Evaluation of optimal droplet size for control of Palmer amaranth (Amaranthus palmeri) with acifluorfen

2020 ◽  
Vol 34 (4) ◽  
pp. 511-519
Author(s):  
Lucas X. Franca ◽  
Darrin M. Dodds ◽  
Thomas R. Butts ◽  
Greg R. Kruger ◽  
Daniel B. Reynolds ◽  
...  
Keyword(s):  
Weed Control ◽  
Droplet Size ◽  
Prediction Models ◽  
Additive Model ◽  
Plant Morphology ◽  
Palmer Amaranth ◽  
Future Research ◽  
Geographical Differences ◽  
Spray Droplet ◽  
Drift Field

AbstractAcifluorfen is a nonsystemic PPO-inhibiting herbicide commonly used for POST Palmer amaranth control in soybean, peanut, and rice across the southern United States. Concerns have been raised regarding herbicide selection pressure and particle drift, increasing the need for application practices that optimize herbicide efficacy while mitigating spray drift. Field research was conducted in 2016, 2017, and 2018 in Mississippi and Nebraska to evaluate the influence of a range of spray droplet sizes [150 μm (Fine) to 900 μm (Ultra Coarse)], using acifluorfen to create a novel Palmer amaranth management recommendation using pulse width modulation (PWM) technology. A pooled site-year generalized additive model (GAM) analysis suggested that 150-μm (Fine) droplets should be used to obtain the greatest Palmer amaranth control and dry biomass reduction. Nevertheless, GAM models indicated that only 7.2% of the variability observed in Palmer amaranth control was due to differences in spray droplet size. Therefore, location-specific GAM analyses were performed to account for geographical differences to increase the accuracy of prediction models. GAM models suggested that 250-μm (Medium) droplets optimize acifluorfen efficacy on Palmer amaranth in Dundee, MS, and 310-μm (Medium) droplets could sustain 90% of maximum weed control. Specific models for Beaver City, NE, indicated that 150-μm (Fine) droplets provide maximum Palmer amaranth control, and 340-μm (Medium) droplets could maintain 90% of greatest weed control. For Robinsonville, MS, optimal Palmer amaranth control could be obtained with 370-μm (Coarse) droplets, and 90% maximum control could be sustained with 680 μm (Ultra Coarse) droplets. Differences in optimal droplet size across location could be a result of convoluted interactions between droplet size, weather conditions, population density, plant morphology, and soil fertility levels. Future research should adopt a holistic approach to identify and investigate the influence of environmental and application parameters to optimize droplet size recommendations.

Droplet size impact on lactofen and acifluorfen efficacy for Palmer amaranth (Amaranthus palmeri) control

2019 ◽  
Vol 34 (3) ◽  
pp. 416-423
Author(s):  
Lucas X. Franca ◽  
Darrin M. Dodds ◽  
Thomas R. Butts ◽  
Greg R. Kruger ◽  
Daniel B. Reynolds ◽  
...  
Keyword(s):  
Droplet Size ◽  
Pulse Width Modulation ◽  
Effective Means ◽  
Cost Effective ◽  
Palmer Amaranth ◽  
Target Movement ◽  
Spray Droplet ◽  
Spray Droplets ◽  
Droplet Sizes ◽  
Biomass Reduction

AbstractHerbicide applications performed with pulse width modulation (PWM) sprayers to deliver specific spray droplet sizes could maintain product efficacy, minimize potential off-target movement, and increase flexibility in field operations. Given the continuous expansion of herbicide-resistant Palmer amaranth populations across the southern and midwestern United States, efficacious and cost-effective means of application are needed to maximize Palmer amaranth control. Experiments were conducted in two locations in Mississippi (2016, 2017, and 2018) and one location in Nebraska (2016 and 2017) for a total of 7 site-years. The objective of this study was to evaluate the influence of a range of spray droplet sizes [150 (Fine) to 900 μm (Ultra Coarse)] on lactofen and acifluorfen efficacy for Palmer amaranth control. The results of this research indicated that spray droplet size did not influence lactofen efficacy on Palmer amaranth. Palmer amaranth control and percent dry-biomass reduction remained consistent with lactofen applied within the aforementioned droplet size range. Therefore, larger spray droplets should be used as part of a drift mitigation approach. In contrast, acifluorfen application with 300-μm (Medium) spray droplets provided the greatest Palmer amaranth control. Although percent biomass reduction was numerically greater with 300-μm (Medium) droplets, results did not differ with respect to spray droplet size, possibly as a result of initial plant injury, causing weight loss, followed by regrowth. Overall, 900-μm (Ultra Coarse) droplets could be used effectively without compromising lactofen efficacy on Palmer amaranth, and 300-μm (Medium) droplets should be used to achieve maximum Palmer amaranth control with acifluorfen.

