@article{moorberg_vepraskas_white_richter_2023, title={Phosphorus Fluxes in a Restored Carolina Bay Wetland Following Eight Years of Restoration}, volume={43}, ISSN={["1943-6246"]}, DOI={10.1007/s13157-023-01725-z}, abstractNote={Restoring wetlands on agricultural land can release soil phosphorus (P) to surface waters. Phosphorus is a limiting nutrient in many freshwater systems, thus restricting its release will improve surface water quality by preventing algal blooms. A P balance was used to examine how P was cycling in a Carolina Bay wetland eight years after restoration from prior-drained agricultural land. The change in soil P was evaluated between archived samples taken at restoration (2005), and eight years after restoration (2013). Measured P fluxes included atmospheric deposition, plant uptake, and loss to surface water outflow. The soil total P pool at the time of restoration was 810 kg P ha−1. No significant (α = 0.05) decrease in the soil P pool was observed over the eight years. Atmospheric deposition contributed 1.0 kg P ha−1 yr−1, plants incorporated 3.3 P ha−1 yr−1 into woody biomass and 0.4 kg P ha−1 yr−1 as forest floor litter, and 0.2 kg P ha−1 yr−1 was lost to surface waters draining the wetland. Because the loss of P to surface waters was small, and because runoff water concentrations of P declined through this period of study to concentrations below those likely to cause eutrophication (< 0.1 mg L−1), we concluded that the wetland was not contributing to the degradation of surface water quality of nearby streams following restoration. Further, isolated wetlands such as that studied may be promising sites for future wetland mitigation projects due to limited impacts on surface water quality.}, number={6}, journal={WETLANDS}, author={Moorberg, Colby J. and Vepraskas, Michael J. and White, Jeffrey G. and Richter, Daniel D.}, year={2023}, month={Aug} }
 @article{white_dodd_walters_2020, title={Can an amino sugar test estimate potentially available nitrogen from biosolids?}, url={https://doi.org/10.1002/saj2.20020}, DOI={10.1002/saj2.20020}, abstractNote={Abstract}, journal={Soil Science Society of America Journal}, author={White, Jeffrey G. and Dodd, Ryan and Walters, Robert}, year={2020}, month={Jan} }
 @article{sullivan_white_vepraskas_2018, title={Assessing Carolina Bay Wetland Restoration Risks to Downstream Water Quality by Characterizing Land Use and Stream Proximity}, volume={39}, ISSN={0277-5212 1943-6246}, url={http://dx.doi.org/10.1007/S13157-018-1095-5}, DOI={10.1007/s13157-018-1095-5}, number={3}, journal={Wetlands}, publisher={Springer Science and Business Media LLC}, author={Sullivan, D.G. and White, J.G. and Vepraskas, M.J.}, year={2018}, pages={1–12} }
 @article{walters_white_2018, title={Biochar In Situ Decreased Bulk Density and Improved Soil-Water Relations and Indicators in Southeastern US Coastal Plain Ultisols}, volume={183}, ISSN={["1538-9243"]}, DOI={10.1097/SS.0000000000000235}, abstractNote={ABSTRACT Biochar may improve soil physical properties for crop growth, but multiyear, multicrop field studies are lacking. To determine the effects of biochar on soil physical properties, we applied 0, 10, 20, 40, and 80 Mg ha−1 biochar with/without NPK fertilizer to the surface 15 cm of 1 × 1 m2 plots in a single association of fine-loamy, siliceous, subactive, thermic Oxyaquic and Aquic Paleudults under a 2-year corn-winter wheat–double-crop soybean rotation. After 3 years, we sampled soil to 7.6 cm, measured bulk density and water retention, and then derived pore-size distribution and related physical and water retention model parameters. Fertilizer had little to no effect. Among the statistically significant results, biochar increased structural porosity (3- to 59-&mgr;m effective pore diameter [EPD]) but neither matrix- (0.2- to 3-&mgr;m EPD) nor macro (EPD >59 &mgr;m) porosity. Biochar ≥40 Mg ha−1 decreased bulk density 16%; 80 Mg ha−1 increased total porosity 14%. However, it also increased water content at −1,500 kPa 22.5%. Biochar ≥40 Mg ha−1 increased the drained upper limit (DUL) by 15%; relative field capacity, 3%; and total and structural plant-available water (PAW: held between the DUL and −1,500 kPa), 7 and 18%, respectively. Increases were greatest at −10 kPa and least at −33 kPa. At −10 kPa, 80 Mg ha−1 biochar increased total PAW 4.0-mm equivalent depth compared with 5.7 mm for structural PAW, approximately 0.5-day demand for actively growing corn. Modeled saturated water content increased with total porosity. Biochar improved plant-soil-water relations, but required high rates.}, number={3}, journal={SOIL SCIENCE}, author={Walters, Robert D. and White, Jeffrey G.}, year={2018}, pages={99–111} }
 @article{white_dodd_walters_2018, title={Biosolids Type, Rate, and Receiving Soil Affect Anaerobic Incubation Nitrogen Availability Coefficients}, volume={82}, ISSN={["1435-0661"]}, DOI={10.2136/sssaj2018.06.0219}, abstractNote={
Core Ideas
Potentially available N (PAN) differed greatly among biosolids, soils, and rates.
Nitrogen availability coefficients (NAC) under or overestimated PAN from −140 to 181%.
The effects of soil and biosolids on PAN and NAC were of similar magnitudes.
Biosolids NAC might best be estimated with the receiving soil and a range of rates.
