Gail A. Wicks

Winter Wheat Cultivar Characteristics Affect Annual Weed Suppression1

Thirteen hard red winter wheat cultivars were evaluated for their ability to suppress summer annual weeds in grain production systems near North Platte, NE, from 1993 through 1997. ‘Turkey’, a 125-yr-old landrace selection, suppressed both broadleaf and grass weeds more than other cultivars. Some relatively new cultivars, such as ‘Arapahoe’, ‘Jules’, ‘Pronghorn’, and ‘Vista’ suppressed summer annual grasses almost as well as Turkey. Total weed density was negatively correlated with number of winter wheat stems/m2, mature winter wheat height, and lodging. Weed density after wheat harvest was positively correlated with delay in winter wheat seeding date and was negatively correlated with precipitation 0 to 30 d after winter wheat seeding, during tillering, tillering to boot stage, and heading to maturity stage. Mean air temperature 0 to 30 d after wheat seeding was positively correlated with weed density. In the spring, weed density was positively correlated with temperatures during the tillering stage, tillering to boot stage, and heading to maturity stage. Stinkgrass and witchgrass densities were positively correlated with severity of wheat leaf rust. The highest grain-producing cultivars included three medium height cultivars ‘Alliance’, Arapahoe, and ‘Niobrara’. Alliance wheat produced 53% more grain than Turkey, and the other two produced 43% more grain. Nomenclature: Stinkgrass, Eragrostis cilianensis (All.) E. Mosher #3 ERACN; witchgrass, Panicum capillare L. # PANCA; winter wheat, Triticum aestivum L.; leaf rust, Puccinia recondita f. sp. tritici. Additional index words: AMAAL, AMARE, CHELR, competition, ECHCG, integrated weed management, KCHSC, lodging, POROL, precipitation, seeding date, SETVI, temperature, wheat stem density. Abbreviation: HRW, hard red winter.

Secale cereale interference and economic thresholds in winter Triticum aestivum

Abstract Secale cereale is a serious weed problem in winter Triticum aestivum–producing regions. The interference relationships and economic thresholds of S. cereale in winter T. aestivum in Colorado, Kansas, Nebraska, and Wyoming were determined over 4 yr. Winter T. aestivum density was held constant at recommended planting densities for each site. Target S. cereale densities were 0, 5, 10, 25, 50, or 100 plants m−2. Secale cereale–winter T. aestivum interference relationships across locations and years were determined using a negative hyperbolic yield loss function. Two parameters—I, which represents the percent yield loss as S. cereale density approaches zero, and A, the maximum percent yield loss as S. cereale density increases—were estimated for each data set using nonlinear regression. Parameter I was more stable among years within locations than among locations within years, whereas maximum percentage yield loss was more stable across locations and years. Environmental conditions appeared to have a role in the stability of these relationships. Parameter estimates for I and A were incorporated into a second model to determine economic thresholds. On average, threshold values were between 4 and 5 S. cereale plants m−2; however, the large variation in these threshold values signifies considerable risk in making economic weed management decisions based upon these values. Nomenclature: Secale cereale L. SECCE, rye; Triticum aestivum L., wheat.

Evaluation of models predicting winter wheat yield as a function of winter wheat and jointed goatgrass densities

Abstract Three models that empirically predict crop yield from crop and weed density were evaluated for their fit to 30 data sets from multistate, multiyear winter wheat–jointed goatgrass interference experiments. The purpose of the evaluation was to identify which model would generally perform best for the prediction of yield (damage function) in a bioeconomic model and which model would best fulfill criteria for hypothesis testing with limited amounts of data. Seven criteria were used to assess the fit of the models to the data. Overall, Model 2, provided the best statistical description of the data. Model 2, regressions were most often statistically significant, as indicated by approximate F tests, explained the largest proportion of total variation about the mean, gave the smallest residual sum of squares, and returned residuals with random distribution more often than Models 1, and 3,. Model 2, performed less well based on the remaining criteria. Model 3, outperformed Models 1, and 2, in the number of parameters estimated that were statistically significant. Model 1, outperformed Models 2, and 3, in the proportion of regressions that converged on a solution and more readily exhibited an asymptotic relationship between winter wheat yield and both winter wheat and jointed goatgrass density under the constraint of limited data. In contrast, Model 2, exhibited a relatively linear relationship between yield and crop density and little effect of increasing jointed goatgrass density on yield, thus overpredicting yield at high weed densities when data were scarce. Model 2, had statistical properties that made it superior for hypothesis testing; however, Model 1s properties were determined superior for the damage function in the winter wheat–jointed goatgrass bioeconomic model because it was less likely to cause bias in yield predictions based on data sets of minimum size. Nomenclature:Jointed goatgrass, Aegilops cylindrica Host. AEGCY; winter wheat, Triticum aestivum L.

