2020
DOI: 10.1002/agj2.20129
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Combination of biological and chemical soil tests best predict maize nitrogen response

Abstract: Soil tests can help optimize nitrogen (N) fertilizer rates, thereby improving farmer profitability and environmental performance. In US Midwest maize (Zea mays) production, however, most soil N tests have limited accuracy to predict N fertilizer requirements. Here we tested the individual and combined ability of 30 soil tests (12 rapid N extractions, seven biological carbon or N tests, six long-term incubation kinetic parameters, and five other routine soil tests), as well as environmental and management data,… Show more

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Cited by 26 publications
(21 citation statements)
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“…We do know that cattle manure was applied for decades to the NW site (personal communication), which may have narrowed the soil C‐to‐N ratio compared to the Central site (10.8 vs. 13.2). Therefore, the legacy organic N input has likely created a strong “site effect” with high baseline N min rates and lower crop need for fertilizer N (Jokela, 1992; McDaniel et al, 2020; Tejera et al, 2019). Many studies show N fertilizer application accelerates N min in what has been called “SOM priming” (Fernández et al, 2017; Jenkinson et al, 1985; Lu et al, 2011); however, we found conflicting evidence of this effect.…”
Section: Discussionmentioning
confidence: 99%
“…We do know that cattle manure was applied for decades to the NW site (personal communication), which may have narrowed the soil C‐to‐N ratio compared to the Central site (10.8 vs. 13.2). Therefore, the legacy organic N input has likely created a strong “site effect” with high baseline N min rates and lower crop need for fertilizer N (Jokela, 1992; McDaniel et al, 2020; Tejera et al, 2019). Many studies show N fertilizer application accelerates N min in what has been called “SOM priming” (Fernández et al, 2017; Jenkinson et al, 1985; Lu et al, 2011); however, we found conflicting evidence of this effect.…”
Section: Discussionmentioning
confidence: 99%
“…Using proven ensemble learning methods, multiple weak predictors (i.e., tools, soil, weather) could be combined for a more accurate prediction of EONR. One example of ensemble learning that was successful at improving a few N recommendation tools was boosting (Bean et al., 2018; McDaniel et al., 2020; Ransom et al., 2019). Boosting works as a forward adaptative model, where an initial model is improved by fitting a new function to the residuals of the prediction (e.g., difference between tool's recommendations and EONR).…”
Section: Introductionmentioning
confidence: 99%
“…Potentially mineralizable N (PMN) is the inorganic N released during the incubation McDaniel & Grandy, 2016). Both PMC and PMN can be an indicator of soil N-supplying power, as has been shown with maize and turfgrass N response studies in the United States McDaniel et al, 2020;Moore et al, 2019Yost et al, 2018).…”
Section: Crop Sciencementioning
confidence: 95%
“…The PMC was calculated by the cumulative CO 2 produced over the 14‐d incubation. The 14‐d length of the incubation is long enough to capture most of the change in CO 2 and a good measure of PMN (McDaniel et al., 2020).…”
Section: Methodsmentioning
confidence: 99%