Limited Seed and Seed Yield Response of Calendula

13 Pages·2017·0.89 MB·English

agriculture
Article
Limited Seed and Seed Yield Response of Calendula
to Applied Nitrogen Does Not Justify Risk of
Environmental Damage from High Urea
Application Rates
JaneM.F.Johnson* ID,RussW.GeschandNancyW.Barbour
USDA-AgriculturalResearchService-NorthCentralSoilConservationResearchLaboratory,
Morris,MN56267,USA;[email protected](R.W.G.);[email protected](N.W.B.)
* Correspondence:[email protected];Tel.:[phone]
Received:20February2018;Accepted:9March2018;Published:13March2018
Abstract: Calendula(CalendulaofficinalisL.)seed,duetoitshighcalendicacidcontent,isrecognized
asapotentialenvironmentallysafesubstituteforvolatileorganiccompounds. Agronomicguidelines
for nitrogen (N) management to produce calendula seed oil on a commercial scale are limited.
Post-harvestsoilNhasthepotentialtomoveoff-farmandcontributetowaterqualitydegradation
(e.g., hypoxia in the Gulf of Mexico). Establishing N management guidelines should consider
agronomic response and potential environmental risk. Calendula seed and oil yield, oil content,
harvest index, N use, seed N use efficiency, oil N use efficiency, agronomic efficiency, vegetative
growth,andtheamountofresidualsoil-NfollowingharvestresponsetofiveureaNrates(0,34,67,
134,and202kgNha−1)wereassessedinareplicatedfieldstudyrepeatedfortwogrowingseasons.
SeedyieldincreasedwithNrate,butbecauseofthelowNconversionefficiency,thereappearedtobe
minimalyieldgainsinapplyingNbeyond34kgha−1. Thelowestamountofsoil-Nleftunderutilized
inthesoilwaspredictedtooccurat39kgNha−1andwasadequateforseedandseedoilcommercial
calendulaproductiononaMollisolintheNorthernMidwestUnitedStates.
Keywords: industrial seed-oil; nitrogen use efficiency; agronomic efficiency; soil nitrogen;
potmarigold
1. Introduction
Calendula (Calendula officinalis L.), also known as pot marigold, belongs to the plant family
Asteraceae, which historically has served worldwide as a summer annual flowering-ornamental
plant. Calendula contains numerous compounds with demonstrated pharmacological activity [1].
Generally,calendulaseedshaveanoilcontentofabout160–210gkg−1[2,3]. Calendulaseed-oilisa
richsourceofcalendicacid(C18:3∆8trans,10trans,12cis),ahighlyoxidativeconjugatedfattyacidthatcan
serveasareplacementforcertainvolatileorganiccompoundsasadryingagentinseveralindustrial
chemicals such as paints, inks, coatings, and adhesives [4,5]. Calendula oil can be a substitute
for tung oil [6], which is produced commercially primarily in Southeast Asia from the tung tree
(AleuritesfordiiHemsl.). Anadvantagethatcalendulahasovertungisthatitcanbeconventionally
cultivated as a crop over a much broader range of environments. Calendula originated from the
Mediterraneanregion[7]andiswelladaptedtogrowinginawiderangeofenvironments,including
thenortherntemperatezoneoftheUSA[3,8].
Calendula has a long history of being cultivated in Europe primarily for pharmaceutical
use [9]; however, since about the late 1990s, in the United States and elsewhere, considerable
interest has focused on developing it as an oilseed feedstock for industrial purposes [3,10,11].
Agriculture 2018,8,40;doi:10.3390/agriculture8030040 www.mdpi.com/journal/agriculture
Agriculture 2018,8,40 2of13
Agronomicmanagementguidelinesforcommercialproductiontargetingindustrialusesoftheseed
oil are inadequate because information has been focused on materials other than seed yield [12].
Agrower’sguidedevelopedbyFromentetal.[13],basedonfieldworkintheUKandtheNetherlands,
recommendsarangeofNfertilizationfrom50to100kgha−1. Król[14]demonstratedthat,when
field-growncalendulainLublinPolandwasfertilizedwith0–160kgNha−1,asignificantincreasein
bothvegetativeandreproductive(dryinflorescences)materialoccurredbetween0and80kgha−1,
but no significant gains were observed at higher levels of amended N. Others [15,16] reported
modest positive responses in calendula seed yield up to 90–100 kg ha−1 of amended N. Under
environment-controlled conditions, Johnson and Gesch (2013) demonstrated that calendula had a
modest response to soil N fertilization; calendula followed a quadratic response to soil-amended
N, with reproductive dry matter optimized at a level equivalent to about 130 kg ha−1. In a field
studyconductedinIranunderirrigation,Moosavietal.[17]foundasignificantincreaseincalendula
reproductivematerialupto120kgha−1ofamendedN.Forlarge-scaleoilseedproduction,N-fertilizer
ratesshouldbeoptimizedformaximumoilyieldandminimumenvironmentalrisks. Mostofthe
literaturehasfocusedonflowercomponents,orseedbiomassbutnotoilproduction,sothisbasic
agronomicinformationisneededbeforelarge-scalecommercialproductionofcalendulaispractical.
Inaddition,thelimitedliteratureoncalendularesponsetoNfertilizerhasnotincludedreportsof
residualsoil–Nattheendofthegrowingseason.