Seven‐day anaerobic incubation can provide relatively quick and easy estimates of potentially available N (PAN), but has been little used to estimate N availability coefficients (NAC) of biosolids destined for land application. We hypothesized that waterlogged‐incubation estimates of PAN and NAC depend on biosolids type, application rate, and receiving soil. We applied three dissimilar biosolids at five rates to four representative southeastern US soils and measured NH4–N and NO3–N after a 7‐d laboratory waterlogged incubation. Target PAN rates were 0, 0.5, 1, 1.5, and 2× a realistic yield expectation (RYE) rate, 127 kg N ha–1, for tall fescue (Festuca arundinacea), a common biosolids‐receiving grass. Biosolids application rates were based on biosolids types, associated book‐value NACs, and biosolids total N. Anaerobic incubation of soil plus biosolids yielded predominantly NH4–N. There were three‐way biosolids × rate × soil interactions for NH4–N, PAN, and NAC. The PAN differed substantially among biosolids, rates, and receiving soils, ranging from –12.1 to 146 mg kg–1, while NAC ranged from ‐0.13 to 0.86. Negative values suggested N lost via denitrification or immobilization. The PAN trends reflected biosolids total N. At the highest application rate, soil had no detectable effect on the NAC; otherwise, soil affected NAC by as much as an order of magnitude. Presuming anaerobic incubation provides reasonable estimates of PAN, NAC of any particular biosolids might best be estimated via incubation with the receiving soil across an RYE‐based range of N application rates, rather than relying on book value NAC.}, number={5}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={White, Jeffrey G. and Dodd, Ryan and Walters, Robert}, year={2018}, pages={1290–1300} }
 @article{sullivan_white_vepraskas_2017, title={Using Land-Use Change, Soil Characteristics, and a Semi-Automated On-Line GIS Database to Inventory Carolina Bays}, volume={37}, ISSN={["1943-6246"]}, DOI={10.1007/s13157-016-0842-8}, number={1}, journal={WETLANDS}, publisher={Springer Nature}, author={Sullivan, Dana G. and White, Jeffrey G. and Vepraskas, Michael J.}, year={2017}, month={Feb}, pages={89–98} }
 @article{jameson_white_osmond_aziz_2016, title={Determination of Biosolids Phosphorus Solubility and Its Relationship to Wastewater Treatment}, volume={88}, ISSN={["1554-7531"]}, DOI={10.2175/106143016x14609975746406}, abstractNote={ABSTRACT:}, number={7}, journal={WATER ENVIRONMENT RESEARCH}, publisher={Water Environment Federation}, author={Jameson, Molly and White, Jeffrey G. and Osmond, Deanna L. and Aziz, Tarek}, year={2016}, month={Jul}, pages={602–610} }
 @inbook{white_d’aiuto_heitman_2016, place={Redlands, CA}, title={Estimating Statewide Soil Moisture Using an In Situ Sensing Network and Passive Microwave Remote Sensing}, ISBN={978-1-58948-448-1}, booktitle={STEM and GIS in Higher Education}, publisher={ESRI Press}, author={White, J.G. and D’Aiuto, C. and Heitman, J.}, editor={Cowen, DavidEditor}, year={2016}, pages={15} }
 @article{bordeaux_grossman_white_osmond_poore_pietrosemoli_2014, title={Effects of rotational infrastructure within pasture-raised pig operations on ground cover, soil nutrient distribution, and bulk density}, volume={69}, ISSN={["1941-3300"]}, DOI={10.2489/jswc.69.2.120}, abstractNote={Interest in pasture-based pork products has increased significantly in recent years. However, nitrogen (N) losses resulting from these systems are common due to importation of feed, high stocking rates, and pig behavior. This study was conducted to evaluate soil inorganic N, soil-test phosphorus (STP), ground cover, and compaction changes as impacted by rotational shade, water, and feed structures in a pasture-raised pig operation over two 12-week pig occupations. Shade and watering structures were rotated weekly for 12 weeks within a rotational (mobile) scheme; data were compared to a stationary structure system as well as to a managed hay operation with no pigs. Soil samples were acquired from subplots and analyzed for distribution of inorganic N concentrations among main plot treatments, including nitrate (NO3), ammonium (NH4), and STP values. Soil inorganic N concentrations were higher in exterior subplot positions than in interior positions. This pattern was not maintained after a second pig group occupied the plots. Soil test phosphorus was unaffected by either pig occupation. Ground cover percentages were higher in control (hay) treatments than for pig treatments, however no difference was found between mobile and stationary structure treatments in either pig occupation. Soil compaction, as measured by soil bulk density, was found to be higher under permanent shade structure locations as compared to mobile and control treatments. Mobile and control compaction levels were not different for the second occupation, utilizing a more intensive sampling scheme, suggesting a benefit to the rotation of shade, water and feed infrastructure. The weekly rotation of infrastructure performed during both occupations was both labor intensive and time consuming. The observed lack of improvement in nutrient distribution to a rotational infrastructure may limit its utility in pastured-pig systems. However, further options are available that would allow the production of pasture-raised pigs while minimizing associated nutrient loading and pasture degradation.}, number={2}, journal={JOURNAL OF SOIL AND WATER CONSERVATION}, publisher={Soil and Water Conservation Society}, author={Bordeaux, C. and Grossman, J. and White, J. and Osmond, D. and Poore, M. and Pietrosemoli, S.}, year={2014}, pages={120–130} }
 @article{pan_boyles_white_heitman_2012, title={Characterizing Soil Physical Properties for Soil Moisture Monitoring with the North Carolina Environment and Climate Observing Network}, volume={29}, ISSN={["0739-0572"]}, DOI={10.1175/jtech-d-11-00104.1}, abstractNote={Abstract}, number={7}, journal={JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY}, publisher={American Meteorological Society}, author={Pan, Weinan and Boyles, R. P. and White, J. G. and Heitman, J. L.}, year={2012}, month={Jul}, pages={933–943} }
 @article{ewing_vepraskas_broome_white_2012, title={Differences in Wetland Soil Chemical Soil Properties after 15, 20, and 30 Years of Drainage and Agricultural Production}, volume={179-180}, ISSN={["1872-6259"]}, DOI={10.1016/j.geoderma.2012.02.018}, abstractNote={When wetland restoration occurs on land previously used for crop production, residual nutrients can cause undesirable plant communities to grow, and increased solubility of excess P may contribute to eutrophication of surface waters. This study assessed how agricultural production in a drained wetland during 15, 20, and 30 yr periods changed morphological and chemical soil properties as compared to natural wetland soils not used for agriculture. The drained wetland, Juniper Bay, is a Carolina bay located in southeastern North Carolina. Three relatively undisturbed Carolina bays with soil types similar to those in Juniper Bay were selected as reference wetlands to compare soil properties. Three general soil types were identified in all the Carolina bays based on thickness of the organic surface layer: 1) organic soils (Histosols), 2) soils with histic epipedons, and 3) mineral soils. The surface horizon of all three soil types at Juniper Bay where crop production had occurred had significantly greater amounts of extractable P, Ca, Mg, Mn, Zn and Cu, along with higher base saturation and pH than soils in the reference bays. Greater length of time in crop production resulted in significant differences in soil chemical properties with depth. For soils farmed for 15 years, significant increases in extractable nutrients occurred only in the topsoil within approximately 20 cm of the soil surface. After 30 years of crop production, significantly increased amounts of extractable nutrients were present to depths of approximately 1 m. Residual nutrients and the higher pH of previously farmed wetland soils are likely to affect restoration of natural plant communities, which consist of plant species adapted to nutrient poor acid soils. Increased solubility of residual P when wetland hydrology and anaerobic soil conditions are restored may degrade water quality. These factors should be considered in planning wetland restoration projects.}, journal={Geoderma}, publisher={Elsevier BV}, author={Ewing, J. and Vepraskas, M.J. and Broome, S.W. and White, J.G.}, year={2012}, pages={73–80} }
