Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-14T07:25:46.424Z Has data issue: false hasContentIssue false

Flumioxazin effects on soybean canopy formation and soil-borne pathogen presence

Published online by Cambridge University Press:  21 April 2020

Grant L Priess*
Affiliation:
Graduate Student, Department of Crop Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Jason K Norsworthy
Affiliation:
Distinguished Professor, Department of Crop Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Trenton L Roberts
Affiliation:
Associate Professor, Department of Crop Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
Terry N Spurlock
Affiliation:
Assistant Professor/Extension Plant Pathologist, Division of Agriculture, University of Arkansas Monticello, Monticello, AR, USA.
*
Author for correspondence: Grant Lawson Priess, Altheimer Laboratory, 1366 West Altheimer Dr., Fayetteville, AR72704. Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Rapid crop canopy formation is important to reduce weed emergence and selection for herbicide resistance. Field experiments were conducted in 2017 and 2018 in Fayetteville, AR, to evaluate the impacts of PRE applications of flumioxazin on soybean injury, soybean density, canopy formation, and incidence of soil-borne pathogens. Flumioxazin was applied at 0, 70, and 105 g ai ha−1 to predetermined flumioxazin-tolerant and -sensitive soybean varieties. Flumioxazin at 70 g ha−1 injured the tolerant and sensitive varieties from 0% to 4% and 14% to 15%, respectively. When averaged over flumioxazin rates, density of the sensitive variety was only reduced in 2017 when activation of flumioxazin was delayed 7 d. Compared to the tolerant soybean variety, flumioxazin at 70 g ha−1 delayed the sensitive variety from reaching 20%, 40%, 60%, and 80% groundcover by 15, 16, 11, and 5 d, respectively. No delay in canopy closure (95% groundcover) was observed with either variety. Consequently, no yield loss occurred for either variety following a flumioxazin application. Flumioxazin did not impact root colonization of Didymella, Fusarium, Macrophomina, or Rhizoctonia. Pythium colonization of the soybean stem was increased by flumioxazin in 2017, but not in 2018. Increased injury, delays in percent groundcover, and an increase in Pythium colonization of soybean following a flumioxazin application may warrant the need for other soil-applied herbicides at soybean planting. Alternatively, soybean injury and delays in percent groundcover following flumioxazin applications can be mitigated through appropriate variety selection; however, comprehensive screening is needed to determine which varieties are most tolerant to flumioxazin.

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 in any medium, provided the original work is properly cited.
Copyright
© Weed Science Society of America, 2020

Introduction

Flumioxazin is a protoporphyrinogen oxidase-(PPO) inhibiting herbicide Group 14 that is used in soybean production for preplant or PRE control of small-seeded broadleaves and annual grass weeds (Taylor-Lovell et al. Reference Taylor-Lovell, Wax and Nelson2001, Reference Taylor-Lovell, Wax and Bollero2002; Yoshida et al. Reference Yoshida, Sakaki, Sato, Hada, Nagano and Oshio1991). PPO-inhibiting herbicides were used extensively to control Amaranthus ssp. before the release of glyphosate-resistant crops (Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barrett2012). Following the evolution of glyphosate-resistant Amaranthus ssp. the use of PPO-inhibiting herbicides increased (Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barrett2012). PPO-resistant Palmer amaranth [Amaranthus palmeri (S.) Wats.] was first confirmed in Arkansas in 2015 (Salas et al. Reference Salas, Burgos, Tranel, Singh, Glasglow, Scott and Nichols2016). Since then, PPO resistance has been confirmed in seven states (Heap Reference Heap2019; Varanasi et al. Reference Varanasi, Brabham, Norsworthy, Nie, Young, Houston, Barber and Scott2018). The evolution and spread of PPO-resistant Palmer amaranth has called into question the utility and importance of these herbicides for weed control in soybean.

Historically, flumioxazin has been used in the mid-south over sulfentrazone, another PPO-inhibiting herbicide, because of lower risk for injury to soybean (Taylor-Lovell et al. Reference Taylor-Lovell, Wax and Nelson2001). The gene controlling soybean tolerance to sulfentrazone has been determined and was once screened for in most commercialized soybean varieties (Swantek et al. Reference Swantek, Sneller and Oliver1998). It has been suggested that flumioxazin and sulfentrazone tolerance in soybean are closely linked but not synonymous; nonetheless, more research is needed to determine the mechanism of soybean tolerance to flumioxazin (Taylor-Lovell et al. Reference Taylor-Lovell, Wax and Bollero2002). Current commercialized soybean varieties are not screened for flumioxazin tolerance, resulting in uncertainty as to the risk for injury from the herbicide. Two factors that contribute to flumioxazin injury to soybean are varietal sensitivity and the splashing of herbicide onto emerged seedlings. The latter may be more severe when a suspected sensitive variety is grown (Yoshida et al. Reference Yoshida, Sakaki, Sato, Hada, Nagano and Oshio1991). Although herbicide injury at high levels can reduce yields (Kapusta et al. Reference Kapusta, Jackson and Mason1986), herbicide-induced injury may have alternative effects on soybean production such as delaying canopy formation (Nelson and Renner Reference Nelson and Renner2001) and increasing incidence of soil-borne pathogens infecting the seedling plants (Dann et al. Reference Dann, Diers and Hammerschmidt1999).

