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BioOne Review: Confirmation of Resistance to Herbicides and Evaluation of Resistance Levels Author(s): Nilda Review: Confirmation of Resistance to Herbicides and Evaluation of Resistance Levels

BioOne Review: Confirmation of Resistance to Herbicides and Evaluation of Resistance Levels Author(s): Nilda Review: Confirmation of Resistance to Herbicides and Evaluation of Resistance Levels
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  BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, researchlibraries, and research funders in the common goal of maximizing access to critical research. Review: Confirmation of Resistance to Herbicides and Evaluation of ResistanceLevels Author(s): Nilda R. Burgos , Patrick J. Tranel , Jens C. Streibig , Vince M. Davis , Dale Shaner , Jason K.Norsworthy , and Christian RitzSource: Weed Science, 61(1):4-20. 2013.Published By: Weed Science Society of AmericaDOI: BioOne ( is a nonprofit, online aggregation of core research in the biological, ecological, andenvironmental sciences. BioOne provides a sustainable online platform for over 170 journals and books publishedby nonprofit societies, associations, museums, institutions, and presses.Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiriesor rights and permissions requests should be directed to the individual publisher as copyright holder.  Review: Confirmation of Resistance to Herbicides and Evaluation ofResistance Levels Nilda R. Burgos, Patrick J. Tranel, Jens C. Streibig, Vince M. Davis, Dale Shaner, Jason K. Norsworthy, andChristian Ritz*  As cases of resistance to herbicides escalate worldwide, there is increasing demand from growers to test for weed resistanceand learn how to manage it. Scientists have developed resistance-testing protocols for numerous herbicides and weedspecies. Growers need immediate answers and scientists are faced with the daunting task of testing an increasingly largenumber of samples across a variety of species and herbicides. Quick tests have been, and continue to be, developed toaddress this need, although classical tests are still the norm. Newer methods involve molecular techniques. Whereas theclassical whole-plant assay tests for resistance regardless of the mechanism, many quick tests are limited by specificity to anherbicide, mode of action, or mechanism of resistance. Advancing knowledge in weed biology and genomics allows forrefinements in sampling and testing protocols. Thus, approaches in resistance testing continue to diversify, which canconfound the less experienced. We aim to help weed science practitioners resolve questions pertaining to the testing of herbicide resistance, starting with field surveys and sampling methods, herbicide screening methods, data analysis, and,finally, interpretation. More specifically, this article discusses approaches for sampling plants for resistance confirmationassays, provides brief overviews on the biological and statistical basis for designing and analyzing dose–response tests,and discusses alternative procedures for rapid resistance confirmation, including molecular-based assays. Resistanceconfirmation procedures often need to be slightly modified to suit a specific situation; thus, the general requirements aswell as pros and cons of quick assays and DNA-based assays are contrasted. Ultimately, weed resistance testing research, aswell as resistance management decisions arising from research, needs to be practical, feasible, and grounded in science-based methods. Key words:  Dose–response assay, molecular-based assay, quick tests, sampling, whole-plant assay. Resistance to herbicides is undoubtedly among the primary concerns in modern agriculture. Since the first report of resistance to 2,4-D in 1957 in wild carrot ( Daucus carota  L.)(Switzer 1957), resistance to herbicides has ballooned toinclude over 200 species worldwide involving at least 20modes of action (Heap 2012). Accurate and timely diagnosisis crucial to resistance management and mitigation. Ideally,growers should be managing crop production fields to delay the onset of resistance to herbicides or avert weed populationshifts that would make weed management difficult oruneconomical. In reality, growers adopt the most convenientand economical crop production practices until a criticalevent, such as weed resistance, forces a change in practices.Thus, close monitoring of weed populations and detection of resistance early and fast, are crucial to avert economic losses. Additionally, such monitoring efforts can enable the tracking of resistance across broad geographies. General guidelines forresistance confirmation are summarized by Moss (1999).Expanding on these guidelines will help weed sciencepractitioners choose, modify, or design appropriate protocolsfor resistance testing to suit different situations. Beckie et al.