 @article{meijer_heitman_white_austin_2012, title={Measuring erosion in long-term tillage plots using ground-based lidar}, volume={126}, ISSN={0167-1987}, url={http://dx.doi.org/10.1016/j.still.2012.07.002}, DOI={10.1016/j.still.2012.07.002}, abstractNote={Erosion remains a serious problem for agricultural soils throughout the world. Tillage significantly affects a soil's susceptibility to erosion. Erosion research is usually conducted in situ by capturing eroded sediment in brief, natural or artificial rainfall events. Methods for measuring long-term erosion are needed to better understand long-term effects of soil management. Landscape change resulting from erosion may be accurately characterized using ground-based lidar. Ground-based lidar data were collected in 2010 at a long-term (28-yr) trial of nine tillage treatments in the North Carolina Piedmont. Tillage effects on plot-surface elevations were examined after removing large-scale variation in elevation (slope) by detrending with first- through fourth-order polynomials. Residuals represented the elevation difference from the trend for each location. Mean plot elevations were calculated for datasets from each detrending model and used to assess erosion. In the subsequent elevation analysis, data derived from the second-order polynomial had the highest R2, attributing 66% of the variation in elevation to block and treatment. Treatment elevations relative to no-till (NT) ranged from +3.20 cm in the fall chisel (CHfa) plots to −13.28 cm in the fall moldboard plow plus disk treatment. Weeds in lesser-tilled treatments such as CHfa and no-till plus in-row subsoiling resulted in artificially high elevation measurements. In general, the most intensely-tilled treatments had the lowest elevations and the least-tilled treatments had the highest. NT was used as the reference elevation for no change, and soil loss was calculated using these data along with field-collected estimates of bulk density. The relative elevation differences corresponded to a maximum soil loss of 1891 Mg ha−1, which corresponds to an average annual soil loss of 67.5 Mg ha−1 yr−1. Soil loss estimates were similar to others estimated from soil profile truncation. This research indicates that ground-based lidar data can be used to estimate soil elevation changes and thus soil loss due to tillage-induced erosion.}, journal={Soil and Tillage Research}, publisher={Elsevier BV}, author={Meijer, A.D. and Heitman, J.L. and White, J.G. and Austin, R.E.}, year={2012}, pages={1–10} }
 @article{wall_weisz_crozier_heiniger_white_2010, title={Variability of the Illinois Soil Nitrogen Test across Time and Sampling Depth}, volume={74}, ISSN={["1435-0661"]}, DOI={10.2136/sssaj2009.0253}, abstractNote={There is potential for using the Illinois soil nitrogen test (ISNT) to improve N fertilizer recommendations for crops in the southeastern United States. The ISNT has been previously calibrated to predict N rates for corn (Zea mays L.) in North Carolina. This study evaluated the effects of sampling time, sampling depth, crop rotation, and fertilizer application on soil ISNT‐N during a 2‐yr period in the humid Coastal Plain and Piedmont regions of North Carolina. Ten sites were repeatedly sampled at 0‐ to 10‐, 10‐ to 20‐, and 20‐ to 30‐cm depths in fall, mid‐winter, and spring between October 2006 and May 2007. Illinois soil nitrogen test N, KCl‐extractable soil NO3–N and NH4–N, and soil organic matter (SOM) derived by loss‐on‐ignition (LOI) were evaluated at each sampling. Temporal changes in these soil parameters were evaluated for various crop rotations and N fertilizer applications. Soil ISNT‐N decreased with depth and showed significant variation with time at all three depths at all sites. Soil ISNT‐N was influenced by crop rotation and tillage but was not significantly affected by N fertilizer applications. Considering all sites together, ISNT‐N was well correlated with LOI; however, ISNT‐N was not correlated with LOI across time within sites. This suggests that the ISNT measured a fraction of SOM that behaved somewhat independently with time.}, number={6}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={Wall, David P. and Weisz, Randy and Crozier, Carl R. and Heiniger, Ronnie W. and White, Jeffrey G.}, year={2010}, pages={2089–2100} }
 @article{sripada_farrer_weisz_heiniger_white_2007, title={Aerial color infrared photography to optimize in-season nitrogen fertilizer recommendations in winter wheat}, volume={99}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2006.0258}, abstractNote={Remote sensing in the form of aerial color infrared (CIR) photography has been shown to be a useful tool for in‐season N management in winter wheat (Triticum aestivum L.). The objectives of this study were (i) to develop a methodology for predicting in‐season optimum fertilizer N rates for winter wheat at growth stage (GS) 30 directly from aerial CIR photography and (ii) to quantify how the relationships between these optimum N rates and spectral indices respond to different levels of biomass of the wheat crop. Field studies were conducted for three winter wheat growing seasons (2002–2004) over a wide range of soil conditions across North Carolina using a split‐split plot randomized complete block design. Different planting date–seeding rate (PDSR) combinations were applied to create a range of biomass levels at GS 30. Different levels of N were applied at GS 25 (N25) to create a range of N supply and winter wheat radiance, and at GS 30 (N30) to measure grain yield response to N30. Aerial CIR photographs were obtained at each site at GS 30 before N applications. Significant biomass response to PDSR and yield response to N25 and N30 were observed. Optimum N30 ranged from 0 to 124 kg ha−1 with a mean of 55 kg ha−1. Better prediction of optimum N30 rates were obtained with spectral indices calculated relative to high‐N reference strips compared to absolute bands or spectral indices. Biomass measured at GS 30 influenced the strength of the relationship between optimum N30 and spectral indices. When the GS‐30 biomass was >1000 kg ha−1, the best predictor of optimum N30 (R2 = 0.85) was a quadratic model based on measured winter wheat radiance relative to mean radiance in the G band for the high N reference strip (Rel GS).}, number={6}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Sripada, Ravi P. and Farrer, Dianne C. and Weisz, Randy and Heiniger, Ronnie W. and White, Jeffrey G.}, year={2007}, pages={1424–1435} }