Using Reflectance Sensors in Agronomy and Weed Science1

Weed-detecting reflectance sensors were modified to allow selective interrogation of the near infrared–red ratio to estimate differences in plant biomass. Sampling was programmed to correspond to the forward movement of the field of view of the sensors. There was a linear relationship (r2 > 0.80) between actual biomass and crop canopy analyzer (CCA) values up to 2,000 kg/ha for winter wheat sequentially thinned to create different amounts of biomass and up to 1,000 kg/ha for spring wheat sampled at different stages of development. At higher amounts of biomass the sensors underestimated the actual biomass. A linear relationship (r2 = 0.73) was obtained with the CCA for the biomass of 76 chickpea cultivars at 500 growing degree days (GDD500). The reflectance sensors were used to determine differences in the herbicide response of soybean cultivars sprayed with increasing rates of herbicides. The CCA data resulted in better dose–response relationships than did biomass data for bromoxynil at 0.8 kg ai/ha and glyphosate at 1.35 kg ai/ha. There was no phytotoxicity to soybean with imazethapyr at 1.44 kg ai/ha. The method offers a quick and nondestructive means to measure differences in early-season crop growth. It also has potential in selecting crop cultivars with greater seedling vigor, as an indicator of crop nutrient status, in plant disease assessment, in determining crop cultivar responses to increasing herbicide dose rates, in weed mapping, and in studying temporal changes in crop or weed biomass. Nomenclature: Bromoxynil; glyphosate; imazethapyr; chickpea, Cicer arietinum L.; soybean, Glycine max (L.) Merr.; wheat, Triticum aestivum L. Additional index words: Crop canopy analysis, crop growth, near infrared–red, weed detection. Abbreviations: CCA, crop canopy analyzer; DAP, days after planting; DAT, days after treatment; FOV, field of view; GDD, growing degree days; LAI, leaf area index; NDVI, normalized vegetation index; NIR, near infrared; R, red.

Effect of Planting Depth and Isoxaflutole Rate on Corn Injury in Nebraska

Field experiments were conducted at five sites in Nebraska in 2000 and 2001 to determine the effect of planting depth and isoxaflutole rate on the response of an isoxaflutole-sensitive corn hybrid, ‘Pioneer 33-G’ across variable environments. Corn was planted at depths of 2.5 and 5.0 cm, and isoxaflutole was applied PRE at the recommended (1×) and twice the recommended (2×) rate. The effects of planting depth and herbicide rate on injury varied considerably across site–years. When injury was evident, it was generally greater at the high rate of isoxaflutole (2×) and at the shallow planting depth (2.5 cm). In most site–years, corn recovered from early season injury, and yields were not reduced, except at Scottsbluff, NE, and North Platte, NE, where soils were lower in organic matter and higher in pH. Isoxaflutole rates should be carefully selected for soils with low organic matter and high pH. Nomenclature: Isoxaflutole, corn, Zea mays L

Survey of Winter Wheat (Triticum aestivum) Stubble Fields Sprayed with Herbicides in 1998: Cultural Practices1

