@article{rajkovich_osmond_weisz_crozier_israel_austin_2017, title={Evaluation of Nitrogen-Loss Prevention Amendments in Maize and Wheat in North Carolina}, volume={109}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2016.03.0153}, abstractNote={1811 Variability in crop N requirements across states, regions, seasons, crops, and even fields complicates the selection of an appropriate N rate, and has led to concerns of the environmental impacts that may result from over-application. Nitrogen from agricultural sources can be lost through volatilization or denitrification, but nitrate (NO3) leaching constitutes the largest percent of loss and can consequently contaminate ground and surface water (David et al., 1997; Jaynes et al., 2001; Randall and Goss, 2001). Aside from the well documented negative health effects of NO3 in drinking water (Spalding and Exner, 1993; Sogbedji et al., 2001), excess NO3 can also cause eutrophication and hypoxia of lakes and coastal waters (Spalding and Exner, 1993; Randall and Goss, 2001), a consequence that can be devastating to ecosystem biodiversity (Kronvang et al., 2001). Minimizing N rates can lower leaching losses and protect water quality while maintaining crop yields, but identifying appropriate N rates can be a challenge. In North Carolina, the realistic yield expectations (RYE) database provides recommended N rates for 32 different crops by soil series (North Carolina Nutrient Management Workgroup, 2003). The database was developed and validated through N rate trials across the state. More recently maize N recommendations were updated to reflect changes in N use efficiency related to new hybrid releases and farmer management practices (Rajkovich et al., 2015). Nationally, the “4Rs” (right rate, right placement, right timing, and right source) have been promoted by private and public organizations (Natural Resources Conservation Service, 2005; The Fertilizer Institute, 2011; International Plant Nutrition Institute, 2012) as a platform for farmers to think about their N applications in a logical, interconnected way. Beyond typical soil-based N rate recommendations, farmers also have access to fertilizer N-loss prevention amendments intended to reduce the amount of N lost; essentially to bolster the “right source” aspect of an N management plan. These N-loss prevention amendments, which can be added to N fertilizers, have various modes of action and reported levels of effectiveness in the literature. The N-loss prevention amendment NBPT+DCD (AgrotainPlus; Koch Agronomic Services LLC, Wichita, KS), contains the urease inhibitor N-(n-butyl)thiophosphoric triamide (NBPT at 30–70 g kg–1 a.i.) and the Evaluation of Nitrogen-Loss Prevention Amendments in Maize and Wheat in North Carolina}, number={5}, journal={AGRONOMY JOURNAL}, author={Rajkovich, Shelby and Osmond, Deanna and Weisz, Randy and Crozier, Carl and Israel, Daniel and Austin, Robert}, year={2017}, pages={1811–1824} }
 @article{besancon_heiniger_weisz_everman_2017, title={Weed Response to Agronomic Practices and Herbicide Strategies in Grain Sorghum}, volume={109}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2016.06.0363}, abstractNote={Core Ideas High sorghum density and narrow row spacing reduce biomass of troublesome weeds. High spatial crop uniformity extends large crabgrass and sicklepod control over time. Optimized crop density and row width may limit the need for postemergence herbicide in sorghum. Sicklepod [ Senna obtusifolia (L.) H.S. Irwin & Barneby] and large crabgrass ( Digitaria sanguinalis L.) are ranked among the top 10 most common or troublesome weeds in grain sorghum [ Sorghum bicolor (L.) Moench] in the southeastern United States. Field studies conducted in North Carolina from 2012 to 2014 investigated the effects of three row widths, four sorghum populations, and three herbicide programs on weed control, density, biomass, and grain yield. Results indicated that 19‐ and 38‐cm rows provided greater sicklepod control 7 and 10 wk after planting (WAP) compared to 76 cm but had no effect on crabgrass control. Under weed‐controlled conditions, sorghum population ≥297,000 plants ha −1 allowed to maintain higher late‐season sicklepod and crabgrass control as compared to lower crop densities. In the weedy control, row spacing had no effect on weed density and biomass, whereas crop population ≥297,000 plants ha −1 reduced sicklepod density and biomass by 38 and 65%, respectively, compared to 99,000 plants ha −1 . Effect on crabgrass was less pronounced with density and biomass reduction by 18 and 45%, respectively, for 396,000 plants ha −1 compared to 99,000 plants ha −1 . In the absence of water stress, the highest grain yields were obtained with high spatial uniformity, corresponding to 19‐cm rows and sorghum population ≥297,000 sorghum plants ha −1 . Our results indicate that increased sorghum density associated with narrow rows may reduce the need for a postemergence (POST) herbicide but underscore the importance of a timely activated preemergence (PRE) treatment to efficiently control sicklepod and crabgrass.}, number={4}, journal={AGRONOMY JOURNAL}, author={Besancon, Thierry and Heiniger, Ronnie and Weisz, Randy and Everman, Wesley}, year={2017}, pages={1642–1650} }
 @article{cowger_weisz_arellano_murphy_2016, title={Profitability of Integrated Management of Fusarium Head Blight in North Carolina Winter Wheat}, volume={106}, ISSN={["1943-7684"]}, DOI={10.1094/phyto-10-15-0263-r}, abstractNote={Fusarium head blight (FHB) is one of the most difficult small-grain diseases to manage, due to the partial effectiveness of management techniques and the narrow window of time in which to apply fungicides profitably. The most effective management approach is to integrate cultivar resistance with FHB-specific fungicide applications; yet, when forecasted risk is intermediate, it is often unclear whether such an application will be profitable. To model the profitability of FHB management under varying conditions, we conducted a 2-year split-plot field experiment having as main plots high-yielding soft red winter wheat cultivars, four moderately resistant (MR) and three susceptible (S) to FHB. Subplots were sprayed at flowering with Prosaro or Caramba, or left untreated. The experiment was planted in seven North Carolina environments (location-year combinations); three were irrigated to promote FHB development and four were not irrigated. Response variables were yield, test weight, disease incidence, disease severity, deoxynivalenol (DON), Fusarium-damaged kernels, and percent infected kernels. Partial profits were compared in two ways: first, across low-, medium-, or high-DON environments; and second, across environment-cultivar combinations divided by risk forecast into "do spray" and "do not spray" categories. After surveying DON and test weight dockage among 21 North Carolina wheat purchasers, three typical market scenarios were used for modeling profitability: feed-wheat, flexible (feed or flour), and the flour market. A major finding was that, on average, MR cultivars were at least as profitable as S cultivars, regardless of epidemic severity or market. Fungicides were profitable in the feed-grain and flexible markets when DON was high, with MR cultivars in the flexible or flour markets when DON was intermediate, and on S cultivars aimed at the flexible market. The flour market was only profitable when FHB was present if DON levels were intermediate and cultivar resistance was combined with a fungicide. It proved impossible to use the risk forecast to predict profitability of fungicide application. Overall, the results indicated that cultivar resistance to FHB was important for profitability, an FHB-targeted fungicide expanded market options when risk was moderate or high, and the efficacy of fungicide decision-making is reduced by factors that limit the accuracy of risk forecasts.