antibiotics impact plant traits, even at small concentrations

Research Article

Antibiotics impact plant traits even at smallconcentrations

Vanessa Minden12 Andrea Deloy2 Anna Martina Volkert2 Sara Diana Leonhardt3 andGesine Pufal4

1 Department of Biology Ecology and Biodiversity Vrije Universiteit Brussel Pleinlaan 2 1050 Brussels Belgium2 Landscape Ecology Group Institute of Biology and Environmental Sciences Carl von Ossietzky-Strasse 9-11 26111 OldenburgGermany3 Department of Animal Ecology and Tropical Biology Biozentrum Am Hubland University of Wurzburg 97074 Wurzburg Germany4 Nature Conservation and Landscape Ecology Faculty of Environment and Natural Resources University of Freiburg TennenbacherStrasse 4 79106 Freiburg Germany

Received 12 October 2016 Editorial decision 7 February 2017 Accepted 8 March 2017 Published 13 March 2017

Associate Editor Rafael Oliveira

Citation Minden V Deloy A Volkert AM Leonhardt SD Pufal G 2017 Antibiotics impact plant traits even at small concentrationsAoB PLANTS 9 plx010 doi101093aobplaplx010

Abstract Antibiotics of veterinary origin are released to agricultural fields via grazing animals or manure Possibleeffects on human health through the consumption of antibiotic exposed crop plants have been intensively investi-gated However information is still lacking on the effects of antibiotics on plants themselves particularly on non-crop species although evidence suggests adverse effects of antibiotics on growth and performance of plants Thisstudy evaluated the effects of three major antibiotics penicillin sulfadiazine and tetracycline on the germinationrates and post-germinative traits of four plant species during ontogenesis and at the time of full developmentAntibiotic concentrations were chosen as to reflect in vivo situations ie concentrations similar to those detected insoils Plant species included two herb species and two grass species and represent two crop-species and two non-crop species commonly found in field margins respectively Germination tests were performed in climate chambersand effects on the remaining plant traits were determined in greenhouse experiments Results show that antibioticseven in small concentrations significantly affect plant traits These effects include delayed germination and post-germinative development Effects were species and functional group dependent with herbs being more sensitive toantibiotics then grasses Responses were either negative or positive depending on plant species and antibioticEffects were generally stronger for penicillin and sulfadiazine than for tetracycline Our study shows that croplandspecies respond to the use of different antibiotics in livestock industry for example with delayed germination andlower biomass allocation indicating possible effects on yield in farmland fertilized with manure containing antibi-otics Also antibiotics can alter the composition of plant species in natural field margins due to different species-specific responses with unknown consequences for higher trophic levels

Keywords Brassica napus Capsella bursa-pastoris germination hormesis penicillin plant functional traits sul-fadiazine tetracycline

Corresponding authorrsquos e-mail address vanessamindenuni-oldenburgde

VC The Authors 2017 Published by Oxford University Press on behalf of the Annals of Botany CompanyThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (httpcreativecommonsorglicensesby40) which permits unrestricted reuse distribution and reproduction in any medium provided the original work is prop-erly cited

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Introduction

Antibiotics are used to treat infections in humans andanimals by either directly killing bacteria or inhibitingtheir growth (World Health Organization 2015 Chopraand Roberts 2001 Miller 2002) The use of antibiotics hasbecome integral to livestock industry with 8481 t of vet-erinary antibiotics sold alone in the EUEEA (EuropeanEconomic Area) in 2011 (European Medicines Agency2013) Antibiotics applied to animals are poorly absorbedin the gut and as much as 90 of some antibiotics maybe excreted (Kumar et al 2005 Winckler and Grafe 2001Jjemba 2002) These antibiotics may be released to theenvironment by grazing animals or manure (Thiele-Bruhn 2003 Martinez-Carballo et al 2007) Some antibi-otics are highly stable in manure and soil with residuesstill detectable one year after application (Thiele-Bruhn2003) Some antibiotics may even persist for severalyears (Forster et al 2009) For example in agriculturallandscapes with conventional land use and manure fer-tilization tetracycline and sulfadiazine were detectedat average soil concentrations of 10ndash15mg kg1 and32ndash198mg kg1 respectively (Hamscher et al 20002002 2005 Christian et al 2003 Aust et al 2008) Fromthe farmlands antibiotics may then be transported fur-ther to ditches streams and rivers via runoff (Kay et al2005 Burkhardt et al 2005 Stoob et al 2007) togroundwater via leaching (Blackwell et al 2007) or maydirectly be ingested by organisms (Boxall et al 2006)How organisms respond to natural concentrations ofantibiotics as found in soil water and other organisms ishowever poorly understood The majority of studiesconducted for elucidating the effect of antibiotics onplants used much higher concentrations which donot resemble in vivo situations (eg Liu et al 2009(100ndash500 000mg L1) Michelini et al 2013(11 500mg L1) Migliore et al 2010 (5ndash50 000mg L1)Michelini et al 2012 (10 000ndash200 000mg kg1))

Whereas possible detrimental effects of antibioticstaken up by crop plants on human health have been in-tensively investigated (Grote et al 2007 Kumar et al2005 Pan et al 2014 Kang et al 2013) the effect of anti-biotics on plants themselves particularly on non-cropspecies has received much less attention There is sig-nificant evidence that antibiotics adversely affect thegrowth and performance of plants (Migliore et al 2010Liu et al 2013) however they can also promote allomet-ric responses (see examples in Table 1)

Further responses can be dose-dependent egincreased growth at lower concentrations and toxic ef-fects at higher ones (so-called hormetic responses seeMigliore et al 2010) Roots are typically most affected byand accumulate most antibiotics (Migliore et al 2010)

where they negatively impact on root length root elong-ation and number of lateral roots with consequences forplant water uptake (Piotrowicz-Cieslak et al 2010Michelini et al 2012) Further studies showed that antibi-otics can alter biomass production number of leavesbranching patterns shoot length internode length rootshoot ratio freshdry weight CN and KCa ratio etc(Bradel et al 2000 Liu et al 2009 Yang et al 2010Michelini et al 2012 Li et al 2011) Physiological traitsaffected by antibiotics are for instance photosyntheticrate chloroplast synthase activity transpiration ratestomatal conductance and synthesis of abscisic acid(ABA) (Kasai et al 2004 Werner et al 2007) These stud-ies clearly demonstrate that various antibiotics in the soilcan be accumulated in plant tissues and have either det-rimental or enhancing effects on functional traits of cropand wild plant species They also show that effects de-pend on plant species plant organ type of antibioticapplied and its concentration However these studieswere conducted under artificial conditions with mostlyunnaturally high antibiotic concentrations not necessar-ily mirroring in vivo conditions Whether these effectsalso occur for lower antibiotic concentrations remainslargely unclear

To address this knowledge gap we studied the effectof three antibiotics with different action modes (ie peni-cillin tetracycline and sulfadiazine) on four plant speciesincluding crop (Brassica napus and Triticum aestivum)and non-crop (Capsella bursa-pastoris and Apera spica-venti) species Both crop species (B napus andT aestivum) belong to the most commonly grown cropsworldwide (Leff et al 2004 FAOmdashFood and AgricultureOrganization of the United Nations 2016) and are highlylikely exposed to antibiotics due to fertilization of cropfields with slurry or manure The non-crop species(C bursa-pastoris and A spica-venti) are commonlyfound along most crop field margins in Germany and arelikely unintentionally exposed to antibiotic charged ma-nure applied to fields (Ellenberg and Leuschner 2010)We applied concentrations of antibiotics as previously re-ported for grasslands (from now on referred to as naturalconcentrations Thiele-Bruhn 2003) to plants grown ingreenhouses and measured germination rates and plantfunctional traits during ontogenesis and at fully de-veloped plant individuals

Specifically we asked (i) whether natural concentra-tions of antibiotics affect both germination and func-tional traits of plants and (ii) whether trait responseswere more similar among crop and non-crop plant spe-cies than between crop and non-crop species (ieB napus and T aestivum versus C bursa-pastoris andA spica-venti) or among herbs and grasses (eg B napusand C bursa-pastoris) than between herbs and grasses

Minden et al ndash Antibiotics impact plant traits

002 AoB PLANTS wwwaobplantsoxfordjournalsorg VC The Authors 2017

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Table 1 Examples of how antibiotics affect crop plants and non-crop plants

Crop plant species

Antibiotic Target species Concentration Effect on plantsreference

Amoxicillin Carrot (Daucus carota) 1ndash10 000mg L1 No effect on germination despite the highest

Chlortetracycline Lettuce (Lactuca sativa) concentration decrease of root and shoot

Levofloxacin Alfalfa (Medicago sativa) lengths at several concentrations1

Lincomycin

Oxytetracycline

Sulfamethazine

Sulfamethoxazole

Tetracycline

Trimethoprim

Tylosin

Chlortetracycline Corn (Zea mays) 002mg mL1 Bioaccumulation2

Green Onion (Allium cepa)

Cabbage (Brassica oleracea)

Chlortetracycline Sweet Oat (Avena sativa) 0ndash500 mg L1 Germination partly inhibited decrease growth

towards sulfonamides inhibition of

Tetracycline Rice (Oryza sativa) phosphatase activity3

Tylosin Cucumber (Cucumis sativus)

Sulfamethoxazole

Sulfamethazine

Trimethoprim

Gentamicin Carrot (Daucus carota) 0 05 1 mg kg1 Bioaccumulation partly reduced growth4

Streptomycin Lettuce (Lactuca sativa)

Radish (Rhaphanus sativus)

Sulfadimethoxine Millet (Panicum miliaceum) 300 mg L1 Reduction in root and stem growth lower num-

ber of leaves lower biomass production5

Pea (Pisum sativum)

Corn (Zea mays)

Sulfamethoxine Barley (Hordeum vulgare) 115mg mL1 Stimulation of root hair and lateral roots

increased electrolyte release from roots6

Sulfamethazine

Sulfamethazine Yellow lupin (Lupinus luteus) 001 01 025 Appearance of necroses and root decay

Pea (Pisum sativum) 1 5 15 20 mM decreased activity of mitochondrial cytochrome

c oxidase7

Lentil (Lens culinaris)

Soybean (Glycine max)

Adzuki bean (Vigna angularis)

Alfalfa (Medicago sativa)

