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Olive tree is an emblematic crop of the Mediterranean region, mainly renowned for its fruit oil, although the species provides several industrial purposes. The Mediterranean basin constitutes the origin of olive species diversification and represents a valuable source of genetic variability of olive germplasm. Therefore, the evaluation of the diversity and the population structure of this Mediterranean germplasm is a challenge for olive species preservation, crop breeding and genetic improvement. In this context, our study aims to analyze the genetic diversity and the population structure of 79 Mediterranean olive accessions using 15 genomic SSRs and by applying computational model-based approaches. The used SSRs revealed a total number of 225 alleles with a mean of 15 alleles per locus. Observed and expected heterozygosity (Ho = 0.79, He = 0.805) with a Polymorphism Information Content value of 0.775 indicate high level of genetic diversity. All results of the Unweighted Pair Group Method with Arithmetic (UPGMA), Jaccard similarity index, Principal Coordinate Analysis (PCoA) and the Bayesian analyses supported the separation of the Mediterranean varieties in two sub-populations, one of which mainly composed by Spanish accessions., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Predicting photosynthetic production in olive trees is a key feature in managing the effect of climate change on arid areas. Functional-structural plant modelling is a promising tool for achieving this goal. We used a photosynthetic sub-model that accounted for water and temperature stress and implemented it into LIGNUM model. We then conducted an experiment to validate the model at the leaf level using olive trees (Olea europaea) grown under various climatic condition. Then, we simulated photosynthetic production of three static olive tree models aged 1, 2, and 3 years. Results revealed a good fit between observed and predicted photosynthesis, with coefficient of determination (R 2 ) values of 0.94 and 0.93 for Chemlali and Zarrazi cultivars, respectively. These results showed that the impact of water stress on photosynthetic production was marginal.

To enhance and highlight the authentication and traceability of table olive oil, we considered the analysis of 11 Tunisian table olive cultivars based on seven SNP molecular markers (SOD, CALC, FAD2.1, FAD2.3, PAL70, ANTHO3, and SAD.1) localized in six different genes. Accordingly, we assessed the potential genotype-phenotypes links between the seven SNPs, on the one hand, and the quantitative and qualitative parameters, on the other. The obtained genotypes were analyzed with computational biology tools based on bivariate analysis, multinomial logistic regression, and the Bayesian networks modeling. Obtained results showed that PAL70 SNP marker was negatively influenced by the phenol rate ( r = -0.886; p < 0.001), the oxidative stability ( r = -0.884; p < 0.001), traducing a direct effect of the PAL70 genotype deviations on the proportion of total phenol for each variety. Additionally, we revealed a significant association of SAD.1 marker with the content of the linolenic unsaturated fatty acids (C18:3; p=0.046 ). Moreover, SAD.1 was positively correlated with the saturated stearic acid C18:0 ( r = 0.644; p = 0.032) based on multinomial logistic regression and Bayesian networks modeling, respectively. This research work provides better understanding and characterization of the quality of Tunisian table olive and supplies a significant knowledge and data information for table olive traceability and breeding.

Background: Virgin olive oil is appreciated for its particular aroma and taste and is recognized worldwide for its nutritional value and health benefits. The olive oil contains a vast range of healthy compounds such as monounsaturated free fatty acids, especially, oleic acid. The SAD.1 polymorphism localized in the Stearoyl-acyl carrier protein desaturase gene (SAD) was genotyped and showed that it is associated with the oleic acid composition of olive oil samples. However, the effect of polymorphisms in fatty acid-related genes on olive oil monounsaturated and saturated fatty acids distribution in the Tunisian olive oil varieties is not understood., Methods: Seventeen Tunisian olive-tree varieties were selected for fatty acid content analysis by gas chromatography. The association of SAD.1 genotypes with the fatty acids composition was studied by statistical and Bayesian modeling analyses., Results: Fatty acid content analysis showed interestingly that some Tunisian virgin olive oil varieties could be classified as a functional food and nutraceuticals due to their particular richness in oleic acid. In fact, the TT-SAD.1 genotype was found to be associated with a higher proportion of mono-unsaturated fatty acids (MUFA), mainly oleic acid (C18:1) (r = - 0.79, p < 0.000) as well as lower proportion of palmitic acid (C16:0) (r = 0.51, p = 0.037), making varieties with this genotype (i.e. Zarrazi and Tounsi) producing more monounsaturated oleic acid (C18: 1) than saturated acid. These varieties could be thus used as nutraceuticals and functional food., Conclusion: The SAD.1 association with the oleic acid composition of olive oil was identified among the studied varieties. This correlation fluctuated between studied varieties, which might elucidate variability in lipidic composition among them and therefore reflecting genetic diversity through differences in gene expression and biochemical pathways. SAD locus would represent an excellent marker for identifying interesting amongst virgin olive oil lipidic composition.