A survey of 174 fields was conducted during August and September of 1998 to investigate effects of cultural and herbicide practices on postharvest weed control in winter wheat stubble fields across western and southern Nebraska. Seventy-four percent of the fields were seeded at rates of 67 to 100 kg/ha, with 60% of the wheat seeded in rows spaced 25 cm apart. Wheat seeded in east–west rows contained 98% more stinkgrass and 82% more tumble pigweed than wheat seeded in north–south rows. Sixty-nine percent of winter wheat stubble fields were rated excellent for weed control. Postharvest weed control with herbicides was not affected by row spacing. In western Nebraska, density of tumble pigweed and Russian thistle was greater when wheat seeding rate was 50 kg/ha than at higher seeding rates. Short-stature winter wheat cultivars had greater densities of Pennsylvania smartweed and toothed spurge than taller cultivars. The most common winter wheat cultivars were ‘Arapahoe’ (34%) and ‘Alliance’ (17%). Weed control was positively correlated with number of winter wheat stems per square meter (r = 0.22**). Density of several weed species was greater in fields seeded with a disk than with a hoe drill. The most common crop rotations sampled were winter wheat–corn–fallow (50%), winter wheat–fallow (18%), and winter wheat–corn–soybean (13%). Winter wheat yields and wheat stem densities were greater and weed density was less when winter wheat was seeded after an 11- to 14-mo fallow period rather than a 0- to 5-mo period. Nomenclature: Green foxtail, Setaria viridis (L.) Beauv. #3 SETVI; kochia, Kochia scoparia (L.) Schrad. # KCHSC; Pennsylvania smartweed, Polygoncum pensylvanicum P. # POLPY; Russian thistle, Salsola iberica Sennen & Pau # SASKR; stinkgrass, Eragrostis cilianensis (All.) E. Mosher # ERACN; toothed spurge, Euphorbia dentata Michx. # EPHDE; tumble pigweed, Amaranthus albus L. # AMAAL; corn, Zea mays L.; soybean, Glycine max (L.) Merr.; winter wheat, Triticum aestivum L. Additional index words: Atrazine, crop rotations, ecofallow, ecofarming, glyphosate, no-till, weed management. Abbreviations: W–C or Sor, winter wheat–corn or sorghum; W–C–F, winter wheat–corn–fallow; W–C–Soy, winter wheat–corn–soybean; W–C–Spgr, winter wheat–corn–spring grains; W–F, winter wheat–fallow; W–W, winter wheat–winter wheat.

Survey of Winter Wheat (Triticum aestivum) Stubble Fields Sprayed with Herbicides in 1998: Weed Control1

A survey of 174 fields was conducted to investigate performance of herbicides applied after winter wheat harvest on weeds across western and southern Nebraska during August and September 1998. Glyphosate plus 2,4-D plus atrazine was applied on 32%, glyphosate plus 2,4-D or dicamba on 24%, paraquat plus atrazine on 23%, glyphosate on 8%, ICIA0224 plus 2,4-D or atrazine on 10%, and atrazine plus 2,4-D on 3% of the fields. These treatments controlled 85 to 100% of the weeds except atrazine plus 2,4-D, which controlled 30%. The frequency of occurrence of the most prevalent summer annual grasses was as follows: green foxtail, 65%; barnyardgrass, 46%; stinkgrass, 41%; witchgrass, 39%; and longspine sandbur, 36%. The most common broadleaf weeds and their frequency were redroot pigweed, 32%; tumble pigweed, 30%; tall waterhemp, 28%; and kochia, 25%. Virginia groundcherry, 22%; common milkweed, 11%; yellow woodsorrel, 9%; and field bindweed, 6% were the most common perennial weeds. The five most difficult weeds to control were yellow nutsedge, spotted spurge, Virginia groundcherry, common milkweed, and toothed spurge, with control ratings of 0, 3, 17, 26, and 33%, respectively. These weeds were not controlled with glyphosate or mixtures containing glyphosate. Only 35% of the fields were treated before summer annual grasses had headed. Late applications required higher herbicides rates for effective control. Nomenclature: Atrazine; 2,4-D; dicamba; glyphosate; ICIA0224 (glyphosate trimethylsulfonium salt); paraquat; barnyardgrass, Echinochloa crus-galli (L.) Beauv. #3 ECHCG; common milkweed, Asclepias syriaca L. # ASCYS; field bindweed, Convolvulus arvensis L. # CONAR; green foxtail, Setaria viridis (L.) Beauv. # SETVI; kochia, Kochia scoparia (L.) Schrad # KCHSC; longspine sandbur, Cenchrus longispinus (Hack.) Fern. # CCHPA; redroot pigweed, Amaranthus retroflexus L. # AMARE; spotted spurge, Euphorbia maculata L. # EPHMA; stinkgrass, Eragrostis cilianensis (All.) E. Mosher # ERACN; tall waterhemp, Amaranthus tuberculatus (Moq.) J. D. Sauer # AMATA; toothed spurge, Euphorbia dentata Michx. # EPHDE; tumble pigweed, Amaranthus albus L. # AMAAL; Virginia groundcherry, Physalis virginiana Mill. # PHYLC; witchgrass, Panicum capillare L. # PANCA; yellow nutsedge, Cyperus esculentus L. # CYPES; yellow woodsorrel, Oxalis stricta L. # OXAST; winter wheat, Triticum aestivum L. Additional index words: AMAAL, AMARE, atrazine, conservation tillage, CYPES, 2,4-D, dicamba, ECHCG, ecofallow, ecofarming, ERACN, glyphosate, KCHSC, KSHSC, no-till, OXAST, PANCA, paraquat, SETVI, weed management.