There is not a good understanding of the adverse effects that flumioxazin-induced herbicide injury has on soybean canopy formation. Soybean canopy formation or light interception by the crop can be measured using digital imagery (Purcell Reference Purcell2000). Light interception of 95% or greater is considered full canopy closure (Board et al. Reference Board, Karmal and Harville1992; Gardner et al. Reference Gardner, Pearce and Mitchell1985; Harder et al. Reference Harder, Sprague and Renner2007; Purcell Reference Purcell2000). An increase in soybean population or spatial distribution of soybean increases light interception, promoting early canopy formation (Bertram and Pederson Reference Bertram and Pedersen2004; Harder et al. Reference Harder, Sprague and Renner2007). Crop canopy development in turn affects weed emergence (Burnside and Moomaw Reference Burnside and Moomaw1977; Chandler et al. Reference Chandler, Shrestha and Swanton2001; Dalley et al. Reference Dalley, Kells and Renner2004; Harder et al. Reference Harder, Sprague and Renner2007; Légère and Schreiber Reference Légère and Schreiber1989; Nelson and Renner Reference Nelson and Renner1997; Nice et al. Reference Nice, Buehring and Shaw2001; Young et al. Reference Young, Young, Gonzini, Hart, Wax and Kapusta2001). An increase in canopy closure decreases weed seed germination by decreasing soil temperature and light quantity and quality that reaches the soil surface (Harder et al. Reference Harder, Sprague and Renner2007; Jha and Norsworthy Reference Jha and Norsworthy2009; Yelverton and Coble Reference Yelverton and Coble1991). Changes in crop canopy formation have the potential to impact weed emergence and disease presence by altering environmental conditions surrounding the crop (Jha and Norsworthy Reference Jha and Norsworthy2009; Levene et al. Reference Levene, Owen and Tylka1998).

PPO-inhibiting herbicides have been shown in the past to affect pathogen presence and disease severity (Dann et al. Reference Dann, Diers and Hammerschmidt1999; Levene et al. Reference Levene, Owen and Tylka1998; Sanogo et al. Reference Sanogo, Yang and Lundeen2001). Lactofen, a PPO-inhibiting herbicide, has been found to reduce soybean stem rot [Sclerotinia sclerotiorum (Lib.) de Bary] severity by 40% to 60% (Dann et al. Reference Dann, Diers and Hammerschmidt1999). A high level of glyceollin was found in soybean leaves treated with lactofen. It is believed that an increase in glyceollin production caused by lactofen injury to soybean is responsible for the control of soybean stem rot (Dann et al. Reference Dann, Diers and Hammerschmidt1999).

Another PPO-inhibiting herbicide, acifluorfen, increases glyceollin in soybean, resulting in a decline in soybean cyst nematode egg production by 50% to 60% (Levene et al. Reference Levene, Owen and Tylka1998). This type of interaction between herbicide and pest is considered an indirect response (Duke et al. Reference Duke, Wedge, Cerdeira and Matallo2007). An indirect response is when the herbicide causes a physiological change within the plant that increases tolerance or changes the environment to the point that it is unsuitable for the disease.

Flumioxazin and sulfentrazone have the ability to reduce root colonization of root rot (Pythium arrhenomanes). Flumioxazin has been shown to reduce in vitro mycelium growth of P. arrhenomanes and P. aphanidermatum (Daugrois et al. Reference Daugrois, Hoy and Griffin2005). This type of interaction is described as a direct response of a herbicide on pathogens (Duke et al. Reference Duke, Wedge, Cerdeira and Matallo2007). A direct relationship between herbicide and disease is the ability of the herbicide to inhibit growth and reproduction by the compound itself (Duke et al. Reference Duke, Wedge, Cerdeira and Matallo2007). Herbicide and disease interactions are complex, requiring the need for additional studies to understand the possible underlying benefits or negative impacts on a cropping system. An area of study that is not thoroughly researched is how early season flumioxazin-induced injury to soybean affects the crop, including incidence of soil-borne pathogens. The objective of this research was to determine whether flumioxazin resulted in delays in soybean canopy development and affected the incidence of soil-borne pathogens.

