The process of recognition and identification of plant species is very time-consuming as it has been mainly carried out by botanists. The focus of computerized living plant's identification is on stable feature's extraction of plants. Leaf-based features are preferred over fruits, also the long period of its existence than fruits. In this preliminary study, we study and propose neural networks and Mutual information for identification of two, three Fig cultivars (Ficus Carica L.) in Syria region. The identification depends on image features of Fig tree leaves. A feature extractor is designed based on Mutual Information computation. The Neural Networks is used with two hidden layers and one output layer with 3 nodes that correspond to varieties (classes) of FIG leaves. The proposal technique is a tester on a database of 84 images leaves with 28 images for each variety (class). The result shows that our technique is promising, where the recognition rates 100%, and 92% for the training and testing respectively for the two cultivars with 100% and 90 for the three cultivars. The preliminary results obtained indicated the technical feasibility of the proposed method, which will be applied for more than 80 varieties existent in Syria

This research was conducted during the period (2018 - 2020) at Hamah Agricultural Research Center in the west central of Syria, in the olive orchard planted with a local variety called “Kaisi”, in order to assess the impact of some organic practices in the productive traits of olive, especially that olive in Syria suffer from a decrease in productivity of unit area due to the lack of services provided to trees, or to repercussion of climate changes in the region. The experimental orchard was divided into four plots: three of them were fertilized as organic treatments coding as follows: (T1: foliar application was applied with certified organic fertilizer its trade name “Amalgerol”, T2: we add fermented manure of free-bred sheep and green manure of vetch and barely plants, T3: in this plot, green manure and organic liquid fertilizer “Amalgerol” were added, whereas the forth plot T4: is a chemical treatment fertilized by NPK. The productive indicators (one year shoot length, No. flowers, fruit set%, productivity kg/tree, fruit weight, pulp%, oil content%) were studied in the field and in the Olive Oil laboratory at General Commission for Scientific Agricultural Research, and a study of costs and profit was also conducted for each experimental plot to find out the most feasible treatment.

This research was conducted during period (2014 – 2016), in collaboration between General Commission of Agricultural Scientific Research/Syria and Food and Agriculture Organization of the United Nations (FAO), in olive orchard that planted of Khodairi variety in Hazour village/Moseif region. The orchard was divided in to two plots, one of them was managed under organic system according to Syrian Organic Law while conventional practices used by farmer were applied in the second. These plots were separated by row of olive trees. Soil properties were studied before and after applying agro practices to evaluate the impact of organic system on soil characteristics, and the chemical analysis (oil percentage, content of Oleic acids, free acidity, total poly phenols) were carried out in order to verify the difference between two treatments, in addition to evaluating diversity in natural vegetation in both experimental plots. Organic agricultural practices have shown a positive effect in increasing soil fertility and the nutrients available to plants. They also exceeded significantly the conventional ones in term of fruit’s oil content the difference was 1.72%, in their contents of oleic fatty acid the difference reached 1.33%, and in polyphenols a difference of 28.7%. The diversity in natural vegetation seemed higher in organic plots, particularly in the spices that belong to leguminous plants such as wild vetch, lupine and types of clover, that allow taking advantage of these spices to enhance the existence of natural enemies, enrich the grove soil and maintain its moisture.