nonconventional weed management strategies for modern ... · sustainable and conservation...

Nonconventional Weed Management Strategies for Modern Agriculture

Ali A. Bajwa, Gulshan Mahajan, and Bhagirath S. Chauhan*

Weeds are a significant problem in crop production and their management in modern agriculture iscrucial to avoid yield losses and ensure food security. Intensive agricultural practices, changing climate,and natural disasters affect weed dynamics and that requires a change in weed management protocols.The existing manual control options are no longer viable because of labor shortages; chemical controloptions are limited by ecodegradation, health hazards, and development of herbicide resistance inweeds. We are therefore reviewing some potential nonconventional weed management strategies formodern agriculture that are viable, feasible, and efficient. Improvement in tillage regimes has long beenidentified as an impressive weed-control measure. Harvest weed seed control and seed predation havebeen shown as potential tools for reducing weed emergence and seed bank reserves. Development in thefield of allelopathy for weed management has led to new techniques for weed control. The remarkablerole of biotechnological advancements in developing herbicide-resistant crops, bioherbicides, andharnessing the allelopathic potential of crops is also worth mentioning in a modern weed managementprogram. Thermal weed management has also been observed as a useful technique, especially underconservation agriculture systems. Last, precision weed management has been elaborated with sufficientdetails. The role of remote sensing, modeling, and robotics as an integral part of precision weedmanagement has been highlighted in a realistic manner. All these strategies are viable for today’sagriculture; however, site-specific selection and the use of right combinations will be the key to success.No single strategy is perfect, and therefore an integrated approach may provide better results. Futureresearch is needed to explore the potential of these strategies and to optimize them on technological andcultural bases. The adoption of such methods may improve the efficiency of cropping systems undersustainable and conservation practices.Key words: Allelopathy, biotechnology, crop nutrition, herbicide resistance, precision agriculture,weed management.

Population explosion during the last few decadeshas exerted immense pressure on crop production,forcing the farming community to intensify agri-culture to meet food demands. Weeds are a majorfactor causing reduction in crop yields throughcompetition and allelopathic interactions. In mod-ern-day agriculture, weed infestations and weedbehaviors frequently change because of intensivemanagement practices, climate change, and ecolog-ical shift (Chauhan et al. 2006, 2014). Asa consequence, the existing management optionsneed to be altered to ensure effective control giventhese shifts. In developing countries, manual ormechanical weed management is more prevalent,whereas in developed and technologically advancedregions, chemical weed management is dominant

(Chauhan 2012; Chauhan and Gill 2014). Thedifference in management practices depends onlabor and resource availability (Zimdahl 2013).Today’s agriculture requires a modified weedmanagement regime to cope with the problemsassociated with traditional techniques (Bajwa 2014).Ecology-based and nonconventional weed manage-ment tools may offer solutions to aggravatingproblems of herbicide resistance, environmentalpollution, weed diversification, biological invasion,and yield losses (Chauhan 2013; Chauhan andJohnson 2010; Chauhan et al. 2010; Singh 2007).Keeping in view these problems and potentialopportunities, nonconventional and nonchemicalweed management strategies like improved tillage,crop nutrient management, weed seed predation,allelopathy, herbicide-tolerant crops, bioherbicides,thermal techniques, and precision weed manage-ment have been discussed comprehensively in thisreview.

The importance of modified tillage in weedmanagement has been reviewed by several research-ers (Bajwa 2014; Brainard et al. 2013; Chauhan etal. 2012; Chauhan and Gill 2014). Walsh et al.(2013) comprehensively reviewed the weed man-

DOI: 10.1614/WS-D-15-00064.1* Research Higher Degree Scholar, School of Agriculture and

Food Sciences, The University of Queensland, Gatton, Queens-land 4343, Australia; Agronomist, Punjab Agricultural Univer-sity, Ludhiana 141004, India; Principal Research Fellow, TheCentre for Plant Science, Queensland Alliance for Agricultureand Food Innovation (QAAFI), The University of Queensland,Toowoomba, Queensland 4350, Australia. Correspondingauthor’s E-mail: [email protected].

Weed Science 2015 63:723–747

Bajwa et al.: Nonconventional weed management N 723

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agement potential of harvest weed seed control.Their key recommendations have been highlightedin this review and the missing links have beenelaborated. Impact of fertilizer management onweed dynamics is a relatively neglected aspect(Bajwa et al. 2014; Blackshaw and Brandt 2008),but this review provides an insight into this subject.Some classic reviews on the role of allelopathy inweed management have been published over theyears (Bhadoria 2011; Cheema et al. 2013; Farooqet al. 2011, 2013; Nawaz et al. 2014; Weston andDuke 2003; Worthington and Reberg-Horton2013). The practical implications, latest scenario,future research needs, and the scope of allelopathyin integrated weed management strategies have beenthoroughly discussed in this review. Differentreviews have concluded that the development ofherbicide-tolerant crops has revolutionized the cropproduction in many regions (Beckie et al. 2006; Dillet al. 2008; Duke and Powles 2009; Green 2012).Although biological weed management is nota panacea under prevailing conditions, it has a greatpotential (Ash 2010; Charudattan 2001, 2005;Hallett 2005). Meanwhile, the advancements intechnology have created vast opportunities for weedmanagement in the form of thermal techniques,including flaming, solarization, electrocution, andmicrowave technology (Bond and Grundy 2001;Knezevic et al. 2011; Rask and Kristofferson 2007).Precision weed management is another prospect ofmodern weed management. The application ofremote sensing, modeling, and robotics in a verysophisticated and highly scientific manner (Chris-tensen et al. 2009; Freckleton and Stephens 2009;Lamb and Brown 2001; Slaughter et al. 2008;Thorp and Tian 2004; Torres-Sanchez et al. 2013;Young et al. 2014) will enable us to pave/treadexcellent paths for a site-specific, efficient, targeted,and economical weed management in the future.

No doubt, each and every weed control strategyhas some unique benefits, but under the currentagriculture scenario, an overall shift toward moresustainable and targeted practices is inevitable. Inthis review, a detailed and comprehensive analysis ofthese potential strategies has been done, which willhelp weed scientists to view the comparativeefficacies and potential implications of thesealternative nonconventional strategies, primarilyavoiding use of the synthetic chemicals. To thebest of our knowledge, a comprehensive review ofall these potential nonconventional weed manage-ment strategies leading to a fruitful effort forintegrated weed management under the present

and future conditions on a sustainable basis has notbeen presented previously.

Improved and Targeted Tillage

Tillage plays an important role in weed controland has been used as an effective management toolsince ancient times. Tillage is still very effective, asdifferent types of modern cultivators and weedersare facilitating mechanical weed management(Wallace and Bellinder 1992). The advent andsuccessful adoption of no-till systems using herbi-cides have shown that tillage is not as necessary forcrop production as it is for weed control (Zimdahl2013). Tillage has significant impact on theefficiency of soil-applied herbicides, particularlydinitroanilines (Singh et al. 2012); higher watervolume is required to improve the efficacy of PREherbicides under zero-tillage systems (Borger et al.2013).

Tillage Implements for Weed Management.Appropriate tillage implements are needed for aneffective weed control. In ancient times, bullocks/horses were used to move different types ofcultivators, sweeps, and hoes for weed eradication.Since the advent of mechanized farming, the trendof using tractor-mounted equipment has increased.Tractor-mounted equipment is easier to use underconventional tillage systems but more difficult inmodified tillage systems, including no-till, striptillage, and other conservation tillage systemsbecause of retained residues (Brainard et al.2013). Residue mulches or living cover crops canbe managed through mowing or use of a high-residue cultivator (Creamer and Dabney 2002).Some important mechanical weed-managementtools include the use of a rotary hoe, rototiller,rotavator, power tiller, rod weeder, cultipacker,spring tine harrow, finger weeder, torsion weeder,brush weeder, spike-tooth weeder, and pneumaticweed blower (Duerinckx et al. 2005; Mohler et al.1997). Murphy et al. (2006) compared moldboard-plowed, chisel-plowed, and no-tilled systems for6 yr and found that weed dynamics wereaffected substantially by tillage systems. However,their respective efficiency declined with increasingdensity of weeds.

