Herbicide resistance in turfgrass: a chance to change the future?

Brosnan, James T.; Barrett, Michael; Bhowmik, Pradip K.

doi:10.1017/wet.2020.28

Cited by 9 publications

(12 citation statements)

References 44 publications

(52 reference statements)

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“…Previous research has indicated that foramsulfuron and simazine are effective annual bluegrass control options (Johnson 1982; Toler et al 2007). However, over-reliance on simazine, glyphosate, and sulfonylurea herbicides such as foramsulfuron for annual bluegrass control has led to an increase in cases of annual bluegrass resistance to these herbicides (Breeden et al 2017; Brosnan et al 2020; Hutto et al 2004).…”

Section: Resultsmentioning

confidence: 99%

Zoysiagrass and weed response to herbicides during post-dormancy transition

2023

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Winter annual weeds begin to germinate as zoysiagrass enters winter dormancy in autumn. These weeds can suppress zoysiagrass shoot development the following spring through competition for sunlight, moisture, and nutrients. Previous research involving winter annual weed control in dormant turfgrass has been conducted primarily on bermudagrass, but less is known about how various herbicides used for this purpose will influence zoysiagrass post-dormancy transition. Two field studies were conducted at 7 site yr between 2016 and 2020 to evaluate 17 herbicide treatments that are typically marketed for broadleaf weed control in spring and 18 herbicide treatments that are typically marketed for annual bluegrass control during winter for effects on a variety of weeds and semi-dormant ‘Meyer’ and dormant ‘Zeon’ zoysiagrass, respectively. Glufosinate, glyphosate + simazine, and indaziflam + simazine controlled Persian speedwell over 90% and significantly higher than auxin-type and other herbicide combinations evaluated. The combination of simazine and glyphosate had better dandelion and Persian speedwell control than glyphosate applied alone. Glufosinate controlled dandelion, hairy bittercress, and Persian speedwell more effectively than glyphosate. In ‘Meyer’ zoysiagrass, glyphosate and glufosinate controlled annual bluegrass equivalently while in ‘Zeon’ zoysiagrass, glyphosate controlled annual bluegrass more than glufosinate. Foramsulfuron or simazine containing treatments controlled annual bluegrass >90%. Flumioxazin admixture with diquat, glufosinate, or glyphosate improved annual bluegrass control. Herbicide treatments containing diquat, glufosinate, glyphosate, and metsulfuron alone or in a tank-mix should not be applied to ‘Meyer’ zoysiagrass with 5% visual green turf cover due to high injury potential. In both studies, glufosinate was more injurious to ‘Meyer’ and ‘Zeon’ zoysiagrass than glyphosate. Overall, several herbicides that control annual bluegrass or broadleaf weeds can be safely applied to ‘Zeon’ zoysiagrass during dormancy or ‘Meyer’ zoysiagrass during post-dormancy transition.

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Section: Resultsmentioning

confidence: 99%

Zoysiagrass and weed response to herbicides during post-dormancy transition

2023

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“…Therefore, weed management is an essential part of any profession in turf. Turfgrass systems, such as golf courses and urban lawns, are high-input systems that require a considerable amount of time, money, and chemicals to maintain aesthetics and functionality at the levels demanded by the clientele of each of those systems (Alumai et al 2008; Brosnan et al 2020a; Marshall et al 2015; Robbins et al 2001). For those reasons, we investigate how the level of interaction with the public (i.e., their clientele) could be affecting responses of survey participants to key challenges and factors and their decision making when choosing new weed control tools.…”

Section: Resultsmentioning

confidence: 99%

“…In turfgrass management, the most dominant form of weed management is the use of herbicides (Watschke et al 2013). This reliance on herbicides is explained by the fact that turfgrass managers cannot use many methods of control common in other crop systems such as tillage or crop rotations (Brosnan et al 2020a). However, there have been multiple examples where herbicides have been restricted due to the public's potential exposure, such as in athletic fields (Brosnan et al 2014).…”

Section: New Technologies In Weed Managementmentioning

confidence: 99%

“…Turf includes residential, commercial, and institutional lawns, parks, athletic fields, and golf courses (Milesi et al 2005). With this large expanse of land, evolution of herbicide resistance has become a major concern for many turfgrass managers (Brosnan et al 2020a(Brosnan et al , 2020b, as herbicides are key for effective weed control at such large scales (Hull 1995). Weeds can cause dramatic changes in root and canopy microenvironments in turf, which can result in undesirable outcomes in turf quality (Schmidt and Blaser 1969).…”

