scholarly journals Soybean row spacing and weed emergence time influence weed competitiveness and competitive indices

Weed Science ◽  
2006 ◽  
Vol 54 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Shawn M. Hock ◽  
Stevan Z. Knezevic ◽  
Alex R. Martin ◽  
John L. Lindquist
Keyword(s):  
Yield Loss ◽  
Variable Parameter ◽  
Field Studies ◽  
Row Spacing ◽  
Emergence Time ◽  
Weed Species ◽  
Trifoliate Leaf ◽  
Soybean Yield ◽  
Broadleaf Species ◽  
Weed Emergence

Weed competitiveness can be quantified with the concept of competitive index (CI), a relative scale of weed competitiveness. Field studies were conducted in 2002 and 2003 in northeastern and southeastern Nebraska to evaluate the influence of soybean row spacing and relative weed emergence time on the competitiveness of major weed species in soybean. Ten weed species were seeded in soybean spaced 19 and 76 cm apart at the planting, emergence, and first trifoliate leaf stages of soybean. Total weed dry matter (TDM), weed plant volume, and percent soybean yield loss were arbitrarily selected as a base for determining the CI for each weed species. Soybean yield loss was the least variable parameter used to quantify weed competitiveness and rank their CIs. In general, weeds grown with soybean planted in 19-cm rows produced less TDM, plant volume, and reduced soybean yield less than weed species grown in 76-cm rows. Later-emerging weeds produced less TDM, plant volume, and reduced soybean yield less than the early-emerging ones. In general, broadleaf species were more competitive than grass weed species. Common sunflower was the most competitive weed species in this study.

scholarly journals Performance of WeedSOFT for Predicting Soybean Yield Loss

2006 ◽  
Vol 20 (2) ◽  
pp. 478-484 ◽  
Author(s):  
Shawn M. Hock ◽  
Stevan Z. Knezevic ◽  
Alex R. Martin ◽  
John L. Lindquist
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Dry Matter ◽  
Yield Loss ◽  
The United States ◽  
Weed Species ◽  
Trifoliate Leaf ◽  
Soybean Yield ◽  
Weed Emergence ◽  
Crop Yield Loss

Decision support systems (DSSs) have been developed to assist producers and consultants with weed management decisions. WeedSOFT is a DSS currently used in several states in the north-central region of the United States. Accurate estimates of crop yield loss due to weed interference are required for cost-effective weed management recommendations. WeedSOFT uses competitive indices (CIs) to predict crop yield loss under multiple weed species, weed densities, and relative times of weed emergence. Performance of several WeedSOFT versions to predict soybean yield loss from weed competition was evaluated using CI values in WeedSOFT version 9.0 compared to new CI values calculated from weed dry matter, weed volume, and soybean yield loss in two soybean row spacings (19 and 76 cm) and two relative weed emergence times (at soybean emergence and first trifoliate leaf stage). Overall, new CI values improved predictions of soybean yield loss by as high as 63%. It was especially true with using new CI values based on yield loss compared to those based on weed dry matter or weed volume. However, there were inconsistencies in predictions for most weed species, suggesting that additional modifications are needed to further improve soybean yield loss predictions.

Interference between pigweed (Amaranthusspp.), barnyardgrass(Echinochloa crus-galli), and soybean (Glycine max)

Weed Science ◽  
1998 ◽  
Vol 46 (5) ◽  
pp. 533-539 ◽  
Author(s):  
Paul Cowan ◽  
Susan E. Weaver ◽  
Clarence J. Swanton
Keyword(s):  
Competitive Ability ◽  
Field Experiments ◽  
Yield Loss ◽  
Seedling Emergence ◽  
Growth Time ◽  
Weed Species ◽  
Soybean Yield ◽  
Competitive Index ◽  
Loss Maximum ◽  
Weed Emergence