Tillage Systems and Weed Dynamics. Tillagesystems interact with soil type, cropping system,and weed flora to affect weed dynamics and weedmanagement (Table 1). Weed germination, stand

724 N Weed Science 63, October–December 2015


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establishment, and subsequent growth are affectedby the tillage processes (Clements et al. 1996).Changing weed flora under different tillage regimescalls for a change in management options. Weedinfestation is a serious problem during initial yearsunder conservation tillage, which causes a reductionin crop yield (Blackshaw et al. 2001). On the otherhand, some weed species may be suppressed inconservation tillage systems. For instance, wheat(Triticum aestivum L.) planting in no-till conditionsreduced the seedling emergence rate of littleseedcanarygrass (Phalaris minor Retz.), when comparedwith conventional plowing and sowing (Frankeet al. 2007).

Tillage systems may also affect weed seed bankpersistence in different seasons, but literature on thisevent is not clear. Effects of tillage on weeds are veryspecific and may vary from species to species.Emergence of tropical crabgrass [Digitaria bicornis(Lam.) Roemer & J.A. Schultes ex Loud.], tumblepigweed (Amaranthus albus L.), giant foxtail (Setariafaberi Herrm.), and common ragweed (Ambrosiaartemisiifolia L.) was suppressed by spring cultiva-tion, whereas that of velvetleaf (Abutilon theophrastiMedik.) and black nightshade (Solanum nigrum L.)was unaffected (Myers et al. 2005). Similarly, tillagehad different effects on the distribution of commonlambsquarters (Chenopodium album L.) and yellowfoxtail [Setaria glauca (L.) Beauv.] in differentseasons (Myers et al. 2005). Chauhan et al. (2006)also reported that weeds respond differently underdifferent tillage regimes. For instance, intensivetillage may affect small-seeded weeds like squirreltailfescue [Vulpia bromoides (L.) S.F. Gray] throughdeep burial. Different tillage systems may have theirown advantages and disadvantages in this regard butsite-specific selection may facilitate weed manage-ment.

Strip Tillage to Target Weeds. No-till is a prag-matic option for resource conservation in manyregions of the world but one serious concern in thissystem is poor crop establishment. Strip tillage isone such innovative approach focusing on targetedtillage for crop sowing while the remaining portionis untilled. This system improves soil quality, cropyield, and resource-use efficiency compared witha conventional tillage system, but weed manage-ment is a major issue hindering its adoption(Brainard et al. 2012). Weed dynamics are verycomplex under this system since the untilled zonemay offer refuge to different predators and mayutilize less mineralized nitrogen (N). In this way,

the situation and distribution of weeds are highlyvariable (Tarkalson et al. 2012). The tilled zone haswell-incorporated residues, fertilizer, mineralized N,and higher temperatures, which contrast with theadjacent untilled patch. Such diversified conditionsthrough targeted tillage directly alter weed dynamicsas propagule movement and belowground biolog-ical functions are affected (Haramoto and Brainard2012).

Winter annual weeds like common chickweed[Stellaria media (L.) Vill.] and henbit (Lamiumamplexicaule L.) were more prevalent in the striptillage system when compared with the conventionaltillage (Brainard et al. 2012). This may be due tohigh survival and reproduction in the untilledportion. According to Brainard et al. (2013),perennials like horsenettle (Solanum carolinense L.)have the ability to recolonize quickly and are moreproblematic under strip tillage. Stable perennialslike dandelion (Taraxacum officinale G.H. Weber exWiggers) do not usually present this problem.Overall, annual, biennial, and perennial weeds havea different growth and emergence pattern understrip tillage (Brainard et al. 2012).

Weed Control through Tillage Rotation. Rota-tion of tillage intensity (number of operations) isa modern approach for weed management, especiallyunder multiple cropping systems. In an experimentspanning 6 yr, it was observed that the density ofsummer annual weeds was reduced significantly whenzero-tilled direct seeding was replaced with full-widthtillage (Peachey et al. 2006). Another potentialstrategy is by adjusting crop rotations in such a waythat the planting geometry automatically rotates thetillage patterns. For example, in the Pacific Northwest,vegetables on wider beds are rotated with cereals onnarrow ridges (Brainard et al. 2013). In another study,foxtail barley (Hordeum jubatum L.) was effectivelycontrolled through shifting from no-till to primarytillage with moldboard plow followed by disking inspring wheat (Donald 1990). Timing of tillage isanother important factor affecting weed management.

Tillage affects weed dynamics, depending onseasonal variations, weed species, and type of tillageimplement. There are numerous other factors, though,that are interacting and making such assumptionsless solid and therefore more complicated.

Crop Nutrient Management

The role of nutrient management through fer-tilizer application in crop production is substantial



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https://doi.org/10.1614/WS-D-15-00064.1



and very clear. Weeds take up significant amountsof nutrients, just like crops. But the comparativeeffects on weed growth, population, distribution,and proliferation are generally ignored. Significantresearch in this area has shown that there existsa strong relationship between nutrient managementand weed behavior and management. In a recentreview, Bajwa et al. (2014) concluded that fertilizersaffect weed growth, development, distribution,dynamics, persistence, emergence, and competitive-ness.

Proper crop nutrient management can playa pivotal role in weed management. Different weedsshow a variable response to nutrient management.For instance, dynamics of Persian darnel (Loliumpersicum Boiss. & Hohen. ex Boiss.), wild oat(Avena fatua L.), and spineless Russian thistle(Salsola collina Benth.) were not affected by Nfertilization, whereas redroot pigweed (Amaranthusretroflexus L.) was significantly affected (Blackshawand Brandt 2008). The possible interactions mightbe due to the effect of fertilizer on weed–cropcompetition (Evans et al. 2003). Nutrient availabil-ity may alter the weed–crop competition duration.In a study, the application of N fertilizer changedthe emergence pattern, density, and competitiveability of different weeds (Sweeney et al. 2008). Nuptake and assimilation rates were reported to bequite higher in redroot pigweed and commonlambsquarters as compared with the crop plants,making them more competitive and successful(Lindsey et al. 2013). Increased supply of nutrientsover a period of time may reduce weed density butincrease total weed biomass (Mohammaddoust-e-Chamanadad et al. 2006). Variable weed responsesto fertility suggest that weeds can be controlledthrough regulating fertilizer management (DiTo-maso 1995). Varying fertilizer doses, applicationtimings, and methods can modify weed–cropcompetition (Blackshaw et al. 2004; Cathcart andSwanton 2003; Mesbah and Miller 1999).

The nature of fertilizers may affect weed biologyand ecology. The rate of a particular fertilizer mayalso improve or suppress the emergence andpersistence of a particular weed (Cathcart andSwanton 2003). Yin et al. (2005) reported thatthe percent abundance of shepherd’s purse [Capsellabursa-pastoris (L.) Medik.], Japanese bindweed(Calystegia hederacea Wallich), fixweed [Descurainiasophia (L.) Webb. ex Prantl], catchweed bedstraw(Galium aparine L.), swamp smartweed [Polygonumamphibium (L.) var. emersum Michx.], cone catchfly(Silene conoidea L.), and bird vetch (Vicia cracca L.)

was highly variable because of variation in the N–P–Ksource (inorganic and organic). Palmer amaranth(Amaranthus palmeri S. Wats.) was reported to behighly responsive to the increased fertilization rate(Ruf-Pachta et al. 2013). Toler et al. (2004) observedthat normally weeds respond positively to the starterfertilizer dose and grow well. It is suggested thata specific amount of fertilizer can provide better cropgrowth but an over- or underapplication mayfacilitate the competing weeds, resulting in yieldlosses (Major et al. 2005). Shifting the N applicationfrom the spring season to the fall season reduced thedensity and biomass of four noxious weeds, includingwild oat, green foxtail [Setaria viridis (L.) Beauv.],wild mustard (Sinapis arvensis L.), and commonlambsquarters (Blackshaw et al. 2004). Therefore,proper consideration must be given to fertilizer type,dose, and application timing when devising weedmanagement strategies.

Above all, the role of nutrient placement in weedmanagement is crucial. Most of the weed seeds arepresent near the soil surface and fertilizer applica-tion in that zone may promote their emergence andsubsequent growth as well (Guza et al. 2008).Blackshaw et al. (2004) reported up to 68% weedreduction in cases where N was injected rather thanbroadcast. Surface banding of N and P reducedweed pressure because of less availability to weeds ascompared with broadcasting (Blackshaw 2005).Significant reductions in the shoot biomass of wildoat and green foxtail were observed when Nfertilizer was applied through banding and injectionrather than broadcasting (Blackshaw et al. 2004).Recently, Chauhan and Abugho (2013) reporteda significant reduction in weed biomass by thesubsurface fertilizer application in dry direct-seededrice (Oryza sativa L.).

