Euphytica 133: 209–218, 2003.© 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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Heritability of Coffea canephora yield estimated from several matingdesigns ∗

Christophe Montagnon1,∗, Thierry Leroy1, Christian Cilas1 & Andre Charrier2

1Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement (CIRAD), TA80/PS3, 34398 Montpellier, France; 2Ecole Nationale Superieure Agronomique – Institut National deRecherche Agronomique, 2 place Viala 34000 Montpellier, France; (∗author for correspondence, e-mail:christophe.montagnon@cirad.fr)

Received 19 February 2001; accepted 15 May 2003

Key words: genetic gain, genetic parameters, hybrid selection, inbreeding coefficient, ortet selection

Summary

Eleven mating designs, 6 top-crosses and 5 North Carolina II, were used to estimate narrow sense, broad sense andwithin-cross heritability of Coffea canephora yield in Côte d’Ivoire. The objective was to predict achievable geneticgains according to different breeding strategies. Narrow sense, broad sense, family and within-cross heritabilitieswere 0.32, 0.43, 0.83 and 0.22, on average respectively. The percentage of additivity was high (81% on average). Adegree of variation was nevertheless observed for estimates over trials. This was found to be mainly due to parentsampling in each trial. By theoretical computation, the minimum number of parents required to obtain optimumprecision was found to be around 30. Predicted genetic gains for yield through clonal selection at a selection levelof 1% ranged from 7 to 28% over the best hybrid in each trial, suggesting thus clones still interesting for breeders.The consequences for coffee breeding are discussed.

Introduction

The coffee tree Coffea canephora is a strict allogam-ous species with a large structured genetic diversity.Since 1984, C. canephora breeding in Côte d’Ivoirehas been carried out in a reciprocal recurrent selection(RRS) programme based on two genetic groups: theGuinean and Congolese groups (Berthaud, 1986). TheCongolese accessions have more recently been shownto be subdivided into four groups: SG1, SG2, B andC (Montagnon et al., 1992; Dussert et al., 1999). Theprediction of genetic gains, and subsequent appropri-ate adaptations of the RRS programme, requires goodknowledge of yield heritability. It could particularlyhelp in deciding between clone and hybrid selection.Hybrids are easier and less expensive to produce fordissemination (Roux & Duris, 1995), but clones yield

∗ This work is the result of a cooperation between the CentreNational de Recherche Agronomique of Côte d’Ivoire (CNRA)and the Centre International de Recherche Agronomique pour leDeveloppement – Cultures perennes (CIRAD-CP).

50 to 70% more than hybrids created before RRS star-ted (Capot, 1977; Charmetant et al., 1990). In theseventies and eighties several countries such as Côted’Ivoire have thus chosen to distribute clones to grow-ers. Through the RRS programme, some between-group hybrids were found to produce as much asclones (Leroy et al., 1997). However, as C. canephorais strictly cross-fertilizing (Berthaud, 1980) and thusparents cannot be fully homozygous, it can be arguedthat outstanding trees within those between-group hy-brids could still provide genetic gains through cloneselection. It actually depends on within-cross heritab-ility and within-cross phenotypic variance. Note thathomozygous genotypes of C. canephora can be ob-tained through haplodiploidisation but their low vigourdoes not practically allow yet to use them as parentsfor hybrids (Lashermes et al., 1994b).

The heritability of C. canephora yield was ex-plored by Bouharmont et al. (1986) who found that ad-ditivity was predominant for yield transmission. Nev-ertheless, their planting material was only composed

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of Congolese parents, whereas RRS involves between-group crosses between Guinean and Congolese par-ents. For such crosses, Leroy et al. (1994) estimatednarrow sense heritability to be 0.38 and broad senseheritability to be 0.75, corresponding thus to a smal-ler part of additivity. The authors pointed out that thenumber of parents involved in their mating designswas limited. Furthermore, the inbreeding coefficient(F) of C. canephora was traditionnally assumed tobe 0, as this species is strictly cross-fertilizing. How-ever, most Guinean C. canephora parents used in RRS(Leroy et al., 1993) and in mating designs are wildor semi-wild, from different forest populations (Ber-thaud, 1986). In such cases, special attention has to bepaid to population genetics parameters (Mitchell-Olds& Rutledge, 1986). Indeed, recent RFLP studies haveshown that the inbreeding coefficient of the geneticgroups involved so far in mating designs aiming at theestimation of genetic parameters, i.e. the CongoleseSG2 and Guinean groups, were 0.00 and 0.26 respect-ively (Montagnon, 2000). The correct value of F hadthus to be integrated in the genetic models as definedby Cocherham (1963).