Inadequatenitrogencanlowerpotentialyield, leadingtoalowereconomicreturn. However,
overfertilizationcanleadtonegativeeconomicandenvironmentalconsequences. Theoveruseof
N fertilizers in agriculture has been cited as a source of air and water pollution [18]. The release
of reactive nitrogen (e.g., nitrate) into the Mississippi watershed from agricultural lands has long
beenrecognizedasacontributortothehypoxiaintheGulfofMexico[19,20]. Despitelong-standing
goalstoreducenutrientloads,the“deadzone”sizemeasuredin2017exceededthefive-yearaverage
(https://www.epa.gov/ms-htf/northern-gulf-mexico-hypoxic-zone). Modelingscenarioshighlighted
the need to improve nitrogen removal efficiency, since residual soil N has the potential to move
off-farm entering watersheds. Several indices of nutrient use efficiency have been established to
evaluate the efficiency of nutrient application on the agronomically desirable product(s) [21–23].
Nitrogenremaininginthesoilattheendofthegrowingseasonrepresentsanunusedinputanda
potentialenvironmentalpollutionrisk.
Managing N-fertility for crop production can vary with soil type and climatic conditions.
Mollisols are common across the Northern Corn Belt region of the USA [24] where the climate is
characterized as continental mid-latitude with cold winters and warm summers [25]. Research to
establishN-fertilizerrecommendationsneedstoconsideragronomicresponseandtomeasuresoil
residualNtoevaluateenvironmentalrisks. Ascalendulaisdevelopedasanindustrialoilseedcropin
theNorthernCornBelt,USA,N-fertilizerrecommendationsareneeded,whichmaybetransferableto
otherareaswithsimilarsoilsandclimate.
Itwashypothesizedthatarecommendedfertilizerrateformaximumagronomicyieldwould
differfromtherecommendedrateforminimumenvironmentalrisk. Theobjectivesofthisstudywere
to(1)evaluatetheeffectsofNratesonbiomass,seed,andoilyield;(2)determinecalendula’sefficiency
toacquireandutilizeN;and(3)measureresidualsoilNaftercropharvestasanindicatorofpotential
environmentalrisk.
2. MaterialsandMethods
2.1. StudySitesandExperimentalDesign
Toassessplantbiomass,seedandoilyieldresponsetoNfertilizer(urea)application,areplicated
plotstudywasconductedduringthe2014and2015growingseasonsatSwanLakeResearchFarm
inWestCentralMinnesota(elevation344m,45◦35(cid:48) N,95◦54(cid:48) W).Eachyeartheplotswerelocated
on different field areas with Barnes soil (fine-loamy, mixed, superactive, frigid Calcic Hapludoll).
Agriculture 2018,8,40 3of13
ThesoilorganicCinthesurface30cmintheBarnessoilontheresearchfarmaverages25gkg−1
soil[26]. Eachyear,theexperimentwasarrangedinarandomizedcompleteblockdesign,consisting
of five nitrogen rates (0, 34, 67, 134, and 202 kg N ha−1) established in four blocks (replications),
whichresultedin20(3m×4.6m)plots. Thefarmsiteisequippedwithaweatherstationthatrecords
maximumandminimumairtemperatureusingashieldedthermistorat2mandprecipitationwith
atippingbucketraingauge[27]Climate1980–2010normalsarefromtheUniversityofMinnesota
WestCentralResearchandOutreachCenter[28]. Monthlyprecipitationnormalsare72,102,99,85,
and74mmforMay,June,July,August,andSeptember,respectively. Minimumandmaximumair
temperaturenormalsexpressedas◦Cwere7.4and20.2inMay,13.1and25.0inJune,15.3and27.3in
July,13.7and26.4inAugust,and8.3and21.7inSeptember.
2.2. AgronomicPracticesandFertilizerTreatments
DuringtheyearprecedingtheNratestudy,theexperimentalsitesweremanagedtoreduceany
carryovereffectsfrompreviouscropsorfertilizerbygrowingsorghum/Sudangrass(Sorghumbicolor
×Sorghumbicolorvar. sudanense)withoutNfertilizer. Theentiretargetedsitewasplantedwiththis
grass,whichwassowninto38cmrowsataplantingrateof502,000plantsha−1. Thegrasswascutand
biomassremovedtwiceduringthegrowingseason. Thenitrateplusammoniumintheexperimental
sitesbeforefertilizingaveraged28and31kgNha−1in2014and2015,respectively.
A pre-emergence herbicide, trifluralin (α,α,α-Trifluoro-2,6-dinitro-N,N-dipropyl-p-toluidine),
at2.34Lha−1wasappliedatthetimeofseedbedpreparation.Eachyear,theentirestudysitewastilled
withafieldcultivatoronceandharrowedtwicetoprepareanevenseedbed. Priortotillage,allplots
received33.6kgha−1ofsuper(triple)phosphate(P O )0-44-0. Justbeforesowing,ureawasapplied
2 5
withasmallhandspreadertoachieveN-ratesof0,34,67,134,and202kgNha−1. Thefertilizerwas
incorporatedatthetimetheplotswereharrowed.
Calendula was sown at 13.5 kg ha−1 on 28 May 2014 and 21 May 2015 into 19 cm spaced
rows using a no-till drill (model 3P1006NT, Great Plains, Salina, KS, USA). Three days prior
to harvesting with a plot combine, calendula was treated with a desiccant, diquot dibromide
[6,7-dihydrodipyrido(1,2-a:2(cid:48),1(cid:48)-c)pyrazinediiumdibromide]at11.7mLL−1with6.25mLL−1crop
oil. Harvestoccurredon18September2014andon1September2015.
2.3. SeedandSeedOilYield
Seed yields are reported as dry seed mass (kg ha−1). Seed oil content was measured by
pulsednuclearmagneticresonance(BrukerMinispecmq10,Bruker,TheWoodlands,TX,USA)on
approximately5gofseedfromeachtreatmentreplicationusingpreviouslydescribedmethods[29]
after calibrating the instrument with known quantities of pure calendula oil. According to AOCS
Method2-75,seedsampleswerefirstdriedat130◦Cfor4handcooledinadesiccatorfor15min
beforeoilcontentwasmeasured.