}, number={8}, journal={PHYTOPATHOLOGY}, author={Cowger, Christina and Weisz, Randy and Arellano, Consuelo and Murphy, Paul}, year={2016}, month={Aug}, pages={814–823} }
 @article{worthington_reberg-horton_brown-guedira_jordan_weisz_murphy_2015, title={Morphological Traits Associated with Weed-Suppressive Ability of Winter Wheat against Italian Ryegrass}, volume={55}, ISSN={["1435-0653"]}, DOI={10.2135/cropsci2014.02.0149}, abstractNote={ABSTRACT Weed‐suppressive wheat ( Triticum aestivum L.) cultivars have been suggested as a complement to chemical and cultural methods of weed control. The objectives of this study were to assess the range of weed‐suppressive ability against Italian ryegrass [ Lolium perenne L. ssp. multiflorum (Lam.) Husnot] existing in winter wheat lines adapted to North Carolina and to identify wheat morphological traits that could facilitate indirect selection for weed suppression in the southeastern United States. Fifty‐three commercially available cultivars and advanced experimental lines were overseeded with a uniform, high rate of Italian ryegrass, evaluated for various morphological traits throughout the growing season, and investigated for weed‐suppressive ability at a total of four field sites. Genotypic differences in Italian ryegrass seed head density ( P ≤ 0.05) were detected among the wheat lines. Reduced Italian ryegrass seed head density was correlated ( P ≤ 0.05) with high vigor during tillering and heading (Zadoks growth stage [GS] 25, 29, 55), erect growth habit (GS 29), low normalized difference vegetation index (NDVI) (GS 29), high leaf area index (LAI) at stem extension (GS 31), early heading date, and tall height throughout the growing season (GS 29, 31, 55, 70 to 80) in three of four sites. Multiple regression models show that 71% of variation in weed‐suppressive ability was accounted for by final height (GS 70 to 80) and either height or plant vigor at late tillering (GS 29). Thus, breeders could improve weed‐suppressive ability using weighted index selection for genotypes that are tall or vigorous during tillering with tall final height.}, number={1}, journal={CROP SCIENCE}, publisher={Crop Science Society of America}, author={Worthington, Margaret and Reberg-Horton, S. Chris and Brown-Guedira, Gina and Jordan, David and Weisz, Randy and Murphy, J. Paul}, year={2015}, pages={50–56} }
 @article{mehra_cowger_weisz_ojiambo_2015, title={Quantifying the Effects of Wheat Residue on Severity of Stagonospora nodorum Blotch and Yield in Winter Wheat}, volume={105}, DOI={10.1094/phyto-03-15-0080-r}, abstractNote={Stagonospora nodorum blotch (SNB), caused by the fungus Parastagonospora nodorum, is a major disease of wheat (Triticum aestivum). Residue from a previously infected wheat crop can be an important source of initial inoculum, but the effects of infected residue on disease severity and yield have not previously been quantified. Experiments were conducted in Raleigh and Salisbury, North Carolina, in 2012, 2013, and 2014 using the moderately susceptible winter wheat cultivar DG Shirley. In 2014, the highly susceptible cultivar DG 9012 was added to the experiment and the study was conducted at an additional site in Tyner, North Carolina. Four (2012) or six (2013 and 2014) wheat residue treatments were applied in the field in a randomized complete block design with five replicates. Treatments in 2012 were 0, 30, 60, and 90% residue coverage of the soil surface, while 10 and 20% residue treatments were added in 2013 and 2014. Across site-years, disease severity ranged from 0 to 50% and increased nonlinearly (P < 0.05) as residue level increased, with a rapid rise to an upper limit and showing little change in severity above 20 to 30% soil surface coverage. Residue coverage had a significant (P < 0.05) effect on disease severity in all site-years. The effect of residue coverage on yield was only significant (P < 0.05) for DG Shirley at Raleigh and Salisbury in 2012 and for DG 9012 at Salisbury in 2014. Similarly, residue coverage significantly (P < 0.05) affected thousand-kernel weight only of DG 9012 in 2014 at Raleigh and Salisbury. Our results showed that when wheat residue was sparse, small additions to residue density produced greater increases in SNB than when residue was abundant. SNB only led to effects on yield and test weight in the most disease-conducive environments, suggesting that the economic threshold for the disease may be higher than previously assumed and warrants review.}, number={11}, journal={Phytopathology}, publisher={Scientific Societies}, author={Mehra, L. K. and Cowger, C. and Weisz, R. and Ojiambo, P. S.}, year={2015}, month={Nov}, pages={1417–1426} }
 @article{worthington_reberg-horton_brown-guedira_jordan_weisz_murphy_2015, title={Relative Contributions of Allelopathy and Competitive Traits to the Weed Suppressive Ability of Winter Wheat Lines Against Italian Ryegrass}, volume={55}, ISSN={["1435-0653"]}, DOI={10.2135/cropsci2014.02.0150}, abstractNote={ABSTRACT Allelopathy and competitive ability have been identified as independent factors contributing to the weed suppressive ability of crop cultivars; however, it is not clear whether these factors have equal influence on weed suppression outcomes of winter wheat ( Triticum aestivum L.) lines in the field. Fifty‐eight winter wheat lines adapted to the southeastern United States were screened for allelopathic activity against Italian ryegrass ( Lolium perenne L. ssp. multiflorum [Lam.] Husnot) in an agar‐based seedling bioassay. Eight strongly and weakly allelopathic lines were identified and evaluated for weed suppressive ability and grain yield tolerance in a replicated field experiment conducted in North Carolina. Significant genotypic differences in weed suppressive ability were found in three of four study environments, while genotypic differences in yield tolerance were identified in all environments. Although the allelopathic activity of genotypes varied in the seedling bioassay, no correlations between allelopathy and weed suppressive ability or grain yield tolerance were observed. Weed suppressive ability was correlated with competitive traits, including vigor and erect growth habit during tillering (Zadoks GS 29), high leaf area index (LAI) at stem extension (GS 31), plant height at tillering and stem extension (GS 29, 31), grain yield in weedy conditions, and grain yield tolerance. Therefore, breeders in the southeastern United States should focus their efforts on improving competitive traits within adapted germplasm rather than selecting for cultivars with high allelopathic activity to achieve maximum gains in weed suppressive ability against Italian ryegrass.