WeedSOFT: Effects of Corn-Row Spacing for Predicting Herbicide Efficacy on Selected Weed Species

2007 ◽  
Vol 21 (1) ◽  
pp. 219-224 ◽  
Author(s):  
Shawn M. Hock ◽  
Stevan Z. Knezevic ◽  
William G. Johnson ◽  
Christy Sprague ◽  
Alex R. Martin
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Yields ◽  
Field Studies ◽  
Yield Potential ◽  
Control Treatment ◽  
Grass Species ◽  
Yield Reduction ◽  
Weed Species ◽  
The North

The ability to accurately estimate herbicide efficacy is critical for any decision-support system used in weed management. Recent efforts by weed scientists in the North Central United States to adopt WeedSOFT across a broad region have resulted in a number of regional research projects designed to assess and improve the predictive capability of WeedSOFT. Field studies were conducted from 2000 to 2002 in Nebraska, Missouri, and Illinois to evaluate herbicide-efficacy predictions made by WeedSOFT in two corn-row spacings. Following crop and weed emergence, input variables, such as weed densities and heights, were entered into WeedSOFT to generate a list of treatments ranked by predicted crop yields. The five treatments evaluated included those predicting highest crop-yield potential (recommended control treatment 1), a 10% yield reduction, a 20% yield reduction, a 10% yield reduction plus cultivation, and cultivation alone. These treatments were applied to corn grown in 38- and 76-cm rows. Generally, treatments applied in 38-cm rows had more accurate herbicide-efficacy predictions compared with 76-cm rows. WeedSOFT provided better control predictions for broadleaf than grass species. WeedSOFT provided excellent herbicide-efficacy predictions for the highest crop-yield potential, which indicates a good potential for practical use of this software for herbicide recommendations.

Influence of Early-Season Yield Loss Predictions from WeedSOFT®and Soybean Row Spacing on Weed Seed Production from a Mixed-Weed Community

2004 ◽  
Vol 18 (2) ◽  
pp. 412-418 ◽  
Author(s):  
Andrew A. Schmidt ◽  
William G. Johnson
Keyword(s):  
Seed Production ◽  
Crop Yield ◽  
Weed Management ◽  
Yield Potential ◽  
Management Decision ◽  
Yield Reduction ◽  
Weed Seed ◽  
Weed Species ◽  
Early Season ◽  
Giant Foxtail

Seed production from weeds that are missed by herbicide application can affect future weed populations and management decisions. It may be possible to expand the utility of computerized weed management decision aids to include an estimate of weed seed production resulting from selected treatments based on crop yield potential. Field studies were conducted in soybean near Columbia, MO, to determine whether weed control recommendations based on crop yield potential from a computerized weed management decision aid influence weed seed production in two soybean row spacings. At approximately 28 d after planting, weed densities and heights were entered into WeedSOFT®to generate a list of treatments ranked by predicted crop yields. Treatments included: (1) highest predicted crop yield in a glyphosate-resistant system, (2) highest predicted crop yield in a nonglyphosate-resistant system, (3) a 10% yield reduction, (4) a 20% yield reduction, and (5) an untreated control. These treatments were applied to soybean grown in 38- and 76-cm rows. Treatments that provided 90% or higher control of an individual species at 22 d after treatment usually produced less seed than untreated checks. Weed seed production based on early-season herbicide efficacy showed a linear relationship and was relatively predictable (r2≥ 0.52) for the predominant weed species. For less dominant weed species, weed seed production was not strongly correlated (r2≤ 0.27) to early-season herbicide efficacy but apparently influenced by control of other weed species. Narrow row spacing reduced giant foxtail biomass both years but did not reduce common ragweed and ivyleaf morningglory biomass. Narrow rows did not decrease giant foxtail, common ragweed, and ivyleaf morningglory seed production.