2.4. PlantandSoilSampleMeasurementsandAnalysis
Standcountsweredeterminedbycountingthenumberofplantsinonemeterofrowwithinthe
harvestedareaofeachplot. In2014,plantstandswerecountedfourtimes(11,18,23,and30June),
whereastheyweretakentwicein2015(10and16June). Thepopulationsreportedarebasedonthe
finaldatecountedineachyear.
Tocalculateshoot-to-rootratio,rootsandcorrespondingabovegroundbiomassweresampled
whenplantstransitionedfromvegetativetoreproductivegrowth(i.e.,initialflowering). Calendula
rootandshootsampleswerecollectedon21July2014and15July2015fromtwo(0.381m2)areasin
eachplot. Shootswerecutoffatsoillevel. Rootweresampledbytakingasoilsamplewithinthe
croprowandbetweenrowsusinga6.5cminnerdiametertippedhydraulicprobetoadepthof60cm.
Asaresult,therewerefourcorestakenineachplot. Soilcoresweresectionedto0–30and30–60cm
intervalstoprovideanestimateofrootmassandrootmassdensity. Soilcoreswerestoredat4◦Cin
Agriculture 2018,8,40 4of13
plasticbagsuntilrootscouldbehand-washedfromthesoilaspreviouslydescribedbyJohnsonand
Gesch[30],asamodificationofthemethodusedbySmuckeretal.[31]. Rootandshootsweredriedin
aforcedairovenat65◦Ctoconstantmassbeforedrybiomasswasdetermined.
Plantbiomassandharvestindexweredeterminedbycollectingabovegroundbiomassjustbefore
plantsweredesiccatedforharvestfroma0.19m2quadrant. Plantsampleswerecollectedasdescribed
above. Seedmasswasdeterminedbyhand-threshingthesesamples. Harvestindexwascalculatedby
dividinghand-thresheddryseedbiomassbytotalabovegrounddrybiomass.
Threeseparatesoilsamplingeventsoccurredannually. First,thenitrateplusammoniumlevel
inthe0–60cmrangewasmeasuredbeforeureawasapplied. Thesecondmeasurementwastaken
prior to planting, but after fertilizer was applied. Soil samples were taken from each plot (4 cm
diametercore)inthespring(4June2014and27May2015)toadepthof60cmanddividedinto0–15,
15–30,and30–60cm. Thethirdsetwascollectedon22September2014and2September2015after
harvesttoprovideameasureofresidualN,usingthesamesamplingprotocolusedpriortoplanting.
Duplicatesofeachsamplingcoreweretakenandeachwasdriedtoaconstantmass,oneat105◦Cfor
bulkdensityandtheotherat37◦Cfornutrientanalysis.
Driedplantmaterialfromthebiomasssampleswasgroundtopassthrougha0.425mmscreen.
Carbon and N content were determined by combustion using a LECO TRU SPEC CN analyzer
(LECOCorporation,St. Joseph,MI,USA).Priortochemicalanalysis,visiblerootsandplantresidue
wereremoved,samplesweregroundusingahammermill,followedbyaballmill(FrischPulvesette5,
Idar-Oberstein, Germany). Total soil C and N were determined by combustion as described for
theplantmaterialandinorganicCasdescribedbyWagneretal.[32]. Soilnitrateandammonium
ionconcentrationsextractedwith1Mpotassiumchloride[33]weredeterminedusingaLACHAT
QuickChem8500Series2(LachatInstruments,Loveland,CO,USA).Asrecommendedforalkaline
soils,availablePwasdeterminedusingacolorimetricassay(wavelength660nm)ofsoilextractedusing
OlsenPextractant(0.5Msodiumbicarbonatesolution)[34]. Potassiumextractedfromsoilwith1N
ammoniumacetatewasquantifiedbyflameemissionwithanAtomicAbsorptionspectrophotometer
(wavelength760nm)[35].
2.5. NUseEfficiencyandStatisticalAnalysis
Likeotherresearchers[21–23],wecalculatedseveralindicesofhowefficientlyNwastakenupand
subsequentlyconvertedtoseedoroilbiomass. SeedNuse(Equation(1))reflectstheeffectivenessof
calendulatoconvertthenitrogentakenupintoseedbiomass[21],whileseedN(Equation(2))andoil
N(Equation(3))useefficienciesreflecttheeffectivenesstoproduceanagronomicallydesirableproduct
perunitofappliedfertilizer[22,23].Agronomicefficiency[23]comparesyieldofanunfertilizedcontrol
toyieldwiththeapplicationofNfertilizer(Equation(4)).
