Soil-based tests for nitrogen fertilizer recommendations in Arkansas rice production

Costs associated with rice production have continued to rise, primarily in the form of nitrogen (N) fertilizer. Current N fertilizer recommendations are based on a combination of three factors; soil texture, cultivar and previous crop. To improve N fertilizer management for Arkansas rice producers a stronger emphasis on the soil's ability to supply N should be considered. New soil testing methods such as the Illinois Soil Nitrogen Test (ISNT) and direct steam distillation (DSD) have been suggested as a predictor of potentially mineralizable-N. Therefore, the first research objective was to evaluate DSD as an alternative to the ISNT. Laboratory experiments were conducted to compare the two methods based on recovery of N from pure organic compounds, and recovery of 15N-labeled glucosamine-N added to soils. Both methods recovered appreciable amounts of amino sugar-N from pure compounds. Recovery of N from glutamine and asparagine was higher using DSD. Glucosamine-15N recovery significantly and positively correlated with soil total N. Although the ISNT and DSD measure different amounts of amino sugar-N and transition amino acid-N, they recover relatively the same amount of hydrolyzable-N for a given soil. The second objective of the study was to identify the changes in alkaline hydrolyzable-N (AH-N) with soil depth as quantified by the ISNT and DSD. Soil samples were collected from 0-60 cm in 15-cm depth increments and analyzed for AH-N (ISNT and DSD) and TN. Alkaline hydrolyzable-N ranged from 22 to 280 mg N kg soil-1 and the highest values were not always in the top 15 cm of the soil. Total N ranged from 191 to 1542 mg N kg soil-1 and the highest values were always in the top 15 cm. Alkaline hydrolyzable-N accounted for 11-38% of soil TN and was variable across sites and depths. Variation in AH-N and the fraction of TN quantified as AH-N with site and soil depth indicates the importance of proper sampling depth (i.e., to the rooting depth of a given crop) for correlation and calibration of crop response using either the ISNT or DSD. The final objective of the study was to evaluate the ability of the ISNT and DSD to correlate with rice response parameters and calibrate the N fertilizer rate to achieve 95% relative grain yield (RGY). Twenty-five N response trials were conducted from 2004 through 2008 to correlate AH-N as quantified by the ISNT and DSD methods with rice response parameters such as total N uptake (TN), check plot grain yield and percent RGY and calibrate AH-N to predict the fertilizer N rate required to achieve 95% RGY. Relationships with the selected parameters were evaluated for both methods over a series of depth increments that included 0-15, 15-30, 30-45, 45-60, 0-30, 0-45 and 0-60 cm using linear regression models. Alkaline hydrolyzable-N was significantly and positively correlated with all rice response parameters, except check plot grain yield and percent RGY at the 45-60 cm depth. Coefficients of determination were greatest for percent RGY at the 0-30 and 0-45 cm depth for the ISNT (r2=0.57) and DSD (r 2=0.73), respectively. Calibration of the N fertilizer rate to achieve 95% RGY resulted in similar trends as the correlation of rice response parameters, but with higher r2 values. Alkaline hydrolyzable-N was able to explain 68% and 89% of the variability in calibration for the ISNT at the 0-30 cm depth and the DSD at the 0-45 cm depth, respectively. The success of AH-N in predicting rice response to N fertilizer as well as the calibration of AH-N with the N fertilizer rate to achieve 95% RGY can be attributed to the N dynamics that exist in direct-seeded, delayed-flood rice production systems and by identifying the proper sampling depth that maximizes the predictive ability of both the ISNT and DSD. Identification of a simple soil test to measure the amount of available soil N is becoming more and more important and will be essential for the long-term sustainability of Arkansas rice production. Benefits of a soil N test are not just about optimizing economic or agronomic returns, but making environmentally sound N fertilizer decisions.