Effect of Herbicides Applied in Winter Wheat (Triticum aestivum) Stubble on Weed Management in Corn (Zea mays)

Abstract: Field studies were conducted in 1992 and 1993 to evaluate weed control by 15 herbicide treatments in wheat stubble and in the succeeding corn crop. Atrazine at 2.24 kg ai/ha plus several herbicide treatments were applied about 13, 21, and 33 d following winter wheat harvest on separate plots in 1992 and 1993 in a soybean–winter wheat–corn rotation. Atrazine with and without 2,4-D isooctyl ester at 1.46 kg ae/ha or dicamba at 0.36 kg ae/ha did not control barnyardgrass, green foxtail, horseweed, kochia, stinkgrass, tumble thistle, or witchgrass in the wheat stubble 30 d after treatment. Atrazine mixtures containing glyphosate or paraquat with or without 2,4-D or dicamba controlled most summer annual weed species. Atrazine plus paraquat at 0.43 kg ai/ha was more effective on redroot pigweed and tumble thistle than atrazine plus glyphosate at 0.43 kg ae/ha plus 2,4-D at 0.95 kg ae/ha. Atrazine plus glyphosate mixtures were more effective on barnyardgrass for the first and second application date than atrazine plus paraquat. Increasing the glyphosate rate from 0.43 to 0.67 kg/ha was necessary to control barnyardgrass 95% at the first date. With the first date of application, kochia control was greater when 2,4-D or dicamba was added to the atrazine plus paraquat (0.43 kg/ha) mixture. Although annual grass control was generally greater when weeds approached maturity, early applications are a more sound weed control strategy because of soil water conservation and prevention of weed seed production. However, corn yields in 1993 were greater on plots treated at the third application in 1992 because weed biomass in corn was less. In 1994, corn yields were highest for the first application in 1993, probably because of better weed control in the corn. Above average rainfall in 1993 and 1994 aided corn yields. Nomenclature: 2,4-D; atrazine; dicamba; glyphosate; barnyardgrass, Echinochloa crus-galli (L.) Beauv. #3 ECHCG; green foxtail, Setaria viridis (L.) Beauv. # SETVI; horseweed, Conyza canadensis (L.) Cronq. # ERICA; kochia, Kochia scoparia (L.) Schrad. # KCHSC; redroot pigweed, Amaranthus retroflexus L. # AMARE; stinkgrass, Eragrostis cilianensis (All.) E. Mosher # ERACN; tumble thistle, Salsola collina Pall.; witchgrass, Panicum capillare L. # PANCA; corn, Zea mays L. # ZEAMX ‘Wilson 1640’; soybean, Glycine max L. Merr. GLYMA; winter wheat, Triticum aestivum L. # TRAES ‘Arapahoe’. Additional index words: Conservation tillage, ecofallow, no-tillage, triazine-resistant kochia. Abbreviations: DAT, days after treatment; NIS, nonionic surfactant; TR, triazine-resistant.