(cid:16) (cid:17)
SeedNuse kgkg−1 =Dryseedyield/SeedNuptake (1)
(cid:16) (cid:17)
SeedNuseefficency kgkg−1 =Dryseedyield/Napplied (2)
(cid:16) (cid:17)
OilNuseefficency kgkg−1 =Oilyield/Napplied (3)
AgronomicNefficency(∆kg)
(4)
= (Dryseedyield − Dryseedyield )/Napplied
WithN NoN
Measuredparameterswereanalyzedforlinearandquadraticresponsetothecontinuousvariable
N fertilizer rate using PROC REG in SAS/STAT software version 9.4 (SAS Institute, Cary, NC,
USA)[36]. Thequadraticfunctionispresentedbecausethequadraticcoefficientsallowedcalculating
thecorrespondinginflectionpoint,whichrepresentsthemaximumfertilizerresponse. Agronomic
yeartoyearvariabilityisexpectedduetoweather;thus,theresponsetofertilizeusingdatafromboth
yearsisofmorevaluefordeterminingrecommendationrates. Therefore,regressionequationsreflect
Agriculture 2018,8,40 5of13
individual data from both years. The overall goal was to determine the response to fertilizer rate;
yearsareconsideredarandomeffect. Annualaveragesandstandarderrorsarepresentedtovisualize
datavariability. Post-hoccomparisonsamongspecificNratetreatmentsoverthetwoyearswasdone
usingLSMEANSPDIFFwithinagenerallinearmodel(PROCGLM).Comparisonsareconsidered
statisticallysignificantatapvalueof≤0.05. FigureswereproducedusingSigmaPlotforWindows
Agriculture 2018, 8, x FOR PEER REVIEW 5 of 13
version12.5Build12.5.038(SystatSoftware,Inc.,SanJose,CA,USA).
3. Results
3. Results
3.1. Growing Season Conditions
3.1. GrowingSeasonConditions
Accumulated growing season precipitation from May through September was comparable
Accumulated growing season precipitation from May through September was comparable
between years at 360 mm in 2014 and 378 mm in 2015, although slightly lower that the longer normal
between years at 360 mm in 2014 and 378 mm in 2015, although slightly lower that the longer
(Figure 1). However, distribution of precipitation varied. In 2014, June was the wettest month (149
normal(Figure1). However,distributionofprecipitationvaried. In2014,Junewasthewettestmonth
mm), while in 2015 the greatest amount of precipitation occurred in May (149 mm). In 2014,
(149 mm), while in 2015 the greatest amount of precipitation occurred in May (149 mm). In 2014,
September (16.5 mm) and July (32.5 mm) were the driest months, while in 2015 the driest month was
September(16.5mm)andJuly(32.5mm)werethedriestmonths,whilein2015thedriestmonthwas
in June (38 mm). Growing season average mean temperatures were 18.2 and 19.0 °C in 2014 and 2015,
in June (38 mm). Growing season average mean temperatures were 18.2 and 19.0 ◦C in 2014 and
respectively.
2015,respectively.
M ay 1 Jun 1 Jul 1 Aug 1 Sep 1 Oct 1
40
60
20
40 0
A 2014
-20
20
n e
o r
cipitati (mm) 600 -4400 mperatuoC) (
e
r 20 e
P T
40 0
B 2015
-20
20
-40
0
1 1 1 1 1 1
M ay Jun Jul Aug Sep Oct

Figure1. May–September2014(A)and2015(B):precipitation(solidverticalbars),dailymaximum
Fteigmupreer 1a.t uMreay(–bSleapcktemdobtetre d20l1i4n e(A),) daanidly 20m1i5n (imB)u: mpretceimpiptaetrioatnu (rseol(isdo lvidertbiclaalc kbalrisn)e, )d,apillya nmtianxgimduamte
t(egmrapyevraetrutircea l(bdlaaschke ddoltitneed) ,lihnaer)v, edsatidlya tmei(ngirmayumve rtteimcapledroatttuerde- d(saoslhide dbllaincek) ,lipnoes),t -phlaarnvteinstgs doailtesa (mgrpalye
vdeartteic(aglr adyasvheerdti clainled)o, thteadrvleinset )d.ate (gray vertical dotted-dashed line), post-harvest soil sample date
(gray vertical dotted line).
3.2. YieldandN-UseEfficiency
3.2. Yield and N-Use Efficiency
Seedyieldcouldbefitwithaquadraticfunction(r2 =0.174, p=0.029)(Figure2A)oralinear
functSioeend( syeieedldy iceoldul=d0 b.9e6 fNit rwatieth+ 5a6 q6u;ra2d=ra0t.i1c5 f9u,npc=ti0o.n01 (1r)2, =s u0g.1g7e4s,t ipn g= th0.a0t2t9h)e (sFeiegdurree s2pAon) doerd aw lienaekalyr
ftuonNctiaopnp (lsiecaedti oyniesl.dM = e0a.9n6s Nanradtes t+a 5n6d6a; rrd2 =e 0rr.1o5r9f,o pr =e 0a.c0h11y)e, asrugagreesptrinesge tnhtaetd t,hwe sheieledr reegsrpeosnsidoendi wsbeaaskelyd
toon Nd aatpapfrliocmatiboontsh. Myeeaarnss( nan=d4 0st)a.nTdhaer0d kegrrNorh fao−r 1earacthe yheaadr aanrea pvererasegnetdedry, wseheidley rieegldreosfsi5o2n4 iksg bhaase−d1,
ownh dilaetda rfyrosmee dboytihe lydeianrcsr (ena s=e 4d0t)o. T7h38e k0g khga N−1 haat−1t hraethe ihgahdes atnN arvaetrea(g2e0 2drkyg sNeehda y−i1e)l.dT ohfe 5c2o4e fkfigc ihean−t1s,
wprhoivlei dderyth seemede ayniesldto incacrlceuaslaetde ttoh e73in8fl kegc thioan−1 paot itnhtes hoifgaheqsuta Ndr raattice f(u20n2c tkiogn Nth haat−c1)o. rTrehsep coonedfsfictoienthtse
pthroeovridetei ctahleo mpteiamnus mto Ncarlacutel.atBea tsheed ionnfletchteioqnu padoirnattsic offu an cqtuioandrdaetiscc rfiubninctgiotnh ethNatr ecsoprroensspeoonvdesr toth tehsee
theoretical optimum N rate. Based on the quadratic function describing the N response over these
