# European maize landraces: genetic diversity, core collection definition and methodology of use

Brigitte Gouesnard, Jacques Dallard, P. Bertin, Armand Boyat, A. Charcosset

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Brigitte Gouesnard, Jacques Dallard, P. Bertin, Armand Boyat, A. Charcosset. European maize landraces: genetic diversity, core collection definition and methodology of use. Maydica, 2005, 50 (3/4), pp.225-234. hal-02675620

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# EUROPEAN MAIZE LANDRACES: GENETIC DIVERSITY, CORE COLLECTION DEFINITION AND METHODOLOGY OF USE

B. Gouesnard<fnref n="1" />,*, J. Dallard<fnref n="1" />, P. Bertin<fnref n="2" />, A. Boyat<fnref n="1" />, A. Charcosset<fnref n="2" />

Received February 6, 2005

**ABSTRACT** - Since its introduction in Europe five centuries ago, maize spread in Europe and numerous landraces have been cultivated. During the second half of the XXth century, large collections have been established to preserve this genetic diversity. The objectives of this paper are (i) to review recent results on the genetic structure and the origin of European maize, (ii) to present the constitution of the representative core-collection of European maize landraces built in RESGEN CT96-088 project, and (iii) to study the methodology of use of these landraces in present breeding programs. Based on molecular markers, five studies found a high allelic richness in landraces from Mediterranean regions such as Spain, and (for two of them) a strong similarity between several populations from Southern Spain and a group of Caribbean populations. These studies also attest the originality of Northern Eastern Europe landraces, for which a similarity is observed with American Northern Flint landraces. Historical investigations confirm the hypothesis of introductions of maize from this origin in the North of Europe, only a few decades after introduction of tropical maize in Southern Spain by Colombus. Starting from a total of 2899 European landraces, we established with the Mstrat software a representative core collection of 96 maize accessions that maximizes allelic richness at molecular markers and best represents variation at phenotypic traits. This collection is characterized for traits of agronomical interest such as silage quality and insect tolerance. Regarding the transfer of relevant traits to elite material, comparison of F₂ versus backcross foundation populations showed that this last strategy leads to a higher population mean while not leading to a decrease in variance, therefore backcross method appears superior. Preliminary selection of superior material within a landrace did not increase average expected genetic gain but increased stability in variable environments. Molecular markers should prove helpful to extend this back-cross approach to the targeted transfer of donor interesting genomic regions.

KEY WORDS: Zea mays L.; Corn; European landraces; Genetic diversity; Core collection; Backcross; Foundation population.

## INTRODUCTION

Maize was first introduced into Europe by Colombus, who brought it back from the West Indies to Southern Spain in 1493. Other introductions are hypothesized to have occurred later from other regions of the world and to have contributed to the diffusion of maize in the Mediterranean region, as well as in Central and Northern Europe (BRANDOLINI, 1970). Hybridizations probably occurred between different introductions. Associated with the selection pressures which have been exerted by the farmers and by climatic conditions, they likely contributed to develop specific European varieties. European maize traditional varieties display a large diversity, but also share some common characteristics, such as insensitivity to the photoperiod, mainly flint texture of the grain and low to medium yield (GAY, 1999).

Since the middle of the XXth century, this diversity has been used to derive inbred lines. These lines appeared highly complementary with inbred lines of US origin to produce hybrids cultivated in Europe areas. Progress brought by plant breeding and agronomical practices constitute a true revolution which made it possible to produce average grain yields of about 90 q/ha (FAO, 2004). Some time after the introduction of the first commercial hybrids, the necessity to preserve genetic resources appeared and led to the constitution of many national maize collections (EDWARDS and LENG, 1965). In order to properly use the populations in breeding programmes, breeders characterised extensively these collections of populations. Morphological de-

<footnote n="1">¹ INRA, UMR Diversité et Génome des Plantes Cultivées, domaine de Melgueil, 34130 Mauguio, France</footnote>

<footnote n="2">² INRA, CNRS, INA PG, UPS, UMR de Génétique Végétale, Ferme du Moulon, 91190 Gif sur Yvette, France</footnote>

<footnote>* For correspondence (fax: +33 4 67 29 39 90; e.mail: gouesnard@ensam.inra.fr).</footnote>
scriptions and classifications have been carried out
on Spanish (SANCHEZ-MONGE, 1962), Italian (BRAN-
DOLINI and MARIANI, 1968), Yugoslavian and Roman-
ian (PAVLICIC and TRIFUNOVIC, 1966), Portuguese
(COSTA-RODRIGUES, 1971) and more recently French
(GOUESNARD et al., 1997) national collections. Com-
parison of populations from different countries was
carried out on populations from Italy, Hungary, Yu-
goslavia and Romania (LENG et al., 1962) and on
populations from Italy, Yugoslavia and Romania
(PAVLICIC, 1971). BRANDOLINI (1969, 1970, 1971) re-
alised several syntheses on major European maize
races.