Field experiments were conducted to determine the influence of time of emergence and density of single and multispecies populations of pigweed and barnyardgrass on soybean yield and competitive abilities of pigweed and barnyardgrass. Pigweed and barnyardgrass were established at selected densities within 12.5 cm on either side of the soybean row. Pigweed and barnyardgrass seeds were sown concurrently with soybean and at the cotyledon stage of soybean growth. Time and density of pigweed and barnyardgrass seedling emergence relative to soybean influenced the magnitude of soybean yield loss. Maximum soybean yield loss ranged from 32 to 99%, depending upon time of emergence relative to soybean. Pigweed was more competitive than barnyardgrass across all locations, years, and time of weed emergence. When pigweed was assigned a competitive index of 1 on a scale from 0 to 1, the competitive ability of barnyardgrass ranged from 0.075 to 0.40 of pigweed, depending upon location and time of emergence. This is the first multiple weed species study to include time of weed emergence relative to the crop. Competitive index values for multiple weed species must be calculated from field experiments in which weeds are grown with the crop under differing environmental conditions.

Predicted Soybean Yield Loss As Affected by Emergence Time of Mixed-Species Weed Communities

Weed Science ◽  
2011 ◽  
Vol 59 (3) ◽  
pp. 416-423 ◽  
Author(s):  
Mark R. Jeschke ◽  
David E. Stoltenberg ◽  
George O. Kegode ◽  
Christy L. Sprague ◽  
Stevan Z. Knezevic ◽  
...  
Keyword(s):  
Decision Support ◽  
Weed Management ◽  
Yield Loss ◽  
Management Decision ◽  
Emergence Time ◽  
Mixed Species ◽  
Soybean Yield ◽  
Weed Communities ◽  
Weed Emergence ◽  
Management Decision Support

Potential crop yield loss due to early-season weed competition is an important risk associated with postemergence weed management programs. WeedSOFT is a weed management decision support system that has the potential to greatly reduce such risk. Previous research has shown that weed emergence time can greatly affect the accuracy of corn yield loss predictions by WeedSOFT, but our understanding of its predictive accuracy for soybean yield loss as affected by weed emergence time is limited. We conducted experiments at several sites across the Midwestern United States to assess accuracy of WeedSOFT predictions of soybean yield loss associated with mixed-species weed communities established at emergence (VE), cotyledon (VC), first-node (V1), or third-node (V3) soybean. Weed communities across research sites consisted mostly of annual grass species and moderately competitive annual broadleaf species. Soybean yield loss occurred in seven of nine site-years for weed communities established at VE soybean, four site-years for weed communities established at VC soybean, and one site-year for weed communities established at V1 soybean. No soybean yield loss was associated with weed communities established at the V3 stage. Nonlinear regression analyses of predicted and observed soybean yield data pooled over site-years showed that predicted yields were less than observed yields at all soybean growth stages, indicating overestimation of soybean yield loss. Pearson correlation analyses indicated that yield loss functions overestimated the competitive ability of high densities of giant and yellow foxtail with soybean, indicating that adjustments to competitive index values or yield loss function parameters for these species may improve soybean yield loss prediction accuracy and increase the usefulness of WeedSOFT as a weed management decision support system.

Row Spacing and Seeding Rate Effects on Eastern Black Nightshade (Solanum Ptycanthum) and Soybean

2007 ◽  
Vol 21 (1) ◽  
pp. 124-130 ◽  
Author(s):  
Adrienne M. Rich ◽  
Karen A. Renner
Keyword(s):  
Dry Weight ◽  
Field Studies ◽  
Production Costs ◽  
Row Spacing ◽  
Seeding Rate ◽  
Soybean Yield ◽  
Eastern Black Nightshade ◽  
Solanum Ptycanthum ◽  
Black Nightshade ◽  
Rate Effects

Reducing seeding rates in 19- or 76-cm row soybean below the optimum rate may reduce soybean competitiveness with weeds, and indirectly increase production costs to the grower. Field studies in 2001 and 2002 evaluated the effect of soybean seeding rate and row spacing on the emergence, growth, and competitiveness of eastern black nightshade (EBN) in soybean. EBN emergence ceased within 45 d after planting (DAP), and was similar across soybean seeding rates and row spacing. EBN control by glyphosate was not affected by soybean population or row spacing. Soybean planted in 19-cm rows was more competitive with EBN, regardless of seeding rate. Increasing the soybean seeding rate in 76-cm rows from 185,000 seeds/ha to 432,000 seeds/ha reduced EBN dry weight threefold at East Lansing and nearly twofold at Clarksville in 2002. There was no increase in EBN density or dry weight in 19-cm row soybean planted at 308,000 seeds/ha compared with 556,000 seeds/ha, whereas a seeding rate of 432,000 seeds/ha in 76-cm row soybean did not suppress EBN dry weight or increase soybean yield in the presence of EBN compared with a seeding rate of 308,000 seeds/ha.