(2000) presented a thorough review of resistance testing forvarious herbicide groups across different weed species. In thelast decade, the global weed resistance database has expandedsignificantly (Heap 2012), and so has our collective experiencein surveying, confirming resistance, and evaluating resistancelevels. DNA-based assays have been developed for target-site–based resistance and have been used for quick, high-throughputresistance confirmation. Understanding the advantages andlimitationsofvariousresistancetestingapproacheswillhelp onechoose the appropriate sampling and assay protocol andinterpret the results properly. Field Surveys for Resistance Evaluation Structured surveys are often an important component of sampling putative resistant (R) plants and collecting infor-mation to understand factors that contribute to the evolutionand spread of R populations. Population sampling forresistance can be conducted with the use of variousmethodologies, but in-field sampling is regarded as the mostprecise method of gathering important management andbiological information. The biology of the species is anintegral part of defining the objectives of the survey. In-fieldsurveys have been used to detect the presence of herbicide-resistant (HR) weeds ranging from several fields surrounding a single, HR seed source (Baumgartner et al. 1999; Falk et al.2005) to many regions within a state or province (Beckie et al.1999, 2001; Bourgeois and Morrison 1997a, 1997b;Bourgeois et al. 1997b; Davis et al. 2008; Le´ge`re et al.2000; Llewellyn and Powles 2001; Tucker et al. 2006; Walshet al. 2001). Beckie et al. (2000) proposed that because HR weeds can be rare, the selection of fields to survey and sampleis the most critical step in determining how surveys should beinterpreted. Some survey objectives are simply to find anddocument new cases of resistance due to reported controlfailures. Other surveys may be designed to estimate thefrequency and distribution of previously documented R biotypes to generate risk models, which can be used to warnsurrounding geographies with similar cropping systems of thepotential for this biotype to evolve or migrate into new areas. DOI: 10.1614/WS-D-12-00032.1*First author and sixth authors: Department of Crop, Soil, and EnvironmentalSciences, University of Arkansas, Fayetteville, AR 72704; second author:Department of Crop Sciences, University of Illinois, Urbana, IL 61801; thirdauthor: Department of Agriculture and Ecology, The University of Copenhagen,Taastrup 2630, Denmark; fourth author: Department of Agronomy, University of Wisconsin-Madison, WI 53706; fifth author: USDA-ARS, Fort Collins, CO80526; seventh author: Department of Basic Science and Environment,University of Copenhagen, Frederiksberg C, Denmark 1871. Corresponding author’s E-mail: Weed Science   2013 61:4–20 4  N  Weed Science 61, January–March 2013  In-field surveys can utilize systematic random procedures,nonrandom procedures, or a combination of both during selection of sampling locations (Davis et al. 2008). However,Beckie et al. (2000) recommended that samples be collecteddirectly from where control failures are observed, in a systematic but nonrandom approach, as illustrated by Falk et al. (2005). They determined driving routes radiating from a known resistant source, and when fields with that weed specieswere observed, samples were collected. These data are alsoknown as presence-only data in some ecological models. Withthis design it is clearly possible to confirm R biotypes among the samples collected and determine the frequency of controlfailures that are due to resistance. However, the data do notprovide the ability to estimate the frequency of whichresistance might be found in all fields, nor to determinemanagement factors that may be contributing to resistanceevolution. Surveys with those objectives require a randomsampling of fields, accompanied by a survey of farming practices.Therefore, if determining the frequency of R biotypes in a particular area is the primary goal, then sample sites should berandom, but with a systematic procedure of preselecting targetlocalities to calculate the frequency of detection, with andwithout the herbicide selector, appropriately (Davis et al.2008; Owen and Powles 2009; Walsh et al. 2007). Walshet al. (2007) and Owen and Powles (2009) utilized systematicprocedures based on travel distance. Davis et al. (2008)demonstrated a systematic random sampling system thatutilized Geographic Information Systems (GIS) hardware andsoftware, in conjunction with the United States Departmentof Agriculture–National Agricultural Statistical Service Crop-land Data Layer program. Although those materials andmethods were well defined, a variety of newer hardware andsoftware programs may be available to meet similar objectives.The primary objective of Davis et al. (2008) was to combinethe resolution power of detecting herbicide resistance at low frequencies, while simultaneously generating data to calculatefrequency, with the ability to model the important manage-ment parameters which predict resistance occurrence (Daviset al. 2008, 2009). With a host of new GIS technologies andcurrent computing power, well-designed surveys can begenerated based on important parameters, which may includecrop rotations, tillage histories, topography and terrain, soiltypes, or other factors that might best define an area of interestfor a given weed species. For these objectives, survey locationscan be selected based on Global Positioning System (GPS)coordinates. To increase the likelihood of finding rare events,nonrandom sample data can be collected between predeter-mined survey locations when weed escapes are observed(Davis et al. 2008). Sampling Plants for Resistance Evaluation  An appropriate process to collect seeds from putative R andsusceptible (S) plants for herbicide assays is critical. How tocollect and how many plants will be collected should bedecided carefully. There is no consensus among researcherswith respect to the sample size of mother plants for resistancetesting, regardless of mating behavior (Table 1). For primarily self-pollinated species like horseweed [ Conyza canadensis   (L.)Cronq.], 30 to 40 seed heads from putative R plants in a composite sample is recommended (Beckie et al. 2000; Daviset al. 2008). Collecting a large sample size for self-pollinatedspecies is done by other research groups (Davis et al. 2010; Weaver 2001). On the contrary, five female plants may be anappropriate sample size for an obligate outcrossing, dioeciousspecies like waterhemp [  Amaranthus tuberculatus   (Moq.)Sauer var.  rudis   (Sauer)] (Trucco et al. 2005). Collecting a large number of samples is unnecessary for species withoutcrossing mating behavior. Where there is thoroughintrapopulation genetic mixing, few plants are needed torepresent the genetic diversity (and HR phenotypic diversity)within the population. Nevertheless, other groups collected10 to 30 females per field of the dioecious species Palmeramaranth (  Amaranthus palmeri   S. Wats.) (Wise et al. 2009)and waterhemp (Legleiter and Bradley 2008). In the majority of cases, the numbers of harvested mother plants per fieldwere not reported (Table 1) and we believe that this variedwidely. Therefore, we surmise that 20 to 40 plants for self-pollinated species and 5 to 10 plants for cross-pollinatedspecies should be sufficient to compose a bulk sample or tocollect individual plant samples. Because survivors generally occur in patches, multiple bulk samples may be collected perfield.The expected resistance frequency in a field can bedetermined from bulk samples. However, composite samplesare not appropriate if the objective is to evaluate intrapop-ulation diversity in resistance evolution. In such cases,individual plant samples should be collected (Hausmanet al. 2011; Patzoldt et al. 2005). Care is needed to referencefrequency of resistance based on previous herbicide exposure.This does not reflect the resistance frequency with respect toall plants that once were in the field prior to herbicideapplication. A true estimation of resistance frequency within a field would need to account for viable seed bank densities.This would require collection of soil cores. This is laborintensive and costly and impractical in many cases, butnecessary for precise characterization of population dynamics.Seed heads must be collected at a time that maximizesviable seeds for whole-plant assays, unless other assays thatonly require plant tissue collections are available. Weeds aregenerally diverse in their maturation time (Muenscher 1935),and often, weed maturation is aligned just prior to cropmaturation. Therefore, the window of opportunity to collectmature inflorescences may be short due to crop harvestoperations. The collection time may be even shorter if controlfailures are bad enough for growers to warrant preharvestherbicide applications. These time constraints must beconsidered during survey design and implementation.The amount and type of extraneous data collected at eachsample location must be considered based on survey objectivesand weed biology. For instance, during the sample collectionof a suspected new case of herbicide resistance, informa-tion regarding prior herbicide use as well as other cropmanagement practices is critical to estimate the risk for otherresistant cases to arise in similar management situations. Onthe other hand, if a species has been previously documentedwith resistance to a certain herbicide, and the survey objectivesare to understand the wide-scale geography that the biotypeinfests, detailed historical data become less critical andunderstanding seed migration patterns and pollen movementpotential become more important. For example, horseweedseeds are windblown, traveling long distances (Dauer et al.2006), whereas other weed seeds may be more prone to travel Burgos et al.: Resistance confirmation  N  5  via farm implements (Rew and Cussans 1997), particularly harvesting equipment. Classical Approach to Resistance Confirmation The classical approach (classical assay) of confirming resistance is to collect bulk seeds from surviving plants insuspected fields, plant these in pots, and apply either PRE orPOST herbicides. To represent the problem areas, seeds frommultiple plants need to be collected (Moss 1999), but thenumber of plants used to constitute a bulk varies widely. Thegoal is to collect enough good-quality seeds to conduct varioustests (see previous section on sampling). From the field to thelaboratory, care should be taken to prevent exposure of collected seeds to unfavorable conditions (e.g., hot, moistconditions) that would trigger seed deterioration or secondary dormancy. Prior to using these seeds for bioassay, it may be necessary to break seed dormancy to obtain uniformgermination. Recalcitrant seeds may have to be pregerminatedand then transplanted to the assay medium (Burke et al. 2006;De´lye et al. 2002a; Huan et al. 2011; Xu et al. 2010). For PREherbicides, field soil must be used to obtain a realistic herbicideactivity, whereas commercial potting media are sufficientfor POST herbicides. To test resistance of a species for thefirst time, conducting a dose–response curve, relative to a susceptible (S) standard, is better than using a single dose, asthis will show the magnitude of resistance and the discrimi-nating dose. In subsequent tests of other populations of thesame species, a single dose can be used. The majority of researchers use the recommended field dose in pot assays toscreen a large number of putative R samples, and the responsecompared with that of a chosen S standard and respectivenontreated checks (Table 1). If space and manpower