The relevance of morphological characters for
the classification of populations appears limited,
mainly because the effect of environment on the
expression of characters. Genetic markers not af-
fected by environmental conditions therefore re-
ceived considerable attention for the analysis of ge-
netic diversity. Isoenzymatic markers were used
first, and allowed to analyze associations among dif-
ferent samples of European populations (SAL-
ABOUNAT and PERNES, 1986; GERIC et al., 1989; LEFORT-
BUSON et al., 1991; GARNIER, 1992; LIAURADO et al.,
1993, REVILLA et al., 1998). DNA markers, particularly
RFLP and then SSR, were used subsequently. Based
on these DNA markers, maize inbred lines were
classified into distinct heterotic groups (for review
see MELCHINGER, 1999).

With the large number of accessions contained
in most crop germplasm collections, the genebank
managers are to face to the maintenance and uti-
lization of these collections. The core collection
concept was proposed as one approach to this
problem. The design of the core collection should
minimize repetitiveness within the collection and
should represent the genetic diversity of crop
species (and possibly its relatives) (FRANKEL, 1984).
The theory was developed on the basis of neutral
marker by BROWN (1989) who showed that 10% of
the base collection, and a maximum of 3000 indi-
viduals, allow preservation of about 70% of alleles.
Most researchers currently believe that the sampling
should first be stratified, according to the organiza-
tion of variability in groups and sub-groups
(HINTUM, 1995). The criteria used could be taxo-
nomic, geographical or ecological, or could be
based on neutral or non-neutral characters (HAMON
et al., 1995). To choose inside the groups, BROWN
(1989) proposed the R, P, L, H strategies for which
the number of accessions inside a group is given by
random, proportional, logarithmic, or diversity in-

dex, respectively. Two main methods proposed a
determinist choice. The M strategy (SCHOEN and
BROWN, 1993) supposes the availability of molecular
or biochemical data for accessions. This method
maximizes the allelic richness. The PCSS method
(NOIROT et al., 1996) requires quantitative or qualita-
tive data for accessions. This method maximizes the
generalized sum of squares of the selected acces-
sions in a space of factorial axes. UPADHYAYA et al.
(2003) gave examples of core collection constitu-
tion in many species. In maize, RADOVIC and JELOVAC
(1994), ABADIE et al. (1999), MALOSETTI and ABADIE
(2001) constituted a core collection of populations
from Yugoslav maize gene bank, Brazilian maize
germplasm and Uruguayan maize landraces, respec-
tively.

The core collection is a mean to manage a large
collection by making possible the evaluation of a
part of the collection which represents the total col-
lection. Then it is an “entry key” to exploit all the
collection by identifying of the best source(s) for
the improvement of trait(s) of agronomical impor-
tance. Following this identification, the second step
is the transfer of this quality to elite accessions.

The objectives of this study were to (i) review
the genetic analysis of European collection of maize
landraces in order to structure the variability, (ii) ex-
amine the methodology of constitution of the Euro-
pean core collection in order to manage and exploit
the available genetic diversity for traits of interest,
and (iii) compare several alternatives to use genetic
resources for the improvement of elite breeding ma-
terial.