two growing seasons, the maximum seed yield was calculated to occur at 194 kg N ha−1 with a
corresponding predicted seed yield of 736 kg ha−1. Seed oil concentration did not respond to N
application, averaging 192 ± 0.25 g kg−1 over the two growing seasons (Figure 2B). Seed oil yield
showed a quadratic response to N rate (r2 = 0.144, p = 0.056) (Figure 2C), but the linear function was
not significant (r2 = 0.129, p = 0.23). The 0 kg N ha−1 treatment had an average seed oil yield of 105 kg
ha−1 and an average seed oil yield increased to 147 kg ha−1 at the highest N rate (202 kg N ha−1). Based
on the quadratic function describing the N response over these two growing seasons, the predicted
Agriculture 2018,8,40 6of13
two growing seasons, the maximum seed yield was calculated to occur at 194 kg N ha−1 with a
corresponding predicted seed yield of 736 kg ha−1. Seed oil concentration did not respond to N
application,averaging192 ± 0.25gkg−1 overthetwogrowingseasons(Figure2B).Seedoilyield
showedaquadraticresponsetoNrate(r2=0.144,p=0.056)(Figure2C),butthelinearfunctionwasnot
significant(r2=0.129,p=0.23). The0kgNha−1treatmenthadanaverageseedoilyieldof105kgha−1
anAdgraicnultauvree 2r0a1g8e, 8s,e xe FdOoRi lPEyEieRl dREinVcIErWea s edto147kgha−1atthehighestNrate(202kgNha−1). Based6 oofn 13
the quadratic function describing the N response over these two growing seasons, the predicted
mmaxaixmimumumo ioliyl iyelideld(1 4(174k7g khga h−a1−)1)i sisc aclacluculaltaetdedto too coccucruar ta1t 81383k gkgN Nh ah−a1−.1.H Hoowweevveer,r,s isnincecet htheed dryrys eseeded
and oil seed yield response was weak, this method may overestimate maximum response; especially
andoilseedyieldresponsewasweak,thismethodmayoverestimatemaximumresponse;especially
cocnosnisdiedreirnigngth tahtamt meaenanse speapraartaiotinonco cmompapraisroisnonsu sguggegsetssttsh tahtatth teh1e3 143a4n adn2d0 220k2g kNg Nha h−a1−d1 dififfefreerdedfr formom
the control, but differences were not noted among the N rates. The lack of differences among N rates
thecontrol,butdifferenceswerenotnotedamongtheNrates. ThelackofdifferencesamongNrates
implies little return per additional unit of fertilizer added.
implieslittlereturnperadditionalunitoffertilizeradded.

Figure2. Calendulaseedyieldat0%moisture(A),seedoilconcentration(B),andoilyield(C)asa
Figure 2. Calendula seed yield at 0% moisture (A), seed oil concentration (B), and oil yield (C) as a
functionofNfertilizerrate.Quadraticequationsshownwerecalculatedusingregressionanalysiswith
function of N fertilizer rate. Quadratic equations shown were calculated using regression analysis
datafrombothyears(n=40).Opencirclesrepresent2014andopensquaresrepresent2015treatment
with data from both years (n = 40). Open circles represent 2014 and open squares represent 2015
meanswithstandarderrorbars(n=4). Lettersatthebottomofeachgraphdenotethesignificance
treatment means with standard error bars (n = 4). Letters at the bottom of each graph denote the
amongNrates.
significance among N rates.
ThequadraticfunctionwassignificantforseedNuse(r2=0.215,p=0.0113),seedNuseefficiency
The quadratic function was significant for seed N use (r2 = 0.215, p = 0.0113), seed N use efficiency
(r2 = 0.701, p < 0.0001), and oil N use efficiency (r2 = 0.668, p < 0.0001), but not for agronomic
(r2 = 0.701, p < 0.0001), and oil N use efficiency (r2 = 0.668, p < 0.0001), but not for agronomic efficiency
efficiency(r2=0.071,p=0.3440)(Figure3). SeedNusewassimilaramongthe0,34,and67kgNha−1
(r2 = 0.071, p = 0.3440) (Figure 3). Seed N use was similar among the 0, 34, and 67 kg N ha−1 rates, and
rates,andamongthe67,134,and202kgNha−1 rates,whilethelowesttworateshadhigherseed
among the 67, 134, and 202 kg N ha−1 rates, while the lowest two rates had higher seed N use
compared to the highest two N rates. Mean comparisons found that greatest seed N use efficiency
and oil N use occurred at the 34 kg N ha−1 rate and decreased precipitously at higher rates. The linear
function was also significant for several of these parameters (seed N use = 46.6 − 0.038 Nrate, r2 =
0.211, p = 0.001), (seed N use efficiency = 18.3 − 0.0828 Nrate; r2 = 0.576, p < 0.0001), and (oil N use
efficiency = 3.67 − 0.016 Nrate; r2 = 0.551, p < 0.0001), but not for agronomic efficiency (r2 = 0.055, p =
0.195). A quadratic function did not significantly describe agronomic efficiency, but it could be
described by a power function (agronomic efficiency = 27.54 (Nrate)−0.623, r2 = 0.901). Harvest index
remained constant over all N rates with an overall average of 0.126 ± 0.005.
Agriculture 2018,8,40 7of13
N use compared to the highest two N rates. Mean comparisons found that greatest seed N use
efficiencyandoilNuseoccurredatthe34kgNha−1rateanddecreasedprecipitouslyathigherrates.
