Two field experiments were conducted to study the effect of Arbuscular Mycorrhizal fungi (VAM) and phosphate dissolving bacteria (PDB) application on soil phosphate availability to barley plant grown in calcareous soil. The experiments were carried out at experimental research station-Ras Sudr, Desert Research Center in winter seasons of 2015-2016 and 2016-2017. Biofertilizers treatments were: control, Glomus macrocarpium (VAM) and Bacillus megatherium (PDB) either single or mixed application. Phosphorus fertilizers were applied from two sources, mono super phosphate (MSP) and rock phosphate (RP) at rates of 50, 75 and 100% of the recommended dose. Application of MSP fertilizer significantly increase of grain, straw and biological yield during both growing seasons by 2.7, 2.1 and 2.3%, respectively as compared to rock phosphate fertilizer treatment. Dual inoculation with VAM and PDB increased significantly nitrogen and phosphorus concentrations in the grain and straw. The plant height, grain and straw dry weight per plant, 100 grain weight were increased by 7.5, 8.9, 14.8 and 15.8%, respectively and the grain, straw and biological yield increased significantly by 13.4, 20.6 and 18.1%, respectively compared with the un-inoculated treatments. The highest significant biological yield (5.248 t/ha) was obtained under MSP, 75, VAM+PDB treatments.

Moisture sorption isotherms (MSI) are required to optimize handling, drying, processing and storage of food products. MSI are obtained by solving nonlinear equations iteratively, which is normally a difficult process. A generic approach was successfully used for collective prediction of MSI for 12 cereals and five legumes simultaneously, by taking advantage of the superior computational capabilities of artificial neural networks (ANNs). A total of 779 observations were collected from literature and used in training and validation of ANNs. The ANNs model used product type (grains or legumes), sorption state (adsorption or desorption), temperature and equilibrium moisture content as inputs to predict equilibrium relative humidity. A one-and two-hidden-layer ANNs were implemented. The overall prediction results obtained from ANNs were found to compare well with those reported for conventional analytical MSI models. The average prediction results obtained from the two-hidden-layer ANN for mean square error, deviation modulus and R 2 were 0.009, 4.47% and 0.984, respectively. The results for each product compared well with those obtained from analytical MSI models. Four important issues that are commonly raised when implementing ANNs in prediction of MSIs were explained. These included preventing network over-fitting, minimizing the time and effort needed for ANN architecture optimization, validating reproducibility of the results and validating the network capability to predict new observations. Unlike conventional MSI models, ANNs used the same network to predict MSIs for several products simultaneously. The principle can be easily expanded to predict MSI for other larger sets of various products, which can save time and effort. PRACTICAL APPLICATIONSDetermination of moisture sorption isotherms (MSI) is required for optimization of grain drying, processing, handling and storage operations. They can be also used to evaluate theoretical drying energy requirements and optimum storage conditions for a specific food product. In addition, they are used in food engineering calculations related to equipment design, shelf life evaluation and stability during storage operations. Determination of MSI for food products involves the use of conventional nonlinear MSI models, which requires an iterative solution methodology. The results are also specific to the food product investigated. Artificial neural networks were therefore proposed in this study as an alternative method for the collective prediction of MSI for some cereal grains and legumes.

Air quality deterioration in urban areas; high energy demand and consumption due to regional population growth and economic development; concerns about safe drinking water supplies due to a scarcity of fresh water; air quality deterioration, industrial pollution, waste management, and pollution in coastal areas; and subsequent stress on marine ecosystems are all major environmental challenges being faced by the Kingdom of Saudi Arabia. For effective protection of the environment, an interdisciplinary approach within a sustainable framework, which integrates human needs with economic development and environmental protection, is required. This paper presents an overview of Saudi Arabia's major environmental problems and challenges and offers opportunities to use economic growth, social equity, and protection of the environment as interrelated components. The role of active participation by governments, stakeholders, businesses, academic institutions, and individuals in the decision-making process and an inter-disciplinary research approach will be identified for each major environmental issue.

Identifying the situation of some micronutrients and study the effect of some physical and chemical properties of soils on nutrients status is reveal their importance on agricultural productivity. Clay content, soil pH, salinity, soil organic matter and calcium carbonate content are the main factors which influence nutrients availability in the soil. Some extractable micronutrients contents i.e., Fe, Mn, Zn, Cu as well as B and their relation to some factors are studied in the soils of El-seala area at El-Bahareya region, Egypt. To achieve this target, thirty two representative soil profiles in the study area were investigated. The obtained results are summarized as follows:DTPA extractable amount of Fe, Mn, Zn, Cu and B ranged between1.3-22.9, 2.1-17.9, 0.1-7, 0.1-20.3 and 0.15-7.15 mg kg-1, respectively. Some values of micronutrients are much greater than the marginal levels reported in the literature i.e. about 30.6 % for Fe, 100 % for Mn, 50 % for Zn, 38 % for Cu and 11.2 % for B. In general the soil profiles which have light texture contain low amounts of micronutrients, while on the other hand high amounts of these elements are shown in the heavy texture. About 7.5 % of soil samples have toxic limits of extractable B for soils under investigation. About 20.05 % of soil samples have sufficient limits of available Fe. About 21.85 % of soil samples contain sufficient amounts of available Mn. About 18.45 % of soil samples have adequate of extractable Zn. The critical values of the studied soil profiles reached to 43.75 % for Cu.The statistical analysis i.e., the simple correlation coefficients between DTPAextractable micronutrients and some soil variables are determined.

Faba bean (Cv. Nubaria 1) was grown during the two winter seasons 2011/2012 and 2012/2013 in saline soil at North Sinai Governorate, Egypt, to study of the effect of potassium sulfate (48 % K2O) rates (50-75 and 100 kg K2O fed-1) , urea (46 % N) rates (10-20-40 kg N fed-1) alone or in combination with bio-fertilizers (Bacillus circulans potassium solubilizing bacteria) + Rhizobium radiobacter nitrogen fixing bacteria strain inoculation, Salt Tolerant PGPR and sowing dates (25 October, 25 November and 25 December) on faba bean productivity and the nutrients content in faba bean grains under saline soil conditions was conducted: Results showed that the greatest seeds yield was obtained with the rate of 40 kg N +100 kg K2O fed-1 combined with bio-fertilizer and sown on date in 15 November in both seasons. Also, the rates of N, K and sowing date significantly increased P, K, Fe Mn and Zn content in faba bean seed in both seasons, while grain N content showed no significant differences in the first season. Soil contents of N, K, Mn and Zn were significantly affected by N, K and sowing date while the available P and Fe showed not significant differences in the first season. Sowing date (25 November) recorded the highest values of seeds protein content. It could be recommended that use of 20 kg N + 75 kg K2O fed-1 combined with biofertilizers and sowing date of 25 November gave the greatest seed yield and improved nutrients content in grains under saline soil conditions Keyword: saline soil, faba bean, bio-fertilizers and sowing dates.