Soil nitrogen. VIII.—some factors affectinga correlations between measurements of soil-N status and crop performance

1964 ◽  
Vol 15 (6) ◽  
pp. 422-428 ◽  
Author(s):  
J. K. R. Gasser ◽  
B. M. Jephcott
Keyword(s):  
Soil Nitrogen ◽  
Soil N ◽  
Crop Performance ◽  
N Status

Stimulation of root growth and soil nitrogen uptake by foliar application of urea to wheat and sunflower

1996 ◽  
Vol 126 (2) ◽  
pp. 127-135 ◽  
Author(s):  
S. Sen ◽  
P. M. Chalk
Keyword(s):  
Soil Nitrogen ◽  
Root Biomass ◽  
Dry Matter ◽  
Foliar Application ◽  
Urea Solution ◽  
Soil N ◽  
Clay Loam ◽  
Limited Effectiveness ◽  
N Status ◽  
Stimulation Of

SUMMARYWheat and sunflower plants were grown in a temperature-controlled glasshouse in Melbourne, Australia (37° 50′ S, 145° 00′ E), from 9 August to 2 October 1991, in cylinders containing two soils (Walpeup loamy sand (LS) and Gombalin clay loam (CL)) of low and moderate N status, respectively. Nitrogen fertilizer was applied by immersion of leaves in 0·18 M urea solution (10·5 atom% 15N).Plants were N-deficient in the Walpeup LS but not in the Gombalin CL soils. Both species had higher root: shoot ratios, and higher proportions of foliar-absorbed N were transferred to the roots, in the Walpeup LS plants. Plant N derived from the fertilizer and root or shoot dry matter were significantly correlated only when plants were N-deficient.In the Walpeup LS soil, N-fertilized wheat harvested 33 days after sowing (DAS) took up significantly less soil N compared with unfertilized plants, whereas significantly more soil N was taken up by N-fertilized sunflower compared with unfertilized plants harvested at 54 DAS. The fertilizerinduced response in uptake of soil N was directly related to the observed response in production of root biomass for both species. The different responses were related to the severity of the N deficiency and the limited effectiveness of foliar applications of urea in ameliorating the deficiency.

Vegetation recovery alters soil N status in subtropical karst plateau area: Evidence from natural abundance δ15N and δ18O

2021 ◽  
Author(s):  
Jing Wang ◽  
Xuefa Wen ◽  
Sidan Lyu ◽  
Xinyu Zhang ◽  
Shenggong Li ◽  
...  
Keyword(s):  
Natural Abundance ◽  
Vegetation Recovery ◽  
Soil N ◽  
Plateau Area ◽  
N Status

scholarly journals Agriculture Model Comparison Framework and MyGeoHub Hosting: Case of Soil Nitrogen

Inventions ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 25
Author(s):  
Anupam Bhar ◽  
Benjamin Feddersen ◽  
Robert Malone ◽  
Ratnesh Kumar
Keyword(s):  
Soil Nitrogen ◽  
Field Data ◽  
Model Comparison ◽  
Test Model ◽  
Soil N ◽  
N Dynamics ◽  
Benchmark Model ◽  
C Dynamics ◽  
Comparison Results ◽  
Speed Up

To be able to compare many agricultural models, a general framework for model comparison when field data may limit direct comparison of models is proposed, developed, and also demonstrated. The framework first calibrates the benchmark model against the field data, and next it calibrates the test model against the data generated by the calibrated benchmark model. The framework is validated for the modeling of the soil nutrient nitrogen (N), a critical component in the overall agriculture system modeling effort. The nitrogen dynamics and related carbon (C) dynamics, as captured in advanced agricultural modeling such as RZWQM, are highly complex, involving numerous states (pools) and parameters. Calibrating many parameters requires more time and data to avoid underfitting. The execution time of a complex model is higher as well. A study of tradeoff among modeling complexities vs. speed-up, and the corresponding impact on modeling accuracy, is desirable. This paper surveys soil nitrogen models and lists those by their complexity in terms of the number of parameters, and C-N pools. This paper also examines a lean soil N and C dynamics model and compares it with an advanced model, RZWQM. Since nitrate and ammonia are not directly measured in this study, we first calibrate RZWQM using the available data from an experimental field in Greeley, CO, and next use the daily nitrate and ammonia data generated from RZWQM as ground truth, against which the lean model’s N dynamics parameters are calibrated. In both cases, the crop growth was removed to zero out the plant uptake, to compare only the soil N-dynamics. The comparison results showed good accuracy with a coefficient of determination (R2) match of 0.99 and 0.62 for nitrate and ammonia, respectively, while affording significant speed-up in simulation time. The lean model is also hosted in MyGeoHub cyberinfrastructure for universal online access.