Sulfonamide Corn (Zea mays) 10 200mg g1

Continued



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Table 1 Continued

Crop plant species


Bioaccumulation reduced stem length develop-

ment death8

Tetracycline Wheat (Triticum aestivum) 0ndash100 mg L1 Reduced growth of roots and stems no effect

on germination9

Tetracycline Pea (Pisum sativum) 0ndash8 mg kg1 Bioaccumulation decreased peroxidase activity

Oxytetracycline (at concentrations above 04 mgkg)

Chlortetracycline decreased root length10

Tetracycline Carrot (Daucus carota) 0ndash300 mg L1 Decrease in germination rates inhibition of root

Sulfamethazine Cucumber (Cucumis sativus) and shoot elongation11

Norfloxacin Lettuce (Lactuca sativa)

Erythromycin Tomato (Lycopersicon esculentum)

Chloramphenicol

Oxytetracycline Wheat (Triticum aestivum) 0ndash008 mmol L1 Decrease in biomass and shoot length de-

creases in photosynthetic rate transpiration

rate and stomatal conductance increase in

intercellular CO2 concentrations12

Non-crop plant species

Ciprofloxacin Common reed (Phragmites 01ndash1000mg L1 bioaccumulation toxic effect on root activity

Oxytetracycline australis) and leaf chlorophyll hermetic responses at low

Sulfamethazine concentrations (01ndash1mgL)13

Sulfonamide Crack Willow (Salix fragilis) 10 200mg g1 Bioaccumulation reduced total chlorophyll con-

tent reduced CN content14

Sulfadimethoxine Common amaranth (Amaranthus

retroflexus)

300 mg L1 Decrease of root length epicotyl length cotyle-

don length and number of leaves15

Broadleaf Plantain (Plantago major) 300 mg L1

Red Sorrel (Rumex acetosella)

Sulfadimethoxine Purple Loosetrife (Lythrum salicaria) 0005ndash50 mg L1 Toxic effect on roots coytledons and cotyledon

petioles dose-depending response of inter-

nodes and leaf length (hormetic response)16

Tetracycline Poinsettia (Euphorbia pulcherrima) 100ndash1000 ppm Suppression of the free-branching pattern17

References 1Hillis et al (2011) 2Kumar et al (2005) 3Liu et al (2009) 4Bassil et al (2013) 5Migliore et al (1995) 6Michelini et al (2013)7Piotrowicz-Cieslak et al (2010) 8Michelini et al (2012) 9Yang et al (2010) 9Kasai et al (2004) 10Ziolkowska et al (2015) 11Pan and Chu

(2016) 12Li et al (2011) 13Liu et al (2013) 14Michelini et al (2012) 15Migliore et al (1997) 16Migliore et al (2010) 17Bradel et al (2000)



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Given the low concentration rates and the three antibi-otics differing in their action modes used in this study weallowed for the following expectations germinationrates and functional trait responses (i) could be nega-tively affected as reported by other studies (ii) could beunaffected and not differ from control treatments and(iii) could be higher than the control treatments The lat-ter would point to a hormetic response with increasedvalues in lower treatments

Methods

Selected species

Two crop species and two non-crop species were chosenwith one representative of either group belonging to thefamily of Brassicaceae (B napus (summer rapeseed) andC bursa-pastoris (shepherdrsquos purse)) or Poaceae (T aesti-vum (wheat) and A spica-venti (loose silky-bent)) Bycomparing closely related species we minimized a poten-tial bias associated with phylogenetic distances or differ-ences in life-history or dispersal mode (congeneric orphylogenetic approach Burns 2004 van Kleunen et al2010) All species were annuals Our choice furtherallowed comparison between crop plantnon-crop plantwithin the functional groups of herbs (Brassicaceae) andgrasses (Poaceae) respectively

Seeds of the plants were ordered in April 2015 fromRieger-HofmannVR Seuroamereien Jehle (both Germany) andBotanik Seuroamereien Switzerland

Selected antibiotics and their modes of action

The three antibiotics used in this study were penicillin Gsodium salt (C16H17N2NaO4S) sulfadiazine (C10H10N4O2S)and tetracycline (C22H24N2O8) These compounds are themost commonly sold antibiotic compound classes forfood-producing species in Europe with 37 23 and11 of sold antibiotics respectively (EuropeanMedicines Agency 2013) They are all polar (withlogKWlt3) and thus likely accumulate in plant tissue(Trapp and Eggen 2013) Using polar antibiotics and con-centrations resembling those measured in grasslands(Thiele-Bruhn 2003) should therefore ensure responsesof plants to treatments and applicability of research re-sults to in vivo situations The selected antibiotics furtherdiffer in their action modes with expected different ef-fects on plants traits enabling us to relate specific resultsto a specific type of antibiotic Penicillin G belongs to thegroup of b-lactam antibiotics which inhibit the biosyn-thesis of peptidoglycan during cell division and thus in-hibits cell wall synthesis (Miller 2002 Hammes 1976)Sulfadiazine inhibits the growth of bacteria without theirdestruction (bacteriostasis) (Henry 1944) Tetracycline is

an anti-infective agent inhibiting protein synthesis bypreventing the attachment of aminoacyl-t-RNA to theribosomal acceptor (Chopra and Roberts 2001) Forknown examples for effects of these antibiotics on plantssee Table 1

Biodegradation differs between different types of anti-biotics The three antibiotics in this study have beenshown to remain stable in soil samples across time peri-ods that extend the period of this experiment (ie8 weeks see Kumar et al 2005 Hamscher et al 20022005 Christian et al 2003)

Experimental design

Plants were treated with 1mg 5mg and 10mg antibioticLfor penicillin (P1 P5 and P10) sulfadiazine (S1 S5 andS10) and tetracycline (T1 T5 and T10) as well as withtwo nitrogen addition treatments (N5 and N10 seebelow) and one control treatment (distilled water C) Toavoid confounding effects of mixtures of antibioticsthese compounds were added as separate treatmentsConverted to the amount of sand in the pots treatmentscorrespond to 0038mg kg1 019mg kg1 and038mg kg1 sand (see description of greenhouse experi-ment below)

Antibiotics were ordered at Alfa Aesar (KarlsruheGermany) Antibiotic solutions were prepared by dissolv-ing 1 mg of antibiotic in 1 L distilled water and furtherfilling up 1 mL (5 mL and 10 mL) of removed solution to1 L volume with distilled water pHs of all solutions were55

Each antibiotic used contains a nitrogen group Onemolecule penicillin contains 78 N tetracycline con-tains 63 N and sulfadiazine 224 N To differentiatebetween potential plant responses to antibiotics andorto nitrogen provided by antibiotic degradation weincluded two nitrogen (N-)treatments Concentrations inthe N-treatments were chosen to represent the amountsof nitrogen provided by the specific antibiotics in the5mg L1 treatment (N5 pooled for penicillin and tetracyc-line) and in the 10mg L1 treatment (N10 for sulfadia-zine) For the nitrogen treatment N5 215 mg NaNO3

were diluted in 1 L distilled water and 1 mL of this solu-tion was further diluted with 1 L distilled water The samewas done for the N10 treatment using 1358 mg NaNO3

Macro- and micronutrients (N P K Ca Mg Fe Cu S BMn Zn Mo) were equally applied to each experimentalpot (5 mL solutionweek) Nitrogen was applied asNaNO3 phosphorus as NaH2PO4 Composition of nutrientsolutions followed Gusewell (2005) pH was adjusted tosix

Germination experiment For each plant species a totalof 100 seeds per treatment were germinated with



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simultaneous application of antibiotics nitrogen solution(N5 and N10) and distilled water (C) respectively [seeSupporting InformationmdashFig S1]

Seeds were stratified following Anandarajah et al(1991) for B napus (4 C for 10 days) and Toorop et al(2012) for C bursa-pastoris (4 C for 3 days) For T aesti-vum and A spica-venti no specific treatment is reportedin the literature except soaking of seeds prior to sowingfor T aestivum (Siddiqui et al 2009) and storing underdry conditions for A spica-venti (Wallgren and Avholm1978)

We placed 25 seeds on filter paper in 90 mm90 mmpetri dishes with four replicates per plant species andtreatment resulting in 192 trials Filter papers weretreated with 5 mL of the respective treatment solutionPetri dishes were covered and kept in a dark climatechamber set to 24 C Germination success was eval-uated using the length of the radicle (gt2mm)Germination success was controlled each day for14 days in total and the corresponding seed was sortedout of the petri dish and discarded from the remainingexperiment

Greenhouse experiment Ten individuals per plant spe-cies were exposed to a given treatment summing up to120 individuals per species and 480 individuals in total[see Supporting InformationmdashFig S1] Plants wereraised from seeds in germination pots with germinationsoil (Gartenkrone Germany) individual plants wereplanted in 400 mL pots filled with quartz sand (VitakraftGermany) starting of June 2015 about three weeks aftersowing (B napus was planted in 2-L pots) To guaranteea homogenous substrate for all treatments and thus toprevent variation in soil-related factors (eg water-holding capacity) across pots to affect our results weused quartz sand instead of potting soil We mixed25 mL of antibiotic andor nitrogen solution with thesand before the seedlings were planted (125 mL for the2-L pots) The volume was equivalent to the quantityheld back by the quartz sand without draining To avoidleaching of the antibiotics from pots distilled water wasfilled only into saucers Nutrient solutions were providedonce a week for eight weeks Control treatmentsreceived only distilled water and nutrients Additionallyinitial biomass was determined for each species by col-lecting 30 seedlings per species separating leavesstems and roots drying them at 70 C for 72 h and finallyweighing dried samples

At the end of the experiment (ie after eight weeks)plant individuals were harvested and separated intoleaves stems and roots which were dried at 70 C for72 h and weighed Relative growth rates (RGR) of above-ground belowground and total biomass were calculated

as RGRfrac14 (logW2 logW1)(t2 t1) with W2 and W1 rep-resenting the biomass at the sequential times t2 and t1respectively (in days Hunt 1990 see Table 2 for overviewof measured traits) Canopy height was measured bi-weekly (ie four times in the total course of the experi-ment) as the distance between the pot surface and thehighest fully developed leaf of each plant individual(Perez-Harguindeguy et al 2013) Stem length was as-sessed as the total length of the aboveground shoot atthe time of harvest (in cm for B napus and C bursa-pas-toris not applicable for the two grass species)