GENETIC DIVERSITY
OF EUROPEAN MAIZE LANDRACES

We review the results of five published studies
on European and both European and American
maize landraces (REBOURG et al. 2001, 2003; GAUTHI-
ER et al., 2002; REVILLA et al., 2003, DUBREUIL et al.,
2005) (Table 1). The sampling consists of two bulks
of 15 plants in all studies except for isozymes for
which analyses were performed for individual
plants. The use of RFLP and SSR for large scale mol-
ecular evaluations of genetic diversity within popu-
lation is expensive and time-consuming effort. In
contrast, the use of bulk analysis (MICHELMORE et al.,
1991) for maize diversity analysis with RFLP
(DUBREUIL et al., 1999) or with SSR (DUBREUIL et al.,
2003) allows an analysis of larger samples.
<table><caption>TABLE 1 - Recent studies on genetic diversity among European maize populations: size of the analysed collection with reference to the programme, allelic richness in European and American landraces, used markers with type of sampling.</caption><thead><tr><th></th><th>Number of European landraces</th><th>Mean number of alleles per locus in Europe</th><th>Number of American landraces</th><th>Mean number of alleles per locus in America</th><th>Markers</th><th>Sample</th></tr></thead><tbody><tr><td>REBOURG et al. (2001)</td><td>131</td><td>9.59</td><td>–</td><td>–</td><td>29 RFLP</td><td>2 bulks of 15 plants</td></tr><tr><td>GAUTHIER et al. (2002)</td><td>488</td><td>11.48</td><td>–</td><td>–</td><td>23 RFLP</td><td>2 bulks of 15 plants</td></tr><tr><td>REBOURG et al. (2003)</td><td>131</td><td>9.55</td><td>88</td><td>12.34</td><td>29 RFLP</td><td>2 bulks of 15 plants</td></tr><tr><td>REVILLA et al. (2003)</td><td>404</td><td>3.1</td><td>–</td><td>–</td><td>19 isozyme loci</td><td>20 plants</td></tr><tr><td>DUBREUIL et al. (2005)</td><td>131</td><td>7.17</td><td>144</td><td>7.75</td><td>24 SSR</td><td>2 bulks of 15 plants</td></tr></tbody></table>

A higher degree of polymorphism was observed in American than in European maize populations (Table 1). Populations of Northern Eastern Europe exhibit a lower allelic richness than in Southern Europe ones, which suggests that (i) Southern Europe was the location of most of the introductions into Europe, (ii) northern introductions had a lower genetic diversity than southern ones (iii) that northern populations were submitted to a higher genetic drift, and/or (iv) that northern populations were stronger selected for adaptation. REVILLA et al. (2003) observed the presence of several rare alleles in Spain that are absent in the other European countries, and suggested that Spain was the entry for most variability of European maize, or that there were several singular introductions of maize into Spain.

In all studies, a clear structuration identifies a cluster of Northern Europe landraces: one cluster of 39 populations in REVILLA et al. (2003), two clusters for German Flint and North-Eastern European Flint in REBOURG et al. (2001, 2003), one cluster for North-Eastern populations in GAUTHIER et al. (2002). This suggests an origin of North-Eastern maize landraces different from the origin of the Southern European landraces. The structuration of other European landraces is variable among different studies. REVILLA et al. (2003) and REBOURG et al. (2001, 2003) found a cluster for Mediterranean landraces, the other populations being in another large cluster, or separated in an Italian cluster and a Pyrenees-Galice cluster. GAUTHIER et al. (2002) found two main clusters: South-Eastern and South-Western clusters. These clusters are consistent with clusters found by REBOURG et al. (2001, 2003).

Results from studies investigating the population

structure among European and American maize populations illustrated that Southern Spain populations were closely related to Caribbean populations. This can be explained by the historical data on the introduction of maize in the South of Spain by Columbus after his second trip in the Caribbean region. In addition, American Northern Flint populations were closely related to North-Eastern European populations considering molecular and morphological data. This suggests that the origin of Northern European germplasm was North America. Opposite to the Southern Spain and Northern European populations, materials from the Pyrenees and Galice in Spain do not display a close similarity with any American material. This suggests that Pyrenees and Galice populations are intermediate between the Caribbean and Northern American Flint populations. This can be explained as a result from hybridizations between these two types of landraces. Finally, it has to be noted that Italian populations constitute a homogenous independent group, which suggests an independent origin and/or local differentiation. Other introductions with lesser contribution may also have occurred, as suggested alleles Glu1-13, Acp1-3.5 and Mdh4-9 shared by maize from the Mediterranean countries (particularly Spain) and from Guatemala (REVILLA et al., 2003).

