estimations, indicating a higher leaching during the seepage periods for both simulated grassland systems.

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