Euphytica 104: 67–72, 1998.© 1998Kluwer Academic Publishers. Printed in the Netherlands.

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Continued response through seven cycles of recurrent selection for grainyield in oat (Avena sativaL.)

David L. De Koeyer1 & Deon D. Stuthman21 Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6 Canada;2 Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108 U.S.A.

Received 20 April 1998; accepted 21 June 1998

Key words: Avena sativaL., combining ability, grain yield, oat, and recurrent selection

Summary

Long-term selection experiments provide germplasm to study the effects of selection in a closed population.Recurrent selection to enhance grain yield in oat has been ongoing at the University of Minnesota since 1968.The objectives of this study were: (i) estimate the GCA and SCA effects for three agronomic traits in the seventhcycle of selection, (ii) assess the effect of the current methods of selection on parental contribution and unselectedtraits, and (iii) determine the direct and indirect responses to seven cycles of recurrent selection for grain yield.Progeny of the Cycle 6 parents and parents for Cycles 0 through 7 were grown in two separate tests. Grain yield,heading date and plant height were evaluated in each test. Grain yield was increased by 21.7% after seven cycles ofselection. Evaluation of Cycle 6 progeny showed that GCA effects were significant for all three traits studied, andSCA effects were significant only for grain yield. Four Cycle 6 parents did not have any progeny selected as Cycle7 parents. Results from this study indicate that long term recurrent selection has continued to increase grain yield.Alternative selection strategies may be necessary to maintain the genetic variability in this population, particularlywhen improvement of secondary traits is required.

Abbreviations:GCA – general combining ability; SCA – specific combining ability

Introduction

Various traits in self-pollinated crops have been im-proved using recurrent selection procedures (Carver &Bruns, 1993). Most recurrent selection studies in auto-gamous crops have been short-term in nature, encom-passing less than five cycles of selection (Goldringer& Brabant, 1993). Short-term recurrent selection pro-grams for improved yield have been successful withoats (Avena sativaL.) and other autogamous crops.Using a method that allows completion of one cy-cle of recurrent selection per year, Frey et al. (1988)obtained gains of 5.4% per cycle after three cyclesof recurrent selection for grain yield in an oat pop-ulation. Three cycles of S1 recurrent selection wereused by Kenworthy & Brim (1979) to enhance seedyield in soybeans (Glycine max(L.) Merr.) by 16%.Significant short-term yield improvements using re-

current selection in soybeans were also reported bySumarno & Fehr (1982), and Piper & Fehr (1987).In barley (Hordeum vulgareL.), grain yield increasesper cycle ranged between 7.8% (Parlevliet & van Om-meren, 1988) and 14.7% (Marocco et al., 1992) overtwo cycles of selection. Olmedo-Arcega et al. (1995)reported a 12.5% improvement in grain yield follow-ing two cycles of recurrent selection in durum wheat(Triticum turgidumL. var. durum). The maximumreported number of cycles of selection for enhancedgrain yield in a self-pollinated crop is five for oat(Pomeranke & Stuthman, 1992) and soybean (Rose etal., 1992).

A recurrent selection program for enhanced grainyield in oat was initiated at the University of Min-nesota in 1968 (Stuthman & Stucker, 1975). Thirtyyears of recurrent selection represents a substantial,long-term research effort. Currently, this program is in

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the eighth cycle of selection. Grain yield was increasedapproximately 6% after two cycles of recurrent selec-tion (Radtke, 1981). After three cycles of selection,estimates of grain yield gains were 11.5 and 13.5%(Payne et al., 1986; Bregitzer et al., 1987, respec-tively). The estimate of yield enhancement over fivecycles was 7.9% per cycle (Pomeranke & Stuthman,1992). Studying this long-term selection program canlead to a better understanding of the effects of selec-tion in a closed population. From a plant breeder’sperspective, germplasm derived from this populationlikely contains many favorable alleles that could en-hance yield in more elite materials. From a geneticist’spoint of view, this material can be examined, usingDNA markers, to obtain a better understanding ofthe recurrent selection process and to localize genescontrolling agronomically important traits.