Better management of crop nutrition can im-prove weed management. Fertilizer type, dose,timing, and application method must be selectedto best manage weed populations given their link.

Weed Seed Destruction

Most of the annual weeds produce a majority ofseeds after completing their vegetative growth.Many seeds are retained in the soil seed bank,which creates problems after emergence in standingcrops. Weed populations can be decreased byremoving their seeds at maturity (Walsh et al.2013). This strategy eliminates potential seeds fromthe system that can be deposited in soil or maygerminate in coming seasons.



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Harvest Weed Seed Control. The harvesting timeof grain crops is very important as weed seeds areretained by plants and easy to remove and discard(Walsh and Powles 2007). Weed seeds can becollected and destroyed during or soon afterharvesting of a crop. Harvest weed seed controlhas been developed in Australia and has shownpromising results. This strategy can be implementedwith the Harrington seed destructor (HSD), chaffcarts, narrow windrow burning, and bale direct(Walsh et al. 2013). Each technology is based on theprinciple of weed-seed collection during grain cropharvest and seed destruction to avoid the replenish-ment of the seed bank.

Harrington Seed Destructor. Weed seeds present inannual grain crops remained a major concern forgrowers. A progressive grain producer, Ray Harring-ton, from Australia tested a cage mill for seeddestruction in 2005 (Walsh et al. 2013). Cage millsare normally used to crush stone materials. Furtherresearch enabled scientists to destroy up to 90% ofseeds of annual ryegrass (Lolium rigidum Gaudin)contained by wheat chaff during harvesting (Walshet al. 2012). HSD is a modified cage mill havinga chaff-and-straw transfer system along with powersource. According to Walsh et al. (2012), fieldstudies showed that HSD offers an impressivedestruction rate of above 95% for annual ryegrass,ripgut brome (Bromus diandrus Roth), wild radish(Raphanus raphsnistrum L.), and wild oat seeds(Table 2). With such impressive results, HSD isa pragmatic option for the destruction of weed seeds.

Chaff Carts. Weed seeds that remain intact duringconventional harvesting operations that are thenadded to the crop residues become randomlydistributed to the whole field. To avoid thisproblem, chaff carts were introduced. Chaff cartsare simply a cart on a trailer that is attached toa harvester that collects the chaff and places weedseeds in a specified bin (Walsh et al. 2013). Chaffcarts effectively collect a significantly large amountof seeds of obnoxious weeds like annual ryegrass,wild oat, and wild radish (Shirtliffe and Entz 2005;Walsh and Powles 2007). Collected weed seeds andchaff are then dumped in piles to be burned.

Narrow Windrow Burning. This technique forcontrolling harvested weed seed is where chaff andresidues containing weed seeds are concentrated ina narrow windrow during harvesting (Walsh et al.2013). The harvester-mounted chute makes abouta 60-cm windrow that is burned later, while keepingecoprotection in mind (Walsh and Newman 2007).The limited burning of the windrow avoidspollution hazards as the whole field is not burned.Windrow burning is promising as it offers maxi-mum weed control after harvesting of wheat, canola(Brassica napus L.), and garden lupin (Lupinuspolyphyllus Lindl.) (Table 2).

Bale Direct. This is another sophisticated method ofharvest weed seed control, in which chaff andresidues from the harvester are converted into balesby a mechanized baler attached to the harvester(Walsh et al. 2013). Despite its efficient and clean

Table 2. Efficiency and adoption of harvest weed seed control systems in Australia.a

System Weed species Seed control (%) Adoption Extra benefit Reference

Harringtonseed destructor

Annual ryegrass 95 High adoption ratedue to highefficiency

Residue retentionfor soil protectionand fertilityenhancement

Walsh et al. (2012)

Brome grass 99Wild oat 99Wild radish 93

Chaff carts Annual ryegrass 73 to 86 Less due to problemsof subsequent handlingof chaff

Alternative use ofchaff as feedfor the livestock

Walsh and Powels (2007)

Wild radish 95Wild oat 74 Shirtliffe and Entz (2005)

Narrowwindrowburning

Annual ryegrassand wild radish

99 for each Most widely adopted aseconomical, simple,and efficient

Relatively ecofriendly asit avoids burning ofthe whole field

Walsh and Newman (2007)

Bale direct Annual ryegrass 95 Less due to lack ofavailability of marketsfor baled material

Baled feed stockfor livestock

Walsh and Powels (2007)



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function, the adoption rate is lower, which may bedue to the marketing issue with bales. However, itoffers remarkable weed seed destruction (Table 2).

Hence, weed seed control during crop harvest isan encouraging prospect in the field of weedmanagement. It helps to reduce weed seed bankand to minimize the chances of weed infestations insubsequent seasons. The development of technologyin this sector may enable the farming community tomanage weeds efficiently.

Weed Seed Predation. Seed predation throughgranivorous insects and small mammals is a usefultactic for weed control. Seed predation may be pre-(seeds still attached with plant) or post- (seedsdispersed after maturity) dispersal. Insects, birds,and small mammals are the major postdispersalweed seed predators (Heggenstaller et al. 2006;Menalled et al. 2007). Most Coleoptera andHymenoptera insects are involved in weed seedfeeding. Several species of carabid beetles and fieldcricket have been observed as potential predators ofredroot pigweed, velvetleaf, large crabgrass [Digi-taria sanguinalis (L.) Scop.], and giant foxtail seedsin North America (Carmona et al. 1999). Miceconsumed up to 20% of seeds of barnyardgrass[Echinochloa crus-galli (L.) P. Beauv.] and commonlambsquarters in no-till soybean [Glycine max (L.)Merr.] and corn (Zea mays L.) in Canada (Carmonaet al. 1999). Feeding habits and preferences of thepredators significantly affect weed seed destructionand concomitant weed emergence. White et al.(2007) observed feeding choice of three beetlespecies (Amara aenea, Anisodactylus sanctaecrucis,and Harpalus pensylvanicus) and the field cricket(Gryllus pennsylvanicus). The beetles consumedmore seeds of redroot pigweed than of giant foxtail.

Experimental and modeling studies have clearlyshown that predation significantly affects weed seeddemographics (Mauchline et al. 2005). A recentstudy in the Philippines reported a seed removal rateof 78 to 91% for junglerice [Echinochloa colona (L.)Link], goosegrass [Eleusine indica (L.) Gaertn.], andsouthern crabgrass [Digitaria ciliaris (Retz.) Koel.]over a 14-d period (Chauhan et al. 2010). Meisset al. (2010) reported that the vegetative coverinfluences weed-seed predators by altering thehabitat quality. Effective predation can be achievedby delaying tillage or increasing interval betweenland preparation and seeding (Chauhan 2012;Chauhan et al. 2010). Seed predation is a potentialnonchemical weed management option. It can be

used alone or in combinations with other culturalmanagement practices.

Allelopathy

A large proportion of the existing allelopathyresearch findings is focused on its role in weedmanagement. Researchers have observed that alle-lopathy is a great organic weed management tool(Cheema et al. 2004; Iqbal et al. 2007; Jamil et al.2009). Allelochemicals suppress physiological func-tioning of plants and thus retard growth whenapplied at high concentrations. This phytotoxicactivity of allelochemicals is responsible for growthsuppression of weeds (Farooq et al. 2013). Allelop-athy can be expressed in two major ways for weedmanagement: cultural means and allelopathicextracts application.

Cultural Means. Allelopathic sources can beintroduced through crop rotations. Allelopathiccrops are included in a planned rotation wheretheir residual effects may suppress weed flora andprovide a weed-free environment to the next crop.Mulches based on allelopathic residues are goodmeans of weed control (Cheema et al. 2013).Emerging weed seedlings are effectively controlledby allelopathic mulches through the leaching ofallelochemicals; however, established weed flora isdifficult to eradicate through this method (Farooqet al. 2013). Similarly, incorporation of sorghum[Sorghum bicolor (L.) Moench ssp. Bicolor] vegeta-tive parts significantly reduced weed density inwheat fields (Cheema and Khaliq 2000). Soilincorporation of sorghum residues alone and whenmixed with sunflower (Helianthus annuus L.), rice,and Brassica spp. trashes provided effective controlagainst littleseed canarygrass, common lambsquar-ters, toothed dock (Rumex dentatus L.), and horsepurslane (Trianthema portulacastrum L.) in wheat,cotton (Gossypium hirsutum L.), and corn fields(Table 3). Surface mulching of sorghum, brassica,and cone marigold (Tagetes minuta) controlledweeds in rice, cotton, and mung bean [Vignaradiata (L.) R. Wilczek] (Batish et al. 2007; Khaliqet al. 2010; Sadia et al. 2013). Intercropping isanother prospect for weed management throughallelopathy (Table 3). Allelopathic crops can also beintroduced as cover and smother crops. Allelopathiccrops like rye (Secale cereal L.), velvet bean [Mucunapruriens (L.) DC.], and barley (Hordeum vulgare L.)offered effective control against southern crabgrass,barnyardgrass, common purslane, and Amaranthus



https://doi.org/10.1614/WS-D-15-00064.1



Tab

le3

.C

ult

ura

lw

eed

man

agem

ent

thro

ugh

alle

lop

ath

icap

pli

cati

on.