Materials and Methods

Field experiments were conducted in 2017 and 2018 at the University of Arkansas-Agricultural Research and Extension Center, in Fayetteville, AR. The experiments were planted on June 15, 2017, and May 11, 2018. The soil at the site of the experiment was a Leaf silt loam (Fine, mixed, active, thermic Typic, Albaquults) with 31% sand, 50% silt, 18% clay, 1.4% organic matter, and pH 6.5 and 6.0 on those dates, respectively. In both years, the fields were prepared prior to planting by disking and hipping beds that were 91 cm wide. The plot size was 7.6 m long and 3.6 m wide. The experiment was conducted in adjacent field sites each year. Trials were planted in fields where soybean was grown the previous year to increase the likelihood that soil-borne pathogens were present.

The experiment was designed as a two-factor factorial randomized complete block design with four replications. The factors were soybean variety [Credenz 4818LL and Credenz 4748LL (Bayer CropScience, Triangle Park, NC 27709)] and flumioxazin (Valor 51WG, Valent USA, Walnut Creek, CA 94596) at three rates (0, 70, 105 g ai ha−1). A greenhouse screening was conducted prior to field experimentation to categorize the two indeterminate soybean varieties. The Credenz 4818LL was flumioxazin-tolerant and Credenz 4748LL was flumioxazin-sensitive. Seed treatments were applied to simulate practices commonly used in soybean production. Both varieties of soybean were treated with commercial seed treatments PONCHO®/VOTiVO®, which contains 40.3% clothianidin, 8.1% Bacillus firmus I-1582; ILeVO®, which contain 48.4% of fluopyram; and REDIGO® 480, which contains 41% prothioconazole and 28.35% metalaxyl, also commonly known as ALLEGIANCE®-FL. Soybean is commonly categorized into medium, medium bushy, and bushy to correctly describe growing characteristics of varieties. CDZ 4748LL is considered a medium bushy and CDZ 4818LL would be considered bushy. Soybean varieties were seeded at 346,000 seed ha−1 at a 2.2-cm depth. The experiments were kept weed free with glufosinate, S-metolachlor, and hand-weeding. Visual estimates of soybean injury to flumioxazin were rated 21 d after planting (DAP) on a scale of 0% to 100%, with 0% being no crop injury and 100% being crop death (Frans and Talbert Reference Frans, Talbert and Truelove1977).

To determine soybean canopy formation over time, photos were taken weekly after planting until soybean reached canopy closure with an unmanned aerial vehicle (DJI Phantom 4 Pro equipped with a 1080p gimbal-mounted camera; Shenzhen, China, 518057). Photographs were taken of the whole trial and were divided into plots using the software program Field Analyzer (https://www.turfanalyzer.com/). Field analyzer produced a proportion of green pixels for the center two rows within the four-row treated plot; thus, an accurate representation of percent groundcover could be calculated (Purcell Reference Purcell2000). Canopy height and width of five soybean plants in the center two rows of each plot were also recorded on a weekly basis. The measurements were then averaged by plot, and soybean volume was calculated using the following equation $\left( {\pi \times plant{\mkern 1mu} hieght} \right){\left( {plant{\mkern 1mu} width \div 2} \right)^2}$ (Norsworthy Reference Norsworthy2004). Soybean grain yield was determined following physiological maturity by harvesting the center two rows in each plot using a small-plot combine and then adjusting moisture to 13%.

When soybean reached V1 in the nontreated plots, 10 plants were sampled from the outside two rows of the plots that received flumioxazin at 107 g ha−1 and from nontreated plots. These plants were dug from the plots, with roots remaining intact, and placed in sterile plastic bags. All samples were placed in a cooler and immediately transported to the laboratory. Individual plants were cut 1.5 cm below and above the soil line, keeping the portion of the soybean plant that contained the soil line. The samples remained grouped by plot and were washed with running water for 20 min. Samples were then soaked in a 6% 87.5 ml L−1 bleach dilution for 30 s. Soybean stems were then placed in 100-mm-diameter petri dishes containing agar (part number 97064-336, VWR International, Arlington Heights, IL 60004) for 3 to 4 d. One sample of hyphal growth that differed in morphological characteristics within a petri dish was selected and transferred by removal using a flame-sterilized scalpel to petri dishes containing an amended potato dextrose agar medium PDArad (18 g Difco potato dextrose agar, 10 mg and 250 mg of the antibiotics rifampicin and ampicillin, respectively) and the miticide fenpropathrin (0.14 mg ai L−1; Danitol 2.4 EC, Valent Chemical Co. Mahomet, IL 59639). Isolates of similar morphological characteristics were grouped 7 to 8 d after the transfers were made. The number of isolates per group was recorded. Isolates of the same group were randomly selected and sent for DNA analysis at the University of Arkansas Plant Pathology laboratory in Monticello, AR.