Selection programs that emphasize single traitsoften indirectly alter other plant characteristics. Cor-related changes associated with recurrent selection forgrain yield have been reported in oat and other cropspecies (Goldringer & Brabant, 1993). After two cy-cles of recurrent selection for improved grain yieldin oat at the University of Minnesota, Radtke (1981)reported later heading dates, increased plant height,and increased seed weight. There was an 8% increasein kernel number, a 3% increase in kernel weight andan almost two-day delay in heading and maturity afterthree cycles of selection (Payne et al., 1986). Ker-nel area, perimeter, length and width, measured usingdigital image analysis, also increased after five cy-cles of selection in this population (De Koeyer et al.,1993). Modifications to this closed recurrent selectionprogram were studied by Sosa-Dominguez & Stuth-man (1995) to attempt to correct for the changes inunselected traits.

There has not been a detailed analysis of the pedi-grees of progeny for the University of Minnesotaoat recurrent selection program or for other recur-rent selection programs. This type of analysis couldbe used to assess the current selection methodology,and modifications could be made to broaden the ge-netic diversity within the program and limit changesto unselected traits. Stuthman & Stucker (1975) stud-ied combining ability (GCA and SCA) in the progenyused for the original cycle of selection. Studying theprogeny of the seventh cycle of selection will give anindication of the changes in the amount and type ofgenetic variance remaining in the Minnesota recurrentselection program.

Pomeranke & Stuthman (1992) reported changesin agronomic traits that occurred during the first fivecycles of the Minnesota recurrent selection program.This paper extends the agronomic evaluation of therecurrent selection population to the Cycle 7 parentsand represents the longest reported study to date in-volving recurrent selection in a self-pollinating crop.Results from this study provide a basis for comparisonwith pedigree and DNA-marker data described in DeKoeyer (1996).

The objectives of this study were to: 1) estimatethe GCA and SCA effects for three agronomic traits inthe seventh cycle of selection, 2) assess the effect ofthe current methods of selection on parental contribu-tion and unselected traits, and 3) determine the directand indirect responses to seven cycles of recurrentselection for grain yield in oat.

Materials and methods

Cycle 6 progeny evaluation

Twenty-one recurrent selection Cycle 6 parents wereintercrossed in a circulant partial diallel. Each parentalline was crossed with six others for a total of 63crosses. Single-seed descent was used to advance 15-25 lines from each cross to the F4 generation. Seedfrom individual F4 plants was increased in 1.5 m rowsand 10 lines were randomly chosen per cross for eval-uation in the F4.6 generation. The genotypes includedin this study were 630 F4.6 lines, 21 Cycle 6 parents,and 6 check genotypes (‘Braun’, ‘Dane’, IL83-8037,‘Milton’, ‘Ogle’, and ‘Troy’). These lines were grownin hill plots (Frey, 1965) at St. Paul, MN, in 1994. Soiltype was a Waukegan silt loam (fine-silty over sandyor sandy skeletal, mixed, mesic Typic Hapludoll).

Hill plots with 30 seeds per hill were arranged in a30 cm grid using a randomized complete block designwith four replicates. Grain yield (g hill−1) was eval-uated in all four replicates, however, heading date (dafter June 1), and plant height (cm) were measured ontwo replicates.

Analysis of variance was computed using the SAS(SAS Institute, 1985) General Linear Model (GLM)procedure. Both crosses and lines within crosses wereconsidered random. Mean squares for GCA and SCAwere obtained by regressing cross means for eachtrait onto a matrix of indicator variables. This regres-sion also provided estimates for the general combiningability effects for each of the 21 Cycle 6 parents. The

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variance components associated with crosses, GCA,and SCA were determined using the expected meanssquares for the analysis of variance. Standard errors ofthe variance components were determined using themethods of Anderson & Bancroft (1952). A variancecomponent was considered significantly different fromzero when it was twice as large as the standard error.