Ap

pli

cati

onm

eth

odA

llel

opat

hic

sou

rce

Ap

pli

cati

onra

teW

eed

sco

ntr

olle

dR

edu

ctio

nin

wee

db

iom

ass

Cro

ps

ben

efit

ted

Ref

eren

ce

th

a21

%

Soil

inco

rpora

tion

Sorg

hu

m2

to6

Lit

tles

eed

can

aryg

rass

,co

mm

onla

mb

squ

arte

rs,

fum

itor

y(F

umar

iaof

fici

nali

sL

.)to

oth

edd

ock

26

to5

6W

hea

tC

hee

ma

and

Kh

aliq

(20

00

)

Com

bin

atio

ns

ofso

rgh

um

,ri

ce,

and

sun

flow

er5

to7

.5H

orse

pu

rsla

ne,

pu

rple

nu

tsed

ge6

0to

98

Wh

eat,

corn

,co

tton

Kh

aliq

etal

.(2

01

0)

Surf

ace

mu

lch

Sorg

hu

m3

.5to

10

.5H

orse

pu

rsla

ne,

fiel

db

ind

wee

d(C

onvo

lvul

usar

vens

isL

.),

ber

mu

dag

rass

,p

urp

len

uts

edge

35

to9

6C

otto

n,

mu

ngb

ean

Kh

aliq

etal

.(2

01

0)

Bla

ckm

ust

ard

(Bra

ssica

nigr

a)W

ild

oat

68

Far

ooq

etal

.(2

01

1)

Con

em

arig

old

1P

urp

len

uts

edge

,b

arn

yard

gras

s4

1R

ice

Bat

ish

etal

.(2

00

7)

Inte

rcro

pp

ing

Cot

ton

+so

rgh

um

2P

urp

len

uts

edge

89

to9

2C

otto

nIq

bal

etal

.(2

00

7)

Cot

ton

+so

ybea

n8

3to

92

Cot

ton

,so

ybea

nC

otto

n+

sesa

me

(Ses

amum

indi

cum

)8

0to

87

Cot

ton

,se

sam

e

Wh

eat

+ch

ickp

ea(C

icer

arie

tinu

m)

2W

ild

oat,

scar

let

pim

per

nel

(Ana

galli

sar

vens

isL

.),

pu

rple

nu

tsed

ge,

bar

nya

rdgr

ass,

less

ersw

inec

ress

[Cor

onop

usdi

dym

us(L

.)Sm

.]

/W

hea

t,ch

ickp

eaB

anik

etal

.(2

00

6)

Cov

ercr

op

sR

ye2

Com

mon

pu

rsla

ne

(Por

tula

caol

erac

eaL

.),

Am

aran

thus

spp

./

Nag

abh

ush

ana

etal

.(2

00

1)

Vel

vet

bea

n2

Bar

nya

rdgr

ass

/P

eter

set

al.

(20

03

)B

arle

y2

Sou

ther

ncr

abgr

ass,

bar

nya

rdgr

ass

/So

ybea

nF

aroo

qet

al.

(20

11

)Sm

oth

erin

gcr

op

sin

rota

tion

Oat

(Ave

nasa

tiva

),p

earl

mil

let

(Pen

nise

tum

glau

cum

),E

gyp

tian

clov

er(T

rifo

lium

alex

andr

inum

)

2P

urp

len

uts

edge

,b

arn

yard

gras

s/

Ric

egr

own

afte

rw

hea

tK

obay

ash

iet

al.

(20

04

)

Wh

eat

2Sm

all

bro

mer

ape

(Oro

banc

hem

inor

Sm.)

/R

edcl

over

(Tri

foli

umpr

eten

se)

Lin

set

al.

(20

06

)

2,

not

app

lica

ble

;/,

not

reco

rded



https://doi.org/10.1614/WS-D-15-00064.1



spp. in different crops (Farooq et al. 2011). Culturalmeans of allelopathic application have varyingdegree of success, depending upon environmentaland managerial factors.

Allelopathic Extracts. Allelochemicals are second-ary metabolites with complete solubility in water.This feature enables them to be extracted in waterafter soaking herbage and subsequently used asfoliar spray. Crop water extracts have been usedsuccessfully for weed suppression through foliarapplication in different crops (Bajwa 2014).Sorghum water extract is one of the most widelyused natural herbicides. Concentrated sorgaab(sorghum water extract) controlled common lambs-quarters, littleseed canarygrass, and toothed dock inwheat crop (Cheema and Khaliq 2000). Similarly, itoffered a substantial reduction in weed density andweed biomass in rice, cotton, corn, and mungbean(Table 4). Combined use of different crop waterextracts improves weed management through syn-ergistic effects (Table 4). In a laboratory experi-ment, Bajwa et al. (2013) showed that single andcombined applications of water extracts of some treeplants and weeds suppressed the germination andgrowth of wild oat. Integrating the use of half dosesof recommended chemical herbicides and differentcrop water extracts together offered favorable weedcontrol (Jabran et al. 2010; Rehman et al. 2010).

Improving Allelopathic Potential of Crops. Im-provement in the allelopathic potential of crops tooffer a substantial competitive advantage againstresistant weeds is under way. Keeping in view thegenetic variability existing in cereals, crops havebeen bred to improve their allelopathic potential(Worthington and Reberg-Horton 2013). Modifiedlines of birdsrape mustard (Brassica campestris L.)have been developed to increase their allelopathicexpression, which offered successful weed control incorn and soybean (Haan et al. 1994). Highly weed-suppressive rice genotypes (e.g., hybrid of Kouket-sumochi and IR24) have been developed throughconventional breeding, which suppress noxiousweeds like junglerice and red rice (Oryza sativa L.)to a great extent. Such cultivars are commerciallyavailable in China and the United States (Fragassoet al. 2013). Improvement in the allelopathicpotential of crops through genetic engineering isamong the latest trends in the field of agrobiotech-nology (Nawaz et al. 2014). Despite the complexgenomics, it is feasible to identify the distinguishedgenes involved in such mechanisms (Singh et al.

2003). Wu et al. (2000) screened a large pool ofwinter wheat accessions (over 400) to assortallelopathic active genes. With the help of genetictools, genes have been located that are responsiblefor the production of allelochemicals. Location ofsuch genes on chromosomes and quantitative traitloci (QTLs) are also being assessed (Jensen et al.2008). Gene mapping for hydroxamic acid expres-sion in wheat has been analyzed and QTLs are beingused for gene transfer (Wu et al. 2000, 2003).Crops with superior allelopathic profile and sup-pressive ability will improve weed management incoming days.

Herbicide-Tolerant (HT) Crops

An increasing trend of genetic modifications incrops has been observed during the last 2 decades.Major transgenic traits introduced in crops areherbicide resistance, insect resistance, virus resis-tance, and stress resistance. However, HT cropscomprise the vast majority (83%) of geneticallymodified (GM) crops (Beckie et al. 2006). Thereason behind the introduction of HT crops andtheir rising acceptance is primarily due to theeffective weed control. Biotechnology has providedsuccessful HT crops that are tolerant to glyphosate,glufosinate, bromoxynil, imidazolinone, and di-camba (Gealy et al. 2003; Givens et al. 2009). HTcrops like cotton, corn, canola, rice, sugar beet (Betavulgaris L.), alfalfa (Medicago sativa L.), brassica,and soybean (Gealy et al. 2003) have revolutionizedweed management in the United States (Givens etal. 2009), Canada (Beckie et al. 2006), Australia(Duke and Powles 2009) and many other countries.