}, number={1}, journal={CROP SCIENCE}, publisher={Crop Science Society of America}, author={Worthington, Margaret and Reberg-Horton, S. Chris and Brown-Guedira, Gina and Jordan, David and Weisz, Randy and Murphy, J. Paul}, year={2015}, pages={57–64} }
 @article{reisig_bacheler_herbert_kuhar_malone_philips_weisz_2012, title={Efficacy and Value of Prophylactic vs. Integrated Pest Management Approaches for Management of Cereal Leaf Beetle (Coleoptera: Chrysomelidae) in Wheat and Ramifications for Adoption by Growers}, volume={105}, ISSN={["1938-291X"]}, DOI={10.1603/ec12124}, abstractNote={ABSTRACT 
 Cereal leaf beetle, Oulema melanopus L., can be effectively managed in southeastern U.S. wheat, Triticum aestivum L., with scouting and a single insecticide treatment, applied at the recommended economic threshold. However, many growers eschew this approach for a prophylactic treatment, often tank mixed with a nitrogen application before wheat growth stage 30. The efficacy of a prophylactic and an integrated pest management (IPM) approach was compared for 2 yr using small plot studies in North Carolina and regional surveys across North Carolina and Virginia. Economic analyses were performed, comparing the total cost of management of each approach using the regional survey data. From a cost perspective, the prophylactic approach was riskier, because when cereal leaf beetle densities were high, economic loss was also high. However, fields under the prophylactic approach did not exceed threshold as often as fields using IPM. Total cost of prophylactic management was also $20.72 less per hectare, giving this approach an economic advantage over IPM. The majority of fields under the IPM approach did not exceed the economic threshold. Hence, from an economic perspective, both the prophylactic and IPM approaches have advantages and disadvantages. This helps explains the partial, rather than complete, adoption of IPM by southeastern U.S. wheat growers. Cereal leaf beetle was spatially aggregated across the region in 2010, but not in 2011. As a result, from an economic standpoint, prophylaxis or IPM may have a better fit in localized areas of the region than others. Finally, because IPM adoption is favored when it has a strong economic advantage over alternative management approaches, more emphasis should be placed on research to reduce costs within the IPM approach.}, number={5}, journal={JOURNAL OF ECONOMIC ENTOMOLOGY}, publisher={Oxford University Press (OUP)}, author={Reisig, Dominic D. and Bacheler, Jack S. and Herbert, D. Ames and Kuhar, Thomas and Malone, Sean and Philips, Chris and Weisz, Randy}, year={2012}, month={Oct}, pages={1612–1619} }
 @article{weisz_cowger_ambrose_gardner_2011, title={Multiple Mid-Atlantic Field Experiments Show No Economic Benefit to Fungicide Application When Fungal Disease Is Absent in Winter Wheat}, volume={101}, ISSN={["0031-949X"]}, DOI={10.1094/phyto-03-10-0096}, abstractNote={ Strobilurin fungicides produce intensified greening and delayed senescence in plants, and have been claimed to enhance yields of field crops in the absence of disease. To help evaluate this claim, available publicly sponsored tests of fungicides on soft red winter wheat in Virginia and North Carolina (n = 42) were analyzed for the period 1994 to 2010. All tests were replicated and had a randomized complete block, split-plot, or split-block design. Each test included 1 to 32 cultivars and one to five fungicides (two strobilurins, one triazole, and two strobilurin-triazole mixtures). There was a total of 311 test–cultivar–fungicide treatment comparisons, where a comparison was the reported yield difference between sprayed and unsprayed treatments of a given cultivar in a given test. Parameters used to calculate the economic benefit or loss associated with fungicide application included a grain price range of $73.49 to 257.21 Mg–1 ($2 to 7 bu–1), a total fungicide application cost of $24.71 to 74.13 ha–1 ($10 to 30 acre–1), and a 0.14 to 0.21 Mg ha–1 (2.3 to 3.4 bu acre–1) loss in yield from driving over wheat during application (with a sprayer 27.4 or 18.3 m [90 or 60 feet] wide, respectively). The yield increase needed to pay for a fungicide application at each combination of cost and price was calculated, and the cumulative probability function for the fungicide yield-response data was modeled. The model was used to predict the probability of achieving a break-even yield, and the probabilities were graphed against each cost–price combination. Tests were categorized as “no-disease” or “diseased” based on reports of the researchers rating the tests. Subsets of the data were analyzed to assess the profitability of the triazole fungicide and the strobilurin-containing fungicides separately in no-disease versus diseased experiments. From the results, it was concluded that, with routine fungicide application based solely on wheat growth stage, total fungicide application costs had to be <$24.71 ha–1 ($10 acre–1) in order to average a ≥50% probability of breaking even or making a profit (compared with not spraying). By contrast, if fungicides were applied when fungal disease was present, total application costs of ≤$47 ha–1 ($19 acre–1) for strobilurins and ≤$72 ha–1 ($29 acre–1) for propiconazole alone were associated with a ≥50% probability of breaking even or making a profit at a wheat price of $184 Mg–1. The results do not support the application of strobilurin or triazole fungicides to mid-Atlantic wheat crops for “plant health” in the absence of disease. Rather, they support basing the decision to apply fungicide on observation of disease, if an economic return for the input is desired. }, number={3}, journal={PHYTOPATHOLOGY}, author={Weisz, Randy and Cowger, Christina and Ambrose, Gaylon and Gardner, Andrew}, year={2011}, month={Mar}, pages={323–333} }