Interference between hemp sesbania (Sesbania exaltata) and soybean (Glycine max) in response to irrigation and nitrogen

Weed Science ◽  
1997 ◽  
Vol 45 (1) ◽  
pp. 91-97 ◽  
Author(s):  
C. Andy King ◽  
Larry C. Purcell
Keyword(s):  
Field Experiments ◽  
Yield Loss ◽  
Individual Species ◽  
Weed Species ◽  
Soybean Yield ◽  
Sesbania Exaltata ◽  
Competition For Light ◽  
Hemp Sesbania ◽  
Chamber Studies ◽  
Growth Chamber Studies

Soybean yield loss from weed interference depends upon weed density and competitiveness of crop and weed species in response to environment. Soil water availability and nitrogen fertility were evaluated for their effect on competitiveness of individual species in field experiments. Early-season temperatures in 1995, which were cool compared to 1994, slowed hemp sesbania growth without affecting soybean growth. This resulted in negligible competition with soybean by hemp sesbania at densities of 3 or 6 plants m−2. In 1994, hemp sesbania grew above the soybean canopy, decreasing soybean light interception 29 to 68%, and reducing soybean yield 30 to 48%. Fertilizer nitrogen increased soybean competitiveness, as indicated by biomass production, only in irrigated plots with hemp sesbania at 3 m−2, but did not affect soybean yield. Apparently, competition for light is a primary cause of soybean yield loss from hemp sesbania infestations. In growth chamber studies, simulating temperatures from the field, hemp sesbania growth was stimulated more by warm temperatures than was soybean. Hemp sesbania and soybean dry weights increased 4.4- and 2.7-fold, respectively, at 30/20 C day/night temperatures compared to 25/15 C.

Glyphosate and Paraquat Effects on Weed Seed Germination and Seedling Emergence

Weed Science ◽  
1978 ◽  
Vol 26 (3) ◽  
pp. 249-251 ◽  
Author(s):  
G. H. Egley ◽  
R. D. Williams
Keyword(s):  
Seedling Emergence ◽  
Soil Surface ◽  
Amaranthus Retroflexus ◽  
Sorghum Halepense ◽  
Weed Species ◽  
Sida Spinosa ◽  
Broadleaf Species ◽  
Prickly Sida ◽  
Grass Weed ◽  
Weed Emergence

Glyphosate [N-(phosphonomethyl)glycine] (30, 125, 250 mg/L) in petri dishes had no effect on germination of prickly sida(Sida spinosaL.), velvetleaf(Abutilon theophrastiMedic), barnyardgrass [Echinocloa crus-galli(L.) Beauv.] and johnsongrass [Sorghum halepense(L.) Pers.] seeds, but additional experimentation indicated that glyphosate stimulated germination of redroot pigweed(Amaranthus retroflexusL.) seeds. Paraquat (1,1′-dimethyl-4,4′-bipyridinium ion) (30, 125, 250 mg/L) did not affect germination of the three broadleaf species, but inhibited johnsongrass and barnyardgrass germination. In the greenhouse, soil surface applications of glyphosate (1.1, 2.2, 9.0 kg/ha) did not significantly affect emergence of these five weed species when they were on or beneath the soil surface at time of treatment. Paraquat (same rates) did not affect broadleaf weed emergence but some rates inhibited grass weed emergence when the seeds were treated while on the soil surface. It is unlikely that normal field use rates of glyphosate will influence weed emergence; whereas paraquat may inhibit the emergence of some grass weeds if the herbicide contacts seeds on the soil surface.