To enhance table olive tree authentication, relationship, and productivity, we consider the analysis of 18 worldwide table olive cultivars (Olea europaea L.) based on morphological, biological, and physicochemical markers analyzed by bioinformatic and biostatistic tools. Accordingly, we assess the relationships between the studied varieties, on the one hand, and the potential productivity-quantitative parameter links on the other hand. The bioinformatic analysis based on the graphical representation of the matrix of Euclidean distances, the principal components analysis, unweighted pair group method with arithmetic mean, and principal coordinate analysis (PCoA) revealed three major clusters which were not correlated with the geographic origin. The statistical analysis based on Kendall's and Spearman correlation coefficients suggests two highly significant associations with both fruit color and pollinization and the productivity character. These results are confirmed by the multiple linear regression prediction models. In fact, based on the coefficient of determination (R 2 ) value, the best model demonstrated the power of the pollinization on the tree productivity (R 2  = 0.846). Moreover, the derived directed acyclic graph showed that only two direct influences are detected: effect of tolerance on fruit and stone symmetry on side and effect of tolerance on stone form and oil content on the other side. This work provides better understanding of the diversity available in worldwide table olive cultivars and supplies an important contribution for olive breeding and authenticity.

The genetic diversity of 22 olive tree cultivars (Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.

Olive (Olea europaea), whose importance is mainly due to nutritional and health features, is one of the most economically significant oil-producing trees in the Mediterranean region. Unfortunately, the increasing market demand towards virgin olive oil could often result in its adulteration with less expensive oils, which is a serious problem for the public and quality control evaluators of virgin olive oil. Therefore, to avoid frauds, olive cultivar identification and virgin olive oil authentication have become a major issue for the producers and consumers of quality control in the olive chain. Presently, genetic traceability using SSR is the cost effective and powerful marker technique that can be employed to resolve such problems. However, to identify an unknown monovarietal virgin olive oil cultivar, a reference system has become necessary. Thus, an Olive Genetic Diversity Database (OGDD) (http://www.bioinfo-cbs.org/ogdd/) is presented in this work. It is a genetic, morphologic and chemical database of worldwide olive tree and oil having a double function. In fact, besides being a reference system generated for the identification of unkown olive or virgin olive oil cultivars based on their microsatellite allele size(s), it provides users additional morphological and chemical information for each identified cultivar. Currently, OGDD is designed to enable users to easily retrieve and visualize biologically important information (SSR markers, and olive tree and oil characteristics of about 200 cultivars worldwide) using a set of efficient query interfaces and analysis tools. It can be accessed through a web service from any modern programming language using a simple hypertext transfer protocol call. The web site is implemented in java, JavaScript, PHP, HTML and Apache with all major browsers supported. Database URL: http://www.bioinfo-cbs.org/ogdd/., (© The Author(s) 2016. Published by Oxford University Press.)

We used eight informative microsatellite markers for fingerprinting and evaluation of genetic similarity among 15 Tunisian olive (Olea europaea L.) cultivars and two feral unknown trees named Soulela 1 and Soulela 2. Thirty-one alleles were revealed, and the number of alleles per SSR varied from 2 (UDO12) to 6 (GAPU71A). Cluster analysis grouped cultivars into three main clusters. The two unknown varieties could not be reliably classified into any of these cultivar groups. SSR analysis indicated the presence of three erroneous denominations of cultivars. We resolved two synonymy cases (Zalmati and Chemlali; Rkhami and Chetoui) and one case of homonymy (Chemlali Tataouine). Genetic analyses of DNA extracted from leaves, oils, and embryos of the two unknown cultivars and the two major Tunisian olive cultivars (Chemlali and Chetoui) were also studied. We conclude that the reliable identification of these two feral cultivars needs to be addressed by a larger set of markers.