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Evaluation of row width and nozzle selection on spray coverage and weed control in flooded rice

Published online by Cambridge University Press:  23 May 2024

Noah H. Reed
Affiliation:
Graduate Research Assistant, Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Thomas R. Butts*
Affiliation:
Associate Professor, Extension Weed Scientist, Department of Crop, Soil, and Environmental Sciences, University of Arkansas System Division of Agriculture, Lonoke, AR, USA
Jason K. Norsworthy
Affiliation:
Distinguished Professor and Elms Farming Chair of Weed Science, Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Jarrod T. Hardke
Affiliation:
Professor, Department of Crop Soil and Environmental Sciences, University of Arkansas System Division of Agriculture, Stuttgart, AR, USA
L. Tom Barber
Affiliation:
Professor, Extension Weed Scientist, Department of Crop, Soil, and Environmental Sciences, University of Arkansas System Division of Agriculture, Lonoke, AR, USA
Jason A. Bond
Affiliation:
Extension/Research Professor, Department of Plant and Soil Sciences, Mississippi State University, Delta Research and Extension Center, Stoneville, MS, USA
Hunter D. Bowman
Affiliation:
Assistant Professor, Department of Plant and Soil Sciences, Mississippi State University, Delta Research and Extension Center, Stoneville, MS, USA
Nick R. Bateman
Affiliation:
Associate Professor/Crop Entomologist, Department of Entomology and Plant Pathology, Stuttgart, AR, USA
Aurelie M. Poncet
Affiliation:
Assistant Professor, Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Koffi B.J. Kouame
Affiliation:
Postdoctoral Research Fellow, Department of Crop, Soil, and Environmental Sciences, University of Arkansas System Division of Agriculture, Lonoke, AR, USA
*
Corresponding author: Thomas R. Butts; Email: buttst@purdue.edu
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Abstract

Barnyardgrass and other troublesome weeds have become a major problem for producers in a flooded rice system. Cultural control options and more efficient herbicide applications have become a priority to increase efficiency and weed control in rice. This study aimed to determine the effects of row width and nozzle selection on spray coverage and weed control in a flooded rice system. A field experiment was conducted at 7 site-years (Lonoke, AR, in 2021 and 2022; Pine Tree, AR, in 2021 and 2022; Rohwer, AR, in 2022; and Stoneville, MS, in 2021 and 2022) as a randomized complete block split-plot design. Five nozzles (XR, AIXR, TTI, TTI60, and AITTJ60) (subplot factor) were used for herbicide applications, and plots were drill-seeded in four row widths (whole plot factor) (13, 19, 25, and 38 cm). A droplet size experiment was conducted to evaluate the droplet size and velocity of each nozzle type used in the field experiment. Overall, as row width increased, barnyardgrass density increased. The rice grown in a wider width took longer to generate canopy closure, allowing weed escapes in the crop. For example, the 13-cm width had a 12 percentage point canopy coverage increase compared to the 38-cm row width at the preflood timing resulting in a reduction of six barnyardgrass plants per square meter. The smallest droplet size-producing nozzle (XR) provided greater weed control throughout the study but is more prone to drift. The dual-fan nozzles (AITTJ60 and TTI60) had variable weed control impacts, and it was difficult to predict when this might occur; however, they did have increased deposits on water-sensitive cards compared to single-fan counterparts (AIXR and TTI). In conclusion, a narrower row width (e.g., 19-cm or less) and a smaller droplet size producing nozzle (XR) are optimal for barnyardgrass control in a flooded rice system.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Weed Science Society of America

Introduction

Rice is considered a staple food crop for nearly half of the world’s population. Increasing urban environments have led to a reduction of land availability, highlighting the importance of high-yielding environments and being more efficient in rice production (Prasad et al. Reference Prasad, Shivay and Kumar2017). In the latest growing season of 2022–2023, the state of Arkansas was the lead rice producing state in the United States with over 50% of rice production in the country (USDA-NASS 2023). Weeds are among the major biotic stresses in rice causing upwards of 70 to 80% yield reduction in direct-seeded rice (Dass et al. Reference Dass, Shekhawat, Choudhary, Sepat, Rathore, Mahajan and Chauhan2017; Smith Reference Smith1968). One of the main weed control options in the United States is the use of chemical herbicides. With the continuous use of these herbicides, survey respondents in Arkansas reported using three or more herbicide applications per field to combat the weed pressure and seventy-eight percent of the respondents had high concerns about herbicide-resistant weeds (Butts et al. Reference Butts, Kouame, Norsworthy and Barber2022). An earlier survey found similar results regarding herbicide-resistant weed concerns in rice (Norsworthy et al. Reference Norsworthy, Burgos, Scott and Smith2007). This emphasizes the importance of developing more efficient integrated weed management strategies to produce a more sustainable rice production system in the future (Mahajan et al. Reference Mahajan, Ramesha and Chauhan2014).