Chlorophyll content was also measured biweekly andwas determined with a Chlorophyll Meter 502-SPAD Plus(Konica Minolta Munich Germany) which calculates anindex in lsquoSPAD unitsrsquo based on absorbance at 650 and940 nm with an accuracy of 610 SPAD units(Richardson et al 2002) At each measurement datethree SPAD measurements were taken from one leaf ofeach individual To obtain total chlorophyll content asdetermined at the time of harvest (Lichtenthaler 1987Lichtenthaler and Wellburn 1983) additional plant indi-viduals of every species and treatment were raised inextra pots to provide leaf material for wet chemical ana-lysis Leaf samples were collected and the area of250 mg fresh material determined (flatbed scanner andcomputer software ImageJ Rasband 2014) Plant mater-ial was grinded in a mortar together with 10 mL acetone(80 ) and sea sand (VWR Chemicals) and subsequentlyfiltered through a glass frit The filtrate was then filled upto 20 mL by adding acetone Absorbance of the solutionswas measured with a UVVisible spectrophotometer(Genesys 10 UV Thermo Spectronic BraunschweigGermany) at 656 and 663 nm Total chlorophyll (Totalchl mgmg) concentrations were referred to leaf dryweight by converting dry weights of scanned leaves toleaf area via regression Slopes and intercepts for chloro-phyll content (mgmg dry weight) versus SPAD units werecalculated via ordinary least square regression and usedto convert SPAD units for all individuals of the experi-ment into chlorophyll content

Specific Leaf Area (SLA) was calculated as the meanarea of two leaves divided by their mean dry weight(mm2 mm1 Perez-Harguindeguy et al 2013) Twoleaves per individual were collected to measure dryweight and area (flatbed scanner and computer softwareImageJ Rasband 2014) Living and dead leaves wereseparated and their number determined for each plantindividual If dead leaves occurred during the experi-ment they were collected and added to the number ofdead leaves at the end of the experiment We also as-sessed the biomass allocated to belowground andaboveground plant parts (RootShoot) respectivelywhich reflects either stronger allocation towards



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belowground organs (valuesgt1) or towards above-

ground organs (valueslt1)To measure Specific Root Length (SRL) ie the ratio of

root length to dry mass of fine roots (lt2 mm diameter)

a 10 cm section of root was separated from the remain-

ing roots dried (70 C 72 h) and its weight determined

(Perez-Harguindeguy et al 2013) Total Root Length was

calculated from SRL and belowground biomass

Secondary Roots were counted along the 10 cm root sec-

tion and number of Secondary Roots per 1 cm deter-

mined Length of Primary Root was measured for

B napus and C bursa-pastoris only as primary roots in

grass species degenerate in the course of ontogenesisCanopy height and chlorophyll content were meas-

ured every two weeks four times in total The remaining

15 traits were determined after the final harvest

Statistical analysis

All statistical analyses were done with the computer

software R (R Core Team 2014) Packages used were sur-

vival (survfit() Therneau and Grambsch 2000) geoR

(Ribeiro and Diggle 2015) car (Fox and Weisberg 2011)

nortest (Gross and Ligges 2015) and ggplot2 (Wickham

2009)

Germination experiment To test for differences in ger-

mination rates between control and treatments Kaplanndash

Meier Survival analysis was performed which estimates

the survival function for exact time events The Kaplanndash

Meier estimator S(t) was used to calculate non-

parametric estimates of the survivor function

SethtTHORN frac14Ys

jfrac141

1dj

nj

with dj being the number of individuals that experienced

the event (ie here germination) in a given interval and nj

the number at risk (ie all individuals) Differences be-

tween groups (control versus treatment) were calculated

using the log-rank test (Kaplan and Meier 1958 McNair

et al 2012 Kleinbaum and Klein 2012)

Greenhouse experiment To test for effects of antibiotics

and concentration (and their interactions) on response

variables (ie plant traits) analysis of variance (ANOVA)

was carried out with species antibiotics and concentra-

tion as factors with four and three levels respectively

We always tested residuals for normal distribution

and variances for homogeneity for each trait and for

each species and transformed the data where applic-

able (log- square root- or boxcox-transformation)

Table 2 Measured plant traits abbreviations and units

Plant trait Abbreviation Unit Trait representative of

Relative growth rate of aboveground biomass RGRAGB mg mg-1 day1 Growth rate

Relative growth rate of belowground biomass RGRBGB mg mg1 day1 Patterns

Relative growth rate of total biomass RGRTotal mg mg1 day1

Dry weight of leaves (live and dead) Leaf mg Biomass allocation

Dry weight of stems Stem mg

Dry weight of roots Root mg

Canopy height CH cm Growth rate and

Stem length StemL cm competition related

Chlorophyll content Chl mg mg1 plant traits

Specific Leaf Area SLA mm2 mg1

Number of live leaves Leaflive number Turnover rates

Number of dead leaves Leafdead number

RootShoot ratio RS ratio

Specific Root Length SRL mm mg1 Traits related to

Total Root Length TRL mm Nutrient uptake

Secondary Roots SecR n cm1

Length of Primary Root LPR cm



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Because differences in traits were strongly speciesspecific and the antibiotic were applied independentlyfrom each other we also tested the treatment effectsseparately for each species and antibiotic We alsotested for significant differences between the nitrogentreatments and the control with the hypothesis that ni-trogen addition in such small amounts should not have

an effect on plant traits As there were no significant dif-ferences the data of the nitrogen treatments and thecontrol treatment were pooled into one control treat-ment in subsequent analyses For the two traits whichwere measured repeatedly during the experiment (iecanopy height and chlorophyll content) we performed

paired T-tests for dependent data and tested whetherantibiotics had a significant effect on the respective traitat each date of measurement

Results

Germination experiment

Within the 14 days of the germination experiment Bnapus and T aestivum germinated most rapidly irre-

spective of treatment with a mean of 19 days (ie 45 h)and 15 days (36 h) across all treatments respectively Cbursa-pastoris germinated latest and very poorly (Table3) with a mean of 142 days and no effects of any

treatment Absolute rates of germination were highest in

T aestivum (99ndash100 ) followed by B napus (93ndash100 )

and A spica-venti (81ndash94 ) When germination was

compared within plant species for different treatments

we found germination to be generally delayed in three of

our four plant species when seeds were exposed to

higher concentrations of antibiotics (except for T1 in B

napus which germinated earlier than the control see

Table 3) For T aestivum and A spica-venti all treat-

ments but the lowest ones (P1 S1 and T1) resulted in a

significant delay of germination with the most severe

delay of 19 days (ie 45 h) at T10 in A spica-venti

Interestingly the nitrogen treatments also produced a

delay in germination in T aestivum and A spica-venti

Greenhouse experiment

Species as factor showed the strongest effect on almost

all plant traits (see F-values in Table 4) Mean trait values

were highest in C bursa-pastoris followed by B napus

and A spica-venti whereas eight out of twelve measured

trait values were lowest in T aestivum (StemL SecR

and LPR not measured for the two grass species

[see Supporting InformationmdashTable S1]) Whereas the

effect of species as factor was most pronounced those

of antibiotic and concentration were less strong

(Table 4) However every plant trait responded

Table 3 Results of KaplanndashMeier survival analysis for germination rates for the four plant species Given are the mean days until germinationfor each treatment (with corresponding hours in brackets) and germination rates in percent Bold numbers indicate significant differences tocontrol treatment (Plt005) green shading indicates earlier germination red shading indicates delayed germination of the treatment com-pared with control group Treatments were nitrogen (N5 and N10 ie 5 and 10mg L1) penicillin (P1 P5 and P10 ie 1 5 and 10mg L1) sulfa-diazine (S1 S5 and S10 ie 1 5 and 10mg L1) and tetracycline (T1 T5 and T10 ie 1 5 and 10mg L1)

Brassica napus Capsella bursa-pastoris Triticum aestivum Apera spica-venti

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



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significantly to an interaction between either SA(SpeciesAntibiotic ie RGRBGB Leaf Root RS and SRL)

SC (SpeciesConcentration ie RGRAGB RGRTotal and

LPR) or AC (AntibioticConcentration ie Stem andStemL)

To further elucidate the specific effects of each antibi-

otic on plant traits we tested for significant differences

on plant traits between the control treatment and eachantibiotic treatment

Canopy height of all four plant species increased in the

course of the experiment Whereas the two grass specieshardly responded to any antibiotic applied (ie no signifi-

cant differences in the trait means between the control

treatment and the antibiotic treatment) the canopyheight of the two herb species differed significantly from

the control plants (Fig 1) Responses were significant for

penicillin and sulfadiazine but not for tetracycline Withregard to penicillin B napus responded only at the ear-

liest two stages of measurement and only to treatment

P5 whereas C bursa-pastoris responded primarily at thelatest two stages of measurement and to treatments P1

and P10 respectively B napus plants treated with sulfa-diazine showed significant responses throughout the

course of the experiment stronger towards S1 and S10

in the earlier stages and more pronounced towards S5 in

the later stages Individuals of C bursa-pastoris re-

sponded primarily to S1 at all times of measurementdespite date 2

Measurements of total chlorophyll content showed

opposing patterns in the herb species with B napus

showing decreased and C bursa-pastoris increased pig-

ment content compared with the control (Fig 2) When

treated with penicillin and tetracycline B napus had sig-

nificantly lower chlorophyll content in the earlier and

later stage of the experiment respectively In contrast

chlorophyll content of C bursa-pastoris was predomin-antly influenced at the earliest time of measurement by

all three antibioticsT aestivum and A spica-venti responded to penicillin

and sulfadiazine but not to tetracycline Responses were

significant both at earlier and at later stages of measure-

ment and pigment content was mostly lower than in the

control treatmentFor the 15 plant traits determined after the final har-

vest 33 of all statistical tests performed (for all plantspecies) yielded significant results when plants were

treated with penicillin (53 out of 162 tests) 19 when

treated with sulfadiazine (31 out of 162) and 10

Table 4 F-values degrees of freedom and significance levels for multi-factor ANOVA analyses testing the effects of plant species antibioticconcentration and their interactions on different plant traits of Brassica napus Capsella bursa-pastoris Triticum aestivum and Apera spica-venti Stem length (StemL) number of Secondary Roots (SecR) and Length of Primary Root (LPR) were only tested for Brassica napus andCapsella bursa-pastoris see text For trait description see Table 2 Significance levels frac14 Plt005 frac14 Plt001 frac14 Plt 0001

