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.

Hairy vetch (Vicia villosa Roth) fixes N for corn (Zea mays L.) production, and cereal rye (Secale cereale L.) accumulates soil N to reduce potential N losses. The objective of this research was to identify optimum seeding rates of vetch‐rye cover crop mixtures at Coastal Plain and Piedmont locations in Maryland. Mixtures evaluated were 14, 21, and 28 kg vetch ha−1, and 47 or 94 kg rye ha−1 in complete factorial combination. Pure vetch, rye, and no cover crop were used as controls. Cover crops were killed in early April (early kill) and early May (late kill), followed by no‐till corn without fertilizer N. Corn grain yields were significantly higher following late‐killed covers. Coastal Plain grain yields ranged from 3.1 to 7.0 Mg ha−1 and Piedmont yields ranged from 5.2 to 10.7 Mg ha−1. Within each kill date, corn yield was highest following vetch, lowest following rye, and intermediate following all six mixtures. Cover crop yield increased by 160% in the Piedmont and 83% at the Coastal Plain location when kill was delayed. Except for pure rye, N content was 1.6 to 2 times greater by the late kill date. Total N content was equal for all vetch‐rye mixtures at each date and within location, ranging from 74 to 109 kg ha−1 for early kill, and from 136 to 219 kg ha−1 for late kill. Carbon‐to‐nitrogen ratios (C/N) were 25:1 for all mixture combinations at the Piedmont location and for mixtures with low rye component at the Coastal Plain location. The best seeding rate mixture for corn production was 21 kg vetch ha−1 and 47 kg rye ha−1. The vetch‐rye mixture can scavenge potentially leachable N, while maintaining corn yields by adding fixed N to the cropping system.

Spring kill date affects cover crop N content and N availability to subsequent no‐till corn (Zea mays L.). This 2‐yr study was conducted in 1990 and 1991 at Coastal Plain and Piedmont locations in Maryland to evaluate three cover crop kill dates, three corn planting dates, and four corn fertilizer N (FN) rates following hairy vetch (Vicia villosa Roth), cereal rye (Secale cereale L.) and a vetch‐rye mixture. No‐cover checks were included for each corn planting date. Fertilizer N rates were 0 to 202 kg ha−1 in the Piedmont and 0 to 270 kg ha−1 for the Coastal Plain. The vetch‐rye mixture contained as much or more N than vetch, and more N than rye within each kill date. Cover crop biomass and N content increased for each delay in kill. In a 50‐d period from late March until early May, vetch and the vetch‐rye mixture accumulated about 2 kg N ha−1 d−1, with total topgrowth N accumulation from 144 to 203 kg ha−1 over two locations and two years. Greatest rye N accumulation was 51 kg ha−1. Corn N content ranged from 37 to 293 kg ha−1, and was significantly affected by FN rate. Within FN rate, N content was greater following vetch or vetch‐rye than following rye or no cover, particularly at low FN rates. Corn N content was greater if cover kill and corn planting were delayed until late April or mid‐May. This was attributed to greater cover crop N production and mulching effects, and the timing of summer rainfall. Corn FN requirements were greatest following rye or no cover, intermediate following vetch‐rye, and least following vetch. This demonstrates that cover crop species and kill date can be managed to conserve N with rye, supply N for the next crop with vetch, or provide both N conservation and N supply with a vetch‐rye mixture.

Winter cover crops can supply N to the next crop, reduce erosion and N leaching, and conserve or deplete soil moisture. To identify optimum corn fertilizer nitrogen (FN) rates following cover crops, we evaluated hairy vetch (Vf: Jlicia villosa Roth), Austrian winter pea [PE: Pisum sativum L. subsp. sativum var. arvense (L.) Poir.], crimson clover (CR: Trifolium incartUllum L.), and wheat (WH: Triticum aes· ti~·um L.) winter cover crops in the U.S. Coastal Plain and Piedmont for no-tillage corn (Zea mays L.) at four FN rates (topdressed NH 4 N0 3 ) onr 4 yr. Parameters evaluated included cover crop yield and N content, corn N uptake, and corn grain yield. On the Coastal Plain, Vf, PE, CR, and WH topgrowth averaged 205, 180, 170, and 40 kg N ha-•, respectively, and ~40% less for the Piedmont. With no FN, grain yields were generally greater after legumes than after no cover crop, and lowest after WH, with the best yields after legumes with 90 to 135 kg FN ha-•. Synergistic responses occurred when FN was ap· plied after legumes. Non·N-Iimited grain yield increases averaged 2 Mg ha-• (Coastal Plain) and 0.5 Mg ha-• (Piedmont), and were not directly related to cover crop N. With no cover crop, FN needed for maximum yield averaged 80 kg ha -• (Piedmont) and 135 kg ha -• (Coastal Plain). After WH, FN needs increased 15 to 30 kg ha-•, but decreased 10 to 75 kg ha-• after legumes. Hairy vetch provided the most consistent increases, with average grain yield of 10.6 Mg ha-1 (Coastal Plain) and 8.2 Mg ha-1 (Piedmont), and an economic opti· mum FN rate of 127 (Coastal Plain) and 66 kg ha-• (Piedmont).

The objective of this work was to investigate the usefulness of near infrared (NIR) reflectance spectroscopy in determining: (i) various constituents (total N, total C, active N, biomass and mineralisable N, and pH), (ii) parameters (soil source, depth from which sample was obtained, type of tillage used) and (iii) rate of application of NH 4 NO 3 fertiliser) of low organic matter soils. A NIRSystems model 6250 spectrometer was used to scan soil samples (n = 179) obtained from experimental plots at two locations with three replicate plots under plow and no till practices at each location with three rates of NH 4 NO 3 for each plot (2 × 3 × 2 × 3). For each of these, samples were taken from five depths for a total of 2 × 3 × 2 × 3 × 5 or 180 samples (one sample lost). The results demonstrated that NIR reflectance spectroscopy can be successfully used to determine some compositional parameters of low organic matter soils (particularly total C and total N). It is also apparent that for non-biological parameters (excluding soil type as reflected by source) such as the depth from which the sample was obtained, the rate of application of NH 4 NO 3 fertiliser and the form of tillage used, that NIR reflectance spectroscopy is not very useful, unless a very limited set of samples is used (i.e. single tillage and location). For other determinations, such as pH, biomass N and active N, the results may be useful depending on the exact needs in question. Finally, from the results presented here, NIR reflectance spectroscopy was not successful in determining soil N mineralisable in 21 days.