Pure cultures of fungi and oomycete isolates were obtained and transferred to the Monticello laboratory using the method described previously. Representative pure cultures of fungi and oomycete were randomly selected from each group for DNA analysis. Deoxyribonucleic acid (DNA) was collected from pure cultures by scraping 0.25 ml to 0.5 ml of mycelia and spores from the tops of colonies using a sterile scalpel blade. Mycelia and spores were placed into a microfuge tube, where 500 µl of 0.9% (w/v) NaCl prepared with sterile distilled water was added. Genomic DNA extractions were obtained by using a Norgen Biotek Genomic DNA Purification kit (Kit 27300, Norgen Biotek Corp., Thorold, ON, L2V 4Y6 Canada). Polymerase chain reaction was achieved by following the GoTaq Green Master Mix 2X (Promega Corp., Madison, WI 53711) using a 25-µl reaction and following the accompanying amplification guidelines. Primers used in reactions were internal transcribed spacer-4 (ITS-4; reverse) and ITS-5 (forward; ThermoFisher Scientific, Waltham, MA 02454). Confirmation of amplification was determined by gel electrophoresis, followed by soaking in GelRed (Biotium, Freemont, CA 94538) nucleic acid stain for 20 min, and viewing the gel on an ultraviolet light box. Digestion of excess nucleotides was achieved by using the ExoSAP-IT protocol (catalog number 78201, ThermoFisher Scientific). Quantification of DNA concentrations were achieved by using a microvolume spectrophotometer (SimpliNano, GE Health Care Life Sciences, Logan, UT 84321). Samples were sent premixed to Eurofins Genomics (Louisville, KY 40299) for sequencing following standard protocol. Sequences were trimmed, aligned using ClustalW in Bio-Edit (version 7.0.5, Ibis Therapeutics, Carlsbad, CA 92008), and identified using the nucleotide basic local alignment search tool in GenBank (BLASTn, NCBI, Bethesda, MD 20892).

Statistical Analysis

Data collected for soybean volume and percent groundcover were analyzed similarly. Data were regressed in the Fit Curve platform of JMP 14.1 (SAS Institute Inc., SAS Campus Drive, Cary, NC 27513). A mechanistic curve {y = a [1 – b * EXP (-c*days)]} where a = asymptote, b = scale, and c = growth was fit to the soybean volume and percent groundcover data by days after planting in a similar manner to that used in other research (SAS Institute 2014). Parameters to fit the mechanistic growth curves are found in Table 1. From the mechanistic curves, inverse predictions of the days until soybean achieved 20%, 40%, 60%, 80%, 95%, and 1,000, 3,000, and 5,000 cm3 were predicted for percent groundcover and soybean volume, respectively. The 95% confidence interval for the mean of the inverse prediction was used to differentiate herbicide treatment and variety effects.

Table 1. Parameters of the mechanistic growth curve {y = a [1 – b * EXP (-c*days)]} where a = asymptote, b = scale, and c = growth rate, fit to groundcover and soybean volume data from 2017 and 2018.

The percent injury data, collected 21 DAP, were not normally distributed; therefore, injury data were subjected to log transformation, determined by the lambda value of a box cox test (Box and Cox Reference Box and Cox1964) and back-transformed for data interpretation. Soybean density, pathogen isolates, and yield data relative to the nontreated plants of the same variety passed all assumptions of ANOVA. Site years were analyzed separately due to differences in soybean emergence prior to a rainfall event that activated the herbicide. In 2017, the experiment went 7 d without rainfall, and in that time period, soybean emerged prior to herbicide activation (data not shown), thus impacting the amount of herbicide injury observed. In 2018, flumioxazin was activated by rainfall prior to soybean emergence (data not shown). Means were separated using a Fisher’s protected LSD test with an α value of 0.05. P-values for each ANOVA are displayed in Table 2.

Table 2. Results of the ANOVA conducted on soybean injury, soybean density, and relative yield are displayed by P-values of all factors initially tested in the analysis.

Results and Discussion

Soybean Injury

In general, injury levels in 2017 were higher than in 2018 likely because of the 7-d delay in herbicide activation versus the 4-d delay in the second year. In both site years, a significant interaction between variety and flumioxazin rate was observed (P < 0.0001 and P = 0.0002 in 2017 and 2018, respectively; Table 2). Similarly, the sensitive variety CDZ 4748LL suffered greater injury from flumioxazin than the tolerant CDZ 4818LL (Table 3), further validating that soybean has differing levels of flumioxazin tolerance as hypothesized by Taylor-Lovell et al. (Reference Taylor-Lovell, Wax and Nelson2001). The sensitive and tolerant soybean varieties displayed 14% to 15% and 0% to 4% visible injury, respectively, due to an application of flumioxazin at 70 g ha−1. Injury increased as flumioxazin rate increased. Flumioxazin applied at 105 g ha−1 to the sensitive and tolerant varieties caused 21% to 30% and 4% to 8% visible injury, respectively, at 21 DAP. The difference in variety tolerance affected the injury level observed. The delay in activation in 2017 increased the chance for herbicide injury to soybean to occur. Yoshida et al. (Reference Yoshida, Sakaki, Sato, Hada, Nagano and Oshio1991) concluded that a delay in activation allows for soybean to emerge prior to the herbicide infiltrating the soil surface, resulting in a splashing of herbicide onto emerged soybean when subsequent rainfall occurs. A delay in herbicide activation may be key in determining variety tolerance of soybean to flumioxazin at labeled field use rates. Through knowledge of variety sensitivity to flumioxazin, injury to soybean may be mitigated when activation of the herbicide is delayed.