Source DF RGRAGB RGRBGB RGRTotal Leaf Stem Root SLA Leaflive

Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183

Source DF Leafdead RS SRL TRL DF StemL SecR LPR

Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



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ber 2022

(16 out of 162) when treated with tetracycline (Tables 5

and 6 results of test statistic and means and relative

standard deviations for all treatments can be found in

[Supporting InformationmdashTable S1]) For the significant

results the direction of response ie whether trait

means were higher or lower in the treatments than in

the control was balanced for penicillin with 28 mean

trait values being higher than in the control treatment

and 25 mean trait values being lower respectively For

sulfadiazine mean trait values tended to be higher than

in the control (21 higher 10 lower) whereas the opposite

was observed for tetracycline (three higher and 13

lower)Across species trait responses were most pronounced

for penicillin In both B napus and C bursa-pastoris 44

of all traits showed a significant response to the penicillin

treatments 9 in T aestivum and 20 in A spica-venti

The responses towards the other two antibiotics were

less pronounced 18 of all B napus-traits responded

significantly to sulfadiazine (C bursa-pastoris 38

Figure 1 Means and standard deviations of canopy height (cm) for the four times of measurement (date 1ndash4) for Brassica napus Capsellabursa-pastoris Triticum aestivum and Apera spica-venti Significant differences to control treatment within each date of measurement areindicated by asterisks with Plt005 C control P penicillin treatment in the order 1 5 and 10 mg L1 S sulfadiazine treatment in the order 15 and 10 mg L1 T tetracycline treatment in the order 1 5 and 10 mg L1

Figure 2 Means and standard deviations of total chlorophyll content (mg mg1) for the four measurements (date 1ndash4) for Brassica napusCapsella bursa-pastoris Triticum aestivum and Apera spica-venti Significant differences to control treatment within each date of measure-ment are indicated by asterisks with Plt005 C control P penicillin treatment in the order 1 5 and 10 mg L1 S sulfadiazine treatment in theorder 1 5 and 10 mg L1 T tetracycline treatment in the order 1 5 and 10mg L1 SPAD values of A spica-venti leaves could not be deter-mined at the first date of measurement as leaf blades were too thin for the measurement device



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ber 2022

Table 5 Results of t-tests (Plt005) for each trait for Brassica napus Capsella bursa-pastoris Triticum aestivum and Apera spica-venti Means are given

for control treatment Arrows indicate significant differences to control treatment red arrows pointing down indicate lower values green arrows point-

ing up indicate higher values within the treatment comparisons For means and relative standard deviations of all treatments see Table 6

Brassica napus

Growth rate patterns Biomass allocation Competition Turnover rates Nutrient uptake

RGRAGB RGRBGB RGRTotal Leaf Stem Root StemL SLA Leaflive Leafdead RS SRL TRL SecR LPR

Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904

P1 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

P5 ndash ndash ndash ndash ndash ndash ndash ndash

P10 ndash ndash ndash ndash ndash ndash ndash

S1 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

S5 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

S10 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

T1 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash


T10 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

Capsella bursa-pastoris



Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504


P5 ndash ndash ndash ndash ndash ndash ndash ndash ndash


S1 ndash ndash ndash ndash ndash ndash ndash

S5 ndash ndash ndash ndash ndash ndash ndash ndash

S10 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash

T1 ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash ndash



Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA

P1 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash NA NA

P5 ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash NA NA


S1 ndash ndash ndash ndash NA ndash ndash ndash ndash ndash NA NA

S5 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash NA NA

S10 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash NA NA

T1 ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash ndash NA NA

T5 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash ndash NA NA


Continued



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ber 2022

T aestivum 17 and A spica-venti 3 ) and 16 ofB napus-traits to tetracycline (16 3 and 3 in theremaining species)

The response direction differed between species In Bnapus most trait values decreased under the influenceof antibiotics (30 out of 35 Table 5) Traits related togrowth (RGR and biomass allocation) were most affectedcompared with other traits and were more strongly af-fected by penicillin than by the other two antibiotics Thelatter was also true for C bursa-pastoris growth and bio-mass related traits responded most strongly to the treat-ments and most strongly to penicillin and sulfadiazineHowever opposite to B napus C bursa-pastoris showedan increase in biomass production (except fortetracycline)

Compared with the herb species the two grass speciesshowed only weak responses to antibiotics (Tables 5 and6) The most pronounced results were found for T aesti-vum which showed a slight increase in growth and a shifttowards higher biomass allocation to belowground parts(higher RootShoot ratio) when exposed to antibiotics Aspica-venti on the other hand only responded to penicil-lin (with one exception each for the other two antibi-otics) When treated with penicillin eight out of 12 meantrait values were lower and one was higher than thecontrol but only in the highest penicillin treatment (P10)

Discussion

Although antibiotics in plants have been intensivelystudied in the context of possible detrimental effects onhuman health (Grote et al 2007 Kumar et al 2005 Pan

et al 2014 Kang et al 2013) their effects on plants them-selves particularly on non-crop species has receivedmuch less attention The results of our study show thatantibiotics in concentrations similar to those of agricul-tural fields had significant effects on the time until ger-mination on trait-development along ontogenesis and onfunctional traits of four different plant species

In our study absolute rates of germination were simi-lar across all antibiotics and concentrations applied(mean germination rates for B napus 976 C bursa-pastoris 325 T aestivum 996 and A spica-venti866 see also Table 3) This lack of an effect on ger-mination is in concordance with most other studieswhich used either similar or higher concentrations (Panand Chu 2016 Ziolkowska et al 2015 Pufal et al unpub-lished data Jin et al 2009 Hillis et al 2011 Yang et al2010 Liu et al 2009) However our KaplanndashMeyer sur-vival analysis revealed a significant antibiotic effect onthe time of germination Germination rates were gener-ally negatively affected (ie delayed except for the P10treatment of B napus) when concentration exceeded1mg L1 irrespective of the type of antibiotic This delaywas most pronounced for the T10 treatment in A spica-venti (45 h) Thus it seems that antibiotics in general donot cause lower germination rates per se but trigger adelay in germination We cannot draw any conclusionson the germination rates of C bursa-pastoris becausethis species hardly germinated at all regardless of treat-ment Its very low germination rates may be explainedby poor quality seed material or adverse effects of thestratification of 4 C for 3 days as suggested by Tooropet al (2012) but the precise reasons remain unclear

Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA

P1 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash ndash NA NA


P10 ndash NA ndash ndash NA NA

S1 ndash ndash ndash ndash ndash ndash NA ndash ndash ndash ndash ndash ndash NA NA








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ber 2022

Table 6 Test statistics for each trait for Brassica napus Capsella bursa-pastoris Triticum aestivum and Apera spica-venti Given are t-valuesand significance levels for the comparisons between mean trait values between control treatment and respective antibiotic treatment Greenshading indicates significantly lower values to control treatment red shading indicates significantly higher values compared with controlPlt0001 Plt001 Plt005Treatments Control P1 P5 P10 penicillin treatment in the order 1 5 and 10mg L1 S1 S5 S10 sulfadiazinetreatment in the order 1 5 and 10mg L1 T1 T5 T10 tetracycline treatment in the order 1 5 and 10mg L1 For abbreviations of traits seeTable 2

Brassica napus

Control P1 P5 P10 S1 S5 S10 T1 T5 T10

RGRAGB 1857 143 ns 298 179 ns 140 ns 067 ns 192 ns 188 ns 218 169 ns

RGRBGB 5975 228 328 296 084 ns 179 ns 233 124 ns 071 ns 094 ns

RGRTotal 1794 161 ns 318 203 137 ns 091 ns 209 185 ns 198 162 ns

Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203

Stem 1883 145 ns 244 127 ns 118 ns 012 ns 233 204 196 ns 148 ns

Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns

StemL 2527 030 ns 006 ns 107 ns 017 ns 108 ns 064 ns 266 137 ns 026 ns

SLA 5836 071 ns 051 ns 132 ns 053 ns 061 ns 061 ns 057 ns 139 ns 131 ns

Leaflive 4145 256 145 ns 352 056 ns 078 ns 173 ns 261 106 ns 191 ns

Leafdead 7877 032 ns 107 ns 046 ns 063 ns 032 ns 037 ns 034 ns 023 ns 110 ns

RS 4095 170 ns 175 ns 221 021 ns 198 139 ns 018 ns 126 ns 049 ns

SRL 1541 287 176 ns 072 ns 002 ns 041 ns 114 ns 082 ns 041 ns 064 ns

TRL 2572 074 ns 044 ns 221 034 ns 121 ns 228 126 ns 059 ns 092 ns

SecR 1481 259 254 014 ns 018 ns 212 131 ns 045 ns 001 ns 029 ns

LPR 1595 059 ns 029 ns 335 119 ns 017 ns 033 ns 126 ns 106 ns 064 ns



RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212

Leaf 1037 128 ns 299 175 ns 167 ns 227 129 ns 125 ns 004 ns 054 ns

Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns

StemL 906 179 ns 027 ns 188 ns 292 205 058 ns 044 ns 136 ns 177 ns

SLA 5700 195 067 ns 155 ns 075 ns 058 ns 084 ns 033 ns 023 ns 064 ns

Leaflive 959 259 084 ns 197 ns 268 128 ns 025 ns 083 ns 201 212

Leafdead 2309 281 196 ns 208 011 ns 091 ns 159 ns 104 ns 078 ns 144 ns

RS 2146 031 ns 079 ns 039 ns 069 ns 047 ns 028 ns 122 ns 240 ns 196 ns

SRL 2468 024 ns 060 ns 091 ns 060 ns 010 ns 057 ns 008 ns 0004 ns 014 ns

TRL 773 167 ns 275 095 ns 232 178 ns 076 ns 119 ns 062 ns 079 ns

SecR 590 041 ns 066 ns 010 ns 031 ns 028 ns 112 ns 072 ns 158 ns 069 ns

LPR 1676 073 ns 190 ns 085 ns 010 ns 148 ns 030 ns 044 ns 137 ns 014 ns

Continued



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ber 2022

In general delayed seedlings likely face higher com-petitive pressure as they need to establish in a commu-nity where other plant individuals may already be aheadof them in terms of aboveground and belowground sizeThis effect may be more severe in natural communities

than in cultivated fields The consequences of delayedgermination may become even more pronounced instressful environments for example in water-stress en-vironments which is known from studies on allelopathiceffects between plant species and described as