Using Estimates of Weed Pressure to Establish Crop Yield Loss Equations

1994 ◽  
Vol 8 (1) ◽  
pp. 114-118 ◽  
Author(s):  
R. Gordon Harvey ◽  
Clark R. Wagner
Keyword(s):  
Linear Regression ◽  
Crop Yield ◽  
Yield Loss ◽  
Sweet Corn ◽  
Crop Yields ◽  
Yield Reduction ◽  
Weed Species ◽  
Field Corn ◽  
Efficacy Trials ◽  
Total Crop

Herbicide efficacy trials in field corn, sweet corn, and soybean were conducted at three locations in Wisconsin over a 6-yr period. Percent weed pressure (WP) was determined by visually estimating the contribution of all weed species present to the total crop and weed volume in each plot. Crop yields in each plot were measured. Percent crop yield reduction (YLDRED) was calculated by comparing mean yields of individual treatments with those of the highest yielding treatment in each trial. Linear regression analyses of YLDRED and WP data from 1640 field corn and 138 sweet corn treatments were significant. Nonlinear regression analysis of YLDRED and WP data from all 1374 soybean treatments was significant; however, a linear regression of those 1154 soybean treatments with WP ratings of 30 or less produced a more easily interpreted regression equation.

scholarly journals Modelling the Economics of Controlling Nodding Broomrape (Orobanche cernua) in Sunflower (Helianthus annuus)

Weed Science ◽  
1996 ◽  
Vol 44 (3) ◽  
pp. 591-595 ◽  
Author(s):  
L. García-Torres ◽  
M. Castejón-Muñoz ◽  
M. Jurado-Expósito ◽  
F. López-Granados
Keyword(s):  
Helianthus Annuus ◽  
Crop Yield ◽  
Treatment Cost ◽  
Yield Loss ◽  
Field Studies ◽  
Control Treatment ◽  
Yield Reduction ◽  
Economic Threshold ◽  
Economic Thresholds ◽  
Crop Yield Loss

Field studies were conducted at nine locations in southern Spain during 2 yr to develop models of nodding broomrape competition with sunflower and to establish economic thresholds. At each location, 30 to 35 small plots, each consisting of three sunflower plants, were chosen at random. The infection severity (BIS, no. of emerged broomrapes per sunflower plant) varied from 0 to 35. Plots were harvested at maturity to assess several sunflower and broomrape population variables. The percent sunflower yield reduction averaged over locations due to broomrape was estimated by the equation: % SYR = 1.7 x BIS (r2= 0.92). Crop yield loss per BIS unit increased with the expected yield and was estimated to be about 25, 50, and 75 kg ha−1for yields of 1000, 2000, and 3000 kg ha−1, respectively. A consistent relationship could be established between broomrape-infected sunflower yield, crop and broomrape biomass, and BIS parameters: SSYI= 0.2259 x PoBio/(1 + 0.0687 x BIS) (r2= 0.7820). The BIS economic threshold was about 1.5 and 3.5 for control treatment cost of $ 40 ha−1and potential yields of 2000 and 1000 kg ha−1, respectively.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

scholarly journals The Pitfalls of Relating Weeds, Herbicide Use, and Crop Yield: Don't Fall Into the Trap! A Critical Review

2020 ◽  
Vol 2 ◽  
Author(s):  
Nathalie Colbach ◽  
Sandrine Petit ◽  
Bruno Chauvel ◽  
Violaine Deytieux ◽  
Martin Lechenet ◽  
...  
Keyword(s):  
Crop Yield ◽  
Weed Management ◽  
Crop Production ◽  
Yield Loss ◽  
Crop Yields ◽  
Cropping Systems ◽  
Crop Productivity ◽  
Arable Farming ◽  
Herbicide Use ◽  
The Impact

The growing recognition of the environmental and health issues associated to pesticide use requires to investigate how to manage weeds with less or no herbicides in arable farming while maintaining crop productivity. The questions of weed harmfulness, herbicide efficacy, the effects of herbicide use on crop yields, and the effect of reducing herbicides on crop production have been addressed over the years but results and interpretations often appear contradictory. In this paper, we critically analyze studies that have focused on the herbicide use, weeds and crop yield nexus. We identified many inconsistencies in the published results and demonstrate that these often stem from differences in the methodologies used and in the choice of the conceptual model that links the three items. Our main findings are: (1) although our review confirms that herbicide reduction increases weed infestation if not compensated by other cultural techniques, there are many shortcomings in the different methods used to assess the impact of weeds on crop production; (2) Reducing herbicide use rarely results in increased crop yield loss due to weeds if farmers compensate low herbicide use by other efficient cultural practices; (3) There is a need for comprehensive studies describing the effect of cropping systems on crop production that explicitly include weeds and disentangle the impact of herbicides from the effect of other practices on weeds and on crop production. We propose a framework that presents all the links and feed-backs that must be considered when analyzing the herbicide-weed-crop yield nexus. We then provide a number of methodological recommendations for future studies. We conclude that, since weeds are causing yield loss, reduced herbicide use and maintained crop productivity necessarily requires a redesign of cropping systems. These new systems should include both agronomic and biodiversity-based levers acting in concert to deliver sustainable weed management.