 @article{cahill_osmond_weisz_heiniger_2010, title={Evaluation of Alternative Nitrogen Fertilizers for Corn and Winter Wheat Production}, volume={102}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2010.0095}, abstractNote={As natural gas, and thus N fertilizer, prices increase, farmers are looking for ways to decrease N costs in farming operations. To potentially alleviate this cost burden, alternative synthetic N fertilizers are available as potential management tools for increasing crop yields and N use efficiency, and decreasing volatilization. In North Carolina specifically, little data exists on these new, synthetic N fertilizer products being marketed to farmers. Therefore, we undertook a study to compare them with aqueous urea ammonium nitrate (UAN) [(NH2)2CO, NH4NO3] during a 2‐yr field experiment. Corn (Zea mays L.) and wheat (Triticum aestivum L.) were grown in the three physiographic regions of North Carolina with four fertilizer sources (NutriSphere [Specialty Fertilizer Products, Leawood, KS], Environmentally Smart Nitrogen Polymer Coated Urea or ESN [Agrium Inc., Alberta, Canada] UCAN‐23 [Yara, Tampa, FL], and UAN) at up to six fertilizer rates. The use of the alternative products did not regularly produce more corn or wheat grain compared to UAN, while wheat straw yield was greater with NutriSphere, UCAN, and UAN compared to ESN in three of four site years. Also, an aerobic incubation experiment was performed to evaluated N release profiles of the fertilizers at 25°C. The study found that NutriSphere and UCAN release time was similarly to UAN, while ESN showed a slower release profile. However, any difference in release did not affect yields of spring planted corn, NutriSphere and ESN increased corn stover yields in 3 of 6 site‐years. In determining whether to use these alternative N fertilizer products, farmers should consider location, climatic conditions, and fertilizer costs in comparison to UAN.}, number={4}, journal={AGRONOMY JOURNAL}, author={Cahill, Sheri and Osmond, Deanna and Weisz, Randy and Heiniger, Ronnie}, year={2010}, pages={1226–1236} }
 @article{cowger_weisz_anderson_horton_2010, title={Maize Debris Increases Barley Yellow Dwarf Virus Severity in North Carolina Winter Wheat}, volume={102}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2009.0357}, abstractNote={In the eastern United States, wheat (Triticum aestivum L.) is often planted with minimal or no tillage into maize (Zea mays L.) residues. We conducted a field experiment in the North Carolina Piedmont to compare the effects of three maize residue treatments (unchopped, chopped, and removed) on Fusarium head blight (FHB) in two winter wheat cultivars. While FHB levels were too low for meaningful comparisons, severe epidemics of barley/cereal yellow dwarf virus (YDV) did develop in 2 yr out of 3. In those 2 yr, YDV symptoms of discoloration and stunting were greater (P ≤ 0.001), and yield was lower (P ≤ 0.01), in plots with maize residue than in plots without maize residue. In the third year, when planting was late because of a severe fall drought, no YDV epidemic developed, and there were no differences in wheat yield due to maize residue treatment (P = 0.25). In the first 2 yr, leaf samples from all plots were assayed for viruses using a multiplexed reverse transcription polymerase chain reaction (RT‐PCR) method. The most common YDV serotypes were MAV, PAV, and RPV, which were each detected in at least 46 and 74% of samples in the 2 yr, respectively. Our finding of greater YDV severity in association with surface residue is consistent with the reported aphid preference for high‐intensity yellow colors, which we hypothesize attracted aphids preferentially to residue‐covered plots in the fall. Our results support a recommendation of seed or seedling insecticide treatment when planting wheat into heavy unincorporated maize residue in the U.S. Piedmont.}, number={2}, journal={AGRONOMY JOURNAL}, author={Cowger, Christina and Weisz, Randy and Anderson, Joseph M. and Horton, J. Ray}, year={2010}, pages={688–695} }
 @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{cambron_buntin_weisz_holland_flanders_schemerhorn_shukle_2010, title={Virulence in Hessian Fly (Diptera: Cecidomyiidae) Field Collections From the Southeastern United States to 21 Resistance Genes in Wheat}, volume={103}, ISSN={["1938-291X"]}, DOI={10.1603/ec10219}, abstractNote={ABSTRACT 
 Genetic resistance in wheat, Triticum aestivum L., is the most efficacious method for control of Hessian fly, Mayetiola destructor (Say) (Diptera: Cecidomyiidae). However, because of the appearance of new genotypes (biotypes) in response to deployment of resistance, field collections of Hessian fly need to be evaluated on a regular basis to provide breeders and producers information on the efficacy of resistance (R) genes with respect to the genotype composition of Hessian fly in regional areas. We report here on the efficacy of 21 R genes in wheat to field collections of Hessian fly from the southeastern United States. Results documented that of the 21 R genes evaluated only five would provide effective protection of wheat from Hessian fly in the southeastern United States. These genes were H12, H18, H24, H25, and H26. Although not all of the 33 identified R genes were evaluated in the current study, these results indicate that identified genetic resistance to protect wheat from Hessian attack in the southeastern United States is a limited resource. Historically, R genes for Hessian fly resistance in wheat have been deployed as single gene releases. Although this strategy has been successful in the past, we recommend that in the future deployment of combinations of highly effective previously undeployed genes, such as H24 and H26, be considered. Our study also highlights the need to identify new and effective sources of resistance in wheat to Hessian fly if genetic resistance is to continue as a viable option for protection of wheat in the southeastern United States.}, number={6}, journal={JOURNAL OF ECONOMIC ENTOMOLOGY}, author={Cambron, Sue E. and Buntin, G. David and Weisz, Randy and Holland, Jeffery D. and Flanders, Kathy L. and Schemerhorn, Brandon J. and Shukle, Richard H.}, year={2010}, month={Dec}, pages={2229–2235} }