Table 6 Continued

Triticum aestivum


RGRAGB 5237 089 ns 066 ns 041 ns 194 ns 088 ns 012 ns 193 ns 048 ns 020 ns

RGRBGB 1133 162 ns 233 197 ns 250 021 ns 153 ns 203 020 ns 100ns

RGRTotal 3172 040 ns 099 ns 072 ns 208 075 ns 010 ns 206 ns 046 ns 027 ns

Leaf 718 018 ns 038 ns 028 ns 142 ns 138 ns 044 ns 232 ns 087 ns 012 ns

Stem 565 099 ns 060 ns 024 ns 199 ns 025 ns 103 ns 279 ns 147 ns 069 ns

Root 1091 156 ns 217 ns 196ns 243 ns 002 ns 128 ns 219 ns 016 ns 063 ns

StemL NA NA NA NA NA NA NA NA NA NA


Leaflive 536 105 ns 264 ns 059 ns 249 ns 075 ns 082 ns 186 ns 051 ns 142 ns


RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns

SRL 2408 092 ns 089 ns 138 ns 015 ns 163 083 ns 053 ns 116 ns 134 ns

TRL 992 075 ns 124 ns 048 ns 230 ns 154 ns 202 ns 232 ns 063 ns 039 ns

SecR NA NA NA NA NA NA NA NA NA NA

LPR NA NA NA NA NA NA NA NA NA NA

Apera spica-venti


RGRAGB 1009 056 ns 046 ns 155 016 ns 075 ns 177 ns 003 ns 008 ns 133 ns

RGRBGB 335 099 ns 033 ns 150 033 ns 084 ns 123 ns 023 ns 029 ns 102 ns

RGRTotal 589 066 ns 045 ns 158 019 ns 077 ns 171 ns 017 ns 009 ns 127 ns

Leaf 607 156 ns 042 ns 206 048 ns 095 ns 165 ns 058 ns 038 ns 122 ns

Stem 605 164 ns 058 ns 127 ns 033 ns 115 ns 137 ns 215 014 ns 134 ns

Root 1211 166 ns 026 ns 201 034 ns 106 ns 141 ns 147 ns 023ns 068 ns


SLA 4984 169 ns 056 ns 188 076 ns 056 ns 089 ns 013 ns 124 ns 096 ns

Leaflive 558 141 ns 096 ns 240 051 ns 129 ns 175 ns 139 ns 081 ns 047 ns

Leafdead 858 157 ns 107 ns 055 ns 008 ns 359 127 ns 199 ns 123 ns 009 ns

RS 2629 088 ns 0008 ns 142 048 ns 064 ns 025 ns 012 ns 059 ns 019 ns

SRL 7224 020 ns 011 ns 210 134 ns 101 ns 026 ns 014 ns 067 ns 073 ns






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ber 2022

lsquoallelopathic retardationrsquo (Escudero et al 2000 and refer-ences therein) We may thus refer to lsquoantibiotic inducedretardationrsquo in order to describe a similar pattern inducedby antibiotics However studies on their effects on com-munity establishment and species composition are stillmissing

Germination rates of seeds treated with nitrogen (ieN5 and N10) were similar to the control however as forantibiotics there was an effect on the timing of germin-ation Both grass species showed a significant delay ingermination in response to nitrogen addition with seedsof T aestivum germinating 10 h later than those of thecontrol and A spica-venti 21ndash27 h later respectivelyThere was no effect on the two herb species The studyof Perez-Fernandez et al (2006) tested germination ratesof eight Mediterranean species to varying levels of pHand nitrogen Whereas pH did not have an effect on thegermination rates addition of nitrogen (in the forms ofNH4NO3 and KNO3 10 and 50 mM each) decreased thegermination rates Using the same concentration asPerez-Fernandez et al (2006) Rossini Oliva et al (2009)detected no effect of nitrogen on the germination ratesof Erica andevalensis whereas Lupinus angustifoliusseeds germinated poorer under different types of nitro-gen compounds (urea nitric acid etc Kasprowicz-Potocka et al 2013) However we know of no other studythat reports of effects of nitrogen on the timing ofgermination

Furthermore the role of microorganisms on germin-ation and growth of the tested plant species was nottaken into account in this study Soil bacteria are signifi-cantly affected by antibiotics (Thiele-Bruhn and Beck2005 Yang et al 2009) which may in turn affect plantperformance and thus plant traits For example Yanget al (2010) found an increase in fungi and a decrease inbacteria in response to exposure to tetracycline Underhydroponic conditions roots of wheat plants rotted andbecame atrophic and partly died whereas germinationrates were not affected by the treatments A synchron-ous inhibition of soil microbial activity and plant biomassproduction was observed by Wei et al (2009) in a pottrial with tetracycline and ryegrass (Lolium perenne)Taking this into account the results of the present studyonly reflect to responses of plant traits to the antibiotictreatments whereas a distinction into direct (uptake andmetabolization of the compound by the plant) and indir-ect (though microbial activity) effects of antibiotics can-not be made

Our results and the mentioned studies indicatespecies-specific responses to both antibiotic and nitro-gen addition Both crop species B napus and T aestivumgerminated most rapidly followed by the non-crop spe-cies A spica-venti whereas C bursa-pastoris hardly

germinated at all Species-specific responses may be dueto differences in seed coats as pointed out by Pan andChu (2016) who observed no effect of antibiotics on ger-mination rates but a linear decrease on root elongationwith increasing concentrations of antibiotics They sug-gested the seed coat to function as a barrier betweenthe embryo and its environment which impedes antibi-otics from penetrating and affecting the developing indi-vidual However once germinated the roots of theyoung seedling take up antibiotics which may then sub-sequently impact growth of the developing plant

Besides germination plant traits of later ontogeneticstages were also affected by antibiotics but effectsstrongly differed between species as well as betweenfunctional plant groups Significant interactions betweenspecies antibiotics and their concentrations further sug-gest that the changes in plant traits resulted from spe-cies specific responses to the antibiotics The two herbspecies both showed clear responses to the treatmentsespecially in growth and biomass related traits whichwere more pronounced for penicillin and sulfadiazinethan for tetracycline In contrast the two grass specieshardly showed any trait responses to antibiotics Theonly noteworthy effects were a shift of the RootShootratio towards a stronger investment in shoot biomass inT aestivum and negative trait responses in A spica-venti but only for the highest penicillin treatmentBecause previous studies mostly used higher concentra-tions of antibiotics we cannot directly compare our re-sults with those studies Whether grasses are in generalless susceptible to natural concentrations of antibioticsthan herbs consequently needs further elucidation

Post-germinative development of the herb speciestested was significantly affected by antibiotics but ef-fects again differed between the two species and be-tween antibiotics Canopy height and chlorophyllcontent (both measured several times in the course ofdevelopment) responded mostly to penicillin and sulfa-diazine but not to tetracycline Migliore et al (1997) re-ported an increase of development-alteration over timeie alterations became more pronounced in later pro-duced plant traits They tested effects ofsulfadimethoxine on root length (lengths of epicotylcotyledon and leaves) in Amaranthus retroflexusPlantago major and Rumex acetosella In our study anti-biotic effects were more pronounced in later ontogeneticstages for canopy height and more pronounced in earlierstages for chlorophyll content

Interestingly effects on chlorophyll content showeddifferent directions for B napus and C bursa-pastoriswhereas pigment content in B napus leaves was lower intreated individuals than in control individuals it washigher in treated individuals of C bursa-pastoris The



Dow



ber 2022

same pattern was found for other functional traits deter-mined at the time of harvest almost all trait values in Bnapus were lower than the control whereas they werehigher than the control in C bursa-pastoris Such oppos-ing patterns have been previously described by two con-cepts a) hormesis and b) the dilution effect of biomass(and water) on active substances Hormesis is a non-linear dose-effect relationship (Klonowski 2007 seeMigliore et al 2010 for plant responses towards antibi-otics and Belz and Duke 2014 for resposes towards her-bizides) which normally implies that a toxin or pollutantprovides a positive stimulus at low doses and inhibitionat higher doses (see Fig 3A for illustration Calabreseand Baldwin 2002 Calabrese and Blain 2009) Hormesiscan occur in all living organisms including plants(Calabrese and Blain 2009) However a certain dose thatmay be beneficial for one individual may be harmful foranother or harmful for a population (illustrated in Fig 3BCalabrese and Baldwin 2002) With regard to the planttrait responses measured in this study responses of Bnapus were mostly negative whereas those of C bursa-pastoris were mostly positive indicating species-specifichormetic responses Whereas the same dose concentra-tion positively stimulated C bursa-pastoris (with trait val-ues lowest for both the lowest and highest antibioticconcentration compare [see Supporting InformationmdashTable S1]) it caused inhibition in B napus

A lsquodilution-effectrsquo means that active substances aretypically diluted by the aqueous cell components they aredissolved in which is why they become effective onlyabove a certain species-specific threshold Consequentlyif two species are treated with the same concentration ofa certain substance the species producing higherbiomass will also show a higher dilution of the substanceand as a consequence may differ in its response Such alsquodilution-effectrsquo was observed for eg Lythrum salicaria-

individuals treated with sulfamethoxine (Migliore et al2010) In their study individuals of the 005 mg L1 treat-ment showed higher drug tissue concentrations than indi-viduals treated with a concentration of 05 mg L1However individuals of the 05 mg L1 treatment showedhigher biomass values and had therefore a lower relativedrug concentration as it was lsquodilutedrsquo by higher biomassand higher water content In our study biomass producedby B napus was always higher than that of C bursa-pasto-ris except for leaves Moreover the response-interval of Bnapus may have shifted along the dose-gradient to agreater extent than that of C bursa-pastoris as antibioticsmay have been comparatively more diluted (illustrated inFig 3C) ultimately leading to the opposing effects be-tween these two species Testing of the two concepts in acomparative way however would require a longer gradi-ent of antibiotic concentrations covering the whole inter-val of both positive and negative trait responses of allspecies and a measuring of the antibiotic concentrationaccumulated in the plant tissue

