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.

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.

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.

Alternatives to Atrazine for Weed Management in Processing Sweet Corn

Weed Science ◽  
2016 ◽  
Vol 64 (3) ◽  
pp. 531-539 ◽  
Author(s):  
Zubeyde Filiz Arslan ◽  
Martin M. Williams ◽  
Roger Becker ◽  
Vincent A. Fritz ◽  
R. Ed Peachey ◽  
...  
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Sweet Corn ◽  
Crop Yields ◽  
Production Systems ◽  
Field Trials ◽  
Management Systems ◽  
Weed Species ◽  
Application Timing ◽  
Production Areas

Atrazine has been the most widely used herbicide in North American processing sweet corn for decades; however, increased restrictions in recent years have reduced or eliminated atrazine use in certain production areas. The objective of this study was to identify the best stakeholder-derived weed management alternatives to atrazine in processing sweet corn. In field trials throughout the major production areas of processing sweet corn, including three states over 4 yr, 12 atrazine-free weed management treatments were compared to three standard atrazine-containing treatments and a weed-free check. Treatments varied with respect to herbicide mode of action, herbicide application timing, and interrow cultivation. All treatments included a PRE application of dimethenamid. No single weed species occurred across all sites; however, weeds observed in two or more sites included common lambsquarters, giant ragweed, morningglory species, velvetleaf, and wild-proso millet. Standard treatments containing both atrazine and mesotrione POST provided the most efficacious weed control among treatments and resulted in crop yields comparable to the weed-free check, thus demonstrating the value of atrazine in sweet corn production systems. Timely interrow cultivation in atrazine-free treatments did not consistently improve weed control. Only two atrazine-free treatments consistently resulted in weed control and crop yield comparable to standard treatments with atrazine POST: treatments with tembotrione POST either with or without interrow cultivation. Additional atrazine-free treatments with topramezone applied POST worked well in Oregon where small-seeded weed species were prevalent. This work demonstrates that certain atrazine-free weed management systems, based on input from the sweet corn growers and processors who would adopt this technology, are comparable in performance to standard atrazine-containing weed management systems.

Estimating yield losses in wheat resulting from infestation by doublegee (Emex australis)

1974 ◽  
Vol 14 (70) ◽  
pp. 656 ◽  
Author(s):  
DJ Gilbey
Keyword(s):  
Crop Yield ◽  
Field Trial ◽  
Yield Loss ◽  
Wheat Yield ◽  
Yield Reduction ◽  
Yield Losses ◽  
Seedling Mortality ◽  
Emex Australis ◽  
Percentage Yield

The effect of doublegee (Emex australis) density on wheat yield was studied in a field trial. Percentage yield reduction (y) was related to doublegee plants m-2 at 1 week (x1) and 8 weeks (x2) after seeding thus: y = 10.3 + 0.24 x1 r = 0.78*** y = 5.6 + 0.44 x2 r = 0.86*** showing that estimates of doublegee density could be used for forecasting crop yield losses before it is too late to spray. No further yield loss occurred when x1 was greater than 120 plants metre-2. Doublegee seedling mortality that occurred during the seven weeks between plant counts was strongly related to the initial counts (x1) thus: r = 0.88***.

scholarly journals Site and hybrid-specific agrotechnical models in sweet corn production

2011 ◽  
pp. 105-108
Author(s):  
Ádám Lente
Keyword(s):  
Crop Yield ◽  
Plant Density ◽  
Sweet Corn ◽  
Crop Yields ◽  
Density Level ◽  
Higher Plant ◽  
Sowing Time ◽  
Corn Production ◽  
High Plant Density ◽  
Crop Density

The effect of three agrotechnical factors (sowing time, fertilization, plant density) and two genotypes on the crop yield of sweet corn was examined on chernozem soil in the Hajdúság region in two different crop years. Compared to the 30-year average, the climate was dry and warm in 2009 and humid in 2010. The experiments were conducted at the Látókép Research Site of the University of Debrecen. In the experiments we applied two sowing times (end of April, end of May), six fertilization levels (control, N30+PK, N60+PK, N90+PK, N120+PK, N150+PK) and two crop density levels (45 thousand ha-1, 65 thousand ha-1). The hybrids we used were Jumbo and Enterprise. As regards the requirements of sweet corn production, the crop year of 2009 was dry and warm. The effect of moisture deficiency was more adverse on the crop yields with the second sowing time. On the contrary, the other examined year (2010) was significantly humid; the precipitation was 184 mm above the 30-year average and the temperature was average.In the dry and hot crop year, the best yields were obtained with the hybrid Jumbo (25677 kg-1) at 65 thousand ha-1 plant density level on the average of the fertilization levels. The crop yields of Enterprise were also the highest at high plant density level (24444 kg ha-1). With the second sowing time the highest yields were obtained at the higher plant density level (65 thousand ha-1) with both hybrids (Jumbo 18978 kg ha-1, Enterprise 18991 kg ha-1), which confirmed the good adaptation capability of these hybrids at high plant density level. In humid crop year with early sowing time the highest yielding hybrid was Enterprise (at 45 thousand ha-1 crop density level 20757 kg-1), at the same time, Jumbo was best yielding at the higher plant density level (18781 kg-1). With the second sowing time the highest crop yield was obtained with Enterprise again (20628 kg ha-1 at 65 thousand ha-1 plant density level). With this sowing time the average yields of Jumbo, was 18914 kg ha-1 respectively. We found that dry crop year and early sowing time provided the best conditions for sweet corn production; the highest yields were obtained under these circumstances, which might be the results of the outstanding water management of chernozem  soils.