In our work, 11 mating designs, top-crosses andNorth Carolina II, involving 9 to 34 parents, were usedto estimate narrow sense, broad sense and within-crossheritability. The objective is to predict achievable ge-netic gains according to different breeding strategies.In particular, it will help deciding whether clonesshould be selected within between-group hybrids.

Material and methods

Planting material (Table 1)

Two reference populations were used in our study.They are described in details by Montagnon (2000).The first population was composed of wild genotypes,belonging to the Guinean genetic group, surveyed inCôte d’Ivoire in the eighties and the second populationwas composed of Congolese SG2 genotypes resultingfrom several generations of intercrossing of wild treessurveyed in the Democratic Republic of Congo in thethirties. Thanks to RFLP markers, it was checked thatthese two populations were in linkage equilibrium andtheir inbreeding coefficient was estimated to 0.26 and0.00 respectively (Montagnon, 2000).

Six top-crosses were studied. They were all com-posed of progenies resulting from the crossing ofrandomly chosen tested Guinean parents with a tester.

The choice of Guinean parents was made independ-ently of the forest population they originated from andthus in each mating design, Guinean parents were asample of the whole Guinean population. Two top-crosses (1 and 2) involved within-group crosses, as thetester also belonged to the Guinean group. The otherfour top-crosses were composed of between-group(BG) crosses, as the tester belonged to the Congolesegroups.

Five North Carolina II (NCII) designs were stud-ied. They only involved BG progenies resulting fromthe crossing of randomly chosen tested parents with 2or 3 testers. In 4 trials (7 to 10), Guinean parents werecrossed with Congolese testers. In the remaining trial(11), the reverse was true. Three Congolese testers (c1,c2 and c3) and two Guinean testers (g1 and g2) wereused as indicated in Table 1. Each Congolese tested ortester genotype belonged to group SG2 (Montagnon etal., 1992).

Three hybrid trials (12, 13 and 14), without anymating design, were used together with trials 3 to11, to estimate genetic gains for yield. The hybridsin these three trials were obtained with parents selec-ted after the first reciprocal recurrent selection cycle(Montagnon, 2000).

All trials were planted between 1986 and 1994in the same research station located at Divo in Côted’Ivoire. The size of progenies ranged from 20 to100 (Table 1). The statistical design was always com-pletely randomized single-tree plots. In all trials, treeswere two-stemmed with free growth at a spacing of3 metres between rows and 1.5 metres between treesalong a row, corresponding to a density of 2222 plantsper hectare. In each trial, the common control clone461 was represented by 30 to 100 repetitions and en-abled comparisons between trials. This clone is thecurrently highest yielding clone distributed in Côted’Ivoire.

Methods

Yield was estimated through the weight of fresh ber-ries per tree cumulated over the first four consecutiveharvest years.

In our study, genetic variances were estimatedfor different genetic situations: i) within the Guineanreference population (Trials 1 and 2), ii) referenceGuinean population when crossed with one or moreCongolese testers (Trials 3 to 10), and iii) referenceCongolese population when crossed with Guineantesters (Trial 11). For simplicity, we present hereafter

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Table 1. Description of the mating designs used for the estimation of Coffeacanephora yield heritability

Mating Number of mean

Design Trial Cross type1 Tester(s) tested parents progeny size

1 g g g1 27 54

Top 2 g g g1 20 54

3 c g c2 24 100

Cross 4 c g c1 20 54

5 c g c2 34 40

6 c g c3 28 20

7 c g c1-c2 18 54

North 8 c g c1-c2-c3 9 44

9 c g c2-c3 11 40

Carolina II 10 c g c1-c2 10 41

11 g c g1-g2 5 100

12 48

No mating 13 Between-group hybrids 47

Design 14 30

1 The genetic group of testers (first) and tested parents (second) are specified: c =Congolese group and g = Guinean group.

the statistical and genetic models for the referenceGuinean population when crossed with one or moreCongolese testers, which is the main situation. Nota-tions and subscribes should be adapted for the othersituations. The Guinean and Congolese inbreedingcoefficients were kept as Fg and Fc to make the equa-tions readable. In calculation, they were replaced bytheir estimated value of 0.26 and 0.00 (Montagnon,2000). We also assumed the absence of epistasis ingenetic models.

