Environmental Variability Associated by Economic Thresholds for Soybeans

Weed Science ◽  
1991 ◽  
Vol 39 (4) ◽  
pp. 564-569 ◽  
Author(s):  
Troy A. Bauer ◽  
David A. Mortensen ◽  
Gaila Wicks ◽  
Thomas A. Hayden ◽  
Alex R. Martin
Keyword(s):  
Environmental Variability ◽  
Soybean Seed ◽  
Field Studies ◽  
Regression Equation ◽  
Significant Source ◽  
Yield Reduction ◽  
Crop Loss ◽  
Regression Equations ◽  
Weed Species ◽  
Weed Density

Field studies were conducted in 1986, 1987, 1988, and 1989 to determine the stability of crop loss functions across site by year environments. Environment was a significant source of variation for the soybean crop loss function as influenced by velvetleaf, but not as influenced by tall waterhemp and common sunflower. Weed density was a highly significant source of variation for all weed species studied. Regressions between percent soybean seed yield reductions and weed populations were linear. The velvetleaf interference regression equations were divided into two groups, those with high soybean-yielding intercepts and those with low-yielding intercepts, to explain the variance observed across environments. The regression equation for the high-yielding intercept group was Ŷ = 4.24X while the low-yielding group was Ŷ = 2.14X, where Y is percent soybean yield reduction and X is weed density per 10.7 m of soybean row. Tall waterhemp and common sunflower regression equations were determined to be Ŷ = 1.37X and Ŷ = 6.52X, respectively. Confidence intervals were used to account for the variance associated with the mean regression equation for each model and to develop economic threshold models that include risk aversion principles.

scholarly journals Perumusan Persepsi Kenyamanan Termis Pejalan Kaki di Iklim Tropis Lembab dan Membandingkan dengan Rumus untuk Iklim lainnya

2012 ◽  
Vol 26 (2) ◽  
pp. 146 ◽  
Author(s):  
S Sangkertadi ◽  
Reny Syafriny
Keyword(s):  
Thermal Comfort ◽  
Land Surface ◽  
Field Studies ◽  
Climatic Conditions ◽  
Regression Equation ◽  
Outdoor Thermal Comfort ◽  
Regression Equations ◽  
Humid Climate ◽  
Wide Range ◽  
Radiation Measurements

This article is about development a regression equation to determine the perception of thermal comfort for pedestrians in the humid tropical climate. Methods used was field studies and questionnaires to 60 samples as respondents in Manado. Each of the respondents was asked to act as pedestrian but walked on a treadmill for 2 minutes 5 five times. They regrouped into two parts, one who walked under open-sky and another group was under the shade of trees. Measurements of climate variables include air temperature, air humidity, radiation temperature, land surface temperature and solar radiation. Measurements to the respondents were their height, weight and skin temperature. By using statistical approach it is obtained a regression equation "Y=- 6.1369 + 0.479 Adu + 0.1143 Ta + 0.0376 Trm + 0.2541 RH + 1.6793 clo". The equation was then validated by comparison with other equations of non-tropical humid climate case. It is found that the empirical regression equations of outdoor thermal comfort developed by means of field studies in a certain climatic conditions could not be applied for a wide range of climate.

Cotton and Weed Response to Glyphosate Applied with Sulfur-Containing Additives

2004 ◽  
Vol 18 (2) ◽  
pp. 404-411 ◽  
Author(s):  
Wilson H. Faircloth ◽  
C. Dale Monks ◽  
Michael G. Patterson ◽  
Glenn R. Wehtje ◽  
Dennis P. Delaney ◽  
...  
Keyword(s):  
Field Studies ◽  
Effective Control ◽  
Yield Reduction ◽  
Mapping Data ◽  
Weed Species ◽  
Yellow Nutsedge ◽  
Treated Area ◽  
Diammonium Sulfate ◽  
Sulfur Containing ◽  
Radiotracer Techniques

Field studies were conducted to assess two sulfur-containing additives for use with glyphosate applied postemergence to glyphosate-resistant cotton for the control of sicklepod and yellow nutsedge. Neither diammonium sulfate (AMS) nor ammonium thiosulfate (ATS), both applied at 2.24 kg/ha, increased control of either species. Effective control of both species was dependent on glyphosate (isopropylamine salt) rate alone, with optimum control at 1.26 kg ae/ha. Plant-mapping data further indicated that sulfur-containing additives generally had no effect on either cotton fruiting patterns or yield. However, applying glyphosate at any rate did increase seed cotton yield in 2 of 3 yr vs. no glyphosate. In addition, applying glyphosate at any rate resulted in an increase in the number of bolls vs. no glyphosate in the following plant-mapping responses: total number of bolls per plant, number of abcised bolls per plant, bolls at the top five sympodial nodes, and bolls at positions 1 and 2 on the sympodia. Glyphosate absorption and subsequent translocation, as influenced by the addition of the sulfur-containing additives, was evaluated using radiotracer techniques. Glyphosate absorption after 48 h was 86, 63, and 37% of amount applied in cotton, sicklepod, and yellow nutsedge, respectively. Absorption by sicklepod and yellow nutsedge was not affected by the addition of either of the additives. Absorption by cotton was reduced by ATS but was not affected by AMS. In yellow nutsedge and cotton, glyphosate concentration in the treated area and adjacent tissue was not affected by either additive. A greater portion of glyphosate was translocated away from the treated area in sicklepod with glyphosate plus AMS (32%) than with glyphosate plus ATS (21%). AMS and ATS may be used in glyphosate-resistant cotton without the risk of either crop injury or yield reduction. However, their use for increased control of annual weed species, such as sicklepod and yellow nutsedge, may not be warranted.