Table 3. Percent visual estimates of injury to soybean 21 d after planting as influenced by the interaction of flumioxazin rate by varietal tolerance to flumioxazin.

a Within column, means followed by different letters are different according to Fisher’s protected LSD test at α = 0.05.

Soybean Density

Soybean density was not affected by the interaction of flumioxazin rate by variety in 2017 or 2018 (P = 0.8223 and P = 0.4529, respectively; Table 2). However, the only significant main effect was variety in 2017 (P = 0.0046). In 2017, there was a 19% reduction in density of the sensitive soybean variety compared with the nontreated, averaged over flumioxazin rates (Table 4). The tolerant variety showed no reduction in density caused by applications of flumioxazin in either site year (Table 4). In 2018, soybean was planted and then went 4 d without an activating rainfall. Soybean seedlings had not yet emerged at the time of herbicide activation, eliminating the effect of herbicide splash onto soybean as a possible mechanism of stand reduction. Yoshida et al. (Reference Yoshida, Sakaki, Sato, Hada, Nagano and Oshio1991) observed that a delay in flumioxazin activation until after soybean emergence increased the splashing of herbicide onto cotyledons, resulting in an increase in crop injury. The lack of emerged plants in 2018 compared with the already emerged plants in 2017 at the time of flumioxazin activation likely resulted in some plant death by the time of stand count assessments, explaining why the treated sensitive soybean variety had reduced density in 2017 but not in 2018.

Table 4. Relative soybean density as affected by variety in 2017 and 2018 at Fayetteville, Arkansas.

a The nontreated plots of CDZ 4818LL and CDZ 4748LL in 2017 had soybean densities of 276,640 and 298,870 plants ha−1, respectively and in 2018 had soybean densities of 266,760 and 251,000 plants ha−1, respectively.

b Within column, means followed by different letters are different according to Fisher’s protected LSD test at α = 0.05.

Soybean Volume

There was no statistical delay in the number of days soybean required to reach the selected soybean volumes in both the sensitive and tolerant varieties (Table 5). Soybean has the ability to increase branching when soybean population per area is reduced (Shibles and Weber Reference Shibles and Weber1965), which may explain the lack of effect on soybean volume in 2017 for the sensitive variety. Also, measuring only five plants per plot may have made it difficult to detect subtle differences in canopy volume between treatments.

Table 5. The number of days predicted for soybean to reach a volume of 1,000, 3,000, and 5,000 cm3. Differences between treatments occur when the 95% confidence intervals of the mean do not overlap.

a The number of days for the soybean to reach the predicted soybean volume (cm3)

b The 95% confidence interval of the true (population mean) number of days for soybean to reach each predicted soybean volume

Percent Groundcover

In the two site years within this study, early-season groundcover of the sensitive soybean was delayed by a flumioxazin application (Table 6). An application of flumioxazin at 70 g ai ha−1 increased the number of days required for sensitive soybean to reach 20%, 40%, 60%, and 80% groundcover by 15, 16, 11, and 5 d, respectively. No delay in canopy formation was observed in the tolerant variety following a flumioxazin application at 70 or 105 g ha−1. Additionally, flumioxazin did not affect the time (days) to 95% groundcover in either the sensitive and tolerant variety. Thus, flumioxazin applied to a sensitive or tolerant variety will not delay canopy closure; canopy formation could be delayed when flumioxazin is applied to a sensitive variety, which could increase weed emergence. Similarly, Nelson and Renner (Reference Nelson and Renner2001) observed soybean injury following a POST herbicide application delayed leaf area index, soybean growth, and development. A delay in soybean canopy formation is undesirable, as it may lead to an increase in weed emergence (Jha and Norsworthy Reference Jha and Norsworthy2009). In turn, this rise in weed emergence increases selection for herbicide resistance (Norsworthy et al. Reference Norsworthy, Ward, Shaw, Llewellyn, Nichols, Webster, Bradley, Frisvold, Powles, Burgos, Witt and Barrett2012).

