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Dive into the research topics where Kurt Steinke is active.

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Featured researches published by Kurt Steinke.


Weed Science | 2013

Nitrogen Release from Weed Residue

Laura E. Lindsey; Kurt Steinke; Darryl D. Warncke; Wesley J. Everman

Abstract Weed residues can impact nitrogen (N) cycling in agro-ecosystems that primarily utilize POST weed control. Quantifying this potential N source or sink may influence weed control and fertilization practices. A laboratory experiment measured the rate and quantity of N release from common lambsquarters, common ragweed, and giant foxtail. Weeds were grown in the field at four N rates (0, 67, 134, or 202 kg N ha−1) and collected at two weed heights (10 or 20 cm) to give a range of residue chemical composition. Residue chemical composition parameters of carbon ∶ N (C ∶ N) ratio and total N, nitrate-N, acid detergent fiber, and neutral detergent fiber concentration were measured and correlated with N release. Nitrogen release from weed residue mixed with soil was determined over a 12-wk period. Nitrogen was released from all weed residues at 12 wk. Prior to 12 wk, N was immobilized by giant foxtail grown with no N application. Prior to 4 wk, N was immobilized by 20-cm weeds grown with no N application. Nitrogen release from weed residue was negatively correlated with C ∶ N ratio. Weed residue with a C ∶ N ratio of < 19 (weeds grown with N application and 10-cm weeds) released 25 to 45% total N concentration within 2 wk and may contribute N within the growing season. Weed residue with a C ∶ N ratio > 19 (giant foxtail and 20-cm weeds grown with no N) initially immobilized N and may not contribute N within the growing season. Nomenclature: Common lambsquarters, Chenopodium album L. CHEAL; common ragweed Ambrosia artemisiifolia L. AMBEL; giant foxtail, Setaria faberi Herrm. SETFA; corn, Zea mays L.


Journal of Environmental Quality | 2013

Potential Contributions of Mature Prairie and Turfgrass to Phosphorus in Urban Runoff

Kurt Steinke; W. R. Kussow; J. C. Stier

Urban vegetative plantings are considered desirable to mitigate and filter stormwater runoff and nonpoint-source pollution. Phosphorus fertilization of turfgrass may enhance P in urban runoff; however, the amount of P from nonfertilized, native vegetation that could potentially replace some turf is not known. This study was conducted to measure the relative contributions of nonfertilized, native prairie vegetation and fertilized turfgrass to runoff water and P loads. Six replicates of side-by-side mature urban prairie and turfgrass were monitored for mean annual runoff volumes and P loads, biomass production, vegetative nutrient composition, and changes in soil moisture. Vegetation type did not significantly affect seasonal or annual runoff volumes or P loads. The mean annual total P loads of 0.46 kg ha for prairie and 0.28 kg ha for turfgrass were significant and comparable to those reported by other researchers when studied separately. Total P concentrations in runoff water from prairie and turf vegetation were above USEPA limits, averaging 1.86 and 1.63 mg L, respectively, over 2 yr. Averaged across 2 yr, 78% of runoff P was collected when the soil was frozen. Biomass P reductions over the period of November to April were strongly related to quantities of runoff total P from frozen soil ( = 0.874). Phosphorus losses from urban areas appeared to be primarily correlated with runoff depth, not vegetation type, because correlation coefficients revealed 86 and 45% of the Year 1 and Year 2 total P loads were directly accounted for by runoff volumes.