 @article{cowger_weisz_2008, title={Winter wheat blends (mixtures) produce a yield advantage in north Carolina}, volume={100}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2007.0128}, abstractNote={Seed mixtures, or blends, of small grain cultivars are unknown in eastern U.S. wheat production, where numerous diseases and abiotic stresses often reduce yield and quality. In 2004–2005 and 2005–2006, a field experiment was conducted at Kinston, Plymouth, and Salisbury, NC, to compare performance of eight soft red winter wheat (Triticum aestivum L.) cultivars having a range of maturities with that of 13 blends, each consisting of equal proportions of two or three of the cultivars. The blends were composed to have complementary disease resistance traits. Disease pressure was at most moderate in any environment. Blends significantly outyielded the means of their respective components (midcomponents) in Plymouth in 2005 (P = 0.042) and across all environments (P = 0.039), with a mean overall blend advantage of 0.13 Mg ha−1. Averaged across environments, two blends significantly outyielded their midcomponents (P ≤ 0.011). Yield stability of blends exceeded that of pure cultivars by the stability variance model and principal component analysis. In general, blends did not differ significantly from midcomponents for test weight (P = 0.37), protein content (P = 0.10), hardness (P = 0.68), or falling number (sprouting tolerance, P = 0.89), but seed diameter nonuniformity of blends exceeded that of midcomponents (P = 0.0002). Wheat blends may offer a small yield advantage to North Carolina growers even in the absence of severe disease.}, number={1}, journal={AGRONOMY JOURNAL}, author={Cowger, Christina and Weisz, Randy}, year={2008}, pages={169–177} }
 @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{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{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{cahill_osmond_crozier_israel_weisz_2007, title={Winter wheat and maize response to urea ammonium nitrate and a new urea formaldehyde polymer fertilizer}, volume={99}, DOI={10.2134/agronj2OO7.0132}, number={6}, journal={Agronomy Journal}, author={Cahill, S. and Osmond, Deanna and Crozier, C. and Israel, D. and Weisz, R.}, year={2007}, pages={1645–1653} }
 @article{farrer_weisz_heiniger_murphy_pate_2006, title={Delayed harvest effect on soft red winter wheat in the southeastern USA}, volume={98}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2005.0211}, abstractNote={Harvest of soft red winter wheat (Triticum aestivum L.) in the southeastern USA can be delayed because of inclement weather or other unforeseen problems. Our objectives were to determine the impact of delaying harvest beyond grain ripeness (135 g kg−1 grain moisture content) on yield, test weight, grain protein, and 20 milling and baking quality parameters, and to determine if these impacts were correlated with environmental conditions occurring between grain ripeness and harvest. In 2001 and 2002, a total of six trials were conducted where treatments consisted of a timely harvest at grain ripeness and a delayed harvest, 8 to 19 d later. Yield was reduced by up to ∼900 kg ha−1 due to delayed harvest, with yield losses negatively related to total precipitation and positively related to minimum daily temperatures (R2 = 0.99) during the delay interval, indicating that dry and warm environments increased yield losses. Test weight reductions up to ∼115 kg m−3 were seen and were linearly related to the number of precipitation events (r2 = 0.93) between harvests. Grain protein was not affected by delayed harvest. Of the milling and baking quality parameters measured, grain and flour falling number, clear flour percentage, grain deoxynivalenol (DON), and farinograph breakdown times were negatively affected by delayed harvest. Lower falling numbers and higher levels of DON are consistent with the high humidity and rainfall typical of the southeastern USA wheat harvest and are problematic for millers. Decreased farinograph breakdown times can be a problem for bakers.}, number={3}, journal={AGRONOMY JOURNAL}, author={Farrer, Dianne and Weisz, Randy and Heiniger, Ronnie and Murphy, J. Paul and Pate, Michael H.}, year={2006}, pages={588–595} }
 @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{weisz_tarleton_murphy_kolb_2005, title={Identifying soft red winter wheat cultivars tolerant to Barley yellow dwarf virus}, volume={89}, ISSN={["1943-7692"]}, DOI={10.1094/PD-89-0170}, abstractNote={ Barley yellow dwarf virus (BYDV) is a serious disease of soft red winter wheat. Although there has been interest in tolerant cultivars, identification and development has been slow due to a lack of precision in rating plants for response to BYDV. Visual ratings of symptoms are commonly used to evaluate cultivars, but these ratings have proven to be inconsistent. The objectives of this research were to assess BYDV visual symptom ratings of wheat cultivars under field conditions, to measure disease-related yield reductions in these cultivars, to determine if a relationship exists between BYDV visual symptoms and yield reductions, and to determine BYDV cultivar tolerance. A split-plot design with insecticide treatment (main plot) and 11 cultivars (subplots) was employed over 4 years. The overall relationship between symptom ratings and BYDV yield reductions was weak (R2 = 0.40) and not consistent across years or cultivars. A consistency of performance analysis showed cultivars clustered into five distinct tolerance classes. Under conditions of high BYDV infestation, visual symptom ratings could be cautiously used to identify highly tolerant cultivars. The most reliable method for rating cultivar tolerance was a direct measure of disease-induced yield reduction across multiple environments. }, number={2}, journal={PLANT DISEASE}, author={Weisz, R and Tarleton, B and Murphy, JP and Kolb, FL}, year={2005}, month={Feb}, pages={170–176} }
 @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} }
 @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} }
 @article{flowers_weisz_heiniger_osmond_crozier_2004, title={In-season optimization and site-specific nitrogen management for soft red winter wheat}, volume={96}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2004.0124}, abstractNote={application up to 70% without a reduction in grain yield compared to a grower’s practice. Site-specific N management based on an in-season assessment of Stone et al. (1996) used an on-the-go sensor measurcrop N status may offer producers increased grain yield, profitability, ing plant N spectral index to create submeter siteand spring N fertilizer use efficiency (SNUE). The goal of this study specific N management units based on an estimate of was to determine the distinct contributions of (i) in-season N rate optimization and (ii) site-specific N management. Our objective was in-season crop N status in wheat. This site-specific N to compare site-specific and field-specific N management with typical management system reduced N fertilizer by 32 and 57 growers’ practices to determine if site-specific N management (i) kg N ha 1 at two of three sites without a reduction in increased soft red winter wheat (Triticum aestivum L.) grain yield, grain yield compared with a typical grower’s practice. (ii) reduced N inputs, (iii) increased SNUE, and (iv) reduced withinThey also reported that the site-specific N application field grain yield variability. Research was conducted at eight sites in reduced spatial variation in wheat forage and grain yield 2000, 2001, and 2002. A randomized complete block design with two compared with the grower’s practice. or five N management