scholarly journals Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 9-18 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Marcio Koiti Chiba ◽  
Célia Regina Grego
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spherical Model ◽  
Exponential Model ◽  
Spatial And Temporal Variability ◽  
No Tillage ◽  
Yield Data ◽  
The North ◽  
Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

Influence of Weed Management Practices and Crop Rotation on Glyphosate-Resistant Horseweed (Conyza canadensis) Population Dynamics and Crop Yield-Years III and IV

Weed Science ◽  
2009 ◽  
Vol 57 (4) ◽  
pp. 417-426 ◽  
Author(s):  
Vince M. Davis ◽  
Kevin D. Gibson ◽  
Thomas T. Bauman ◽  
Stephen C. Weller ◽  
William G. Johnson
Keyword(s):  
Population Dynamics ◽  
Crop Rotation ◽  
Crop Yield ◽  
Cover Crops ◽  
Weed Management ◽  
Management Practices ◽  
Plant Density ◽  
Crop Yields ◽  
Management Systems ◽  
No Till

Horseweed is an increasingly common and problematic weed in no-till soybean production in the eastern cornbelt due to the frequent occurrence of biotypes resistant to glyphosate. The objective of this study was to determine the influence of crop rotation, winter wheat cover crops (WWCC), residual non-glyphosate herbicides, and preplant application timing on the population dynamics of glyphosate-resistant (GR) horseweed and crop yield. A field study was conducted from 2003 to 2007 in a no-till field located at a site that contained a moderate infestation of GR horseweed (approximately 1 plant m−2). The experiment was a split-plot design with crop rotation (soybean–corn or soybean–soybean) as main plots and management systems as subplots. Management systems were evaluated by quantifying in-field horseweed plant density, seedbank density, and crop yield. Horseweed densities were collected at the time of postemergence applications, 1 mo after postemergence (MAP) applications, and at the time of crop harvest or 4 MAP. Viable seedbank densities were also evaluated from soil samples collected in the fall following seed rain. Soybean–corn crop rotation reduced in-field and seedbank horseweed densities vs. continuous soybean in the third and fourth yr of this experiment. Preplant herbicides applied in the spring were more effective at reducing horseweed plant densities than when applied in the previous fall. Spring-applied, residual herbicide systems were the most effective at reducing season-long in-field horseweed densities and protecting crop yields since the growth habit of horseweed in this region is primarily as a summer annual. Management systems also influenced the GR and glyphosate-susceptible (GS) biotype population structure after 4 yr of management. The most dramatic shift was from the initial GR : GS ratio of 3 : 1 to a ratio of 1 : 6 after 4 yr of residual preplant herbicide use followed by non-glyphosate postemergence herbicides.

Interference of Annual Sowthistle (Sonchus oleraceus) in Wheat

Weed Science ◽  
2019 ◽  
pp. 1-21 ◽  
Author(s):  
Sudheesh Manalil ◽  
Hafiz Haider Ali ◽  
Bhagirath Singh Chauhan
Keyword(s):  
Weed Management ◽  
Field Studies ◽  
Integrated Weed Management ◽  
Yield Reduction ◽  
Sonchus Oleraceus ◽  
Poor Seed ◽  
Exponential Decay Model ◽  
Weed Infestation ◽  
Varying Environments ◽  
Asteraceae Family