allow,including more than one dose in the screening test is beneficialbecause it gives some indication of resistance level among populations. Thus, in some cases, two to four doses had beenused in resistance confirmation assays (Kaloumenos et al. 2011;Maneechote et al. 2005; Wise et al. 2009). Where there are few (i.e., , 5) populations to test, one may opt to conduct a dose–response assay instead to confirm resistance and determine theresistance level in one experiment. In Petri plate assays, putativeR and S populations are first tested with a wide range of dosesto determine the discriminatory dose before conducting thelarge-scale resistance testing (Bourgeois et al. 1997a; Kaundunet al. 2011b). Where an R population has already beenidentified, an R standard may also be included. An S standardshould be included in every run of a resistance assay.The selection of an S standard has been discussed at greatlengths in many venues. What matters to growers is resistanceto the recommended field dose. For scientists, knowing whether a population is gaining the capability to survive therecommended dose helps in promoting mitigation measuressoonest. Putative herbicide-S plants need to be collected fromthe same agricultural region to confirm resistance and conductthe herbicide dose assays, but within reasonable distance fromthe problem field. Plants in areas adjacent to the source fieldmay be contaminated with the resistance trait because of geneflow. In this case, a true wild type should be collected at a farenough distance from the source field. Plants adjacent to thesource field are also exposed to low doses of the selectorherbicide because of drift from spraying field edges. It isdocumented in rigid ryegrass ( Lolium rigidum  Gaud.) andPalmer amaranth (Busi and Powles 2009; Neve and Powles2005a, 2005b; Norsworthy 2012) that resistance, specifically polygenic, is gradually selected by iterative exposure of a weedpopulation to sublethal doses of a herbicide. Therefore,populations in the immediate vicinity of a source field wouldmost likely exhibit reduced sensitivity to the herbicide thanpopulations with no prior exposure to it. In most cases,researchers use an S standard with no prior exposure to theherbicide or collect from a different field in the same locality,state, or region (Table 1). Itis common for research laboratoriesworldwide to use the same S standard population for testing theresistance of multiple populations across a large region. Underthese situations, utilizing a common S population is appropriateto compare levels of resistance between different populationsand between different experiments. When a species is being investigated for resistance to a herbicide with a previously undocumented mechanism of action, a putative S population should be collected from a relatively close distance if possible. This is important becausegenetic diversity among weed species may be greatly influenced by different climate and geographical conditions;S and R populations from within the same locality should besimilar in extraneous genetic characteristics that could impactresponse to herbicides.Comparison between populations is most commonly doneby determining the effective dose that causes 50% inhibition(GR  50 ) of growth noted by biomass reduction and/or visualratings or the dose needed to kill 50% of the plants (LD 50 )through rate titration experiments. The procedure andcalculations to determine the GR  50  and LD 50  are explainedin more detail in the next section. Determining the value of the S population with an appropriate representation of theexpected normal wild-type population is just as critical asdetermining the value of the putative R population becausethe GR  50  or LD 50  value for S sets the resistance index. Ideally,one should compare responses of multiple S populations, andthereby obtain baseline herbicide sensitivity data as well as anindication of the natural variability of the species. An averageS population should be used. GR  50  or LD 50  values should notbe compared between experiments using S populations withdifferent sensitivity levels to the herbicide. Furthermore, insome screening experiments multiple R standards may beneeded because different resistance mechanisms could result indifferent levels of herbicide tolerance.Treatments should be replicated and the test repeated, toverify the results. Generally, three to four replications are used(Table 1) with a few cases using five to six replications(Maneechote et al. 2005; Marshall and Moss 2008). The goalis to test a large enough number of plants per population toincrease the power of resistance detection. In cases where theresistance test was not replicated, a large number of seeds wereplanted in flats and 80 to . 100 plants per population weretreated (Dickson et al. 2011; Wise et al. 2009; Zheng et al.2011). Where only two replications were prepared, 40 to 50plants were tested per replication (Dickson et al. 2011; Owenet al. 2012); the test by Dickson et al. (2011) was repeated intime. If a replicate consists of a single plant, at least 10replicates should be used. The number of plants to include perreplicate is determined based on the objectives of thescreening, plant size, and growth characteristic, concerns of herbicide coverage (for POST treatments), greenhouse spaceavailability, and other factors. Although the majority of resistance confirmation tests are not repeated (Table 1), we Burgos et al.: Resistance confirmation  N  7
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