@article{reisig_reay-jones_meijer_2015, title={Aggregation and Association of NDVI, Boll Injury, and Stink Bugs in North Carolina Cotton}, volume={15}, ISSN={["2250-2645"]}, DOI={10.1093/jisesa/iev119}, abstractNote={Sampling of herbivorous stink bugs in southeastern U.S. cotton remains problematic. Remote sensing was explored to improve sampling of these pests and associated boll injury. Two adjacent 14.5-ha cotton fields were grid sampled in 2011 and 2012 by collecting stink bug adults and bolls every week during the third, fourth, and fifth weeks of bloom. Satellite remote sensing data were collected during the third week of bloom during both years, and normalized difference vegetation index (NDVI) values were calculated. Stink bugs were spatially aggregated on the third week of bloom in 2011. Boll injury from stink bugs was spatially aggregated during the fourth week of bloom in 2012. The NDVI values were aggregated during both years. There was a positive association and correlation between stink bug numbers and NDVI values, as well as injured bolls and NDVI values, during the third week of bloom in 2011. During the third week of bloom in 2012, NDVI values were negatively correlated with stink bug numbers. During the fourth week of bloom in 2011, stink bug numbers and boll injury were both positively associated and correlated with NDVI values. During the fourth week of bloom in 2012, stink bugs were negatively correlated with NDVI values, and boll injury was negatively associated and correlated with NDVI values. This study suggests the potential of remote sensing as a tool to assist with sampling stink bugs in cotton, although more research is needed using NDVI and other plant measurements to predict stink bug injury.}, number={1}, journal={JOURNAL OF INSECT SCIENCE}, publisher={Oxford University Press (OUP)}, author={Reisig, Dominic D. and Reay-Jones, F. P. F. and Meijer, A. D.}, year={2015}, month={Sep} }
 @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{reberg-horton_grossman_kornecki_meijer_price_place_webster_2012, title={Utilizing cover crop mulches to reduce tillage in organic systems in the southeastern USA}, volume={27}, ISSN={["1742-1713"]}, DOI={10.1017/s1742170511000469}, abstractNote={Abstract}, number={1}, journal={RENEWABLE AGRICULTURE AND FOOD SYSTEMS}, publisher={Cambridge University Press (CUP)}, author={Reberg-Horton, S. Chris and Grossman, Julie M. and Kornecki, Ted S. and Meijer, Alan D. and Price, Andrew J. and Place, George T. and Webster, Theodore M.}, year={2012}, month={Mar}, pages={41–48} }
 @article{smith_reberg-horton_place_meijer_arellano_mueller_2011, title={Rolled Rye Mulch for Weed Suppression in Organic No-Tillage Soybeans}, volume={59}, ISSN={["1550-2759"]}, DOI={10.1614/ws-d-10-00112.1}, abstractNote={Rising demand for organic soybeans and high price premiums for organic products have stimulated producer interest in organic soybean production. However, organic soybean producers and those making the transition to organic production cite weed management as their main limitation. Current weed management practices heavily rely on cultivation. Repeated cultivation is expensive and has negative consequences on soil health. Research is needed to improve organic reduced tillage production. Rye cover crop mulches were evaluated for weed suppression abilities and effects on soybean yield. Experiments were planted in 2008 and 2009 at three sites. Rye was planted in the fall of each year and killed at soybean planting with a roller/crimper or flail mower, creating a thick weed-suppressing mulch with potential allelopathic properties. The mulch was augmented with one of three additional weed control tactics: preemergence (PRE) corn gluten meal (CGM), postemergence (POST) clove oil, or postemergence high-residue cultivation. Roll-crimped and flail-mowed treatments had similar weed suppression abilities at most sites. There were no differences between CGM, clove oil, or cultivation at most sites. Sites with rye biomass above 9,000 kg ha−1of dry matter provided weed control that precluded soybean yield loss from competition. In Goldsboro 2008, where rye biomass was 10,854 kg ha−1of dry matter, the soybean yield in the rolled rye treatment was not significantly different from the weed-free treatment, yielding at 2,190 and 2,143 kg ha−1, respectively. Likewise, no difference in soybean yield was found in Plymouth 2008 with a rye biomass of 9,256 kg ha−1and yields of 2,694 kg ha−1and 2,809 kg ha−1in the rolled rye and weed-free treatments, respectively. At low rye biomass levels (4,450 to 6,606 kg ha−1), the rolled rye treatment soybean yield was 628 to 822 kg ha−1less than the weed-free treatment. High rye biomass levels are critical to the success of this production system. However, high rye biomass was, in some cases, also correlated with soybean lodging severe enough to cause concern with this system.}, number={2}, journal={WEED SCIENCE}, publisher={Cambridge University Press (CUP)}, author={Smith, Adam N. and Reberg-Horton, Chris and Place, George T. and Meijer, Alan D. and Arellano, Consuelo and Mueller, J. Paul}, year={2011}, pages={224–231} }
 @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} }