Row width manipulation is effective in other crops for efficient weed control. Research conducted in soybean [Glycine max (L.) Merr.] provided evidence that the crop yield increased and weed yield decreased as the row width decreased (Butts et al. Reference Butts, Norsworthy, Kruger, Sandell, Young, Steckel, Loux, Bradley, Conley, Stoltenberg, Arriaga and Davis2016; Hock et al. Reference Hock, Knezevic, Martin and Lindquist2006; Wax and Pendleton Reference Wax and Pendleton1968). Profitability also increased when switching to narrow row (38 cm) soybean from wider row widths (76 cm) (Lambert and Lowenberg-DeBoer Reference Lambert and Lowenberg-DeBoer2003). This provides support that similar results may be achievable in a rice production system with new higher tillering capabilities of hybrid rice enhancing canopy closure (Chauhan and Opeña Reference Chauhan and Opeña2013; N.H. Reed unpublished data). A similar crop to rice is soft red winter wheat (Triticum aestivum L.) and a study in eastern Kansas investigated row widths of 19 and 38 cm. In this study, weed emergence increased and yield decreased for the 38-cm width compared to the 19-cm width (Shoup and Adee Reference Shoup and Adee2014). One major pest to control in rice is barnyardgrass, and narrow widths of 20 cm or less have the potential to reduce weed density leading to less seed in the soil seedbank (Butts et al. Reference Butts, Kouame, Norsworthy and Barber2022; Chauhan and Johnson Reference Chauhan and Johnson2010; Schwartz-Lazaro and Copes Reference Schwartz-Lazaro and Copes2019). The recommended row width in Arkansas is between 10 and 25 cm depending on crop production limitations of farmers, such as equipment and field conditions (Hardke Reference Hardke2022). These results could impact weed control in a rice production system.

In any crop production system, profitability from yield is an important consideration for farmers. In some situations, a rice crop with no weed control implementation can cause yield reductions of 94% to 96% (Chauhan and Johnson Reference Chauhan and Johnson2011). In a drill-seeded rice system, increased grain yield and reduced weed infestations were observed as a result of rice planted in a narrow row width of 19 to 25 cm, which in return, can reduce herbicide use by up to 50% in some conditions (Dass et al. Reference Dass, Shekhawat, Choudhary, Sepat, Rathore, Mahajan and Chauhan2017; Jones and Snyder Reference Jones and Snyder1987; Lytle et al. Reference Lytle, Hardke, Roberts, Frizzell, Castaneda-Gonzalez, Frizzell, Hale and Amos2021).

Herbicide optimization is critical to maximize weed management efforts, and a site-specific management approach would be beneficial throughout the mid-south (Butts et al. Reference Butts, Samples, Franca, Dodds, Reynolds, Adams, Zollinger, Howatt, Fritz, Hoffmann and Kruger2018). Some regulations limit the use of certain application methods, like particular nozzles, because of the drift potential due to smaller droplet sizes. The greater the droplet size, the more drift potential is reduced; however, herbicide efficacy has been reduced with increased droplet sizes (Butts et al. Reference Butts, Samples, Franca, Dodds, Reynolds, Adams, Zollinger, Howatt, Fritz, Hoffmann, Luck and Kruger2019; Carter et al. Reference Carter, Prostko and Davis2017; Creech et al. Reference Creech, Henry, Fritz and Kruger2015). To achieve an effective herbicide application, all parameters such as nozzle selection, droplet size, and spray drift potential should be considered by producers (Chethan et al. Reference Chethan, Singh, Dubey, Subhash and Dibakar2019).

The most effective pesticide applications are made when the greatest area of the plant is covered with spray solution. Dual-fan nozzles increased spray coverage and efficacy compared to a single-fan highlighting the potential of providing greater weed control while using a larger droplet size to reduce drift potential at the same time (Ferguson et al. Reference Ferguson, Hewitt and O’Donnell2016). Smaller droplet size-producing nozzles provide greater spray coverage than larger droplet size-producing nozzles, which could increase weed control with an effective herbicide application (Priess et al. Reference Priess, Norsworthy, Farr, Mauromoustakos, Butts and Roberts2021). Velocity is another component that can impact coverage and drift potential; when the vertical velocity is increased, and the horizontal velocity is decreased, then a reduction of drift is observed (Farooq et al. Reference Farooq, Balachandar, Wulfsohn and Wolf2001). Smaller droplet size and lower terminal velocity increased the effectiveness and coverage of solution on plants compared to larger droplets and a higher velocity (Lake Reference Lake1977). As a result, the objective of this research was to determine the effects of row width manipulation and nozzle selection on coverage and weed control in a flooded rice system across diverse environments and herbicide application systems.

Materials and Methods

Field Sites

Field experiments were conducted across 7 site-years in 2021 and 2022. The first location occurred at the University of Arkansas Pine Bluff Small Farm Outreach Center near Lonoke, Arkansas (34.85°N, 91.88°W) with the soil being an Immanuel silt loam (fine-silty, thermic Oxyaquic Glossaqualfs) consisting of 14% sand, 72% silt, 14% clay, and 1.25% organic matter with a pH of 5.6. The planting dates at this location were June 16, 2021, and May 16, 2022. The second location occurred at the University of Arkansas System Division of Agriculture Pine Tree Research Station near Colt, Arkansas (35.13°N, 90.96°W) with a Calhoun silt loam (fine-silty, thermic Typic Glossaqualfs) consisting of 12% sand, 70% silt, 18% clay, and 1.02% organic matter with a pH of 5.6. The rice was drill-seeded on July 7, 2021, and June 7, 2022, at this location. The third location of the experiment was at the University of Arkansas System Division of Agriculture Rohwer Research Station near Watson, Arkansas (33.79°N, 91.29°W) and was only conducted in 2022. The soil was a Sharkey clay (very-fine, thermic Chromic Epiaquerts) consisting of 2% sand, 45% silt, 53% clay, and 1.98% organic matter with a pH of 6.8. The planting date at this location was June 28, 2022. The last location was at the Delta Research and Extension Center near Stoneville, Mississippi (33.40°N, 90.86°W). The soil classification of this site was a Sharkey clay (very-fine, thermic Chromic Epiaquerts) consisting of 2% sand, 32% silt, 66% clay, and 2.4% organic matter with a pH of 7.5. The Stoneville location was planted on May 26, 2021, and May 11, 2022.