A majority of HT crops, including soybean,cotton, corn and canola, is glyphosate resistant (GR)(Green 2012). GR crops have the largest share intransgenic HT crops globally. GR cotton was alsoadopted quickly in the United States and othercountries because of convenience and effective weedmanagement. Singh (2014) reported that . 95% ofcotton varieties planted in the United States wereGM varieties where area under stacked gene cottonvarieties increased from 24% (2000) to 77% in2014. Weed management in the conventional non-HT cotton was difficult because of the narrowspectrum and ineffectiveness of PRE herbicides(Duke and Powles 2009). GR canola has beensuccessful in different parts of world. However,about 90% of the global GR canola production is inCanada (Gianessi 2005). HT soybean is the most



https://doi.org/10.1614/WS-D-15-00064.1



Tab

le4

.W

eed

man

agem

ent

thro

ugh

alle

lop

ath

iccr

opw

ater

extr

acts

alon

ean

din

com

bin

atio

nw

ith

oth

erex

trac

tsan

dre

du

ced

dos

esof

her

bic

ides

.a

All

elop

ath

icex

trac

t/P

erce

nta

gere

du

ctio

n

com

bin

atio

nW

eed

sco

ntr

olle

dW

eed

den

sity

Wee

db

iom

ass

Cro

ps

ben

efit

edR

efer

ence

Sor

ghu

mF

um

itor

y,li

ttle

seed

can

aryg

rass

,to

oth

edd

ock,

com

mon

lam

bsq

uar

-te

rs

22

to4

43

5to

49

Wh

eat

Ch

eem

aan

dK

hal

iq(2

00

0)

Hor

sep

urs

lan

e,b

erm

ud

agra

ss,

pu

rple

nu

tsed

ge4

72

9to

40

Cot

ton

Ch

eem

aet

al.

(20

02

)

Pu

rple

nu

tsed

ge,

com

mon

lam

bsq

uar

ters

,fi

eld

bin

dw

eed

18

to3

22

4to

60

Mu

ngb

ean

Ch

eem

aet

al.

(20

01

)

Jun

gler

ice,

pu

rple

nu

tsed

ge,

rice

flat

sed

ge(C

yper

usir

iaL

.)

–c

40

Ric

eW

azir

etal

.(2

01

1)

Su

nfl

ow

erW

ild

oat,

yell

owsw

eetc

love

r[M

elil

otus

offi

cina

lis

(L.)

Lam

.],

bro

adle

afd

ock

(Rum

exob

tusi

foli

usL

.)

11

to3

42

to1

6W

hea

tN

asee

met

al.

(20

10

)

Sor

ghu

m+

sun

flow

er2

10

to6

2W

hea

tJa

mil

etal

.(2

00

9)

Sorg

hu

m+

bra

ssic

aSo

rgh

um

+to

bac

co(N

icot

iana

taba

cum

)W

ild

oat,

litt

lese

edca

nar

ygra

ss

Sorg

hu

m+

sesa

me

(Sor

ghu

m)b

+is

opro

turo

nL

ittl

esee

dca

nar

ygra

ss9

46

5W

hea

tC

hee

ma

etal

.(2

00

2)

(Sor

ghu

m+

sun

flow

er)

+p

end

imet

hal

inC

omm

onla

mb

squ

arte

rs8

46

7Su

nfl

ower

Aw

anet

al.

(20

09

)

(Sor

ghu

m)

+p

end

imet

-h

alin

Hor

sep

urs

lan

e5

25

0C

otto

nIq

bal

etal

.(2

00

9)

(Sorg

hu

m+

bra

ssic

a)+

pen

dim

eth

alin

Hor

sep

urs

lan

e,b

erm

ud

agra

ss,

pu

rple

nu

tsed

ge,

less

ersw

inec

ress

43

to9

13

7to

94

Can

ola

Jab

ran

etal

.(2

01

0)

(Sor

ghu

m+

sun

flow

er+

rice

)+

bu

tach

lor

Bar

nya

rdgr

ass,

rice

flat

sed

ge,

crow

foot

gras

s[D

acty

loct

eniu

mae

gypt

ium

(L.)

Wil

ld.]

67

to7

46

6to

76

Ric

eR

ehm

anet

al.

(20

10

)

aA

llth

eex

trac

tsw

ere

app

lied

two

toth

ree

tim

esin

ap

ure

form

wit

hou

td

ilu

tion

and

her

bic

ide

dos

esw

ere

red

uce

dto

hal

f.b

All

elop

ath

icex

trac

tsu

sed

inco

mb

inat

ion

wit

hre

du

ced

dos

eof

her

bic

ide

are

pre

sen

ted

inp

aren

thes

es.

c–

,n

ot

reco

rded

.



https://doi.org/10.1614/WS-D-15-00064.1



prevalent, where around 60% of the total pro-duction is transgenic crops (Beckie et al. 2006).

Nontransgenic HT corn, canola, wheat, soybean,sunflower, and sorghum developed in the past weretolerant to imidazolinones, photosystem II inhibi-tors, and sulfonylureases (Green 2012). Clearfield(CF) rice is exclusively nontransgenic, developedthrough the breeding technique, relying totally onrice DNA. CF rice is resistant against imidazolinoneherbicide, which is very effective against red/weedyrice. Weed control in CF rice is very easy as it allowsPRE and POST application of imazethapyr (Azmiet al. 2012). Wheat is the crop in which bio-technology has not given successful commercialvarieties yet. A lot of work is under progress atMonsanto, Bayer, BASF, and many other multina-tional companies for biotechnological developmentin wheat. Research trials have shown that RoundupReady wheat is safe, nutritious, and efficient interms of weed management (Obert et al. 2004).However, its commercialization has not taken place.

Critics of HT crops raise concerns aboutenvironmental hazards, health issues, biodiversitydecline, and moral obligations. Above all, theconundrum of herbicide resistance development inweeds has seriously threatened the sustainable use ofHT crops as a weed management option (Heap2014). No doubt, HT crops are playing a remark-able role in weed management but a seriousproblem remains the leakage of resistant genetictraits from crops to the associated weeds (Owen andZelaya 2005). To allay the problem of herbicideresistance in weeds, a second-generation phase ofHT crops is being developed (Mortensen et al.2012). In the future, integrated approaches on thebasis of stacked gene crops and rotational use ofherbicides may offer effective weed control indifferent cropping regimes.

Bioherbicides

Bioherbicides are potential plant pathogensapplied to agroecosystems exogenously and repeat-edly to control weeds. Biological weed controlgained traction in the mid-80s when some of thepotent pathogens were successfully utilized to makeeffective formulations for weed control. Despite itsearly gains, this particular field is still strugglingregarding inventions or launching products, butconsistent theoretical development is still evident(Hallett 2005). Given the changing climate, evolu-tion of herbicide resistance in weeds, and laggingscience of synthetic herbicides, innovations in the

field of bioherbicides are much needed (Charudattanand Dinoor 2000). Currently, eight bioherbicideshave been registered and are being commercialized.These products have been proven effective in specificweed management scenarios and helped a great dealin effective integrated weed management. Most ofthem include fungal pathogens and are based in theUnited States or Canada. Over 200 plant pathogenshave been identified for use of this purpose afterconsiderable technological developments (Hoagland1996). Biotechnology has a pivotal role in thedevelopment and modification of bioherbicides.Advancements in screening, formulation, augmen-tation, and application of bioherbicides dependupon biotechnological tools (Ghosheh 2005).

Bioherbicides have some unique advantages,making them suitable for weed management ina variety of environments. One of the mostimportant benefits of bioherbicides is their specificaction. There are no side effects like residualtoxicity, nontarget destruction, or health issues(Charudattan and Dinoor 2000). However, therole of bioherbicides in modern weed managementis complementary rather than exclusive. They lackattributes to be considered as a solo scavenger(Hoagland et al. 2007). There are many limitationsand constraints in the implementation of bioherbi-cides in weed management (Table 5). Comprehen-sive research on genetic, biological, environmental,technological, and financial aspects of this technol-ogy is recommended.

Thermal Weed Management

Plant tissues are susceptible to high temperatures,when most of the physiological functions aredisrupted because of membrane rupture, proteindenaturation, and enzyme inactivation. This led tothe development of weed management strategiesinvolving high temperature. Most of the plants dieafter exposure temperatures between 45 and 55 C(Zimdahl 2013). To control weeds, heat may beused in different ways, including direct flaming,solarization, and microwave technology.