To complete the study on contribution of Northern Flints to European material, historical analyses were performed by M. Chastanet. They show that this North-American maize had probably been brought back at the time of the voyages of Giovanni Verazzano (1524) and possibly Jacques Cartier (1535), i.e. much earlier than one believed up to now (REBOURG et al., 2003; DUBREUIL et al., 2005).
## CONSTITUTION OF CORE COLLECTION OF EUROPEAN MAIZE LANDRACES

The European collections analyzed within the European RESGEN CT96-088 include a total of 2899 landraces (Table 2). The objective of the project was to build a core collection of around 100 landraces in order to evaluate them for several traits relevant to the European Common Agricultural Policy. The 2899 landraces were first described for passport data and some primary descriptors (such as flowering time, ear and kernel types, see http://www.montpellier.inra.fr/gap/resgen88/). The first step towards a core collection consisted in the definition of a representative national collection of maize landraces in each country. Size of these representative collections was decided in common by the different researchers (Table 2). The selection was based on passport data, primary descriptors, and secondary descriptors (such as plant height, ear length). The objective was to eliminate redundancy, to get accessions for each agro-ecological region of cultivating maize and a good representativity of the different categories of maize obtained after classification. On a second step, the different national representative collections were assembled and analysed for molecular markers. These 395 landraces were also evaluated for forage quality (MIEG et al., 2001). The advantage of analysing together all representative national collections is to eliminate redundancy in frontier zones (Alsace and West Germany, French and Spanish Pyrenees, Galice and North of Portugal).

The method of constitution of the core collection is the M method proposed by SCHOEN and BROWN (1993) which maximizes the allelic richness. The software used is Mstrat (GOUESNARD et al., 2001) for which richness is defined for alleles and classes of phenotypic values. To do so, distribution of quantitative traits is cut out in classes. The richness of a sample is defined as the number of classes for which there is at least one accession. In the case of two samples having the same richness scores, the software uses the inertia criterion, as defined in the principal score analysis method or PCSS (NOIROT et al., 1996). The M method was found superior to random method and sampling methods proposed by BROWN (1989) (C, constant; P, proportional; L, logarithmic) on a simulated dataset (BATAILLON et al., 1996). This method is used for the management of genetic resources collections (DAVID et al., 2003; BARANGER et al., 2004; MCKHANN et al., 2004, and in other experimental works).

<table><caption>TABLE 2 - Size of the total collection, representative collections and core collection for each country in Resgen088 programme.</caption><thead><tr><td>Country</td><td>Total collection</td><td>Representative collection</td><td>Core collection</td></tr></thead><tbody><tr><td>France</td><td>272</td><td>80</td><td>16</td></tr><tr><td>Germany</td><td>15</td><td>15</td><td>8</td></tr><tr><td>Greece</td><td>201</td><td>50</td><td>12</td></tr><tr><td>Italy</td><td>562</td><td>90</td><td>19</td></tr><tr><td>Spain</td><td>948</td><td>90</td><td>24</td></tr><tr><td>Portugal</td><td>901</td><td>70</td><td>17</td></tr><tr><td>Total</td><td>2899</td><td>395</td><td>96</td></tr></tbody></table>

Reference maize landraces such as ones used for breeding, analysed in former studies, and/or of key historical importance are chosen. This first sample, inferior in size to the total size of the final sample, is called kernel core (22 landraces). In a second step, the genetic diversity (allelic or class richness) of the core collection sample is maximised using Mstrat by adding iteratively new accessions to the kernel core. Genetic diversity is defined for a whole of traits: passport data (country of origin), primary descriptors (growing degree units to female flowering, kernel type, ear shape, number of kernel rows, kernel and cob colour), isozyme analysis (14 loci and 47 alleles), RFLP analysis (21 loci with 127 alleles in frequency and 60 alleles in presence/absence). To choose the last accessions of the core collection, we have sampled among the accessions most frequently drawn by Mstrat (the most original accessions) those which were representative of the groups obtained by classification on the allelic frequencies with 19 loci RFLP.

The Mstrat strategy is mainly based on marker data (234 alleles versus 5 traits of primary descriptors and country of origin). The question is the effectiveness of the strategy mainly based on neutral diversity at other diversity levels such as adaptation to ecogeographical conditions. It can be noted first that the classification obtained on 19 RFLP loci on the representative collections (GAUTHIER et al., 2002) is in agreement with the geographical origin of accessions. Secondly in a previous study, GOUESNARD et al. (personal communication) analysed the diversity of 80 French Pyrenean maize landraces, both with 15 agromorphological traits and 16 RFLP loci. They compared the richness obtained at morphological traits by sampling either on morphological diversity
(direct method), on molecular data (indirect method), or at random. Fig. 1 shows that the response of the indirect method is higher than the random sampling. The result was expected because the correlation coefficient estimated between morphological distances and molecular distances is significantly different from zero (0.18). Thus, strategy based on neutral diversity is effective to maximize the agro-nomical variability on this Pyrenean collection.