systems was used at two and six sites, respecSimilarly, Raun et al. (2002) used a multispectral optitively. Site-specific management did not improve grain yield compared cal sensor to create 1-m2 site-specific N management with field-specific management when based on the same in-season units in wheat. A N fertilizer optimization algorithm estimation of optimum N rates. At sites where site-specific or field(NFOA) that estimates in-season crop N status and specific systems were compared with typical growers’ practices, grain potential grain yield was used to adjust N rates. They yield benefits of in-season N optimization (up to 2267 kg ha 1) were reported that by using NFOA, it might be possible to apparent. For grain yield, in-season optimization of N rate was more important than site-specific management. A large reduction in N inset more efficient and profitable fertilization levels and puts (up to 48.6%) was also attributed to in-season N rate optimizaincrease N use efficiency compared with typical growtion. After incorporating in-season optimization, a further reduction ers’ practices. in N inputs (up to 19.6%) was possible through site-specific applicaMulla et al. (1992), Bhatti et al. (1998), Stone et al. tion. Site-specific N application maximized SNUE compared with (1996), and Raun et al. (2002) compared site-specific N either field-specific or typical growers’ practices at all sites and reduced management based on either a preor in-season estiwithin-field grain yield variance at four sites. mate of the crop’s N requirement to a typical grower’s practice. Consequently, the reduction in N rates compared with growers’ practices might not have been the S N management is the adjusting of withinresult of site-specific application but could instead be field N fertilizer rates based on spatially variable due to using a preor in-season estimation of the crop’s factors that affect optimum N rate (Sawyer, 1994). This N requirement. practice may offer producers the ability to increase grain In the southeastern USA, Scharf and Alley (1993), yield, profitability, and N fertilizer efficiency by applyAlley et al. (1994), Weisz and Heiniger (2000), and ing N only where required for optimum plant growth. Weisz et al. (2001) developed a field-specific N manageSite-specific management may also be environmentally ment system for soft red winter wheat based on an inbeneficial to producers. season evaluation of the crop’s N requirement (Fig. 1). Mulla et al. (1992) created site-specific management This system first determines the whole-field tiller density units (18.3 m by 564–655 m) based on preseason soil N at Zadoks’ Growth Stage (GS) 25 (Zadoks et al., 1974). (nitrate N and ammonium N) tests and available soil When GS-25 tiller density is below a critical threshold water content. Similarly, Bhatti et al. (1998) created (540 tillers m 2), a GS-25 N application is made to insite-specific N management units based on crop produccrease tiller development (Ayoub, 1974; Power and tivity. In both cases, site-specific N reduced N fertilizer Alessi, 1978; Lutcher and Mahler, 1988; Scharf and Alley, 1993; Weisz et al., 2001). A GS-25 N application can stimulate tiller development in southeastern areas M. Flowers, USDA-ARS, Air Quality–Plant Growth and Dev. Res. because winter wheat does not enter a dormant state Unit, 3908 Inwood Rd., Raleigh, NC 27603; R. Weisz, Dep. of Crop in these southern latitudes. If GS-25 tiller density is Sci., North Carolina State Univ., Box 7620, Raleigh, NC 27695-7620; above the threshold, a GS-25 N application is not necesR. Heiniger, Dep. of Crop Sci, North Carolina State Univ., Vernon James Res. and Ext. Cent., 207 Research Rd., Plymouth, NC 27692; sary. At GS 30, a field-averaged tissue test is used to D. Osmond, Dep. of Soil Sci., North Carolina State Univ., Box 7619, optimize N application rates (Alley et al., 1994). This Raleigh, NC 27695-7619; and C. Crozier, Dep. of Soil Sci., North system resulted in an increase in estimated profit of $73 Carolina State Univ., Vernon James Res. and Ext. Cent., 207 Research ha 1 across 20 site-years (Scharf and Alley, 1993). Rd., Plymouth, NC 27692. Received 5 Dec. 2002. *Corresponding author (mike_flowers@ncsu.edu). While this system (Fig. 1) has been tested and adopted Published in Agron. J. 96:124–134 (2004).  American Society of Agronomy Abbreviations: GS, growth stage; SNUE, spring nitrogen fertilizer use efficiency. 677 S. Segoe Rd., Madison, WI 53711 USA}, number={1}, journal={AGRONOMY JOURNAL}, author={Flowers, M and Weisz, R and Heiniger, R and Osmond, D and Crozier, C}, year={2004}, pages={124–134} }
 @article{murphy_navarro_leath_bowman_weisz_ambrose_pate_fountain_2004, title={Registration of 'NC-Neuse' wheat}, volume={44}, ISSN={["1435-0653"]}, DOI={10.2135/cropsci2004.1479}, abstractNote={Crop ScienceVolume 44, Issue 4 p. 1479-1480 Registration of Cultivar Registration of ‘NC-Neuse’ Wheat J.P. Murphy, Corresponding Author J.P. Murphy njpm@unity.ncsu.edu Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Corresponding author (njpm@unity.ncsu.edu)Search for more papers by this authorR.A. Navarro, R.A. Navarro Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorS. Leath, S. Leath Dep. of Plant Pathology, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorD.T. Bowman, D.T. Bowman Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorP.R. Weisz, P.R. Weisz Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorL.G. Ambrose, L.G. Ambrose Beaufort Co. CES, 155 Airport Rd., Washington, NC, 27889Search for more papers by this authorM.H. Pate, M.H. Pate MidState Mills, Inc., P.O. Box 350, Newton, NC, 28658Search for more papers by this authorM.O. Fountain, M.O. Fountain Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this author J.P. Murphy, Corresponding Author J.P. Murphy njpm@unity.ncsu.edu Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Corresponding author (njpm@unity.ncsu.edu)Search for more papers by this authorR.A. Navarro, R.A. Navarro Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorS. Leath, S. Leath Dep. of Plant Pathology, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorD.T. Bowman, D.T. Bowman Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorP.R. Weisz, P.R. Weisz Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this authorL.G. Ambrose, L.G. Ambrose Beaufort Co. CES, 155 Airport Rd., Washington, NC, 27889Search for more papers by this authorM.H. Pate, M.H. Pate MidState Mills, Inc., P.O. Box 350, Newton, NC, 28658Search for more papers by this authorM.O. Fountain, M.O. Fountain Dep. of Crop Science, North Carolina State Univ., Raleigh, NC, 27695-7629Search for more papers by this author First published: 01 July 2004 https://doi.org/10.2135/cropsci2004.1479Citations: 17 Research supported in part by grants from the North Carolina Small Grains Growers Association, the North Carolina Foundation Seed Producers, Inc., and the North Carolina Crop Improvement Association. Registration by CSSA. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume44, Issue4July–August 2004Pages 1479-1480 RelatedInformation}, number={4}, journal={CROP SCIENCE}, author={Murphy, JP and Navarro, RA and Leath, S and Bowman, DT and Weisz, PR and Ambrose, LG and Pate, MH and Fountain, MO}, year={2004}, pages={1479–1480} }