Conclusions

This study demonstrates as one of the first that evencomparatively small concentrations of antibiotics as typ-ically found in the soil of agricultural landscapes candelay the time of germination and differently affect traitdevelopment of different plant species with effects de-pending on species traits antibiotics and concentrations

Also responses were either negative or positive likelydepending on the species the functional plant group itbelongs to or the size (ie weight) of an individual (andthus biomass diluting the antibiotics) This relationshipbetween antibiotic-dilution and hormetic responsesshould be further investigated as an apparent positiveresponse could result from a diluted toxic effect

Figure 3 (A) Model of non-linear response after Klonowski (2007) and Migliore et al (2010) Damage is caused by deficient doses of an agent (leftof A) positive response is caused by low doses (between A and B) while doses exceeding a certain amount cause harmful or toxic effects (right ofB) (B) Damages andor hormetic responses (Hormesis A and B) can occur at the same dose-concentrations for different species (Species A and B)respectively (C) Further elaboration of the lsquodilution-effectrsquo described by Migliore et al (2010) A species that would theoretically show a hormeticresponse at a certain dose-level shifts its response-interval towards the left side of the concentration gradient as the agent is diluted by its bio-mass and tissue water content The extent of dilution should differ between different species with the same dose-concentration



Dow



ber 2022

Furthermore our study revealed that antibiotics in con-

centrations similar to those detected in grassland soils

can have significant effects on the time of germination If

antibiotic effects are indeed largely species-specific ef-fects of concentrations typically found in real (agricul-

tural) environments could be either negative in some

species (ie antibiotic induced retardation of germination)

or neutral (as in C bursa-pastoris) In this case less sensi-

tive species may experience a competitive advantage

which might trigger changes in species composition in

natural communities This assumption however does not

take into account (i) that antibiotics may also accumulate

in the soil (Hamscher et al 2002) which can increase total

soil concentrations over time and therefore change re-sponse patterns in plant communities (ii) that antibiotics

are often found in mixtures in agricultural soils with likely

interactive effects between antibiotics and (iii) that antibi-

otics may also interact with microorganisms in the soil

potentially affecting the response of plantsThis study shows that cropland species can respond to

concentrations of antibiotics as typically found in agricul-

tural soils with for example delayed germination or

reduced biomass which may negatively affect yield in

farmland fertilized with antibiotic treated manure Ourstudy also implies that different antibiotics could poten-

tially affect the species composition of natural commun-

ities in field margins due to species-specific responses

which may affect their competitive abilities Such species-

specific responses may alter the plant species communityrsquos

composition with secondary effects on species of higher

trophic levels like pollinating and herbivorous insects

Sources of Funding

This study has been financed by the German Research

Foundation (DFG MI 13653-1)

Contributions by the Authors

VM SL and GP designed the study and raised funding

VM AD and AMV performed the greenhouse study

VM primarily wrote the manuscript with contributions of

SL GP AD and AMV

Conflict of Interest Statement

None declared

Acknowledgements

The authors thank H Ihler Botanical Garden of the

University of Oldenburg for support with greenhouse

work and K Bahloul and D Meiszligner for assistance in the

laboratory Funding was provided by the Deutsche

Forschungsgemeinschaft (DFG project MI 13653-1)

Supporting Information

The following additional information is available in the

online version of this article mdashTable S1 Means and relative standard deviations

(RSD ) of each trait for Brassica napus Capsella bursa-

pastoris Triticum aestivum and Apera spica-venti Bold

numbers indicate significant differences to control treat-

ment (t-test Plt005 compare Table 6) green shading

indicates significantly lower values red shading indicates

significantly higher values compared with control

Treatments Control P1 P5 P10 penicillin treatment in

the order 1 5 and 10mg L1 S1 S5 S10 sulfadiazine

treatment in the order 1 5 and 10mg L1 T1 T5 T10

tetracycline treatment in the order 1 5 and 10mg L1

For abbreviations of traits see Table 2Figure S1 Setup of germination experiment (upper

part) and greenhouse experiment (lower part) Number

of treatments is calculated by the number of antibiotics

times the number of concentrations plus control Plant

species are depicted with their inflorescence

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Induction of desiccation tolerance in microspore-derived em-

bryos of Brassica napus L by thermal-stress Plant Science 77

119ndash123

Aust MO Godlinski F Travis GR Hao XY McAllister TA Leinweber P

Thiele-Bruhn S 2008 Distribution of sulfamethazine chlortetra-

cycline and tylosin in manure and soil of Canadian feedlots after

subtherapeutic use in cattle Environmental Pollution 156

1243ndash1251

Bassil RJ Bashour II Sleiman FT Abou-Jawdeh YA 2013 Antibiotic

uptake by plants from manure-amended soils Journal of

Environmental Science and Health Part B-Pesticides Food

Contaminants and Agricultural Wastes 48570ndash574

Belz RG Duke SO 2014 Herbicides and plant hormesis Pest

Management Science 70698ndash707

Blackwell PA Kay P Boxall ABA 2007 The dissipation and transport

of veterinary antibiotics in a sandy loam soil Chemosphere 67

292ndash299

Boxall ABA Johnson P Smith EJ Sinclair CJ Stutt E Levy LS 2006

Uptake of veterinary medicines from soils into plants Journal of

Agricultural and Food Chemistry 542288ndash2297

Bradel BG Preil W Jeske H 2000 Remission of the free-branching

pattern of Euphorbia pulcherrima by tetracycline treatment

Journal of Phytopathology-Phytopathologische Zeitschrift 148

587ndash590

Burkhardt M Stamm C Waul C Singer H Muller S 2005 Surface

runoff and transport of sulfonamide antibiotics and tracers on



Dow



ber 2022

manured grassland Journal of Environmental Quality 34

1363ndash1371

Burns JH 2004 A comparison of invasive and non-invasive day-

flowers (Commelinaceae) across experimental nutrient and

water gradients Diversity and Distributions 10387ndash397

Calabrese EJ Baldwin LA 2002 Defining hormesis Human amp

Experimental Toxicology 2191ndash97

Calabrese EJ Blain RB 2009 Hormesis and plant biology

Environmental Pollution 15742ndash48

Chopra I Roberts M 2001 Tetracycline antibiotics Mode of action

applications molecular biology and epidemiology of bacterial

resistance Microbiology and Molecular Biology Reviews 65

232ndash260

Christian T Schneider RJ Farber HA Skutlarek D Meyer MT

Goldbach HE 2003 Determination of antibiotic residues in ma-

nure soil and surface waters Acta Hydrochimica Et

Hydrobiologica 3136ndash44

Ellenberg H Leuschner C 2010 Vegetation mitteleuropas mit den

alpen Stuttgart Eugen Ulmer Verlag

Escudero A Albert MJ Pita JM Perez-Garcia F 2000 Inhibitory ef-

fects of Artemisia herba-alba on the germination of the gypso-

phyte Helianthemum squamatum Plant Ecology 14871ndash80

European Medicines Agency 2013 European Surveillance of

Veterinary Antimicrobial Consumption lsquoSales of veterinary anti-

microbial agents in 25 EUEEA countries in 2011rsquo (EMA236501

2013)

FAOmdashFood and Agriculture Organization of the United Nations

2016 FAOSTAT Domains ndash Production of Crops httpfaostat3

faoorgdownloadQQCE (27 June 2016)

Forster M Laabs V Lamshoft M et al 2009 Sequestration of

manure-applied sulfadiazine residues in soils Environmental

Science amp Technology 431824ndash1830

Fox J Weisberg S 2011 An R companion to applied regression

Thousand Oaks CA USA Sage

Gross J Ligges U 2015 nortest Tests for normality R package ver-

sion 10-4 httpsCRANR-projectorgpackagefrac14nortest (27

April 2016)

Grote M Schwake-Anduschus C Michel R et al 2007 Incorporation

of veterinary antibiotics into crops from manured soil

Landbauforschung Volkenrode 5725ndash32

Gusewell S 2005 High nitrogen phosphorus ratios reduce nutrient

retention and second-year growth of wetland sedges New

Phytologist 166537ndash550

Hammes WP 1976 Biosynthesis of petidoglycan in Gaffkya homari

ndash The mode of action of Penicillin G and Mecillinam European

Journal of Biochemistry 70107ndash113

Hamscher G Pawelzick HT Hoper H Nau H 2005 Different behavior

of tetracyclines and sulfonamides in sandy soils after repeated

fertilization with liquid manure Environmental Toxicology and

Chemistry 24861ndash868

Hamscher G Sczesny S Abu-Qare A Hoeper H Nau H 2000

Substances with pharmacological effects including hormonally

active substances in the environment identification of tetracyc-

lines in soil fertilized with animal slurry Deutsche Tieraerztliche

Wochenschrift 107332ndash334

Hamscher G Sczesny S Hoper H Nau H 2002 Determination of persist-

ent tetracycline residues in soil fertilized with liquid manure by high-

performance liquid chromatography with electrospray ionization

tandem mass spectrometry Analytical Chemistry 741509ndash1518

Henry RJ 1944 The mode of action of Sulfonamides Bacteriological

Reviews 7176ndash262

Hillis DG Fletcher J Solomon KR Sibley PK 2011 Effects of ten anti-

biotics on seed germination and root elongation in three plantspecies Archives of Environmental Contamination and

Toxicology 60220ndash232

Hunt R 1990 Basic growth analysis London Unwin Hyman

Jin CX Chen QY Sun RL Zhou QX Liu JJ 2009 Eco-toxic effects of sulfa-diazine sodium sulfamonomethoxine sodium and enrofloxacin on

wheat Chinese cabbage and tomato Ecotoxicology 18878ndash885

Jjemba PK 2002 The potential impact of veterinary and human

therapeutic agents in manure and biosolids on plants grown onarable land a review Agriculture Ecosystems amp Environment 93

267ndash278

Kang DH Gupta S Rosen C et al 2013 Antibiotic uptake by vege-

table crops from manure-applied soils Journal of Agriculturaland Food Chemistry 619992ndash10001