Field evaluation of soybean (Glycine max) genotypes for weed competitiveness

Weed Science ◽  
1997 ◽  
Vol 45 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Alvin J. Bussan ◽  
Orvin C. Burnside ◽  
James H. Orf ◽  
Eric A. Ristau ◽  
Klaus J. Puettmann
Keyword(s):  
Soybean Seed ◽  
Field Evaluation ◽  
Field Studies ◽  
Weed Species ◽  
Weed Biomass ◽  
Soybean Yield ◽  
Canopy Area ◽  
Soybean Genotypes ◽  
High Yields ◽  
Grass Weed

In the first of 2 field studies, weed biomass and soybean seed yield were used to evaluate 16 soybean genotypes for competitive ability against 12 weed species at Rosemount, MN, in 1992 and 1993. The yield and ranking of soybean genotypes often varied with the weed species. Grass weed species reduced yields the most, and small-seeded broadleaf weeds reduced yields the least across years. ‘Parker’ was highly competitive, as it suppressed weed biomass and produced high soybean yield. ‘Kato,’ ‘Kasota,’ ‘Dawson,’ and ‘Glenwood’ minimized weed biomass and maintained soybean yield while in competition with grass weeds but yielded poorly relative to other soybean genotypes in weed-free conditions. ‘Lambert’ produced high soybean yield in weed-free conditions, but yield dropped markedly when in competition with grass weeds. ‘Grande,’ ‘Heifeng 25,’ and ‘Norman’ soybeans were poor competitive genotypes in weedy situations and low yielding in weed-free conditions. A 2nd field study conducted at Rosemount and St. Paul, MN, during 1993 evaluated 16 soybean genotypes under 4 levels and durations of weed pressure for weed competitiveness. Parker, ‘Sturdy,’ and M89-794 were most competitive in suppressing weed biomass and producing high yields. Lambert yielded fairly well but allowed high weed biomass. M89-1743, M89-1006, ‘Archer,’ and ‘Ozzie’ yielded poorly and did not sup press weed biomass production. No relationship was found between weed competitiveness and soybean canopy area, height, and volume measured 30–45 d after planting (DAP).

Large crabgrass (Digitaria sanguinalis) and Palmer amaranth (Amaranthus palmeri) intraspecific and interspecific interference in soybean

Weed Science ◽  
2019 ◽  
Vol 67 (6) ◽  
pp. 649-656 ◽  
Author(s):  
Nicholas T. Basinger ◽  
Katherine M. Jennings ◽  
David W. Monks ◽  
David L. Jordan ◽  
Wesley J. Everman ◽  
...  
Keyword(s):  
Yield Loss ◽  
Maximum Yield ◽  
Field Studies ◽  
Palmer Amaranth ◽  
Amaranthus Palmeri ◽  
Weed Species ◽  
Digitaria Sanguinalis ◽  
Weed Density ◽  
Loss Estimate ◽  
Large Crabgrass

AbstractField studies were conducted in 2016 and 2017 at Clinton, NC, to quantify the effects of season-long interference of large crabgrass [Digitaria sanguinalis (L.) Scop.] and Palmer amaranth (Amaranthus palmeri S. Watson) on ‘AG6536’ soybean [Glycine max (L.) Merr.]. Weed density treatments consisted of 0, 1, 2, 4, and 8 plants m−2 for A. palmeri and 0, 1, 2, 4, and 16 plants m−2 for D. sanguinalis with (interspecific interference) and without (intraspecific interference) soybean to determine the impacts on weed biomass, soybean biomass, and seed yield. Biomass per square meter increased with increasing weed density for both weed species with and without soybean present. Biomass per square meter of D. sanguinalis was 617% and 37% greater when grown without soybean than with soybean, for 1 and 16 plants m−2 respectively. Biomass per square meter of A. palmeri was 272% and 115% greater when grown without soybean than with soybean for 1 and 8 plants m−2, respectively. Biomass per plant for D. sanguinalis and A. palmeri grown without soybean was greatest at the 1 plant m−2 density. Biomass per plant of D. sanguinalis plants across measured densities was 33% to 83% greater when grown without soybean compared with biomass per plant when soybean was present for 1 and 16 plants m−2, respectively. Similarly, biomass per plant for A. palmeri was 56% to 74% greater when grown without soybean for 1 and 8 plants m−2, respectively. Biomass per plant of either weed species was not affected by weed density when grown with soybean due to interspecific competition with soybean. Yield loss for soybean grown with A. palmeri ranged from 14% to 37% for densities of 1 to 8 plants m−2, respectively, with a maximum yield loss estimate of 49%. Similarly, predicted loss for soybean grown with D. sanguinalis was 0 % to 37% for densities of 1 to 16 m−2 with a maximum yield loss estimate of 50%. Soybean biomass was not affected by weed species or density. Results from these studies indicate that A. palmeri is more competitive than D. sanguinalis at lower densities, but that similar yield loss can occur when densities greater than 4 plants m−2 of either weed are present.