Table 6. The number of days predicted for soybean treated with flumioxazin at 0, 70, and 105 g ai ha−1 to reach 20%, 40%, 60%, 80%, and 95% groundcover.

a The number of days for soybean to reach the predicted percent groundcover (%).

b The 95% confidence limits of the number of days required for soybean to reach the predicted percent groundcover.

* Designates the confidence limits of a treatment not overlapping with the nontreated of the same variety and groundcover (%).

** Shows significant differences due to nonoverlapping confidence intervals of same treatment and same percent groundcover between varieties.

Soybean Yield

The interaction of variety by flumioxazin rate was not significant in 2017 or 2018 (P = 0.3293 and P = 0.3856, respectively; Table 2). Likewise, the main effects in 2017 and 2018 of soybean variety (P = 0.3388 and P = 0.3284, respectively) and flumioxazin rate (P = 0.9052 and P = 0.9452, respectively) did not affect soybean yield (Table 2). Similarly, Taylor-Lovell et al. (Reference Taylor-Lovell, Wax and Nelson2001) did not observe yield loss in 15 soybean varieties treated with flumioxazin at 105 g ha−1, even when 59% injury was observed soon after emergence.

Pathogen Response

In 2018, soybean root colonization of pathogens was not affected by an application of flumioxazin application rate. Macrophomina, a possible causal agent of charcoal rot in soybean (Khan Reference Khan2007), was found to be influenced by variety selection in both 2017 and 2018 (P = 0.0132 and P = 0.0196, respectively; Table 7). Thus, soybean varietal tolerance to Macrophomina colonization may be present as noted in a previous study (Pearson et al. Reference Pearson, Schwenk, Crowe and Kelly1984). In 2017, both variety and flumioxazin rate affected the degree of soybean stem colonization by Pythium. Pythium is the causal agent for root rot in soybean (Hendrix and Campbell Reference Hendrix and Campbell1973). The flumioxazin-tolerant soybean variety (CDZ 4818LL) had an average of 0.67 isolates of Pythium per 10 soybean plants, and the sensitive variety had 1.77 isolates per 10 plants (data not shown). Flumioxazin increased the likelihood of Pythium colonizing the stems of soybean. The nontreated averaged 0.46 isolates of Pythium per 10 plants, whereas isolates found in plots treated with flumioxazin increased to an average number of isolates of 1.94 per 10 plants (data not shown). The increase of Pythium is contrary to in vitro studies that showed that flumioxazin has a direct effect on reducing mycelium growth of Pythium (Daugrois et al. Reference Daugrois, Hoy and Griffin2005).

Table 7. The effects of variety, flumioxazin rate, and the interaction of variety × flumioxazin rate on the incidence of soybean root colonization of soil-borne pathogens.

a Abbreviation: na, not applicable.

It was hypothesized that the splashing of flumioxazin on to soybean stems near the soil line results in necrotic wounds, which allowed for an increase in Pythium colonization. It does not appear that flumioxazin increased glyceollin in soybean to compensate for the injury at levels similar to those caused by POST application of lactofen and acifluorfen (Dann et al. Reference Dann, Diers and Hammerschmidt1999; Levene et al. Reference Levene, Owen and Tylka1998). Soybean injury from flumioxazin also resulted in delays in growth, as observed in the percent groundcover data (Table 5). Delays in growth caused by environmental stresses can contribute to an increase in root rot severity (Kirkpatrick et al. Reference Kirkpatrick, Rothrock, Rupe and Gbur2006). Thus, the delay in soybean growth resulting from flumioxazin-induced injury could have contributed to an increase in Pythium colonization.

Conclusions and Practical Implications

Preemergence flumioxazin injury had season-long effects on the growth of a sensitive soybean variety, and full recovery was not achieved until late in the season when soybean approached canopy closure. Although the herbicide injury to soybean did not impact yield, other monetary and cultural aspects may be directly affected. Delaying canopy formation of the sensitive variety by 15 d would expose the weed seedbank to environmental conditions that were conducive for emergence, thus potentially increasing the need for additional weed control measures. Increased weed emergence through reducing crop competitiveness via herbicide-induced injury to soybean may place added selection for herbicide resistance on POST herbicides.

Flumioxazin injury to soybean can be mitigated through tolerant varietal selection; however, large-scale flumioxazin variety screening is needed to make this practical. Soybean root colonization of Didymella, Fusarium, Macrophomina, and Rhizoctonia were not affected by an application of flumioxazin, but Pythium colonization of soybean roots was increased when flumioxazin was applied in one of two years. The necrotic wounding following a delayed activation of flumioxazin, as observed in 2017, may lead to an increase in Pythium colonization. For soybean varieties that are sensitive to flumioxazin, the risk for crop injury, delayed canopy formation, and increased disease incidence likely outweighs any weed control benefit from the herbicide, especially in areas infested with PPO-resistant Amaranthus spp.