Abstract Annual sowthistle (Sonchus oleraceus L.) is a broadleaf weed that is increasing in prevalence in the northern cropping regions of Australia. Being a member of Asteraceae family, this weed possesses many biological attributes needed to thrive in varying environments and weed management pressure. Interference of this weed was examined in a wheat (Triticum aestivum L.) crop through field studies in 2016 and 2017. Different densities of S. oleraceus were evaluated for their potential to cause yield loss in wheat: 0.0 (weed free), low (9 to 15 plants m−2), medium (29 to 38 plants m−2), and high (62 to 63 plants m−2). Based on the exponential decay model, 43 and 52 plants m−2 caused a yield reduction of 50% in 2016 and 2017, respectively. Yield components such as panicles m−2 and grains per panicles were affected by weed density. At the high weed infestation level, S. oleraceus produced a maximum of 182,940 and 192,657 seeds m−2 in 2016 and 2017, respectively. Sonchus oleraceus exhibited poor seed retention at harvest as more than 95% of seeds were blown away by wind. Adverse effects on crop, high seed production and wind-blown dispersal may lead to an increased prevalence of this weed in the absence of an integrated weed management strategy utilizing both herbicides and non-chemical options.

scholarly journals Interactions of Nitrogen Source and Rate and Weed Removal Timing Relative to Nitrogen Content in Corn and Weeds and Corn Grain Yield

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Alexandra M. Knight ◽  
Wesley J. Everman ◽  
David L. Jordan ◽  
Ronnie W. Heiniger ◽  
T. Jot Smyth
Keyword(s):  
Grain Yield ◽  
Weed Management ◽  
Management Strategies ◽  
Field Studies ◽  
Weed Species ◽  
Weed Interference ◽  
Coated Urea ◽  
N Fertility ◽  
Corn Grain ◽  
Corn Grain Yield

Adequate fertility combined with effective weed management is important in maximizing corn (Zea mays L.) grain yield. Corn uptake of nitrogen (N) is dependent upon many factors including weed species and density and the rate and formulation of applied N fertilizer. Understanding interactions among corn, applied N, and weeds is important in developing management strategies. Field studies were conducted in North Carolina to compare corn and weed responses to urea ammonium nitrate (UAN), sulfur-coated urea (SCU), and composted poultry litter (CPL) when a mixture of Palmer amaranth (Amaranthus palmeri S. Wats.) and large crabgrass (Digitaria sanguinalis L.) was removed with herbicides at heights of 8 or 16 cm. These respective removal timings corresponded with 22 and 28 days after corn planting or V2 and V3 stages of growth, respectively. Differences in N content in above-ground biomass of corn were noted early in the season due to weed interference but did not translate into differences in corn grain yield. Interactions of N source and N rate were noted for corn grain yield but these factors did not interact with timing of weed control. These results underscore that timely implementation of control tactics regardless of N fertility management is important to protect corn grain yield.

scholarly journals Over-Optimistic Projected Future Wheat Yield Potential in the North China Plain: The Role of Future Climate Extremes

Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 145
Author(s):  
Rui Yang ◽  
Panhong Dai ◽  
Bin Wang ◽  
Tao Jin ◽  
Ke Liu ◽  
...  
Keyword(s):  
Drought Stress ◽  
North China Plain ◽  
North China ◽  
Crop Yields ◽  
Wheat Yield ◽  
Yield Potential ◽  
Severe Drought ◽  
The North ◽  
The North China Plain ◽  
Stress Environments

Global warming and altered precipitation patterns pose a serious threat to crop production in the North China Plain (NCP). Quantifying the frequency of adverse climate events (e.g., frost, heat and drought) under future climates and assessing how those climatic extreme events would affect yield are important to effectively inform and make science-based adaptation options for agriculture in a changing climate. In this study, we evaluated the effects of heat and frost stress during sensitive phenological stages at four representative sites in the NCP using the APSIM-wheat model. climate data included historical and future climates, the latter being informed by projections from 22 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) for the period 2031–2060 (2050s). Our results show that current projections of future wheat yield potential in the North China Plain may be overestimated; after more accurately accounting for the effects of frost and heat stress in the model, yield projections for 2031-60 decreased from 31% to 9%. Clustering of common drought-stress seasonal patterns into key groups revealed that moderate drought stress environments are likely to be alleviated in the future, although the frequency of severe drought-stress environments would remain similar (25%) to that occurring under the current climate. We highlight the importance of mechanistically accounting for temperature stress on crop physiology, enabling more robust projections of crop yields under future the burgeoning climate crisis.

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