<figure><img src="image_2.png" /></figure>

FIGURE 1 - Richness level measured on morphological variables in percentage of the total collection of 80 Pyrenean maize landraces (GOUESNARD *et al.*, personal communication). Measures for two sizes of the core collection (25% of the total in white, 12.5% of the total in black) and for three methods of constitution (1: direct method; 2: indirect method with molecular data, 3: random method).

On allelic and class richness criterion, 93% of the richness of the European representative collections is included in the core collection. On qualitative morphological variables, the Chi2 tests show that the percentage of each class is not significantly different between the total collection and the core collection. On quantitative variables, the mean of the variables are not significantly different. The minimum and the maximum of quantitative variables are nearly all identical. The distribution by country are globally conserved between the whole collection and the core collection (8% Germany, 12.5% Greece, 16.5% France, 18% Portugal, 20% Italy, 25% Spain) except for Germany for which the higher proportion of selected landraces is due to the originality of these accessions. Considering the classification found on 19 RFLP (GAUTHIER *et al.*, 2002), the distribution is the following: East Group (mainly Germany) 3%, Central Group (mainly France and Italy) 15.5%, South-Eastern Group (mainly Greece) 15.5%, South-Eastern Group (mainly Italy) 22%,

South-Western Group (mainly Portugal) 22%, South-Western Group (mainly Spain) 22%. The list of the core collection is available in the database (http://www.montpellier.inra.fr/gap/resgen88/). The European Maize Landraces Core Collection (EUMLCC) was evaluated for various traits according to the European Common Agricultural Policy (Forage traits - MIEG *et al.*, 2001; Insect tolerance - MALVAR *et al.*, 2004; quality of the grains - BERARDO *et al.*, 2003; drought tolerance - DALLARD *et al.*, 2003; tolerance to low nitrogen level - BRICHETTE *et al.*, 2003).

## USE OF EUROPEAN GENETIC RESOURCES

According to BERTHAUD (1997), there are three main ways to use genetic resources: (i) the linear model relied on an *ex situ* conservation for which an interesting accession is directly extracted from the gene bank for agricultural use, (ii) the triangular model in which a broad initial genetic diversity is progressively restricted by selection towards elite material suitable for agricultural use, and (iii) the “circular” model based on *in situ* conservation, in which agricultural use, multiplication and selection are fully integrated. Numerous examples of the triangular approach exist in maize: the Latin American Maize Project (SALHUANA, 1989; SEVILLA *et al.*, 1994), the Germplasm Enhancement of Maize (GEM, http://www public.iastate.edu/~usda-gem/home- page.html), the INRA/PROMAIS project (GROUPE MAIS DGAP-INRA and PROMAIS, 1994; GALLAIS and MONOD, 1998), the HOPE (Hierarchical Open-ended Population Enrichment; KANNENBERG, 2001).

The triangular model seems to be the more appropriate one for the utilisation of European maize landraces, mostly because of their low yield relative to present elite material. Indeed, maize landraces often yield only approximately half of present commercial hybrids and their hybrid performance is lower than that of elite inbred lines, when evaluated with the same tester lines (GALLAIS and MONOD, 1998). Therefore the main strategy to use them efficiently is to cross them with elite materials to create new breeding populations. This raises however several questions such as the proportion of elite material to be considered (e.g. 50% elite or 75% elite) and that kind of the necessity of a preliminary selection of individuals within landrace prior to crossing with elite material.

A pilot experiment was conducted on 4 French maize landraces to address these points (CHARCOSSET
<figure><img src="image_3.png" /><figcaption>FIGURE 2 - Design of experiment on methodology of use of maize landraces (CHARCOSSET et al., personal communication). For each French landrace, initial families were an unselected pool of 30 S<sub>1</sub> families or the best S<sub>1</sub> family into this subset (DUBREUIL, 1996). These materials were crossed once with the F<sub>2</sub> line and then selfed (F<sub>2</sub> generation), or crossed twice with F<sub>2</sub> line (Back-Cross generation). 30 S<sub>1</sub> families for each type were evaluated in crosses with the MBS847 tester.</figcaption></figure>