Thelinearfunctionwasalsosignificantforseveraloftheseparameters(seedNuse=46.6−0.038Nrate,
r2=0.211,p=0.001),(seedNuseefficiency=18.3−0.0828Nrate;r2 =0.576,p<0.0001),and(oilN
useefficiency=3.67−0.016Nrate;r2=0.551,p<0.0001),butnotforagronomicefficiency(r2=0.055,
p=0.195). Aquadraticfunctiondidnotsignificantlydescribeagronomicefficiency,butitcouldbe
describedbyapowerfunction(agronomicefficiency=27.54(Nrate)−0.623,r2=0.901). Harvestindex
Agriculture 2018, 8, x FOR PEER REVIEW 7 of 13
remainedconstantoverallNrateswithanoverallaverageof0.126±0.005.

Figure 3. Calendula seed nitrogen (N) use (A), seed N use efficiency (B), oil N use efficiency (C),
Figure 3. Calendula seed nitrogen (N) use (A), seed N use efficiency (B), oil N use efficiency (C), and
andagronomicefficiency(D).Quadraticequationsshownwerecalculatedusingregressionanalysis
agronomic efficiency (D). Quadratic equations shown were calculated using regression analysis with
withdata fromboth years(n =40). Opencirclesrepresent2014and opensquares represent 2015
data from both years (n = 40). Open circles represent 2014 and open squares represent 2015 treatment
treatmentmeanswithstandarderrorbars(n=4). Lettersatthebottomofeachgraphdenotethe
means with standard error bars (n = 4). Letters at the bottom of each graph denote the significance
significanceamongNrates.
among N rates.
3.3. VegetativeParameterResponse
3.3. Vegetative Parameter Response
Calendula plant stands did not respond to N rate, and similar stands were achieved both
Calendula plant stands did not respond to N rate, and similar stands were achieved both years,
years, averaging 871,000 ± 69,300 plants ha−1. Shoot and root biomass N concentrations were
averaging 871,000 ± 69,300 plants ha−1. Shoot and root biomass N concentrations were significantly
described by quadratic function (Figure 4). A linear function could be used to describe biomass N
response (shoot biomass N = 30.8 + 0.0846 Nrate, r2 = 0.458; p < 0.0001; root biomass N = 17.1 + 0.0258
Nrate, r2 = 0.414; p < 0.0001). Mean comparisons suggested that shoot N concentration was lower at
N rates of 0 and 34 kg N ha−1 compared to the three other N rates. Root tissue N concentration at the
three lower N rates were similar and significantly less than the root N concentration at 134 and 202
kg N ha−1 rates. Greater tissue N concentration did not translate to additional shoot biomass (2030 ±
1120 kg ha−1) nor root biomass (2010 ± 593 kg ha−1), so the root-to-shoot ratio (1.34 ± 0.86) was not
impacted. The lack of growth response to N rate is consistent with weak seed and seed oil yield
responses. Furthermore, this indicates that calendula takes up the additional N but is inefficient at
utilizing it to produce more biomass or agronomic product.
Agriculture 2018,8,40 8of13
significantly described by quadratic function (Figure 4). A linear function could be used to
describe biomass N response (shoot biomass N = 30.8 + 0.0846 Nrate, r2 = 0.458; p < 0.0001; root
biomass N=17.1+0.0258Nrate, r2 = 0.414; p < 0.0001). Mean comparisons suggested that shoot
N concentration was lower at N rates of 0 and 34 kg N ha−1 compared to the three other N rates.
RoottissueNconcentrationatthethreelowerNratesweresimilarandsignificantlylessthanthe
rootNconcentrationat134and202kgNha−1rates. GreatertissueNconcentrationdidnottranslate
to additional shoot biomass (2030 ± 1120 kg ha−1) nor root biomass (2010 ± 593 kg ha−1), so the
root-to-shootratio(1.34±0.86)wasnotimpacted. ThelackofgrowthresponsetoNrateisconsistent
withweakseedandseedoilyieldresponses. Furthermore,thisindicatesthatcalendulatakesupthe
Agriculture 2018, 8, x FOR PEER REVIEW 8 of 13
additionalNbutisinefficientatutilizingittoproducemorebiomassoragronomicproduct.

FFiigguurree4 4..C Caalelenndduullaas shhoooott( (AA))a annddr roooott( B(B))t itsisssuueeN Nc coonncceenntrtraatitoionno offs saammpplelessc coollleleccteteddi ninJ uJulylyw whheenn
pplalanntstsw weerreet rtraannssitiitoionnininggf rfroommv veeggeetatatitviveet otor erepprorodduucctitviveeg grorowwthth..Q Quuaaddrraatticice eqquuaattioionnsss shhoowwnnw weerree
ccaalclcuulalateteddu usisninggr ergergersessiosinonan aanlyaslyissiws iwthitdha tdaaftrao fmrobmo tbhoyteha yrsea(nrs= (n40 =). 4O0p).e Onpciernc lecisrrcelepsr erseepnrte2se0n14t 2a0n1d4
oapnedn osqpueanr essqureaprreess erenptr2e0s1e5nttr e2a0t1m5 etnretamtmeaennst wmitehanstsa nwditahrd stearnrodrabrdar ser(rno=r 4b)a.rLs e(tnte =rs 4a)t. tLheettbeortst oamt tohfe
ebaocthtogmra pofh edaecnho gteratphhe dsiegnnoifitec athnec esiagmniofnicganNcer aatmeso.ng N rates.