 @article{williams_crozier_white_sripada_crouse_2007, title={Comparison of soil nitrogen tests for corn fertilizer recommendations in the humid southeastern USA}, volume={71}, ISSN={["0361-5995"]}, DOI={10.2136/sssaj2006.0057}, abstractNote={Environmental concerns about increasing NO3 levels in watersheds in North Carolina and elsewhere indicate the need for better N fertilizer management. Nitrate levels might be reduced if N rates could be adjusted based on field‐ or site‐specific knowledge of corn (Zea mays L.) response to N fertilization. Currently, there is no effective soil N test for the humid southeastern USA. This study was conducted to compare three soil N tests for practicality, precision, and ability to correlate with economic optimum N rate (EONR) and fertilizer response on southeastern U.S. soils. The soil N tests were the Illinois soil N test (ISNT), the gas pressure test (GPT), and the incubation and residual N test (IRNT). Soil samples were collected from the sites of 16 N‐response trials from 2001 to 2003 where different mineralizable and residual N levels were expected. The ISNT was determined to be the most practical test because it was the easiest to perform and could be completed in 1 d. The ISNT and GPT had better precision (lower CV) than the IRNT (9 and 13 vs. 61%, respectively). All three tests were related to EONR; ISNT had the strongest linear relationship (r2 = 0.90) when consideration was restricted to sites on mineral soils. The ISNT and GPT were related to delta yield (maximum yield minus check yield; r2 = 0.49 and 0.60, respectively) and fertilizer response (r2 = 0.31 and 0.51, respectively). These results indicate the potential of the ISNT and GPT to account for mineralizable and residual soil N levels and thus improve current corn N recommendations in the humid southeastern USA.}, number={1}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={Williams, Jared D. and Crozier, Carl R. and White, Jeffrey G. and Sripada, Ravi P. and Crouse, David A.}, year={2007}, pages={171–180} }
 @article{hong_white_weisz_gumpertz_duffera_cassel_2007, title={Groundwater nitrate spatial and temporal patterns and correlations: Influence of natural controls and nitrogen management}, volume={6}, ISSN={["1539-1663"]}, DOI={10.2136/vzj2006.0065}, abstractNote={To use shallow groundwater NO3–N concentration as an indicator of groundwater quality requires understanding its patterns, correlations, and controls across space and time. Within a study comparing variable‐rate and uniform N management, our objectives were to determine groundwater NO3–N patterns and correlations at various spatial and temporal scales and their association with natural controls and N management. Experiments in a random, complete block design were conducted in a 2‐yr crop rotation in North Carolina that included one variable‐rate and two uniform N management treatments to wheat (Triticum aestivumL.) and corn (Zea maysL.). We measured groundwater NO3–N and depth every 2 wk at 60 well nests, sampling the 0.9‐ to 3.7‐m depth. Field‐mean NO3–N varied with time from 5.5 to 15.3 mg NO3–N L−1These variations were correlated primarily with concurrent changes in water table elevation and depth. Mean NO3–N exhibited two preferred states: high when the water table was shallow and low when the water table was deep. Temporal NO3–N fluctuations greatly exceeded treatment effects. Treatments appeared to affect NO3–N temporal covariance structure. Groundwater NO3–N spatial patterns and correlations were associated mostly with saturated hydraulic conductivity and water table fluctuations and appeared influenced by subsurface lateral flow. When treatment effects became consistently significant later in the study, they overrode natural controls, and NO3–N was spatially uncorrelated or exhibited shorter spatial correlation ranges and patterns associated predominantly with treatments.}, number={1}, journal={VADOSE ZONE JOURNAL}, publisher={Soil Science Society of America}, author={Hong, Nan and White, Jeffrey G. and Weisz, Randy and Gumpertz, Marcia L. and Duffera, Miressa G. and Cassel, D. Keith}, year={2007}, month={Feb}, pages={53–66} }
 @article{williams_crozier_white_heiniger_sripada_crouse_2007, title={Illinois soil nitrogen test predicts southeastern US corn economic optimum nitrogen rates}, volume={71}, ISSN={["0361-5995"]}, DOI={10.2136/sssaj2006.0135}, abstractNote={An accurate and quick soil N test is needed for N fertilizer recommendations for corn (Zea mays L.) for the humid southeastern USA. The Illinois soil N test (ISNT) has been used to distinguish fertilizer-responsive from unresponsive sites in Illinois. We determined relationships between economic optimum N rates (EONR) and ISNT levels in representative southeastern soils in 35 N-response trials in the Piedmont (n = 4) and Middle (n = 8) and Lower (n = 23) Coastal Plains of North Carolina from 2001 to 2004. The ISNT was strongly correlated with EONR for well or poorly drained sites (r 2 = 0.87 [n = 20] and 0.78 [n = 10], respectively); data were insuffi cient for establishing correlations for very poorly drained or severely drought-stressed sites. Expressing ISNT on a mass per unit volume basis vs. EONR improved the correlations slightly (r 2 = 0.88 and 0.79 for well and poorly drained sites, respectively), but these improvements would not justify the necessary soil bulk density determinations. Regressions of ISNT vs. minimum, average, and maximum EONR based on different N-fertilizer cost /corn price ratios (11.4:1, 7.6:1, and 5:1, respectively) showed strong correlations with EONR for well-drained sites (r 2 = 0.77, 0.87, and 0.87, respectively) and poorly drained sites (r 2 = 0.84, 0.78, 0.70, respectively). The ISNT–EONR correlations were different among the cost/price ratios for well-drained sites, but not different for poorly drained sites. Because ISNT predicted EONR robustly to different cost/price ratios, ISNT has the potential to modify or replace current N recommendation methods for corn. Abbreviations: EONR, economic optimum nitrogen rate; HM, humic matter; ISNT, Illinois soil nitrogen test; RYE, realistic yield expectation.}, number={3}, journal={SOIL SCIENCE SOCIETY OF AMERICA JOURNAL}, publisher={Soil Science Society of America}, author={Williams, Jared D. and Crozier, Carl R. and White, Jeffrey G. and Heiniger, Ronnie W. and Sripada, Ravi P. and Crouse, David A.}, year={2007}, pages={735–744} }
 @article{weisz_sripada_heiniger_white_farrer_2007, title={In-season tissue testing to optimize soft red winter wheat nitrogen fertilizer rates: Influence of wheat biomass}, volume={99}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2006.0112}, abstractNote={In the southeastern USA, soft red winter wheat (Triticum aestivum L.) N fertilizer recommendations are based on growth stage (GS) 30 tissue testing and models that assume that the relationship between tissue N concentration (Ncon) and optimum N fertilizer rates (MaxN30) is stable across fields differing in GS‐30 biomass. However, previous research has indicated this may not be the case. Consequently, it was critical to re‐evaluate these models. Using a split‐split plot design, six experiments were conducted in North Carolina between 2002 and 2004. Main plots were planting date–seeding rate combinations that produced wheat with different GS‐30 biomass. Subplots and sub‐subplots were five N rates applied at GS‐25 and GS‐30, respectively. Wheat yield was responsive to fertilizer N at all site‐years. The overall relationship between MaxN30 and Ncon was weak (r2 = 0.43). The relationship between MaxN30 and N uptake (Ncon × biomass) was weaker (r2 = 0.27). However, when the data were divided into different biomass classes, the overall model improved (R2 = 0.75). For biomass < 340 kg ha−1, the Ncon at which no additional N fertilizer was required (Ncritical) was 70.0 g N kg−1. As biomass increased, Ncritical decreased to 33.2 g N kg−1. Intermediate classes had slopes of MaxN30 versus Ncon and Ncritical values that were similar to those previously reported. This study indicates that to use tissue testing to determine N fertilizer recommendations across a range of GS‐30 biomass conditions requires information regarding dry matter biomass.}, number={2}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Weisz, Randy and Sripada, Ravi P. and Heiniger, Ronnie W. and White, Jeffrey G. and Farrer, Dianne C.}, year={2007}, pages={511–520} }
