Curt s. Dare. Delso'", j2 - l ue sa, -. D" ao,r' l"C: De sov 5:Cl l-lo:- --l'-. Dorma'. Dyer- trpp5. ISSEX. Ga. U3SO1. Graham. Gregg. Harbar. Haske. Hilt. Holladay. Hood. Hood 75. Hutcheson. JE. Krno ...... Boerma, H.R., R.S. Hussey, D.V. Phillips.
RESEARCH
Morphological Responses to Low Plant Population Differ Between Soybean Genotypes James E.
ABSTRACT Because of increased seed costs for soybean fGlycine max (L ) Merr.], minimizing plant
population to a level that still optimizes yield (minimal optimal plant population) has become important. Because little
is
known about possible
genotypic strategies addressing this problem, the objectives of this study were to (i) determine the relative accuracy of three putative selection
criteria for genotypic differences in minimal optimal plant population and (ii) use the best criterion to identify cultivar differences within the southern U.S. public cultivar germplasm collection. Two studies to address these objectives were conducted near Baton Rouge, LA (30" N lat). The first study (in 2007 to 2008) involved eight cultivars grown at normal (198,000
plants ha ') and sparse plant populations
(10,000 plants ha-1). Cultivar potential for a low
minimal optimal plant population was assessed by relative yield (%) in sparse vs. normal plant population. Normalized branch dry matter (BDM) per plant (BDM per days to R5) was the
most accurate selection criterion for minimal optimal plant population. This criterion was then used in a second study to assess minimal optimal plant population differences among 41 cultivars. Wide differences in normalized BDM per plant occurred, ranging from 0..10 to 1.50 g per plant d-1. ln conclusion, normalized BDM per plant is an accurate and efficient selection measure for minimal optimal plant population.
Board* and Charanjit S. Kahlon
J.E. Board and C.S. Kahlon. School of Plant, Environrnental, and Soil Sciences, Louisiana State unir,. Agricultural Center. Baton Rouge, LA 70U03. Pubhshed ',vith the approval of the Director of the Louisi:rna St:rte lJniv. Agricultur:rl Experiment Station ;rs p:]per no. 2012-306-
7135. Received 15 Aug. 2012. *Corresponding :ruthor
fiboarcl@,,
agcenter.lsu.edr-r).
Abbreviations: BDM, br;rnch dry nratter; BDMPART, percenttrge of branch dry lnirtter partitioned rnto branches: MG. maturity group; NS, not significant; TDM, total dr,v nlatter.
I ualon -\cRoNoMIC oBJECTIVE for soybean is to reduce the I \niinirrral pl.rnt popularion required for oprinral vield (i.e.. rninimal optimal plant population). Although considerable information is available explaining hor,v environnrental factors reduce nrininral optimal plant popr.rlation (Lehman and Lanrbert, 1960; Lueschen and Hicks, 1977; We1ls, 1991, 1993; Carpenter and Board, 7997u 1997b; B:r1l et al., 2001), little research has been done on genotvpic approaches to recluce rninirnal optimal plant population. Soybean yieid denronstrates ;in asylDptotic ,vrelcl platear,r as plant popul:rtion is incre:rsed (Edr.varcls :rnci Purcell, 2005; De Bruin and Pedersen, 2008). Therefore, siurilar ,vielcls can be obtained across :t range of plant populations. The nrost profrtable strategv for a soybean Ilrtner is to plant at the seeding rate that achieves the nrininral optirnal
plant population. This objective has gained greater itnportance because seed of genetically nrodified cultivars costs about USS28 to 36 ha-1 more than conventional seed (Chen and'Wiatrak,201,1). A typical Louisiana sol,bean fanner pays $2.18 kg 1 for geneticallv rrrodifi.ecl seed (Paxton, 201,1). Studies b.v'Wel1s (1991, 1993), Ball et a1. (2000), and De Bruin and Pedersen (2008) have deuronstratecl that the nrinirnal optinral Published rn Crop Sci. 53:1109-1119 (2013) doi: 10.21 35/cropsci20 12.0,1.0255 ,O Crop Science Society ofAmerica 55115 Guilibrd Rd.. Madson, WI 51711 USA
All rights reservetl. No prrt ofthis periotlrcll nrrY be reproduced or rrarrslritted irr rnv tbrrn or bv .rDv rneirls, electrorric or rrrechanical, irrcludiue photocopying, recordinq. or arry intbrmarion storrge irrrd retrievll svsten, rvithont pernissiou irr rvritirrg iiottr the publisher. Perlrrssion ibr printine rrrd tbr reprinting tlre rnacerial corrtairrecl herern has beerr obraiued bv the publisher.