Weed Technology | 2014

Impact of Nitrogen and Weeds on Glyphosate-Resistant Sugarbeet Yield and Quality

Alicia J. Spangler; Christy L. Sprague; Kurt Steinke

Abstract Field experiments were conducted in 2010 and 2011 at two locations in Michigan to determine the effects of nitrogen and weed removal on glyphosate-resistant sugarbeet yield and quality. Nitrogen rates were 0, 67, 100, 134, and 67 : 67 kg N ha−1, and weeds were removed when they were < 2, 8, 15, and 30 cm tall. At the beginning of the growing season, weeds responded to N sooner than sugarbeet. Nitrogen assimilation by weeds was three times greater than sugarbeet at 0, 67, 100, and 134 kg N ha−1 and four times greater than sugarbeet with the split application of N (67 : 67 kg N ha−1) averaged over the weed removal timings. Higher N rates increased N sufficiency index values and sugarbeet canopy closure; weeds 30 cm tall had lower N sufficiency index values and a smaller sugarbeet canopy. The effect of N on root yields varied, but the highest N rates (134 kg N ha−1 or 67 : 67 kg N ha−1) were among the highest sugarbeet yields at all locations. Highest yields were achieved when weeds were controlled before reaching 2 cm tall at three of the four site-years. Delaying weed control until weeds were 8 or 15 cm tall reduced yield by 15%, whereas 30-cm-tall weeds reduced yield up to 21%. Recoverable white sucrose ha−1 (RWSH) also was reduced by 8 to 16% if weeds were 8 cm tall. These results indicate that weeds are highly competitive with sugarbeet and can assimilate large quantities of N early in the growing season, especially at larger growth stages. However, it appears that sugarbeets were able to scavenge sufficient N at the N rates used in this study to overcome N removal effects from larger weeds, resulting in no interaction between N rate and weed removal timing for sugarbeet root yield, quality, or RWSH. Nomenclature: Glyphosate; sugarbeet; Beta vulgaris L. ‘Hilleshög 9042’. Resumen En 2010 y 2011, se realizaron experimentos de campo en dos localidades en Michigan para determinar los efectos de aplicaciones de nitrógeno y la remoción de malezas en el rendimiento y la calidad de la remolacha azucarera resistente a glyphosate. Las dosis de nitrógeno fueron 0, 67, 100, 134, y 67:67 kg N ha−1, y las malezas fueron removidas cuando tuvieron una altura <2, 8, 15, y 30 cm. Al inicio de la temporada de crecimiento, las malezas respondieron al N antes que la remolacha. Al promediarse todos los momentos de remoción de malezas, la asimilación de N por las malezas fue tres veces mayor que la de la remolacha a 0, 67, 100, y 134 kg N ha−1 y cuatro veces mayor que la remolacha con la aplicación dividida de N (67:67 kg N ha−1). Las dosis más altas de N incrementaron los valores del índice de suficiencia de N y el cierre del dosel de la remolacha. Las malezas de 30 cm de altura tuvieron valores del índice de suficiencia de N más bajos y un dosel de la remolacha más pequeño. El efecto de N en los rendimientos de raíces variaron, pero las dosis más altas de N (134 kg N ha−1 ó 67:67 kg N ha−1) tuvieron los rendimientos de remolacha más altos en todas las localidades. Los rendimientos más altos fueron alcanzados cuando se controló las malezas antes de que alcanzaran 2 cm de altura, en tres de los cuatro sitios-año. El retrasar el control de malezas hasta que estas tuvieron 8 ó 15 cm de altura, redujo el rendimiento en 15%, mientras que malezas de 30 cm de altura redujeron el rendimiento en hasta 21%. Sucrose blanca recuperable ha−1 (RWSH) también se redujo entre 8 y 16% si las malezas tuvieron 8 cm de altura. Estos resultados indican que las malezas son altamente competitivas con la remolacha y pueden asimilar grandes cantidades de N temprano en la temporada de crecimiento, especialmente en estados de crecimiento más grandes. Sin embargo, parece que las remolachas fueron capaces de buscar y absorber suficiente N a las dosis de N usadas en este estudio, para compensar los efectos de la remoción de N por las malezas más grandes, lo que resultó en la ausencia de interacciones entre la dosis de N y el momento de remoción de malezas en el rendimiento, calidad y RWSH de la remolacha.