Interaction of Linuron and Row Spacing for Control of Yellow Foxtail and Barnyardgrass in Soybeans

Weed Science ◽  
1969 ◽  
Vol 17 (4) ◽  
pp. 489-491 ◽  
Author(s):  
Cyril A. Kust ◽  
R. R. Smith
Keyword(s):  
Weed Control ◽  
Comparative Effectiveness ◽  
Field Studies ◽  
Row Spacing ◽  
Weed Species ◽  
University Of Wisconsin ◽  
Row Width ◽  
Setaria Glauca ◽  
Soybean Leaves ◽  
The University

Field studies were conducted during 1967 and 1968 at the University of Wisconsin Experimental Farm, Arlington, Wisconsin, to determine the comparative effectiveness of combinations of row spacings and rates of 3-(3,4-dichlorophenyl)-1-methoxy-1-methylurea (linuron) for control of yellow foxtail (Setaria glauca(L.) Beauv.) and barnyardgrass (Echinochloa crusgalli(L.) Beauv.) in soybeans (Glycine max(L.) Merr.). Soybean yields and weed control increased as row spacing decreased. Lower rates of linuron were required for comparable weed control as row spacing decreased. Yield increases with decreasing row width were much greater in 1968 than in 1967, probably because of better rainfall during July, August, and early September in 1968. Improved weed control in the narrow rows may have been due partially to absorption by soybean leaves of light wavelengths that may be most favorable for photosynthesis and vegetative growth of some weed species.

Interference of large crabgrass (Digitaria sanguinalis), redroot pigweed (Amaranthus retroflexus), and hairy galinsoga (Galinsoga ciliata) with bell pepper

Weed Science ◽  
2006 ◽  
Vol 54 (02) ◽  
pp. 364-372 ◽  
Author(s):  
Rongwei Fu ◽  
Richard A. Ashley
Keyword(s):  
Hyperbolic Equation ◽  
Competitive Ability ◽  
Yield Loss ◽  
Maximum Yield ◽  
Bell Pepper ◽  
Nonlinear Hyperbolic Equation ◽  
Emergence Time ◽  
Weed Species ◽  
Redroot Pigweed ◽  
Large Crabgrass

Large crabgrass, redroot pigweed, and hairy galinsoga are three important weed species in bell pepper and other crops in the northeastern United States. Field experiments were conducted in 1998 and 1999 to determine the influence of density and relative emergence time of the three weed species on bell pepper fruit yield. Densities of 0, 1, 2, 4, 8, 16, and 32 plants m−1row were established for each weed species from naturally occurring weed populations. The effects of relative emergence time were studied by investigating the different yield responses to weeds emerging at two different times: 3 d or 2 wk after transplanting of pepper. Both weed density and relative emergence time affected pepper yield loss. The relative competitive ability of weed species varied between years. Large crabgrass was the most competitive species in 1998 and the measure of yield loss at low weed densities,I, was estimated to be 34% on the basis of the nonlinear hyperbolic equation. Redroot pigweed was most competitive in 1999 with an estimate of 88% forI.Hairy galinsoga was the least competitive weed in both years. Maximum yield loss under 32 plants m−1row ranged from 19% with late-emerging hairy galinsoga in 1998 to 99% with early-emerging redroot pigweed in 1999. A new equation was proposed to characterize the relation between yield loss and weed pressure by expanding the nonlinear hyperbolic equation to include a parameter to account for the change of maximum yield loss with emergence time. The expanded equation generally provided a more accurate prediction of yield loss. In addition, several models are introduced to describe both the effects of density and relative emergence time of multiple weed species on crop yield. Generally these models provided an adequate fit of the data and a good description of the competitive ability of the mixed population.

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