 @article{duffera_white_weisz_2007, title={Spatial variability of Southeastern US Coastal Plain soil physical properties: Implications for site-specific management}, volume={137}, ISSN={["1872-6259"]}, DOI={10.1016/j.geoderma.2006.08.018}, abstractNote={Our objectives were to describe the field-scale horizontal and vertical spatial variability of soil physical properties and their relations to soil map units in typical southeastern USA coastal plain soils, and to identify the soil properties, or clusters of properties, that defined most of the variability within the field. The study was conducted on a 12-ha field in Kinston, NC. A 1:2400 scale soil survey had delineated three soil map units in the field: Norfolk loamy sand, Goldsboro loamy sand, and Lynchburg sandy loam. These are representative of millions of hectares of farmland in the Coastal Plain of the southeastern USA. Sixty soil cores were taken to ∼ 1-m depth, sectioned into five depth increments, and analyzed for: soil texture as percentage sand, silt, and clay; soil water content (SWC) at − 33 and − 1500 kPa; plant available water (PAW); saturated hydraulic conductivity (Ksat); bulk density (BD); and total porosity. A penetrometer was used to measure cone index (CI) at each sample location. Variography, two mixed-model analyses, and principal components analysis were conducted. Results indicated that soil physical properties could be divided into two categories. The first category described the majority of the within-field variability and included particle size distribution (soil texture), SWC, PAW, and CI. These characteristics showed horizontal spatial structure that was captured by soil map units and especially by the division between sandy loams and finer loam soils. The second class of variables included BD, total porosity, and Ksat. These properties were not spatially correlated in the field and were unrelated to soil map unit. These findings support the hypothesis that coastal plain soil map units that delineate boundaries between sandy loams versus finer loam soils may be useful for developing management zones for site-specific crop management.}, number={3-4}, journal={GEODERMA}, publisher={Elsevier BV}, author={Duffera, Miressa and White, Jeffrey G. and Weisz, Randy}, year={2007}, month={Jan}, pages={327–339} }
 @article{sripada_heiniger_white_meijer_2006, title={Aerial color infrared photography for determining early in-season nitrogen requirements in corn}, volume={98}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2005.0200}, abstractNote={In‐season determination of corn (Zea mays L.) N requirements via remote sensing may help optimize N application decisions and improve profit, fertilizer use efficiency, and environmental quality. The objective of this study was to use aerial color‐infrared (CIR) photography as a remote‐sensing technique for predicting in‐season N requirements for corn at the V7 growth stage. Field studies were conducted for 2 yr at three locations, each with and without irrigation, in the North Carolina Coastal Plain. Experimental treatments were a complete factorial of four N rates at planting (NPL) and five N rates at V7 (NV7). Aerial CIR photographs were taken at each of the locations at V7 before N application. Optimum NV7 ranged from 0 to 207 kg N ha−1 with a mean of 67 kg N ha−1. Significant but weak correlations were observed between optimum NV7 rates and the band combinations relative green, Relative Green Difference Vegetation Index, and Relative Difference Vegetation Index as measured in CIR photos. High proportions of soil reflectance in the images early in the corn growing season (V7) likely confounded our attempts to relate spectral information to optimum NV7 rates. The primary obstacles to applying this technique early in the season are the use of relative digital counts or indices that require high‐N reference strips in the field and strong background reflectance from the soil. When the NPL treatments that were nonresponsive to NV7 (i.e., optimum NV7 = 0) were removed from the analysis, the normalized near infrared, the Green Difference Vegetation Index, the Green Ratio Vegetation Index, and the Green Normalized Difference Vegetation Index were the best predictors of optimum NV7 rate (r2 = 0.33).}, number={4}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Sripada, Ravi P. and Heiniger, Ronnie W. and White, Jeffrey G. and Meijer, Alan D.}, year={2006}, pages={968–977} }
 @article{szuch_white_vepraskas_doolittle_2006, title={Application of ground penetrating radar to aid restoration planning for a drained Carolina Bay}, volume={26}, ISSN={["1943-6246"]}, DOI={10.1672/0277-5212(2006)26[205:aogprt]2.0.co;2}, abstractNote={Clayey subsurface strata in precipitation-driven wetlands act as aquitards that retain water and can affect wetland hydrology. If the aquitard layers have been cut through by drainage ditches, then restoring wetland hydrology to such sites may be more difficult because of the need to fill ditches completely with low hydraulic conductivity material. Ground penetrating radar (GPR) surveys were conducted to determine the depth and continuity of shallow clay layers and identify those that have been pierced by drainage ditches at Juniper Bay, a 300-ha drained Carolina bay in North Carolina, USA that will be restored. Carolina bays are a wetland type that occur as numerous, shallow, oval-shaped depressions along the Atlantic Coastal Plain. The GPR interpretations found that moderately fine-textured (clay loam, sandy clay loam, silty clay loam) and fine-textured (sandy clay, silty clay, clay) aquitards underlay coarser-textured horizons in most of the bay at an average depth of 1.6 m. Extensive ground truthing showed that, on average, GPR predicted the depth to these aquitards to within 16% of their actual depth. An atypical GPR reflection in the southeast sector of the bay was interpreted as a fluvial deposit without aquitards until a depth of 3 to 5 m. This area may require different restoration strategies than the rest of the bay. By comparing the depths of aquitards and drainage ditches, several areas were identified as likely locations of ditch-induced aquitard discontinuity that may require filling or lining of suspect ditches to prevent potential water losses if there are downward hydraulic gradients. Cost estimates by two professional firms indicated that GPR could provide large volumes of data with cost and time efficiency. GPR surveys are proposed as a useful tool for characterizing potential wetland restoration sites on the Atlantic Coastal Plain and other regions with similar soils.}, number={1}, journal={WETLANDS}, author={Szuch, RP and White, JG and Vepraskas, MJ and Doolittle, JA}, year={2006}, month={Mar}, pages={205–216} }
 @article{sripada_heiniger_white_crozier_meijer_2006, title={Attempt to validate a remote sensing-based late-season corn nitrogen requirement prediction system}, ISBN={1543-7833}, journal={Crop Management}, author={Sripada, R. P. and Heiniger, R. W. and White, J. G. and Crozier, C. R. and Meijer, A. D.}, year={2006}, pages={1} }