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plant population is lor'vest (i.e., optinral vield can be achieved r,vith lower plant population) r'vhen grorving conditions are
pod, nrain stenr, and BDM. Branch dry nratter refers only
favorable. lJnder favorable grorving conditions (greater
Genotypic factors interact rvith environrnental conditions in a{Iecting nrinirnal optiural plant population.
1ight, higher teirperatures, and more timely rainfalls), Wells (1993) reported a nrinirnal optillral plant population of only 30,000 plants ha-1. In contrast, mininral optimal plant population in a year of poor growing conditions was 110,000 plants ha-i. Ball et al. (2000) demonsrrated that at late planting dates where a shortening photoperiod and hieher tenrperatures curtail the vegetative grou,ing period (enrergence to R5; Egli and Leggett, 1973) and reduce crop bionrass, minimal optinlal plant population had to be increased to 600,000 plants ha-1 fronr the typical 300,000 plants ha I g;ror,vn at optinral planting dates. Workins at a nriclwestern lJ.S. location, De Bruin and Pedersen (2008) clenronstrated a highly nesative resression relationship betr,veen yield and minirnal optimai plant population (R = -0.92, P < 0.01), supporting previous research indicating that rnininral optirnal plant population declines .rs grorving corrclitions inrprove (Wells, 1991, 1993; Bali et al., 2000). An exception to this inverse relationship between gror,ving conditions ancl minimal optimal plant population occurs r'vith drought stress during reproductive gror,vth (Devlin et a1., 1995). In this case, high plant populations exhaustecl soil water sooner than low plant populations, resultins in a greater relative yield inhibition. Consequently, rtrinirtr:rl optimal plant population under drought conclitions r,vas achieved rvith a seeding rate of only 1.29,1.1.2 vs. 573,0,10 seed ha-1 for plants receiving adequate water. Yielci is unaffected rvhen crop srowth rate for low plant populations equilibrates rvith that of hieher plant populations bv R1 (stages according to Fehr ancl Caviness 11977)) (Board, 2000). The resulting yield colrlpensation in sparse vs. nomral plant populations has been attributecl to qreater branch stenr developnlent (Herbert ancl Lrtchtlelcl, 1982; Hicks et al., 1969; Lehuran ancl Lanrbert. 1960: Lueschen and Hicks, 1977). Specifically, greater br;rnch dry nratter (BDM) per plant creates nrore branch noc'les. branch pocls, and branch seeds, rvhich results in qrelrer 1,ielcl per plant in sparse vs. norrnal plant populrrtions (Carpenter and Board, 1997a). Branch dry rnltter per pl:rnt is deternrined by R5 (Hanway and'Weber, 1971; Egli and Leggett, 1973; Board and Settirni, 1986) and changes little betlveen R5 and R7; hor,vever, detennination is usualhdone shortlv after R7. This greater BDM per plant clerives fronr greater tot:rl dry nratter (TDM) per plant, sreater percentage ofbranch dry nratter partitioned into branches (BDMPART), and/or a synergistrc interaction betrveen the trvo (Carpenter and Board, 1997a, 1997b: Board, 2000). More favorable environnrental conditions enhance this process, rvhich explains why nrininral optinral plant population is generally lower under good gror,ving conditions. When sampled shortly after R7 such as was done in the cr,rrrent study, TDM per plant is the sum of 1110
to branch stems and not branch pods.