Statistical model

The statistical model is described for the top-crossesand North Carolina II in Table 2. The effect of test-ers was fixed whereas the effect of tested parents wasconsidered as random. Thus, the NCII model wasmixed. The effect of tested parents is dependant onthe specific tester or testers of each design. The ef-fect of interaction is also dependant on the specifictesters used. For this reason, the notation τ was in-troduced for the set of specific testers used in eachtrial: τ corresponds to one single tester in the caseof top-crosses and to several testers in the case ofNCII models. There should be no confusion betweenτ σ 2

g and σ 2g i.e. between the variance of the random

effect of Guinean tested parents when crossed withthe specific set of testers τ and the variance of therandom effect of Guinean parents when crossed withthe reciprocal population in general. Variance com-

ponents were estimated from mean square values afterANOVA (Searle, 1971) by the Restricted Maximum-Likelihood Method (REML), using the SAS SoftwareVarcomp procedure (SAS, 1989).

The normality of both raw data and residuals, aswell as the homogeneity of variances, were checked.In all trials, Papadakis (1937) correction was appliedin order to take micro-environmental variation intoaccount more effectively.

model Genetic model

As precised for the statistical model, the additiveand dominance genetic variances and consequentlythe heritabilities are estimated and valuable only forthe testers used in each design. The same distinctionshould thus be made between τ σ 2

Ag and σ 2Ag or between

τ σ 2Dgc and σ 2

Dgc. The general notations of heritabilitieswere kept for simplicity but should be considered foreach given τ . In the case of the top-cross, the additiveτ σ 2

Ag and the dominant τ σ 2Dgc parts of the genetic vari-

ance can not be separated and only a majorant h2ns of

narrow sense heritability can thus be estimated as:

h2ns = 4

1 + Fg

τσ 2g.

1

σ 2P

where σ 2P is the estimated phenotypic variance assum-

ing no dominance (= 2.τσ 2g + σ 2).

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Table 2. ANOVA model, observed and expected mean squares for top-cross and North Carolina II (mixed effects) mating designs (afterDagnelie, 1970)

Mating MODEL1 ANOVA

Guinean Congolese Interaction

Design Error Tested parents Testers Parents*testers

Observed

North Mean Square MSE MSg MSc MScg

Carolina II (NCII) Yijk = µ + τ gi + aj + τ cgij + Eijk Expected

Mixed effects Mean Square σ 2 σ 2 + nτ σ 2cg + ntτ σ 2

g σ 2 + nτ σ 2cg + mn/(t-1)�ja

2j σ 2 + nτ σ 2

cg

Observed

Top-Cross Mean Square MSE MSg

Yik = µ + τ gi + Eik Expected

Mean Square σ 2 σ 2 +τ σ 2g

1 Model is given here for Guinean genotypes tested with one or more Congolese testers. Notations should be adapted for other situations.Yik Yield of individal k from the progeny of tested parent i (top-cross)

Yijk Yield of individal k from the progeny of tested parent i crossed with tester j (NCII)

µ Overall trial mean

m and t Number of tested parents and testers, respectively

n Progeny size

τ Set of specific tester(s) of the design: one tester in top-crosses and several in NCIIτ gi Effect of tested parent i when crossed with τ , random effect of variance τ σ 2

gτ gcij Effect of the interaction between tested parent i and tester j when crossed with τ (several testers), random effects

of variance τ σ 2cg

aj Effect of testeur j, fixed effect: �jaj = 0

Eik and Eijk Error term, random effect of variance σ 2.