Experimental Design

This experiment was designed as a split-plot randomized complete block (24 treatments) replicated four times with four nontreated controls, one for each row width. The whole-plot factor consisted of four row widths of 13, 19, 25, and 38 cm. These row width treatments were selected because 1) 19- and 25-cm row widths are currently commercially available, 2) a reduced width of 13 cm was hypothesized to aid in cultural weed management, and 3) a 38-cm row width may become commercially available in the future with enhancements in precision planting technology. This wider row width may aid in facilitating crop rotation capabilities with reduced equipment inputs. The subplot factor consisted of five nozzle types used for herbicide applications, including three single-fan and two dual-fan nozzles. Single-fan nozzles comprised the XR-11002 (Extended range), AIXR-11002 (Air induction extended range), and TTI-11002 (Turbo TeeJet induction). Dual-fan nozzles comprised the TTI60-11002 (Turbo TeeJet induction dual fan) and AITTJ60-11002 (Air induction turbo TeeJet). All nozzles were from TeeJet Technologies (Spraying Systems, Inc., Glendale Heights, IL). These nozzles were selected based on commercial usage, the range of droplet sizes produced, and the comparable designs of the dual-fan and single-fan nozzles.

At all site-years, a hybrid rice cultivar, ‘RT7521 FP’ (RiceTec Inc., Alvin, TX), was drill-seeded at 128 seeds m−2. Plot dimensions were 7.6 m long and 1.5 m wide, and standard University of Arkansas recommendations for nutrients, pests, and irrigation/flooding were used (Hardke et al. Reference Hardke2022).

High levels of weed infestation and previous survey results indicated commercial rice fields in Arkansas typically receive three to four herbicide applications including a preemergence and two to three postemergence applications (Butts et al. Reference Butts, Kouame, Norsworthy and Barber2022). As a result, the decision was made to apply a noncommercial herbicide program within this research targeting grass, sedge, and broadleaf weed species specific to each respective site-year. This noncommercial program included two herbicide applications (one preemergence and one postemergence) to allow assessment of the cultural factors but provide the opportunity for trials to be harvested for yield assessment. Additionally, as it is common commercially for a singular nozzle type to be used throughout an entire growing season across multiple herbicide programs, a fixed herbicide program was not implemented so as to provide insights into nozzle selection impacts across a range of herbicide application systems. Applications were made with an all-terrain vehicle equipped with a CO2-pressurized sprayer calibrated to deliver 94 L ha−1 at 8 km h−1 at the Arkansas locations, rotating each nozzle for individual applications. At the Mississippi location, applications were made using a CO2-pressurized backpack sprayer calibrated to deliver 140 L ha−1 at 5.6 km h−1 with each appropriate nozzle.

Across site-years, a preemergence application of clomazone at 315 g ai ha−1 (Command® 3ME; FMC, Philadelphia, PA) and saflufenacil at 75 g ai ha−1 (Sharpen; BASF, Morrisville, NC) was applied. Different postemergence applications were made across site years depending on the certain type of weed species and density that were observed in the experiment. The postemergence applications at the Lonoke and Pine Tree locations in 2021 consisted of cyhalofop at 313 g ai ha−1 (Clincher® SF; Corteva Agriscience, Indianapolis, IN) and halosulfuron + thifensulfuron at 35 + 4.5 g ai ha−1 (Permit Plus; Gowan, Yuma, AZ). The postemergence application at the Lonoke site in 2022 was bentazon applied at 560 g ai ha−1 (Basagran®; BASF Canada, Mississauga, ON). The postemergence application at the Stoneville site in 2021 and 2022 was imazethapyr applied at 105 g ai ha−1 (Preface®; ADAMA, Raleigh, NC) and quinclorac at 420 g ai ha−1 (Facet®; BASF). Applications at the Pine Tree and Rohwer locations in 2022 consisted of fenoxaprop at 122 g ai ha−1 (Ricestar HT; Gowan), bispyribac-sodium at 3.5 g ai ha−1 (Regiment®; Valent U.S.A., Walnut Creek, CA), and halosulfuron + thifensulfuron at 35 + 4.5 g ai ha−1. All postemergence applications contained a 1% vol/vol rate of crop oil concentrate. The appropriate nozzle for each treatment was used to apply both the preemergence and postemergence herbicide applications.

Data Collection

Barnyardgrass density was assessed from two 0.25-m2 quadrants per plot at the 5- to 6-leaf rice stage (preflood) and the preharvest stage. All density data were then converted to a square meter for ease of presentation.