Anrong cuitivars grown at a lor,v (95,000 plants ha-r) vs. nomral plant popularion (250,000 plants ha-r), yielcl '"vas largelv associated r,vith factors related to branch developrnent:
BDMPART, TDM per plant, BDM per p1ant, and days frorrr R1 to R5 (Rigsby and Board, 2003). Flor,vever, these putative preclictors have not been validatecl in independent studies and their relative accuracies for rdentification of cultivars having lo-uv rninimal optinral plant population have not been determined. Edlvards and Purcell (2005) denronstratecl that across nlaturity group (MG) I through VI cr-rltivars qrown in the rnid south ljnited States, urininral optirilal plant propulation declined as nraturity lengthened. Although cletailed branch developrnent data were nor reported. the authors did show that days from R1 to R5 (period lbr nrost branch developnrent [Board and Settimi, 1986]) increasetl qoinq frorn earlv to late nraturing cultivars. Since cultir:ars \\-ere qro\\-n in the sanre environluent! branch development probablv increased as MG increased. C onrparison of cleterrninate vs. indeterrninate mid'"vestern cultivars denronstrated greater branch number and greater BDM production in rhe lbrrtrer cornpared r,vith the latter (Beaver et al., 1985). G:ri et al. (198,1) reported greater branch nunrber and branch nodes in determinate vs. indeterininate Chinese cultivars. Because
of large environmental and genotypic
efecrs.
nrininral optinral plant population has varied fronr 30.()()(l to 500,000 plants ha I (Lehnran :rnd Lanrbert. 196r,): LetGl and Barber, 1961; Ltieschen and Hicks. 1977: Costa et a1.. 1980: Eg1i, 1988; Wel1s. 1991). Usine a sinsle cultivar €fo\\-n across t\\'o rou' spacinqs. 3 r-r. and three locations in Iorva,
DeBmin
ancl Petlersen r2lt( tEl shos'er1
nrinintal optinral plant poprrlations (c.rlcu1are.1 .ls pla,r, popularron required for 95'/r, of nrarinral r're1.1) r'arvinq iionr 118.800 to 213,800 plants ha-r. Iir sunrnrarr'. .rlrhor-rgh nruch research has been done on enr-iroi-rrrrental t.rcrors allecting mininral optinral planr pol.ulrtion. lirtle rese:rrch is avarlable at the genotypric ler-el.
rhe rhree putritive predictors for nrininr;rI optinr.rl planr popularion (TDM per p1ant, BD-\l fs1 p1anr. and BD\,IPART) need to be vaiidated to derennine s'hich i: rnosr accurate. The objectives of thrs .ruJr- are to ir; .leternrine lr.hich of the three paranrerers Frevrerushsrr-rdiec'l (TDM per plant, BDM per plant, .rnil BD\ 1P-\RT: Rigsbr- .rnd Boarcl [2003]) is the best selection -:::-rL)r lor Specric.rll,,".
identitr-rng so,vbean cultivars having los- urrr:rnr.r- ..::::ra1 planr population and (ii) use this selecrior- ,r-i:r-crrt !o iclentifv cultivars r'vithin the southern U.S. r-::..-- . .:...r11 Eaernrplasni collection that have 1ou' ir:::t::-..- --::::trl1 plant popr-r1ation. Public cultivars u-ere '.r.:j ::-- :1:, .:'.:dv because o[ legal restriccions for errcerin= :': . ,:i ..:.:.r':rs into genotypic or breeding studies.
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Table 1. Selected public cultivars for studies one and two from the southern soybean germplasm collection with year of release, growth habit, state of derivation, and reference citation. Cultivar
Study
Anand Bay Bedford Bradley
2 2 2
Bragg Brim
2
vil
2
Catoosa Celest
2
CF46] CF492 Choska C ifford
2
Colqu Curt s
MGt
l IV
IV 2 2
ii
Dare
2
vil
2
V]
2
Delso'", j2
-
l
2
ue sa, D" ao,r'
-
2
l"C:
2
De sov
5:Cl
2
l-lo:-
--l'-
2
Dorma'
1
State of
derivation
Det, Det.
989
Det.
958 1 965
Det.
I 991
r 1
Det.
1
991
lndet. lndet.
r
989
lndet,
1
995
Det.
Det. Det.
Carter et al., 1997
Det,
Harv le et a., 19BB lvlontoya and Cast lo, 1993
2
Gregg Harbar Haske
2
Det. Det.
Georg a North Caroi na Louisiana Mexico Georgla
989 993
Det.
1
M ss ssrppr
r
959
Det.
1
993
Det.
r
958
Det.
1975
Det.
1987
Det.
1
980 966 1 983 1 993
Det.