In the case of the mixed model of North CarolinaII design, τ σ 2

g and τ σ 2cg were derived from Cockerham

(1963) as:

τ σ 2g = 1 + Fg

4· τ σ 2

Ag

and

τ σ 2cg = (1 + Fg)(1 + Fc)

4· τ σ 2

Dcg

τ σ 2Ag and τ σ 2

Dcg lead to the estimation of narrow andbroad sense heritabilities with:

h2ns =

τ σ 2Ag

σ 2P

and h2bs =

τ σ 2Ag + τ σ 2

Dcg

σ 2P

where σ 2P is the estimated phenotypic variance (=σ 2

g +

σ 2cg + σ 2).

Furthermore, within-cross heritability is expressedas:

h2wc =

1−Fg

2τ σ 2

Ag + 4−(1+Fg)(1+Fc)

4τ σ 2

Dcg

σ 2

Note that the estimation of broad sense and within-cross heritabilities requires the assumption thatGuinean and Congolese additive genetic variances areequal.

In each progeny trial, a family mean heritability isestimated as (Gallais, 1990):

h2f = σ 2

f

σ 2f + σ 2

n

where n is the harmonic mean of progenies size.σ 2

f is the estimated variance of the family effect.σ 2

f = σ 2g(c) in the top-cross. In NCII, progenies were

considered as the single source of variation, withouttaking into account the tester or tested parent level.

The confidence interval at the 5% level of eachestimation was calculated by the Jackknife method asdescribed by Baradat et al. (1995) with 20 sub-samplesby trial, i.e. representing each 5% of the total size ofthe trial.

Influence of the number of parents and size ofprogenies on the estimation of heritabilityExpressing data as a percentage of the clonal control461 (T%) over several top-crosses, we could observethe distribution of the parental effect of 100 Guineangenotypes all tested with the same Congolese tester c2(see Montagnon, 2000 for details). The standard errorof the parental effect σg could thus be estimated at

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14 T%. Furthermore, residual (= within-cross) stand-ard deviation σ averaged over the same top-crosses,was found to reach 39 T%. From these values, topcrosses could hence be simulated through the variableZ where i) the mean of crosses between each parenti and c2 was Zi. = σg.rannor, rannor being a randomvalue following the standard normal distribution andii) repetitions for each crosses between parent i andc2 were Zik = Zi. + σ .rannor. For varying numberof tested parents (5 to 70 by 5) and varying progenysize (20, 40 and 100), 1000 testcrosses, ie iterations,were computed. For each number of parents / progenysize pair, heritability and its confidence interval wererecorded.

Estimation of the genetic gainsUsing the estimation of h2

f and h2wc from the analysis of

the mating designs, we could predict the genetic gainsthrough hybrid and clonal selection in our trials.

Hybrid selection: Yield of each hybrid i in a trialwas predicted by:

Yi = µ + h2f .(Yi. − µ)

whereµ was the overall hybrid meanYi. was the observed mean yield of hybrid i.

The genetic gain through hybrid selection was es-timated for the selection of the best hybrid (hybrid h)in each trial as a percentage of the control clone 461:

�Gh% = 100.Yh − Y461

Y461

Note that the observed mean of clone 461 was con-sidered because the heritability at the clonal meanlevel with more than 30 trees per clone was close toone, as can be deducted from the individual broadsense heritability estimated in the results of the presentstudy.

Clonal selection: Yield of each tree ij (genotype jfrom hybrid i) in each trial was predicted accordingto the combined family/individual selection (Falconer,1989):

Yij = µ + h2f .(Yi. − µ) + h2

wc.(Yij − Yi.)

whereYij was the observed yield of tree ij.

The best 1% of trees for predicted yield were selec-ted. Their mean predicted value was Ycl. The geneticgain through clonal selection was expressed either asa percentage of the control clone (�G1cl%) or as apercentage of the best hybrid in the trial (�G2cl%):

�G1cl% = 100.Ycl − Y461

Y461

�G2cl% = 100.Ycl − Yh

Yh

Results

Heritability estimates

Narrow sense (h2ns), broad sense (h2

bs) and within-cross(h2

wc) heritability, averaged over all the trials involvingmating desings (Table 3), were 0.32, 0.43 and 0.22respectively. However, variations for heritability es-timates were observed among trials (Table 3): h2

nsranged from 0.21 to 0.45, h2

bs from 0.26 to 0.59 andh2

wc from 0.13 to 0.33. The percentage of additivitywas high on average (81%) and ranged from 68% to97% (Table 3). The heritability of family means (h2

f )averaged 0.83 and ranged from 0.66 to 0.90 (Table 3).