 @article{flowers_weisz_heiniger_tarleton_meijer_2003, title={Field validation of a remote sensing technique for early nitrogen application decisions in wheat}, volume={95}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2003.0167}, abstractNote={Studies have shown that winter wheat (Triticum aestivum L.) tiller density at growth stage 25 (GS 25) can be used to determine when a GS-25 N application is needed. However, determining GS-25 tiller density is difficult and time consuming. Color infrared aerial photographs have been successfully used to predict GS-25 tiller density. The objective of this study was to validate a previously reported remote sensing technique to predict GS-25 tiller density based on near-infrared (NIR) digital counts and within-field tiller density references across a wide range of environments. The NIR remote sensing technique was evaluated through linear regression and quadrant plot analysis to determine the accuracy of GS-25 tiller density predictions and GS-25 N application decisions based on a critical GS-25 tiller density threshold. The impact of different wheat varieties, soil colors, and weed populations were also evaluated through covariate analysis using 10 site-years of data. At three site-years, a randomized complete block design with three varieties and either two or three seeding rates was used. At these site-years, variety had a significant influence on spectral measurements. Seven additional site-years had a single variety and seeding rate. The NIR remote sensing technique was found to account for 76% of the variation between predicted and measured GS-25 tiller density across 10 site-years of data. Accurate GS-25 N application decisions were made 85.5% of the time by the NIR remote sensing technique across a wide range of environments including six soil types, six wheat varieties, and two systems.}, number={1}, journal={AGRONOMY JOURNAL}, author={Flowers, M and Weisz, R and Heiniger, R and Tarleton, B and Meijer, A}, year={2003}, pages={167–176} }
 @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} }
 @article{flowers_weisz_heiniger_2003, title={Quantitative approaches for using color infrared photography for assessing in-season nitrogen status in winter wheat}, volume={95}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2003.1189}, abstractNote={Due to the timing and rates of N applications in wheat (Triticum aestivum L.), the potential exists for high N loading to the environment. Plant tissue tests offer growers the ability to determine in‐season N status, and to optimize N applications and N use efficiency. However, sampling and N analysis can be costly, difficult, and time consuming. Remote sensing may offer a solution to these problems. The objectives of this study were to determine (i) if remote sensing could be used to estimate in‐season N status, (ii) if within‐field calibration would improve the ability of remote sensing to estimate crop N status, and (iii) if optimum N rates could be estimated using remote sensing. Research was conducted in 1999 to 2001 at eight sites. Two sites had randomized complete block designs with variety, seeding rate, and N rate as treatments. Six sites had a single seeding rate and wheat variety. Biomass was found to influence spectral measurements of in‐season N status. A strong relationship between the normalized difference vegetation index (NDVI) and growth stage (GS)‐30 whole‐plant N concentration (R2 = 0.69) and GS‐30 N uptake (R2 = 0.61) was found. Within‐field calibration did not improve the estimation of in‐season N status by NDVI. While it was possible to use NDVI to estimate GS‐30 N uptake, predicted N fertilizer rates based on N uptake were highly unreliable. However, NDVI reliably predicted GS‐30 N fertilizer rates based on whole‐plant N concentration for wheat that had mean GS‐30 biomass values >1000 kg ha−1}, number={5}, journal={AGRONOMY JOURNAL}, author={Flowers, M and Weisz, R and Heiniger, R}, year={2003}, pages={1189–1200} }
 @article{weisz_crozier_heiniger_2001, title={Optimizing nitrogen application timing in no-till soft red winter wheat}, volume={93}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2001.932435x}, abstractNote={As no‐till acreage increases, N management guidelines need re‐examination due to the potential effects of surface residue on N transformations and crop development. Our objectives were to determine: (i) if N applied at Zadok's Growth Stage (GS) 25 improves grain yield of no‐till winter wheat (Triticum aestivum L.), (ii) if any yield increase was the result of increased spring tillering, and (iii) if there is a critical tiller density above which N application at GS‐25 in no‐till wheat was not required. Research was conducted at three sites in North Carolina with seven site‐years between fall 1996 and spring 1999. A continuum of GS‐25 tiller densities was generated (161‐1774 tillers m−2) by planting at different seeding rates and dates in a randomized complete block design. Five N treatments were applied at GS‐25, and three were applied at GS‐30. Tillering response to early spring N, yield, and yield components were measured. increasing early spring N rates resulted in higher tiller densities at GS‐30, and GS‐25 tiller density was a significant covariate. With GS‐25 tiller densities >550 tillers m−2, yields were higher when all N was applied at GS‐30. In years without spring freezes, wheat with <550 tillers m−2 achieved optimum yields when spring N was applied at GS‐25. Manipulating the timing of spring N application can optimize early spring tillering and yield component formation.}, number={2}, journal={AGRONOMY JOURNAL}, author={Weisz, R and Crozier, CR and Heiniger, RW}, year={2001}, pages={435–442} }