Weed Science | 2013

Fertilizer and Population Affects Nitrogen Assimilation of Common Lambsquarters (Chenopodium album) and Redroot Pigweed (Amaranthus retroflexus)

Laura E. Lindsey; Darryl D. Warncke; Kurt Steinke; Wesley J. Everman

Abstract Weed growth and N assimilation usually increase with N application rate. With the increasing price of N fertilizer, a better understanding N assimilation by weeds is necessary to maximize economic return. Total plant yield is generally independent of population density, except when plants are very small or at very low population density. If plant yield is independent of population density, weed N assimilation may also be independent of population density. However, the effect of weed population density on N assimilation has not been thoroughly investigated. A 2011 controlled-environment study was established in East Lansing, MI, to evaluate the effect of weed population density and N application rate on growth and N assimilation by common lambsquarters and redroot pigweed. Study factors included four weed densities (1, 2, 4, and 8 plants pot−1), three N application rates (0, 67, and 134 kg N ha−1), and two weed species (redroot pigweed and common lambsquarters). Weeds were destructively harvested 3 wk after emergence, and shoot height, biomass, total N concentration, N use efficiency, and N assimilation were measured. Redroot pigweed was taller, had greater shoot biomass, and a greater shoot N assimilation than did common lambsquarters. With similar environmental conditions, redroot pigweed is expected to be more competitive than common lambsquarters. Shoot N assimilation increased with increasing weed population density, indicating that N assimilation was not independent of population density 3 wk after emergence because weeds were small or at low population density. Nomenclature: Common lambsquarters, Chenopodium album L. CHEAL; redroot pigweed, Amaranthus retroflexus L. AMARE


Journal of Crop Improvement | 2017

Determining corn nitrogen rates using multiple prediction models

Jeff Rutan; Kurt Steinke

ABSTRACT Weather uncertainty and soil spatial variability impact nitrogen (N) cycling and corn (Zea mays L.) growth, making accurate N predictions a challenge. Field studies were conducted in Lansing, Michigan, to evaluate a computer model (i.e., Adapt-N), a preseason year-based model (i.e., maximum return to N [MRTN]), and a crop sensor model (i.e., active canopy sensor with algorithm) for recommending corn N rates. To determine site-specific economic optimum N rates (EONR), five N rates were also applied (0, 33%, 66%, 133%, and 166% of the suggested MRTN) as starter + sidedress (SD) at V4. In a wet year (i.e., 2015), Adapt-N increased V8 SD N rates 35 kg N ha−1 relative to the MRTN V4 SD N application. Although the greater rate of N may have provided additional yield protection, no statistical yield differences were observed between the two models. The MRTN model increased partial factor productivity (PFP) 20% relative to Adapt-N. Limited expression of V8 corn N deficiency reduced crop sensor total N rates (21–56 kg N ha−1) and yield (0.82–1.05 Mg ha−1) relative to other models. In a drier year (i.e., 2016), N demand was reduced (EONR 64 kg N ha−1 less than 2015), resulting in similar corn response to all three models. Despite differences in actual corn N rate recommendations, all three models resulted in similar economic net returns across study years. Abbreviations: EONR, economic optimum nitrogen rate; MRTN, Maximum Return to Nitrogen; NUE, nitrogen-use efficiency; PFP, partial factor productivity; SBNRC, sensor-based nitrogen rate calculator; SD, side-dress


Crop Science | 2003

Nitrogen Selection and Growth Regulator Applications for Improving Shaded Turf Performance

Kurt Steinke; John C. Stier


Journal of Environmental Quality | 2007

Prairie and turf buffer strips for controlling runoff from paved surfaces.

Kurt Steinke; John C. Stier; W. R. Kussow; Anita M. Thompson


Crop Science | 2011

Bermudagrass and Buffalograss Drought Response and Recovery at Two Soil Depths

Kurt Steinke; David R. Chalmers; James C. Thomas; Richard H. White


Crop Science | 2010

Drought Response and Recovery Characteristics of St. Augustinegrass Cultivars

Kurt Steinke; David R. Chalmers; James C. Thomas; Richard H. White; G. Fipps


Hortscience | 2010

Landscape Coefficients for Single- and Mixed-species Landscapes

Tim R. Pannkuk; Richard H. White; Kurt Steinke; Jacqueline A. Aitkenhead-Peterson; David R. Chalmers; James C. Thomas

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John C. Stier

University of Wisconsin-Madison

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Jeff Rutan

Michigan State University

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W. R. Kussow

University of Wisconsin-Madison

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Anita M. Thompson

University of Wisconsin-Madison

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