Kaplan EL Meier P 1958 Nonparametric estimation from incom-

plete observations Journal of the American Statistical

Association 53457ndash481

Kasai K Kanno T Endo Y Wakasa K Tozawa Y 2004 Guanosine

tetra- and pentaphosphate synthase activity in chloroplasts of a

higher plant association with 70S ribosomes and inhibition by

tetracycline Nucleic Acids Research 325732ndash5741

Kasprowicz-Potocka M Walachowska E Zaworska A Frankiewicz A

2013 The assessment of influence of different nitrogen com-

pounds and time on germination of Lupinus angustifolius seeds

and chemical composition of final products Acta Societatis

Botanicorum Poloniae 82199ndash206

Kay P Blackwell PA Boxall ABA 2005 Transport of veterinary anti-

biotics in overland flow following the application of slurry to ar-

able land Chemosphere 59951ndash959

Kleinbaum DG Klein M 2012 Survival analysis ndash a self-learning textHeidelberg Germany Springer

Klonowski W 2007 From conformons to human brains an informal

overview of nonlinear dynamics and its applications in biomedi-

cine Nonlinear Biomedical Physics 1 19 pp

Kumar K Gupta SC Baidoo SK Chander Y Rosen CJ 2005 Antibiotic

uptake by plants from soil fertilized with animal manure Journal

of Environmental Quality 342082ndash2085

Leff B Ramankutty N Foley JA 2004 Geographic distribution of major

crops across the world Global Biogeochemical Cycles 1833

Li ZJ Xie XY Zhang SQ Liang YC 2011 Wheat growth and photo-

synthesis as affected by oxytetracycline as a soil contaminant

Pedosphere 21244ndash250

Lichtenthaler HK 1987 Chlorophylls and carotinoids ndash pigments of

photosynthetic biomembranes Methods in Enzymology 148

350ndash382

Lichtenthaler HK Wellburn AR 1983 Determination of the total car-

otinoids and chlorophylls a and b of leaf extracts in different

solvents Biochemical Society Transactions 603591ndash592

Liu F Ying GG Tao R Jian-Liang Z Yang JF Zhao LF 2009 Effects of

six selected antibiotics on plant growth and soil microbial andenzymatic activities Environmental Pollution 1571636ndash1642

Liu L Liu YH Liu CX et al 2013 Potential effect and accumulation

of veterinary antibiotics in Phragmites australis under hydro-

ponic conditions Ecological Engineering 53138ndash143

Martinez-Carballo E Gonzalez-Barreiro C Scharf S Gans O 2007

Environmental monitoring study of selected veterinary



Dow



ber 2022

antibiotics in animal manure and soils in Austria EnvironmentalPollution 148570ndash579

McNair JN Sunkara A Frobish D 2012 How to analyse seed germin-ation data using statistical time-to-event analysis non-parametric and semi-parametric methods Seed ScienceResearch 2277ndash95

Michelini L La Rocca N Rascio N Ghisi R 2013 Structural and func-tional alterations induced by two sulfonamide antibiotics onbarley plants Plant Physiology and Biochemistry 6755ndash62

Michelini L Reichel R Werner W Ghisi R Thiele-Bruhn S 2012Sulfadiazine uptake and effects on Salix fragilis L and Zea maysL plants Water Air and Soil Pollution 2235243ndash5257

Migliore L Brambilla G Cozzolino S Gaudio L 1995 Effects onplants of sulfadimethoxine used in intensive farming (Panicummiliceaum Pisum sativum and Zea mays) AgricultureEcosystems amp Environment 52103ndash110

Migliore L Civitareale C Brambilla G Cozzolino S Casoria P GaudioL 1997 Effects of sulphadimethoxine on cosmopolitan weeds(Amaranthus retroflexus L Plantago major L and Rumex aceto-sella L) Agriculture Ecosystems amp Environment 65163ndash168

Migliore L Rotini A Cerioli NL Cozzolino S Fiori M 2010 Phytotoxicantibiotic sulfadimethoxine elicits a complex hormetic responsein the weed Lythrum salicaria L DosendashResponse 8414ndash427

Miller EL 2002 The penicillins a review and update Journal ofMidwifery amp Womenrsquos Health 47426ndash434

Pan M Chu LM 2016 Phytotoxicity of veterinary antibiotics to seedgermination and root elongation of crops Ecotoxicology andEnvironmental Safety 126228ndash237

Pan M Wong CKC Chu LM 2014 Distribution of antibiotics inwastewater-irrigated soils and their accumulation in vegetablecrops in the Pearl River Delta Southern China Journal ofAgricultural and Food Chemistry 6211062ndash11069

Perez-Fernandez MA Calvo-Magro E Montanero-Fernandez JOyola-Velasco JA 2006 Seed germination in response to chem-icals effect of nitrogen and pH in the media Journal ofEnvironmental Biology 2713ndash20

Perez-Harguindeguy N Dıaz S Garnier E et al 2013 New handbookfor standardised measurement of plant functional traits world-wide Australian Journal of Botany 61167ndash234

Piotrowicz-Cieslak AI Adomas B Nalecz-Jawecki G Michalczyk DJ2010 Phytotoxicity of sulfamethazine soil pollutant to six leg-ume plant species Journal of Toxicology and EnvironmentalHealth-Part a-Current Issues 731220ndash1229

R Core Team 2014 R A Language and Environment for StatisticalComputing R Foundation for Statistical Computing R Foundationfor Statistical Computing Vienna Austria httpwwwR-projectorg

Rasband W 2014 ImageJ 148r National Institutes of Health USA

Ribeiro PJ Diggle PJ 2015 geoR Analysis of Geostatistical Data Rpackage version 17-51 httpsCRANR-projectorgpackagefrac14geoR (27 April 2016)

Richardson AD Duigan SP Berlyn GP 2002 An evaluation of nonin-vasive methods to estimate foliar chlorophyll content NewPhytologist 153185ndash194

Rossini Oliva S Leidi EO Valdes B 2009 Germination responses ofErica andevalensis to different chemical and physical treat-ments Ecological Research 24655ndash661

Siddiqui S Bhardwaj S Khan SS Meghvanshi MK 2009 Allelopathiceffect of different concentration of water extract of Prosopsisjuliflora leaf on seed germination and radicle length of wheat

(Triticum aestivum Var-Lok-1) American-Eurasian Journal of

Scientific Research 481ndash84

Stoob K Singer HP Mueller SR Schwarzenbach RP Stamm CH 2007

Dissipation and transport of veterinary sulfonamide antibioticsafter manure application to grassland in a small catchment

Environmental Science amp Technology 417349ndash7355

Therneau TM Grambsch PM 2000 Modeling survival data extendingthe Cox model New York Springer

Thiele-Bruhn S 2003 Pharmaceutical antibiotic compounds in soilsndash a review Journal of Plant Nutrition and Soil Science 166

145ndash167

Thiele-Bruhn S Beck IC 2005 Effects of sulfonamide and tetracyc-

line antibiotics on soil microbial activity and microbial biomassChemosphere 59457ndash465

Toorop PE Cuerva RC Begg GS Locardi B Squire GR Iannetta PPM2012 Co-adaptation of seed dormancy and flowering time in

the arable weed Capsella bursa-pastoris (shepherdrsquos purse)Annals of Botany 109481ndash489

Trapp S Eggen T 2013 Simulation of the plant uptake of organo-phosphates and other emerging pollutants for greenhouse ex-

periments and field conditions Environmental Science andPollution Research 204018ndash4029

van Kleunen M Weber E Fischer M 2010 A meta-analysis of trait

differences between invasive and non-invasive plant speciesEcology Letters 13235ndash245

Wallgren B Avholm K 1978 Dormancy and germination of Aperaspica-venti L and Alopecurus myosuroides Huds seeds Swedish

Journal of Agricultural Research 811ndash15

Wei X Wu SC Nie XP Yediler A Wong MH 2009 The effects of re-

sidual tetracycline on soil enzymatic activities and plantgrowth Journal of Environmental Science and Health Part B-

Pesticides Food Contaminants and Agricultural Wastes 44461ndash471

Werner JJ Chintapalli M Lundeen RA Wammer KH Arnold WAMcNeill K 2007 Environmental photochemistry of tylosin

Efficient reversible photoisomerization to a less-active isomerfollowed by photolysis Journal of Agricultural and Food


Wickham H 2009 ggplot2 Elegant graphics for data analysis New

York Springer

Winckler C Grafe A 2001 Use of veterinary drugs in intensive ani-mal production evidence for persistence of tetracycline in pigslurry Journal of Soils and Sediments 166ndash70

World Health Organization 2015 WHO Model List of Essential

Medicines ndash a reprint of the text on the WHO Medicines websitehttpwwwwhointmedicinespublicationsessentialmedicinesen

Yang QX Zhang J Zhu KF Zhang H 2009 Influence of oxytetracyc-line on the structure and activity of microbial community in

wheat rhizosphere soil Journal of Environmental Sciences 21954ndash959

Yang QX Zhang J Zhang WY Wang Z Xie YS Zhang H 2010Influence of tetracycline exposure on the growth of wheat seed-

lings and the rhizosphere microbial community structure in hydro-ponic culture Journal of Environmental Science and Health Part B-


Ziolkowska A Piotrowicz-Cieslak AI Margas M Adomas B Nalecz-

Jawecki G 2015 Accumulation of tetracycline oxytetracyclineand chlortetracycline in pea (Pisum sativum L) Fresenius

Environmental Bulletin 241386ndash1391



Dow



ber 2022

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Introduction

Antibiotics are used to treat infections in humans andanimals by either directly killing bacteria or inhibitingtheir growth (World Health Organization 2015 Chopraand Roberts 2001 Miller 2002) The use of antibiotics hasbecome integral to livestock industry with 8481 t of vet-erinary antibiotics sold alone in the EUEEA (EuropeanEconomic Area) in 2011 (European Medicines Agency2013) Antibiotics applied to animals are poorly absorbedin the gut and as much as 90 of some antibiotics maybe excreted (Kumar et al 2005 Winckler and Grafe 2001Jjemba 2002) These antibiotics may be released to theenvironment by grazing animals or manure (Thiele-Bruhn 2003 Martinez-Carballo et al 2007) Some antibi-otics are highly stable in manure and soil with residuesstill detectable one year after application (Thiele-Bruhn2003) Some antibiotics may even persist for severalyears (Forster et al 2009) For example in agriculturallandscapes with conventional land use and manure fer-tilization tetracycline and sulfadiazine were detectedat average soil concentrations of 10ndash15mg kg1 and32ndash198mg kg1 respectively (Hamscher et al 20002002 2005 Christian et al 2003 Aust et al 2008) Fromthe farmlands antibiotics may then be transported fur-ther to ditches streams and rivers via runoff (Kay et al2005 Burkhardt et al 2005 Stoob et al 2007) togroundwater via leaching (Blackwell et al 2007) or maydirectly be ingested by organisms (Boxall et al 2006)How organisms respond to natural concentrations ofantibiotics as found in soil water and other organisms ishowever poorly understood The majority of studiesconducted for elucidating the effect of antibiotics onplants used much higher concentrations which donot resemble in vivo situations (eg Liu et al 2009(100ndash500 000mg L1) Michelini et al 2013(11 500mg L1) Migliore et al 2010 (5ndash50 000mg L1)Michelini et al 2012 (10 000ndash200 000mg kg1))

