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This study aimed to identify and evaluate the genetic diversity of olive trees in Jordan, a country located in the eastern Mediterranean, where olive domestication originated. For this purpose, a total of 386 olive trees were analyzed, including 338 collected from two surveys (JOCC-1 and JOCC-2) across seven regions, and 48 selected accessions from the Olive Germplasm Bank of Jordan (JGBOC). These trees underwent comprehensive phenotypic and molecular characterization using different tools. Significant differences inmorphological traits were detected among tested regions using the Chi-square test. Principal components analysis revealed that fruit color change and growth habit as the most discriminating traits, segregating the trees into two groups, with the first group including the KANABISI cultivar and the second group including the KFARI BALADI cultivar. Utilizing Kompetitive Allele Specific PCR assay, two sets of informative SNPs were used for the genetic diversity analysis. Cladograms were constructed using the maximum likelihood method, revealing a consistent pattern where two clades containing identical genotypes were observed to cluster with the KFARI BALADI or KANABISI. In addition, the SNP data was used to perform a comparative analysis with the Worldwide Olive Germplasm Bank of Co'rdoba, which revealed 73 unreported olive genotypes from Jordan. Genetic structure analyses using Discriminant Analysis of Principal Components (DAPC) identified four clusters with distinctive patterns of relatedness among 149 unique accessions, including 52 olive accessions from various Mediterranean countries (IOCC-3). ADMIXTURE analysis revealed four genetic clusters, consistentwith the clustering observed inDAPC and cladogram analysis, indicating a high level of genetic admixture among Jordanian olive germplasm. In conclusion, the results show that olive trees in Jordan are highly diverse, providing valuable information for future conservation and management plans. [ABSTRACT FROM AUTHOR]

This work introduces a smart robotic arm for harvesting olive fruits. The work started by planning the main steps. After deciding on the robot concept design, a kinematic and dynamic analysis is conducted. Based on the results of the analysis, a simulation is performed to determine the required specifications of the main components. Based on these results, an experimental model of the robot arm is designed, built, configured, and tested, where the model yielded good results. The next step is to configure and test different types of end effectors. In order to make the harvesting process effective for olive trees, picking a single fruit each time is not practical. Therefore, the procedure adopted in this work focuses on picking a group of fruit in each stroke. The harvesting system consists of a robotic arm guided by a stereovision camera to enable 3-D vision. Once the fruits location is detected, a reverse kinematics algorithm is initiated, yielding 3-points coordinates. These coordinates are commanded to the manipulator to move to the location and performs the picking process. Further developments will include building a larger manipulator that can reach out to all parts of a regular tree.