Section: Introductionmentioning

confidence: 99%

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Views of RNAi approaches for weed management in turfgrass systems

et al. 2023

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Public concern regarding the use of herbicides in urban areas (e.g., golf courses, parks, lawns) is increasing. Thus, there is a need for alternative methods for weed control that are safe for the public, effective against weeds, and yet selective to turfgrass and other desirable species. New molecular tools such as RNAi have a potential to meet all those requirements, but before these technologies can be implemented, it is critical to understand the perceptions of key stakeholders to facilitate adoption as well as regulatory processes. With this in mind, turfgrass system managers, such as golf course superintendents and lawn care providers, were surveyed to gain insight to the perception and potential adoption of RNAi technology for weed management. Based on survey results, turfgrass managers believe that cost of weed management and time spent managing weeds are the main challenges faced in their fields. When considering new weed management tools, survey respondents were most concerned about cost, efficacy, and efficiency of a new product. Survey respondents were also optimistic toward RNAi for weed management and would either use this technology in their own fields or be willing to conduct research to develop RNAi herbicides. Although respondents believed that the general public would have some concerns about this technology, they did not believe this to be the most important factor for them when choosing new weed management tools. The need for new herbicides to balance weed control challenges and public demands is a central factor for turfgrass managers’ willingness to use RNAi-based weed control in turfgrass systems. They believe their clientele will be accepting of RNAi tools, although further research is needed to investigate how a wider range of stakeholders perceive RNAi tools for turfgrass management more broadly.

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“…Also, broadleaf weeds such as buckhorn plantain (Plantago lanceolata) developed resistance to 2,4-D (Heap, 2020). As a result, scientists and practitioners have called for more research into developing novel modes of action (Brosnan et al, 2020a). However, the truth of the matter is that no significant new MOA has been discovered since the 1980's and this fact, combined with the increasingly rapid evolution of herbicide resistance, has led some researchers to suggest that almost all existing herbicides may be unusable by 2050 (Westwood et al, 2018).…”

Section: Synthetic Herbicides and The Shift Towards Alternative Weed Control Strategiesmentioning

confidence: 99%

Towards strategies to manage weeds in turf without herbicides

Hahn

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The sportsturf industry in Europe is moving toward non-chemical broadleaf weed management.This thesis explored building a framework for alternative weed management strategies in turfgrass areas. Most importantly, I focused on the strategy of using suitable turfgrass species to maintain vigorous, dense turfgrass that is competitive against weeds. In light of climate change and stricter regulations regarding water, fertilizer and pesticide use, practitioners recently opted to use low input species such as Festuca spp. We therefore investigated the growth interfering capacity of 27 cultivars from five Festuca species (Chewings fescue [F. rubra L. ssp. fallax (Thuill.) Nyman], slender creeping red fescue [F. rubra L. ssp. littoralis (G.Mey.) Auquier] strong creeping red fescue [F. rubra L. ssp. rubra Gaudin], hard fescue [F.brevipila Tracey] and tall fescue [Schedonorus arundinaceus (Schreb.) Dumort., nom. cons.]) against three common broadleaf turfgrass weeds, namely clover (Trifolium repens L.), daisy (Bellis perennis L.) and yarrow (Achillea millefolium L.). In a climate chamber, 60 Festuca seeds were placed on water agar in a series of plastic containers for 30 days. Thirteen days after sowing, twenty weed seeds were introduced to each container, and germination and root length of those weeds was recorded. Interference by presence of Festuca species did not affect weed seed germination, but a pronounced negative effect on weed root growth was observed, with reductions of up to 85%. Clover was most severely affected in the presence of tall fescue, whereas all fescue species caused a similar reduction in root length for yarrow. Within most Festuca species we observed cultivar differences in growth interfering capacity. Weed species used in this experiment differed in their susceptibility to interference by fescue, with yarrow being more sensitive to growth interference by Festuca cultivars than clover. Daisy was most sensitive, and due to high mortality rates the species was removed from the experimental analysis. While we conducted the growth chamber screening, we also sowed a field trial with six cultivars representing each species used in the growth chamber experiment and four weed treatments including clover, daisy, yarrow and a mixture of these species in a randomized block design replicated by year. Weather conditions varied between years and caused different results, however cultivar Musica (Chewings fescue) and Barpearl (slender creeping red fescue) were least affected by weed growth over both years and resulted in acceptable visual sward quality.Manual counting of weeds with a 100-point quadrat in the above-described experiment was time consuming and limited the number of recordings. We therefore collected aerial multispectral images and applied random forest model (RF) machine learning algorithms to quantify vegetation cover using image analysis. Object-based classification using spectral features from a previous segmented orthoimage resulted in highest classification accuracy to detect weeds with 99% acc...

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Herbicide resistance in turfgrass: a chance to change the future?

Cited by 9 publications

References 44 publications

Zoysiagrass and weed response to herbicides during post-dormancy transition

Zoysiagrass and weed response to herbicides during post-dormancy transition

Views of RNAi approaches for weed management in turfgrass systems

Towards strategies to manage weeds in turf without herbicides

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