Whereas possible detrimental effects of antibioticstaken up by crop plants on human health have been in-tensively investigated (Grote et al 2007 Kumar et al2005 Pan et al 2014 Kang et al 2013) the effect of anti-biotics on plants themselves particularly on non-cropspecies has received much less attention There is sig-nificant evidence that antibiotics adversely affect thegrowth and performance of plants (Migliore et al 2010Liu et al 2013) however they can also promote allomet-ric responses (see examples in Table 1)

Further responses can be dose-dependent egincreased growth at lower concentrations and toxic ef-fects at higher ones (so-called hormetic responses seeMigliore et al 2010) Roots are typically most affected byand accumulate most antibiotics (Migliore et al 2010)

where they negatively impact on root length root elong-ation and number of lateral roots with consequences forplant water uptake (Piotrowicz-Cieslak et al 2010Michelini et al 2012) Further studies showed that antibi-otics can alter biomass production number of leavesbranching patterns shoot length internode length rootshoot ratio freshdry weight CN and KCa ratio etc(Bradel et al 2000 Liu et al 2009 Yang et al 2010Michelini et al 2012 Li et al 2011) Physiological traitsaffected by antibiotics are for instance photosyntheticrate chloroplast synthase activity transpiration ratestomatal conductance and synthesis of abscisic acid(ABA) (Kasai et al 2004 Werner et al 2007) These stud-ies clearly demonstrate that various antibiotics in the soilcan be accumulated in plant tissues and have either det-rimental or enhancing effects on functional traits of cropand wild plant species They also show that effects de-pend on plant species plant organ type of antibioticapplied and its concentration However these studieswere conducted under artificial conditions with mostlyunnaturally high antibiotic concentrations not necessar-ily mirroring in vivo conditions Whether these effectsalso occur for lower antibiotic concentrations remainslargely unclear

To address this knowledge gap we studied the effectof three antibiotics with different action modes (ie peni-cillin tetracycline and sulfadiazine) on four plant speciesincluding crop (Brassica napus and Triticum aestivum)and non-crop (Capsella bursa-pastoris and Apera spica-venti) species Both crop species (B napus andT aestivum) belong to the most commonly grown cropsworldwide (Leff et al 2004 FAOmdashFood and AgricultureOrganization of the United Nations 2016) and are highlylikely exposed to antibiotics due to fertilization of cropfields with slurry or manure The non-crop species(C bursa-pastoris and A spica-venti) are commonlyfound along most crop field margins in Germany and arelikely unintentionally exposed to antibiotic charged ma-nure applied to fields (Ellenberg and Leuschner 2010)We applied concentrations of antibiotics as previously re-ported for grasslands (from now on referred to as naturalconcentrations Thiele-Bruhn 2003) to plants grown ingreenhouses and measured germination rates and plantfunctional traits during ontogenesis and at fully de-veloped plant individuals

Specifically we asked (i) whether natural concentra-tions of antibiotics affect both germination and func-tional traits of plants and (ii) whether trait responseswere more similar among crop and non-crop plant spe-cies than between crop and non-crop species (ieB napus and T aestivum versus C bursa-pastoris andA spica-venti) or among herbs and grasses (eg B napusand C bursa-pastoris) than between herbs and grasses



Dow



ber 2022


Crop plant species





Lincomycin

Oxytetracycline

Sulfamethazine

Sulfamethoxazole

Tetracycline

Trimethoprim

Tylosin








Sulfamethoxazole

Sulfamethazine

Trimethoprim






Pea (Pisum sativum)

Corn (Zea mays)



Sulfamethazine



c oxidase7






Continued



Dow



ber 2022

Table 1 Continued

Crop plant species



ment death8


on germination9








Chloramphenicol












retroflexus)













Dow



ber 2022


Methods

Selected species







Experimental design









Dow



ber 2022











Dow



ber 2022





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19


Crop plant species





Lincomycin

Oxytetracycline

Sulfamethazine

Sulfamethoxazole

Tetracycline

Trimethoprim

Tylosin








Sulfamethoxazole

Sulfamethazine

Trimethoprim






Pea (Pisum sativum)

Corn (Zea mays)



Sulfamethazine



c oxidase7






Continued



Dow



ber 2022

Table 1 Continued

Crop plant species



ment death8


on germination9








Chloramphenicol












retroflexus)













Dow



ber 2022


Methods

Selected species







Experimental design









Dow



ber 2022











Dow



ber 2022





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19

Table 1 Continued

Crop plant species



ment death8


on germination9








Chloramphenicol












retroflexus)













Dow



ber 2022


Methods

Selected species







Experimental design









Dow



ber 2022











Dow



ber 2022





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19


Methods

Selected species







Experimental design









Dow



ber 2022











Dow



ber 2022





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19











Dow



ber 2022





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19





















2009)







SethtTHORN frac14Ys

jfrac141

1dj

nj





































Dow



ber 2022




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19




Results































Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Days until

germination

Rate

()

Control 173 (415) 100 1400 (3360) 0 114 (274) 100 322 (773) 94

N5 176 (422) 99 1369 (3286) 3 156 (374) 98 410 (984) 86

N10 181 (434) 98 1396 (3350) 1 151 (362) 100 436 (1046) 82

P1 166 (398) 100 1400 (3360) 0 133 (319) 100 340 (816) 89

P5 219 (526) 98 1465 (3516) 3 190 (456) 100 421 (1014) 85

P10 172 (413) 99 1397 (3357) 9 168 (403) 99 428 (1027) 88

S1 167 (401) 97 1357 (3257) 4 104 (249) 99 293 (703) 92

S5 225 (540) 96 1421 (3410) 8 184 (442) 100 408 (979) 88

S10 210 (504) 98 1458 (3499) 4 173 (415) 100 492 (1181) 83

T1 149 (358) 93 1387 (3329) 1 111 (266) 100 292 (701) 89

T5 216 (518) 96 1488 (3571) 1 189 (454) 100 501 (1202) 82

T10 211 (506) 98 1445 (3468) 5 173 (415) 100 513 (1231) 81



Dow



ber 2022






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19






































Species (S) 3 476 219440 113989 175973 23662 39843 20317 15933 29686

Antibiotic (A) 2 477 047 033 037 094 077 080 014 123

Concentration (C) 2 477 296 217 307 138 072 216 072 168

SA 6 468 097 217 109 267 042 638 071 146

SC 6 468 238 185 259 096 011 096 108 087

AC 4 471 092 096 106 064 370 068 043 124

SAC 12 444 053 055 068 126 131 106 088 183


Species (S) 3 476 6730 2643 4455 6578 1 238 414 086 8542

Antibiotic (A) 2 477 678 039 442 133 2 237 198 481 144

Concentration (C) 2 477 237 054 088 364 2 237 051 097 215

SA 6 468 196 523 386 160 2 234 110 006 121

SC 6 468 166 053 183 190 2 234 107 117 359

AC 4 471 157 047 110 099 4 231 551 143 052

SAC 12 444 227 116 117 124 4 222 208 181 211



Dow



ber 2022
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19
























Dow



ber 2022




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19




Brassica napus



Control 0083 0072 0081 6844 6629 2195 331 402 95 60 016 2698 549 141 904













Control 0132 0127 0132 6882 2602 1056 350 587 907 93 011 1689 167 177 1504










Triticum aestivum



Control 0042 0014 0036 2909 626 474 NA 348 40 69 013 523 23 NA NA










Continued



Dow



ber 2022




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19




Discussion




Table 5 Continued

Apera spica-venti



Control 0110 0085 0104 1999 641 402 NA 577 681 103 015 1938 76 NA NA












Dow



ber 2022


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19


Brassica napus





Leaf 1348 146 ns 348 249 148 ns 146 ns 167 ns 094 ns 230 203


Root 1883 254 376 324 087 ns 226 288 118 ns 056 ns 133 ns












RGRAGB 4964 280 330 299 306 314 222 247 194 219

RGRBGB 4279 273 320 256 258 269 183 ns 183 ns 090 ns 132 ns

RGRTotal 4922 281 332 298 303 312 220 241 185 ns 212


Stem 868 235 103 ns 269 365 256 014 ns 079 ns 161 ns 195 ns

Root 1585 232 302 225 232 239 134 ns 110 ns 017 ns 072 ns










Continued



Dow



ber 2022



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19



Table 6 Continued

Triticum aestivum












RS 5455 372 379 341 237 168 ns 306 076 ns 122 ns 168 ns





Apera spica-venti



















Dow



ber 2022











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19











Dow



ber 2022




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19




Conclusions






Dow



ber 2022




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19




























Sources of Funding







SL GP AD and AMV


None declared

Acknowledgements



























119ndash123





1243ndash1251









292ndash299







587ndash590





Dow



ber 2022


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19


1363ndash1371











232ndash260













2013)











April 2016)

































267ndash278
































350ndash382













Dow



ber 2022



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19



























145ndash167


















York Springer














Dow



ber 2022

plx010-TF1

plx010-TF2

plx010-TF3

plx010-TF4

plx010-TF5

plx010-TF6

plx010-TF7

plx010-TF8

plx010-TF9

plx010-TF10

plx010-TF11

plx010-TF12

plx010-TF13

plx010-TF14

plx010-TF15

plx010-TF16

plx010-TF17

plx010-TF18

plx010-TF19

antibiotics impact plant traits, even at small concentrations

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