No obvious differences could be detected betweenheritabilities estimated from within-Guinean crosses(trials 1 and 2), Congolese parents crossed withGuinean testers (trial 11) and Guinean parents crossedwith Congolese testers (trials 3 to 10).

The confidence interval was quite large for mostestimations, except for h2

f (Table 3). The precision waslower for mating designs with a small progeny size(trial 6) or whose number of tested parents was aroundor below 10 (trials 9, 10 and 11). Trial 8, involvingonly 9 tested parents, seemed to benefit from the thirdtester to maintain acceptable precision.

The variation in heritability estimates among trialsmay be partly explained by the rather low precisionfound for each of them. Other factors were sought,however, to interpret those variations: difference intesters, in mating design, in soil fertility estimatedfrom the clonal control yield, overall progeny yield,estimated error variance and estimated parental effectvariance. From all these factors, only the estimatedparental effect variance was significantly correlatedwith heritability estimates (data not shown). This in-fluence was studied by computing data based on theobserved residual and parental effect standard errorexpressed as a percentage of the clonal control (seeMaterial and Methods). From these observed values,an estimate of 0.34 was found for h2

ns. The confidenceinterval decreased as the number of parents increased(Figure 1). It seemed that at least 30 tested parentswere necessary to achieve optimum precision. How-ever, even if 70 tested parents were used, the lower

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Table 3. Narrow sense, broad sense, within-cross and family mean heritability (h2ns, h2

bs, h2wc and

h2f ) of Coffea canephora yield estimated in several mating designs. (between brackets = 1,96 ∗

standard error = semi-confidence interval at 0.05 level)

Trial h2ns h2

f h2bs h2

wc % Additivity

1 0.41 (0.24) 0.84 (0.12)

Top 2 0.32 (0.18) 0.81 (0.12)

3 0.21 (0.28) 0.87 (0.08)

Cross 4 0.21 (0.18) 0.77 (0.24)

5 0.41 (0.22) 0.86 (0.08)

6 0.29 (0.46) 0.66 (0.48)

North 7 0.32 (0.18) 0.88 (0.08) 0.46 (0.18) 0.24 (0.16) 70 (42)

8 0.25 (0.22) 0.80 (0.12) 0.29 (0.24) 0.13 (0.14) 86 (60)

Carolina II 9 0.40 (0.44) 0.90 (0.06) 0.59 (0.36) 0.33 (0.24) 68 (70)

10 0.45 (0.70) 0.89 (0.08) 0.53 (0.70) 0.25 (0.18) 85 (58)

11 0.25 (0.34) 0.80 (0.08) 0.26 (0.34) 0.14 (0.20) 97 (80)

Table 4. Estimated genetic gains for Coffea canephora yield through hybrid or clonal selection in NCII mating designs

Genetic gain as a percentage of

Nb of selected trees1 the control clone (461) the best hybrid

Trial (Clonal selection at a level of 1%) Best hybrid (�Gh%) Selected trees (�G1cl%) Selected trees (�G2cl%)

3 22 = 8 + 6 + 2(2) + 4(1) –35 –16 28

4 10 = 2(3) + 2+ 2(1) –35 –22 18

5 14 = 12 + 2(1) –30 –23 7

6 6 = 2(3) –48 –37 18

7 14 = 5 + 4 + 3 + 2(1) –29 –18 13

8 11 = 6 + 3 + 2(1) –16 –1 18

9 8 = 8 0 13 12

10 8 = 6 + 2(1) –20 –5 20

11 8 = 7 + 1 –7 5 14

12 24 = 21 + 3 25 35 8

13 10 = 10 3 11 8

14 9 = 8 + 1 46 70 16

1 x(y) means that in x different hybrids, y trees per hybrid were selected (if x = 1, only y is mentioned).For instance, in trial 3, 1 hybrid provided 8 trees, one other 6 tress, two others 2 trees and four others 1 single tree.

