Field-scale N fertilizer recommendations: The spatial covariance problem

2002 ◽  
Vol 82 (1) ◽  
pp. 59-64 ◽  
Author(s):  
Bing Cheng Si ◽  
R. Gary Kachanoski

Theory is needed to estimate field-scale crop response and calibration relationships (soil test versus recommended fertilize r rate) from local scale measurements, in fields with spatially variable soil properties. The objective of this study is to present a theoretical stochastic framework for examining the influence of the spatial variability of soil properties, and covariance between soil properties, on field-scale crop response to fertilizer. An analytical solution of the general stochastic scaling equation is given for the specific case of wheat grain yield response to applied N fertilizer with variable soil-N test and available water in Saskatchewan, Canada. The analytical solution indicates spatial variance of soil properties within fields influences field average yield response to applied fertilizer. The field-scale maximum economic rate of fertilizer N (MERN), depends not only on the average soil properties, but also on (1) the amount of variability of soil properties in the field, and (2) the correlation between the spatial patterns of soil properties (e.g., soil test and available water). For the specific soil examined, positive spatial correlation between soil-N test and available water significantly increases MERN, for the same average soil test and available water. Negative correlation decreases MERN. Key Words: Fertilizer recommendation, soil test, spatial variability, crop response, soil water

1996 ◽  
Vol 76 (1) ◽  
pp. 1-6 ◽  
Author(s):  
R. G. Kachanoski ◽  
G. L. Fairchild

Soil fertility may vary considerably within a field. The effects of variable soil fertility on the relationships among average crop yield response, average soil test, and fertilizer applied evenly to a field have not been examined. This paper develops stochastic equations to describe the average yield gain on a field basis from the application of a single constant rate of fertilizer, in fields with variable soil fertility. The equations are solved numerically for the specific case of nitrogen fertilizer on corn (Zea mays L.) in Ontario, Canada. The results suggest that since the relationships among yield response, soil test, and applied fertilizer are non-linear, a single soil test calibration cannot exist for fields with different spatial variability. Soil test calibrations obtained from sites with low variability (for example small plots) will not hold for sites with higher variability (for example farm fields). Calibrations obtained from sites with low variability will under-predict the optimum economic fertilizer rate for sites with low variability will under-predict the optimum economic fertilizer rate for sites with high variability. The results do not invalidate soil test calibration relationships per se. The challenge is to combine these calibrations with additional knowledge about the spatial distribution and field-scale variability of soil test values in order to maximize economic benefit. Key words: Spatial variability, soil test, fertilizer recommendation, yield, corn, field scale


2008 ◽  
Vol 88 (5) ◽  
pp. 837-848 ◽  
Author(s):  
S J Steckler ◽  
D J Pennock ◽  
F L Walley

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


2015 ◽  
Vol 154 (7) ◽  
pp. 1218-1240 ◽  
Author(s):  
T. J. SALO ◽  
T. PALOSUO ◽  
K. C. KERSEBAUM ◽  
C. NENDEL ◽  
C. ANGULO ◽  
...  

SUMMARYEleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study.


Geoderma ◽  
2019 ◽  
Vol 333 ◽  
pp. 108-122 ◽  
Author(s):  
Adrian L. Collins ◽  
Emma Burak ◽  
Paul Harris ◽  
Simon Pulley ◽  
Laura Cardenas ◽  
...  

Soil Research ◽  
2003 ◽  
Vol 41 (4) ◽  
pp. 653 ◽  
Author(s):  
R. F. Brennan ◽  
M. D. A. Bolland