At the postemergence application for the Arkansas locations, one water-sensitive spray card (7.6 × 5.1 cm; Spraying Systems, Inc.) was placed per plot parallel to the soil surface at 15 cm above the soil at the top of the rice canopy to measure percent spray coverage and spray deposits per square centimeter. The cards were initially yellow, and as the herbicide mixture encountered the card, the solution would cause the droplets to turn blue. After the application, the cards were allowed to air dry before being handled to prevent any data contamination. Water-sensitive spray cards were analyzed using USDA-ARS DepositScan for the above factors (Zhu et al. Reference Zhu, Salyani and Fox2011).

A small, unmanned aircraft system (sUAS) (Inspire 2; DJI Technology Co., Nanshan, Shenzhen, China) was manually flown to take digital images from directly above of each plot at the preflood and panicle differentiation rice stages to assess canopy coverage. Images from sUAS were taken at the Lonoke, Pine Tree, and Rohwer locations in 2022 only. In 2021, technological complications caused the images to not be taken accurately to assess canopy coverage. At the Stoneville, MS location, technological difficulties did not allow for proper data collection. The images were captured at a 46-m height across all plots for consistency in the analysis software. Aerial images were analyzed using FieldAnalyzer software (Green Research Services, Fayetteville, AR). Green pixel counts were measured in each plot to determine the canopy coverage percentage.

Before rice harvest, barnyardgrass panicles were clipped and averaged from two 0.25-m−2 quadrants per plot and placed in paper bags. Barnyardgrass inflorescences were dried at 66 C for 3 to 5 d to constant mass. The panicles were then hand threshed and cleaned to gather the barnyardgrass seed. The mass of 100 barnyardgrass seeds was recorded and divided by the total mass of cleaned seed to determine the seed production per 0.25 m−2 of each plot. Seed production was converted to a square meter scale for ease of presentation.

Rough rice grain yield was collected at harvest with a small-plot research combine. The entire width of the plot was harvested at the Lonoke, Rohwer, and Stoneville locations. At the Pine Tree location, two identical plot combines with different header widths were equally calibrated and used according to the row width of the plot. This was done because no single header could harvest the entirety of the plot at this location. With a fixed header size and variable row widths, it would have resulted in a variable number of rows entering the combine. Therefore, a 51-cm header was used to harvest two rows of the 25-cm row width and four rows of the 13-cm width per plot. A 72-cm header harvested two rows of the 38-cm row width and four rows of the 19-cm width per plot.

Statistical Analyses

Site-year and block nested within site-year were run as random effects across all analyses to generate broader conclusions across diverse environments as indicated in the overall objective, and with 5 site-years of data, it was deemed statistically beneficial (Midway Reference Midway2022). Row width and nozzle type were considered fixed effects. All data were analyzed using ANOVA. Rice canopy coverage and water-sensitive card spray coverage were analyzed using SAS software (v. 9.5; SAS Institute, Cary, NC) with the GLIMMIX procedure and a beta distribution. Preflood barnyardgrass density, preharvest panicle counts, and seed production were analyzed in JMP Pro 17.0 (SAS) using the GLIMMIX procedure with a Poisson distribution. Rough rice yield was analyzed in JMP Pro 17.0 using the GLIMMIX procedure and a normal distribution. All means were separated using Tukey’s honestly significant difference (HSD) test with an alpha value of 0.05.

Droplet Size and Velocity Experiment

A laboratory experiment was conducted at the Lonoke Extension Center near Lonoke, AR, to evaluate the droplet size and velocity from each nozzle type used in the previously described field experiment. Data collected included the Dv0.1, Dv0.5, and Dv0.9, driftable fines (defined as the percent of spray volume less than 200 µm), average droplet velocity, and maximum droplet velocity. The Dv0.1, Dv0.5, and Dv0.9 are the droplet diameters in which 10%, 50%, and 90% of the spray volume are contained in droplets with a lesser diameter, respectively. Spray classifications were also determined according to standard S572.1 as published by the American Society of Agricultural and Biological Engineers (ANSI/ASABE 2020). Measurements were made using the VisiSize P15 Portable Particle/Droplet Image Analysis System (Oxford Lasers, Imaging Division, Oxford, UK) using similar methods to previous research (Kouame et al. Reference Kouame, Butts, Werle and Johnson2022). The system was installed within a Generation 4 Research Track Sprayer (Devries Manufacturing, Hollandale, MN). Before measurements, the VisiSize P15 components were aligned and calibrated according to manufacturer’s recommendation. The spray chamber was operated at 276 kPa and traversed at 0.22 m s−1 to allow for sampling of spray droplets from the entire spray plume. Data acquisition was set to measure diameter and velocity of 2,500 individual droplets per replication, with three separate replications being recorded, giving a total of 7,500 individual droplets measured per treatment.

The DV0.1, DV0.5, and DV0.9 average droplet velocity, and maximum droplet velocity data were subjected to ANOVA using the GLIMMIX procedure in SAS software (v. 9.5) with a gamma distribution. Treatment means were separated using Tukey’s HSD (α = 0.05). The percent of driftable fines were predicted using the Rosin-Rammler equation:

(1) $$V\left( d \right) = 100 - 100\ {\rm{*\ exp}}\left( { - {{\left( {{d \over c}} \right)}^m}} \right)$$

where V is the cumulative percent volume of droplets with the diameter lower than a certain value (d); c is the characteristic droplet diameter, defined as the diameter at which the cumulative volume fraction is 63.2%; and m is a constant indicating the uniformity of the distribution.