Flaming. Flaming is a unique technique to killweeds through the use of direct heat in the form offire. The temperature of about 55 C is used to killthe weeds by destroying the cell wall structure. Fueland temperature requirements depend on weedgrowth stage and biomass. However, for effectiveweed control, frequent flaming is often needed(Ascard 1994). Commonly, propane is used as fuel,



https://doi.org/10.1614/WS-D-15-00064.1



but relatively renewable alternatives like hydrogen arealso under consideration (Andersen 1997). Flameweeding is most prevalent in European countries(Bond and Grundy 2001). Weeds that have thinleaves like common lambsquarters, nettle, andchickweed are readily burnt through flaming,whereas shepherd’s purse, barnyardgrass, and annualbluegrass (Poa annua L.) could not be burnt ina single operation (Ascard 1995). Flaming has showngood results after weed emergence but before cropemergence in potato (Solanum tuberosum L.), sugarbeet, carrot (Daucus carota L.), and cayenne pepper(Capsicum annuum L.) (Melander 1998). Rask et al.(2012) studied the effect of flaming on grasses andshared some positive results regarding the control ofgrasses. Knezevic and Ulloa (2007) evaluatedbroadcast flaming in different agronomic crops tomanage barnyardgrass, green foxtail, velvetleaf, andredroot pigweed and concluded that flaming offersbest control for broad-leaved weeds, whereas thegrasses are less susceptible. Corn and sorghum (bothfrom the Poaceae family) were tolerant to flaming,whereas soybean and sunflower were susceptible(Knezevic and Ulloa 2007). Weeds of corn weresignificantly controlled through integration of tillageand flaming (Knezevic et al. 2011).

Flaming has provided effective weed control indifferent ecosystems and has led to system stability.

In many regions, fire is not a threat but a tool toreduce competition and to improve nutrient cycling(Kyser and DiTomaso 2002). A quick response andprompt results are also the distinct features of flameweeding. With advancement in this subject, logisticmodels have been developed to estimate theefficiency of flame weeding and species responseto flaming (Ascard 1995). Further research isneeded to optimize the technology for its safe usein field crops.

Solarization. Solarization is a practice of coveringthe soil with plastic sheets, converting solar energyto heat to kill weeds before sowing of the crop. Soilsterilization is an effective approach toward weedmanagement by applying steam directly to killweeds or by solarization. It suppresses weedgermination and kills existing seedlings (Horowitzet al. 1983). Additional benefits of solarization areimproved crop germination due to optimal tem-perature attainment and destruction of plantpathogens due to the sterilization effect of heat.Winter annual weeds were found to be moresensitive to solarization, but summer annuals likecrabgrass and common purslane were less affectedby heat. Perennials like bermudagrass (Cynodondactylon L.), Johnsongrass [Sorghum helepense (L.)Pers.], and field bindweed (Convolvulus arvensis L.)

Table 5. Limitations in bioherbicide development.

Limitations

Type Factors Processes affected Suggested measures Reference

Environmental Effect of temperature,dew period, relativehumidity, rainfall;environment ofphyllosphere

Formulationand efficacy

Frequent applications, improvementin formulation process, use ofvigorous pathogens, improvedapplication technology

Charudattan andDinoor (2000);Ghosheh (2005);Hallett (2005);Scheepens et al. (2001)

Biological Host specificity, resistance,infection period, andnarrow spectrum

Formulation,infection,effectiveness,augmentation

Genetic improvement,stacking technology to widenthe effectiveness spectrum,integration with chemicalherbicides

Auld and Morin (1995);Charudattan (2001,2005)

Technological Pathogen strainidentification,shelf life, applicationtechniques

Formulation,application

New formulations,use of surfactants andadjuvants to improveapplication and efficacy

Ghosheh (2005);Patzoldt et al. (2001)

Legal Rigid registrationlaws, dominatingchemical herbicideindustry

Registration,dissemination

Restructuring registrationlaws and extension policies

Ghosheh (2005)

Financial Funding forresearch programs,commercialization

Overalldevelopmentand progress ofbioherbicides

Allocation of funds forintegrated programs based onbioherbicide development,development ofcross-disciplinary projects

Ghosheh (2005);Hallett (2005);McConnachie et al. (2003)



https://doi.org/10.1614/WS-D-15-00064.1



were least affected by solarization because of theirwell-developed underground parts (Horowitz etal.1983; DeVay et al. 1991). Solarization durationand its interaction with cultivated soil depth causesignificant difference in weed control. It works moreefficiently in tilled soils. Solarization along with greenmanuring suppressed annual bluegrass significantly(Peachey et al. 2001). Integrated use of polyethylenesheets and poultry manure mulch affected emergenceof field dodder (Cuscuta campestris Yuncker) (Haidarand Sidahmed 2000). Solarization for 2 mo withpolyethylene covering killed 95% of broomrape(Orobanche ramosa L.) seeds (Mauromicale et al.2005). The success of solarization depends uponexposure to light, soil texture, moisture status, andweed flora. It is a pragmatic option and has vastimplications for integrated weed management.

Microwaves and Radiations. Use of microwaveenergy to kill weeds has gained popularity in therecent past. It is based on the high energy ofmicrowaves, which can kill weeds very efficiently.This method is highly targeted and there is no fearof nontargeted damage (Rask and Kristofferson2007). Microwaves were successfully used in Den-mark for the control of little mallow (Malvaparviflora L.), hairy fleabane [Conyza bonariensis(L.) Cronq.], and gooseberry gourd (Cucumismyriocarpus E. Mey. ex Naud.) (Brodie et al.2007). This technology is effective against manyweeds, but the energy required is very high, whichincreases its cost (Sartorato et al. 2006). However,its efficiency and energy budget may be decreasedby flux configuration and through induction ofthermal runaway in weed plants, making itcomparable with other weed-control tools in termsof cost (Brodie et al. 2011). Similarly, laserradiation may be used effectively to kill weeds(Rask and Kristofferson 2007). In the United States,laser beams were used to kill water hyacinth plants.Lasers transfer high energy to plant tissues and raisethe water temperature at the cellular level, resultingin cell death. Mathiassen et al. (2006) studiedthe biological efficacy of laser treatment againstcommon chickweed and scentless chamomile[Tripleurospermum inodorum (L.) Schultz-Bip.] un-der varying levels of exposure time and observedthat weeds were significantly suppressed. Use ofultraviolet radiation for weed management has alsobeen tested (Andreasen et al. 1999; Day et al. 1993)and it was observed that the ultraviolet energy actsseverely on plant tissues. It kills weeds just likeflaming; however, limited development of this

technology is due to possible health hazards. Furtherresearch is needed in this particular aspect todevelop economically viable options on a sustainablebasis.

Hot Water, Steam, and Hot Air. Heat can also beused to kill weeds through hot water application.Hot water treatment for weed control has beentrialed in many countries with a great deal of success(Rask and Kristofferson 2007). In the 1990s,a commercial tool, Aqua Heat, was developed inthe United States to apply hot water for weedcontrol (Berling 1992). Hot water applicationproved effective against most of the annual anda large number of perennial weeds. The effects wereeven comparable against a glyphosate application.Similar kinds of equipment were successfully usedagainst weeds in New Zealand, where hot waterremained in contact with weeds for a longer periodof time (Rask and Kristofferson 2007). Hot waterequipment for weed control is also available inDenmark and the Netherlands. Hot water treat-ment is safe and has no side effects like flameweeding or radiation methods. Its effectiveness isgreater under dense weed population because ofincreased penetration ability (Hansson and Ascard2002). Because of a greater success rate, thistechnique is being considered in precision weedmanagement strategies in European countries. Useof steam instead of hot water has been observed asa more effective, quick, and sustainable method,especially in cases where weed control is onrelatively hard surfaces (Rask and Kristofferson2007). Engineering efforts are needed in this area toimprove the efficiency of availability of equipmentand to introduce new equipment for weed manage-ment in crop production regimes.

Electrocution. The practice of weed control viaelectric shock is called electrocution. Although it isa less-researched domain, evidence supports the factthat weeds can be killed by spark discharge orelectrical contact (Diprose and Benson 1984; Parish1990). The strength of electric shock, contact orexposure duration, weed species, morphologicalfeatures, and growth stage significantly affect thesuccess of electrocution. The severity of damage isaggravated in cases of dry soil conditions (Diproseand Benson 1984). However, because of higher costsinvolved, energy crises, and hazards to operators, itsapplication in agriculture is limited. In the future,this particular method may have practical implica-tions, especially in organic farming.



https://doi.org/10.1614/WS-D-15-00064.1



Precision Weed Management

Precision weed management is based on bringingin information technology for decision makingabout site-specific weed control (Christensen et al.2009). Spatial heterogeneity in weed infestationprovides the basis for the implication of suchsystems. For instance, early-season site-specific weedmanagement is the approach of weed patch de-tection, mapping, and prompt control throughmachine vision, while keeping the economicfeasibility in mind (Freckleton and Stephens 2009).