Estimation of Crop Yield Loss Due to Interference by Multiple Weed Species

Weed Science ◽  
1994 ◽  
Vol 42 (1) ◽  
pp. 103-109 ◽  
Author(s):  
Scott M. Swinton ◽  
Douglas D. Buhler ◽  
Frank Forcella ◽  
Jeffrey L. Gunsolus ◽  
Robert P. King
Keyword(s):  
Crop Yield ◽  
Yield Loss ◽  
Yield Function ◽  
Data Sets ◽  
Species Competition ◽  
Coefficient Estimates ◽  
Weed Species ◽  
Common Lambsquarters ◽  
Competition Coefficient ◽  
Crop Yield Loss

Previous efforts to model crop yield loss from multiple weed species constructed competitive indices based on yield loss from individual weed species. Our model uses a multispecies modification of Cousens’ rectangular hyperbolic yield function to estimate a nonlinear competitive index for weed-crop interference. Results from 13 Minnesota and Wisconsin data sets provide measures of the relative competitiveness of mixed green and yellow foxtails, common lambsquarters, redroot pigweed, velvetleaf, and several other weed species. Competition coefficient estimates are stable over years, but not locations.

Traditional Tillage Systems as Drought Adaptation Strategies of Smallholder Farmers: The Case of Semi-Arid Central Tanzania

2009 ◽  
Vol 4 (2) ◽  
pp. 191-207 ◽  
Author(s):  
Riziki S. Shemdoe ◽  
Idris S. Kikula ◽  
Patrick Van Damme
Keyword(s):  
Soil Moisture ◽  
Soil Fertility ◽  
Crop Yield ◽  
Crop Yields ◽  
Smallholder Farmers ◽  
Positive Influence ◽  
Weed Species ◽  
Tillage Practices ◽  
No Till ◽  
Selection Of

This article presents local knowledge on ecosystem management by analyzing and discussing traditional tillage practices applied by smallholder farmers as a response to drought risks in dryland areas of Mpwapwa District, central Tanzania. Farming activities in the area wholly depend on rain-fed systems. Information from key informants and in-depth household interviews indicate that farmers in this area use three different traditional tillage practices—no-till (sesa), shallow tillage (kutifua), and ridges (matuta). Available information suggests that selection of a particular practice depends on affordability (in terms of costs and labor requirements), perceived ability to retain nutrient and soil-water, and improvement of control of erosion and crop yield. In this area, smallholder farmers perceive no-till practice to contribute to more weed species, hence more weeding time and labor are needed than in the other two practices. The no-till practice also contributes to low soil fertility, low soil moisture retention, and poor crop yield. No plans have been made to introduce irrigation farming in these marginal areas of central Tanzania. Thus, improving the ability of the tillage practices to conserve soil moisture and maintain soil fertility nutrients using locally available materials are important tasks to be carried out. This will ensure the selection of practices that will have positive influence on improved crop yields in the area.

Effect of DPX-V9360 and Terbufos on Field and Sweet Corn (Zea mays) Under Three Environments

1991 ◽  
Vol 5 (1) ◽  
pp. 130-136 ◽  
Author(s):  
Cathy A. Morton ◽  
R. Gordon Harvey ◽  
James J. Kells ◽  
William E. Lueschen ◽  
Vincent A. Fritz
Keyword(s):  
Zea Mays ◽  
Nonionic Surfactant ◽  
Sweet Corn ◽  
Field Studies ◽  
Application Rate ◽  
Yield Reduction ◽  
Crop Response ◽  
Field Corn ◽  
Significant Yield ◽  
Fertilizer Solution

Field studies were conducted in Michigan, Minnesota, and Wisconsin to explore interactions among DPX-V9360 herbicide applied postemergence, terbufos insecticide applied as an in-furrow treatment, and the environment. Field corn (‘Pioneer 3751’) and sweet corn (‘Jubilee’) were planted with and without an in-furrow application of terbufos. DPX-V9360 was applied postemergence when the corn was in the 4- to 6-leaf stage at 0, 35, 70, 140, and 280 g ai ha-1with nonionic surfactant and 28% N fertilizer solution. Crop response to DPX-V9360 was similar at all three locations, varying only in magnitude of injury. Crop injury was greater with Jubilee sweet corn than with Pioneer 3751 field corn. Injury to both hybrids increased as DPX-V9360 application rate increased. Application of terbufos increased injury from DPX-V9360 to both hybrids. Significant yield reduction did not occur with either hybrid when DPX-V9360 was applied at rates of 140 g ha-1or less and no terbufos was applied.

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.

scholarly journals Establishment of Vegetables in the Field

1991 ◽  
Vol 1 (1) ◽  
pp. 78-81 ◽  
Author(s):  
M.D. Orzolek
Keyword(s):  
Environmental Stress ◽  
Crop Yield ◽  
Crop Production ◽  
Abiotic Factors ◽  
Yield Reduction ◽  
Biotic Factors ◽  
Plant Populations ◽  
Stand Establishment ◽  
Physical Conditions ◽  
Total Crop

Optimization of crop production can be accomplished only if successful stand establishment is achieved first, since each plant contributes to the total crop yield. Reduction of plant populations after planting will reduce yield and/or quality, even though plants compensate to some degree for stand losses. Successful stand establishment is achieved if factors that affect establishment are known, evaluated, and modified appropriately at the time of field planting. The factors that affect stand establishment are biotic and/or abiotic. Biotic factors are generally pathogens that attack plants as parasites, while abiotic factors are the environmental and physical conditions to which the plant or seed is exposed at the time of planting. Abiotic factors can be classified under three headings: soil, planting requirements, and environmental stress.

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