Additionally, the four-parameter log-logistic model (Eq. 2) was fit to droplet size and velocity paired measurements data to predict droplet velocities of specific droplet size spray particles from each nozzle type:

(2) $$Y = c + {{d - c} \over {1 + {\rm{exp}}\left[ {b\left( {{\rm{log}}\left( x \right) - {\rm{log}}(e} \right)} \right]}}$$

where Y is the droplet exit velocity (m s−1), b is the slope at the inflection point, c is the lower limit (m s−1), d is the upper limit (m s−1), e is the inflection point, and x is the droplet size (µm). All curve fittings were accomplished using nonlinear least squares regression with the R package (version 4.0.0) (R Core Team 2021).

Results and Discussion

Droplet Size and Velocity Data

The Dv0.1, Dv0.5, and Dv0.9 were impacted by nozzle type (Table 1). The TTI produced the largest droplet diameter at the Dv0.5 and Dv0.9, followed by the TTI60, AITTJ60, AIXR, and XR, respectively. The TTI and TTI60 produced the largest Dv0.1, followed by the AITTJ60, AIXR, and XR, respectively. The Dv0.1 had a range from 91 µm emitted by the XR to 333-µm emitted by the TTI60. The Dv0.5 ranged from 160-µm emitted by the XR to 733-µm emitted by the TTI, which provided spray classifications ranging from Fine to Ultra Coarse. The Dv0.9 ranged from 302-µm emitted by the XR to 1200-µm emitted by the TTI. It is important to take into consideration not only the Dv0.5, often considered the average droplet size, but also the Dv0.1 and Dv0.9 as these values provide an overall observation of the complete droplet size distribution. A droplet size distribution with a similar Dv0.5, but reduced Dv0.1 and/or increased Dv0.9 would indicate a less homogenous spray droplet size mixture, which is often undesirable from an efficacy and spray drift mitigation perspective. Driftable fines were calculated to find the potential of the solution to move off target (Stainer et al. Reference Stainer, Destain, Schiffers and Lebeau2006). In this study, driftable fines was defined as the percentage of spray volume contained in droplets with diameters less than 200 µm. The XR and AIXR nozzles had the greatest potential to move off-target with 66.98% and 25.68% driftable fines, respectively. For high drift concerns, nozzles like the TTI and TTI60 should be considered as they produced the fewest driftable fines, but a loss of weed control has been observed due to the increased droplet size (Butts et al. Reference Butts, Samples, Franca, Dodds, Reynolds, Adams, Zollinger, Howatt, Fritz, Hoffmann and Kruger2018, Reference Butts, Samples, Franca, Dodds, Reynolds, Adams, Zollinger, Howatt, Fritz, Hoffmann, Luck and Kruger2019; Meyer et al. Reference Meyer, Norsworthy, Kruger and Barber2016). Creech et al. (Reference Creech, Henry, Fritz and Kruger2015) found a 176% change in droplet size from the XR to a TTI nozzle, which is similar to the results found in this study.

Table 1. Dv0.1, Dv0.5, and Dv0.9; driftable fines; and spray classification determined by using an Oxford Laser system in a spray chamber. a

a Means followed by the same letter within a column are not different based on Tukey’s honestly significant difference test (α = 0.05).

b Driftable fines are defined as the percentage of spray volume contained in droplets with diameters less than 200 µm.

c Spray classifications were determined using American Society of Agricultural and Biological Engineers standard S572.1, where F indicates Fine; M, Medium; C, Coarse; VC, Very Coarse; EC, Extremely Coarse; and UC, Ultra Coarse.

Both the average and maximum velocities were also impacted by nozzle type (Table 2). The XR and AIXR produced the fastest average droplet velocities, followed by the TTI60, TTI, and AITTJ60 nozzles, respectively. The predicted velocities at specific droplet sizes numerically followed this similar trend. Greater velocities have the potential to reduce weed control because the droplets will bounce or shatter more easily, but they do have the potential to reduce drift (Kouame et al. Reference Kouame, Butts, Werle and Johnson2022). When comparing single-fan versus dual-fan nozzles, the single-fan AIXR produced a smaller Dv0.1, Dv0.5, and Dv0.9 than its counterpart, the dual-fan AITTJ60. Conversely, the single-fan TTI had a greater Dv0.5 and Dv0.9 compared to the dual-fan TTI60. Overall, the nozzle types evaluated in this research had a wide range of droplet sizes, drift potential, and droplet velocities that could impact resulting spray coverage and weed control.

Table 2. Average, maximum, and predicted droplet velocity for each nozzle type in the experimental laboratory study. a

a Means followed by the same letter within a column are not different based on Tukey’s honestly significant difference test (α = 0.05).

Field Experiment

Data collected varied across site-years. Spray coverage, number of spray deposits, preflood barnyardgrass density, panicle counts, and seed production were collected from the 5 site-years conducted in Arkansas. Rice canopy coverage data were collected only in 2022 from the three Arkansas locations. Rough rice yield was collected from all 7 site-years.

No interaction between row width and nozzle type occurred across all response variables (Table 3). Across site-years, row width and nozzle main effects affected barnyardgrass density and panicle counts at the preflood and preharvest stage, respectively. At the preflood stage, row widths of 13, 19, and 25 cm had a barnyardgrass density count of 14, 15, and 16 m−2, respectively (Table 4). The highest barnyardgrass density was observed in the 38-cm row width with 20 plants m−2. Barnyardgrass density increased by 42% in the widest row width of 38 cm compared to 13-cm. Additional control efforts would likely be needed to reach adequate control for barnyardgrass and other weed species at the widest row width of 38-cm, and a narrower width from 13- to 25 cm likely would help reduce barnyardgrass populations.