Modeling. Modeling is a potential tool to assessthe actual scenario of weed dynamics for thesubsequent management strategies. Weed modelingis a relatively complex subject and several mathe-matical and statistical tools are used to forma precise model (Freckleton and Stephens 2009).Successful modeling that is based on the datacollected through sensing technologies providesa clear picture about weed seed bank dynamics,emergence patterns, replacement trends, competi-tiveness, canopy architecture, and possible yieldlosses (Christensen et al. 2009; Rew and Cousens2001). Decision-making tools and models help toidentify and measure the influence of variables likesoil conditions, environmental factors, crop hus-bandry practices and mechanization on weedemergence, distribution, and competition patterns(Christensen et al. 2009).

There are generally two aspects of weed model-ing: one is efficacy based and the other is populationbased (Freckleton and Stephens 2009). Efficacy-based modeling involves the assessment of controlmeasures and their effectiveness (Wiles et al. 1996).It helps in making decisions about herbicide choiceand dose for appropriate weed control. For instance,the weed model SELOMA helps to decide thesuitable herbicide under prevailing conditions(Stigliani and Resina 1993). The precision of anymodel depends on details provided, number andnature of variables, and the validation process(Freckleton and Stephens 2009). On the otherhand, population-based predictive models are in-tensively researched and are more prevalent in weedscience. They are used to deliver information aboutweed infestation patterns, weed density, and weedcover in a given area over a period of time. Some ofthe most useful deterministic population modelsinclude HERB, WEEDSIM, GWM, PALEWEED,and GESTINF (Christensen et al. 2009; Freckletonand Stephens 2009).

The economic feasibility of a control measure canalso be measured precisely through modeling whereonly cost-effective strategies may be considered(Christensen et al. 2009). Another beneficial aspectof weed modeling is the evaluation of weed–cropcompetition status (Christensen et al. 2003). Thefindings of a 5-yr study were encouraging, as thepredictions about dose reduction, economic status,and competition intensity were precise (Christensenet al. 2009). Modeling for weed dynamics in wheat,sugar beet, corn, and barley also provided goodresults in terms of precision and decision support(Gerhards and Christensen 2003). The modelingapproach is very impressive for the implementationof precision weed management; however, there arecertain limitations with it. Most of the predictivedecision support models rely on weed data thatconsider weed populations in even distributions andthus foresee the yield losses in an exaggeratedmanner. Similarly, the weed population trend maybe misread sometimes, because of uneven weeddistribution (Brain and Cousens 1990; Christensenet al. 2009). Problems related to input data, remotesensing, and choice of model may also influence theefficiency and precision of weed models. Finetuning of the whole regime may improve theefficacy of modeling and consequently the implica-tion of precision weed management.

Remote Sensing. Remote sensing is a moderntechnology used in agriculture to ensure theprecision management of inputs as well as to frameout weed presence (Thorp and Tian 2004). Re-mote-sensing tools can be used to detect weedpatches, or in other words, to map weed densities infield crops and forest areas. It is well known thatweeds are mostly prevalent in patches on agricul-tural lands. Therefore, remote sensing is a goodoption to reduce the herbicide application and costof production by enhancing the herbicide applica-tion efficiency (Medlin and Shaw 2000). Remotesensing is based on differential spectral reflectance ofweeds and other vegetation, like crops and spectralresolution of the instrument in use. These twofactors govern the efficacy of remote sensing inmapping weeds. It is a prerequisite that the pixelquality must be higher than the difference inreflective indices of vegetation. The higher thisdifference is and the sharper the pixels, the higherthe quality of the picture will be, which is crucial forsubsequent mapping (Zhang et al. 1998). On theother hand, stubbles or residues may hinder becauseof the similarity with emerging or even established



https://doi.org/10.1614/WS-D-15-00064.1



weed vegetation, which makes it hard to discrim-inate the living and nonliving vegetation. Similarly,at the earlier stages of the crop stand, this problemmay be enhanced in part, but a simple solution isthe comparison of images obtained with the maps offallow land plots (Lamb and Weedon 1998).

Some weed species have been successfullymapped through remote sensing in cereal andlegume crops, especially with higher-resolutionimagery in row crops (Table 6). It was observedthat weeds can be identified from visuals and can bediscriminated from the background vegetation. Theprime considerations about weed floristic composi-tion, canopy architecture, and leaf dimensions havemade it feasible to map them against different crops’background (Zhang et al. 1998). Differences ingrowth stages of weeds and crops, emergence

patterns, growing habits, vigor, and characteristicsat maturity also provide help in sensing themremotely to sketch fine and accurate maps (Lamband Weedon 1998; Medlin and Shaw 2000). Someresearchers use classification algorithms for POSTweed sensing. These algorithms are actually basedon statistical variability and the trend between theweed densities before crop emergence against baresoils and after expected populations (Lamb andWeedon 1998; Lass et al. 2005). In this way, remotesensing is currently being used for statisticalmodeling of weed distribution patterns (Lass et al.2005). One such technique is geostatistics, which isused for descriptive analysis of weed aggregationand spatial variation (Medlin et al. 2000). Differentmethods of remote sensing are based on thisprinciple; however, they differ in the position of

Table 6. Weed species mapped against different background environments through remote sensing.

Weed species mapped

Name Family Background environment Reference

Quackgrass Poaceae No-till corn at seedlingstage having stubbleand bare soil background

Lamb and Brown (2001)

Foxtail grasses(Setaria spp.)

Poaceae

Dandelion AsteraceaeCommon lambsquarters ChenopodiaceaeWild oat Poaceae Seedlings of Triticale

sown with cloverLamb et al. (1999)

Hairy panic(Panicum effusum)

Poaceae Canola stubbles Lamb and Weedon (1998)

Wild radish(Rhaphanus raphanistrum)

Brassicaceae Oat Lamb et al. (1999)

Wild oat Poaceae WheatLondon rocket

(Sisymbrium irio L.)Brassicaceae Cabbage

(Brassica oleracea var. capitata)Menges et al. (1985)

Johnsongrass Poaceae SorghumPigweed Amaranthaceae Mature cottonRagweed parthenium

(Parthenium hysterophorous L.)Asteraceae Carrot

Broom snakeweed[Gutierrezia sarothrae(Pursh) Britt. & Rusby]

Asteraceae Rangelands Everitt et al. (1987)

Spiny aster(Aster spinosus Benth.)

Asteraceae

Meadow hawkweed(Hieracium pratense Tausch)

Asteraceae Pastures Lass and Callihan (1997)

Oxeye daisy(Chrysanthemum leucanthemum L.)

Asteraceae Forest meadows

Common cocklebur(Xanthium strumarium L.)

Asteraceae Soybean Hestir et al. (2008)

Perennial pepperweed(Lepidium latifolium L.)

Brassicaceae Estuaries Hestir et al. (2008)

Water hyacinth[Eichhornia crassipes (Mart.) Solms]

Pontederiaceae

Brazilian waterweed(Egeria densa Planch.)

Hydrocharitaceae



https://doi.org/10.1614/WS-D-15-00064.1



the sensor, resolution used, and mapping orienta-tion. Each has merits and demerits associated withefficacy of tools being used (Table 7).

Aerial and Satellite Remote Sensing. Aerial installa-tion of weed sensors is a useful way to monitora large area. This technique can be used for imagingweed vegetation as it provides an overhead view ofthe whole field. The use of aerial sensors for weeddetection was started after the 1980s and has gainedreasonable popularity since then (Thorp and Tian2004). Color imaging was the first method used inthis technology and which later developed into colorinfrared photography to better screen weeds fromremaining vegetation. Reflective indices of the near-infrared (NIR) spectrum were more variable ascompared with those of visible spectrum (Price1994). Noxious weeds of different arable crops weresuccessfully detected and mapped with reasonableaccuracy (Table 6). Spectral signature mixing inweed sensing through aerial sensing remains an issueand was only used for thematic classifications. Thus,weed infestation regions were delineated on thebasis of statistical variability measurements. On theother hand, aerial tools are being successfully usedto delineate weed boundaries in rangelands, asthematic classification is more appropriate in suchsystems (Medlin et al. 2000). However, computer-based weed sensing is still a useful option via aerialsensor data input. Airborne sensors are more flexiblein their function and application.