et al., personal communication). The landraces were Lacaune (FRA0410015), Gazost (FRA0411041), Moncassin (FRA0410570), Roux de Chalosse (FRA0410622). The three last populations originated from south-western of France were studied by DUBREUIL (1996) evaluating 30 S<sub>1</sub> progenies per population in crosses with two testers. For each population, four types of progenies (Fig. 2) were created by crossing to inbred line F2 (derived from the Lacaune population and widely used in commercial hybrids up to the early 1990s). They are combinations of: i) two types of initial donor material: unselected S<sub>1</sub> families or the best S<sub>1</sub> family derived from the landrace; ii) 50% or 75% of the elite material derived by one cross (F<sub>2</sub>) and two crosses (BC) respectively. Thirty families for each such breeding population (16 in total) were evaluated in crosses with dent tester MBS847 in two locations (Gif sur Yvette, Clermont-Ferrand) with 2 replicates, in 1999 and 2000. Three traits were evaluated: grain yield, grain moisture and lodging. An economical index was estimated: I(CTPS) = yield - 2.5 * moisture. Three trials were considered in the study with an error variation coefficient lower than 7% for yield. Genetic variance and genetic x environment variance were estimated for each landrace and its 4 types of progenies. The interest of each type of progenies and landraces for breeding can be estimated by the utilisation criterion proposed by SCHNELL (1983). U= Mean + G(α) with G(α)= k(α) σ<sub>g</sub> h, where k is the standardised selection differential for a given selected proportion (α), σ<sub>g</sub> is the genotypic standard deviation, h is the square root of heritability.

Only number of crosses with the elite material (BC or F<sub>2</sub>) and landrace factors and their interaction had significant effects on the trait variation (data not

shown). No difference between selected S<sub>1</sub> family and the landrace itself were observed. The criterions of utilisation for the different traits are presented in Table 3. For yield and I(CTPS), BC were better than one cross F<sub>2</sub> in all cases except in the case of Lacaune and Roux de Chalosse (yield only) where methods are equivalent. For grain moisture, the behaviour of progenies depends on the earliness of F2 compared with the landrace. For early landraces (Lacaune, Gazost), the criterion of utilisation is better for F<sub>2</sub> than BC. On the opposite, for Roux de Chalosse and Moncassin, the criterion of utilisation is better for BC than for F<sub>2</sub>. Back-cross method has an advantage also for lodging when the level is high in the original landrace. Several instances exist where the criterion of utilisation exceeds the value of elite parent F2, confirming the usefulness of landraces for genetic improvement.

The main conclusions are: (i) BC is preferable than the method with one cross F<sub>2</sub> because it increases the average of the population without decreasing the variance; (ii) the cross with too closely related lines has to be avoided (here Lacaune with F2) because of the reduction of genetic variance (data not shown); (iii) preliminary selection within landraces has no effect on the cross performance but it tends to reduce the genotype x environment interaction.

