A gronomy J our n al • Volume 110 , I ssue 1 • 2 018 1 T he goal of an N recommendation system is to accurately estimate the gap between the N provided by the soil and the N required by the plant. Accurately estimating this gap depends on the ability of the recommendation system to accurately estimate fi eld or subfi eld specifi c economically optimal nitrogen rates (EONR). Current recommendation systems are not as accurate as needed to provide consistently reliable estimates of N needs across years at the fi eld or subfi eld scale. Uncontrollable factors like temperature, rainfall timing, intensity and amount, and interactions of temperature and rainfall with factors such as N source, timing and placement, plant genetics, and soil characteristics combine to make N rate recommendations for an individual fi eld or rates for subfi elds a process guided as much by science as by the best professional judgement of farmers and farm advisors.Substantial evidence has accumulated that EONRs can vary widely across fi elds, within fi elds and over years in the same fi eld for a wide range of crops and geographies. Examples ABSTRACTNitrogen fi xation by the Haber-Bosch process has more than doubled the amount of fi xed N on Earth, signifi cantly infl uencing the global N cycle. Much of this fi xed N is made into N fertilizer that is used to produce nearly half of the world's food. Too much of the N fertilizer pollutes air and water when it is lost from agroecosystems through volatilization, denitrifi cation, leaching, and runoff . Most of the N fertilizer used in the United States is applied to corn (Zea mays L.), and the profi tability and environmental footprint of corn production is directly tied to N fertilizer applications. Accurately predicting the amount of N needed by corn, however, has proven to be challenging because of the eff ects of rainfall, temperature, and interactions with soil properties on the N cycle. For this reason, improving N recommendations is critical for profi table corn production and for reducing N losses to the environment. Th e objectives of this paper were to review current methods for estimating N needs of corn by: (i) reviewing fundamental background information about how N recommendations are created; (ii) evaluating the performance, strengths, and limitations of systems and tools used for making N fertilizer recommendations; (iii) discussing how adaptive management principles and methods can improve recommendations; and (iv) providing a framework for improving N fertilizer rate recommendations.

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Many states have invested significant resources to identify components of their Phosphorus (P) Index that reliably estimate the relative risk of P loss and incentivize conservation management. However, differences in management recommendations and manure application guidelines for similar field conditions among state P Indices, coupled with minimal reductions in the extent of P-impaired surface waters and soil test P (STP) levels, led the U.S. Natural Resources Conservation Service (NRCS) to revise the 590 Nutrient Management Standard. In preparation for this revision, NRCS requested that a review of the scientific underpinnings and accuracy of current P Indices be undertaken. They also sought to standardize the interpretation and management implications of P Indices, including establishment of ratings above which P applications should be curtailed. Although some states have initiated STP thresholds above which no application of P is allowed, STP alone cannot define a site's risk of P loss. Phosphorus Indices are intended to account for all of the major factors leading to P loss. A rigorous evaluation of P Indices is needed to determine if they are directionally and magnitudinally correct. Although use of observed P loss data under various management scenarios is ideal, such data are spatially and temporally limited. Alternatively, the use of a locally validated water quality model that has been shown to provide accurate estimates of P loss may be the most expedient option to conduct Index assessments in the short time required by the newly revised 590 Standard.

While P sorption in mineral soils has been extensively studied, P sorption behavior in organic‐rich soils is less known. This study was conducted to determine the relationships between Langmuir P sorption maxima (Smax) and selected physicochemical properties of soils, with particular emphasis on organic matter (OM) content. The Smax values were determined for 72 soil samples from the North Carolina Coastal Plain, along with pH, clay and OM contents, oxalate‐extractable P (Pox), Al (Alox), and Fe (Feox), and Mehlich 3 extractable P (PM3), Al (AlM3), and Fe (FeM3). Path analysis was used to examine direct and indirect effects of soil properties on Smax In the oxalate path analysis, the direct effects of clay, Alox, and Feox on Smax were significant in the order Alox > clay > Feox (P < 0.05). The Smax was highly influenced by the indirect effect of Alox and Feox through OM content. A two‐piece segmented linear relationship existed between Smax and OM and the regression slope in soils with OM ≤ 49 g kg−1 was 10‐fold greater than that for soils with OM > 49 g kg−1 This finding suggested that noncrystalline or organically bound Al and Fe in the soils with OM > 49 g kg−1 is less effective for P sorption than in the soils with lower OM content. In the Mehlich 3 path analysis, the direct effects of clay, OM, and AlM3 on Smax were significant in the order AlM3 > OM > clay (P < 0.05) while the direct effect of FeM3 on Smax was not significant. Oxalate may be better suited than Mehlich 3 as an extractant for predicting P sorption capacity in the Coastal Plain soils.