1
Det.
ndet.
aad2
Holladay Hood
2
North Caro na
2
Hood 75
2
Mississippi Arkansas
Hutcheson
2
V rg nia
JE
2
Krno
2
Arkansas Arizona
vil
i
orida Kansas Kansas Misslssippi Arkansas Arkansas F
2 2 2 2 2
USDA.ARS,2012b Brim, 1966 Anand,1992a Anand,1992b Anand, l99l Anand,1997 Anand, 2000 Werss ard Slevenson, 1955 Hartw g and Epps, 1968 Hartwig, 1984 Smrth and Camper, 1973 Brlgham, 1979 Baker and Harris, 1979
1996 1983
Graham
VI
1991
100/
Det.
vil
1
lndet.
1977
IV
l
Young
ndet.
995
1978
2
l l
995
r
Det.
U3SO1
Pershing Vance
1
1972
Ga
2
USDA-AFS, 20]2A Pfeiffer et a., 1996b Pfeiffer et a., 1996a Edwards et ai., 1995 Burton et al., 1997 Boerma et al., 1990
Det.
2
Lyon
Farno et al., 2003
Det.
967 1983
ISSEX
KS5292 Lamar Lee 68
Det.
1977
1
Mississ pp Virgin a Miss ss ppl
1
Det.
Det.
2
Kirby KS4694
Det.
990 2000 I
998 1 955
trpp5
1
Det.
1963
r
Miss ss ppl
Hilt
Det.
983
1
Det.
Missouri Miss ss pp
2
vI
1977
Anand et al., 2001 Buss et al.,1979 Hartw g and Epps, 1 978 Anand and Shannon, 1984 Hinson and Hartwig, 1964 Burton ei al.,1994
Missouri Missouri Missouri
and2
2
Reference citaiion
Det.
Louisiana North Carolina Missouri
Dyer-
2
Growth habit+
999 1 978
1
Kentucky Oklahoma North Carolina Georg a
IV
VII
Year of release
Missouri Virginia M ssissippi M ssouri Flor da North Carol na Oklahoma Delaware Kentucky
Det.
Det.
1990
Det.
1
989
Det.
I
968
Det.
1974
Det.
Boerma et a., 1994 Johnson, 1960a Burton et a., 1996 Johnson, 1960b Caviness and Waters, 1976 Buss et al., l9BB Caviness et al., 1982 USDA-ARS, 2012C USDA-ARS, 2012d Schapaugh and Dille, l99B Schapaugh and Todd, 1998 Hartwig et al., 1990 Caviness and Walters, 1968 Cav ness et al., 1975 Hartwig et a., 1994 Anand and Srannon, l9B5
Mississipp Missour
r 1
993 984
V rgin a
r
986
Det.
USDA-ARS, 20]2C
North Carolina
1
984
Det.
Burton et al., 1987
Det. I
n
det.
'MG, matur ty group. iDet., determinate growth hab
t; ndet.
indeterm nate growth habit.
MATERIALS AND METHODS Development of Screening Methods for ldentification of Cultivars with Low Minimal Optimal PIant Population (Study One) The str-rdy 'uvas pl:rnted at the Ben Hur research f:rrm near Baton Rouge, LA (30" N lat) on a Commerce Silt Loam soil (frnesilty, nrixed, superactive, nonacid. thermic Fluvaquent Endoirquepts). The test site h:rd tile drainage and access to irrigrtion.
CROP SCIENCE, VOL.
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Eight cultivars (described in Table 1) from the southern U.S. sovbean germplasm collectron were selected for the study: Gaso1, 17, Celest, Young, Kirb.v, Dorrnan, Hil1, Pershing, and Vance. Planting dates were 20 Apr. 2007 and 8 Mav 2008. Seeding rates rvere 310,000 seecl ha I lor the normal plant population tre:rtnent and 19t3,000 seed ha I for the lor,v plant population cre.rtnlenr. Seeding rates for the nornral plant population rvere sufficienr to achieve a final plant stand ofat least 198,000 plants ha-r (verrfied bv stand counts taken at the V3 stage [Fehr and Caviness, 1977]), recognized as optimal for the :rrea (Carpenter and Board, 1997a).