The question of BC population in comparison with F<sub>2</sub> population is related with the choice of the optimum proportion of exotic and adapted material to create the foundation population. Theoretical studies have taken into account the divergence between the parents, the level of dominance of the considered trait, and long or short-term goals, in order to determine the best foundation population (DUDLEY, 1982; BRIDGES and GARDNER, 1987; MEL-
<table><caption>TABLE 3 - Mean, expected genetic progress for a selection of 10% (ΔG), criterion of utilisation (U), for yield, grain moisture, CTPS index, and lodging. gaz: Gazost, lac: Lacaune, mon: Moncassin, rdc: Roux de Chalosse; 0: unselected families, best: best S<sub>1</sub> family; bc and f2 indicate back-cross and F<sub>2</sub> populations, respectively, their absence indicate direct evaluation.</caption><thead><tr><th rowspan="2">type<br>of<br>progenies</th><th colspan="3">yield (q/ha)</th><th colspan="3">grain moisture (%)</th><th colspan="3">CTPS index</th><th colspan="3">lodging (%)</th></tr><tr><th>mean</th><th>ΔG</th><th>U</th><th>mean</th><th>ΔG</th><th>U</th><th>mean</th><th>ΔG</th><th>U</th><th>mean</th><th>ΔG</th><th>U</th></tr></thead><tbody><tr><td>F2 (check)</td><td>96.51</td><td>0.00</td><td>96.51</td><td>27.88</td><td>0.00</td><td>27.88</td><td>26.85</td><td>0.00</td><td>26.85</td><td>1.73</td><td>0.00</td><td>1.73</td></tr><tr><td>Gaz 0</td><td>94.53</td><td>-</td><td>-</td><td>28.26</td><td>-</td><td>-</td><td>23.88</td><td>-</td><td>-</td><td>3.43</td><td>-</td><td>-</td></tr><tr><td>Gaz 0 f2</td><td>89.46</td><td>3.26</td><td>92.72</td><td>26.99</td><td>1.09</td><td>25.90</td><td>22.04</td><td>3.73</td><td>25.77</td><td>2.77</td><td>1.36</td><td>1.41</td></tr><tr><td>Gaz 0 bc</td><td>94.21</td><td>1.92</td><td>96.13</td><td>27.69</td><td>1.03</td><td>26.66</td><td>25.01</td><td>2.79</td><td>27.80</td><td>2.92</td><td>0.92</td><td>2.00</td></tr><tr><td>gaz best</td><td>81.19</td><td>-</td><td>-</td><td>26.12</td><td>-</td><td>-</td><td>15.21</td><td>-</td><td>-</td><td>5.19</td><td>-</td><td>-</td></tr><tr><td>gaz best f2</td><td>90.09</td><td>0.00</td><td>90.09</td><td>27.01</td><td>0.77</td><td>26.24</td><td>22.53</td><td>0.67</td><td>23.20</td><td>3.23</td><td>0.00</td><td>3.23</td></tr><tr><td>gaz best bc</td><td>93.25</td><td>5.63</td><td>98.88</td><td>27.67</td><td>1.27</td><td>26.40</td><td>24.12</td><td>4.08</td><td>28.20</td><td>2.83</td><td>0.67</td><td>2.16</td></tr><tr><td>lac 0</td><td>82.53</td><td>-</td><td>-</td><td>26.77</td><td>-</td><td>-</td><td>15.62</td><td>-</td><td>-</td><td>11.11</td><td>-</td><td>-</td></tr><tr><td>Lac 0 f2</td><td>92.59</td><td>2.71</td><td>95.30</td><td>27.14</td><td>1.09</td><td>26.05</td><td>24.74</td><td>2.74</td><td>27.48</td><td>5.79</td><td>0.16</td><td>5.63</td></tr><tr><td>Lac 0 bc</td><td>95.99</td><td>0.00</td><td>95.99</td><td>27.44</td><td>1.03</td><td>26.41</td><td>27.40</td><td>0.00</td><td>27.40</td><td>3.12</td><td>1.32</td><td>1.80</td></tr><tr><td>lac best</td><td>87.39</td><td>-</td><td>-</td><td>26.66</td><td>-</td><td>-</td><td>20.76</td><td>-</td><td>-</td><td>15.46</td><td>-</td><td>-</td></tr><tr><td>lac best f2</td><td>93.73</td><td>3.10</td><td>96.83</td><td>27.06</td><td>1.45</td><td>25.61</td><td>26.09</td><td>3.00</td><td>29.09</td><td>5.49</td><td>0.00</td><td>5.49</td></tr><tr><td>lac best bc</td><td>97.17</td><td>2.67</td><td>99.84</td><td>27.36</td><td>0.64</td><td>26.72</td><td>28.78</td><td>0.45</td><td>29.23</td><td>3.37</td><td>1.90</td><td>1.47</td></tr><tr><td>Mon 0</td><td>90.26</td><td>-</td><td>-</td><td>29.04</td><td>-</td><td>-</td><td>17.66</td><td>-</td><td>-</td><td>7.28</td><td>-</td><td>-</td></tr><tr><td>Mon 0 f2</td><td>92.98</td><td>2.38</td><td>95.36</td><td>28.21</td><td>0.50</td><td>27.71</td><td>22.35</td><td>2.61</td><td>24.96</td><td>5.39</td><td>0.92</td><td>4.47</td></tr><tr><td>Mon 0 bc</td><td>95.39</td><td>2.69</td><td>98.08</td><td>28.08</td><td>1.07</td><td>27.01</td><td>25.21</td><td>2.62</td><td>27.83</td><td>3.50</td><td>1.23</td><td>2.27</td></tr><tr><td>mon best</td><td>87.26</td><td>-</td><td>-</td><td>27.84</td><td>-</td><td>-</td><td>17.65</td><td>-</td><td>-</td><td>14.16</td><td>-</td><td>-</td></tr><tr><td>mon best f2</td><td>92.06</td><td>4.04</td><td>96.10</td><td>28.43</td><td>0.83</td><td>27.60</td><td>20.94</td><td>2.18</td><td>23.12</td><td>5.51</td><td>0.00</td><td>5.51</td></tr><tr><td>mon best bc</td><td>95.26</td><td>3.84</td><td>99.10</td><td>28.01</td><td>0.68</td><td>27.33</td><td>25.24</td><td>4.26</td><td>29.50</td><td>3.79</td><td>2.27</td><td>1.52</td></tr><tr><td>Rdc 0</td><td>87.56</td><td>-</td><td>-</td><td>28.92</td><td>-</td><td>-</td><td>15.26</td><td>-</td><td>-</td><td>5.83</td><td>-</td><td>-</td></tr><tr><td>Rdc 0 f2</td><td>95.19</td><td>3.20</td><td>98.39</td><td>28.00</td><td>1.45</td><td>26.55</td><td>24.95</td><td>3.09</td><td>28.04</td><td>4.56</td><td>1.06</td><td>3.50</td></tr><tr><td>Rdc 0 bc</td><td>93.85</td><td>5.08</td><td>98.93</td><td>27.88</td><td>1.82</td><td>26.06</td><td>24.06</td><td>6.13</td><td>30.19</td><td>3.81</td><td>1.55</td><td>2.26</td></tr><tr><td>rdc best</td><td>97.13</td><td>-</td><td>-</td><td>29.11</td><td>-</td><td>-</td><td>24.36</td><td>-</td><td>-</td><td>7.51</td><td>-</td><td>-</td></tr><tr><td>rdc best f2</td><td>93.95</td><td>1.70</td><td>95.65</td><td>28.21</td><td>0.93</td><td>27.28</td><td>23.45</td><td>2.41</td><td>25.86</td><td>4.09</td><td>1.00</td><td>3.09</td></tr><tr><td>rdc best bc</td><td>94.37</td><td>4.73</td><td>99.10</td><td>28.09</td><td>0.69</td><td>27.40</td><td>24.10</td><td>3.93</td><td>28.03</td><td>2.40</td><td>0.87</td><td>1.53</td></tr></tbody></table>