 @article{flowers_weisz_heiniger_2001, title={Remote sensing of winter wheat tiller density for early nitrogen application decisions}, volume={93}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2001.934783x}, abstractNote={There is increasing evidence that scouting of winter wheat (Triticum aestivum L.) fields to determine tiller density at Growth Stage (GS) 25 is useful in deciding if N should be applied. However, to obtain an accurate average of field tiller density, frequent and intensive measurements must be made. A solution to this problem may be remote sensing. The objectives of this study were to determine (i) if a spectral index or digital counts in the near infrared (NIR), red (R), green (G), or blue (B) wavelengths could be used to estimate GS‐25 tiller density across environments and (ii) if the inclusion of within‐field references would improve the estimation of GS‐25 tiller density for determining N recommendations. Research was conducted at four site‐years in 1998 and 1999 using two wheat varieties. At three locations, a randomized replicated strip‐plot design with three seeding rates was used. The fourth location was an on‐farm test with one seeding rate. Spectral indices and individual NIR, R, G, and B digital counts were tested for correlation with tiller density at each site. Tiller density at GS 25 and NIR digital counts were found to be consistently correlated (0.67 ≤ r ≤ 0.87). The inclusion of within‐field tiller density references resulted in a high correlation (r = 0.88) between relative tiller density and relative NIR digital counts across environments. Using relative NIR digital counts to predict tiller density would have resulted in the correct N recommendation 82% of the time.}, number={4}, journal={AGRONOMY JOURNAL}, author={Flowers, M and Weisz, R and Heiniger, R}, year={2001}, pages={783–789} }
 @article{flowers_weisz_heiniger_2000, title={Aerial photographic determination of nitrogen application timing and rate recommendations in winter wheat}, 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={Flowers, M. and Weisz, R. and Heiniger, R.}, year={2000}, pages={1} }
 @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{weisz_bowman_1999, title={Influence of tillage system on soft red winter wheat cultivar selection}, volume={12}, ISSN={["0890-8524"]}, DOI={10.2134/jpa1999.0415}, abstractNote={Soft red winter wheat (Triticum aestivum L.) producers in the southeastern USA are adopting no-till production practices. Official wheat cultivar testing programs, however, are conducted in conventional-till. The objective of this research was to determine whether soft red winter wheat cultivars perform differently across tillage systems, indicating the need for no-till cultivar testing programs. Twelve winter wheat cultivars commonly produced in the southeastern USA were tested in a split-plot design with tillage system as the main effect. The test was located in the North Carolina Piedmont and Coastal Plain in 1996 and 1997. In the Piedmont the soil type was Hiwassee clay loam (fine, kaolinitic, thermic Typic Rhodudults), and in the Coastal Plain the soil was Goldsboro sandy loam (fineloamy, siliceous, subactive, Aquic Paleudults). Plant density after emergence, head density at harvest, kernel weight, grain yield, and test-weight were determined and compared across cultivars and tillage systems. For each of these variables, environment and cultivar effects were significant (P ≤ 0.05). Tillage system had a significant effect only on plant density with average no-till stands being 8.3 % lower than those in the conventional-till system. Relative cultivar performance, or rank, did not change across tillage systems for any of these variables. Consequently, soft red winter wheat cultivars that perform well in conventional-till will probably be the best adapted for no-till production. Separate cultivar trials are not required for the two tillage systems.}, number={3}, journal={JOURNAL OF PRODUCTION AGRICULTURE}, author={Weisz, R and Bowman, DT}, year={1999}, pages={415–418} }
 @article{fleischer_blom_weisz_1999, title={Sampling in precision IPM: When the objective is a map}, volume={89}, ISSN={["1943-7684"]}, DOI={10.1094/phyto.1999.89.11.1112}, abstractNote={ Measuring and understanding spatial variation of pests is a fundamental component of population dynamics. The resulting maps can drive spatially variable pest management, which we define as precision integrated pest management (IPM). Precision IPM has the potential to reduce insecticide use and slow the rate of resistance development because of the creation of temporally dynamic refuges. This approach to IPM requires sampling in which the objective is to measure spatial variation and map pest density or pressure. Interpolation of spatially referenced data is reviewed, and the influence of sampling design is suggested to be critical to the mapped visualization. Spatial sampling created problems with poor precision and small sample sizes that were partially alleviated with choosing sampling units based on their geostatistical properties, adopting global positioning system technology, and mapping local means. Mapping the probability of exceeding a threshold with indicator kriging is discussed as a decision-making tool for precision IPM. The different types of sampling patterns to deploy are discussed relative to the pest mapping objective. }, number={11}, journal={PHYTOPATHOLOGY}, author={Fleischer, SJ and Blom, PE and Weisz, R}, year={1999}, month={Nov}, pages={1112–1118} }
 @article{weisz_fleischer_smilowitz_1995, title={MAP GENERATION IN HIGH-VALUE HORTICULTURAL INTEGRATED PEST-MANAGEMENT - APPROPRIATE INTERPOLATION METHODS FOR SITE-SPECIFIC PEST-MANAGEMENT OF COLORADO POTATO BEETLE (COLEOPTERA, CHRYSOMELIDAE)}, volume={88}, ISSN={["0022-0493"]}, DOI={10.1093/jee/88.6.1650}, abstractNote={We describe a sampling program using sample units that might be feasible for mapping Colorado potato beetle, Leptinotarsa decemlineata (Say), densities for site-specific integrated pest management (IPM), an approach that varies the spatial placement of interventions in relation to the variation in pest density within a field. The influence of 5 interpolation methods (kriging, 4 inverse distance weighted functions, and thin plate spline with tension) on 3 estimators of the error associated with each interpolation method (the overall error sum of squares, the proportion of total variation explained by the interpolated map (R 2 ), and the categorization of cells relative to a threshold) were computed. When the threshold contour was overlaid onto surfaces, different interpolators suggested similar areas for treatment. The error sum of squares from kriging was generally smaller or equal to that achieved with other interpolators. The error sum of squares from inverse distance interpolators generally decreased with increasing weight in the exponent. With the higher exponents, the error sum of squares from inverse distance interpolators was as low as kriging and better than spline with tension. The R 2 increased with mean density for all interpolators. At threshold densities, R 2 values were 0.90 for adults and large larvae, and 0.75 for egg masses. All interpolators classified cells with respect to threshold density for all life stages with good to excellent accuracy (>85%). This research shows that kriging or simpler interpolators could be used for implementation of site-specific IPM.}, number={6}, journal={JOURNAL OF ECONOMIC ENTOMOLOGY}, author={WEISZ, R and FLEISCHER, S and SMILOWITZ, Z}, year={1995}, month={Dec}, pages={1650–1657} }