and upper limits of the confidence interval at the 0.05level were 0.22 and 0.46, still far from the mean 0.34.Progeny size had less influence on precision exceptwhen few parents were sampled. The estimates of h2

ns,corresponding to the eight trials involving Guineanparents crossed with Congolese testers, were posi-tioned in Figure 1 according to the number of testedparents in each trial. They were all within the limitsof the confidence interval. Parent sampling thus had agreat influence on heritability estimation, even whenmore than 20 parents were sampled. This influencemay explain why h2

ns estimated from the top-crosswere not higher than h2

ns estimated from NCII. Indeed,

the former is supposed to be a majorant of the lat-ter. The range of variation due to sampling error maytherefore overcome variation due to the assumptionof no dominance, at least when dominance is low, asobserved in our study.

Genetic gains

In trials 12 to 14 only, selection of the best hybrid andbest trees provided a positive genetic gain comparedto clone 461. In trial 14, the best hybrid provided agenetic gain for yield of 46% over clone 461.

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Figure 1. Mean heritability (bold line) and its confidence interval for several studied parents and progeny sizes estimated through a top-crossdesign from computed data samples (See text for details). Each � corresponds to an estimation of heritability obtained from a studied trial withthe corresponding number of parents.

Clonal selection did not enable clone 461 to beovercome in trial 3 to 11, except in trials 9 and 11. Theadded genetic gain obtained by clonal selection overthe best hybrid in each trial ranged from 7 to 28%.In the most favourable trials, i.e. when genetic gainwas positive as compared to clone 461, the added gainfor clonal selection ranged from 7 to 16% of the besthybrid.

In most trials, clonal selection concerned only afew hybrids: one hybrid in trials 9 and 13, one majorhybrid in trials 5, 10, 11, 12 and 14.

Discussion

The analysed mating designs allowed the estimationof narrow sense, broad sense, family and within-crossheritabilities: 0.32, 0.43, 0.83 and 0.22, on averagerespectively. The percentage of additivity was high(81% on average). These estimations were used to pre-dict genetic gains achieved through hybrid or clonalselection. Before these estimations and genetic gainswith their consequences on breeding strategies are dis-cussed, three possible limitations due to the specific

genetic background of our populations and matingdesigns are listed: history of Guinean populations, useof specific testers and assumption of equal Guineanand Congolese additive genetic variance.

The C. canephora Guinean reference populationis composed of individuals surveyed from wild orsemi-wild forest populations. These forest popula-tions are not genetically isolated (Berthaud, 1986) andMontagnon (2000) checked with ten RFLP markersthat no linkage disequilibrium was observed in thispopulation but estimated an inbreeding coefficient of0.26. We hence could consider the Guinean popu-lation as a whole taking into account the estimatedinbreeding coefficient different from 0. Further studiesare of course needed with more molecular markers toconfirm linkage equilibrium. Should linkage disequi-librium be found among Guinean sub-populations,due to natural selection and/or random drift, thenour present estimations of genetic variances would bebiased upward.

Our mating designs imply that genetic variancesare estimated for the reference population whencrossed with one to three specific testers. Extrapol-

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ations to interpopulation genetic variances should beavoided or at least carefully considered. However, inthe present study, genetic parameters were used topredict genetic gains from the same designs and thus,except in trials 12 to 14, no extrapolation was needed.

Another limitation of our work lies in the es-timation of within-cross heritability. Assuming equalGuinean and Congolese additive genetic variancesmight be too strong. This assumption seems howeverto be a posteriori supported by our results: no sig-nificant differences were found between heritabilitiesestimated from different populations: within-Guineancrosses, Guinean parents crossed with Congolesetesters and Congolese parents crossed with Guineantesters. Nevertheless, 8 out of the 11 trials studiedinvolved Guinean parents crossed with Congolese test-ers. Differences in genetic parameters from differentgenetic groups or populations have been reported inmaize (Landi & Frascaroli, 1995; Menz & Hallauer,1997) or Medicago truncalata (Bonnin et al., 1997).Hence, more mating designs involving Congolese par-ents with respect to their recently identified precisegenetic groups (Montagnon et al., 1992; Dussert etal., 1999) would be needed, to further explore geneticparameters within Congolese groups.