Table 3. P-values from ANOVA for barnyardgrass density at preflood and preharvest rice stages, canopy coverage percentage for 2022, barnyardgrass seed production before harvest, and rough rice yield across site-years. a, b

a Values in bold indicate statistical significance at α = 0.05.

b Canopy coverage is from 2022 only due to excessive weed pressure and software limitations. Five site-years of data were collected for barnyardgrass preflood density, preharvest panicles, and seed production. Rough rice yield was collected across all 7 site-years.

Table 4. Barnyardgrass preflood density, preharvest panicle counts, and seed production across site-years. a , b

a Means followed by the same letter within a main effect and column are not different based on Tukey’s honestly significant difference test (α = 0.05).

b Five site-years were used for barnyardgrass density, panicles, and seed production.

c Row width is measured in centimeters.

At the preflood stage, the lowest barnyardgrass densities of 15 to 17 plants m−2 occurred from applications with the XR, AIXR, AITTJ60, and TTI nozzles (Table 4). The TTI60 had the greatest barnyardgrass density with 21 plants m−2. At this preflood timing, only a preemergent application had been made. This would indicate there may be negative consequences resulting in greater barnyardgrass density when a TTI60 nozzle that produced an Ultra Coarse spray, low droplet velocity, and had dual-fans (Tables 1 and 2) was used for a PRE application to bare soil. However, further research is needed to fully characterize this relationship. Dual-fan nozzles can lessen the angle of spray to the target and have previously improved coverage to the leaf surface compared to a single-fan nozzle (Gossen et al. Reference Gossen, Peng, Wolf and McDonald2008). While this is the case for leaf surface coverage, it could be a different result for soil surface coverage and the ability of the herbicide to be activated.

The preharvest panicle counts followed a similar trend as the preflood density counts with reduced barnyardgrass panicles observed in narrower rice row widths. At the preharvest rice stage, the lowest number of panicles occurred in the 13-cm row width with 6 panicles m−2 (Table 4). Barnyardgrass panicles increased to 8 panicles m−2 in the 19- and 25-cm row widths compared to the 13-cm row width. The greatest number of panicles was in the 38-cm row width with 13 panicles m−2. There was a 116% increase in barnyardgrass panicle counts in the widest row width of 38 cm compared to 13-cm. The use of narrower row widths such as 13 cm in rice could help reduce herbicide use and reduce weed control costs like it has in other crops like corn (Zea mays L.) and soybean (Forcella et al. Reference Forcella, Westgate and Warnes1992).

At the preharvest rice stage, applications from the AITTJ60, AIXR, TTI, and TTI60 nozzles resulted in similar panicle counts of 8 to 10 m−2 (Table 4). The fewest barnyardgrass panicle counts of 6 panicles m−2 occurred in rice following applications with the XR nozzle. Droplet size is considered an important factor in weed control which could explain why greater panicle density occurred in the larger droplet size producing nozzles with Dv0.5 greater than 160 µm (Table 1) (Oliveira et al. Reference Oliveira, Lopes, Raetano, Lima and Prado2021). Other research has also identified better weed control from applications with a smaller droplet size producing nozzle such as the XR than larger droplet sizes (Brankov et al. Reference Brankov, Simic, Ulber, Tolimir, Chachalis and Dragicevic2023). Although applications from the XR nozzle provided the greatest panicle density reduction, it also had the highest driftable fine percentage (Table 1). This nozzle could potentially have the highest off-target movement of herbicides and may not be the most suitable nozzle in some cases as a result. Identifying other nozzles that can provide adequate weed control and lower driftable fines coupled with altering other application parameters, such as spray volume, should be considered when making a herbicide application.

For barnyardgrass seed production, only the main effect of row width was significant (Table 3). The narrowest row width of 13 cm resulted in 2,590 fewer barnyardgrass seeds per square meter compared to the widest row width of 38 cm (Table 4). This wide row width allowed for more weed seed to be returned to the soil seedbank increasing the likelihood of herbicide resistance evolution and negatively impacting long-term weed management. The 19- and 25-cm row widths resulted in similar barnyardgrass seed production with 4,610 and 4,390 seeds m−2, respectively. A narrower row width, particularly 13 cm, provided numerically lower barnyardgrass density counts and seed production, as well as statistically lower panicle counts, thereby likely reducing the number of weed seeds returned to the soil seedbank and improving long-term weed management. In a wheat study, seed production from a single plant was three times greater in a wheat row width of 30 cm compared to a 10-cm width (Mertens and Jansen Reference Mertens and Jansen2002).

Nozzle selection did not have statistical differences in barnyardgrass seed production, but the fewest number of seeds numerically were produced following applications with the XR nozzle with 3,900 seeds m−2. However as previously stated, this nozzle has the highest drift potential and should be used cautiously.

Water-sensitive spray cards were used to measure percent spray coverage and number of spray deposits across all five Arkansas 5 site-years. A significant nozzle-type main effect was observed for both response variables (Table 5). The order of nozzle type from greatest to least percent spray coverage occurring from applications with their respective use were XR = AIXR > AITTJ60 = TTI = TTI60. Increased coverage from a herbicide application can lead to greater weed control. This was observed by Carter et al. (Reference Carter, Prostko and Davis2017) where they found 5% to 6% lower grass control from applications using TTI nozzles compared to AIXR and DriftGuard (Spraying Systems, Inc.) nozzles.