33.4.4.. PPoosstt--HHaarrvveessttR ReessiidduuaallS SooiillN N
TThheea ammoouunntto offs sooililr reessididuuaallN Nf foolllolowwininggh haarrvveesstta att0 0––1155,,1 155––3300,,3 300––6600,,a annddf foorr0 0––6600c cmmc coouullddb bee
ddeessccrriibbeedd bbyye eiitthheerra al ilnineeaarro orrq quuaaddrraattiiccf fuunnccttiioonn;; hhoowweevveerr,,o onnlylyt htheeq quuaaddrraatticicf fuunnccttioionnssa arrees shhoowwnn
((FFigiguurere5 5))b ebceacuasueseth tehseesfeu fnucnticotniosnws ewreerues eudsetod ctaol ccuallactuelathtee tphoei nptoaitnwt ahti cwhhthicehN threa tNe craautsee cdatuhseedle athste
rleesaisdtu raelsisdouilaNl s.oTilh Ne.l iTnheea rlifnuenacr tfiuonncstwioenrse wsoerile ksgoiNl khg aN− 1h=a−19 =.1 97.1+70 +. 204.274N7 rNartea,ter,2 r=2 =0 0.3.31111,,p p= =0 0.0.0000022
aatt 00––1155 ccmm;; ssooiill kkgg NN hhaa−−1 1== 2.22.62 6+ +0.109.189 N8rNartea,t er,2 =r2 0=.2007.2, 0p7 =, p0.=0003. 0a0t3 15a–t3105 –c3m0; csmoi;l skogi lNk ghaN−1 h= a8−.216= +
80.2.067+8 N0.0ra7t8e,N rr2 a=t e0,.2r222=, p0 .=2 202.0,0p2= at0 3.000–260at c3m0;– a6n0dc mso;ial nkdg Nso ihlak−g1=N 19h.7a −+ 10=.51293. 7N+ra0t.e5,2 r32 =N 0r.a3t2e7,,r 2p == 00..0302071,
pa=t 00–.06000 c1ma.t A0–t 6a0llc pmr.oAfiltea ilnltperrovfialles,i nmteeravna clso,mmpeaarniscoonmsp faoruisnodn tshfaotu tnhde t2h0a2t kthge N20 h2ak−1g fNerthilaiz−e1rf rearttiel ihzeard
rmatoerhea sdoiml roerseidsouiallr Nes icdoumaplNarecdo mtop oatrheedr tNo ortahteesr.N Atr athtees .2A02t kthge N2 0h2ak−1g raNteh, a1−501 rkagt eh,a1−51 0wkags hmae−a1suwraesd
mine athsue rseodil i0n–t6h0e csmo islo0i–l 6p0rocfmiles (oFiligpurroefi 5leD()F, iwguitrhe m5Dos)t, owfi tthhem No sdteotefcttheed Nin dtheete 0c–te1d5 icnmt h(Feig0u–1re5 5cmA)
(aFnigdu 1re5–53A0) camnd (F1i5g–u3r0ec 5mB)( Fsoigiul irnec5rBem)seoniltsin. cTrheem qeunatsd.rTahtiec qeuquadartiaotnic perqeudaitcitoendp lorewdeicstte rdesloidwueaslt Nre swidouualdl
Nocwcuoru ladt ofcecrutirliaztefre rrtaitliezse rorf a3te0s, o4f93, 0a,n4d9 ,4a1n dk4g1 Nkg hNa−h1 ai−n 1tihnet h0e–105–,1 51,51–53–03, 0a,nadnd 3300––6600 ccmm iinntteerrvvaallss,,
respectively. For the 0–60 cm profile, the minimum residual soil N of 34 kg ha−1 was predicted to
occur at a fertilizer rate of 39 kg N-applied ha−1.
Agriculture 2018,8,40 9of13
respectively. Forthe0–60cmprofile,theminimumresidualsoilNof34kgha−1 waspredictedto
Agriculture 2018, 8, x FOR PEER REVIEW 9 of 13
occuratafertilizerrateof39kgN-appliedha−1.

Figure5.ResidualsoilN(kgNha−1)at0–15(A),15–30(B),30–60(C),and0–60cm(D)profileintervals
Figure 5. Residual soil N (kg N ha−1) at 0–15 (A), 15–30 (B), 30–60 (C), and 0–60 cm (D) profile intervals
following calendula harvest in 2014 and 2015. Quadratic equations shown were calculated using
following calendula harvest in 2014 and 2015. Quadratic equations shown were calculated using
regressionanalysiswithdatafrombothyears(n=40).Opencirclesrepresent2014andopensquares
regression analysis with data from both years (n = 40). Open circles represent 2014 and open squares
represent2015treatmentmeanswithstandarderrorbars(n=4).Differentlettersatthebottomofeach
represent 2015 treatment means with standard error bars (n = 4). Different letters at the bottom of each
graphdenotesignificanceamongNratesp≤0.05.
graph denote significance among N rates p ≤ 0.05.