 @article{szuch_white_vepraskas_doolittle_2006, title={Finding the soil surface in ground-penetrating radar profiles: The lift test}, volume={47}, DOI={10.2136/sh2006.1.0010}, abstractNote={Ground-penetrating radar (GPR) can be used to determine the depth to a subsurface layer if the user can identify where the ground surface is on the GPR trace. This study demonstrates a simple field procedure for unequivocally determining the ground surface in a GPR trace. A “lift test” was performed simply by raising the transceiving antenna unit off the ground and setting it back down while the GPR unit was recording. This procedure produced a distinct wave pattern on the GPR profile that clearly showed the soil surface. The lift test improved accuracy of depth estimates by approximately 10% in a GPR study to determine depths to moderately fine and fine textured horizons at a drained Carolina bay wetland restoration site. Though easy to perform, this procedure has apparently not been used in many GPR studies. The lift test provides an efficient means of determining the soil surface in GPR surveys, a necessity if accurate depth measurements are to be made.}, number={1}, journal={Soil Survey Horizons}, publisher={Soil Science Society of America}, author={Szuch, R.P. and White, J.G. and Vepraskas, M.J. and Doolittle, J.A.}, year={2006}, pages={10–12} }
 @article{farrer_weisz_heiniger_murphy_white_2006, title={Minimizing protein variability in soft red winter wheat: Impact of nitrogen application timing and rate}, volume={98}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2006.0039}, abstractNote={Grain protein content in soft red winter wheat (Triticum aestivum L.) is highly variable across years and environments in the southeastern USA. This variability makes southeastern wheat undesirable to millers and negatively impacts its value in the export market. The objectives of this study were to determine how different N fertilizer rates and application times would affect grain protein variability and to determine if there were N fertilizer recommendations that would minimize regional protein variation. We conducted experiments in the North Carolina Piedmont, Coastal Plain, and Tidewater in 2001 and 2002. At each site–year, we used a split‐plot design with three or five N fertilizer rates at growth‐stage 25 (GS) (main plots), and an additional five N fertilizer rates applied at GS 30 (subplots). Analysis of variance indicated that environment contributed 68 and 90.5% of the variability in yield and test weight, respectively. Though environment contributed 23.3% of grain protein variability, the majority (51.4%) was attributed to timing and rate of N application. As grain protein levels increased at higher N rates, so did overall protein variability. Additionally, applying the majority of N fertilizer at GS 30 increased grain protein variability compared to application at GS 25. Based on these results, our recommendations to reduce grain protein variability in the southeastern USA are to: (i) reduce the range in N fertilizer rates used across the region, (ii) avoid overapplication of N beyond what is required to optimize yield and economic return, and (iii) apply spring N at GS 25.}, number={4}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Farrer, Dianne C. and Weisz, Randy and Heiniger, Ronnie and Murphy, J. Paul and White, Jeffrey G.}, year={2006}, pages={1137–1145} }
 @article{hong_white_weisz_crozier_gumpertz_cassel_2006, title={Remote Sensing-Informed Variable-Rate Nitrogen Management of Wheat and Corn}, volume={98}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2005.0154}, abstractNote={In‐season, site‐specific, variable‐rate (SS) N management based on remote sensing (RS) may reduce N losses to groundwater while maintaining or increasing yield and N fertilizer‐use efficiency. We compared in‐season, RS‐informed N management applied on a uniform, field‐average (FA) or SS basis with the current uniform best management practice (BMP) based on “Realistic Yield Expectations” (RYE) in a typical 2‐yr southeastern U.S. coastal plain rotation: winter wheat (Triticum aestivum L.)–double‐crop soybean [Glycine max (L.) Merr.]–corn (Zea mays L.). Compared with the RYE‐based BMP, RS‐informed SS management achieved: (i) a maximum of 2.3 mg L−1 less groundwater NO3–N after 2001 wheat due to 39 kg ha−1 less fertilizer N and a 25% greater harvest N ratio (N in grain or forage/total N applied); (ii) 370 kg ha−1 more 2002 corn grain with 32 kg ha−1 greater N applied, similar harvest N ratio, and 37 kg ha−1 greater surplus N; (iii) 670 kg ha−1 more 2003 wheat grain associated with 14 kg ha−1 greater fertilizer N, 27% greater harvest N ratio, and 9 kg ha−1 less surplus N. Excepting one corn FA treatment that received excessive N, RS‐informed management produced equal or greater economic returns to N than RYE, and less surplus N for wheat. Treatments produced enduring effects on groundwater [NO3–N] consistent with agronomic results, but small relative to temporal [NO3–N] fluctuations that were positively correlated with water table elevation. To assess N management in leaching‐prone soils, frequent, periodic groundwater monitoring during and after the cropping season appears essential.}, number={2}, journal={Agronomy Journal}, publisher={American Society of Agronomy}, author={Hong, N. and White, J.G. and Weisz, R. and Crozier, C.R. and Gumpertz, M.L. and Cassel, D.K.}, year={2006}, pages={327–338} }
 @article{sripada_heiniger_white_weisz_2005, title={Aerial color infrared photography for determining late-season nitrogen requirements in corn}, volume={97}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2004.0314}, abstractNote={Fast and accurate methods of determining in‐season corn (Zea mays L.) N requirements are needed to provide more precise and economical management and potentially decrease groundwater N contamination. The objectives of this study were (i) to determine if there is a response to late‐season N applied to corn at pretassel (VT) under irrigated and nonirrigated conditions, and (ii) to develop a methodology for predicting in‐season N requirement for corn at the VT stage using aerial color infrared (CIR) photography. Field studies were conducted for 3 yr over a wide range of soil conditions and water regimes in the North Carolina Coastal Plain. Different fertilizer N rates were applied (i) at planting (NPL) to create a range of N supply, corn color, and near‐infrared (NIR) radiance; and (ii) at VT (NVT) to measure yield response to NVT. Aerial CIR photographs were obtained for each site at VT before N application. Significant grain yield responses to NPL and NVT were observed. Economic optimum NVT rates ranged from 0 to 224 kg ha−1 with a mean of 104 kg ha−1. Better prediction of economic optimum NVT rates was obtained with spectral band combinations rather than individual bands, and improved when calculated relative to high‐N reference strips measured at VT. The best predictor of economic optimum NVT (R
2 = 0.67) was a linear‐plateau model based on corn color and NIR radiance expressed using the Green Difference Vegetation Index (GDVI) relative to high‐N reference strips (Relative GDVI, RGDVI).}, number={5}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Sripada, RP and Heiniger, RW and White, JG and Weisz, R}, year={2005}, pages={1443–1451} }