scholarly journals LEAF TOTAL NITROGEN CONCENTRATION AS AN INDICATOR OF NITROGEN STATUS FOR PLANTLETS AND YOUNG PLANTS OF EUCALYPTUS CLONES

2015 ◽  
Vol 39 (4) ◽  
pp. 1127-1140 ◽  
Author(s):  
Eric Victor de Oliveira Ferreira ◽  
Roberto Ferreira Novais ◽  
Bruna Maximiano Médice ◽  
Nairam Félix de Barros ◽  
Ivo Ribeiro Silva
Keyword(s):  
Total Nitrogen ◽  
Block Design ◽  
Nitrogen Concentration ◽  
Soil N ◽  
Total N ◽  
Chlorophyll Meter ◽  
N Concentration ◽  
Total Nitrogen Concentration ◽  
N Status ◽  
Leaf N

The use of leaf total nitrogen concentration as an indicator for nutritional diagnosis has some limitations. The objective of this study was to determine the reliability of total N concentration as an indicator of N status for eucalyptus clones, and to compare it with alternative indicators. A greenhouse experiment was carried out in a randomized complete block design in a 2 × 6 factorial arrangement with plantlets of two eucalyptus clones (140 days old) and six levels of N in the nutrient solution. In addition, a field experiment was carried out in a completely randomized design in a 2 × 2 × 2 × 3 factorial arrangement, consisting of two seasons, two regions, two young clones (approximately two years old), and three positions of crown leaf sampling. The field areas (regions) had contrasting soil physical and chemical properties, and their soil contents for total N, NH+4-N, and NO−3-N were determined in five soil layers, up to a depth of 1.0 m. We evaluated the following indicators of plant N status in roots and leaves: contents of total N, NH+4-N, NO−3-N, and chlorophyll; N/P ratio; and chlorophyll meter readings on the leaves. Ammonium (root) and NO−3-N (root and leaf) efficiently predicted N requirements for eucalyptus plantlets in the greenhouse. Similarly, leaf N/P, chlorophyll values, and chlorophyll meter readings provided good results in the greenhouse. However, leaf N/P did not reflect the soil N status, and the use of the chlorophyll meter could not be generalized for different genotypes. Leaf total N concentration is not an ideal indicator, but it and the chlorophyll levels best represent the soil N status for young eucalyptus clones under field conditions.

Relationship of the Illinois soil nitrogen test to spring wheat yield and response to fertilizer nitrogen

2008 ◽  
Vol 88 (5) ◽  
pp. 837-848 ◽  
Author(s):  
S J Steckler ◽  
D J Pennock ◽  
F L Walley
Keyword(s):  
Soil Nitrogen ◽  
Crop Yields ◽  
Wheat Yield ◽  
N Fertilizer ◽  
Yield Response ◽  
Regression Equations ◽  
Soil N ◽  
Fertilizer N ◽  
Available N ◽  
Nitrate N

The Illinois soil N test (ISNT) has been used to distinguish between soils that are responsive and non-responsive to fertilizer N in Illinois. We examined the suitability of this test, together with more traditional measures of soil fertility, including spring nitrate-N and soil organic carbon (SOC), for predicting yield and N fertilizer response of wheat (Triticum aestivum) on hummocky landscapes in Saskatchewan. The relationship between ISNT-N and wheat yield and fertilizer N response was assessed using data and soils previously collected for a variable-rate fertilizer study. Soils were re-analyzed for ISNT-N. Our goal was to determine if ISNT-N could be used to improve the prediction of crop yields. Although ISNT-N was correlated with both unfertilized wheat yield (r = 0.467, P = 0.01) and fertilizer N response (r = -0.671, P = 0.01) when data from all study sites were combined, correlations varied according to landscape position and site. Stronger correlations between nitrate-N and both unfertilized wheat yield (r = 0.721, P = 0.01) and fertilizer N response (r = -0.690, P = 0.01) indicated that ISNT-N offered no advantage over nitrate-N. Although both tests broadly discriminated between sites with high or low N fertility, few relationships were detected on a point-by-point basis within a field. Stepwise regression equations predicting yield and yield response did not include ISNT-N, due in part to the high degree of collinearity between ISNT-N and other variables such as SOC, suggesting that ISNT-N alone was not a key indicator of soil N supply. Key words: Illinois soil nitrogen test, potentially available N, soil N, fertilizer N recommendations