Size-Dependent Economic Thresholds for Three Broadleaf Weed Species in Soybeans

1991 ◽  
Vol 5 (3) ◽  
pp. 674-679 ◽  
Author(s):  
Susan E. Weaver
Keyword(s):  
Leaf Area ◽  
Crop Yield ◽  
Soybean Seed ◽  
Yield Losses ◽  
Weed Species ◽  
Damage Functions ◽  
Area Index ◽  
Weed Density ◽  
Size Dependent ◽  
Economic Thresholds

Soybean seed yield losses due to interference from common cocklebur, velvetleaf, and jimsonweed, with and without a PPI application of 0.42 kg ai ha-1metribuzin, were determined in 1986, 1987, and 1988. Damage functions were calculated based on weed density, weed leaf density, and relative weed leaf area index, respectively. Functions relating crop yield losses to weed density varied significantly among treatments and years for each species. Weeds which escaped soil-applied metribuzin were shorter with fewer leaves at 3 wk after planting, and caused lower crop yield losses than control plants at equal densities. Yield loss estimates based upon relative weed leaf area at 3 wk after planting showed least variation between years and treatments.

scholarly journals Regression analysis to predict the impact of dietary neutral detergent fiber on carcass yield in swine1

2019 ◽  
Vol 3 (4) ◽  
pp. 1270-1274 ◽  
Author(s):  
Jose A Soto ◽  
Mike D Tokach ◽  
Steve S Dritz ◽  
Márcio A D Gonçalves ◽  
Jason C Woodworth ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Large Intestine ◽  
Negative Impact ◽  
Statistical Significance ◽  
Regression Equation ◽  
Neutral Detergent Fiber ◽  
Yield Reduction ◽  
Regression Equations ◽  
Carcass Yield ◽  
The Impact

Abstract Research has shown that carcass yield in swine is reduced when ingredients with high neutral detergent fiber (NDF) content. Carcass yield reduction from feeding high-fiber ingredients results from an increase in the weight of intestinal contents. NDF has been shown to result in the digestive contents to swell in the large intestine by absorbing water thus increasing the fecal volume in the large intestine. Considering the financial implications of changing carcass yield, the objective of this project was to develop a regression equation to estimate carcass yield from dietary NDF and strategies where high-NDF ingredients are taken out of the diet in the last dietary phases before slaughter (withdrawal period; WP). Data from 8 experiments (43 observations) originated from 6 journal articles and 1 technical memo were used to develop the regression equation. The WP of high NDF ingredients was either none or ranged from 5 to 63 d in the experiments. Treatment diets of each trial were reformulated to obtain dietary nutrient content using the NRC ingredient library (NRC, Nutrient requirements of swine. 11th ed, 2012). Composition of experimental diets was used to calculate dietary net energy, crude protein, crude fiber, NDF, and acid detergent fiber in the last two dietary phases. These dietary compositions along with the number of days of WP were used to develop regression equations. The model was determined using a step-wise selection procedure starting with guided forward selection through individual predictor variables, with a statistical significance at P < 0.05 used to determine inclusion of terms in the final model. The regression analysis showed that WP, NDF level in the dietary phase prior to the final phase (NDF1), NDF level in the last dietary phase before marketing (NDF2), and the interaction between NDF2 and WP were the most important variables in the dataset to predict carcass yield. The resulting regression equation was as follows: carcass yield, % = 0.03492 ± 0.02633 × WP (d) – 0.05092 ± 0.02862 × NDF1 (%) – 0.06897 ± 0.02931 × NDF2 (%) – 0.00289 ± 0.00216 × (NDF2 [%] × WP [d]) + 76.0769 ± 1.33730. In conclusion, high levels of NDF up to slaughter had a negative impact on carcass yield. Increasing the length of the WP improved carcass yield; however, the effect of WP was dependent on the level of NDF2. The equation herein provides a tool to estimate of the impact of dietary NDF on carcass yield.

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.