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1111
Fin;,rl
low plant population rvas achieved by hand thinning to
by PROC MIXED (SAS Institute, 2006) rvith replications and
10,000 plant ha-r based on soil test recomrnendations and the site rvas Grtilized at rhe rare of 0-34-67-33 kg ha-t (N P K S). Soil pH ."vas lvithin the optimal range ar 6.2. Planting rvas done on raised beds rvith a 97-crn ror,v spacing and a 7.2-rn ro.,v length. Seed wirs nrachine plantecl into four-rorv plots. Recommended pesticides r'vere used to control rveeds, diseases, and insects.
years as random factors. Mean separation r.vas by
Rainfall levels drflered betrveen the 2 yr of the stud1,. During theJune throughJuly reproductive period, only 1,1 cm of rain fell in 2008 vs. 33 cnr rn2007. Although irrigation was done to ensure st;rnd establishnrent and early crop growth in Mav 2008, subsequent irrigation was not clone because the test site is adjacent to the Mississippi River and ground water levels are usually high enough during the summer to supply established crops r.vith adequate water. Horvever, in 2008, ground water levels may have
if the
been belor,v nornl2rl resr"rlting in gror.vth ret2rrclation. Experirnental design was l rirndonrized conlplete block in a split-plot arran€lenrent with 2 yr and four replications. Years and replications r,vere treated as random factors i.vhile cultit ars and plant populations rvere fixed. Treatment mean separation and analyses of inter:rctions are only appropriate for fixed factors (cultivars and plant populations) (Blouin et ,il., 2011). Randorn f:rctors (years and replic:itions) :rffect variances used to c:rlcr-rlate F tests for the fixed factors. Main plots r.vere cultivars and split plots rvere nomral (198.000 plants ha 1) and lorv plant populations (10,000 planrs ha-l). Yield rvas based on a 4-rn2 :rrea harvested from the trvo middle ror.vs of the plot. Ro'uvs r,vere end trinuned before harvest. Plants were threshecl by a Hege small-plot combine (Hege Maschinen). Approxinratei.v tlO plants were han,ested for vield determination in the nomral plant populatron plots rvhile four plants rvere used for the lorv plant population plots. Seed samples were moisture tested and,vield adjusted to 130 gkg-L moisture content. Relative 1,ie1d [(yrelcl,,,,,r,u/]'i"1.1,,.,,,,r"J x 100, rn'"vhich vield,,,.,r,.r, represents the vield i, 1611. plant popuhtion and yieldno,,,p.p represents yield in nornral pl:rnt popularion] rvas calculated from plot vields. The follorvinE! gro\\.th dynarnic parameters for the lorv plant popr"rlation rvere also determined: TDM per pl:rnt. BDM per plant, Lrnd BDMPART. Because these three factors ri. e re srnrpled only for the lorv plant popr,rlation, experinrental desiqn tbr chese factors and relative vield rvas a randomized conlplere block u'rrh 2 yr and four replications as random factors and cultl'ars tked. Data rvere based on random sanrpies of four plants for each 1os' plant population plot sampled shortl,v after R7. Samples n'ere sepirrated into pods, ruain stenrs. :rnd branches, oven driecl .rt 60oC to constant rveight, rtnd then rveighed. Total drv ltlarrer per plant was the average rveight for the sum of ali three planr parts. Branch dry matter per plant rvas the average r.veight for the branch stems only .,vhile BDMPART r.vas the average value for BDM divided by TDM (nultrplied by 100 to percenra€te). After shelling, seed slze (g per 100 seed), r.vas deternrined on a 300 seed sample. Because of rnaturitv differences anlong cultivars, TDM per plant, BDM per plant, and BDMPART rvere normalized by dividing each by the number of days from emergence ro R5 (perioci for vegetative TDM and BDM developnlenr [Bo2rrd and Settinri, 19tt6; Egli end Leggett, 1973]). Data r,vere also taken on enlergence date, days to R5, and days to R7 according to methods described in Fehr and Caviness (1977).Datafor relative yield, normalized TDM per planr, normalizecl BDM per plant, and norm:rlized BDMPART ."vere :rnalyzed
1112
LSMEANS using
< 0.05). Regression analyses for relative yreld on nomralized TDM per plant, norrnalized BDM per plant, and Tlrkey's test (P
nonnalized BDMPART r.vere done rvithin each year using SAS regression (PROC MIXED) in which linear, qr-r:idr:rtic, and cubic conponents were successively tested for significance and inciuded residual sum of squares r,vas significantl1, reduced (P
