Apricots (Prunus armeniaca L.) belong to the family Rosaceae, subfamily Prunoideae, the Prunophora subgenus of the genus Prunus. They are found in the five continents; they are adapted to grow from arid to southern temperate climates and are characterized by an extensive variability that is related to their ecological requirements. Nevertheless, apricots are characterized by a high specificity of the existing cultivars (Bailey and Hough 1975; Faust et al. 1998) with narrow adaptative areas.
Apricots are traditionally cultivated in Tunisia and cultivars of minor economical interest are not used in the intensive modern orchards. Accordingly, a sizable fraction of the autochthonous germplasm was threatened by genetic erosion in particular in the restricted traditional areas of cultivation. Previous studies conducted by Valdeyron and Crossa-Raynaud (1950), Crossa-Raynaud (1960) and Carraut and Crossa-Raynaud (1974) showed that only few of the previously described cultivars have been encountered in the last surveys. In fact, among the 48 traditional cultivars previously described, 26 disappeared according to the recent sur veys conducted in the same areas (Krichen et al. 2009). Accordingly, the variability described in Tunisia was threatened as a consequence of intensive agricultural practice which was advantageous for a limited number of cultivars widely propagated while most of the traditional landraces were cultivated in small area and were unknown elsewhere. This erosion of genetic diversity called for an initiative based on genetic resources preservation as soon as possible.
The main goal of germplasm management is to collect and to characterize diverse forms, in particular at the national and regional level (Khadari et al. 2003). The first criterion to select representative accessions is based on morphological and agronomic traits of interest. Plant breeders routinely use morphological characterization for the initial description and classification of germplasm in order to select valuable genetic resources for direct use by farmers or in breeding programs. However, recent studies show that molecular markers are indispensable for the germplasm management. Consequently, studies on genetic variability of genetic resources under collecting, help to efficiently preserve valuable germplasm and at the same time, avoid the storage of redundant ones which contributes to the germplasm management.
The need to develop collections for efficient conservation and utilization of genetic diversity has led to the development of core collections for many crop plants including tomato (Ranc et al. 2008), grape (Le Cunff et al. 2008), loquat (Martínez-Calvo et al. 2008), pearl millet (Bhattacharjee and Khairwal 2007), West African yam (Mahalakshmi et al. 2007), common bean (Rodino et al. 2003; Logozzo et al. 2007), soybean (Wang et al. 2006), safflower (Dwivedi et al. 2005), taro (Okpul et al. 2004), groundnut (Upadhyaya et al. 2003), sugarcane (Balakrishnan et al. 2000; Amalraj et al. 2006) and sesame (Xiurong et al. 2000).
Frankel (1984), Brown (1989a, 1989b), Marita et al. (2000) and Rodino et al. (2003) argue that the purpose of a core is to provide potential end-users with a representative sample of the available genetic variation of the crop gene pool in a subset of a manageable number. The purpose is to improve utilization and accessibility to vast collections of crop germplasm already maintained and characterized by a gene bank. The entire collection must be reduced to a manageable size that can be easily evaluated to generate good data and enhance utilization.
The core collection is defined as a subset of accessions from a larger collection of particular crop plant that captures most of the available genetic diversity of that crop and its wild relatives with a minimum amount of repetitiveness of this germplasm including its geographical variation. This subset must retain the largest part of the diversity (more than 70% of the entire collection diversity) without redundancy and must be small enough to be easily managed. The rest of the collection should be maintained as the reserve collection. The collection can be evaluated extensively and the information could be used to guide a more efficient utilization of the entire collection. The choice of a sampling strategy is critical in the establishment of core collections, in particular when there are several available criteria and methods proposed to build core collections.
Frankel (1984) and Brown (1989a, and Brown 1989b) described methods using information on the origin and on the characteristics of the accessions Before the setting of the core collection, the size of the final collection as well as the degree of genetic similarity or commonality among accessions have to be taken into consideration to then determine groups within the entire collection.
The Frankel and Brown (1984) strategy involves the stratification of the collection and the selection of a representative set by random sampling from each of the classified groups. The accessions are first classified according to the taxonomy (species, subspecies, races) then according to their geographic location (country, state), climate or agro-ecological regions. The clustering within the broad geographic group could be done using strongly inherited traits. The number of accessions selected from each cluster will depend on the strategy used and the selection of core collection was made after sub-clustering within the identified groups (Spagnoletti-Zeuli and Qualset 1993; Upadhyaya et al. 2003; Mahalakshmi et al. 2007). According to Xiurong et al. (2000) the hierarchical clustering methodology was chosen after testing and comparing several cluster trees with respect to their balance, expansibility with consideration of the ecological genotype, origin and correlation of identified traits. Ward's method was proven to be the best one for clustering. It is defined by Hintze (2001) as follow: on the base of the variance minimization within groups; groups are formed so that the pooled within-group sum of squares is minimized. That is, at each step, the two clusters are linked which results in the least increase in the pooled within-group sum of squares (Hintze 2001). Dwivedi et al. (2005) used the stratified sampling by geographic origin based on Ward's hierarchical clustering and divided the collection into groups or strata and then a simple random sample is selected from each group on the base of passport or characterization data.
Balakrishnan et al. (2000) proposed two methods: 1) non-hierarchical cluster analysis with previous iden tification of clusters number; 2) principal component analysis which consists on the identification of the generalized sum of squares defined as the product of individual numbers and variable numbers constituting the factor space. A comparison of these two methods proved that the most suitable one for core collection identification is the principal component analysis which defines new independent variables, maximizes diversity and avoids redundancy or duplicates.
Marita et al. (2000) developed an algorithm to assist in selecting core collection which maximizes genetic distances among a set of accessions and ranks all other accessions relative to one accession.
Gouesnard et al. (2001) proposed a maximization strategy consisting in the construction of an algorithm for building germplasm core collection by maximizing allelic or phenotypic richness. The methodology to identify the core size depends on the equation of cumulative inertia for successive accessions; the number corresponds to the peak or inflection point of the curve.
Diwan et al. (1995) compared three methodologies for cores selection implying logarithmic method, proportional method and relative diversity method and defined which one of these methods to use depending on conditions and set of data.
Extensive collection in national and international gene banks has been going on for some time. But, as described above, in Tunisia the variability of apricot landraces was severely threatened. The associated risk of genetic diversity lost induced the initiation of a national core collection policy based on the recollection of the largest genetic diversity in the shortest delays.
For the management of these ex situ plant germplasm, three important goals were set. First, all accessions should be characterized in order to eliminate cases of mislabeling and redundancies and to create a complete data base. Second, to keep a minimum of accessions, this should represent a maximum of variability, constituting a core collection. Third, integrate this germplasm in future breeding programs for new cultivars selection.
As for all fruit trees, an ex situ collection need to be installed for an optimal management and use of the apricot genetic diversity. Such core will be taken in charge by the national gene bank as far as their evaluation and management is concerned.
In this aim we tried to select the Tunisian apricot germplasm core collection using morphological characters and data on molecular markers. Such core collection is needed to safeguard all cultivars and particularly the minor ones, to avoid a loss of genetic diversity and to offer an adequate genetic basis of breeding programs that will use the collection as a reference in Tunisia and at a larger scale.