Soybean (Glycine max) Response to Weed Interference and Rhizoctonia Foliar Blight (Rhizoctonia solani)

Weed Science ◽  
1996 ◽  
Vol 44 (4) ◽  
pp. 842-846 ◽  
Author(s):  
B. David Black ◽  
James L. Griffin ◽  
John S. Russin ◽  
Johnnie P. Snow
Keyword(s):  
Rhizoctonia Solani ◽  
Growth Stage ◽  
Field Studies ◽  
Growth Stages ◽  
Weed Species ◽  
Weed Density ◽  
Weed Interference ◽  
Foliar Blight ◽  
Hemp Sesbania ◽  
Soybean Plants

Field studies evaluated response of soybean to Rhizoctonia foliar blight (RFB) disease in combination with varying densities of common cocklebur, hemp sesbania, or johnsongrass. Soybean plants at both V10 and R1 growth stages were not inoculated or inoculated with suspensions containing equal concentrations ofRhizoctonia solaniAG-1 IA and IB mycelia. Intensity of RFB was rated weekly beginning at V1 soybean growth stage, and data were used to determine area under disease progress curves. Intensity of RFB was greater in 1993 than in 1994. When averaged across weed species and weed densities, soybean yield in 1993 was reduced 18% in plots inoculated withR. solanicompared with those not inoculated. Intensity of RFB, however, did not differ between inoculated and noninoculated plots in 1994. Interactions betweenR. solaniand weed density for RFB intensity and yield were not significant either year. Soybean yields in 1994, however, were reduced by hemp sesbania and johnsongrass in inoculated plots. Soybean maturity was delayed both years when hemp sesbania was present.

Interference of Redstem Filaree (Erodium cicutarium) in Sugarbeet

Weed Science ◽  
2011 ◽  
Vol 59 (3) ◽  
pp. 310-313 ◽  
Author(s):  
Dennis C. Odero ◽  
Abdel O. Mesbah ◽  
Stephen D. Miller ◽  
Andrew R. Kniss
Keyword(s):  
Maximum Yield ◽  
Field Studies ◽  
Yield Reduction ◽  
Root Yield ◽  
Negative Effects ◽  
Rectangular Hyperbola ◽  
Weed Density ◽  
Erodium Cicutarium ◽  
Critical Timing ◽  
The Relationship

Redstem filaree is a troublesome weed for sugarbeet growers in northern Wyoming and southern Montana. Field studies were conducted in Powell, WY, in 2006 and 2008 to determine the influence of season-long interference of various redstem filaree densities and the duration of interference on sugarbeet. Root and sucrose yield decreased with increasing redstem filaree density. The rectangular hyperbola model with the asymptote (A) bounded at 100% maximum yield reduction characterized the relationship between redstem filaree density and sugarbeet yield reduction. The estimated parameterI(percent yield reduction per unit weed density as density approaches zero) was 5% for root and sucrose yield reduction. Sugarbeet root yield decreased as the duration of redstem filaree interference increased. The critical timing of redstem filaree removal to avoid 5 and 10% root yield reduction was estimated to be 25 and 32 d after sugarbeet emergence, respectively. Redstem filaree interference did not affect the sucrose content percentage. These results demonstrate that redstem filaree is competitive with sugarbeet and should be managed appropriately to reduce negative effects on yield.

Smooth Pigweed (Amaranthus hybridusL.) and Livid Amaranth (Amaranthus lividus) Interference with Cucumber (Cucumis sativus)

2006 ◽  
Vol 20 (1) ◽  
pp. 227-231 ◽  
Author(s):  
Adrian D. Berry ◽  
William M. Stall ◽  
B. Rathinasabapathi ◽  
Gregory E. Macdonald ◽  
R. Charudattan
Keyword(s):  
Dry Weight ◽  
Field Studies ◽  
Fruit Yield ◽  
Yield Reduction ◽  
Cucumber Plant ◽  
Weed Density ◽  
Weed Interference ◽  
Shoot Dry Weight ◽  
Cucumber Fruit ◽  
Smooth Pigweed

Field studies were conducted to determine the effect of season-long interference of smooth pigweed or livid amaranth on the shoot dry weight and fruit yield of cucumber. Smooth pigweed or livid amaranth densities as low as 1 to 2 weeds per m2caused a 10% yield reduction in cucumber. The biological threshold of smooth pigweed or livid amaranth with cucumber is between 6 to 8 weeds per m2. Consequently, weed interference resulted in a reduction in cucumber fruit yield. Smooth pigweed, livid amaranth, and cucumber plant dry weight decreased as weed density increased. Evaluation of smooth pigweed, livid amaranth, and cucumber mean dry weights in interspecific competition studies indicated that cucumber reduced the dry weight of both species of amaranths.

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.

Sign in / Sign up

Export Citation Format

Share Document