Table 5. Water-sensitive spray cards across 5 site-years in Arkansas including percent coverage and number of spray deposits for each nozzle used at the postemergence application. a , b , c

a Means followed by the same letter within a column are not different based on Tukey’s honestly significant difference test (α = 0.05).

b Five site-years were used for coverage percentage and spray deposits on water-sensitive spray cards.

c Values in bold indicate statistical significance at α = 0.05.

The number of spray deposits from each nozzle type trended similarly to the percent spray coverage, except 36 more spray deposits per square centimeter were observed for the AITTJ60 compared to the AIXR (Table 5). Additionally, applications from the TTI60 resulted in 51 more deposits per square centimeter than the TTI nozzle. This indicates although the dual-fan AITTJ60 and TTI60 nozzles did not have greater percent spray coverage, they did have an increased number of spray deposits compared to the similar droplet size producing single-fan AIXR and TTI nozzle counterparts, respectively (Table 1). As a result, there could be more complex interactions that would occur on resulting weed control that coverage alone would not indicate, and dual-fan nozzles could be beneficial in spraying from two different angles that single-fan nozzles are not capable of. Previous research indicated that dual-fan nozzles produced greater coverage on vertical leaves, but the single-fan outperformed the dual-fan nozzles on horizontal leaves in wheat (Ozkan et al. Reference Ozkan, Paul, Derksen and Zhu2012).

Nozzle selection effects on weed control were variable throughout the study. Priess et al. (Reference Priess, Norsworthy, Farr, Mauromoustakos, Butts and Roberts2021) found that increased coverage or decreases in droplet size did not consistently impact Palmer amaranth groundcover. Another study evaluating a big dataset of various spray application factors also found that weed control results can be highly variable and that several different factors working together, such as droplet size, spray volume, herbicide active ingredient, etc., may help explain this variability with each application (Knoche Reference Knoche1994). The dual-fan nozzles generally did not impact weed control compared to single-fan nozzles; however, there was an interesting trend with barnyardgrass seed production in relation to water-sensitive card droplet deposition. Although not statistically different, there was numerically less barnyardgrass seed produced from applications using the AITTJ60 and TTI60 dual-fan nozzle treatments compared to the AIXR and TTI single-fan nozzle counterparts, respectively (Table 4). The barnyardgrass seed production numerical trend resulting from applications using the various nozzle types generally mirror the spray deposit results from the water-sensitive card data, indicating that the increased number of droplet deposits may have aided in weed control efforts, at least to a small extent. Further research is needed to validate these observations. Overall, the best-suited nozzle for applications to control barnyardgrass in rice would be the XR, but drift concerns and herbicide regulations could prevent this from being an option in some cases. In these instances, the AITTJ60 dual-fan nozzle may be recommended as it had increased droplet size compared to the XR, and applications using the AITTJ60 resulted in similar barnyardgrass densities, numerically less barnyardgrass seed production, and the second greatest number of spray deposits on water-sensitive cards compared to all other nozzles tested.

For rice canopy coverage at both preflood and panicle differentiation rice stages, the row width main effect was significant (Table 3). At the preflood stage, rice canopy coverage decreased as the row width increased (Table 6). A 12 percentage-point increase in canopy coverage was observed from the 13-cm width compared to the 38-cm width. This rice canopy coverage trend for row width links to the barnyardgrass data previously discussed in which the greatest barnyardgrass density, panicles, and seed production occurred in the wider row width (Table 4). This early in the rice growth stages, the widest width provided the least amount of rice canopy closure allowing for greater weed escapes (Table 4). The greatest rice canopy coverage occurred in the 13-cm row width and resulted in the numerically lowest preflood barnyardgrass density (Tables 4 and 6). The wider row width likely allowed greater light transmittance to the soil and increased diurnal temperature fluctuations compared to narrower row widths for weeds to be able to germinate, emerge, and grow. Light is the most important suppression tactic compared to allelopathy or physical impedance for weed control (Norsworthy Reference Norsworthy2004; Teasdale Reference Teasdale1993; Thompson and Grime Reference Thompson and Grime1983). Teasdale (Reference Teasdale1995) saw similar results in corn where the crop canopy in a 38-cm row width reduced light transmittance 1 wk earlier than a 76-cm row width.

Table 6. Rice canopy coverage at preflood and panicle differentiation growth stages across site-years in 2022, and rough rice yield across all site-years. a, b

a Means followed by the same letter within a main effect and column are not different based on Tukey’s honestly significant difference test (α = 0.05).

b Three site-years were used for canopy coverage due to excessive weed pressure and software limitations and 7 site-years were used for rough rice yield.

c Row width is measured in centimeters.