Correlations were computed among the three agro-nomic traits for parental, progeny, and half-sibprogeny performance, and for GCA effects. For eachtrait, correlations were also calculated among parentalperformance, GCA effects, and the relative contribu-tion of Cycle 6 parents to Cycle 7 parents. Relativecontributions to Cycle 7 parents were determined byexamining the pedigrees and by using the assumptionthat each parent contributed equally to the progeny ofa cross.

Cycle 7 parent selection

Selection of the Cycle 7 parents from the progenyof the Cycle 6 parents was based on 1994 data only.The twenty-one highest yielding crosses were selectedand the most agronomically desirable line within eachcross was chosen to be a parent for Cycle 7. Earlierheading date and shorter plant height were empha-sized during within-cross selection. These selectedlines have since been intercrossed using the proce-dures described above for the Cycle 6 parents. Progenyare currently being advanced for testing.

Evaluation of parents for cycles 0 through 7

One hundred and thirty-eight parents (12 from Cycle0, and 21 from each of Cycles 1 through 6) and fivecheck cultivars (Dane, Jerry, Milton, Jim, and Troy)were planted in hill plots at Rosemount and St. Paul,MN, in 1994 and 1995. Twenty-one Cycle 7 parentswere grown at St. Paul in 1994, and at both locations in1995. The parents used in this study were F4-derivedlines in at least the F6 generation. A randomized com-plete block design with four replicates was used ineach environment. Grain yield (g hill−1) was evaluatedusing four replicates, and heading date (d after June1) and plant height (cm) were determined from tworeplicates in each environment.

Analysis of variance was computed using the SASGLM procedure. A mixed model was assumed, withcycles and parents within cycles considered fixed, andlocations and years random. Cycle means were cal-culated for each trait and linear regression, weightedby the number of parents in each cycle, was used to

Table 1. Estimates of variance components and their stan-dard errors for crosses, GCA, and SCA from 630 F4.6progeny of the 21 parent partial diallel grown at St. Paul,MN, in 1994

Trait σ2Cross σ2

GCA σ2SCA

Yield 10.43± 1.25 1.93± 0.71 2.54± 0.93

Heading 0.78± 0.19 0.40± 0.14 0.06± 0.07

Height 8.33± 1.96 4.28± 1.49 0.71± 0.72

determine the response per cycle. The linear responsewas tested for statistical significance using a t-testof the regression coefficients. Phenotypic correlationswere calculated among the traits measured. Dunnett’stest (Steel and Torrie, 1980) was used to compare therecurrent selection material with the check cultivars.

Results and discussion

Cycle 6 progeny evaluation

Differences among crosses were detected for grainyield, heading date, and plant height. Variance com-ponents for crosses (σ2

Cross) and GCA (σ2GCA) were

significant for all traits (Table 1). The estimate ofσ2

SCA for grain yield also was significant. A signifi-cantσ2

GCA term suggests that additive genetic effectsare important in these progeny. Additive x additiveepistasis for grain yield is likely present in this popula-tion, due to the significantσ2

SCA term. The variancecomponents for grain yield in this study were simi-lar to those reported by Stuthman and Stucker (1972).These authors obtained single-year estimates of 2.34and 1.56 forσ2

GCA and estimates of 2.72 and 0.93for σ2

SCA using Cycle 0 progeny. Comparison of thetwo studies indicates that there has been little changein the level and type of genetic variance for grain yieldpresent in the Minnesota recurrent selection programafter seven cycles of selection.

Moderate correlations (P< 0.01) between headingdate and plant height were detected for Cycle 6 par-ent performance, progeny performance, and for GCAeffects of the Cycle 6 parents (Table 2). Bahri (1992)reported similar correlations between heading date andplant height for Cycle 5 parents and progeny, indicat-ing that there is a tendency for taller lines to also belater in heading in this recurrent selection population.