Thirty-five unfertilised soils collected in south-western Australia were used to measure the effect of soil properties on (i) shoot yield responses of 50-day-old clover (Trifolium subterraneum L. cv. Nungarin) plants to applied phosphorus (P), and (ii) extractability of bicarbonate soil test P (slope of the linear relationship between Colwell P and the amount of P applied). Data for the relationship between shoot yield and the amount of P applied were fitted to a rescaled Mitscherlich equation to calculate the amount of P required to produce 50% and 90% of the maximum yield (P50% and P90%) and determine the curvature (c) and n coefficients of the equation. When the value of n is 1.00, the response curve is exponential, and as the value of n increases above 1.00 the response curve becomes more sigmoidal. The c, n, P50%, P90%, and extractability values were related to properties of the 35 soils.There was a significant (P < 0.05) trend for the values of c and extractability to decrease as the capacity of the soil to sorb P increased. Consequently, as the soil sorbed more P, the trend was that (1) more P needed to be applied to produce the same yield, so both P50% and P90% tended to significantly (P < 0.05) increase; (2) shoot yield responses to applied P became more sigmoidal so the value of the n coefficient tended to significantly (P < 0.05) increase; (3) more P needed to be applied to a soil to produce the same soil test P value; and (4) larger soil test P values were needed to produce the same yield. No single soil property adequately predicted P50%, P90%, extractability, c, or n. Stepwise multiple regression indicated that (1) clay content and P buffer capacity (PBC) of soil together accounted for 48% of the variation in P50%, 56% of the variation in P90%, and 52% of the variation in c; (2) PBC and soil pH together accounted for 17% of the variation in n; and (3) PBC, percentage clay and percentage organic carbon content of soil together accounted for 68% of the variation in extractability.


2004 ◽  
Vol 84 (3) ◽  
pp. 307-316 ◽  
Author(s):  
I. P. O’Halloran ◽  
A. P. von Bertoldi ◽  
S. Peterson

Identification of management units for the variable application of fertilizer N is a critical component for the implementation of a site-specific N management program. Field studies were conducted to examine the spatial variability of soil nitrate levels, spring barley (Hordeum vulgare) and corn (Zea mays L.) yields and yield responses to fertilizer N applications on two sites in southwestern Ontario, Canada. Soil sampling on a 3 × 10 m grid indicated that soil NO3-N test values had a log-normal distribution and varied considerably at both sites with CVs exceeding 57% on the untransformed data. Ranges of spatial correlation varied from 20 to 95 m with 30 to 80% of the total variance of the ln-transformed data existing as either random or unsampled variance, and these parameters were not temporally stable. Although NO3-N tended to increase at lower slope positions in two of the 3 site-years, considerable within-slope variability of soil NO3-N levels was also observed. Spatial variations in soil N test levels, crop yields and crop yield responses to applied fertilizer N were not strongly related to one another indicating that it would be unlikely that either soil N test level or yield would adequately delineate management zones for the variable application of N fertilizer at these sites. Key words: Variogram, topography, site-specific crop management


2021 ◽  
pp. 20-25
Author(s):  
Abdurahman Husien ◽  
Tilahun Firomsa ◽  
Tilahun Abera

Nowadays, a balanced fertilizer recommendation is of paramount importance in order to confirm the security and sustainably increase crop productivity for farmers and other stakeholders. Soil test crop response based phosphorus calibration study in two years (2017 and 2018) was done for bread wheat in kofele district with objectives to assess and evaluate yield response of bread wheat to phosphorus-fertilizer applications in soils that have initial high/medium/low levels of phosphorus on Eutric Vertisols. A composite soil samples collection were made in zigzag method from farmer’s land and analyzed for available P in order to identify the level of the required parameters in the soil to select farmland for actual experiment. Accordingly, phosphorus calibration study treatments include application of 0, 10,20,30,40 and 50 kg P ha-1 with recommended nitrogen 69 kg N ha-1 with RCBD design was used with two replications. The plot size of 5mx4m with a seed rate of 150 kg ha-1 and Ogolcho variety which had been recommended for the area was used. So that the result showed that phosphorus fertilizer application significantly affects yield and yield components of bread wheat. Similarly, phosphorous fertilizer application at different rates increased grain yield of bread wheat by 28 to 44% compared to the control. Furthermore, the study was revealed that phosphorus critical (Pc) point for bread wheat was 19, and phosphorus requirement factor was also 3.30. Therefore, future research should focus on verification of the result on farmland before disseminating the technology to the end-user.


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