Effect of Formulation and Nozzle Type on Droplet Size with Isopropylamine and Trimesium Salts of Glyphosate

1997 ◽  
Vol 11 (4) ◽  
pp. 639-643 ◽  
Author(s):  
Thomas C. Mueller ◽  
Alvin R. Womac
Keyword(s):  
Nonionic Surfactant ◽  
Weed Control ◽  
Droplet Size ◽  
Management Tool ◽  
Spray Droplet ◽  
Droplet Distribution ◽  
Extended Range ◽  
Glyphosate Formulation ◽  
Nozzle Type ◽  
Flat Fan Nozzle

When spray mixtures were examined using a laser spray droplet analyzer, the new isopropylamine glyphosate formulation produced more small droplets than a previous isopropylamine salt of glyphosate formulation or glyphosate–trimesium plus nonionic surfactant. The use of a pre-orifice flat-fan nozzle and an impact type flat-fan nozzle reduced the amount of small droplets produced compared to an existing extended range flat-fan nozzle, while maintaining a spray droplet distribution that could still provide good weed control. The new nozzle technologies could provide a useful management tool to manage potential drift situations.

Fading Activities of Herbicidal Droplets Amended with Emulsifiable Spray Adjuvants on Cucurbitaceous Leaves

2018 ◽  
Vol 61 (6) ◽  
pp. 1881-1888
Author(s):  
Jeng-Liang Lin ◽  
Heping Zhu
Keyword(s):  
Weed Control ◽  
Droplet Size ◽  
Spray Deposition ◽  
Herbicide Application ◽  
Spray Droplet ◽  
Coverage Area ◽  
Maximum Coverage ◽  
Fading Time ◽  
Selection Of ◽  
Spray Adjuvants

Abstract. Understanding reactions of surfactant-amended droplets on difficult-to-wet weed surfaces could help develop application strategies to increase herbicide efficacy. Behaviors of herbicidal droplets containing different emulsifiable anti-evaporation spray adjuvants were investigated by characterizing 250 and 450 µm herbicidal droplet dispersion and fading time on cucurbitaceous leaves placed inside a 20°C chamber at 30% and 60% relative humidity (RH). Droplet maximum coverage area increased with droplet size but not with RH, while droplet fading time increased with both droplet size and RH. Despite 450 µm droplets having greater maximum coverage area than 250 µm droplets, the larger droplets had higher fading rates and lower ratios of maximum coverage area to droplet volume. Droplet maximum coverage area and fading time on leaves were affected by adding spray adjuvants to the herbicide-only solution. The Uptake surfactant was more effective than the other two surfactants (AntiEvap+BS1000 and Enhance) in increasing droplet maximum coverage area and fading time. Compared to the herbicide-only solution, addition of Uptake surfactant to the herbicide solution could increase maximum coverage area by 68% and 52% for 250 and 450 µm droplets, respectively, but addition of AntiEvap+BS1000 or Enhance surfactants did not show significant increase. Similarly, addition of Uptake surfactant to the herbicide-only solution increased droplet fading times by 11.1% and 13.2% at 30% and 60% RH, respectively, for 250 µm droplets and by 34.7% and 2.8% at 30% and 60% RH, respectively, for 450 µm droplets. In contrast, addition of AntiEvap+BS1000 surfactant reduced fading time, and addition of Enhance surfactant did not significantly affect fading time. Therefore, appropriate selection of spray adjuvants for herbicide applications could significantly influence droplet deposit behaviors on cucurbitaceous leaves, leading to improved effectiveness of weed control. Keywords: Herbicide application, Spray deposition, Spray droplet, Surfactant, Weed control.

Impact of Auxin Herbicides on Palmer amaranth Groundcover

2021 ◽  
pp. 1-32
Author(s):  
Grant L Priess ◽  
Jason K Norsworthy ◽  
Rodger B Farr ◽  
Andy Mauromoustakos ◽  
Thomas R Butts ◽  
...  
Keyword(s):  
Droplet Size ◽  
Field Experiments ◽  
Palmer Amaranth ◽  
Clear Understanding ◽  
Spray Droplet ◽  
Extended Range ◽  
Droplet Sizes ◽  
Auxin Herbicides ◽  
Control Technologies ◽  
The Impact