CHINGER, 1987; CROSSA, 1989). In experimental studies, CROSSA and GARDNER (1987) found some advantage in using one cross with elite material (F<sub>2</sub> populations), rather than the backcross for yield. ALBRECHT and DUDLEY (1987), MELCHINGER et al. (1988), and GOUESNARD et al. (1996), for a weak selection, reported the superiority of the backcross generation for yield. Results obtained here for European landraces comfort the conclusions of these last studies so that back-crossing should be recommended for their use in breeding.

PERSPECTIVES

The genetic diversity of European maize landraces is very broad and represented by thousands of populations. The morphological descriptors and

now the molecular markers allowed to structure the genetic variability and to understand the great lines of the phenomena that shaped it: foundation and hybridization events in particular. To manage such a collection, the core collection concept is useful. Maximisation of allelic or class richness is effective and makes it possible to represent the diversity in a small sample size that facilitates further evaluation and use.

It can be noted that results presented here mostly address all or representative samples of the 2899 landraces maintained in Western European collections and less European Eastern landraces (30 landraces among 131 European ones in REBOURG et al., 2001). These may therefore contain further original sources, which should deserve investigations in a global survey of molecular diversity and agronomic evaluation of Eastern European maize landraces,
in order to constitute a core collection really repre-
sentative for all Europe.

Our result show that use of landraces in (back-)-
cross with elite material can yield promising breed-
ing populations. Use of molecular markers is expect-
ed to increase the efficiency of this approach by
means of targeted utilisation of some genomic re-
gions. Recent investigation on polymorphism within
candidate genes and its association with phenotypic
variation appear promising to identify favourable al-
leles and closely associated markers (THORNSBERRY *et al.*, 2001), which offers promising avenues for the
transfer of alleles from genetic resources to elite ma-
terial by marked-assisted selection.

ACKNOWLEDGEMENTS - These researches were partially supported by the European Union (contract: RESGEN CT96-088), by CIMMYT, by the PROMAIS association, by French Ministry of Agriculture, and by INRA. We gratefully acknowledge J. Moreno-Gonzales, I. Bricette-Mieg, A. Ordas, R.A. Malvar, P. Revilla, A. Alvarez, M. Motto, R. Redaelli, E. Lazarou-Kallinaki, G. Evgenidis, A.M. Barata, P. Ruaud, T.J.L. Van Hintum, A. Borner, for providing plant material and for helpful discussions concerning maize germplasm.

We are indebted to C. Tollon-Cordet, D. Madur, V. Combes, S. Santoni for expert technical support in the molecular analyses, and to J. Bordes, P. Jamin, D. Coubriche, D. Jolivot for phenotypic experiments. The authors thank Bastien Lemoine for the result interpretation of methodology of use of 4 maize landraces, and Pierre Dubreuil for his research on maize landraces.

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