Balancing Corn Yield Goals and N Fertilization Rates

Establishing realistic yield goals is essential for environmentally and economically sustainable crop production. It is also important because many of the variable inputs, including fertilizer N rates, are often based upon those goals. If yield goals are beyond what uncontrollable factors such as rainfall can support, many controllable inputs such as N fertilizer will probably be used at rates in excess of crop needs. This scenario will result in reduced nutrient recovery, decreased profitability or return on fertilizer investment, and an increased potential for N loss to groundwater resources. If yield goals are set too low, crop nutrient needs may be underestimated leading to loss of yield, quality, and profit

Soil Degradation: Will Humankind Ever Learn?

Citation: Karlen, D. L., & Rice, C. W. (2015). Soil Degradation: Will Humankind Ever Learn? Sustainability, 7(9), 12490-12501. doi:10.3390/su70912490Soil degradation is a global problem caused by many factors including excessive tillage, inappropriate crop rotations, excessive grazing or crop residue removal, deforestation, mining, construction and urban sprawl. To meet the needs of an expanding global population, it is essential for humankind to recognize and understand that improving soil health by adopting sustainable agricultural and land management practices is the best solution for mitigating and reversing current soil degradation trends. This research editorial is intended to provide an overview for this Special Issue of Sustainability that examines the global problem of soil degradation through reviews and recent research studies addressing soil health in Africa, Australia, China, Europe, India, North and South America, and Russia. Two common factorssoil erosion and depletion of soil organic matter (SOM)emerge as consistent indicators of how the thin layer covering the planet that stands between us and starvation is being degraded. Soil degradation is not a new problem but failing to acknowledge, mitigate, and remediate the multiple factors leading to it is no longer a viable option for humankind. We optimistically conclude that the most promising strategies to mitigate soil degradation are to select appropriate land uses and improve soil management practices so that SOM is increased, soil biology is enhanced, and all forms of erosion are reduced. Collectively, these actions will enable humankind to take care of the soil so it can take care of us.Soil degradation is a global problem caused by many factors including excessive tillage, inappropriate crop rotations, excessive grazing or crop residue removal, deforestation, mining, construction and urban sprawl. To meet the needs of an expanding global population, it is essential for humankind to recognize and understand that improving soil health by adopting sustainable agricultural and land management practices is the best solution for mitigating and reversing current soil degradation trends. This research editorial is intended to provide an overview for this Special Issue of Sustainability that examines the global problem of soil degradation through reviews and recent research studies addressing soil health in Africa, Australia, China, Europe, India, North and South America, and Russia. Two common factors—soil erosion and depletion of soil organic matter (SOM)—emerge as consistent indicators of how “the thin layer covering the planet that stands between us and starvation” is being degraded. Soil degradation is not a new problem but failing to acknowledge, mitigate, and remediate the multiple factors leading to it is no longer a viable option for humankind. We optimistically conclude that the most promising strategies to mitigate soil degradation are to select appropriate land uses and improve soil management practices so that SOM is increased, soil biology is enhanced, and all forms of erosion are reduced. Collectively, these actions will enable humankind to “take care of the soil so it can take care of us”

SMAF: A Soil Health Assessment Tool

The Soil Management Assessment Framework (SMAF) was developed to help quantify soil quality/health effects of tillage, crop rotation, and other soil management practices. Our objective was to determine if the SMAF could detect soil health differences after growing a single winter triticale (X Triticosecale Wittmack) crop. Soil samples were collected from 0 to 7.5- and 7.5 to 15- cm depth increments during the 2003 – 2004 and 2004 – 2005 growing seasons near Ames and Lewis, IA, and analyzed for several potential soil quality indicators. The SMAF analysis showed higher soil quality ratings for surface than subsurface samples. It also showed that a single winter grain crop can significantly improve soil quality after either corn (Zea mays L.) or soybean (Glycine max [L.] Merr.). Finally, in response to increasing interest in soil health assessments, a detailed appendix is attached to provide guidance for future soil health assessments

Spatial Variability Analysis: A First Step in Site-Specific Management

Small-scale spatial variability of selected soil-test parameters in two adjacent central Iowa fields is discussed. We used semivariance analysis to detect the distance to which parameters were correlated and to estimate the strength of each correlation. Distinct differences in spatial dependence patterns were observed for the two farming systems

Crop Rotation Effects on N03-N Leaching and Corn Yields Under Manure Management Practices

Nonpoint source nutrient pollution is recognized as an important environmental and social issue for several reasons. First, manure from swine production facilities can have serious impacts on the quality of surface and ground water resources. Second, several states are in the process of creating laws to reduce nitrogen and phosphorus loadings from manure to soil and water resources. Third, pollution of water resources from nutrients supplied by manure to croplands will set parameters for developing public policies on the management of manure

Statistical Asynchronous Regression: Determining the Relationship Between two Quantities that are not Measured Simultaneously