Parental performance was not correlated (P>0.05) with GCA effects for any trait. These results

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Table 2. Correlations among agronomic traits for 630 F4.6 progeny, 21 Cycle 6 parents, half-sib progeny, andGCA effects determined at St. Paul, MN, in 1994

Trait Progeny Parent Half-sib GCA

Yield Height Yield Height Yield Height Yield Height

Height 0.15 −0.04 0.42 0.30

Heading −0.00 0.43∗∗ 0.06 0.49∗∗ −0.17 0.32 −0.12 0.57∗∗

∗∗ Significant at the 0.01 probability level.

are in contrast to those reported by Bahri (1992), whoreported a strong, positive association between thesetwo parameters for grain yield, heading date, and plantheight in the Cycle 5 parents. An explanation for thesediffering results may be the fact that the years of se-lection and testing of the Cycle 6 parents were quitedifferent. Cycle 6 parents were selected in 1990, ayear with excessive rain and wind that produced severelodging. These parents were also selected using datafrom two locations, St. Paul, and Rosemount, MN.Testing of the Cycle 6 parents in this part of the studywas only at St. Paul in 1994, which had a favorablegrowing season for oat with little lodging.

Selection of cycle 7 parents

Twenty-one lines were selected as Cycle 7 parents.The highest yielding crosses were first selected andthen the most agronomically desirable line was se-lected from each cross. GCA effects for grain yieldwere a good indicator (r = 0.89, P< 0.01) of the rel-ative contribution of a Cycle 6 parent to the Cycle 7parents, confirming the importance of additive geneticeffects.

It is apparent from the pedigrees that there is anunequal contribution by each of the Cycle 6 parentsto the Cycle 7 parents (Table 3). One parent (6–15)contributed to 11.9% of the pedigree base of Cycle7 parents. Eight parents accounted for 64.2% of thegermplasm base of Cycle 7, whereas, seven other par-ents accounted for only 7.1%. Four parents (6–8, 6–10,6–16, and 6–20) did not contribute any progeny toCycle 7. Examining the GCA effects for these fourparents indicated that some of them may possess desir-able alleles for plant height and heading date. Parents6–8 and 6–10 had GCA effects of−2.46 and−3.41for plant height, respectively. Parents 6–8 and 6–16had GCA effects of−0.54 and−0.49 for heading date,respectively. Parent 6–20 did not possess any desirableGCA effects. It is important to maintain as much of

Table 3. Number of half-sib progeny of Cycle 6 par-ents selected to be Cycle 7 parents, and the relativecontributions of each Cycle 6 parent to all Cycle 7parents

Cycle 6 No. of Relative

Parent half-sib contribution

progeny to Cycle 7

selected %

1 3 7.14

2 2 4.76

3 2 4.76

4 2 4.76

5 3 7.14

6 3 7.14

7 1 2.38

8 0 0.00

9 2 4.76

10 0 0.00

11 4 9.52

12 3 7.14

13 3 7.14

14 1 2.38

15 5 11.90

16 0 0.00

17 2 4.76

18 1 2.38

19 3 7.14

20 0 0.00

21 2 4.76

the genetic variability as possible in this population toprovide for continued progress.

A goal of recurrent selection is to maintain geneticvariability within a population; therefore, considera-tion must be given to an alternative selection strategyto meet this objective. One alternative in this popu-lation would be the selection of the highest yieldinghalf-sib cross for each parent followed by within-crossselection for the most desirable lines. Using this al-

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Table 4. Means for agronomic traits of cycle parentsand checks grown in four Minnesota environments

Cycle or Grain Heading Plant

checks yield date height

g hill−1 d after June 1 cm

0 22.6∗ 23.4∗ 106.5∗1 23.6∗ 22.6∗ 107.1∗2 23.2∗ 22.0 105.1∗3 23.9∗ 23.6∗ 111.4∗4 24.3∗ 22.6∗ 108.1∗5 25.2∗ 22.3∗ 107.7∗6 23.8∗ 22.8∗ 108.2∗7a 27.5∗ 22.4∗ 111.6∗

Checks 20.9 21.8 94.6

∗ Significantly different from the mean of checks atthe 0.05 probability level.a Grown in three environments.

ternate approach for Cycle 7 parent selection, therewould have been only four lines differing from thecurrent strategy. All of the Cycle 6 parental lineswould have contributed to Cycle 7 to some degreeand some of their desirable alleles could still be in thepopulation.