The panicle differentiation rice stage is classified as the last vegetative stage and the start of the reproductive stage where vegetative production ceases and the seed head begins formation (Moldenhauer et al. Reference Moldenhauer, Counce and Hardke2022). At this growth stage, similar trends were observed to the preflood stage where the rice canopy coverage percentage decreased as row width increased; however, the 19- and 25-cm row widths resulted in the same canopy coverage percentage as the 13-cm row width (Table 6). The lowest canopy coverage percentage occurred in the 38-cm row width with a 10-percentage point decrease compared to the 13- and 19-cm widths. The canopy coverage of the 38-cm row width at the rice panicle differentiation growth stage provides further evidence as to why higher panicle counts and increased barnyardgrass seed production occurred in this row width. Light transmittance was able to penetrate the rice canopy more and likely increased diurnal temperature fluctuations allowing for greater weed escapes and enhanced weed growth (Norsworthy and Oliveira Reference Norsworthy and Oliveira2007; Thompson and Grime Reference Thompson and Grime1983). In soybean, 15- to 36-cm widths suppressed weeds by 92% because of a higher rate of canopy closure likely indicating similar potential in rice (Teasdale and Frank Reference Teasdale and Frank1983).

Across all site-years, no differences were observed from the main effects of row width and nozzle selection on rough rice yield. Despite the negative consequences observed on weed management, it would indicate that wider row widths may be feasible agronomically since there were no row width impacts on yield; although additional weed management efforts would be required for long-term success. This was previously observed in soybean where row width did not affect crop yield (Butts et al. Reference Butts, Norsworthy, Kruger, Sandell, Young, Steckel, Loux, Bradley, Conley, Stoltenberg, Arriaga and Davis2016). Conversely, a previous rice study planted in conventional cultivars did see an increase of rice yields in narrower rows compared to wider rows (Jones and Snyder Reference Jones and Snyder1987). One reason for the lack of a row width effect on rice yield in the present research may be due to the use of a hybrid cultivar which could have led to enhanced competitiveness against weeds allowing for similar rice yields across row widths (N.H. Reed, unpublished data). Greater density of barnyardgrass has been found to lower yields in a rice production system (Smith Reference Smith1968). This could mean that higher weed pressure in a field could lead to a greater impact from narrower row widths and increased yields compared to a wider row width. Even in lower weed pressure environments, additional weed control strategies would need to be considered for wider row widths to reduce weed seed from returning to the soil seedbank affecting long-term weed management.

Practical Implications

Overall, trends across site-years identified that as row width increased, barnyardgrass density, panicle counts, and seed production also increased. Throughout the study, better weed control and similar rice yields were observed in the 13-cm row width. The wider row width of 38-cm maintained similar yields and resulted in minimal weed densities and seed production compared to other row widths in a low weed-pressure environment. However, it should be acknowledged that the delayed planting dates within this research and resulting barnyardgrass emergence timings may have influenced the overall results. Future research should explore the role of rice planting date and barnyardgrass emergence timings paired with these cultural management efforts to further examine their impacts. Applications using smaller droplet size-producing nozzles like the XR resulted in greater coverage but are more prone to drift potential compared to the other nozzle types tested. Overall, there could be potential for applications with dual-fan nozzles, particularly the AITTJ60, to aid in weed control in some conditions. While it was observed that an increased number of deposits on water-sensitive cards occurred from applications from the AITTJ60 and TTI60 dual-fan nozzles, there was no consistent increased barnyardgrass control in the field studies compared to single-fan counterparts. Further field research evaluating these nozzle types should be conducted to investigate efficacy with other prominent weeds in rice. In conclusion, the 13-cm row width would be a viable choice to use in rice production to aid in weed management needs, but it would require additional equipment purchased by growers. The 19-cm row width would likely still be the most feasible because it is the industry standard, and producers would not be required to purchase new equipment for similar results regarding weed control, rice canopy coverage, and rice yield. An appropriate nozzle selection for all rice growing scenarios could not be made because of variable responses; therefore, selecting a row width based on equipment availability and weed densities was deemed more important for weed control and yield potential.

Acknowledgments

We thank the University of Arkansas System Division of Agriculture and the University of Arkansas Department of Crop, Soil, and Environmental Sciences; Arkansas Soybean Promotion Board; and Brad Davis, Troy Dillon, and Leah Collie.

Funding

This research was partially supported through Arkansas Rice Checkoff Program dollars administered by the Arkansas Rice Research and Promotion Board, and in part by the U.S. Department of Agriculture–National Institute of Food and Agriculture, Crop Protection and Pest Management under award number 2020-70006-32981.

Competing Interests

The authors declare they have no competing interests.

Footnotes

Associate Editor: Eric Webster, University of Wyoming

*

Current affiliation: Clinical Assistant Professor, Extension Weed Scientist, Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA.

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Figure 0

Table 1. Dv0.1, Dv0.5, and Dv0.9; driftable fines; and spray classification determined by using an Oxford Laser system in a spray chamber.a

Figure 1

Table 2. Average, maximum, and predicted droplet velocity for each nozzle type in the experimental laboratory study.a

Figure 2

Table 3. P-values from ANOVA for barnyardgrass density at preflood and preharvest rice stages, canopy coverage percentage for 2022, barnyardgrass seed production before harvest, and rough rice yield across site-years.a,b

Figure 3

Table 4. Barnyardgrass preflood density, preharvest panicle counts, and seed production across site-years.a,b

Figure 4

Table 5. Water-sensitive spray cards across 5 site-years in Arkansas including percent coverage and number of spray deposits for each nozzle used at the postemergence application.a,b,c

Figure 5

Table 6. Rice canopy coverage at preflood and panicle differentiation growth stages across site-years in 2022, and rough rice yield across all site-years.a,b