We introduce the Statistical Asynchronous Regression (SAR) method: a technique for determining a relationship between two time varying quantities without simultaneous measurements of both quantities. We require that there is a time invariant, monotonic function Y = u(X) relating the two quantities, Y and X. In order to determine u(X), we only need to know the statistical distributions of X and Y. We show that u(X) is the change of variables that converts the distribution of X into the distribution of Y, while conserving probability. We describe an algorithm for implementing this method and apply it to several example distributions. We also demonstrate how the method can separate spatial and temporal variations from a time series of energetic electron flux measurements made by a spacecraft in geosynchronous orbit. We expect this method will be useful to the general problem of spacecraft instrument calibration. We also suggest some applications of the SAR method outside of space physics.Comment: 27 pages, 10 figures, stronger motivations and rewriting to make the paper more accessible to a general audience. in press in J. Geophys. Res. (Space Physics

Land management effects on wet aggregate stability and carbon content

Land management affects soil structure and many other soil properties and processes. Our objectives were to evaluate soil organic C (SOC), aggregate size distribution, aggregate-associated C, and soil structure as affected by long-term land management and slope. A chronosequence of 38 on-farm sites with low to high (5–18%) slopes was selected to evaluate 5–40 yr of management. The sites were classified as business as usual (BAU) cropland (BAU-Crop), BAU pasture (BAU-Past), newly established conservation reserve program (CRP) areas (CRP-New), and established CRP (CRP-Old). Soil samples were collected from the 0-to-5- and 5-to-15-cm depth increments and processed for soil property measurements including fractionation by wet sieving into five aggregate size classes (\u3e2,000, 1,000–2,000, 500–1,000, 250–500, and 53–250 μm). Within the surface 5 cm, mean weight diameter (MWD) and geometric mean diameter (GMD) were used to characterize soil structural stability. The BAU-Past and CRP-Old sites had 79% more macroaggregates (\u3e2,000, 1,000–2,000, and 500–1,000 μm), 123% higher MWD, 38% higher GMD, and 47% higher SOC than BAU-Crop or CRP-New sites. The 5-to-15-cm depth increment showed a similar but lower magnitude response. Aggregate-associated C was quantified using a constant soil mass that reflected aggregate size distribution to prevent overestimating C content. Lower-slope locations had more SOC, more macroaggregates, more C associated with macroaggregates, and higher GMD and MWD compared with high-slope locations across all management classifications and soil depths. The results support our hypothesis that the high-slop soils may benefits from specific management decisions than the lower-sloping soils as a function of landscape property. We recommend reestablishing grassland on sloping land that is susceptible to excessive soil erosion, although those practices will likely take a long time to restore soil structural stability and SOC content to precultivation levels

Multilocation Corn Stover Harvest Effects on Crop Yields and Nutrient Removal

Corn (Zea mays L.) stover was identified as an important feedstock for cellulosic bioenergy production because of the extensive area upon which the crop is already grown. This report summarizes 239 site-years of field research examining effects of zero, moderate, and high stover removal rates at 36 sites in seven different states. Grain and stover yields from all sites as well as N, P, and K removal from 28 sites are summarized for nine longitude and six latitude bands, two tillage practices (conventional vs no tillage), two stover-harvest methods (machine vs calculated), and two crop rotations {continuous corn (maize) vs corn/soybean [Glycine max (L.) Merr.]}. Mean grain yields ranged from 5.0 to 12.0 Mg ha−1 (80 to 192 bu ac−1). Harvesting an average of 3.9 or 7.2 Mg ha−1(1.7 or 3.2 tons ac−1) of the corn stover resulted in a slight increase in grain yield at 57 and 51 % of the sites, respectively. Average no-till grain yields were significantly lower than with conventional tillage when stover was not harvested, but not when it was collected. Plant samples collected between physiological maturity and combine harvest showed that compared to not harvesting stover, N, P, and K removal was increased by 24, 2.7, and 31 kg ha−1, respectively, with moderate (3.9 Mg ha−1) harvest and by 47, 5.5, and 62 kg ha−1, respectively, with high (7.2 Mg ha−1) removal. This data will be useful for verifying simulation models and available corn stover feedstock projections, but is too variable for planning site-specific stover harvest

Magnetic field sensors using 13-spin cat states

Measurement devices could benefit from entangled correlations to yield a measurement sensitivity approaching the physical Heisenberg limit. Building upon previous magnetometric work using pseudo-entangled spin states in solution-state NMR, we present two conceptual advancements to better prepare and interpret the pseudo-entanglement resource as well as the use of a 13-spin cat state to measure the local magnetic field with a sensitivity beyond the standard quantum limit.Comment: 6 pages, 5 figures; v2: corrected figure 3, expanded conclusion, simplified explanation of equation 2; v3: accepted versio