Nitrogen Uptake of Field-grown Cotton. II. Nitrate Reductase Activity and Petiole Nitrate Concentration as Indicators of Plant Nitrogen Status

1983 ◽  
Vol 19 (1) ◽  
pp. 103-109 ◽  
Author(s):  
D. M. Oosterhuis ◽  
G. C. Bate
Keyword(s):  
Nitrate Reductase ◽  
Seasonal Changes ◽  
Nitrate Reductase Activity ◽  
Nitrate Concentration ◽  
Reductase Activity ◽  
Soil N ◽  
Plant Nitrogen ◽  
Petiole Nitrate Concentration ◽  
Leaf Nitrate ◽  
N Status

SUMMARYThe possibility of using seasonal changes in leaf nitrate reductase activity (NRA) as a reliable and sensitive indicator of plant nitrogen (N) status has been investigated in field-grown cotton. These changes were compared with those in nitrate concentration in petioles and variations in soil-N concentration. We conclude that NRA in the uppermost, fully-expanded sympodial leaves may provide a more convenient, sensitive and reliable indicator of plant-N status than measurements of nitrate concentrations in petioles.

scholarly journals Spatial Distribution of Soil Nitrogen, Phosphorus and Potassium Stocks in Moso bamboo Forests in Subtropical China

2016 ◽  
Author(s):  
Xiaolu Tang ◽  
Mingpeng Xia ◽  
Fengying Guan ◽  
Shaohui Fan
Keyword(s):  
Spatial Patterns ◽  
Soil Nitrogen ◽  
Spatial Dependence ◽  
Nutrient Management ◽  
Biomass Accumulation ◽  
Moso Bamboo ◽  
Soil N ◽  
Nutrient Inputs ◽  
Extrinsic Factors ◽  
Stand Productivity

Moso bamboo is famous for fast growing and biomass accumulation, as well as high annual output for timber and bamboo shoots. These high outputs require high nutrient inputs to maintain and improve stand productivity. Soil nitrogen (N), phosphorus (P) and potassium (K) are important micronutrients for plant growth and productivity. Due to high variability of soils, analysing spatial patterns of soil N, P and K stocks is necessary for scientific nutrient management in Moso bamboo forests. In this study, soils were sampled from 138 locations across Yong’an City and ordinary kriging was applied for spatial interpolation of soil N, P and K stocks. Soil N stock showed a strong spatial dependence while soil N and P stocks presented a moderate spatial dependence, indicating soil N was mainly controlled by intrinsic factors while soil N and P stocks were controlled by both intrinsic and extrinsic factors. Different spatial patterns were observed for soil N, P and K stocks across the whole study area, indicating that fertilizations with different ratios of N:P:K should be applied for different sites to maintain and improve stand productivity. The total soil N, P and K stocks within 0-60 cm were 0.624, 0.020 and 0.583 Tg, respectively.

scholarly journals Crop Mass and N Status as Prerequisite Covariables for Unraveling Nitrogen Use Efficiency across Genotype-by-Environment-by-Management Scenarios: A Review

Plants ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1309 ◽  
Author(s):  
Gilles Lemaire ◽  
Ignacio Ciampitti
Keyword(s):  
Growth Rate ◽  
Plant Growth ◽  
Nitrogen Use Efficiency ◽  
Soil N ◽  
Nitrogen Use ◽  
Genotype By Environment ◽  
N Supply ◽  
Fertilizer Application Rate ◽  
Use Efficiency ◽  
N Status

Due to the asymptotic nature of the crop yield response curve to fertilizer N supply, the nitrogen use efficiency (NUE, yield per unit of fertilizer applied) of crops declines as the crop N nutrition becomes less limiting. Therefore, it is difficult to directly compare the NUE of crops according to genotype-by-environment-by-management interactions in the absence of any indication of crop N status. The determination of the nitrogen nutrition index (NNI) allows the estimation of crop N status independently of the N fertilizer application rate. Moreover, the theory of N dilution in crops indicates clearly that crop N uptake is coregulated by (i) soil N availability and (ii) plant growth rate capacity. Thus, according to genotype-by-environment-by-management interactions leading to variation in potential plant growth capacity, N demand for a given soil N supply condition would be different; consequently, the NUE of the crop would be dissimilar. We demonstrate that NUE depends on the crop potential growth rate and N status defined by the crop NNI. Thus, providing proper context to NUE changes needs to be achieved by considering comparisons with similar crop mass and NNI to avoid any misinterpretation. The latter needs to be considered not only when analyzing genotype-by-environment-by-management interactions for NUE but for other resource use efficiency inputs such as water use efficiency (colimitation N–water) under field conditions.

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