Acknowledgments

Funding for this research was provided by the Arkansas Soybean Promotion Board. No conflicts of interest have been declared.

Footnotes

Associate Editor: Prashant Jha, Iowa State University

References

Bertram, MG, Pedersen, P (2004) Adjusting management practices using glyphosate-resistant soybean varieties. Agron J 96:462468 Google Scholar
Board, JE, Karmal, M, Harville, BG (1992) Temporal importance of greater light interception to increased yield in narrow-row soybean. Agron J 84:575579 CrossRefGoogle Scholar
Box, GEP, Cox, DR (1964) Analysis of transformations. J Roy Stat Soc B Met 26:211252 Google Scholar
Burnside, OC, Moomaw, RS (1977) Control of weed in narrow-row soybeans. Agron J 69:793796 CrossRefGoogle Scholar
Chandler, K, Shrestha, A, Swanton, CJ (2001) Weed seed return as influenced by the critical weed-free period and row spacing of no-till glyphosate-resistant soybean. Plant Sci 81:877–672Google Scholar
Dalley, CD, Kells, JJ, Renner, KA (2004) Effect of glyphosate application timing and row spacing on corn (Zea mays) and soybean (Glycine max) yields. Weed Technol 18:165176 CrossRefGoogle Scholar
Dann, EK, Diers, BW, Hammerschmidt, R (1999) Suppression of Sclerotina stem rot of soybean by lactofen herbicide treatment. Phytopathology 89:598602 CrossRefGoogle Scholar
Daugrois, JH, Hoy, JW, Griffin, JL (2005) Protoporphyrinogen oxidase inhibitor herbicide effects on Pythium root rot of sugarcane, Pythium species, and the soil microbial community. Phytopathology 95:220226Google Scholar
Duke, SO, Wedge, DE, Cerdeira, AL, Matallo, MB (2007) Herbicide effects on plant disease. Outlooks Pest Manag 18:3640 CrossRefGoogle Scholar
Frans, RE, Talbert, RE (1977) Design of field experiments and the measurement and analysis of plant responses. Pages 1523 in Truelove, B, ed. Research Methods in Weed Science. 2nd ed. Auburn, TX: Southern Weed Science SocietyGoogle Scholar
Gardner, FP, Pearce, RB, Mitchell, RL (1985) Physiology of Crop Plants. Ames, Iowa: Iowa State Press. Pp 3156 Google Scholar
Harder, DB, Sprague, CL, Renner, KA (2007) Effect of soybean row width and population on weeds, crop yield, and economic return. Weed Technol 21:744752 CrossRefGoogle Scholar
Heap, IM (2019). The International Survey of Herbicide Resistant Weeds. http://www.weedscience.com Accessed: January 2, 2019Google Scholar
Hendrix, FF, Campbell, WA (1973) Pythium as plant pathogens. Annu Rev Phythopathol 11:7798 Google Scholar
Jha, P, Norsworthy, JK (2009) Soybean canopy and tillage effects on emergence of Palmer amaranth (Amaranthus palmeri) from a natural seed bank. Weed Sci 57:644651 CrossRefGoogle Scholar
Kapusta, G, Jackson, LA, Mason, DS (1986) Yield response of weed-free soybeans (Glycine max) to injury from postemergence broadleaf herbicides. Weed Sci 34:304307 Google Scholar
Khan, SK (2007) M. phaseolina as causal agent for charcoal rot of sunflower. Mycopathology 5:111118 Google Scholar
Kirkpatrick, MT, Rothrock, CS, Rupe, JC, Gbur, EE (2006) The effect of Pythium ultimum and soil flooding on two soybean varieties. Plant Dis 90:597602 CrossRefGoogle Scholar
Légère, A, Schreiber, MM (1989) Competition and canopy architecture as affected by soybean (Glycine max) row width and density of redroot pigweed (Amaranthus retroflexus). Weed Sci 37:10291038 CrossRefGoogle Scholar
Levene, BC, Owen, MDK, Tylka, GL (1998) Response of soybean cyst nematodes and soybeans (Glycine max) to herbicides. Weed Sci 46:264270 CrossRefGoogle Scholar
Nelson, KA, Renner, KA (1997) Weed management in wide- and narrow-row glyphosate-resistant soybean. J Prod Agric 12:460465 CrossRefGoogle Scholar
Nelson, KA, Renner, KA (2001) Soybean growth and development as affected by glyphosate and postemergence herbicide tank mixtures. Agron J 93:428434 CrossRefGoogle Scholar
Nice, GR, Buehring, NW, Shaw, DR (2001) Sicklepod (Senna obtusifolia) response to shading, soybean (Glycine max) row spacing, and population in three management systems. Weed Technol 15:155162 CrossRefGoogle Scholar