Leroy et al. (1994) estimated h2ns for yield to be

0.38 in a single trial, which is close to the presentaverage estimation of 0.32 but the average broad senseheritability estimated here is much lower than the es-timation by Leroy et al. (1994): 0.43 as opposed to0.75. Lashermes et al. (1994b) estimated an interme-diate value (h2

bs = 0.57) from doubled haploids. Someof the differences seen in literature may be due todifferences in the composition of the reference pop-ulations. However, Leroy et al. (1994) and Lashermeset al. (1994b) dealt with one design. Their estimationsshould thus be viewed having in mind the intervals ofconfidence we could determine in the present study.The high percentage of additivity generally found forcoffee yield transmission (Bouharmont et al., 1986;Lashermes et al., 1994a) was confirmed in our work,thus allowing an efficient choice of parents from theirvalue per se.

Mean family heritability was high (h2f = 0.83), in

accordance with previous estimations over 0.90 ob-tained for families ranging in size from 50 to 100(Leroy et al., 1997). Only trial 6, where the progenysize was below 40, showed a relatively low h2

f , thusconfirming the minimum size of 40–50 for a progenyto be correctly assessed (Leroy et al., 1991). No es-timation of within-cross heritability for coffee yield

is available in the literature. Our averaged estimation,h2

wc = 0.22, is however comparable to that made foroil palm oil yields, which ranged from 0.04 to 0.26allowing an efficient clonal selection within hybrids(Meunier et al., 1988).

Heritability estimates varied among trials and con-firmed the need to work with several mating designsin order to be confident in the overall estimations. Thevariation proved to be mainly due to parent samplingrather than other factors, including the environment.A similar observation was made on forage maize byGallais et al. (1983): in different trials, variation in her-itability was explained by changes in genetic variancewithin the populations used, rather than changes inerror variance, which remained relatively stable overtrials. Theoretical computation showed that at least 30parents would be necessary in a top-cross design toachieve optimum precision. However, the confidenceinterval remained large, confirming the low preci-sion generally observed for heritability estimations(Nyquist, 1991). Nonetheless, a further gain in preci-sion should be obtained by implementing other matingdesigns, including disconnected designs (Namkoong& Roberds, 1974; Cilas, 1995). Moreover, all studiedtrials were in the same research station whereas someslight genotype-environment interactions were iden-tified over the coffee growing area of Côte d’Ivoire(Montagnon et al., 2000). In this regard, heritabil-ity and genetic gains at the country level should beslightly inferior to the present estimation.

The next improved populations of RRS will be ob-tained after separate intercrossing of the best Guineanand Congolese genotypes. After intercrossing, the in-breeding coefficient of the new Guinean populationwill thus be 0.00. A decrease of heritability is expectedas selection will reduce the additive component of thegenetic variance. Between trees competition may alsoincrease in future trials with selected high yieldinggenotypes. As competition proved to influence greatlycoffee yield (Montagnon et al., 2001), this could alsoinfluence the estimation of heritability. Furthermore, apossible linkage disequilibrium among Guinean sub-populations, not detected by previous analysis withfew markers (Montagnon, 2000), would be lowered insubsequent generations and would also lower geneticvariances.

The estimations of heritability are useful to predictgenetic gains and to decide between several breedingstrategies. Our results confirm previous observations(Leroy et al., 1997) that the expressed BG hybridvigour enables substantial genetic gains through hy-

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brid selection: up to 46% over the control clone intrial 14. Furthermore, our results indicate that cloneselection within BG hybrids will bring 7 to 28% overthe best BG hybrid. Thus, even if seeds are easier thancuttings to produce and disseminate to coffee growers,selecting clones within BG hybrids seems still attract-ive for coffee breeders. Clones actually selected withinBG hybrids, including some of the trials studied inthe present study, have been evaluated in clonal tri-als. Realized genetic gains and heritability can thus beevaluated and compared to estimates. This will be thesubject of a future article.

Acknowledgements

We thank Dr P. Baradat and two anonymous refereesfor helpful discussion on this paper.

References

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