Evaluation of parents for cycles 0 through 7

Combined location analysis indicated that cycles dif-fered (P< 0.05) for grain yield, heading date, andplant height. A cycle× year interaction was detectedfor grain yield. This interaction may have resultedfrom differences in growing conditions between thetwo years of testing, with 1994 being a more favorableyear for oat growth. Lodging was severe at St. Paul in1995, and yields were quite low at Rosemount in 1995due to moisture stress during the grain filling period.Pomeranke & Stuthman (1992) also reported that yearof evaluation was a more important factor than loca-tions for producing cycle× environment interactionsin this population.

Cycle means for the agronomic traits included inthis study are presented in Table 4. Regression analy-sis showed that the slope for grain yield was greaterthan 0 (Table 5). Grain yield was increased by 21.7%after seven cycles of recurrent selection. This resultindicates that selection response has continued overthe long duration of this program. The value for grainyield improvement after seven cycles is lower than thatobtained by Pomeranke & Stuthman (1992) follow-ing five cycles of recurrent selection. However, on a

Table 5. Selection response per cycle for agronomictraits measured in four Minnesota environments

Trait Slopea Standard % Change

error cycle−1b

Grain yield 0.49∗ 0.15 2.17

(g hill−1)

Heading date −0.08 0.08 0.33

(d after June 1)

Plant height 0.55 0.31 0.52

(cm)

∗ Slope greater than 0 at the 0.05 probability level.a Slope determined by weighted linear regression of cy-cle mean on cycle number.b % change cycle−1 calculated as (slope/mean of Cycle0) times 100.

per cycle basis, the response to selection is compara-ble to estimates obtained by Radtke (1981) and Payneet al. (1986) after two and three cycles, respectively.There were no significant linear responses for head-ing date and plant height (Table 5). However, plantheight for Cycle 7 parents was significantly greater (P< 0.05) than Cycle 0 parents (Table 4). Heading datewas reduced (P< 0.05) in Cycle 7 relative to Cycle0. Apparently, attempts to reduce plant height in thispopulation after Cycle 3 have not been as successfulas attempts to maintain or reduce heading date duringthe same time (Table 4).

Parents from all cycles of recurrent selection werehigher yielding and taller than the check cultivars (Ta-ble 4). With the exception of Cycle 2 parents, parentsof each cycle also were later to head than the checks.The relative tallness of the recurrent selection mater-ial has limited its usefulness for varietal development.This material is more prone to lodging, particularlyunder high moisture and fertility conditions.

There is a moderate correlation between plantheight and grain yield for the recurrent selection par-ents (r = 0.54, P< 0.01). One explanation for this maybe the selection system which involves the use of hillplots. Due to the close proximity of hill plots, inter-plot competition may provide a selective advantage totaller genotypes. Previous research by Pomeranke &Stuthman (1992) and De Koeyer et al. (1993) has in-dicated that measurements of selection responses aresimilar in row and hill plots. Other selection systems,such as the use of row plots or the use of block-ing methods that account for the variability in plantheight may promote the selection of high yielding, yetshorter lines. The incorporation of elite material into

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the recurrent selection program has corrected some ofthe agronomic deficiencies; however, the ‘opened’ re-current selection population is still significantly tallerthan check cultivars (Sosa-Dominguez & Stuthman,1995).

In conclusion, recurrent selection to increase grainyield in oat has continued to be very effective overseven cycles. The estimated GCA and SCA variancecomponents for grain yield in the seventh cycle of se-lection were similar to those obtained in the first cycleof selection reported by Stuthman & Stucker (1975).These results indicate that there has not been a signif-icant change in the level of genetic variance over theseven cycles of selection. The requirement to maintainthe genetic variability and improve unselected traits inthis population suggests that alternative selection andevaluation systems for this program be considered.

Acknowledgement

The financial support of The Quaker Oats Company isgratefully acknowledged.

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