Abstract In current and next-generation weed control technologies, sequential applications of contact and systemic herbicides for POST control of troublesome weeds are needed to mitigate the evolution of herbicide resistance. A clear understanding of the impact auxin herbicide symptomology has on Palmer amaranth groundcover will aid optimization of sequential herbicide applications. Field and greenhouse experiments were conducted in Fayetteville, AR and a laboratory experiment was conducted in Lonoke, AR, in 2020 to evaluate changes in Palmer amaranth groundcover following an application of 2,4-D and dicamba with various nozzles, droplet sizes, and velocities. Field experiments utilized three nozzles: Extended Range (XR), Air Induction Extended Range (AIXR), and Turbo TeeJet Induction (TTI), to assess the effect of spray droplet size on changes in Palmer amaranth groundcover. Nozzle did not affect Palmer amaranth groundcover when dicamba was applied. However, nozzle selection did impact groundcover when 2,4-D was applied; the following nozzle order XR>AIXR>TTI reduced Palmer amaranth groundcover the greatest in both site-years of the field experiment. This result (XR>AIXR> TTI) matches percent spray coverage data for 2,4-D and is inversely related to spray droplet size data. Rapid reductions of Palmer amaranth groundcover from 100% at time zero to 39.4 to 64.1% and 60.0 to 85.8% were observed 180 minutes after application in greenhouse and field experiments, respectively, regardless of herbicide or nozzle. In one site-year of the greenhouse and field experiments, regrowth of Palmer amaranth occurred 10080 minutes (14 days) after an application of either 2,4-D or dicamba to larger than labeled weeds. In all experiments, complete reduction of live Palmer amaranth tissue was not observed 21 days after application with any herbicide or nozzle combination. Control of Palmer amaranth escapes with reduced groundcover may potentially lead to increased selection pressure on sequentially applied herbicides due to a reduction in spray solution contact with the targeted pest.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review

2020 ◽  
Vol 27 (5) ◽  
pp. 385-391
Author(s):  
Lin Zhong ◽  
Zhong Ming ◽  
Guobo Xie ◽  
Chunlong Fan ◽  
Xue Piao
Keyword(s):  
Supervised Learning ◽  
Protein Interactions ◽  
Computational Models ◽  
Prediction Models ◽  
Chromatin Modification ◽  
Computational Prediction ◽  
Human Diseases ◽  
Future Research ◽  
Non Coding Rna ◽  
Long Non Coding Rna

: In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well as many other processes. Surprisingly, lncRNA has an inseparable relationship with human diseases such as cancer. Therefore, only by knowing more about the function of lncRNA can we better solve the problems of human diseases. However, lncRNAs need to bind to proteins to perform their biomedical functions. So we can reveal the lncRNA function by studying the relationship between lncRNA and protein. But due to the limitations of traditional experiments, researchers often use computational prediction models to predict lncRNA protein interactions. In this review, we summarize several computational models of the lncRNA protein interactions prediction base on semi-supervised learning during the past two years, and introduce their advantages and shortcomings briefly. Finally, the future research directions of lncRNA protein interaction prediction are pointed out.

Safety and efficacy of linuron with or without an adjuvant or S-metolachlor for POST control of Palmer amaranth (Amaranthus palmeri) in sweetpotato

2021 ◽  
pp. 1-18
Author(s):  
Levi D. Moore ◽  
Katherine M. Jennings ◽  
David W. Monks ◽  
Ramon G. Leon ◽  
David L. Jordan ◽  
...  
Keyword(s):  
Nonionic Surfactant ◽  
Weed Control ◽  
Critical Period ◽  
Total Yield ◽  
Field Studies ◽  
Palmer Amaranth ◽  
Amaranthus Palmeri ◽  
Foliar Injury ◽  
Protoporphyrinogen Oxidase ◽  
Safety And Efficacy

Abstract Field studies were conducted to evaluate linuron for POST control of Palmer amaranth in sweetpotato to minimize reliance on protoporphyrinogen oxidase (PPO)-inhibiting herbicides. Treatments were arranged in a two by four factorial where the first factor consisted of two rates of linuron (420 and 700 g ai ha−1), and the second factor consisted of linuron applied alone or in combinations of linuron plus a nonionic surfactant (NIS) (0.5% v/v), linuron plus S-metolachlor (800 g ai ha−1), or linuron plus NIS plus S-metolachlor. In addition, S-metolachlor alone and nontreated weedy and weed-free checks were included for comparison. Treatments were applied to ‘Covington’ sweetpotato 8 d after transplanting (DAP). S-metolachlor alone provided poor Palmer amaranth control because emergence had occurred at applications. All treatments that included linuron resulted in at least 98 and 91% Palmer amaranth control 1 and 2 wk after treatment (WAT), respectively. Including NIS with linuron did not increase Palmer amaranth control compared to linuron alone, but increased sweetpotato injury and subsequently decreased total sweetpotato yield by 25%. Including S-metolachlor with linuron resulted in the greatest Palmer amaranth control 4 WAT, but increased crop foliar injury to 36% 1 WAT compared to 17% foliar injury from linuron alone. Marketable and total sweetpotato yield was similar between linuron alone and linuron plus S-metolachlor or S-metolachlor plus NIS treatments, though all treatments resulted in at least 39% less total yield than the weed-free check resulting from herbicide injury and/or Palmer amaranth competition. Because of the excellent POST Palmer amaranth control from linuron 1 WAT, a system including linuron applied 7 DAP followed by S-metolachlor applied 14 DAP could help to extend residual Palmer amaranth control further into the critical period of weed control while minimizing sweetpotato injury.

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