 @article{hong_white_gumpertz_weisz_2005, title={Spatial analysis of precision agriculture treatments in randomized complete blocks: Guidelines for covariance model selection}, volume={97}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2004.0130}, abstractNote={Failure to account for spatially correlated errors when present in the classical randomized complete block (RCB) analysis may cause inefficient estimation of treatment significance. Covariance model selection is a necessary component for spatial adjustment to estimate treatment significance. We discuss methods for selecting a covariance model in RCB analyses in the presence of spatial correlation and demonstrate one procedure in detail. The procedure uses three models: the randomized complete block with independent and identically distributed errors (RCBiid), RCB with correlated errors, and models with correlated errors but no block effects. The semivariogram of the residuals from fitting a model with just fixed effects, the likelihood ratio test, and Akaike Information Criterion are used for model selection. To illustrate the procedure, we analyzed winter wheat (Triticum aestivum L.) forage and corn (Zea mays L.) grain yield in the presence of spatial heterogeneity within blocks from a site‐specific N management study. We compared the selected covariance models to the RCBiid models and to other spatial models with respect to the estimation of treatment significance. The procedure can be extended to any experiment with fixed effects, or with both fixed and random effects, and which may potentially have spatially correlated errors. The procedure is systematic and readily implemented; however, it remains difficult to evaluate whether an adequate covariance model has been selected.}, number={4}, journal={AGRONOMY JOURNAL}, publisher={American Society of Agronomy}, author={Hong, N and White, JG and Gumpertz, ML and Weisz, R}, year={2005}, pages={1082–1096} }
 @inproceedings{williams_crozier_crouse_white_bang_duffera_2005, place={Oxford, UK}, title={Spatial relationships between soil amino sugar nitrogen, soil properties, and landscape attributes}, booktitle={Proc. Eur. Conf. Precision Agric., 5th, Uppsala, Sweden}, publisher={BIOS Scientific Publishers}, author={Williams, J.D. and Crozier, C.R. and Crouse, D.A. and White, J.G. and Bang, J. and Duffera, M.}, editor={Stafford, J.V.Editor}, year={2005}, month={Jun} }
 @article{flowers_weisz_white_2005, title={Yield-based management zones and grid sampling strategies: describing soil test and nutrient variability}, volume={97}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2004.0224}, abstractNote={Alternatives such as yield‐based management zones may solve problems associated with grid soil sampling while effectively describing soil test and nutrient variability. The main objective was to delineate yield‐based management zones using multiyear yield data and compare them with whole‐field average and grid soil‐sampling methods to determine the most effective strategy for describing soil test and nutrient variability. Research was conducted in four continuous no‐till fields that had varied cropping histories and yield monitor data for at least 3 yr from 1996 through 2000. Four yield‐based management zone methods, (i) mean normalized yield map (MNY), (ii) coefficient of variation map (CVM), (iii) MNY × CVM, and (iv) yield region map (YRM), were evaluated. Three grid soil‐sampling strategies, (i) grid cell, (ii) grid center, and (iii) grid center with kriging at two sampling distances (68 and 98 m), were also tested. Grid cell sampling consistently captured more soil test and nutrient variability than the grid center and grid center with kriging methods. Of the yield‐based management zone strategies, YRM was the most effective and in all four fields explained more soil test and nutrient variability compared with the whole‐field average approach. Yield region map also performed better than or similar to the 98‐m grid center and 98‐m grid center with kriging strategies. When the field had low soil test values, YRM was also nearly as effective in capturing nutrient recommendation variability as the 98‐m grid cell method. However, compared with all other strategies, the 68‐m grid cell method was the most effective way to describe soil test and nutrient variability.}, number={3}, journal={Agronomy Journal}, publisher={American Society of Agronomy}, author={Flowers, M. and Weisz, R. and White, J.G.}, year={2005}, pages={968–982} }
 @inproceedings{hong_white_gumpertz_weisz_2004, place={Madison, WI}, title={Covariance model selection in spatial analysis of yield-monitor data in randomized complete blocks}, booktitle={Proc. Int. Conf. Precision Agric. and other Precision Natural Resource Management, 7th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Hong, N. and White, J.G. and Gumpertz, M.L. and Weisz, R.}, editor={Mulla, D.J. and Swenson, J.A.Editors}, year={2004}, month={Jul} }
 @inproceedings{sripada_heiniger_white_crozier_2004, place={Madison, WI}, title={Remote sensing based early and late in-season N management decisions in corn}, booktitle={Proc. Int. Conf. Precision Agric. and other Precision Natural Resource Management, 7th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Sripada, R.P. and Heiniger, R.W. and White, J.G. and Crozier, C.R.}, editor={Mulla, D.J. and Swenson, J.A.Editors}, year={2004}, month={Jul} }
 @inproceedings{crozier_white_weisz_heiniger_crouse_garoma_farrer_sripada_hong_williams_2004, place={Madison, WI}, title={Remote sensing for precision N management in a corn-wheat-soybean rotation}, booktitle={Proc. Int. Conf. Precision Agric. and other Precision Natural Resource Management, 7th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Crozier, C.R. and White, J.G. and Weisz, R. and Heiniger, R. and Crouse, D.A. and Garoma, M. and Farrer, D. and Sripada, R.P. and Hong, N. and Williams, J.}, editor={Mulla, D.J. and Swenson, J.A.Editors}, year={2004} }
 @inproceedings{hong_white_gumpertz_weisz_2004, place={Madison, WI}, title={Temporal pattern and spatial complexity of shallow groundwater nitrate in a coastal plain agricultural field}, booktitle={Proc. Int. Conf. Precision Agric. and other Precision Natural Resource Management, 7th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Hong, N. and White, J.G. and Gumpertz, M.L. and Weisz, R.}, editor={Mulla, D.J. and Swenson, J.A.Editors}, year={2004}, month={Jul} }
 @article{weisz_heiniger_white_knox_reed_2003, title={Long-term variable rate lime and phosphorus application for Piedmont no-till field crops}, volume={4}, ISBN={1385-2256}, DOI={10.1023/a:1024908724491}, number={3}, journal={Precision Agriculture}, author={Weisz, R. and Heiniger, R. and White, Jeffrey and Knox, B. and Reed, L.}, year={2003}, pages={311} }
 @inproceedings{sripada_heiniger_white_burleson_crozier_weisz, place={Madison, WI}, title={Aerial color infrared photography for determining in-season nitrogen requirements for corn}, booktitle={Proc. Int. Conf. on Precision Agric. and other Precision Natural Resource Management, 6th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Sripada, R.P. and Heiniger, R.W. and White, J.G. and Burleson, J.M. and Crozier, C.R. and Weisz, R.}, editor={Robert, P.C.Editor} }
 @inproceedings{li_white_crozier_r.weisz_crouse, place={Madison, WI}, title={Spatial associations of soil chemical properties with soil map units in a coastal plain field}, booktitle={Proc. Int. Conf. on Precision Agric. and other Precision Natural Resource Management, 6th, Bloomington, MN}, publisher={ASA/SSSA/CSSA}, author={Li, H. and White, J.G. and Crozier, C.R. and R.Weisz, R.Heiniger and Crouse, D.A.}, editor={Robert, P.C.Editor}, pages={14} }
 @article{crouse_havlin_mcbride_white_heiniger_weisz_roberson_2000, title={Precision farming education at NC State University}, journal={Proceedings of the 5th International conference on precision agriculture, Bloomington, Minnesota, USA, 16-19 July, 2000}, publisher={Madison, WI : Precision Agriculture Center, University of Minnesota, ASA-CSSA-SSSA}, author={Crouse, D. A. and Havlin, J. L. and McBride, R. G. and White, J. G. and Heiniger, R. and Weisz, R. and Roberson, G.}, year={2000}, pages={1} }