Norsworthy, JK (2004) Conventional soybean plant and progeny response to glyphosate. Weed Technol 18:527531 CrossRefGoogle Scholar
Norsworthy, JK, Ward, SM, Shaw, DR, Llewellyn, R, Nichols, RL, Webster, TM, Bradley, KW, Frisvold, G, Powles, SB, Burgos, NR, Witt, W, Barrett, M (2012) Reducing the risks of herbicide resistance: Best management practices and recommendations. Weed Sci 60(SP1):3162 CrossRefGoogle Scholar
Pearson, CAS, Schwenk, FW, Crowe, FJ, Kelly, K (1984) Colonization of soybean roots by Macrophomina phoseolina. Plant Dis 68:10861088 CrossRefGoogle Scholar
Purcell, LC (2000) Soybean canopy coverage and light interception measurement using digital imagery. Crop Sci 40:834837 CrossRefGoogle Scholar
SAS Institute (2014) Specialized Models. SAS Institute. 11th ed. Cary, NC: SAS Institute. Pp 101107 Google Scholar
Salas, RA, Burgos, NR, Tranel, PJ, Singh, S, Glasglow, L, Scott, RC, Nichols, RL (2016) Resistance to PPO-inhibiting herbicides in Palmer amaranth from Arkansas. Pest Manage Sci 72:864869 Google ScholarPubMed
Sanogo, S, Yang, XB, Lundeen, P (2001) Field response of glyphosate-tolerant soybean to herbicides and sudden death syndrome. Plant Dis 85:773779 CrossRefGoogle Scholar
Shibles, RM, Weber, CR (1965) Leaf area, solar radiation interception and dry matter production by soybeans. Crop Sci 5:575578 CrossRefGoogle Scholar
Swantek, JM, Sneller, CH, Oliver, LR (1998) Evaluation of soybean injury from sulfentrazone and inheritance of tolerance. Weed Sci 46:271277 CrossRefGoogle Scholar
Taylor-Lovell, S, Wax, LM, Bollero, G (2002) Preemergence flumioxazin and pendimethalin and postemergence herbicide systems for soybean (Glycine max ). Weed Technol 16:502511 CrossRefGoogle Scholar
Taylor-Lovell, S, Wax, LM, Nelson, R (2001) Phytotoxic response and yield of soybean (Glycine max) varieties treated with sulfentrazone or flumioxazin. Weed Technol 15:95102 CrossRefGoogle Scholar
Varanasi, VK, Brabham, C, Norsworthy, JK, Nie, H, Young, BG, Houston, M, Barber, T, Scott, RC (2018) A statewide survey of PPO-inhibitor resistance and the prevalent target-site mechanism in Palmer amaranth (Amaranthus palmeri) accessions from Arkansas. Weed Sci 66:149158 CrossRefGoogle Scholar
Yelverton, FH, Coble, HD (1991) Narrow row spacing and canopy formation reduces weed resurgence in soybean (Glycine max). Weed Sci 25:7378 Google Scholar
Yoshida, RM, Sakaki, R, Sato, T, Hada, E, Nagano, H, Oshio, Kamoshita K (1991) A new N-phenyl phthalimide herbicide. Crop Prot 1:6975 Google Scholar
Young, BG, Young, GM, Gonzini, LC, Hart, SE, Wax, LM, Kapusta, G (2001) Weed management in narrow- and wide-row glyphosate-resistant soybean (Glycine max). Weed Technol 15:112121 CrossRefGoogle Scholar
Figure 0

Table 1. Parameters of the mechanistic growth curve {y = a [1 – b * EXP (-c*days)]} where a = asymptote, b = scale, and c = growth rate, fit to groundcover and soybean volume data from 2017 and 2018.

Figure 1

Table 2. Results of the ANOVA conducted on soybean injury, soybean density, and relative yield are displayed by P-values of all factors initially tested in the analysis.

Figure 2

Table 3. Percent visual estimates of injury to soybean 21 d after planting as influenced by the interaction of flumioxazin rate by varietal tolerance to flumioxazin.

Figure 3

Table 4. Relative soybean density as affected by variety in 2017 and 2018 at Fayetteville, Arkansas.

Figure 4

Table 5. The number of days predicted for soybean to reach a volume of 1,000, 3,000, and 5,000 cm3. Differences between treatments occur when the 95% confidence intervals of the mean do not overlap.

Figure 5

Table 6. The number of days predicted for soybean treated with flumioxazin at 0, 70, and 105 g ai ha−1 to reach 20%, 40%, 60%, 80%, and 95% groundcover.

Figure 6

Table 7. The effects of variety, flumioxazin rate, and the interaction of variety × flumioxazin rate on the incidence of soybean root colonization of soil-borne pathogens.