4. Discussion
4. Discussion
In a greenhouse pot study with about 37 kg N ha−1 in the potting mix before fertilizer was
In a greenhouse pot study with about 37 kg N ha−1 in the potting mix before fertilizer was added,
added, maximum calendula capitula biomass occurred at the equivalent of a fertilizer rate of
maximum calendula capitula biomass occurred at the equivalent of a fertilizer rate of 169 kg N ha−1
169kgNha−1[30]. Slightly less than the 194 kg N ha−1 fertilizer rates for maximum seed and
[30]. Slightly less than the 194 kg N ha−1 fertilizer rates for maximum seed and 183 kg N ha−1 rate for
183kgNha−1 rateforoilyieldwerecalculatedinthisstudy. SamoonandKirad[37]reportedthe
oil yield were calculated in this study. Samoon and Kirad [37] reported the greatest seed yield (115
greatestseedyield(115kgha−1)atafertilizationrateof150kgNha−1foranornamentalcalendula
kg ha−1) at a fertilization rate of 150 kg N ha−1 for an ornamental calendula variety on a sandy soil
with a baseline of about 5 kg N ha−1. They also reported that, although this fertilizer rate (150 kg N
ha−1) provided the greatest seed yield, the efficiency to utilize the N to produce additional yield was
very low. On a silt loam with a baseline soil N of 2.3 kg N ha−1 calendula seed yield did not respond
strongly to N application [14]. The current study was conducted on Barnes clay loam soil with an
Agriculture 2018,8,40 10of13
varietyonasandysoilwithabaselineofabout5kgNha−1. Theyalsoreportedthat,althoughthis
fertilizerrate(150kgNha−1)providedthegreatestseedyield,theefficiencytoutilizetheNtoproduce
additionalyieldwasverylow. OnasiltloamwithabaselinesoilNof2.3kgNha−1calendulaseed
yielddidnotrespondstronglytoNapplication[14]. ThecurrentstudywasconductedonBarnesclay
loamsoilwithaninitialsoilNofabout30kgNha−1,andbasedonthechangeinsoilNinthecontrol
plotsabout40kgha−1ofNwasmineralizedoverthecourseofthegrowingseason,implyingthatthe
soilcouldprovidesomeoftheNneededtosupportthecalendula. MineralizationofsoilNisexpected
toinfluencetheamountofNfertilizerrequiredtosupportcropproduction. Ingeneral,asmoreNcan
bederivedfrommineralization,theamountoffertilizerNincreases[38]. Mineralizationiscomplex;
itisimpactedbythequalityofresidueinputs,temperature,moisture,interactionwiththecurrentcrop,
theadditionoffertilizer,andthetypeoffertilizer[38,39]. Recommendationforfertilizerratesreflect
theclimaticandsoilconditionswheretheywereestablished. Assuch,theseNraterecommendations
mayserveasaninitialguideforexpectedresponsebuttheyneedtobecheckedandmodifiedforlocal
conditionspriortoadoption.
BasedonthreeindicesofNuseefficiencymeasuredinthepresentstudy(seedNuseefficiency,
oilNuseefficiency,andagronomicefficiency),thereappearstobeminimalgainsinNuseefficiency
beyondafertilizerrateof34kgNha−1. Thelowestresidualsoil-Nattheendofthegrowingseason
wascalculatedtooccuratafertilizerrateof39kgNha−1,predictedtoyield738kgseedha−1 and
124kgha−1seedoil. AtthisNrateandusingthecorrespondingquadraticresponsefunctionsforseed
yieldandseed-oil,thoseyieldsarepredictedtobeaboutonly15%lessthantheyieldcalculatedusing
theNrateof194and183kgNha−1,respectively,formaximumseedandseedoilyield,butusing
78–79%lessfertilizer. ApplyingNattherateformaximumyieldassumingapriceof$313.31Mg−1
(http://www.farmersco-op.coop/pages/custom.php?id=21023),itwouldcost$0.083kg−1 seedand
$0.39 kg−1 seed oil, compared to a cost of $0.021 kg−1 seed and $0.099 kg−1 seed oil if urea was
appliedat39kgNha−1,tominimizeresidualsoilN,whichisafour-foldincreaseincostperunit
yield. Thus,exceedingabout39kgNha−1fertilizerapplicationresultsingreatercostperunityield
andincreasesthepotentialresidualsoilN.
Attheendoftheseason,about150kgNha−1wasmeasuredinthesoilprofileatthe202Nkgha−1
rate,which,assumingabackgroundmineralizationof37kgNha−1fromthecontrol,correspondsto
50%oftheNappliedbeingunused. Nitrogenremaininginthesoilprofileattheendofthegrowing
season is at risk of becoming an environmental liability instead of an agronomic asset [18]. In the
presentstudy,growingseasonprecipitationwas71and53mmbelowthe431mm30-yearaverage
(https://www.ncdc.noaa.gov/cdo-web/datatools/normals)in2014and2015,respectively. In2014,
Septemberprecipitation(16.5mm)waslowcomparedtothe74mm30-yearaverageforthesame
month(https://www.ncdc.noaa.gov/cdo-web/datatools/normals). Asaresult,Nnottakenupby
growingplantsremainednearthesoilsurfaceinsteadofmovingdeeperintotheprofile,likelybecause
oflittledownwardwaterflowduringdryconditions.Inhumidclimates,excessNcanmovewithwater
intogroundwatersuppliesorthroughartificialornaturaldrainagetosurfacewater. Alternatively,
Ncanmovewitherodingsoilintowaterways. Regardlessofthepathway,displacedreactiveNmay
causewaterquality(e.g.,hypoxia)andhumanhealthissues. Nitrogeninexcessofplantdemandcan
result in the release of nitrous oxide [40], which has long been recognized as a potent greenhouse
gas[41]. PrudentNmanagementprovidesenvironmentbenefitsandavoidsineffectiveuseofvaluable
fertilizerinputs.
Plantutilizationoffertilizerincludesnutrientuptake. Calendulaappearedtoeffectivelyacquire
Nasevidencedbytheincreaseintissueconcentrationintherootsandshoot. However,calendula
didnotconverttheadditionalNintoshoot,root,orreproductivebiomassimplyingalowutilization
efficiency. SeedNusedeclinedwithNapplication,implyingreducedreturnoninvestmentconsistent
withveryincreasedcostperunitseedascalculatedabove.
ThisstudyconductedonaBarnesclayloam,aMollisolintheNorthernMidwestUnitedStates
demonstrated that calendula, especially calendula seed and oil production, responded weakly to