 @article{white_zasoski_1999, title={Mapping soil micronutrients}, volume={60}, DOI={10.1016/s0378-4290(98)00130-0}, abstractNote={Soils vary widely in their micronutrient content and in their ability to supply micronutrients in quantities sufficient for optimal crop growth. Soils deficient in their ability to supply micronutrients to crops are alarmingly widespread across the globe, and this problem is aggravated by the fact that many modern cultivars of major crops are highly sensitive to low micronutrient levels. Original geologic substrate and subsequent geochemical and pedogenic regimes determine total levels of micronutrients in soils. Total levels are rarely indicative of plant availability, however, because availability depends on soil pH, organic matter content, adsorptive surfaces, and other physical, chemical, and biological conditions in the rhizosphere. Micronutrient availability to plants can be measured in direct uptake experiments, or estimated with techniques that correlate quantities of micronutrients extracted chemically from soils to plant uptake and response to micronutrient fertilization. Rational management of micronutrient fertility and toxicity requires an understanding of how total and plant-available soil micronutrients vary across the land. A variety of approaches have been used to survey and map the geographic distribution of soil micronutrient content and availability at scales ranging from global to sites within single production fields. Soil micronutrient maps covering large areas improve our understanding of the nature and extent of micronutrient problems, and aid in determining their relationships with climate, soil properties, and soil genetic characteristics determined at similar scales, for example, Soil Taxonomy to the order, sub-order, or great group levels. Intermediate scale maps can be useful in delineating specific areas where deficiencies or toxicities are likely for agriculture, and in determining localized soil characteristics that may be associated with such problems. Highly detailed maps of soil micronutrient content and availability in individual fields are being developed for site-specific precision agriculture. Soil micronutrient maps have fostered discovery of relationships between soil micronutrient content and availability and some human and livestock health problems such as goiter, Keshan and Kaschin–Beck diseases, and cancer. Advances including the global positioning system (GPS), geographic information systems (GIS), inductively coupled plasma (ICP) spectrometry, geostatistics, and precision agriculture facilitate soil micronutrient mapping and provide quantitative support for decision and policy making to improve agricultural approaches to balanced micronutrient nutrition.}, note={invited}, number={1-2}, journal={Field Crops Research}, publisher={Elsevier BV}, author={White, J.G. and Zasoski, R.J.}, year={1999}, pages={11–26} }
 @article{white_welch_norvell_1997, title={Soil zinc map of the USA using geostatistics and geographic information systems}, volume={61}, DOI={10.2136/sssaj1997.03615995006100010027x}, abstractNote={Abstract}, number={1}, journal={Soil Science Society of America Journal}, publisher={Soil Science Society of America}, author={White, J.G. and Welch, R.M. and Norvell, W.A.}, year={1997}, pages={185–194} }
 @inproceedings{white_nkunzimana_mussche_1993, place={Cali, Columbia}, title={Transfert et test d'une méthode de lutte contre la mouche du haricot et les fontes de semis: résultats provisoires (Transfer and test of a method of combatting bean shoot fly and damping off: Provisional results)}, booktitle={La production du haricot au Burundi (Bean production in Burundi). Proc. Workshop of the Institut des Sciences Agronomiques du Burundi (ISABU)-International Center for Tropical Agriculture (CIAT), Bujumbura, Burundi}, publisher={ISABU-CIAT}, author={White, J.G. and Nkunzimana, S. and Mussche, G.}, editor={Godderis, W.Editor}, year={1993}, month={May} }
 @article{white_scott_1991, title={Effects of perennial forage legume living mulches on no-till winter wheat and rye}, volume={28}, DOI={10.1016/0378-4290(91)90079-b}, abstractNote={No-till winter cereals sown in narrow rows may compete successfully with perennial forage-legume living mulches that can fix nitrogen (N), conserve soil, increase dry-matter production, and suppress weeds. The effects of small-grain species, mulch species, and top-dress N on grain and mulch yield and the grain N concentration of winter cereals direct-drilled into legume living mulches were examined in a two-year field study in New York, U.S.A., on soils of the Lima and Kendaia series: fine-loamy, mixed, mesic Glossoboric and Aeric Hapludalfs. Wheat (Triticum aestivum L.) or rye (Secale cereale L.) were grown in monoculture or drilled into summer-established plots of alfalfa (Medicago sativa L.), birdsfoot trefoil (Lotus corniculatus L.), crownvetch (Coronilla varia L.), ladino clover (Trifolium repens L. forma lodigense Hort ex. Gams), red clover (T. pratense L.), or white clover (T. repens L.). Spring top-dress N was applied at 0 or 56 kg N ha−1. Cereals were reseeded for a second season. Mulches generally interfered more and yielded more with wheat than with rye. Birdsfoot trefoil, crownvetch, and white clover had little effect on grain-yield the first year; birdsfoot trefoil and crownvetch interfered strongly with cereals the second year. Red clover did not affect rye grain-yield in the absence of top-dress N, but did tend to reduce wheat yield. Top-dress N increased cereal grain-yield and decreased mulch yield. In general, legume mulches did not appear to enhance cereal N nutrition the first year; red and white clovers appeared to contribute N to rye the second year. Second-year grain-yields were generally lower than first-year yields, due to increased interference from living mulches and broadleaf weeds. All living mulches except crownvetch suppressed weeds the second year. The results indicate that some species of perennial forage legumes may be suitable for use as living mulches for direct-drilled small grains, especially tall early winter cereals.}, number={1-2}, journal={Field Crops Research}, publisher={Elsevier BV}, author={White, J.G. and Scott, T.W.}, year={1991}, pages={135–148} }
 @inproceedings{ntibashirwa_white, place={Bujumbura, Burundi}, title={Les Ateliers Régionaux de Recherche: Une démarche de recherche et de transfert adaptée à l'agriculture burundaise. (The Regional Research Workshops: A method of research and transfer adapted to Burundian agriculture)}, booktitle={Actes de la Séminaire sur l'Etude des Systèmes d'Exploitation Agricole au Burundi}, publisher={FACAGRO/University of Burundi-ISABU}, author={Ntibashirwa, S. and White, J.G.}, pages={280–284} }
 @article{kirtikar_cathcart_white_ukstins_goldthwait_1977, title={Mutations in Escherichia coli altering an apurinic endonuclease, endonuclease II, and exonuclease III, and their effect on in vivo sensitivity to methylmethanesulfonate}, volume={16}, DOI={10.1021/bi00644a037}, abstractNote={The levels of endonuclease II, an apurinic endonuclease, and exonuclease III in the parent strains (AB 1157) of Escherichia coli and in various mutants were determined by chromatography on DEAE-cellulose. AB 3027 and NH 5016 lacked endonuclease II and exonuclease III. BW 2001 lacked the apurinic endonuclease and exonuclease III while BW 2007, BW 9093, and BW 9059 lacked only exonuclease III. Deletion mutants BW 9101 and BW 9109 lacked all three enzymes. The latter mutants locate the genes for the two endonucleases in the region of exonuclease III (chith) of 38.2 min (White et al., 1976). All of the mutants which were sensitive to methylmethanesulfonate in vivo lacked exonuclease III, but not all mutants lacking exonuclease III were MMS sensitive. The deletion mutants and NH 5016 were the exceptions.}, number={25}, journal={Biochemistry}, publisher={American Chemical Society (ACS)}, author={Kirtikar, D.M. and Cathcart, G.R. and White, J.G. and Ukstins, I. and Goldthwait, D.A.}, year={1977}, pages={5625–5631} }