Satellite images are used for weed sensing. It isvery common to use global positioning systems(GPS) and geographic information systems (GIS)for spectral analysis, tracking, and aerial locationdetection—their role in weed detection, though, israre and complex. Multispectral images are com-mercially available from different satellites (Stafford2000). The IKONOS satellite offered 4-m resolu-tion in a multispectral mode. Similarly, images fromSPOT, AVHRR, and TM satellites are in the rangeof 30 m to 1.1 km. These multispectral images fallwithin a wide range of visible, infrared (IR), andNIR spectrums (Lamb and Brown 2001; Lamb andWeedon 1998). In a previous study, Memon et al.(2011) surveyed and mapped noxious weed speciesof wheat and cotton in the cotton–wheat croppingsystem through GIS and GPS. Recent advancementin the use of aerial and satellite weed sensing isreplacing color and color infrared imaging withhyperspectral and multispectral technologies. Mul-tiband multispectral cameras have been introducedto take images of densely populated weed species;

encouraging results have been observed (Hestir et al.2008). The use of multispectral scanners isbecoming popular in place of aerial or satelliteimaging and video sensing. For instance, thecompact airborne spectrographic imager is anairborne scanning device operated at a height of1,200 m with great accuracy (Stafford 2000).

On-Ground Remote Sensing. To compensate for theproblems associated with aerial and satellite remotesensing, ground-based sensing devices have beendeveloped. On-ground remote sensing has a highdegree of precision and efficiency. Photodetectorsare actually used along with sensors. These givea very clear picture about weed infestation anddensity (Thorp and Tian 2004). On the basis of thisprinciple, weed-detection model instruments havebeen developed. Hanks and Beck (1998) analyzedtwo commercially available systems, the DetectsprayModel S-50 and the WeedSeeker Model PhD 1620,which use photoelectric sensor readings to triggernozzles for a spraying application. Photoelectricsensors are not able to distinguish between crop andweeds; therefore, plastic spray hoods were used toprevent vegetation within the crop rows fromtriggering the spray (Thorp and Tian 2004).

Unmanned Aerial Vehicles (UAVs). Weed popula-tions in patches make it difficult to assess the actualscenario from the remote images with very smallpixels. Weeds growing against a soil or stubblebackground offer difficulty in gathering accur-ate information (Lopez-Granados 2011; Torres-Sanchez et al. 2013). To address these issues, UAVshave been introduced in recent years. These areautomated drones with fixed high-resolution cam-eras, able to fly at very low altitudes. Given theirability to fly immediately, frequent high-resolutionimaging capabilities, capacity to capture imageseven under clouds, placement flexibility, andeconomic feasibility are the unique selling pointsof UAVs, which make viable tools for futureautomated weed management (Anderson andGaston 2013; Pena et al. 2013; Torres-Sanchezet al. 2013 Xiang and Tian 2011). The use of UAVsin agriculture is still premature but encouraging. AUAV was used in monitoring glyphosate applica-tion to turf grasses through multispectral imaging(Xiang and Tian 2011). In another study, Primi-cerio et al. (2012) used a six-rotor UAV to sensevineyard growth through a multispectral camera.The use of acquisition, georeferencing, and mo-saicking in UAV imaging has improved this



https://doi.org/10.1614/WS-D-15-00064.1



Tab

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https://doi.org/10.1614/WS-D-15-00064.1



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technology, making it more suitable for precisionweed management (Zhang and Kovacs 2012). Theuse of a UAV aided by a six-band multispectralcamera was very successful for weed detection ina cornfield (Pena et al. 2013).

A successful case study on the use of UAVs forweed management in agronomic crops in Spain isworth sharing with details. Torres-Sanchez et al.(2013) directly utilized the UAV technology in site-specific weed management. It was suggested thatUAV technology can play a vital role in early-seasonsite-specific weed management in sunflower, corn,sugar beet, and tomato (Solanum lycopersicum L.)crops (Torres-Sanchez et al. 2013). After initialexpertise in technical management, UAVs canprovide very useful information for precision weedmanagement in a very short time. The availabilityand efficient working of UAVs in agriculture alsoprovide opportunities to ecologists for scale-appro-priate measurements of ecosystems. Anderson andGaston (2013) reviewed the UAV technology witha special focus on their use in framing spatialecology. It was reported that a range of UAVs isavailable on the basis of size, structure, spatialspecifications, camera position, mobility, and flightaltitude. UAVs are mainly applicable in the fields ofpopulation ecology (Sarda-Palomera et al. 2012),vegetation dynamics (Getzin et al. 2012), andecosystem processing (Mayer et al. 2012).

Robotics. With the advancement in roboticsresearch for agriculture, it is now possible to usethem for one of the least mechanized aspect, that is,weed control (Young et al. 2014). Weed control isno longer limited to the use of manual eradicationor herbicide sprays but can now include the use oftargeted operations of machines. Slaughter et al.(2008) reported the use of robotics for weedmanagement, a revolutionary development withmultiple benefits.

Robotic weed management is a four-step process,involving guidance, identification, precision roboticremoval, and mapping of weed species (Young 2012;Young et al. 2014). The feasibility of a robotic weed-control system depends upon machine visionanalyses, robotic efficiency/suitability, variable rateapplication technology, decision support system, andstrength of weed-sensing tools, directly or indirectly(Slaughter et al. 2008; Young 2012). Guidance inrow crops is accomplished with real-time kinematicGPS or through machine vision. This techniqueenables a researcher to detect the intensification of in-row weeds and helps to frame threshold levels for

applying control measures (Slaughter et al. 2008;Young 2012). Slaughter et al. (1999) used real-timecolor segmentation technology for guidance indirect-seeded lettuce, cotton, and tomato crops atdifferent growth stages. Similarly, Kise et al. (2005)developed a guidance system on the basis of NIRstereovision, providing data of weeds in cereals butrequiring some weed-free areas for calibration beforeactual guidance operation.

The machine vision directly depends uponclimate conditions, farming practices, regionaltopographic differences, and cropping systems(Astrand and Baerveldt 2002; Slaughter et al.2008). The bases for detection are classified asmorphological features, spectral features, and visualtextures. Morphological features of weed plants areconsidered as potential tools for machine visiondetection, especially for distinction from othervegetation (Brown and Noble 2005; Søgaard2005). Søgaard (2005) classified shepherd’s purse,scentless mayweed, and wild mustard with greataccuracy by using these active shape models. Plantreflectance is another successful indicator for weeddetection through machine vision (Scotford andMiller 2005). Precise robotic weed removal on thebasis of weed indication by guidance and detec-tion is the next step. There might be the use ofmechanical (Astrand and Baerveldt 2002), chemical(Lamm et al. 2002; Lee et al. 1999), thermal, orelectrical (Blasco et al. 2002) approaches to removeweeds through robots. All the methods showedvariable response regarding weed control; however,certain benefits are associated with each one(Table 8). Young et al. (2014) suggested automatedweed control through robotics, a viable option forbest integrated weed management in the future.

These technologies are no doubt the future ofmodern weed management and have a great role toplay in precision agriculture. There is still a lot ofresearch needed to optimize the technical require-ments and to resolve the complex issues at theinterface of weed spatial ecology and precisionmanagement.

Conclusions and Future Perspective

Weed management under changing climate andagricultural practices requires modern strategies. Thenonjudicious use of chemical herbicides is causingenvironmental damage, health hazards, herbicideresistance in weeds, and nontarget actions. Thus,a set of alternative weed-management tools isneeded under the prevailing conditions. The use of



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nonconventional and possibly nonchemical weed-management strategies discussed above in an in-tegrated manner can help on a sustainable basis. Allthese methods focus on environmental protection,practical viability, compatibility for integrated pro-grams, and ecological stability. The right choice ofone or more of these strategies according togeographic, agricultural, and socioeconomic condi-tions may offer an impressive weed control. None ofthem has the potential to comprehensively replacechemical weed management; however, an integratedapproach may lead to success. The diversified natureof these strategies may be very useful against invasiveand resistant weeds. Further research is needed tooptimize these tools for improvement in efficiencyand practical suitability. In the long run, a singleweed-control measure may not remain effective and,thus, integrated weed management on the basis ofadvanced nonconventional strategies will be a prag-matic option in modern intensive agriculture.

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Received April 18, 2015, and accepted June 16, 2015.

Associate Editor for this paper: William Vencill, Universityof Georgia.



https://doi.org/10.1614/WS-D-15-00064.1



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